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Culture as an Issue in Knowledge Sharing: A Means of Competitive Advantage Martin Soley and Kaushik V. Pandya* University of Luton, UK [email protected] [email protected] * Author for Correspondence Abstract: In order for companies to remain competitive they must be able to utilise their knowledge of customers,

products, services and resources. This can be instilled in the culture of the organisation, and this becomes paramount when the organisation deals in international markets. This research paper focuses on five main attributes, most pertinent to this study, of culture (identified by Terpstra and Sarathy, and by Gesteland). These attributes are technology and material culture, religion, language, education, and business ethics. The primary data comprised of interviews from six different e-Businesses. Keywords: culture, knowledge sharing, technology, e-business,

1. Introduction A major source of cultural globalisation today is business activities. As businesses find new markets for products, they transmit cultural messages of how people should talk, dress, think and feel (Chee & Harris 1998). Many international scholars have argued that we are living in a ‘borderless world’ where customer’s needs are converging. Many businesses are trying to produce a standardized product or service that can serve all global needs. As images like these and business activities go global, they increasingly have an effect on traditional cultural habits and beliefs of different nations. However, businesses are realising that local adaptation is needed due to local culture. This paper identifies whether culture really does effect UK business operations in B2B and B2C markets, analysing how UK businesses have overcome cultural barriers, what methods they have used to overcome these barriers. Also, can technology overcome cultural barriers in international markets? If technology does prove to overcome cultural barriers, then theoretically UK businesses should not encounter cultural barriers. These five main attributes/elements/traits of culture are derived partly from that proposed by Terpstra and Sarathy (1972) and Gesteland (1999). These attributes are: technology and material culture, language, education, religion and business ethics. The primary data collected in the study consists of interview with six different organisations. The study also explores whether technology can overcome cultural barriers. The new data also considers whether the systems and policies of UK businesses currently is utilised in order to overcome cultural barriers. This is not a definitive collection of solutions for UK businesses to adopt, but provides new insights

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into how UK businesses can overcome some of the cultural barriers in international markets. The lack of in-depth research into international culture issues for e-Business prompted the authors to carry out this study.

2. Objectives of the research The objectives of these research investigations were: To evaluate whether culture really does effect UK business operations in international markets. To examine and analyse the provisions businesses utilise to overcome the cultural problems of today’s international marketing, if they exist. Identify the main cultural problems associated with UK business operations in international markets, suggesting solutions based on primary research. To investigate whether technology can overcome cultural problems in international markets. The research identified and examined a number of knowledge related issues associated with culture and the UK e-Business industry. This study examines the work of academics in relation to culture and the impact it has on E-Business. Subsequently, the authors examined how these businesses have overcome problems in today’s market. This assisted in highlighting potential problems and formulation of recommendations.

2.1

General hypothesis

Certain cultural attributes could impede UK organisations carrying out business in international markets. This could be due to a lack of knowledge sharing between the home and the host country partners, or a lack of preparation and expertise on the part of the UK

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business. The most prominent of these was studied in relation to their effect on the UK organisations. The cultural traits were investigated; some attributes have a major influence, whilst others do not have any effect at all. This research identifies and analyses the main cultural variables that UK businesses should have knowledge (either as explicit or implicit) of and share this knowledge. A general hypothesis was offered: “Certain cultural traits could effect UK Business operations in international markets to the extent that if not taken seriously could result in misunderstandings that may result in lost time and money, or further still result in the disbandment of the international relationship.”

2.2

Methodology

To undertake an empirical study into the effects of culture on international markets interviews were considered to be necessary to gather fresh insight as to how UK eBusinesses overcome cultural barriers. The dynamic nature of e-Business and culture means that much of secondary data is out of date, which arguably would lead to an inaccurate analysis, in addition to not answering the issues raised in the objectives. The other important element of the primary source was to identify whether industry professionals agree or disagree with various academics from the literature review.

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Secondly, does the use of technology overcome cultural barriers? To spare the unnecessary details, the details of the questions and the response from the interviews are not shown. The study was carried out using the results from interview with six UK e-Businesses. They were: 1. A supply chain optimisation company 2. A world's leading management consulting and technology services company working within every industry worldwide 3. A consultancy working with clients to make the most of their investments in technology 4. A global technology services company with employees in 100 countries 5. An information systems company providing a range of consultancy, systems integration and support services to many business sectors including transportation, energy, industry and finance. 6. A software developer that analyses the performance and scalability of IT systems.

3. What is culture?

In order to carry out research of this nature, it was necessary to collect a sample of the UK businesses by choosing carefully a selected number of businesses that had expertise in the field of e-Business and international marketing. The reasoning behind the choice of eBusinesses as an area of focus was because they possess a wealth of experience and expertise in this field, which in-turn can provide much needed knowledge for businesses and SME attempting to enter international working relations.

The word ‘culture’ stems from the Latin “colere”, translated as to build on, to cultivate, to foster. Leibnitz, Voltaire, Hegel, von Humbold, Kant, Freud, Adorno, Marcuse, all have reflected on the meaning of the word in different versions of its use. Since then various schools of thought concerning the term culture have been encountered. For instance, during the 19th century the concept of mass culture and popular culture emerged. During this time, theories emerged epitomizing culture as values shared amongst distinctive social groups and classes. Another view of culture identifies culture as a set of values and attributes of a given group, and the relation of the individual to the culture, and the individual’s acquisition of those values and attributes. Hofstede (1991) refers to this as the “collective programming of the mind.”

All interviews were with senior managers and conducted over the telephone due to geographical distances. Anonymity was granted to participants to keep their identity unknown. The detailed questions asked in the interviews were designed to query the importance of international culture on the eBusiness industry and thus exploiting knowledge sharing. Two enquires were of particular interest. Firstly, does knowledge of culture affect the way UK organisations carry out business with international partners?

Indeed culture is not an easy phenomenon to quantify, having seen no less than one hundred definitions, with definition such as culture a “shared system of perceptions and values, or a group who share a certain system of perceptions and values.” The authors of this study would add to this; “sub-groups, shared beliefs and basic assumptions deriving from a group”. The authors acknowledge that this definition is not exhaustive. This is because culture as a collectively held set of attributes is constantly evolving and dynamic in nature.

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Kahal (1994) stated, “In international business dealings, ignorance of cultural differences is not just unfortunate, it is bad business.” This lead to ask: How much knowledge has one regarding culture? However many organisations fail to acknowledge this. Culture has always provided problems for many organisations and it is generally a lack of understanding and knowledge sharing regarding the culture that has brought culture under the spotlight. This paper aims to simplify the complexity of culture by identifying and examining a number of cultural traits/attributes that are pertinent to the UK organisations. When examining culture many researchers have initiated cultural issues, where attributes such as language, material culture and religion can be further analysed and discussed. The authors of this research paper have proposed a basis for a cultural framework and identified attributes having effect on the organisations, important mainly to the e-Business industry.

3.1

Issue of communication

Communication is an important concept in this study as it entails the sharing and transfer of knowledge among and of cultures, examining and identifying the major traits. It is considered that any organisation’s knowledge repository should include the knowledge of the culture of their trading partners or end consumer. The authors have identified and analysed various schools of thought derived from academics. Schramm (1955) defines communication at its simplest level as “the process of establishing a commonness or oneness of thought between a sender and receiver.” Managers at all levels generally need to be able to communicate successfully. Increasingly they must communicate in a new world of diverse colleagues, clients and customers of international operations. Indeed the way one communicates today is in contrast to even five years ago. Communication, via Internet, can enable people, separated by thousands of miles, to know of the activities of others whom they do not personally know, and show potentially common elements in the ways different geographically separated people conduct their lives. Culture and communication are necessary simultaneously – they go handin-hand. This also highlights the decisions UK businesses face, whether to standardize products or services even though products or

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services may be culturally bound and lose potential clients, or adapt to local cultural conditions. The latter decision will provide additional costs. A key question therefore is whether the cost of adaptation is exceeded by higher margins. In high-context cultures people rely heavily on the overall situation to interpret messages and so the messages, which are explicitly spoken, can be elliptical. In low-context cultures people rely more on explicit verbal content of messages. Conflicts could arise between high and low context cultures. Many examples of these two contexts have been seen. This may prove difficult for UK e-Businesses that attempt to sell a business proposition by e-mail to a high-context culture. There are two theories the convergence and divergence of cross-cultural communication. The convergent theory argues that increased cultural uniformity occurs through increased communication between home and host country. Here cross-cultural communication is defined as a process of creating, maintaining, or bridging racial, ethnic, or national boundaries. The emphasis is on sharing knowledge, leading to mutual understanding, mutual agreement, and collective action. The divergence school of thinking (Chee and Harris, Browning 1998) argue that as communication across cultures increases, there may be greater recognition of cultural differences. Munter (1993) argues, “We need to remember that other cultures do not necessarily share our behaviours, verbal and non-verbal, claiming that cultures differ from one another because there is less contact between cultures than within them. If everybody communicated with people outside their culture as much as they with people within it, cultures would soon disappear. Chee and Harris (1998) argue that few countries are dominated by a culture that goes unchallenged. Thus, Intra-cultural differences have to be understood as well as cross cultural communication. 3.1.1 Online technology Online communication technology allows individuals from different cultural backgrounds to communicate with each other directly and quickly. However, such technology, in its removal of more traditional communication obstacles such as time and distance, may increase other cultural differences. ComputerMediated Communication (CMC) is the process by which people create, exchange,

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and perceive information using networked telecommunication systems (or non-networked computers) that facilitate encoding, transmitting, and decoding messages (December, 2002). The way people from different nations interpret a message across CMC or the approach in which they use CMC in a business relationship can vary from country to country depending on the culture. From analysing the literature, it is considered that communication should be an integral part of this study. UK e-Business must act with caution when communicating across national borders.

3.2

Culture’s place in international markets

What is the role of culture in international markets? This role is partly because it helps to explain why different groups of people perceive things on their own way and perform things differently from other groups. Some authors argue that knowledge of a culture can help reduce complexity and uncertainty in decision-making, while others argue that the issue of culture and the need for better understanding have become major parts of organisational behaviour. Academics have debated the importance of understanding the culture values of foreign associates. This makes it increasingly important for businesses to understand the value of other cultures, as well as their own. However, Usunier (1996) argues that not everything is culture based. Referring to the work of authors who typically stereotype individual nations by behaviours, Usunier (1996) believes that we have a rather stereotyped perception of such behaviours, which only provides a superficial incomplete picture of the cultural group. Some authors have argued that all societies are culturally unique, and pose a unique set of marketing problems that keep changing over time. Others have contradicted this by saying that as countries industrialise, basic human needs and behaviours become similar. Hofstede (1984) and Trompenaars (1993) suggested that human behaviours could be affected by cultural variants. Hofstede argued that culture is collective programming, which affects behaviour. Hofstede’s work represents an attempt to understand work related differences between countries and to account for these by reference to preferred management styles. Trompenaars also attempted to make a direct link between

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cultural variance and workplace behaviour. Both Hofstede’s and Trompenaars’ work identifies a linkage between national culture and workplace behaviour. Deresky (1994) provides some assistance for managing and contrasting cultural variables across national borders. Deresky terms the skill for managing people and processes in other countries as ‘cultural savvy’, that is, a working knowledge of the cultural variables, affecting management decisions. She also proposes that global managers should develop a cultural profile for each country/region with which one does or is considering doing business. Managers should be careful not to generalise in compiling cultural profiles. Keegan and Schlegelmilch (1999) argue the reason why there are so many international marketing blunders is because many global managers suffer from cultural myopia. They argue that becoming a global manager means learning how to let go of cultural assumptions. Failure to do so will hinder accurate understandings of the meanings, significance of the statements and behaviours of business associates from a different culture. The ability to see the exact dimensions within a culture can eliminate ethnocentrism from the global marketer’s perspective. The concept of ethnocentrism can often be interpreted as a form of nationalism. Comments such as “they all speak English anyway,” can be an unnecessary attitude towards the host nation. In this study the authors adopted the definition of culture identified by Terpstra & Sarathy (1972) with key five attributes of culture: Technology and material culture, language, education and religion. Gesteland (1999) added ethics as an attribute of culture. All these attributes together were analysed in relation to their effects on businesses, and as an issue in Knowledge sharing. 3.2.1 Technology and Material Culture Material culture is divided into two closely related subjects, technology and economics. The people of society possess technology, including the technical knowledge. Terpstra and Sarathy (1972) argue that a host country’s technological infrastructure can hinder international business. Africa has 12% of the world’s population, but just 2% of the world’s main telephone lines (Internet World, Nov 1995). There is a lack of technical knowledge in Africa. This spread of the Internet among nations has been unequal mainly depending

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on each country’s economic and social development level (http://www.nua.com/surveys/how_many_onlin e/index.htm). The main problems for developing countries is that many businesses can not afford to get wired, while country as a whole was suffering from, among other such things; HIV/AIDS, famine, governmental instability, from inefficient phone systems. Many academics label this the ‘digital divide.’ The two major cultural stumbling blocks are the lack of IT infrastructure and the insufficient technical knowledge in the host nation. 3.2.2 Language The primary Internet Language is English. Terpstra and Sarathy (1972) argue that language is the most obvious difference between cultures. Inextricably linked with all other aspects of culture, language reflects the nature and value of culture. For example the English language has a rich vocabulary for commercial activity within the e-Business sector, reflecting the nature of the English and U.S. Societies. Many societies have only limited vocabularies for e-Business activities but richer vocabularies for matters important to their culture. Businesses need to recognise that language is such an obvious cultural difference that must be dealt with. Indeed in most cases, international partners can speak English, but it is wrong to assume that they are willing to speak English. The knowledge of a host partner in dealing with particular cultural problems such as language provides a solution. 3.2.3 Education Terpstra and Sarathy (1972) define education as “the process of transmitting skills, ideas and attitudes, as well as training in particular disciplines”. Literacy rates are used to describe the educational achievement in the host nation. The level of education in the host country is a concern, especially in emerging markets where technical and basic educational levels are predominately low. There are real disparities in access and use of information and communications technologies (ICT) existing between countries. UK e-Businesses may encounter low levels of technical education as a cultural barrier in these countries. Education is a concern for many UK eBusinesses, especially when considering business opportunities in emerging markets. This partly because it is a key determinant of the kinds of business associates available.

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3.2.4 Religion Terpstra and Sarathy (1972) argue that religion is concerned with the human involvement of business, arguing that if one is to get a full understanding of culture, one must gain familiarity with the implicit or mental behaviour that gives rise to the external manifestations. Generally it is the religion of a culture that provides the best insights into this behaviour. The very nature of religion unites people over continents as well as causing hostilities and war. Although the international business is primarily interested in knowing how people behave as consumers or workers, managements will be aided by understanding why people behave the way they do. The main three religions of the world are; Christianity, Islam and Hinduism. Religion can have a major impact on attitudes towards economic matters. For example, Religious holidays vary greatly among countries, not only from Christian to Muslim, but also from one Christian country to another (Daniels and Radebaugh, 2000). The economic role of women also varies, and religious beliefs are an important cause. For example, in some religions women may be restricted in their capacity as workers. This will have some bearing on the way UK organisations approach business in these countries (Terpstra and Sarathy, 1972). Also, in many developing countries women are also largely excluded from formal education, reflecting in how different cultures are receptive towards business practices. 3.2.5 Business Ethics The word ethics in the term business ethics derives from the Greek word ethos meaning “character or custom”. From culture to culture, customs and behaviours differ. This has a detrimental affect on the various meaning of the term ‘ethics’ across cultures. For instance offering a gift to an international partner is totally acceptable in some nations, whilst in other nations this behaviour will be interpreted as a form of bribe. A motive for bribery could be to secure government contracts that otherwise might not be forthcoming at all or to obtain them at the expense of competitors. Another motive could be to facilitate governmental services that companies receive which officials otherwise might delay, such as import clearances and product or service registrations (Daniels and Radebaugh 2000). This paper discusses bribery and corruption as part of the cultural differences between nations regarding the term ‘business ethics’.

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The Transparency Corruption Perception Index (2002) highlights nations in the world with high levels of bribery and corruption. This index also highlights the government sector as the most corrupt business sector. Anti-bribery legislation in the UK has been enforced since 1999, based on the 1997 OECD convention on bribery. However big multi-nationals continue to ignore such laws without receiving large fines as a deterrent. UK e-Businesses should be cautious of bribery, particularly in emerging markets, where certain government officials may expect a bribe.

3.3

Summary

In summary, business should identify these cultural differences that may occur and analyse how they may interfere in international business. There are two main schools of thought dominating international marketing literature; the convergence and divergence. From the discussions above, adapting business etiquette to a particular culture would be the best course of action for UK eBusinesses.

4. Specific hypothesis From the evidence collected in the literature review, a specific hypothesis has been offered. “Culture does have an adverse effect on UK business operations in international markets, where certain cultural attributes if not taken seriously will result in misunderstandings across cultures. This will result in lost time, money and in some cases the disbandment of the international relationship.” To test the hypothesis a collection of both academic research and commercial sector information was needed. The authors have used the attributes discussed above. These attributes assisted in the formulation of questions in the interview, exploring them in greater depth.

4.1

Discussion and findings

The study covers three major themes; the first investigates the impacts culture has on UK organisations operations in international markets. This theme particularly explored the cultural attributes identified in relation to EBusiness. The majority of the respondents claimed that culture has a major influence on E-Business operations in International markets. Many respondents identified language as a major problem above all other attributes.

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The second theme investigated the systems and policies organisations utilise to overcome cultural barriers. Many of the respondents claimed that adaptation was needed in order to overcome cultural problems. The use of a host nation partner is also useful to acquire and share knowledge of the local culture and thus localise many of the services. The final theme investigated whether technology can overcome cultural barriers in international markets. The majority of respondents claimed technology could assist in negating some aspects of culture. However, culture is a human issue. Thus overall technology cannot overcome all cultural issues in international markets.

4.2

Testing hypothesis

From the information gathered on the cultural attributes, there has been some real evidence to justify this hypothesis. Technology and material culture was an attribute that needed consideration by UK businesses. There are significant differences between developed and emerging markets regarding the level of IT infrastructure capabilities. Language proved to be an important factor to take into consideration for UK E-Businesses. Many businesses lack the language skills. However because many foreign associates can speak English, language differences across cultures can be overcome. Some UK e-Businesses assume that foreign counterparts want to speak English in business dealings. This maybe construed as a cultural imperialism. Many parts of the world have both low technical and formal educational levels compared to the UK. The difference across nations this can hinder UK e-Businesses operating in countries where technical competence and the overall formal education levels are also low. Religion also affected the role of women across cultures and the working calendar week. The UK, which is predominately a Christian country, will encounter different religious beliefs in say a predominately Muslim country. This is different to the UK culture, where the workforce is a even split between male and female Also, the working calendar week varies across cultures. Business ethics also differ across cultures. Sources of bribery and corruption are highly concentrated in third world markets. UK e-

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Businesses should be prepared to foresee any problems that may exist in the host nation. Both the literature review and the data collected proved that culture does effect UK business operations in international markets. Thus acquiring and sharing knowledge of the culture of the business partners and end consumers is vital. The possibility of technology overcoming cultural barriers was also questioned as this would contribute to the argument that if technology can overcome cultural barriers then international cultural barriers would not exist in markets today or in the future.

2.

3.

5. Conclusions The authors believe that the information collected in this study helps to explore the cultural attributes further. The five main attributes discussed do have an adverse effect on the way UK e-Businesses operate in international markets. This research does not offer definitive solutions, however it highlighted issues that UK e-Businesses could foresee and adopt if they encounter a similar cultural barrier. This enabled the authors to conclude that the specific hypothesis was in a way proven. The majority of the interviewees agreed that technology cannot overcome all cultural barriers, but can reduce some cultural nuances. UK e-Businesses should be aware that technology could facilitate in the sharing of knowledge, which means it is much easier than ever to gather information on different cultures. These factors will assist the UK e-Businesses in establishing a long-term successful international relationship. A UK e-Business that adopts an ethnocentric attitude to the host nation will suffer in lost time and money, leading in some cases to the disbandment of the international relationship.

5.1

Recommendations

The authors would like to point out that this research paper is not a definitive study into the subject matter. The subject matter is too complex to be covered in one research, however much can be learnt from the study. Other authors have already identified culture as essential part of KM. Thus it is considered that recommendations identified below are fundamental when considering knowledge sharing in international markets. The following recommendations derive from this study: 1. The major rule of thumb for all UK eBusinesses considering expanding

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4.

5.

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internationally is preparation, flexibility, a positive attitude, a desire to learn about different cultures and patience to build long-term relationships. UK e-Businesses expanding into third world and emerging markets should be aware that technological infrastructure in many third world markets is inferior to the UK infrastructure. This will require UK eBusinesses to put their own mobile IT infrastructure in place. This can be expensive. The key question is whether the cost of adaptation is exceeded by higher profit margins. Many European and developed nations can speak English competently, however the lack of linguistic skills in the UK reduces flexibility in international markets. Collaborating with international partners in the host nation can provide expertise regarding the culture and language, and localising services or use of translators can also negate language barriers. The educational levels in third world nations are below par with the UK. UK eBusinesses could transfer key personnel over to these parts of the world in order to share knowledge. This can bridge the gap between the UK and many third world nations. The key question for many UK eBusinesses is whether the cost of sending key personnel out to these countries outweighs any possible benefits from the partnership. Religion can affect the economic role of women from culture to culture and religious holidays also vary greatly among countries. UK e-Businesses should be sensitive to the different religions across cultures and work within a local religious context. UK e-Businesses should also be aware of corruption and bribery, especially in third world and emerging markets. UK eBusiness should be particularly careful when dealing with government officials in these markets. UK e-Businesses should prepare and build a profile of the present political climate to ascertain the chances of encountering corruption and bribery. If UK e-Businesses should encounter sources of bribery and corruption the best policy is to walk away and return to the market when the political climate changes favourably. For further professional advice you can contact organisations such as the British Council and Confederation of British Industry (CBI).

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7. If the UK e-Business conducts the majority of business internationally, it may be worthwhile employing a specialist to deal with cultural issues in international markets. This specialist can negate some of the cultural barriers mentioned; speed up contract negotiations and market entry, thus providing the business with a competitive advantage. Some of the recommendations are also applicable to business (not just E-Business) operating in international markets. Many researchers would say not having a quantitative analysis does not prove the hypotheses above. However it is considered by the authors that the qualitative research undertaken here forms a basis on which further work can be undertaken. This paper is of interest to researchers, academics and practitioners of E-Business and KM systems.

References Chee, H. and Harris, R. (1998) Global Marketing Strategy, McGraw-Hill, London December, J. (2002) “Units of Analysis for Internet Communication”, Journal of Computer Mediated Communication, Volume 6, No 3, pp 67-72. Deresky, H. (1994) International Management Managing Across Borders and Culture, New York, Wiley and Sons. Gesteland, R. (1999) Cross-Cultural Business Behaviour Marketing, Negotiating and

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Managing Across Cultures. Handelshojskolens , Copenhagen. Hofstede, G. (1991) Culture and Organisations Intercultural Cooperation and Its Importance for survival- Software of the Mind. McGraw-Hill, London. Kahal, S. (1994) Introduction to International Business. McGraw-Hill, London. Keegan, J. and Schlegelmilch, A. (1999) Global Marketing Management, Prentice Hall, New Jersey. International, Transparency. (2002) “International Corruption: A Survey of Business Perceptions”, http://www.transparency.org, [Accessed 02/04/03] International, Transparency. (2002) Bribery in Different Business Sectors, http://www.transparency.org, [Accessed 02/04/03] Munter, M. (June 1993) “Cross-Cultural Communication for Managers”, Business Horizons, Volume 1, pp 69-77. (S:N) (September 2002) “The Number of Internet Users by Region in the World”, http://www.nua.com/surveyshow_many_online-index.html, [Accessed 23/03/03] Terpstra, V. and Sarathy, R. (2000) International Marketing, Dryden Press, Fortworth. Usunier, C J. (1998) International & CrossCultural Management Research, Sage Publications, California.

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Achieving Closure Through Knowledge Management Strategy Duncan Shaw, John S. Edwards, Brad Baker and Paul M. Collier Aston Business School, Birmingham, England. [email protected] Abstract: Case studies of knowledge management practices are often conducted in organizations where the aim is to manage knowledge for future operational improvements. What about knowledge management for organizations with limited life-spans that are preparing for closure? Such organizations are not common but can benefit from knowledge management strategy. This case study concerns the knowledge management strategy of an organization that is preparing for its final phase of operations. We facilitated two group workshops with senior managers to scope a strategy, following which the organization initiated a set of projects to implement the resulting actions. This paper reviews their implemented actions against those designed in the workshop to shed light on knowledge management in this uncommon situation. Keywords: strategy; knowledge management; limited life-span; implementation; evaluating group workshops.

1. Introduction The focus of a knowledge manager’s role is often to improve performance through enhancing business processes, believing that even if immediate measurable paybacks are few, performance improvements will reap benefits over the long-term. Research in knowledge management has concentrated, with few (if any) exceptions, on organizations with a future; assuming that changes today will over time feed through to performance improvements. There is almost no empirical research which informs our response to a client/collaborator who asks “Our organization is closing – what should we do about knowledge management?” Such a client has a great need for knowledge management. However, the literature is very limited indeed, perhaps because the opportunity to research an organization with a limited life-span is extremely rare. There has been a stream of research on joint ventures, some of which do indeed have a limited lifespan, but we are not aware of any work specifically looking at the knowledge management implications for such organisations. This paper reports initial results from an ongoing research study with an organization that has a limited lifespan, which for reasons of confidentiality will be called ConsumProt. ConsumProt is a consumer protection organization. We facilitated two group workshops, several months apart, including senior managers of both operational and support departments. In the first workshop the managers explored knowledge management and developed a preliminary action plan for improving knowledge management practices. The second workshop focused more in-depth on four of the issues to be tackled – issues which the managers agreed were the most

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crucial and realistic priority areas given the constraints imposed by time pressures, budget and the need for rapid results before closure. The output from these workshops was a programme of actions that had the agreement and commitment of managers from both departments. The paper first briefly explores the knowledge management issues associated with an organization having a limited life-span. The organization and the workshops are then described in more detail. Next the nature of the actions agreed in the workshops is outlined, leading to a more detailed discussion on what the organization is actually doing to improve knowledge management practices in preparation for the final phase of their operations before closure. The paper concludes by identifying potentially transferable lessons, noting that even in continuing organizations, helping people to develop their skills and secure future employment has a wide applicability.

2. Knowledge management with a difference In the extensive literature on knowledge management, the future life of the organization is rarely explicitly considered. Well-known texts (Nonaka and Takeuchi, 1995; Davenport and Prusak, 1998) typically imply an unlimited future for the organization. If one looks hard, it is however acknowledged that an everexpanding future is not the only possibility, and that there can be some negatives relevant to the context of knowledge management. These include the need to archive knowledge in case key staff leave (Mullin, 1996; Probst et al., 1999); and losing knowledge through downsizing (Bair, 1997; Probst et al., 1999). These are examples of the more general term “knowledge erosion”, used by Hendriks and Vriens (1999) and coined originally by Lucardie

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and Arts (1990). This refers to the loss of knowledge resulting from people leaving an organisation or changing jobs within it. Whether organizations can have a “memory” that goes beyond that of the people in it, or a knowledge archive or repository, remains a moot point (Walsh and Ungson, 1991). A particular problem for an organization facing closure is that knowledge workers are said to require better than average working conditions (Drucker, 1992; Probst et al., 1999). An organization with limited life-span runs an especial risk that its most valuable staff will leave first. All the aspects above would apply to any organization facing closure. Additional factors relevant to the particular organization described here were the need to preserve knowledge (in some form) for the replacement organization and to continue to carry out the same amount of work with fewer staff. These are, however, different forms of very common knowledge management problems of knowledge retention and more effective knowledge use to promote greater efficiency.

workload, and a culture of ‘us and them’ between A and B. Our involvement with this organization began as part of a project to find out what managers in UK organizations thought about the present and future state of knowledge management in their organization. More details of that project may be found in Edwards et al (2002) and Edwards et al (2003b). The methodology used was based on facilitated, computer-supported group workshops, the specific approach being called Journey Making (Eden and Ackermann, 1998). Space does not permit a detailed explanation here. More information on the approach, in the context of this particular knowledge management project, may be found elsewhere (Edwards et al., 2003b; Edwards et al., 2002; Edwards et al., 2003a), and a more general discussion can be found in Shaw (2003) and Eden and Ackermann (1998). We now look at each of the two workshops in detail.

3.1

3. Introduction to the organization and the workshops ConsumProt is a non-statutory regulatory organisation charged with consumer protection and raising standards in its industry. When it was set up in 1997, the possibility that an official government body would in time replace it was acknowledged, and it has only recently been confirmed that this will happen towards the end of 2004. ConsumProt’s goal for knowledge management was to identify and evaluate a knowledge management strategy that would initiate or improve processes and tasks in order to continue effective operations for a defined period and close the operation of the organization more effectively. For obvious reasons ConsumProt would only consider actions which could be implemented quickly within existing resource constraints, with immediate/rapid payback. ConsumProt is split into two operational departments – A and B, with a range of other supporting departments (including department C as mentioned later). Tensions in the organization were high, both across and within A and B. Taking their toll on the employees were the combining pressures of a declining workforce who were not being replaced, the prospect of unemployment, uncertainty over when unemployment might happen, a healthy

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The first workshop

The first workshop was a scoping exercise. The aims of the workshop were (1) to understand what knowledge ConsumProt needs to harness to improve its business; (2) to develop effective processes to harness knowledge; and (3) to consider how these processes should be evaluated. During this workshop the group explored the enormity of their task in terms of: the knowledge which informs their business and which had to be managed; where effort needed to be placed to improve existing processes and initiate new processes; how they could evaluate progress on knowledge management; and over what time scale results might be seen. The group identified a range of actions that might improve their knowledge management activities. These covered 17 different areas of the business, including: operational efficiency; external and internal communications (written and verbal); external acquisition of knowledge; archiving knowledge; external views of ConsumProt’s effectiveness; codifying knowledge; key performance indicators. These 17 areas were then further structured into 6 core concerns for the future: accepting and managing change, archive knowledge, communication, process efficiency, review

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priorities, and staff issues. {Note that throughout the paper we use exactly the phrases used in the workshops, even where it leads to inconsistency in the parts of speech, as here.} Instead of attempting to address all 6 core concerns within existing resources and time constraints, the group decided to concentrate on one topic for the rest of the workshop, and follow a similar methodology for the other core concerns when they returned to their workplace. The topic they concentrated on was staff retention. As well as being central to the “staff issues” core concern, this also impacted on several of the others. Given that some employees’ contracts would finish before the organization closed, it was critical to try to retain the remaining staff to allow a planned run-down. Three elements central to staff retention were identified, and discussed in as much detail as time permitted: Monitoring staff attitudes – to attend to satisfaction and motivation. Expanding remits and refocusing expertise – contingency planning through mentoring and work shadowing. Training and professional development – to make staff more appealing to the market when searching for future employment.

3.2

The second workshop

Three months later a second workshop took place. The aims of this workshop were “to explore how we can improve the sharing of information within the organization; and to develop an action plan of 3-4 achievable ‘next steps’ that can be completed within 6 months”. Early in the workshop it was decided to concentrate on four topics for improvement. These were staff development (including training and professional development from the previous workshop); team building (including staff attitudes); communication of roles and functions (including expanding remits and refocusing expertise); formal continuous process improvement. As may be seen, three of these originated from the focus on staff retention in the first workshop, while the fourth explicitly centred on one of the other core concerns, improving process efficiency. Taking one of these areas as an example – staff development – the group designed three programmes of actions that, they felt, would make significant progress in this area. The

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programmes of actions are displayed in the map in Appendix 1 and were: Encourage the development of transferable skills within the organization – so that skills of people who leave are not lost (contingency planning). Actions included: prioritise the skills that need to be transferred; rotate jobs within the same department, job swaps, buddying; document key procedures; build a skills database. Making better and consistent use of existing software – to enable freer information exchange. Actions included: assess email workloads across the organization; managing software better enabling all tasks to be located in same software; identify training needs. Develop a training strategy – to retain staff and prepare them to move on. Actions included: develop training plans; provide career counselling; get staff to take advantages of opportunities; offer rewards and recognition. For each programme of actions the group assigned 2 or 3 managers who would take responsibility for further design and implementation of the actions, and for reporting progress to the group (the names shown in the map are disguised). Programmes of actions (and maps) at a similar level of granularity were developed for each of the other three areas for improvement. Rather than commenting more fully on each of these areas, we prefer to use the limited space here to review what the organization has actually done. This will form the core of the next section.

4. What the organization is doing on knowledge management The second workshop was a catalyst for setting up the ‘Aston Group’ project, which is the name of both the initiative and the team leading the change programme. Six months after the workshop the project was described by the organization’s internal staff newsletter as “an internal initiative with the aim of improving the way information and knowledge is shared and used within ConsumProt … the [senior] management team fully support these initiatives.” The newsletter described seven components of the initiative, so-called ‘projects’. We will review these projects and the approach taken to address them – to identify what the

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organization is actually doing on knowledge management in its limited lifespan. This will lead to a comparison between what they are doing and what they had agreed to do in the workshop – to explore the use of the workshops in determining this direction. The 7 project areas of activity, each led by at least two ‘project managers’, are: Project 1: Contingency Planning – ensuring knowledge and skills of people leaving the organisation are not lost This project involves encouraging management to find ways of preventing skill shortages if and when employees leave the organization. Initially a very analytical approach was designed: planning to identify the key functions to be maintained during the remaining life of the company and to produce a matrix of skills necessary to carry out those tasks. Then as a separate exercise, a schedule of existing staff and their skills was to be generated and mapped against the tasks matrix, thereby identifying areas lacking contingency (Coombs and Hull, 1998). Following consultation with department heads, a more pragmatic approach was adopted to dovetail with the strategies set by individual departments to manage workload in the remaining period. Since then: Department A has launched a succession planning initiative. Employees are being trained to assume roles other than their core job function and the artificial boundaries between some functions have been removed. Department B has identified a number of labour-intensive tasks which can be redesigned to lower effort and time. This includes redesigning the client audit process, and lowering the emphasis on visits to clients’ premises. The staff currently on these tasks will be redeployed within the organization to create skills contingencies. Additional experienced staff have been recruited on short-term contracts. In department C (a support department) any gaps will be plugged with temporary staff as there is already a significant amount of shared knowledge within the department. Most of the attention on this project has been placed on the key operational areas of the organization. Future attention is required on three key support parts of the organization – one being the Senior Management team. As

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with all 7 of these projects, this work is ongoing. Project 2: Retention strategy – focusing on staff retention and preparing people for the future This project is being developed at a corporate level and fits with the strategic focus for closure of operations. Support has been offered throughout the organization to help staff to develop their plans for the future, for example through the provision of support for individuals’ own training and development goals, and staff have been offered career profiling and counselling. Soon help in developing CVs will be offered. Many team members are making use of the opportunities for gaining personal development and qualifications. Project 3: Build an open and supportive environment to encourage teamwork This project aims to encourage staff to work as a team organization-wide, and relates to breaking the “us and them” atmosphere that would play a destructive role as the organization becomes smaller and there is more dependency across departments. A key part of this project is showing that everyone is human and approachable. The newsletter is being used a tool for this – through a Personal Profile section – to highlight individuals and to give the rest of the organization the opportunity to learn a little more about their colleagues and identify shared interests. Those featured here have been operational, rather than executive, staff. Project 4: Implement continuous improvement – focusing on using staff knowledge to improve our processes This project aims to ensure that the organization is operating in the most efficient and effective way. As part of this project, volunteers from all departments have been sought to join a 'Focus Group' to discuss ways to improve and streamline processes and implement these improvements. So far nine volunteers have responded, showing a willingness throughout the organization at the operational level (ConsumProt has fewer than 100 staff in total). Project 5: Enhance everyone’s knowledge of each other’s roles and impact on the organisation Project 6: Create a sense that we all belong to the same organisation Building an open and supportive environment (project 3) complements these two inter-related projects. Part of this work is being implemented through the newsletter’s Personal Profiles section by including a summary of an individual’s job activities. In addition, the

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in them. Analyses of the results are currently taking place. Future work will involve the design and scheduling of appropriate courses.

minutes of departmental management meetings are being circulated outside the department – to share knowledge of issues and activities around the organization.

4.1 The newsletter has been supplemented by cross-department awareness training and presentations to increase each other’s understanding of roles and processes, and generally to increase departmental visibility. In addition, the annual organization-wide away day enables everyone to get to know one another in a positive and relaxed environment. More informal social events are planned, with many impromptu events being centred locally. Project 7: Make better use of existing software This project targets improving users’ awareness of available software and improving skills in a range of applications. This aims to deliver organizational benefits in improved productivity and personal benefits in additional transferable skills.

Summary

The projects are highly interlinked. Progress on one project often leads to progress on one (or more) other(s). There is also considerable overlap of the projects with the organization’s seven ‘Core Values’ (Make a Difference, Innovation, Teamwork, Support, Integrity, Learning, Enjoyment) which govern its internal management and policy making process. Thus it is expected that this work will further enhance the application of the core values within the organization.

5. Comparing agreed and implemented programmes of actions In this section we return to the 4 topics for improvement explored in the second workshop. We examine how the projects being implemented address each of these four topics. Table 1 summarises the comparison of agreed and implemented actions.

The first step involved assessing existing staff’s IT skill levels by means of an IT literacy survey. The goal was the identification of potential IT trainers for particular applications and those who wanted/needed further training

Table 1: How projects contribute to the four topics for improvement Project number: Staff development Team building Communication of roles and functions Formal continuous process improvement

5.1

Staff development

Development of skills and professional qualifications is a core theme of the actions being implemented. Four projects have elements of staff development: Project 1 – Staff development is taking place through skills sharing and succession planning to build contingency into the organization’s skills availability. Project 2 – The main focus of this project is to raise the marketability of the staff through identifying training and development goals. While this is aimed at retention of staff who are being trained, it also helps to prepare them for future employment. Project 5 – Some staff development will be a consequence of the awarenesstraining which is part of this project as staff will be exposed to issues they were

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1 x x x x

2 x x

3

4

x

x x x

5 x x x x

6 x x

7 x x x

previously unaware of – though its primary focus is team building and communication. Project 7 – Identifying and fulfilling staff software training needs and raising skills is a component of this project. With regards to staff development, each of the actions in these project were discussed in the workshop as part of developing staff – comparison with map in Appendix 1 supports this. However, and while we recognise the restrictions of limited resources, there were 3 issues discussed in the workshop which are not part of the actions as reported in the newsletter: Rewards and recognition – there is no explicit mention of any formal recognition scheme for staff development. Create a cross-functional buddy scheme – there are a number of initiatives which encourage cross-departmental

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information sharing and support, but not this one specifically. Document key procedures – documentation, and archiving (as mentioned later), has been neglected in the implementation strategy despite its importance in the workshop.

5.2

Team building

Team building is an important factor as the organization diminishes in size putting more emphasis on the existing, smaller workforce being able to work together. All projects aim to build team working: Project 1 – Through having succession planning in advance of people leaving, the organization is able to build teams through closer working with colleagues while they are still employed. Project 2 – Through having a more consistent workforce the team will become stronger which may positively influence the retention of key social and operational staff. Project 3 – The aim is for an open and supportive environment through getting to know each other. The newsletter and social events are both vehicles for this. Project 4 – Cross-functional team building is occurring as staff are working in the continuous improvement focus groups with colleagues whom they might not normally encounter. Project 5 – Cross-awareness training and presentations exposes staff to individuals they might never have had reason or opportunity to talk with before – even in the few minutes of informal chats before and after such sessions. Project 6 – The annual organization-wide away day and the informal social activities are a central part of team building. Project 7 – Depending on how the training sessions are organised, it is possible that having cross-sections of the organization together in the same room learning about software again provides exposure to other individuals in the organization. The lunch and tea breaks are useful opportunities. All but one of the actions for team building have been implemented. The exception is: Increase formal and informal team building sessions between departments on a scheduled basis – it is the ‘scheduled basis’ of this action which has not been reported. There was the away day, and reportedly informal social events, but it seems that repeated formal events to

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supplement the away day have not been core to the teambuilding strategy.

5.3

Communication of roles and functions

ConsumProt aim to communicate, and expand, the remits of staff as well as refocus expertise to more critical areas of their business. Four projects move the organization towards this: Project 1 – Through building a skills matrix and task matrix the organization is able to identify individuals with redeployable skills. This is a first step to expanding remits and refocusing expertise. Project 4 – Through the continuous improvement groups staff are able to explore their working with colleagues whom they might not normally have an opportunity to interact with. The second workshop itself was cited as an example of this benefit. Projects 5 and 6 – Entirely focussed on sharing knowledge about individual roles and departmental functions. These are supported through: newsletter articles promoting individual roles; crossdepartmental awareness training sharing information on departmental functions; sharing the minutes of departmental management meetings across the organization; the away day bringing the entire organization together for discussion. Many of the agreed actions for improving communication have been implemented. There are two actions which have not been reported on: Monthly summaries of Executive activity – this has not happened, although minutes of meetings are being circulated more widely. Information flow to people working off-site – however, the number of formal client visits is being reduced so perhaps there is less of a need for mass information flow. However, there are still off-site people to be communicated with and they need more formal information than newsletters and the like.

5.4

Formal continuous process improvement

Improving and rationalising the processes and services is made more urgent due to the diminishing workforce. Four projects address this:

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Project 1 – Some labour-intensive tasks have been re-designed to lower time/effort and enable those resources to be redeployed. Project 4 – Cross-departmental focus groups are tasked with reviewing and streamlining processes. Project 5 – The additional awareness gained by staff of other peoples’ roles and departments’ functions will enable additional process efficiencies to be identified – provided some mechanism exists for this feedback to reach the appropriate responsible individuals. Project 7 – The process improvements from effective and consistent use of software will be realised through migration to common software and consistent training in how it should be used in ConsumProt. It might be that while the organization is redesigning processes, these are not unconditionally process improvements from the customer’s viewpoint. The reduction in formal client visits to save resources might not mean an improvement in the service offered. There are four actions on which progress has not been reported: Automation of repetitive tasks. Automation takes time, especially without large-scale investment, and in addition there needs to be some prerequisite level of IT skills and a consistency in how software is used, so progress here would not be expected to be rapid. It is likely that in the near future the continuous improvement focus groups will have been able to automate where appropriate. The staff suggestion scheme – certainly the focus groups and more team meetings will capture more suggestions from staff, but there are no reported opportunities for ‘uninvolved’ or off-site staff to feedback into the decision making process. Again, there is no mention of a reward for any suggestions which come through other processes. Asking customers about improvements – the knowledge management strategy has been largely an internal initiative and there is no mention of looking externally for guidance on process improvements. Measuring improvements – as yet there have been no measurements of improvement proposed. ConsumProt do however have another workshop scheduled with us and we anticipate

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evaluation of improvements may be a central theme.

6. Conclusion The management of ConsumProt are confident that knowledge management while faced with closing operations is necessary and within their control. Their knowledge management strategy is an active one, designed to positively influence the work environment. The implementation of actions is progressing well, even while a diminishing workforce is creating additional strains and the life-span is ever shorter. The strategy has 5 main foci (in no particular order): 1. Improve the skill base of existing staff (with new skills and qualifications) to benefit the organization, retain those staff in the meantime, and make the staff more marketable following closure. This emphasis on individual development is rarely seen in the knowledge management literature, with a few exceptions such as Skyrme (1999). 2. Retain the skills currently available through building contingencies in the workforce and having overlap in roles and capabilities. 3. Communicate with the staff and encourage their feedback through the newsletter, away-days, questionnaires, distributing meeting minutes, and awareness training. 4. Build a supportive, welcoming environment in which to work so that people will not be motivated to leave before closure. This is achieved through a diverse range of actions, such as: publicising staff who are known throughout the organization to show their ‘human’ side; encouraging staff who never normally talk to one another to do so in the work environment and socially; getting people involved in the improvements through focus groups; enriching jobs with diversity. 5. Rationalise processes to enable the resources saved to be redeployed to create contingencies in other areas of the organization. Looking at these as examples of good knowledge management practice, numbers 1-4 would potentially be valuable to any organization, whether with a limited life-span or not. There is, however, a difference in emphasis in numbers 1 and 4, looking to the future of the staff after closure. The major difference is perhaps in number 5. Process redesign can be recommended to any organization, but at least in the case of ConsumProt, the limited life-span means that the main aim is rationalisation, not necessarily

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improvement. In the terms coined by Hansen et al (1999), ConsumProt is very much following the personalisation strategy. By our estimate 31 of the 41 actions agreed during the workshop have been implemented, with 10 outstanding. However, many of these 10 are overlapped by other actions which have been implemented and so the additional benefit foregone is likely to be small. This is significant progress in a relatively short time (just over one year from the first workshop at the time of writing). Management at ConsumProt may need to safeguard against too much change for certain individuals. While some people might flourish in a changing environment, others might be overwhelmed and uncomfortable with seeing so much change happen, never mind being asked to change themselves. This seems to be an issue which has been overlooked in the existing strategy, but is perhaps more appropriately addressed at a line management level.

6.1

Acknowledgements

We are grateful to CIMA, the Chartered Institute of Management Accountants in the U.K., for funding the first workshop with ConsumProt.

References Bair, J. (1997) "Knowledge management: The era of shared ideas". Forbes, September 22, pp.28. Coombs, R. and Hull, R. (1998) ""Knowledge management practices" and path dependency in innovation". Research Policy, Vol 27, No. 3, pp237-253. Davenport, T. H. and Prusak, L. (1998) Working knowledge : how organizations manage what they know. Harvard Business School Press, Boston, Mass. Drucker, P. F. (1992) "The new society of organizations". Harvard Business Review, Vol 70, No. 5, pp95-104. Eden, C. and Ackermann, F. (1998) Making Strategy: The Journey of Strategic Management. Sage, London.

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Edwards, J. S., Collier, P. M. and Shaw, D. (2003a) "Making a journey in knowledge management strategy". Journal of Information and Knowledge Management, Vol 2, No. 2, pp135-151. Edwards, J. S., Collier, P. M. and Shaw, D. (2003b) Management accounting and knowledge management. CIMA, London. Edwards, J. S., Shaw, D. and Collier, P. M. (2002) Group perceptions of knowledge management. In Proceedings of Third European Conference on Knowledge Management MCIL, Reading, UK, Trinity College, Dublin, Ireland, pp. 209-222. Hansen, M. T., Nohria, N. and Tierney, T. (1999) "What's your strategy for managing knowledge?" Harvard Business Review, Vol 77, No. 2, pp106-116. Hendriks, P. H. J. and Vriens, D. J. (1999) "Knowledge-based systems and knowledge management: friends or foes?" Information and Management, Vol 35, No. 2, pp113-125. Lucardie, G. and Arts, G. (1990) Strategic use of expert systems in organisations - the knowledge perspective, an underexposed issue. In Proceedings of ES90 London. Mullin, R. (1996) "Knowledge management: A cultural evolution". Journal of Business Strategy, Vol 17, No. 5, pp56-59. Nonaka, I. and Takeuchi, H. (1995) The knowledge-creating company, how Japanese companies create the dynamics of innovation. Oxford University Press, New York and Oxford. Probst, G., Raub, S. and Romhardt, K. (1999) Managing knowledge: building blocks for success. Wiley, Chichester. Shaw, D. (2003) "Evaluating electronic workshops through analysing the 'brainstormed' ideas". Journal of the Operational Research Society, Vol 54, No. 7, pp692-705. Skyrme, D. J. (1999) Knowledge networking: creating the collaborative enterprise. Butterworth-Heinemann, Oxford. Walsh, J. P. and Ungson, G. R. (1991) "Organizational memory". Academy of Management Review, Vol 16, No. 1, pp57-91.

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Appendix 1 – An anonymised map from ConsumProt illustrating their agreed actions on staff development

Understanding Knowledge-Sharing in Online Communities of Practice Mark Sharratt and Abel Usoro University of Paisley, Scotland [email protected] [email protected] Abstract: Information Technology is no longer regarded solely as a repository within knowledge management but also as a collaborative tool. This change of role gives rise to online communities (OLCs), which extend the loci of existing communities of practice. To leverage the potential of these communities, organisations must understand the mechanisms underpinning members’ decisions to share knowledge and expertise within the community. This paper discusses existing research and develops a theoretical model of factors that affect knowledge sharing in OLCs. The aim is to increase our understanding of the antecedents to knowledge-sharing in OLCs. Keywords: knowledge sharing, online communities of practice, extrinsic rewards, motivation, trust, value congruence.

1. Introduction Knowledge is widely recognised as a critical organisational resource irrespective of economic sector or type of organisation (Stewart 1997; Sveiby 1997; Davenport & Prusak 1998). It is difficult, if not impossible, to maximise the value of this resource without adequate understanding of how to leverage and share knowledge throughout the organisation. This paper seeks to promote this understanding by first discussing trends in knowledge management (KM) and examining the emerging role of online communities (OLCs). This review of existing literature leads to the development of various hypotheses as to the relationship between knowledge-sharing and its antecedent factors in OLCs. The factors include the ease of use and perceived usefulness of the KM system, trust, the perceived proximity of knowledge-sharing to career advancement, sense of community and perceived value congruence. These factors are operationally defined and are presented as a theoretical model. Groundwork is laid for a follow-up study that will test and validate this model.

2. Developments in knowledge management The fixed, tangible resources of the organisation are no longer considered a sustainable source of competitive advantage. Such assets quickly become available to competitors. Knowledge, on the other hand, is far harder to replicate, it is unique amongst organisational resources in that no other resource increases in value through use (Probst et al. 2000). Davenport and Prusak (1998) explain the central role of ideas in this process: “Unlike material assets … knowledge assets increase with use: ideas breed new

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ideas, and shared knowledge stays with the giver while it enriches the receiver … only new knowledge resources – ideas – have unlimited potential for growth” (p.1617). However, despite this realisation and the recent explosion of interest in KM, a review of the literature indicates that many KM initiatives only partially deliver on expectations (Swan & Scarbrough 1999). Many contributing factors have been posited (Szulanski 1996; Ruggles 1998; Doswell & Reid 2000) with a recurring theme being the overemphasis on the role of IT, combined with a lack of consideration for cultural and motivational factors (Newell 2001; Beaumont & Hunter 2002). New information systems (IS) tend to have the effect of reinforcing existing behavioural norms (McDermott 1999) and do nothing to change attitudes towards open communication and sharing (Ellis 2003). What is required for effective KM is a combined approach focused on both social and information systems.

2.1

KM and IS

An information system stores, processes and communicates information (Mallach 1994). KM seeks to leverage the organisation’s expertise and know-how to add value to the business, utilising some form of technological support system (Ellis 2003). IS focuses on the core processes that pump the business, critical data that enables the business to effectively operate. KM focuses beyond the day-to-day operations and seeks to build the capability to improve the way the business functions. By developing the capabilities of the organisation’s members, KM develops the high value-adding expertise and creativity that enables business evolution and growth. Hence, KM seeks to effectively harness IS to achieve the goal of maximising the value of the organisation’s knowledge-base.

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This high value-adding knowledge is less factual, and is based more on the experiential knowledge that is hard to transfer via information systems. Such knowledge can act as a sustainable source of competitive advantage (Bowman 2001). The challenge, therefore, is to understand how we can increase the context of information and communication so as to facilitate the sharing of this more elusive and tacit experiential knowledge.

2.2

CoPs, Context and OLCs

There has been a growing focus on the role of communities of practice (CoPs) within the KM domain. CoPs have been described as “groups of people informally bound together by shared expertise and passion for a joint enterprise" (Wenger & Snyder 2000). They are different from teams and functional units as they are self-organising systems whose lifespan is determined by its members, based on the intrinsic value that membership brings. Such communities are not constrained by time and space and therefore can span organisational boundaries (Wenger 1998). CoPs have been identified as effective loci for the creation and sharing of knowledge (Lave & Wenger 1991). Such communities are able to retain dynamic and evolving knowledge within a real-time process that adds context to existing static repositories. Members identify and engage each other with a common set of codes and language. The development of a strong network of likeminded individuals who share a common understanding is conducive to the development of an environment typified by high levels of trust, shared behavioural norms, mutual respect and reciprocity (Lesser & Storck 2001). Such an environment has been identified as being high in social capital, and has been linked directly with the processes of the creation and sharing of knowledge (Nahapiet & Ghoshal 1998). Of recent, the development of OLCs has resulted in CoPs that are mediated by IS. For OLCs to maximise their value in KM terms, practitioners need to understand the mechanisms and processes that underpin members’ decisions to share what they know.

3. Knowledge-sharing A review of the existing literature did not reveal knowledge-sharing as a well-defined construct. Therefore, in order to establish what we mean

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by knowledge-sharing, this section builds our understanding by discussing root definitions.

3.1

Knowledge

Knowledge is an intangible resource that exists within the mind of the individual (Sveiby 1997). The recent explosion of interest surrounding KM has brought with it much confusion with critics arguing that knowledge in itself cannot be managed and that KM is just another management fad (Wilson 2002). Indeed, there is the view that knowledge management is, by definition, an oxymoron (Malhotra 2000). Hildreth and Kimble (2002) identify a lack of distinction between KM and information management. In order to clarify this distinction it is necessary to understand how information and knowledge relate to each other. Both information and knowledge are grounded on data. The two can be differentiated if we consider interpretation and meaning. Information by definition is informative and, therefore, tells us something. It is data from which we can derive meaning. Knowledge is directly related to understanding and is gained through the interpretation of information. Knowledge enables us to interpret information i.e. derive meaning from data. The interpretation of meaning is framed by the perceiver’s knowledge. So what one person perceives as information can equate to meaningless data to another. So information that is interpreted generates meaning and new knowledge. Thus, information can be added to knowledge to increase what is known. It is also valid to state that knowledge comes before both information and data since one needs to know the context of data before it can be interpreted as information. Hence it can be seen that knowledge is subjective and can only reside within the mind of the individual. So what do we mean by sharing knowledge, if knowledge cannot exist outside the individual?

3.2

Sharing

Sharing is a process whereby a resource is given by one party and received by another. For sharing to occur, there must be an exchange; a resource must pass between source and recipient. The term knowledgesharing implies the giving and receiving of information framed within a context by the knowledge of the source. What is received is the information framed by the knowledge of the recipient. Although based on the knowledge of the source, the knowledge received cannot be identical as the process of interpretation is

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subjective and is framed by our existing knowledge and our identity (Miller 2002). By definition, an IS shares information. So what differentiates information-sharing from knowledge-sharing? The sharing of information covers a broad spectrum of exchanges and does not necessarily lead to the creation of new knowledge (Van Beveren 2002). Knowledge-sharing intrinsically implies the generation of knowledge in the recipient. In face-to-face communication, an effective mechanism for gaining knowledge is to request help from another i.e. someone who may possess the knowledge or expertise required. This request may lead to a conversation that will facilitate the creation of new knowledge in the recipient. This suggests that in face-to-face interactions, conversations can be an effective conduit for knowledge-sharing. Indeed it has been suggested that conversation may be the only effective means of sharing knowledge (Pierce 2002). Conversation is framed by a unique common context that is built between participants. It is this common context that facilitates the transfer and development of the more deeply rooted tacit knowledge. The context is built through communication and is enabled by a shared perspective, language and common understanding. It is thus through conversation that we learn how to learn together (Brown & Isaacs 1996). Zeldin (1998) provides a useful description of the role of conversation in the creation of knowledge: “Conversation is a meeting of minds with different memories and habits. When minds meet, they don’t just exchange facts: they transform them, reshape them, draw different implications from them, engage in new trains of thought. Conversation doesn’t just reshuffle the cards: it creates new cards.” (from www.gurteen.com). Conversation can occur electronically via email and online discussion board tools. Within the context of an OLC, the direct mechanisms for engaging another member of the group who may possess the knowledge one seeks is to post an open question or a request for assistance on the community’s discussion board. Although lacking the richness of faceto-face dialogue, the benefit of online discussion forums is that the conversation becomes accessible to the whole of the community and can be archived and accessed by other members. Similarly, a single request

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may generate many responses. Hence through the shared perspective, common language and context of OLCs, individuals are able to help resolve problems by sharing what they know. Online conversations may take many forms. Through conversation we articulate "hunches, insights, misconceptions, and the like, to dissect and augment ... understanding" (Brown & Duguid 1991: 45). For example, knowledge may be shared in the form of a story describing a similar experience whereby a method or technique was developed or used to solve a problem. If unable to provide a solution directly, knowledge may be shared in relation to contacting someone who might know and be willing and able to help. The process of knowledge-sharing involves the knowledgesource using the online community system as a mechanism to effectively convey what they know. The process facilitates the creation of the necessary understanding in the recipient, enabling the development of a solution to a problem. Hence, within the context of OLCs, knowledgesharing can be narrowly defined as instances whereby a member responds to a posted problem by sharing what they know. Based on this conceptualisation of knowledge-sharing, the next section investigates and discusses factors that affect the decision to share knowledge within an OLC.

4. Factors affecting knowledgesharing Synthesising recent research, this section provides the theoretical foundations for the development of a number of hypotheses as to the relationship between a number of factors and knowledge-sharing in OLCs.

4.1

Organisational structure

Working practices are constantly changing as individuals and organisations adapt within an ever-changing environment. New knowledge is created as best practice and working methods evolve and are improved. When this creation of new best practice occurs below the level of upper management, at a more operational level, it becomes management’s challenge to harness and spread this new knowledge throughout the organisation in order to leverage maximum value and advantage from it (Brown & Duguid 2000). Organisations with a centralised, bureaucratic management style can stifle the creation of new knowledge, whereas a flexible,

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decentralised organisational structure encourages knowledge-sharing, particularly of knowledge that is more tacit in nature. Thus “[i]n order to be successful in knowledge transfer … firms must be organised to be highly flexible and responsive” (Chung 2001: 2). Furthermore, status similarity has been shown to positively relate to knowledge-sharing (Hall 2001b). Thus, organisations with a flatter, less hierarchical structure may benefit from increased levels of knowledge-sharing. Synthesising these research findings leads to the development of the following proposition: H1: The less hierarchical an organisation’s structure, the greater the instances of knowledge-sharing.

4.2

Technical infrastructure

Information technology (IT) can facilitate collaborative work and enable the knowledgetransfer process (Chung 2001). However, such technologies are inherently limited in their ability to transfer knowledge that is more tacit in nature (Hildreth & Kimble 2002). Researchers argue that the technical infrastructure is highly dependent on the value of the content it holds (Hall 2001a) and the relationships it can foster. Two aspects of systems use have been related to the motivation to act. Firstly, the action must itself not be difficult to undertake. Secondly, the outcome of the action must be perceived to be useful (Hall 2001a). In the context of online communities, a critical mass of activity is required to attract others (Preece 2000); without critical mass, the perception of the usefulness of the knowledge-sharing system will inhibit its use. Furthermore, information quality has been shown to indirectly affect participation in online communities (Yoo et al. 2002). In online communities, an additional factor that is likely to influence the perceived usefulness of the system is the perception of the knowledge of a community’s members. Hence, the following hypotheses can be derived: H2: The greater the ease of use of a knowledge-sharing system, the greater one’s use of the system for knowledgesharing. H3: The greater the perceived usefulness of the knowledge-sharing system, the greater a user’s participation in knowledgesharing.

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4.3 Trust Trust is a much debated construct (Kramer & Tyler 1996). It involves a willingness to make one’s self vulnerable to others and involves trust in various facets of another party, namely: (1) trust in their competence; (2) trust in their openness and honesty; (3) trust in their intensions and concerns; and (4) trust in their reliability (Mishra 1996). Trust is an important facilitator in communication. According to Mitzal, "trust, by keeping our mind open to all evidence, secures communication and dialogue" (Mitzal 1996: 10). Trust facilitates transactions and collaboration (Fukuyama 1995). This suggests that “where relationships are high in trust, people are more willing to engage in … cooperative interaction (Nahapiet & Ghoshal 1998). Indeed empirical research has linked trust with levels of inter-unit resource exchange (Tsai & Ghoshal 1998). Following Maher et al. (1995), trust can be conceptualised across three dimensions, viz. integrity, benevolence and competence. Integrity-based trust is the perception that another party is honest and reliable. Benevolence-based trust relates to the perception that another party would keep the best interests of the trustor at heart. Competence-based trust is rooted in the perception that another party is knowledgeable or possesses a certain level of competence. These dimensions can be held at various levels of analysis, e.g. trust can be held in the individual, the community or the entire organisation. Integrity-based trust has an important role to play in motivating knowledge-sharing. One is not likely to be motivated to share one’s knowledge with another individual or a community if one perceives them to be dishonest or unreliable. Similarly, when one views a community as upholding trustworthy values such as mutual reciprocity, honesty, reliability and commitment, there is likely to be a greater degree of motivation to participate and share one’s knowledge. Hence, H4: The greater one’s perceived integrity in a community, the greater one’s engagement in knowledge-sharing. Fear of losing face has been identified as one of the main barriers to knowledge-sharing (Ardichvili et al. 2002). The fear of posting an incorrect or misleading contribution, or the belief that one’s contribution may not be sufficiently important or relevant, can have a

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significantly negative effect on one’s motivation to share knowledge. Competence- and benevolence–based trust may both have a role to play in overcoming such fears. The higher the perceived benevolence of a community, the more likely one is to feel less threatened by making an erroneous contribution or one that lacks relevance. A benevolent community is likely to encourage the participation and development of its members. Hence, H5: The greater the perceived benevolence in a community, the greater one’s participation in knowledge-sharing. Conversely, a high degree of competencebased trust in relation to one’s own competence is likely to generate demotivational fears such as losing face and this would encourage the person to abstain from sharing their knowledge. Hence, H6: The greater the trust in the competence of one’s community, the less one’s participation in knowledge-sharing.

4.4

Career advancement

Knowledge resides within individuals. Therefore, in order to effectively share knowledge, individuals must be motivated to do so. It has been argued that the provision of appropriate incentives will most likely influence the behaviour of employees in knowledgesharing (Chung 2001: 9). Hall (2001b) views knowledge-sharing as a social exchange and argues that to “entice people to share their knowledge … actors need to be persuaded it is worth entering into a transaction in exchange for some kind of resource (p. 7). These arguments raise the question of what constitutes an appropriate incentive. Indeed, there is much debate as to the most effective and appropriate incentive in motivating knowledge-sharing activities (Brown & Duguid 2000; Chung 2001). Hall (2001b) suggests that knowledge-sharing could be included within ‘good citizenship’ where “[e]mployees who feel that they have been well supported by their organizations tend to reciprocate by performing better and engaging more readily in citizen behaviour” (Wayne et al. 1997: 90 in Hall, 2001b: 15). Hence, would a perceived high level of investment in employee development motivate members to engage in knowledge-sharing? Knowledge-sharing could be motivated by a sense of moral obligation. Indeed, recent studies of CoPs have suggested an association between moral obligation to the

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community and levels of knowledge-sharing (Ardichvili et al. 2002). Extrinsic rewards such as financial incentives are another method of motivating knowledgesharing (Hall 2001b). However, extrinsic rewards may provide only temporary compliance, rupturing relationships and reducing pro-social behaviour: “Systems based on extrinsic rewards quickly turn moral obligation into acts of self-interest, and could potentially destroy the open provisioning of knowledge in a community” (Wasko & Faraj 2000: 170). Indeed, O’Dell and Grayson (1998) argue that “if the process of sharing and transfer is not inherently rewarding, celebrated, and supported by the culture, then artificial rewards won’t have much effect” (p. 82). Herzberg (2003) found that financial rewards and other external factors are important in avoiding demotivation, but have little effect on sustaining the motivation of employees. Instead Herzberg discovered that factors that are intrinsically rewarding, such as the work itself, recognition and reputation, had a far greater influence on an employee’s motivation. Hall (2001a) argues that career advancement is an effective incentive in motivating knowledge-sharing. Although by definition an extrinsic reward, career advancement is closely related to the intrinsic motivators of recognition and reputation. Furthermore, it has been argued that employees may feel their job security is threatened by sharing the knowledge that represents their value to the company (Davenport & Klahr 1998). This may act as a demotivator. This leads to the proposition that a positive association between knowledge-sharing and career advancement is likely to motivate members to share their knowledge. Hence, H7: When knowledge-sharing is perceived to be closely linked to an individual’s career advancement, knowledge-sharing will be higher.

4.5

Sense of community

Sense of community (SoC) has been defined within a group as “a feeling that members have of belonging … that members matter to one another … and a shared faith that members’ needs will be met through their commitment to be together” (McMillan & Chavis 1986: 9). SoC leads to a common perspective of knowledge as a public good, owned and maintained by the community (Wasko & Faraj 2000). Thus, knowledge-sharing is likely to be motivated by

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between an individual and their organisation can generate distrust (Fox 1974) and lead to lower levels of job satisfaction, job performance and organisational commitment (Balazs 1990).

moral obligation that results in a deeper sense of satisfaction than when motivated by extrinsic factors. A strong SoC will also lead to a greater degree of importance being placed on recognition of knowledge-sharing. This brings with it feelings of intrinsic satisfaction. Hence,

Community members with little commitment to the organisation are likely to be less motivated to participate in KM initiatives. Conversely, high value congruence may manifest itself in higher commitment to KM initiatives. Hence,

H8: Where SoC is stronger, participation in knowledge-sharing will be greater.

4.6

192

Value congruence

A value has been defined as “an enduring belief that a specific mode of conduct or endstate of existence is personally or socially preferable to an opposite or converse mode of conduct or end-state of existence” (Rokeach 1973: 5). Our values affect our goals, attitudes, behaviour and are closely related to commitment (O'Reilly 1989).

H9: The greater the perceived congruence an individual has with an organisation’s values, the greater their participation in knowledge-sharing.

4.7

Research model

A theoretical model is developed and presented in Figure 1. This expresses and draws together the research propositions. Table 1 provides an operational definition for each of the constructs and provides the foundation for the empirical testing of the research model in a future study.

Organisational values are defined as the values that management ascribe to and promote (Money & Graham 1999). Value congruency is the sharing of values between an individual and their organisation (Balazs 1990). A perception of value incongruence

H1 H2 H3 H4 H5 H6 H7 H8 H9

Figure 1: Research model

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Table 1: Operational definitions Concept Knowledgesharing Organisational Structure

Component Contribution Hierarchical Structure Ease of use

Information System

Trust

Recognition

Perceived usefulness Integrity -based trust Benevolencebased trust Competence based trust Career Advancement Sense of community Value congruence

Definition An instance of a response to an online request for assistance whereby a member contributes what they know. The number of levels of authority in an organisation (Buchanan and Huczynski, 1997, p 304). The degree to which a member believes that using the community discussion board is free from effort (Davis 1989). The degree to which a member believes that using the community discussion board enhances their job performance (Davis 1989). The degree to which a member believes the community to be honest and reliable (Mayer et al. 1995). The degree to which a member believes the community will act in their best interest (Mayer et al, 1995). The degree to which a member believes that the community is knowledgeable and competent (Mayer et al 1995). The degree to which a member believes sharing their knowledge will positively affect their career. The degree to which a member feels a sense of belonging in a community (Yoo et al. 2002). The degree to which a member’s values are congruent with the organisation’s.

5. Limitations of study

6. Conclusions and future research

Adopting a narrow view of knowledge-sharing can simplify quantitative approaches such as hypothesis testing. However, this approach can attenuate some of the richness associated with a construct. For example, how would the factors discussed affect the sharing of other online knowledge-based resources such as documents, templates and presentations that typically reside within repository-based systems?

In this paper we have discussed the importance of knowledge as an organisational resource and sustainable source of competitive advantage. We have explored the role of technology within KM and have identified the emergence of CoPs in KM as loci for the creation and sharing of knowledge. Having ascertained the importance of both information systems and social interaction in leveraging knowledge, we have highlighted the role of OLCs as an effective mechanism for extending the knowledge-related benefits of existing CoPs.

Knowledge-sharing could also prove difficult to measure, as knowledge is not easy to quantify. Knowledge-sharing involves a dyadic relationship between source and recipient. It is feasible and likely that these two actors would place differing values on a given instance of knowledge being shared. Furthermore, there is an inherent limitation and criticism of the applicability of the hypothetico-deductive method within social sciences research. Checkland (1989) in a plenary address to the OR (Operational Research) Society highlights the difference between research in the social and the traditional sciences: “How different studying the chemistry of the reaction of nitrogen and hydrogen to yield ammonia would be if the molecules of nitrogen and hydrogen could decide capriciously whether or not to combine, doing so today but deciding not to next Thursday! But that is the situation the would-be social scientist is in” (p. 38).

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We have advocated through this paper that in order for organisations to fully leverage their knowledge-based assets, they must first understand the factors that affect knowledgesharing at an individual level. A lack of clarity surrounding the term 'knowledge-sharing' has been identified and we have set forth an operational definition. We have then presented the theoretical underpinning for the development of a number of hypotheses based on the relationship of nine factors to knowledge-sharing in OLCs. The factors identified include: organisational structure; the ease of use and perceived usefulness of the information system; trust based upon the benevolence, competence and integrity of the community; the perceived proximity of knowledge-sharing to career advancement; sense of community; and organisational value congruence. These factors are presented within a theoretical

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model and the constructs operationally defined.

have

been

This paper provides the foundations for a subsequent phase of research. This will seek to identify and validate measures based on the operational definitions and empirically test the hypotheses underpinning the model. This research will continue the work of this paper in extending our understanding of the antecedents to knowledge-sharing within OLCs.

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Probst, G, Raub, S & Romhardt, K, Managing Knowledgë: Building blocks for success, John Wiley & Sons, Chichester, England (2000). Rokeach, M R, The nature of human values, Free Press, New York (1973). Ruggles, R L, 'The State of the Notion', California Management Review, 40(3), (1998) pp. 80-89. Stewart, T A, Intellectual Capital: The New Wealth of Organizations, New York, Currency/Doubleday (1997). Sveiby, K E, The New Organizational Wealth, Berret-Koehler, San Francisco (1997). Swan, J & Scarbrough, H, Case Studies in Knowledge Management, Chartered Institute for Personnel & Development, London (1999). Szulanski, G, 'Exploring Internal Stickiness: Impediments to the Transfer of Best Practice Within the Firm', Strategic Management Journal, 17, (1996) pp 2743. Tsai, W & Ghoshal, S, 'Social Capital and Value Creation: The Role of Intrafirm Networks', Academy of Management Journal, 41(4), (1998) pp 464-476. Van Beveren, J, 'A Model of Knowledge Acquisition that Refocuses Knowledge Management', Journal of Knowledge Management, 6(1), (2002) pp 18-22. Wasko, M M & Faraj, S, '"It is what one does": why people participate and help others in electronic communities of practice', Journal of Strategic Information Systems, 9(2-3), (2000) pp 155-173. Wayne, S, Shore, L & Liden, R, 'Perceived organizational support and leadermember exchange: a social exchange perspective', Academy of Management Journal, 40(1), (1997) pp 82-111. Wenger, E, 'Communities of Practice: Learning as a Social System', Systems Thinker, (June, 1998) [online: http://www.co-il.com/coil/knowledgegarden/cop/lss.shtml]. Wenger, E & Snyder, W M, 'Communities of Practice: The organisational frontier', Harvard Business Review, (2000) pp 139145. Wilson, T D, 'The nonsense of "knowledge management''', Information Research, 8(1), (2002) [online: informationr.net/ir/81/paper144.html]. Yoo, W-S, Suh, K-S & Lee, M-B, 'Exploring Factors Enhancing Member Participation in Virtual Communities', Journal of Global Information Management, 10(3), (2002) pp 55-71.

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Visual Tools within MaKE - A Knowledge Management Method Peter Sharp, Alan Eardley, and Hanifa Shah Staffordshire University, UK. [email protected] [email protected] [email protected] Abstract: This paper focuses on the practical significance of visual tools in Knowledge Management (KM) and Information Systems (IS) development in the context of the development of MaKE, a KM method. Visual tools are used extensively in KM and IS. However, this paper identifies a dilemma in the use of visual tools and examines how this dilemma was addressed during the development of some visual tools in MaKE. A brief description of MaKE is provided before visual tools are presented and discussed. The visual tools are called the Knowledge Targets Pyramid, Knowledge Tree, Knowledge Block, and the Linking Overview which are used to help present outcomes. They were reviewed and analysed in workshops in a major UK Fast Moving Consumer Goods manufacturer. The authors suggest that the findings of this research are relevant to visual tools used as part of KM methods and frameworks and that if certain guidelines are borne in mind, visual tools are very helpful for understanding and communicating, in a short time frame, relatively complex phenomena. Within the context of MaKE the Knowledge Targets Pyramid, Knowledge Block, and the Linking Overview do this more effectively than the Knowledge Tree. Keywords: Knowledge Management method, action research, visual tools

1. Introduction There is a need for Knowledge Management (KM) not to remain purely in the realms of academic thought, but be translated into practically relevant structures that can benefit organisations. This is a relatively simple to write, but difficult to bring into practice and is particularly significant in KM and Information Systems (IS) development today. The authors argue that much work is required to hone useful KM concepts to create practically valuable outcomes. This can be done by applying and reflecting on KM concepts in organisations. This paper examines the use of some visual tools developed in the context of MaKE - a KM method. This is done by outlining the practical significance of visual tools in KM and IS in Section 2 before a dilemma associated with the use of visual tools is identified in Section 3. MaKE and 'Outcome Visual Tools' are introduced in Section 4 and Section 5 contains a brief description of the research method and the context for the research. The visual tools and the feedback about them are provided in Section 6.

2. The practical significance of visual tools in IS and KM 'Visual tools' are used in this paper to refer to diagrams and tables used for purposes such as illustration, elicitation, description or explanation. The practical significance of visual tools in is and km is endorsed by the wide use of them in both domains.

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IS methodologies use visual tools extensively. Examples of these include the Unified Modelling Language (Booch, Jacobson, Rumbaugh, 1999), Jackson System Development, Structured Systems Analysis and Design Method (Avison and Fitzgerald, 1997), Methods for Elicitation, Analysis and Specification of User Requirements (Liu, 2000), and Soft Systems Methodology (Checkland and Scholes, 2000). These methodologies use visual tools to clarify IS domains, communicate IS requirements and provide structures for designing or understanding software. In KM visual tools are widely used in frameworks, models, methods and evaluative techniques. Examples of where visual tools are used include the Core Capabilities and Activities framework (Leonard Barton, 1995), Knowing Organisation Model (Choo, 2001), Organizational Capabilities Framework (Kusunoki, Nonaka, and Nagata, 1998), Intellectual Capital Model (Edvinsson and Malone, 1997) and the Three-Fold Framework (Holsapple and Joshi, 2001). Normally these visual tools are used to help simplify complex detail or summarise the overall 'picture' and thereby enhance the communicability of a viewpoint or content.

3. Dilemma associated with use of visual tools There is a dilemma in the use of visual tools that the author of MaKE (‘the Designer’) was aware of when designing it. The use of visual

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tools to simplify or summarise complex phenomena may enhance communicability but paradoxically may lead to misunderstanding and misrepresentation of what is being communicated. This problem has been identified in the context of symbolic notation and logical rules where, in simplifying what is done, much of the richness and usefulness is diluted. This is one reason for advocating case study as a storytelling device (Remenyi, Money, Price and Bannister, 2002). A similar problem has been identified in the use of frameworks (Doyle, 1991). Some frameworks simplify to such an extent, that they obscure insight and can give rise to distortion. In intellectual capital (IC) there is a difficulty of making evaluative tools that are sufficiently detailed to measure the value of intangible assets but at the same time are navigable and communicable across companies (Edvinsson and Malone, 1997). This problem led to years of work to develop an approach that attempted to do both (Skandia Navigator). Therefore the drive for simplification and clarity needs to be balanced with inclusion of sufficient detail in visual tools. This challenge is significant for KM and IC frameworks and was relevant in the development of MaKE. The next section introduces MaKE and Outcome Visual Tools.

4. MaKE and outcome visual tools MaKE stands for 'Manage Knowledge Effectively', which is a statement of intent and label for a new KM method. MaKE is designed to help organisations manage and evaluate knowledge effectively (Sharp 2002a). It builds on the concept of SolSkeme (Sharp, 2002b) and is designed to address a number of practical challenges that have been identified in KM (Sharp, 2002b). SolSkeme built on principles and concepts adopted in the ThreeFold Framework (Holsapple and Joshi, 2001). Figure 1 illustrates MaKE. MaKE has three major components applied in sequence. It begins with MaKE First Steps. The outcome of this component is a definition of knowledge for the context to which the rest of MaKE is to be applied. This definition is used as a starting

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point of MaKE Direct and MaKE Executive. MaKE Direct is conducted with employees to elicit ‘Knowledge Requirements’ and the means by which the Knowledge Requirements may be achieved (Sharp, 2002a). In theory MaKE Direct can be conducted any number of times and this is represented by the 'MaKE Direct n' ellipse in Figure 1. The Knowledge Requirements are ranked in a ranking table and pooled within the MaKE Executive component and Knowledge Targets and their associated Knowledge Blocks are generated. Once this is completed MaKE Measures is implemented to marry up appropriate measures with knowledge manipulation activities in the Knowledge Blocks. A Linking Overview can also be generated. In Figure 1 there is a dotted line from MaKE Measures to MaKE First Steps because MaKE is designed to be used repeatedly at periodic intervals. This can be done to see whether Knowledge Targets have been achieved and knowledge manipulation activities have been effectively carried out. The latter can be gauged by reference to measures and indicators in the Knowledge Blocks. When MaKE is applied in a new cycle new Knowledge Targets may be articulated as previous Knowledge Targets are achieved and the organisations’ circumstances change. MaKE is a process that produces a number of outcomes. MaKE uses visual tools to assist in the implementation of the process and illustration of the outcomes. The visual tools provide frameworks for collating, categorising and structuring information. Some of the visual tools have more than one of these uses. Only some of MaKE’s visual tools are discussed in this paper. Table 1 provides a summary of the main components and the primary visual outputs that have existed within MaKE. This paper focuses on visual tools used to help illustrate some of the outcomes of MaKE which are identified by asterisks below ("Outcome Visual Tools"). One of these, the Knowledge Tree, does not appear in Figure 1 for reasons explained in Section 5.

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MaKE Direct 1

MaKE Direct 2

MaKE Measures

MaKE Executive

MaKE First Steps

MaKE Direct n

Knowledge Definition Template

Linking Overview

Knowledge Pyramid

Knowledge Blocks

Figure 1: Summary of Components of MaKE Table 1: Components and primary visual outputs of MaKE Component 1 MaKE First Steps

2

MaKE Direct and MaKE Executive

3 MaKE Measures

Summary of What it Does Process to facilitate creation of knowledge definition for context to which MaKE is applied. Application of SolSkeme (Sharp, 2002b) in an updated form. This involves prioritising Knowledge Targets and articulating means of achieving them. Presentation of results and applying measures.

5. Research method and context of feedback MaKE was tested, validated and developed at a major UK Fast Moving Consumer Goods (FMCG) manufacturer. The company makes and distributes FMCG branded goods and it has several brands within the top 20 best selling grocery brands in the UK. MaKE was applied and developed within the context of marketing and sales functions of a brand of the company. The Outcome Visual Tools were used as part of a piece of action research and were

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Primary Visual Outputs - Knowledge Definition Template

- Knowledge Tree* - Knowledge Targets Pyramid* - Knowledge Blocks* - Linking Overview*

discussed in workshops with senior managers in the company who worked in IT and business departments. These workshops occurred within two full cycles of the application of MaKE, which are referred to as ‘Cycle 1’ and ‘Cycle 2’ in the rest of this paper. Over the course of the two cycles the form of MaKE changed and some of the visual tools were discarded and replaced. This meant that the collection of Outcome Visual Tools was different at the start than at the end of the action research. Table 2 provides a brief summary of visual tools that were retained,

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discarded or created over the course of the action research.

design. In particular the focus was upon whether the Outcome Visual Tools performed their function effectively and were deemed useful and clear in presenting outcomes (i.e. addressing the dilemma referred to in Section 3).

A mixture of techniques was used to elicit feedback during the workshops including written questionnaires, discussion with participants and personal reflection on the Table 2: Outcome Visual Tools Discarded, Retained, or Created Visual Tool

Part of Initial Design?

Discarded, Retained, Created and at what stage Discarded between Cycle 1 and Cycle 2

Knowledge Tree

Yes

Knowledge Targets Pyramid

Yes

Retained

Knowledge Block

No

Created between Cycle 1 and Cycle 2

Linking Overview

No

Created between Cycle 1 and Cycle 2

6. Outcome visual tools and feedback during development of MaKE Sections 6.1 to 6.4 provide a description of each Outcome Visual Tool and feedback about them. The feedback came in various forms; written responses in questionnaires (‘Formal Direct Feedback’); verbal communication with the Designer in workshops (‘Informal Direct Feedback’); verbal communication from colleagues in the organisation outside workshops (‘Indirect Feedback’) and in the form of reflections in and on practice. The senior managers who were involved in the workshops are referred to as Employees A, B, and C. They had an overview of the context to which MaKE was applied. Employees A and B were at the workshop for Cycle 1, and Employees A, B and C were present at the workshop for Cycle 2. The three authors were also present at these workshops. The feedback was primarily qualitative in nature.

6.1

Knowledge targets pyramid

This visual tool shows Knowledge Targets (‘Targets’) that the organisation should aim for and is illustrated in Figure 2. The shape of the profile of the pyramid depends on the organisation to which MaKE is applied. The Knowledge Targets are the Knowledge Requirements that are a 'left standing' at the

If retained, was it modified? Not retained Slightly modified Retained and integrated with Linking Overview See above cell

top of the pyramid and are prioritised by a coordination team at a senior management level. This Outcome Visual Tool was retained throughout the implementation of the action research and therefore feedback was obtained from Cycle 1 and 2. The Formal and Informal Direct Feedback from Cycle 1 endorsed the view that the Pyramid is useful in helping to clarify what the organisation should aim for in the context to which MaKE is applied. Employee A recommended incorporating a description of how Targets are generated at level 4 working up from level 1. There was no Indirect Feedback and the Designer concurred with the above on the semantics of the visual tool. Overall the feedback suggested that the Knowledge Targets Pyramid (‘the Pyramid’) was useful and the Designer decided to retain it. The feedback also suggested that the visual tool struck a good balance between clarity and detail, although perhaps only so far as it interlocks with other features of MaKE. In Cycle 2, the Designer introduced the Knowledge Block feature that interlocks with the Pyramid (Section 6.3). It was also suggested that another Outcome Visual Tool that links Knowledge Targets with Knowledge Blocks would be helpful. This led to the production of the Linking Overview (Section 6.4).

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Largest Segments

4. Knowledge Targets (environmental and management issues do not preclude them)

Target 1 (X% significance)

Smallest Segments

Target 2 (Y% significance)

3. Knowledge Requirements (not eliminated by inability to obtain knowledge resources) 2. Prioritised Knowledge Requirements (with percentage importance allocated) 1. All Knowledge Requirements Identified

Figure 2: Knowledge targets pyramid

6.2

Knowledge Tree

The Knowledge Tree was an Outcome Visual Tool that derives from SolSkeme and was used in Cycle 1. On the tree are noted key knowledge resources, manipulation and management activities, and environmental influences identified as required to achieve the Targets. The Knowledge Tree was designed to provide a summary of these features for all the Targets. The tree is a pictorial backdrop providing an image of the organisation/context as a living organism effected by and affecting its environment (Figure 3). The Formal and Informal Direct Feedback from Cycle 1 suggested that it helped focus thinking on the key knowledge resources, manipulation/managerial activities and environmental influences. Employee B

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suggested the use of measurements as part of the tool. There was concern as to how the visual tool fitted with the rest of MaKE and, in terms of the visual tool dilemma, it erred on the side of not having sufficient detail and not being clearly enough linked to other components of MaKE. There was no Indirect Feedback although on reflection the Designer had reservations about its usefulness. In summary, the Designer concluded that although the Knowledge Tree provides a rich descriptive backdrop for information, not enough information could be presented on it and it only loosely integrated with the Knowledge Targets. Therefore the Designer decided to discard the Knowledge Tree for Cycle 2.

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Key Environmental Influences

Key Managerial Influences

Key Manipulation Activities

Key Knowledge Resources

Figure 3: The knowledge tree

6.3

Knowledge block

The Knowledge Block was created between Cycle 1 and Cycle 2. This feature replaced the Knowledge Tree. A simplified version of a Knowledge Block is illustrated in Figure 4. Unlike the Knowledge Tree, a Knowledge Block is completed for each Target. The idea is to give a detailed breakdown of knowledge resources, manipulation/management activities and environmental influences identified as effecting the achievement of the Target. In the second column each category is broken down into sub-categories that derive from another level of the Three-Fold Framework (Holsapple and Joshi, 2001). In the fourth column suitable measures and indicators for each resource or activity are selected to measure progress in carrying out the activities. Unlike the Knowledge Tree the Knowledge Block is more closely linked with the Pyramid and is intended

to conjure up the image of a 'block' that helps 'prop up' the Targets in the Pyramid. There was no Formal Direct Feedback or Indirect Feedback on the Knowledge Block in Cycle 2. However, the Informal Direct Feedback was that the level of detail contained within the Knowledge Blocks and the use of measurements were very helpful. Therefore, in terms of the visual dilemma it was deemed more useful and helpful to participants than the Knowledge Tree. The Designer reflected that the Knowledge Blocks integrated better with the Pyramid than the Knowledge Tree. Employee B and C suggested that an Outcome Visual Tool that summarises the link between the Targets and the detail in the Knowledge Blocks would also help strike the right balance between detail and clarity. This led to the creation of the Linking Overview.

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Knowledge Target: TARGET X Category

Sub category

Resource, Activity or Influence

Measure / Indicator

Knowledge Resources Manipulation Activities Management Activities / Influences Environmental Influences

-

Figure 4: Knowledge Block

6.4

Linking overview

The Linking Overview provides a summary of Knowledge Targets and an indication of the types of actions identified to improve KM in the

context to which MaKE is applied (Figure 5). It cross-refers to Knowledge Blocks that relate to each Target.

Summary of Knowledge Targets and actions needed to improve management of [context] (from [Date]) Horizontal width indicates relative priority of Targets

Knowledge Targets

Vertical distance indicates the relative number of actions needed to try to achieve Target

TARGET 1 (1: 15%)

TARGET 2 (2: 14.8%)

1-1 1-2

2 -1 2 -2

1-5

1-5

1-6 3-5

1-6

TARGET 3 (3: 13.5%)

3 -3

3 -5

References for actions to help achieve Targets which cross refer to Knowledge Blocks Key of Categories of Actions People Process Computing

Figure 5: Linking Overview Figure 5 illustrates a version of the Linking Overview created and presented during the research. In a way the Linking Overview fulfils the function the Knowledge Tree used to perform but now does this by providing a bridge between the Pyramid and Knowledge Blocks. The participants chose the categories of actions (people, process and computing systems) but other categories may be appropriate for other organisations. It was created as a visual tool to help present the outcomes of MaKE although it is untested and may be a visual tool more suited to the organisation for which it was made than for others.

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7. Conclusion Visual tools are widely used in KM and IS for different purposes. However in KM many, although helpful, are often conceptual in nature and need to be developed, applied in practice and refined. Visual tools are normally used to aid communication. However, there is a dilemma that often tends to arise in the use of them. This is that in using visual tools complex phenomena may be simplified at the expense of important detail and consequently readers of the tools may be misled. The findings of the research indicate that there are various things designers of KM

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methods/frameworks need to address when designing visual tools for users in industry. Visual tools used for presenting outcomes of KM work need to aid communication in terms of the purpose(s) for which they are designed and should be integrated well with other parts of the KM method. There is also a need to strike a balance between the need for simplicity and clarity with sufficient detail. It is also necessary not to use visually rich tools at the expense of practical value. Reflecting on the feedback on the Outcome Visual Tools of MaKE as a whole one can conclude that if the above is done, practitioners can regard visual tools as very helpful for understanding and communicating relatively complex phenomena. Within the context of the development of MaKE the Knowledge Targets Pyramid, Knowledge Block, and the Linking Overview do this more effectively than the Knowledge Tree. Note about MaKE, funding and authorship MaKE stands for 'Manage Knowledge Effectively', a KM method designed by the primary author of the paper, Peter Sharp. He wishes to acknowledge that the acronym is not to be confused with a similar acronym which is described in Winfield, M. J., Basden, A., and Cresswell, I. (1996), Knowledge Elicitation Using a Multi-Modal Approach, World Futures, Vol. 47, pp.93-101. Alan Eardley and Hanifa Shah were supervisors in the research and the primary author was provided with scholarship funding by the School of Computing, Staffordshire University.

References Avison, D.E. and Fitzgerald, G.(1997) Information Systems Development: Methodologies, Techniques and Tools,(Second Edition), Information Systems Series, McGraw Hill Companies: ISBN: 0-07-709233-3. Booch, G., Jacobson, I. and Rumbaugh, J.(1999) The Unified Modelling Language Referencing Manual - UML; AddisonWesley, Addison Wesley Longman, Inc, Reading, UK: ISBN: 0 201 30998 x. Checkland, P. and Scholes, J. (2000) Soft Systems Methodology in Action (Includes a 30-year retrospective)(Reprint), John Wiley & Sons, Ltd: ISBN: 0471 986054. Choo, C.W. (2001) Summary of "The Knowing Organisation: How Organisations Use

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Information To Construct Meaning, Create Knowledge, and Make Decisions", Oxford University Press. [http://choo.fis.utoronto.ca/FIS/KO/KO.htm l#contents, 23rd February, 2001] Doyle, J.R. (1991)"Problems With Strategic Information Systems Frameworks.", European Journal of Information Systems (1991) 1(4), p.273-280. Edvinsson, L. and Malone, M.S. (1997) Intellectual Capital: The Proven Way to Establish Your Company's Real Value By Measuring Its Hidden Brainpower; HarperBusiness, ISBN: 0 7499 17 67 9 (hb). Holsapple, C.W. and Joshi, K.D. (2001) Knowledge Management: A Three Fold Framework, The Information Society, 18(1), p.47-64. Kusonoki, K., Nonaka, I. and Nagata, A. (1998) "Organisational Capabilities in Product Development of Japanese Firms: A Conceptual Framework and Empirical Findings", Organisational Science: Journal of the Institute of Management Sciences, 9, issue 6, November/December. Leonard-Barton, D.(1995) Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation, Harvard Business School: ISBN, 0 87584 612 2. Liu, K.(2000) Semiotics in Information Systems Engineering; Cambridge University Press: ISBN: 0 521 59335 2. Remenyi, D., Money, A., Price, D. and Bannister, F. (2002) The Creation of Knowledge Through Case Study Research, Proceedings of Third European Conference on Knowledge Management (3rd ECKM), Trinity College, Dublin, Ireland, 24th - 25th September 2002, MCIL, Reading, UK, 575 - 585. Sharp, P.J. (2002a) "MaKE - 'Manage Knowledge Effectively' - a Method for Prioritising Knowledge Requirements as Part of Information Systems Development Strategy", Seminar Presentation, Staffordshire University, 4th December 2002. Sharp, P.J. (2002b) "SolSkeme - A Scheme for Managing Knowledge in Organisations." Proceedings of Third European Conference on Knowledge Management (3rd ECKM), Trinity College, Dublin, Ireland, 24th - 25th September 2002, MCIL, Reading, UK, 609 - 617.

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Knowledge Networking: A Strategy to Improve Workplace Health & Safety Knowledge Transfer Mario Roy, Robert Parent and Lise Desmarais Université de Sherbrooke, Quebec, Canada [email protected] [email protected] [email protected] Abstract: This article proposes a Knowledge Networking approach to the development of Workplace Health & Safety Knowledge in order to overcome the limits and obstacles associated with the more traditional linear model of Knowledge Transfer in organisations. The province of Québec has developed a Network approach to managing workplace health and safety that is highly regarded by health & safety practitioners and researchers throughout Canada. Its research arm, the Robert Sauvé Research Institute on Workplace Health & Safety (IRSST) also uses a Knowledge Network approach to guide its research agenda. The success of those network initiatives has led the Eastern Canada Research Consortium on Workplace Health & Safety to create a Knowledge Transfer Research Laboratory (KTLab) to support research on the transfer of WHS best practices develop in Québec and elsewhere to Atlantic Canada using a networking approach. Keywords: Knowledge Transfer, Knowledge Networks, Virtual Team, Workplace Health and Safety, Information Technology.

1. Introduction How is new knowledge (i.e. research findings) about workplace health and safety transferred from the producer of that new knowledge to users of that knowledge? What are the factors that facilitate or impede health and safety knowledge transfer in and between organisations? How does knowledge about health and safety prevention gained in one culture get transferred to another culture? How does such knowledge developed in an industrialised setting transfer to a semi-rural or rural setting? How do we measure health and safety knowledge transfer? These are some of the questions the Knowledge Transfer Research Laboratory of the Eastern Canada Consortium on Workplace Health and Safety was created to address over the course of a five-year research project. Our investigation involves different levels of analysis, different theoretical perspectives and the use of different methodologies. We began our investigation by looking at what is known about knowledge transfer between individuals and organisations, followed by what is known about health and safety knowledge transfer between individuals and organisations and finally, we will identify important pieces of information needed to develop models and fill gaps in our understanding of this important organisational activity.

2. The knowledge transfer process The ability to transfer knowledge from one organisational unit to another or from one organisation to another has been identified as a major contributor to organisational performance in many studies (Epple, Argote, & Murphy, 1996; Galbraith, 1990; Baum & Ingram, 1998; Darr, Argote, & Epple, 1995; Argote, Ingram, Levine & Moreland 2000; Goh,

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2002; Dougherty, 1999). While most studies agree on the benefits of knowledge transfer in general, the effectiveness of knowledge transfer varies considerably among and between organisations (Argote, 1999; Szylanski, 1996). At its core the study of knowledge transfer is concerned with the process of moving useful information from one individual to another. It’s not surprising that most of the literature on knowledge transfer has its roots in the field of psychology and predates the study of knowledge transfer in organisations by several decades (Argote, Ingram, Levine, & Moreland, 2000). Early models of organisational knowledge transfer looked at knowledge as if it was an object that could be passed on from the creator to a translator who would adapt it in order to transmit the information to the user (Dissanayake, 1986). Within this paradigm, the user is viewed as a passive actor and the context within which the transfer occurs is completely ignored. This model implies a hierarchical top down relationship between the generator of knowledge who holds the resource (knowledge) and the user who is locked in a dependency stance (Roling, 1992; Boggs, 1992). In social sciences, this view tends to be even more pernicious because subjects can be assimilated to variables and loose their quality of actors on social reality. Many reasons can be advanced to explain why knowledge transfer is so difficult within this paradigm. Some of these are related to the research itself, the way it is conducted and communicated to others. Other reasons are related to blockages and obstacles that can be found in organisations themselves. Let us first consider the relationship between the

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researcher and the practitioner; a relationship Knowledge Producers (Researchers)

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that is often nonexistent.

Translators

Knowledge Users (Practioners)

Figure 1: Linear Model of Knowledge Transfer Research findings are typically communicated by specialists to a select group of peers who are interested by the subject matter, and who have the necessary expertise and knowledge to understand the jargon of the authors. Unfortunately, the research they produce provides answers to questions that were not necessarily posed by practitioners and managers, leaving unanswered most of the questions concerning intervention and action in the real world.

divergent ways in which the two groups consider knowledge. Their concerns, values, interests and worldviews are different. Most theorists lack the practical knowledge of the field and many practitioners lack the theoretical support to frame their action. Argyris (1996) points out the difficulties and flaws related to the use of traditional empirical research in the development of what he called actionable knowledge. Table 1 below describes some of the researchers' and practitioners' divergent views on knowledge.

This gap between producers and users of knowledge can be partly explained by the Table 1: Divergent views of knowledge Researchers

Concerns and interests

Attitude

Problem formulation

Practitioners Reduce uncertainty Discover scientific findings Solve current problems immediately Describe and explain phenomena Gain organisational influence Develop valid and testable models Improve practices Focus on publication in top journals Focus on bottom line Normative stand favoring what seems Neutral stand favoring what seems to to work be objective Compare knowledge with Compare knowledge with literature experience Multiple variables with systemic Few variables with causal relationship interactions Preference for objective, measurable Preference for subjective and data gathered in a standardised way experiential data gathered informally

Irwin and More (1991) proposed that we rely on specialists at organisational interfaces like "boundary spanners" or "linkage champions" to close the gap between providers and users of knowledge and technologies. Hargadon (1998) referred to them as “knowledge brokers”. These specialists interact with "gatekeepers" who screen information at the organisational border and select only the knowledge and technologies they consider useful to their organisation. Gatekeepers are informal leaders who play a determinant role in building norms within their peer group. McCormick (1990) showed that doctors look at their informal leaders to chose new practices because they cannot spend more time trying to stay up to date than practicing their profession. This view is still well alive despite numerous failures that were recorded with its use. Recent models insist on the fact that the relationship between social systems that produce and use knowledge is not linear but circular. Hutchison and Huberman (1993) who

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conducted a lot of research on the transfer of knowledge in education, consider that users of knowledge are active problem solvers and generators of their own knowledge base instead of merely passive receptacles of information and expertise. Any knowledge is necessarily a product of cognitive processes and is linked to past learning. Transferring knowledge implies much more than merely acknowledging the existence of new information. The creation and diffusion of true findings do not imply their adoption. For example, everybody knows that smoking has dangerous effects on health; however, this knowledge is not strong enough to stop many people from smoking. Another thousand findings on health impairment related to smoking will not make any difference. The challenge here is not the transfer of information, but the change of habit and the adoption of new behaviours. Even in the field of the transfer of technology, the real issue is

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known for a long time not to be a technological but a human one (Bilynsky, 1990). The process by which knowledge is transferred can be divided into six stages: generation, transformation, diffusion, reception, adoption and utilisation (Roy, Guindon et Fortier, 1995). These stages are not linear and iterations from one stage to the other are necessary to go from an initial idea to its application in the real world. The interaction between producers and users during each stage however will have a determining effect on the utilisation of knowledge afterward. The participation of users at every phases of the knowledge development process has been identified as a key factor for its subsequent adoption (Johnston and Leenders, 1990; Irwin and More, 1991; Frambach, 1993). When users are involved from the beginning in a research project they are in better position to be interested by the end results. Informal communication networks are at the heart of the knowledge diffusion process; it is through them that peers stabilise behaviours and create group norms that will ultimately favor or hinder the adoption of knowledge (Havelock, 1986b; Henault, 1992). Openness to new knowledge (reception) is much easier when users need it. Understanding users need and providing information when the timing is appropriate is of prime importance and cannot be ignored by researchers (Cavanaugh, 1990; Datta, 1993). The adoption and utilisation of new knowledge by a group or a society often means the rejection of past practices, which may also impact on current political, economical or cultural equilibrium in the social system. The legitimacy of a new knowledge is then validated according to the values, the beliefs and the culture of potential users (Roling, 1992). All these factors have to be taken into consideration if one wants to ease the process of generation, diffusion and utilisation of knowledge within target groups. Knowledge does not exist without the context in which it is used. In other words, we view knowledge less as a product or thing and more as a process used by a group of individuals to make sense of their world. In this context we define knowledge as “an organised representation of reality held to be true either based on experimentation, experience, practice, science or beliefs”. Knowledge is then considered as the byproduct of interactions occurring between the actors trying to appreciate, name and act

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Mario Roy, Robert Parent and Lise Desmarais

on reality, as they understand it. Practitioners, researchers and target groups are working together at every step of the process to produce knowledge that can be truly usable in practice. While the linear model was used in the past to illustrate the knowledge transfer process, we suggest the use of the network model to convey the idea that sharing information, points of view and understanding is the root of knowledge creation in societies. The greater the number of participants and level of activity around a specific subject in a particular network the better the chances of the knowledge created by that network has of being adopted. Knowledge networking has been defined by Seufert, von Krogh, and Back (1999), as “signifying a number of people, resources and relationships among them, who are assembled in order to accumulate and use knowledge primarily by means of knowledge creation and tranfer processes, for the purpose of creating value.” In Canada, the Canadian Institutes of Health Research (CIHR) has popularised the term knowledge translation (KT) to refer to the complex set of interactions between producers of new health related knowledge and users of that new knowledge. In the context of the CIHR (2003), Knowledge Translation is defined as the exchange, synthesis and ethicallysound application of knowledge – within a complex system of interactions among researchers and users – to accelerate the capture of the benefits of research for Canadians through improved health, more effective services and products, and a strengthened health care system. In building its knowledge translation framework the CIHR has reinforced the need for the committed engagement of the full range of knowledge producers and users in developing tailored approaches to accommodate the unique relationships between pairs of sources and users. The field of workplace health and safety research has remained underdeveloped in most of Canada, particularly when compared to the situation in European countries such as Sweden, Norway, Germany and France. This gap has been especially serious in Atlantic Canada where, until quite recently, there did not exist a single academic or governmental research unit specialising in workplace health and safety research and there were only minimal and poorly-funded efforts by the region’s provincial workers’ compensation agencies to bring in knowledge from research units operating elsewhere. Broad,

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The Institut de recherche Robert-Sauvé en santé et en sécurité du travail (IRSST) in Montreal, Canada’s largest independent WHS research institute; and The Chaire d’étude en organisation du travail (CEOT) in the Faculty of Business Administration at the Université de Sherbrooke in Sherbrooke, Québec. An additional collaborator in the Consortium is the Québec Network in Work Rehabilitation (Réseau en réadaptation au travail du Québec (RRTQ), which is linked to the Université de Sherbrooke The first activity of the Consortium was to compare the workplace health and safety environment in Québec with that of Newfoundland. As mentioned earlier, in Québec there exists a long established tradition of collaboration and networking around health and safety issues. For example, in 1979 the Québec parliament passed an act establishing the base for a networked approach to managing workplace health and safety.

interdisciplinary and gender-informed research related to rural and remote, resource-based sectors is particularly lacking. It was in the hope of filling this gap that CIHR, in March 2001, funded a ‘community alliance for health research’ team based at Memorial University (SafetyNet). To help in its efforts to improve the situation in Atlantic Canada and enhance interdisciplinary research and Knowledge Translation capacity related to workplace injury, SafetyNet joined up with two partners in 2002 to create the Eastern Canada Research Consortium on Workplace Health and Safety (WHS). It is comprised of the following three partners: The Community Research Alliance for Marine and Coastal Workplace Health and Safety in Atlantic Canada (SafetyNet), funded by CIHR, based at Memorial University in St. John’s and linked to partner organisations and researchers in Newfoundland and Labrador, other parts of Atlantic Canada, Québec and Ontario;

Department of Health and Community Services

Department of Labour Robert-Sauvé Workplace Health and Safety Research Institute (IRSST)

Permanent committee

Board of directors

CSST

regional health divisions (16) And their regional workplace health team

Regional departments (21)

Employer-Worker Safety Associations (12 sectors)

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• prevention/inspection • compensation/ rehabilitation

Regional consultation tables

CLSC (70) (Local community services centres) •local workplace health team

Companies – Workplace Health and Safety Committee/Representative

Figure 2: The Workplace Health and Safety Network in Quebec Figure 2 illustrates the various components of the network and some of the relationships that it fosters. We can see clear links between all stakeholders of workplace health and safety, including the: Ministry of Labour, WHS Safety Commission, Employer-Employee Representatives, Healthcare Professionals, the Research Community and a variety of other government agencies. All of these organisations are involved to some degree in

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the prevention and management of workplace health and safety. Requests for research in health and safety can come from any part of the network, although in 1995 the IRSST decided to adopt a knowledge network approach to research that requires most research initiatives to involve all stakeholders of a particular research issue in the entire research protocol from the outset of the project. In this way the IRSST increased the

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likelihood that the research it produces will ultimately be utilised. Prior to 1995 much of the research was done from the researchers’ perspective who then tried to push the research results onto the practitioner community. After 1995 the knowledge network began exerting a pull influence on the research agenda, which meant that the end users became increasingly interested in the findings of the research projects. Along with that early involvement has come a significant increase in the knowledge transfer of research results. In Newfoundland & Labrador, on the other hand, there is no such tradition of networking and collaboration although serious signs of a willingness to collaborate are becoming increasingly evident. The major difference between the WHS networks in Québec and Newfoundland & Labrador centre around the strong presence of employer representatives in Québec and very little or no presence in Newfoundland and Labrador. For example, there are 12 joint sector associations in Québec and only two or thee similar associations in Newfoundland and Labrador. There is also no equivalent research association to the IRSST in Newfoundland and Labrador as well as no links to local workplace health teams. Determining the type of WHS Knowledge Network required in Newfoundland and Labrador will constitute the main focus of

the work of the Consortium in the months ahead. The Consortium is designed to foster the rapid transfer of WHS research results from the IRSST to Atlantic Canadian researchers, community partners and workplaces. It is in the process of identifying the best practices for KT developed in Québec, with its long established tradition of university-government-workplace collaboration, adapting these best practices for rural and remote, resource-dependent environments and use action-research methods to test these KT practices and refine them. Working together, the researchers in the Consortium will develop new models for the analysis and prevention of workplace injuries, disabilities and diseases and apply these methods to a broader range of Atlantic Canada’s economic sectors than those currently being studied by SafetyNet. The Consortium combines the capacities and the needs of the partners into a Knowledge Network of producers and users of new workplace healthy and safety knowledge and creates an environment of shared ‘virtual’ structures to enhance capacity in Atlantic Canada. Figure 3 below shows the initial knowledge-sharing network developed by the Consortium.

Government Agencies

IRSST*

CEOT** Union and Management

SAFETY NET Organization

* IRSST : Institut de recherche Robert Sauvé en santé et en sécurité du travail **CÉOT : Chaire d’étude en organisation du travail

Figure 3: Eastern Canada Consortium on Workplace Health and Safety In contrast to earlier linear models of knowledge-transfer where knowledge was viewed as unidirectional, top down, this networked model illustrates clearly the intent of Consortium partners to fully and equally

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involve both producers and users of new knowledge at every level of a knowledgebased view of workplace health and safety research. We believe the Knowledge Network model is exceptionally well suited to work of

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the Consortium. By fostering open and frequent communications among network members the Consortium hopes to create a knowledge-sharing environment that will go a long way in improving the health and safety of our fellow citizens. The work of the Consortium will also benefit WHS research and injury prevention in Canada as a whole by transferring to English Canada a body of research and a set of innovative methodologies that have been largely confined to French-speaking Québec. IRSST has produced a substantial volume of important research reports and several innovative prevention tools relevant to resource-based occupations but most of these are not disseminated in English and are not widely known to scholars, decision-makers and workplace partners outside Québec.

2.1 Specific consortium objectives To add new, interdisciplinary research and KT capacity related to workplace injury and permanent structures for ongoing capacity enhancement linking the participating organisations; To build a network of research and community WHS collaborators in Atlantic Canada linked to the three Québec research organisations with their established social capital of community and institutional connections, thus creating a truly Eastern Canadian regional organisation; To enhance the capacity of researchers and decision makers in Atlantic Canada to work together more effectively in the field of WHS by transferring models and techniques developed in Québec and adapting them to Atlantic Canadian contexts; To combine the KT expertise of the two Quebec partners with the emerging skills and partnerships of SafetyNet to develop methods for knowledge translation from researchers to industry and workplaces— methods specifically adapted to rural and remote locations, resource-based industries and small enterprises; To develop new, gender-informed methods for the analysis, prevention, treatment and rehabilitation of occupational accidents and illnesses, methods specifically designed for rural and remote, resource-based industries and small enterprises;

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To apply these methods to new problems and sectors, by developing collaborative pilot projects drawing on the skills and resources of Consortium members including many who will be newly recruited and/or retrained collaborators of SafetyNet, and by securing additional grant funding to pursue these projects; To bring to English-speaking Canada a body of research results, methods and tools in WHS and KT largely unknown outside Québec, by translating and transferring the work of the IRSST, CEOT and RRTQ.

3. Knowledge translation research laboratory To help conduct and direct research in Knowledge Transfer the Consortium has created the WHS Knowledge Translation Research Laboratory, housed at the Université de Sherbrooke but also operating as a virtual, multi-site laboratory with ongoing electronic and in-person participation by researchers and staff from all partner organisations. The overall mandate of the KT Research Laboratory is to excel, according to internationally accepted scientific standards, in research on the translation of new knowledge into improved methods of prevention and management in WHS. The specific objectives of the KT Research Laboratory will be: To increase understanding of the theory and practice of KT as it applies to WHS; To develop and evaluate new KT tools and strategies fitting the objectives of the Consortium, building on the strength of existing knowledge such as that of the IRSST; To integrate an understanding of KT principles and practices into the training and continuing education of WHS professionals.

4. Virtual teaming and collaboration tools Building on the belief that knowledge is best shared, and learning most effectively generated when people sharing common interests work together to solve problems, the KT laboratory has developed a virtual office using new Information Technology tools (i.e. Sametime, Quick place) to support knowledgesharing and distance collaboration for members of the Consortium. It contains general information on all facets of the Consortium's work as well as specific, secure, team related information pertaining to the

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multitude of projects the Consortium is involved in. Teams can easily use or create a workspace to help members communicate with one another, share information and resources, insure follow-up to meetings and activities and deliver projects on time. The only requirement for members to access the Lab support system is an Internet connection. The intranet site makes it possible to organise video conferences between participants from their computer desktop. Through this technology the Consortium hopes to create a “network” environment in which researchers are encouraged to involve potential users of the research findings (new knowledge) at every stage of the research process. We also intend to encourage the creation of workplace health and safety networks throughout Eastern Canada to encourage what Kogut and Zander (1996) refer to as the “shared identity” of network members. This “shared identity” to a network according to Kogut and Zander (1996) establishes tacit and explicit rules of coordination through which knowledge is most effectively generated combined, and transferred by individuals who identify with the larger network. Although Kogut and Zander applied the concept of “shared identity” to firms, we believe, as does Dyer and Nobeoka (2000) who’ve studied the Toyota Knowledge– Sharing Network extensively, that “shared identity” applies equally well to networks to which members are strongly linked through a common purpose. A network that succeeds at creating a “shared identity” amongst its members increases the opportunity for knowledge to be transferred. The virtual site is intended to support that “shared identity” by improving production, diffusion and utilisation of knowledge in the area of workplace health and safety. All present and future partners in the Consortium will be trained in the use of the technology. The challenge is to create a network, process and environment that can induce continuous sharing and learning for all present and future Consortium partners. The KT Lab will also help SafetyNet refine the IRSST best practices to optimise them for use in Newfoundland and Labrador, particularly for workplaces with male and female workers in the workplaces that characterise much of the Atlantic Canadian economy and some parts of Quebec. Careful attention will be paid to the ways in which sectors, firms and communities in Newfoundland and Labrador (and Atlantic Canada as a whole) differ administratively,

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organisationally and culturally counterparts in Québec.

from

their

The Eastern Canada Consortium on Workplace Health and Safety is a multi-site, bilingual, multi-province network that has been designed to make a significant contribution to the ability of researchers in the region to do cutting-edge, interdisciplinary work on the analysis and prevention of injuries in the workplace and to get the results of that research into the hands of decision makers and workplace users as soon after the research as possible. The measure of effectiveness of the knowledge transfer activities included in this research will reside in the changes in knowledge or changes in performance of both producers and users of that knowledge.

References Argote, L. (1999) Organisational learning: Creating, retaining, and transferring knowledge, Norwell, MA: Kluwer. Argote, L., Ingram, P., Levine, J. & Moreland, R. (2000) “Knowledge transfer in organisations: learning from the experience of others”, Organisational Behaviour and Human Decision Processes, vol.82, no.1, pp.1-8. Argyris, Chris.(1996) "Actionable Knowledge: Design Causality in the Service of Consequential Theory", The Journal of applied behavioural science, vol. 32, no 4, p. 390-406. Baum, J. A. C., & Ingram, P. (1998). “Survivalenhancing learning in the Manhattan hotel industry, 1898-1980”, Management Science, 44, 996-1016. Boggs, James P. (1992) "Implicit Models of Social Knowledge Use", Knowledge: Creation, Diffusion, Utilisation, vol. 14, no 1, pp. 29-62. Bylinsky, Gene. (1990) "Turning R& D into real products", Fortune, Vol. 122, no 1, pp 7277. Cavanaugh, Betty. (1990) "Effective Dissemination of energy-related information", American Psychologist, vol. 45, no 10, pp. 1109-1117. CIHR, (2003) Knowledge Translation Framework [on line] http://www.cihrirsc.gc.ca/about_cihr/organisation/knowle dge_translation/index_e.shtml Darr, E., Argote, L., & Epple, D.(1995) “The acquisition, transfer and depreciation of knowledge in service organisations: Productivity in franchises”, Management Science, 41, 1750-1762.

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Datta, Lois Ellin. (1993) “A Grass-Roots Perspective on Legislating Knowledge Utilisation: The Seventh Annual Howard Davis Memorial Lecture, April 1992”, Knowledge: Creation, Diffusion, Utilisation, vol. 14, no 3, p. 291-304. Dissanayake,W. (1986) “Communication models and knowledge generation, dissemination and utilisation activities: a historical survey”, In Knowledge Generation, Exchange and Utilisation, ed. George M. Beal, Wimal Dissanayake and Suniye Konoshima, Westview Press, pp. 61-76. Dougherty, V. (1999) “Knowledge is about people, not databases.” Industrial and Commercial Training, 31(7), 262-266. Dyer, J. H., & Nobeoka, K. (2000) “Creating and Managing a High Performance Knowledge-Sharing Network: The Toyota Case”, Strategic Management Journal, 21: 345-367. Epple, D., Argote, L., & Murphy, K. (1996) “An empirical investigation of the micro structure of knowledge acquisition and transfer through learning by doing”, Operations Research, 44, 77-86. Frambach, Ruud T. (1993) "An integrated model of organisational adoption and diffusion of innovations", European Journal of Marketing, vol. 27, no 5. pp. 22-41. Galbraith, C. S. (1990) “Transferring core manufacturing technologies in high technology firms”, California Management Review, vol.32. no. 4, 56-70. Hargadon, A. B. (1998) “Firms as knowledge brokers: Lessons in pursuing continuous innovation”, California Mangement Review, vol.40, no.3, pp. 209. Havelock, Ronald G. (1986b) "Modeling the Knowledge System", In Knowledge Generation, Exchange and Utilisation, ed. George M. Beal, Wimal Dissanayake and Suniye Konoshima, Westview Press, pp. 77-104. Henault, Georges. (1992) "The Dissemination of Research Results in Southeast Asia", Canadian Journal of Development Studies, vol. 13, no.1, pp. 39-56. Hutchison, J., and M. Huberman. (1993) "Knowledge Dissemination and Use in Science and Mathematics Education: A Literature Review", National Science Foundation, NSF-93-75. Irwin, Harry, et Elisabeth More. (1991) "Technology Transfer and Communication: Lessons from Silicon Valley, Route 128, Carolina's Research Triangle and Hi-Tech Texas", Journal of Information Science Principles & Practice, vol. 17, no 5, pp. 273-280.

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Johnston, David A., et Michel R. Leenders. (1990) "The Diffusion of Innovation Within Multi-Unit Firms", International Journal of Operations & Production Management, vol. 10, no. 5, p. 15-24. Goh, S.C. (2002) Managing effective knowledge transfer : an integrative framework and some practice implications. Journal of Knowledge Management, 6(1), 23-30. Kogut, B. and U. Zander (1996) “What do firms do? Coordination, identity, and learning” Organisation Science, vol. 7, no.5, pp. 502-518. McCorrmick, Brian. (1990) "Can Research Change the Way MDs Practice Medicine?", Hospitals, vol. 64, no 19 pp. 32-38. Roling, Niels G. (1992) "The Emergence of Knowledge Systems Thinking: A Changing Perception of Relationships among Innovation, Knowledge Process and Configuration", Knowledge and Policy, vol. 5, no. 1, p. 42-64. Roy M., Guindon, J.C. et Fortier, L. (1995) Transfert de connaissances- revue de littérature et proposition d’un modèle, Collection Études et recherches. IRSST R099. 53 p. Seufert, A., von Krogh, G., Bach, A., (1999) Journal of Knowledge Management. Kempston: Vol. 3, Iss. 3; p. 180 Szylanski, G. (1996) “Exploring internal stickiness: Impediments to the transfer of best practice within the firm”, Strategic Management Journal, 17, 27-43.

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Facilitating Organisational Sustainability Through Expert Investment Systems Carol Royal and Farhad Daneshgar University of New South Wales, Sydney, Australia [email protected] [email protected] Loretta O’Donnell Macquarie University, Sydney, Australia [email protected] Abstract: This paper uses literature from the fields of organisational sustainability and human capital, which have demonstrated a link between sustainable human capital and the financial performance of the firm, to argue that securities analysts need to be able to systematically analyse human capital in order to provide transparent and well-informed investment recommendations. It is the function of securities analysts to attempt to predict the future financial performance of firms within an industry sector. Models for this analysis have traditionally been heavily quantitative, relying on mathematical models of future earnings forecasts, based on published annual financial statements from listed companies. Securities analysts’ quantitative modeling methods are directly underpinned by qualifications and certification processes that encourage demonstrated skills in quantitative methods. The authors provide an opportunity for securities analysts to systematically gain insights on the human capital of firms using a future expert system, called Human Capital Analyser (HCA), whose general characteristics are also outlined in the conclusion of this article. This expert system will help bridge the knowledge gap in the work of securities analysts. Keywords: knowledge representation; human capital analysis; expert systems; finance industry; securities analysts.

1. The value of organisational sustainability Generations of investors, managers and fund managers have asked the deceptively simple question, “How can we predict the future value of the firm?” Historically, the answers have been found in complex financial modeling, econometric forecasts and statistical analysis. Yet, there is a trend towards more qualitative analysis of the current and future value of the firm. Organisational sustainability research pioneers such as Dunphy, Griffiths and Benn (2003) use qualitative analysis of firms to argue for indices of financial, environmental and human sustainability. They provide a case for the adoption of corporate sustainability principles in every element of the organisation. Dunphy et. al. (2003:12) state “an organisation is sustainable [when] its stakeholders continue to support it”. Stakeholders include financiers, employees and the wider society and environment, which form the context in which the firm operates. Dunphy et. al. propose the adoption of an environmental sustainability index, in conjunction with a human sustainability index, which would measure the progress of the organisation along a potential six steps to genuine sustainability. The authors of this paper believe that this concept of systematically analysing environmental and human sustainability can be taken one step further, and might be a valuable addition to the methodology used by securities analysts as they value firms for investment purposes.

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The work of De Geus (1999) on the lifespan of companies, Collins and Porras (2000) on visionary organisations, Elkington (2001) on the triple bottom line, Senge (2000), Beer and Nohria (2000) on multiple objective functions, Drucker (2001) on the rise of the new social entrepreneurship, Watson Wyatt (2002) on human capital indices and Collins (2001) on companies which are “built to last”, has a common sub-theme: that organisational sustainability in general, and human capital sustainability in particular, can be seen as potential indicators of the future performance of the firm. This body of literature, and additional research by the authors of this paper, leads to the following proposition: As the sustainability of human capital is likely to influence the future financial performance of the firm, it needs to be systematically analysed by the financial markets. This would be a complementary process to more traditional financial measures. To systematically analyse the sustainability of human capital in a firm within its industry sector requires a level of objectivity, and an expert system can provide objectivity. This paper presents the outline of a future expert system, titled Human Capital Analyser (HCA), based on principles of organisational and human capital sustainability. This expert system bridges a gap between otherwise disparate fields of organisational sustainability and corporate finance. The Human Capital Analyser does not, at this stage, deal with environmental analysis, as further research

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needs to be done to ensure appropriate frameworks and metrics.

1.1

Evidence for the financial impact of sustainable human capital

Of specific interest to the organisational sustainability debate is the Watson Wyatt Worldwide Research (2002), which indicates superior human capital is a leading, rather than lagging, indicator of future financial success. Surveys were administered in 1999 and 2001 to fifty one organisations in North America and Europe. The organisations wereplaced into three groups based on their overall Human Capital Index (HCI) scores. The HCI was derived from matching survey data to market value, returns to shareholders and Tobin’s Q to create an index of human capital. Using the organisations’ five-year total returns to shareholders, the researchers found that organisations with a low HCI averaged a 21% five-year return, those with a medium HCI averaged 39% and those with a high HCI averaged 64%. This analysis noted that human capital can be managed and exploited to increase shareholder value. Supporting this research are Bassi, Lev, Low, McMurrer, & Sissfield (2001) who found that non-financial insights make up a large proportion of investment decisions. In their survey of 275 active US institutional investors on their basis for investment, approximately 35% of investment decisions were reported as based on non-financial data, of which over half is related to human resources issues, while other non-financial data includes marketing, strategy and quality. Over 60% indicate that between 20-50% of decisions are non financial. Bassi, et. al. (2001: 348) note that, although “the quality of the business plan or strategy is important…The focus is on action.” Therefore, securities analysts need to distinguish and to report on the capability of the management team to execute strategy. The future HCA, as an expert system, can assist in a more systematic analysis of the rhetoric versus the reality of the human capital of listed firms. This helps to make insights on human capital relatively more rigorous and transparent. Further evidence of the connection between sustainable human capital and the financial value of the firm is seen in Hewitt and Associates examination of employee engagement and commitment to create an index of Best Employers, 2003. They found in their Australian data that Best Employers experienced 13% revenue growth between

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2000 and 2002 compared with 7% for other companies. Average profit growth was 21% in the same period (2000-2002) for Best Employer companies compared with negative 44% for other, non-Best Employer, companies in the survey. This study is part of a wider study that covers over 25 countries, 350 companies and 125,000 employees. Boston Consulting Group researched one hundred German companies, covering ten industrial sectors over a seven year period from 1987-1994, (Bilmes, Wetzker, and Xhonneux (1997). Companies which produced a greater total shareholder return than their competitors also scored highly on such measures as: expenditure per employee, contribution of employees as reflected in mission statements, promotion opportunities and flexible work hours, among other evidence of sustainable human capital practices. Collins’ (2001) “visionary” companies ploughed a greater percentage of year’s earnings back into the company, returning less in cash dividends to shareholders. They invested more heavily in management practices and human capital, specifically in training, recruiting and the professional development of staff, and in R&D and property and plant. Visionary companies outperformed their non-visionary counterparts on all key financial measures. Prior to this, Collins and Porras (1994) had analysed eighteen paired comparison visionary companies, and these companies had outperformed the US stock market, by a factor of fifteen at the time of the study. They were six times more successful than comparison companies. Individual leaders, no matter w Another study indicating links between human capital and financial performance is Schuster’s (1986) employee surveys and interviews of 1300 of the largest U.S. industrials and nonindustrials. His aim was to research whether a significant relationship exists between the way in which organisations manage their employees and profitability. His findings included a statistically positive relationship between the use of employee-centred management practices and superior financial performance. An average return on equity of those firms at the time using one or more innovative, sustainable human capital practices was 11% higher than those firms not using any of the practices. In terms of more specific components of sustainable human capital, Ranft and Lord (2000) recognise that strategically significant

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intellectual property, in some cases, rests within individuals, rather than in the firm itself, a potentially important issue for financial markets to incorporate in their analysis. Also, Gupta, Iyer, and Aronson (2000) have noted that knowledge management can have an impact on the efficiency and the performance of the firm. The American Management Association 1996 study indicated a strong correlation between increased training budgets and larger profits and productivity flowing from workforce reductions. The study found that organisations performed better when they were strategically well-positioned in the changing environment and pushed the pace of internal organisational change fast enough to match the external pace of change, cited in Dunphy (2000). Without these kinds of insights into the relative sustainability of human capital within firms within an industry sector, the investment analysis process is suboptimal. A major study by Turner and Crawford (1998) of 243 case studies in Australia and New Zealand to determine the capabilities that drive corporate renewal found specific clusters of competencies affect performance, including business technology (operational), market responsiveness (operational), performance management (operational/reshaping), engagement and development of employees (reshaping). Quantitative financial analysis, as typically used by securities analysts, would not be able to distinguish these human capital capabilities. Kotter and Heskett (1992) found that corporate culture has a major effect on corporate performance and, although difficult to change, corporate culture can be made more performance enhancing. O'Reilly and Pfeffer (2000) examine successful companies that use ordinary people to achieve extraordinary results and find that an organisation that has well-articulated values, puts culture first, has a strong alignment and consistency in the people-centred practices that express those values, and where senior management maintain these values, are able to compete very successfully. Dunphy and Stace (2001), provide case studies of companies which improved financial performance as a result of appropriate leadership styles and change management strategies. Cox and Blake (1991), concluded there are six areas where specific human capital practices

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are highly related to organisational performance. Abbott, De Cieri, and Iverson (1997), provide an examination of the dollar cost associated with exit of high performing managerial women. Total costs (direct and indirect) associated with separation, replacement and training of these and new employees are considerable. Researchers such as Royal (2000), Collins (2001), Dunphy (2000), Turner and Crawford (1998), Watson Wyatt Worldwide Research (2002) and Bassi et al. (2001) use rigorous qualitative techniques to provide evidence for their findings on the positive relationship between sophisticated use of human capital and future financial performance of the firm. Typically, few of these of these insights systematically inform the process by which securities analysts calculate earnings forecasts.

2. How do securities analysts analyse listed companies? Securities analysts, on either the sell side or buy side, make investment recommendations in a research report, on a “relative basis comparing a companies’ performance within a sector or industry... It is not limited to financial statements, [and includes] research on the company, industry, product or sector, and public statements by and interviews with executives of the company, its customers and suppliers” (Fernandez 2001). Securities analysts work for a brokerage firm, bank, investment bank and or fund management institution. They draw financial data from published financial accounts, and then create earnings forecasts using financial modeling. The quantitative component of the securities analysts work is underpinned by undergraduate qualifications in finance and business, or in specialised quantitative fields such as engineering or actuarial studies (Royal & Althauser, 2003). Certification of securities analysts in Australia, by the Securities Institute and similar bodies, is centred on a demonstration of highly developed quantitative skills. As the skill sets have been so strong in quantitative areas, a knowledge gap has emerged in terms of analysts’ skills in analysing qualitative data, such as human capital data. More than half of the shares issued by US based companies have become controlled by institutional investors who are becoming increasingly concerned with the evaluation of a firm’s internal performance, (Szarycz, 2001). In

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Australia, as the number of retail investors increases, through compulsory superannuation levies, the investing public is increasingly interested in all elements of firm performance. However, as most corporate websites and brokers reports indicate, the performance measures used are primarily described in quantitative and financial terms, such as Economic Value Added (EVA), Cash Flow Return On Investing (CFROI), other accounting ratios, Balanced Scorecard, Value Based Management (VBM) and Activity Based Costing (ABC). Lev, (2001:17) notes that there is currently intense interest in the intangible assets of a firm, which may include human capital. Many companies do not have systematic ways of either valuing or leveraging intangibles, yet intangibles are fundamental drivers of innovation. The costs of managing and organising human capital within firms has been analysed effectively by Mayo (2002). The authors of this paper argue that the value created by sustainable human capital, rather than the costs of managing and accounting for human capital, is the more compelling instigator for systematic human capital analysis in the financial markets. As noted earlier, the future HCA can be used by securities analysts to systematically access insights into human capital. These insights, together with more traditional financial analysis, provide further transparency into the investment recommendation process.

2.1

Applying human capital analysis

In complex contemporary knowledge-based organisations, it is often difficult to distinguish the causes of sustainable high performance. However, the model presented in Figure 1 does provide a basis for qualitative analysis of the human capital of a firm. It is the basis of the HCA, which can be used by securities analysts to identify emerging patterns in human capital that ultimately affect financial performance and market valuation. With appropriate training and support, a securities analyst may be able to use the HCA to systematically access additional insights into a firm’s human capital. It is worth warning that human capital analysis needs to be carefully applied. Delery (1998) and Harris and Ogbonna (2001) emphasize the complexity of mediating variables between strategic human resource management and performance. The publication of the Watson Wyatt research into the links between

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shareholder value and human resource management has assisted researchers, who still need to be cautious in linking complex variables. Delery (1998) notes that some human resource practices are additive (independent, non overlapping effects on outcomes), some are interactive (depend on other elements in the system) and some may be substitutes for one another. So, securities analysts need to be able to access comprehensive and rigorous data on the subtleties of systems of human capital. Human capital analysis should always be used in conjunction with traditional financial analysis. The HCA, like any expert system, has specific technical and logical requirements. Representation of knowledge within the knowledge base component of the expert system is one major pre-requisite for the development of any expert system. The proposed expert system incorporates an awareness-based knowledge representation and knowledge-sharing tool used to represent and share knowledge that flows within the investment recommendation processes.

3. Closing the skill gap An expert system (ES) is a system that uses human knowledge captured in a computer to solve problems that ordinarily require human expertise (Turban, 2001). These systems imitate reasoning processes experts use to solve specific problems. It is claimed that such systems could function better than any single human expert in making judgments in a specific, usually narrow, area of expertise (referred to as a domain). The writers believe that this possibility may have a significant impact on the task of human capital analysis performed by the securities analysts when making investment decisions on behalf of their clients. In order to clarify the role and importance of the proposed knowledge representation tool within a given context, characteristics of an ES called HCA that can be used by securities analysts for this purpose is highlighted and discussed in this section. The proposed HCA must allow for the following functionalities wherever necessary: Generic reasoning rules that reside in the inference engine component must be able to be broken by the user; in this capacity the expert system will play the role of an 'adviser', Knowledge structures within the knowledge-base component can be restructured by the user,

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Users are degraded gracefully. This is based on the previous observations made by the capital investment experts that are already aware of limitations of the users of the proposed system.

3.1

Expertise of the HCA

Such expertise include the following types of knowledge: Organisational Sustainability Human Capital Sustainability Strategic Human Resource Management Organisational Behaviour Change Management The above knowledge enables securities analysts to make more efficient and effective decisions. The first and third authors of this paper acted as the finance expert for the HCA. These persons possess the following required qualifications as an expert in the area of investment recommendation processes: They are frontrunners of research and practice in human capital analysis with expertise in teaching, researching and consulting in the areas of Organisational Sustainability, Human Capital Sustainability, Strategic Human Resource Management, Organisational Behaviour, Change Management Also, they have already identifiable solutions to the problem of human capital analysis (Royal & O’Donnell, 2002), (Royal, Daneshgar & O’Donnell, 2003) and (Royal and Althauser, 2003). They have explained the solution to a non-expert knowledge engineer (the second author) clearly, and the knowledge engineer has already understood the solution and has structured the knowledge, and created a preliminary version of the knowledge base

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for the proposed HCA, and is shown in the next section.

3.2

Transferring expertise

The objective of the HCA is to transfer knowledge from the human capital analysts (the experts) to a computer system, and then to other securities analysts (nonexperts). This process involves the following four activities: Knowledge Acquisition from experts Knowledge representation Knowledge inference, and Knowledge transfer to the user. Preliminary results for the first activity above has already been presented and published in (Royal, Daneshgar & O’Donnell, 2003). This will lay necessary foundation for the remaining three activities that constitute the authors current research activity in progress. In this article an extension of the first activity above is demonstrated. Such extension focuses on the implementation and design issues related to the knowledge acquisition and representation, and is discussed below.

3.3

A framework for knowledge acquisition:

Knowledge acquisition is the accumulation, transfer, and transformation of problem-solving expertise from experts or documented knowledge sources to a computer program for constructing or expanding the knowledge base (Turban 2001; 411). In this paper a framework is proposed for acquisition and representation of the knowledge of human capital as an important factor in making investment decisions (Daneshgar, 2003). The objective of this framework is to arrive at a set of generic rules as well as domain-specific knowledge structures that constitute the bulk of the knowledge base and inference engine components of the HCA. A graphical demonstration of this framework appears as Figure 1 and is explained in more detail in the next section.

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EXTERNAL INFLUENCES Historical trends Economic environment resources supply & demand for skilled labour Institutional factors, alliances/competitors Product/Market Technological Change Cross cultural factors Costs search recruitment salaries Exogenous variables (unanticipated events)

Organisational Historical Context Future Anticipated Trends

INTERNAL INFLUENCES Employment relations Cultural integration Corporate Governance Costs training & development career systems performance management and reward systems general overhead costs Workforce skills Need to secure commitment Workforce values Insider-Outsider Relations

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Market Valuation

Performance: Financial Human Environmental

Managerial Beliefs & Perceptions

Managerial Strategy

Sustainable people management practices

Figure 1: Human capital drivers of the value of the firm (adapted from Royal, 2000)

4. Deriving the factors for human capital analysis

and external influences are interrelated, but they have not evolved in a linear fashion.

As Figure 1 indicates, the following human capital factors were derived (Royal, 2002:238), as relevant to the expertise provided by human capital analysts. These factors are structured on the basis of their variability and will be weighted on the basis of their importance in the analysis of human capital.

Even though cause and effect are less clear in qualitative models than in mathematical models, the HCA expert system, based on this model, would assist securities analysts to identify emerging patterns in human capital which ultimately affect financial performance and hence market valuation. So, the expert system would allow the securities analyst to access information and insights on themes such as those listed below. As noted earlier, human capital data can act as a lead indicator of future financial performance, so these insights are potentially valuable to securities analysts, their clients and to the finance industry.

The model examines key variables which shape management beliefs and perceptions which then drive the human capital systems, appropriate to the context of the organisation, which help to drive the value of the firm. Internal influences that affect managerial beliefs and perceptions and management strategy include: the state of employment relations, cultural factors, and costs associated with the need to secure commitment of employees (such as reward, performance management, career and development systems) and insider-outsider relations. External influences that affect managerial beliefs and perceptions and management strategy include historical trends, the competitive nature of the economic environment, institutional factors, the nature of the product, technological changes and the costs associated with recruitment. The internal

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Elements of analysis in the HCA: 1. Organisational history/culture 2. Macroeconomic environment 3. Financial data and market trend 4. Stage of competitiveness 5. Labour market conditions Supply/demand for labour Relative costs of search/recruitment Salaries 6. Intellectual Capital

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Product/services Trends 7. Importance of technology 8. Importance of cross-cultural fitness or alignment Macro level: organisational fit with its environment Micro levels: internal alignment with strategy 9. Exposure to external risks/opportunities 10. Employment relations Union activity/industrial relations Cultural integration/alignment with corporate strategy Level of engagement and commitment Relevance of insider-outsider relations eg, customer, supplier, etc. 11. Composition of executive team/board and its alignment with strategy 12. Classification of human capital systems Training, recruiting, career planning within traditional, professional, individual models. Is the above mix appropriate in this organisation? 13. Are managerial beliefs and perceptions consistent with strategy? 14. Overall, are human capital practices designed to execute strategy? Insights from this analysis would be considered by the users of the HCA in addition to traditional forms of financial data analysis.

5. Criteria for an appropriate knowledge representation framework Once the above knowledge is acquired, it must be organised in an application knowledge base for later use. The reason for such a need is that throughout this article, the process of making investment decision is treated as a collaborative process. For example, a client may seek advice from a securities analyst for making some investment decisions. The securities analyst, on the other hand, may request a copy of company profile from various companies before a share purchase is made for that company. This will make client, securities analysts and prospective company actors of the potentially collaborative process that performs investment research for the client. Therefore, in order to effectively manage such collaborative process it would be necessary to provide actors with certain

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degree of automated support that provides required awareness to the actors within the process so that collaboration among these actors are maintained at appropriate levels. Over the years, a variety of knowledge representation frameworks have been developed each serving specific purposes depending on the users’ requirements and system development strategies (Daneshgar, 2003). In search for an appropriate representation tool for the purpose of the proposed HCA system it was primarily noticed that the tool must be programmable using existing hardware, software and communication technologies. Next, the representation tool must be designed so that the facts and other knowledge contained within them can be used in provision of awareness to the actors when and where they are needed for maintaining collaboration among actors. One condition for successful implementation of such awareness provisioning mechanism is the presence of a knowledge representation tool that can represent knowledge about investment decisions in a way that suits both the storage requirements of the Knowledge Base component, as well as the reasoning requirements of the Inference Engine for the proposed HCA. We may summarise this section by concluding that the collaborativeness of the investment decisions implies that: 1. Various actors within the process rely on services provided by other actors either directly or indirectly. such collaborative process on would require The above factors however require a context 2. For these actors to collaborate effectively, an awareness provisioning mechanism must be in place so that awareness requirements of the actors in such collaborative environment are maintained at appropriate levels. Development of a knowledge representation with above characteristics is a challenging task for the authors and constitutes one of their major research activities in progress.

6. Conclusion Human capital analysis is grounded in the literature on organisational sustainability, pioneered by Dunphy (2000) and extended in the research of Drucker (2001), Senge (2000), Collins and Porras (2000) De Geus (1999), Elkington (2001) and Collins (2001). This paper presents an expert system, called

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“Human Capital Analyser” to systematically bridge the knowledge gap in the work of securities analysts to assist them to analyse human capital in listed firms. Insights from the human capital of firms can provide further transparency in the investment recommendation process. The HCA expert system acts as a theoretical and practical bridge between corporate finance and organisational sustainability. More objective analysis of human capital by securities analysts can act as a force for positive change, to ensure clearer alignment of human capital with strategy and thus organisational sustainability. All stakeholders, including investors, managers and employers, as well as the finance industry, can benefit from more transparent and systematic human capital analysis.

References Bassi, L. J, B. Lev, J. Low, D.P. McMurrer, and A.G. Sissfield, (2001). “Measuring Corporate Investments in Human Capital”, The New Relationship: Human Capital in the American Corporation, edited by Blair, M. M. and T.A. Kochan, New York: Brookings Institute. Beer M. and Nohria N. (eds) (2000) Breaking the Code of Change, Harvard Business School Press: Boston. Bernstein, R. (2001) Navigate the Noise: Investing in the New Age of Media and Hype, Wiley: New York. Bilmes, L., K. Wetzker, and P. Xhonneux. (1997). “Value in human resources: A strong link between companies”, Financial Times, 10 February 1997. Collins, J. C. and J. I. Porras. (2000). Built to Last: Successful Habits of Visionary Companies. (revised edition) New York: Harper Collins. Collins, Jim. (2001). Good to Great: Why some companies make the leap, and others don't. New York: Harper Business. Daneshgar, Farhad (2003). “Sharing of Contextual Knowledge in Virtual Communities”, Book Chapter in eCollabourations and Virtual Organisations edited by Dr. Michelle Fong, title "", IGP/INFOSCI/IRM Press, Hershey, PA, USA. De Geus, A. (1999) The Living Company – Growth, Learning and Longevity in Business, Nicholas Brearley: London. Dunphy, D. Griffiths, A. and Benn, S (2003) Organisational Change for Corporate Sustainability, Routledge, Taylor and Francis, Grays: London.

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Dunphy, D and A. Griffiths. (1998). The Sustainable Corporation: Organisation Renewal in Australia. St Leonards: Allen and Unwin. Dunphy, D and D Stace. (2001). Beyond the Boundaries: leading and recreating successful enterprises. Sydney: McGraw Hill. Dunphy, D. ed. (2000). Sustainability: The Corporate Challenge of the 21st Century. Sydney: Allen and Unwin. Drucker, P. (2001) The Essential Drucker, Butterworth Heinemann: Oxford. Elkington, John (2001) “Value Versus Values: Penetrating the Values and Value Barriers”, Ch. 4 in The Chrysalis Economy: How Citizen CEOs and Corporations can Fuse Values and Value Creation, Capstone: Oxford. Economist (2002) “Analysts on Wall Street, Sell? Dishonest Research and Gullible Investors”, The Economist, May 11th, (2002): 68. Fernandez, F. A. (2001) “The Role and Responsibilities of Securities Analysts”, Securities Industry Association Research Reports, (August), pp. 3-10. Feigenbaum, E A (1977) “The Art Of Artificial Intelligence: Theme And Case Studies Of Knowledge Engineering” in Proceedings 5th International Joint Conference on Artificial Intelligence, pp.1014-29. Guthrie, J. and R. Kramar, (2002) “Sunrise in the Knowledge Economy: Managing and Measuring Human Competencies”, Australian Master Human Resources Guide, Sydney: CCH. Harris, L. C. and E. Ogbonna. (2001). “Strategic human resource management, market orientation and organisational performance”, Journal of Business Research 51, no. 2001:157-166. Hewitt and Associates, (2003) “Best Retainers of the Year” Survey on Hewitt and Associates Website (http://was.hewitt.com/bestemployersaustr alia/index.htm). Ittner, C. (2002) "Technological Wizadry Aside, How Can the Internet Reshape Your Business." Wharton School of Business, www.knowledge.wharton.upenn.edu/articl es Jackson P. (1999). Introduction to Expert Systems, Addison Wesley Longman Limited: Essex, England. Kotter, J. and J. Heskett. (1992). Corporate Culture and Performance. New York: Free Press Macmillan. O'Reilly, C. A. and J Pfeffer. (2000). Hidden Value: How Great Companies Achieve

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Extraordinary Results with Ordinary People, Boston: Harvard Business School Press. Ranft, A.L. and M.D. Lord. (2000). “Acquiring New Knowledge: The Role of Retaining Human Capital in Acquisitions of HighTech Firms”, The Journal of High Technology Management Research 11, no. 2:295-319. Royal, C., F. Daneshgar and L. O’Donnell, (2003) “Identifying Knowledge Gap in Current Investment Recommendation Processes”, Proceedings of the 4th European Conference on Knowledge Management (ECKM 2003), Oxford University, UK, pp: 767-774. Royal, C. (2003) “Snakes and Career Ladders in the Investment Banking Industry. The Making of Barclays De Zoete Wedd (BZW), 1982-1996” Accounting, Business and Financial History, Volume 13, No.2: 233-262, UK, (July 2003). Royal, C. and Althauser, R. P. (2003) 'The Labour Markets of Knowledge Workers: Investment Bankers' Careers in the Wake of Corporate Restructuring’, Work and Occupations, Volume 30, No.2: 214-233. Royal, C. and O'Donnell, L. (2002) 'The Human Factor: Taking a Less Subjective Approach to Investment Decisions', Banking and Financial Services Journal, Volume 118, No.6: 10-

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Carol Royal, Farhad Daneshgar and Loretta O’Donnell

13, Melbourne, Australia. Schack, J. (2001). “Should Analysts Own Stock in the Companies They Cover?” Institutional Investor, (April), 2001, pp. 6071. Schuster, F. E. 1986. The Schuster Report: The Proven Connection Between People and Profit, New York: Wiley. Senge, P. M. (2000), “The Puzzles and Paradoxes of How Living Companies Create Wealth”, Ch. 2 in M. Beer and N. Nohria, Breaking the Code of Change, Harvard Business School Press: Boston. Szarycz, C. (2001) “Developing Strategic Management Systems: Integrating the Balanced Scorecard (BSC) Rolling Forecasts, Economic Value Added (EVA) and Activity Based Costing (ABC) to improve your strategic performance”, Beyond Budgeting Conference Proceedings, Sydney, pp. 1-7. Turban E. & Aronson J. A. (2001), Decision Support Systems and Intelligent Systems, Prentice Hall: New Jersey, USA. Turner, D. and M. Crawford. (1998). Change Power: Capabilities that Drive Corporate Renewal, Sydney: Business and Professional Publishing. Watson Wyatt Worldwide Research, Human Capital Index: Linking Human Capital and Shareholder Value, Watson Wyatt. 1-12. (2002). Washington, D.C., Watson Wyatt Worldwide Research.

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The effect of Managerial Power and Relational Trust on the Skills and Traits of Knowledge Acquisition: Evidence from the United Arab Emirates John D. Politis Higher Colleges of Technology, Dubai, United Arab Emirates

[email protected] Abstract: Many organisations have recognised that knowledge is the most important resource in today’s economy. Although knowledge management is seen as central to process and product innovation and improvement, to executive decision making and to organisational adaptation and renewal, little is known on the effect of managerial power and relational trust on the traits and skills of knowledge acquisition. A survey of 140 first line managers was conducted to investigate the relationship between managerial power, relational trust and knowledge acquisition attributes. Results indicate that most, but not all, of the managerial power dimensions enable employees’ knowledge acquisition. Moreover, the findings show that relational (interpersonal) trust had a negative effect on the skills and traits of knowledge acquisition. It was also found that the dimensions of managerial power provided statistically significant additional predictive power, after having statistically controlled for the predictive effects of interpersonal trust. Keywords: Knowledge acquisition ♦ managerial power ♦ relational (interpersonal) trust ♦ United Arab Emirates.

1. Introduction st

As we have move rapidly into the 21 century organisations face the challenge of being effective in a global knowledge environment. In his book PowerShift, Toffler (1990) made it clear that knowledge has become the global competitive driver. The real challenge for organisations is “capturing the tacit knowledge which is in people’s heads – the experience, knowledge and judgement you get from doing something for a long time,” says Stephanie Pursley [1]. But actively managing (acquiring) knowledge relies on individual’s effort and cooperation, so the new model of knowledge management is about personal relevance (Bailey & Clarke, 2001), it is about people and actions and their behaviour in aligning knowledge processes with organisational objectives (Politis, 2003). It is about how we move from the old way of doing things where knowledge was power, to sharing knowledge and achieving a competitive advantage. Sharing the individual and collective brain power of people (knowledge) however, cannot be harnessed in the absence of trust and cooperation, help and care, shared values and vision, sincerity and goodwill (Rastogi, 2000). Professor John Kotter told the Australian Institute of Management that “if people don’t trust the information they are getting from you they won’t necessarily act on it; they won’t pass it on as if it is credible, and that’s a killer” (Kotter, 2003:1). In line with Kotter’s comment, it has even been argued that “trust is, after all, the single most important precondition for knowledge exchange” (Rolland & Chauvel, 2000: 239). The importance of trust has been supported in a study by Politis (2002). In this study,

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respondents indicated that most of the interpersonal trust dimensions are positively related to the skills and traits of knowledge acquisition. It is also acknowledged that power is often employed by management to influence the behaviour of employees (Fairholm, 1993). Although in a recent study Politis (2003) reported that most of the dimensions of power associated with French and Ravens’ (1959) power-based taxonomy enable followers’ knowledge acquisition, current research lacks the empirical evidence supporting the prediction of the skills and traits of knowledge acquisition from the combine effect of the relational (interpersonal) trust and managerial power factors. To this end, this research started by asking the following questions. Is the influence of managerial power more important than the influence of relational (interpersonal) trust in the process of knowledge acquisition? Are the correlations derived from the factors of interpersonal trust and knowledge acquisition stronger, and more positive, than those with the managerial power factors? Will the statistical prediction of the knowledge acquisition attributes be increased with the addition of managerial power factors in the set of the predictor variables? Answers to these questions are some of the objectives of this paper.

2. Managerial power and the determinants of knowledge acquisition According to Sir Francis Bacon “knowledge is power” [2], and where power resides, resides success. Within the managerial power literature, power refers to the “capacity that A has to influence the behaviour of B so that B acts in accordance with A’s wishes” (Robbins,

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2003: 366). In line with this definition, Kanter (1979: 66) argues that power is fundamentally “the ability to mobilise resources (human and machine) to get things done”. It is thus, implied that leaders use power as a means of attaining organisational goals. According to Kipnis and Schmidt (1988), favourable performance gain ratings are largely affected by the manager’s effective use of influence behaviour (power). In this context, power is defined as the ability of management to influence the behaviour, intentions, attitudes, beliefs, emotions, and the values of subordinates (French & Raven 1959). But where does power come from? What is it that gives an individual (i.e. leader) influence over others? Over the years a number of power sources have been presented by Stephenson (1985), Hunt (1986), and Morgan (1986), with French and Raven (1959) being the authors most heavily utilised. Frence and Raven’s powerbased taxonomy consists of five important bases of managerial power: coercive, expert, legitimate, referent, and reward. Coercive power is based on the target’s belief that the manager has the ability to punish employees; expert power is based on the target’s belief that the manager can provide him or her with special knowledge; legitimate power is based on the target’s perception that the manager has the legitimate right to influence the target and that he or she is obligated to comply; referent power is based on the target’s identification with or desire to be associated with the manager; and reward power is based on the target’s belief that the manager has the ability to provide him or her with desired tangible or intangible objectives. On the other hand, knowledge management (acquisition) is jointly a goal and a process. As an organisational outcome or goal, knowledge management is entirely focused on sharing information for the benefit of the organisation (Bollinger & Smith, 2001). Of central importance to organisations however, is to define the term knowledge and identify the type of knowledge that they are forced to manage. Although it seems obvious to define the seemingly self-evidence term – knowledge, the reality is that knowledge and knowledge management are quite complex (Clark & Rollo, 2001); that is because knowledge is usually classified as either explicit or tacit (Nonaka, 1998). Explicit knowledge is described as formal, systematic knowledge that can be expressed or communicated without vagueness or ambiguity. It can be stored in books, manuals, and databases. Tacit knowledge, on the other hand, is considered

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as highly personal know-how that is derived from experience and beliefs and usually hard to articulate and communicate. Moreover, Bollinger and Smith (2001) explained that “tacit knowledge is unarticulated knowledge that is in a person’s head that is often difficult to describe and transfer” (p. 9). Given that 42 percent of corporate knowledge is held within employee’s minds (Clark & Rollo, 2001), it is important for organisations to set up processes whereby tacit knowledge is more accessible and people are easily connected enabling them to think together and to take time to articulate and share information (Lang, 2001). Although setting up such processes could be a complex exercise, authors (Galagan, 1997; Bath, 2003) and organisations concur that a common business practice that is connected to knowledge acquisition is that of “acquiring information directly from domain experts” (Mykytyn, Mykytyn & Raja, 1994: 98). Mykytyn and colleagues revealed 26 behavioural skills and traits (attributes) that are essential for knowledge acquisition. These attributes are presumed to produce seven factors: Communication/problem understanding; Personal traits Control Organisation Negotiation Liberal arts and Non-verbal communication. Communication/problem understanding refers to interviewing; listening; sensitivity; openminded; probing; conceptualising; rational thinking; and hindsight. Personal traits refer to empathy; sense of humour; tolerance; and amiable. Control refers to politics; organisational knowledge; assertiveness; and salesmanship. Organisation refers to leadership; speaking; writing; management; and domain knowledge. Negotiation refers to diplomacy; patience; and co-operation. Liberal arts and non-verbal communication refer to being broadly educated, well informed, having knowledge on subjects dealing with humanities, philosophy and literature and having a broad view of company’s goals and operations. However, these behavioural skills and traits do not emerge spontaneously or in a vacuum. They evolve out of the context and the history of the organisation and their impact is conditioned by the subjective perceptions of knowledge workers whose experience is ruled by that history. This draws attention among

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other things (i.e. organisational process and mechanisms of knowledge creation) to the influence, and hence the power, exercised by management in developing and linking these attributes to successful knowledge acquisition. But like influence, power involves human relationships among leaders and employees (Ivancevich & Matterson 1993). In relation to human relations it is being argued that relationships within an organisation are crucial for knowledge creation, sharing, and utilisation (Lang, 2001). Moreover, recently Politis (2003) found that a number of managerial power dimensions are positively related to knowledge acquisition attributes of knowledge workers. It is thus reasonable to hypothesise that the factors representing managerial power will be predictive variables of the traits and skills of knowledge acquisition. This prediction is further reinforced by the findings of the empirical work in which ‘knowledge leaders’ were found to be positively related to the skills and traits (attributes) that are essential for knowledge acquisition (Politis, 2001). The assumed connectedness between managerial power and knowledge acquisition attributes is expressed in the following hypotheses: Hypothesis 1a: Coercive power will be positively related to the skills and traits of knowledge acquisition. Hypothesis 1b: Expert power will be positively related to the skills and traits of knowledge acquisition. Hypothesis 1c: Legitimate power will be positively related to the skills and traits of knowledge acquisition. Hypothesis 1d: Referent power will be positively related to the skills and traits of knowledge acquisition. Hypothesis 1e: Reward power will be positively related to the skills and traits of knowledge acquisition.

3. Relational trust and determinants of knowledge acquisition It is being argued that knowledge management (KM) is the combination of human resource management and information management, and thus relates to all processes that are combined with the identification, acquisition, creation, distribution and use of both

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information and knowledge (Iivonen & Huotari, 2000). Therefore, human factors are essential components for effective knowledge acquisition and must be taken into account. But, trust belongs to the area of human factors in KM. While it has not been extensively discussed, it has been suggested that trust is required for knowledge generation and knowledge sharing (Probst, Raub & Romhardt, 2000; Rolland & Chauvel, 2000; Kotter, 2003). The employees must trust each other to share their information and knowledge (Connelly & Kelloway, 2000), to generate knowledge. One reason that individuals might be willing to share information is due to the individual’s identification with the organisations’ goals and the simple action of sharing information within a relationship creates relational trust (Ford, 2001). The promotion of relational trust is illustrated through the recommendation to create communities of practice for knowledge generation and sharing (von Krogh, Ichijo & Nonaka, 2000). Communities of practice are groups in which the social cohesiveness has been promoted, and the groups assist on the generation of new knowledge (Davenport & Prusak, 1998). The promotion of social ties within these groups is related to the development of knowledge-based, identification-based and relational trust. With respect to relational trust, Cook and Wall (1980) have distinguished two components of dyadic or interpersonal trust: faith and confidence. Interpersonal trust is been viewed as faith and confidence in peers (that is, coworker trust), as well as, as faith and confidence in management (that is, trust in both the supervisor and top management). The definitions of faith and confidence have been adopted from Cook and Wall (1980: 40). Trust refers to the “faith in the trustworthy intentions of others”. Trust refers to the “confidence in the ability of others, yielding ascriptions of capability and reliability”. Research reported in the literature suggests that high levels of trust between managers and employees are correlated with more open communication (Ruppel & Harrington, 2000) fostering generative learning. Moreover, evidence has shown that collaborative problem solving in organisations presupposes interpersonal trust (Davenport & Prusak, 1998; Politis, 2002), and specifically co-worker trust. Furthermore, Ford (2001) argued that acquisition of knowledge from an individual outside the organisation couldn’t benefit from organisational trust, as the individual is not part

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of the organisation. Yet, impersonal trust would not be effective as the trust is directed to the position within the organisation; therefore, “interpersonal trust is the best type of trust for knowledge acquisition” (Ford, 2001: 14). Therefore, it is reasonable to assume that the factors of interpersonal trust will be the predictive variables of the determinants of knowledge acquisition. The assumed connectedness between interpersonal (relational) trust and knowledge acquisition is expressed in the following hypotheses. Hypothesis 2a: Faith in peers will be positively related to the skills and traits of knowledge acquisition. . Relational (Interpersonal) Trust and Managerial Power Variables

150

Hypothesis 2b: Faith in management will be positively related to the skills and traits of knowledge acquisition. Hypothesis 2c: Confidence in peers will be positively related to the skills and traits of knowledge acquisition. Hypothesis 2d: Confidence in management will be positively related to the skills and traits of knowledge acquisition. The nine hypotheses are summarised in the research model shown in Figure 1

Determinants of Knowledge Acquisition

Managerial Power (French & Raven, 1959) •

Coercive Power



Expert Power



Legitimate Power



Referent Power



Reward Power Relational (Interpersonal) Trust (Cook & Wall, 1980)

Skills & Traits of Knowledge Acquisition (Mykytyn et al., 1994) •

Communication/Problem Understanding



Personal Traits



Control



Organisation



Faith in Peers



Negotiation



Faith in Management





Confidence in Peers

Liberal arts/non-verbal communication



Confidence in Management

Figure 1: Summary of variables used in the paper Moreover, in a recent study Politis (2001) found strong positive relationships between various leadership style dimensions and knowledge acquisition attributes. Yet, performance is largely affected by leadership’s effective use of power (Kipnis & Schmidt, 1988). It is thus, reasonable to hypothesise that the dimensions of managerial power would provide an increase in the level of prediction of knowledge acquisition, after being statistically controlled for the predictive effects of interpersonal trust. Hypothesis 3: The statistical prediction of the knowledge acquisition factors from the relational (interpersonal) trust variables will be increased with the addition of power factors in the set of interpersonal trust predictor factors.

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4. Sample and procedures 4.1

Sample

The sample was selected from service (telecommunications and banking) and manufacturing organisations operating in the United Arab Emirates. Discussions with both management and employees suggested that the selected organisations were relatively flat with maximum six levels of hierarchy. First line managers/supervisors, namely knowledge workers, who were engaged in selling services, servicing customers and manufacturing operations, participated in the study. One hundred and nineteen first line managers (82.5 percent response rate) provided the data. Twenty-one first-line-managers returned

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incomplete questionnaires, which were excluded, from the final sample of 119. The sample consisted of 100% males. Approximately two-quarters of participants had attained a college diploma or degree qualifications and almost one-half had received technical college qualifications.

4.2

Procedures

Survey questionnaires were pre-tested, using small number of respondents (about one dozen; the pre-test participants did not participate in the final data collection). As a consequence of the pre-testing, relatively minor modifications were made in the written instructions and in several of the demographic items. The revised survey, written in English, was then administered to the organisational respondents in a class room environment. Written instructions, along with brief oral presentations, were given to assure the respondents of anonymity protection and to explain (in broad terms) the purpose of the research. The participants were all given the opportunity to ask questions and were encouraged to answer the survey honestly; anonymity was guaranteed and no names or other identifying information was asked.

4.3

Analytical procedure

Confirmatory factor analysis (CFA) is a widely acknowledged technique for testing the psychometric properties of measurement instruments. Bagozzi, Yi and Phillips (1991) emphasised the superiority of CFA to other methods such as the traditional factor analysis and Campbell and Fiske’s (1959) multitrait/multi-methods approaches for examining the construct validity of survey instruments. Thus, a CFA was used for the factor analysis (measurement model) and for the regression analysis (structural model). Following the recommendations of Sommer, Bae and Luthans (1995), a measurement model was developed and then, with this held, a structural (path) model. The factorial validity of the measurement model was assessed using CFA. Given adequate validity coefficient of the measurement model, the number of indicator variables in the model was reduced by creating a composite scale for each latent variable (Politis, 2001). The parameters of regression coefficient λi and measurement error θi, of each composite latent variable, were used as fix parameters in the structural model. The analytical procedure, to calculate the λi and θi, is detailed in Politis’s (2001) study. All of the CFAs were run using the Analysis of Moment

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Structures (AMOS, (Arbuckle, 1997).

version

4)

software

As a test of the measurement and structural models, a mixture of fit-indices was employed to assess model fit. The ratio of chi-square to degrees of freedom (χ2/df) has been computed, with ratios of less than 2.0 indicating a good fit. However, since absolute indices can be adversely affected by sample size (Loehlin, 1992), three other relative indices; the goodness-of-fit index (GFI), the adjusted goodness-of-fit index (AGFI) and the Tucker and Lewis index (TLI) were computed to provide a more robust evaluation of model fit (Tucker & Lewis, 1973; Tanaka, 1987). For GFI, AGFI and TLI, coefficients closer to unity indicate a good fit, with acceptable levels of fit being above 0.90 (Marsh, Balla & McDonald, 1988). For root mean square residual (RMR) and root mean square error approximation (RMSEA), evidence of good fit is considered to be values less than 0.05; values from 0.05 to 0.10 are indicative of moderate fit and values greater than 0.10 are taken to be evidence of a poorly fitting model (Browne and Cudeck, 1993). To improve the psychometric properties of either the measurement or structural model, without altering the base models, the Modification Indices (MI) provided by AMOS were utilised to trim individual items contained in each factor. The author chose to trim items from the survey to eliminate items that crossloaded on different factors. Refinements to survey instruments using ‘item trimming’ without altering the underlying model can help further organisational research on survey measures (Podsakoff & Organ, 1986), without necessarily modifying the conceptual model it was designed to assess.

5. Measurement models 5.1

Managerial power variables

For this research, managerial power was assessed by using French and Raven’s (1959) power-based taxonomy. We measured French and Raven’s (1959) bases of power using a modified version of Hinkin and Schriesheim’s (1989) 20-item power scale, as adapted by Nesler, Aguinis, Quigley and Tedeschi (1993). The scale employs a nine-point response scale (1 = disagree; 9 = agree), and consists of five subscales: coercive power, expert power, legitimate power, referent power, and reward power. Based on the results of a CFA supporting five power factors, these items were used to create five composite scales: coercive

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power (3 items, α = 0.71); expert power (4 items, α = 0.76); legitimate power (4 items, α = 0.81); referent power (4 items, α = 0.89); and reward power (3 items, α = 0.77). Two items were dropped due to cross loading; these being of the order of, or less than, 0.16.

5.2

Relational (interpersonal) trust variables

Relational (interpersonal) trust measures were assessed by using Cook and Wall’s (1980) 12item scale. The scale employs a seven-point response scale (1 = strongly disagree; 7 = strongly agree), and consists of four subscales: faith in peers, faith in management, confidence in peers, and confidence in management. Based on the results of a CFA supporting three factors, these items were used to create three scales: faith in peers (3 items, α = 0.82), confidence in peers (4 items, α = 0.79), and confidence in management (4 items, α = 0.69). One item was dropped due to cross loading; this being of the order of, 0.15.

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Table 1: Descriptive statistics, reliabilities, and λi and θi estimates Reliability

Regression

Error

estimate

coefficient

variance

λ= σ

2 θ = σ (1- α)

Mean SD (σ)

α

Coercive power

6.52

2.27

.71

1.91

1.49

Expert power

5.68

1.84

.76

1.60

.812

Legitimate power

6.79

1.42

.81

1.38

.444

Referent power

6.67

2.01

.89

1.89

.440

Reward power

6.09

2.26

.77

1.98

1.17

Composite latent variables

Managerial bases of power

Relational (interpersonal) trust variables Faith in peers

5.59

1.09

.82

0.99

.214

Confidence in peers

5.79

1.09

.79

1.05

.292

Confidence in management

4.79

1.51

.69

1.25

.707

Determinants of knowledge acquisition

5.3

Determinants of knowledge acquisition

The skills and traits of knowledge acquisition were assessed by using Mykytyn, et al.’s (1994) 26-item scale. The scale employs a seven-point response scale (1 = very unqualified; 7 = very qualified), and consists of six subscales: communication/problem understanding, personal traits, control, organization, negotiation, liberal arts and nonverbal communication. Based on the results of the CFA four factors were supported: communication (6 items, α = 0.74), personal traits/control (6 items, α = 0.77), problem understanding (5 items, α = 0.82), and organisation (6 items, α = 0.70). Three items were dropped due to cross loading; these being of the order of, or less than, 0.11.

6. Path modelling As discussed earlier in the analytical procedure section, the parameters in the path model (i.e. λi and θi) we calculated. Table 1 reports the means, standard deviations, reliability estimates, and λi and θi, estimates for the analysis. Once these parameters—regression coefficients (λi), and the measurement error variances (θi) — were calculated, this information was fed into the path model to examine the relationships among the latent variables. The model of Figure 2 contains the five dimensions of managerial power, the three relational (interpersonal) trust dimensions and the four knowledge acquisition variables.

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Communication

5.37

0.83

.74

0.71

.179

Personal traits/Control

5.27

0.92

.77

0.81

.195

Problem understanding

5.39

0.98

.82

0.89

.173

Organisation

5.43

0.74

.70

0.62

.164

N = 119 The analysis revealed that the structural model of Figure 2 fit the data fairly well, with χ2 = 69.6; df = 24; (χ2/df = 2.90); GFI = 0.90; AGFI = 0.88; TLI = 0.86; CFI = 0.89; RMR = 0.106; and RMSEA = 0.083. Alternative models were examined with either paths added, reversed or removed, but none improved the model fit.

6.1

Hypotheses testing

Figure 2 displays results of the best fit structural equations model. As predicted by hypothesis 1a (H1a), there were significant positive relationships between coercive power and knowledge acquisition attributes. Coercive power was strongly and positively related to communication (γ1 = 0.32, p < 0.001), personal traits/control (γ2 = 0.21, p < 0.01), problem understanding (γ3 = 0.30, p < 0.001), and organisation (γ4 = 0.27, p < 0.01), supporting H1a. Hypothesis 1b (H1b) predicted that expert power will be positively related to knowledge acquisition attributes. The standardised path coefficient between expert power and problem understanding was strong and significant (γ5 = 0.57, p < 0.001), marginally supporting H1b.

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The expected relationship between expert power and the other dimensions of knowledge acquisition, viz. communication, personal traits/control, and organisations, was not supported. Contrary to Hypothesis 1c (H1c), legitimate power was negatively related to

problem understanding (γ6 = - 0.11, p < 0.10), and organisation (γ7 = -0.15, p < 0.05), while the results showed no other relationship between legitimate power and communication or personal traits/control.

R e la tio n a l (In te r p e r so n a l) T r u st a n d M a n a g e r ia l P o w e r V a r ia b le s

D e te r m in a n ts o f K n o w le d g e A c q u isitio n

C oercive P ow er

γ 1 = .3 2 * * * C om m u n ica tion

E xp ert P ow er

γ 1 1 = -.1 2 +

γ 5 = .5 7 * * * L eg itim a te P ow er

γ 2 = .2 1 * *

γ 6 = -.1 1 +

P ers o n a l T ra its /C o n trol

γ 7 = -.1 5 * R eferen t P ow er

γ 8 = .5 5 * * *

γ 3 = .3 0 * * *

γ 9 = .3 5 * * *

P ro b lem U n d ers ta n d in g

R ew a rd P ow er

γ 1 0 = -.2 0 * * γ 4 = .2 7 * *

γ 1 2 = -.1 2 +

F a ith in P eers

O rg a n iza tio n C on fid en ce in P eers

γ 1 3 = -.1 9 *

γ 1 4 = -.2 2 *

C on fid en ce in M a n a g em en t

Figure 2: Structural estimates of the hypothesised model α Note: α Standardised path coefficients, N = 119 + p < 0.10 *p < 0.05 ** p < 0.01 *** p < 0.001 All corelations of predictor variables were statistical significant at 0.01 level. As predicted by Hypothesis 1d (H1d), there were significant positive relationships between referent power and two dimensions of knowledge acquisition. Specifically, referent power was strongly and positively related to

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problem understanding (γ8 = 0.55, p < 0.001) and organisation (γ9 = 0.35, p < 0.001). The expected relationship between referent power, communication and personal traits/control was not supported. Finally, the relationship

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between reward power and organisation was in the wrong direction (γ10 = -0.20, p < 0.05), not supporting predictions. No paths were significant between reward power and the other knowledge acquisition attributes, hence, not supporting Hypothesis 1e (H1e). In relation to relational (interpersonal) trustknowledge acquisition relationship, the findings are not consistent with the hypotheses. Specifically, the results showed that faith in peers was negatively related to communication (γ11 = - 0.12, p < 0.10) and organisation (γ12 = 0.12, p < 0.10), not supporting Hypothesis 2a (H2a). Hypothesis 2b was not tested, because the variable faith in management was not supported by the CFA. Moreover, Hypothesis 2c (H2c) predicted that confidence in peers will be positively related to knowledge acquisition attributes. This prediction was not supported (see Figure 2), in that no paths were significant between confidence in peers and the factors of knowledge acquisition. Finally, Hypothesis 2d (H2d) predicted a positive and significant relationship between confidence in management and knowledge acquisition. Contrary to prediction, the relationships between confidence in management and both personal traits/control and problem understanding, were in the wrong direction (γ13

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= -0.19, p < 0.05 and γ14 = -0.22, p < 0.05, respectively), not supporting H2d. No other paths were significant between confidence in management and the dimensions of knowledge acquisition. The structural equations results supported Hypothesis 3 (H3) for all dimensions of knowledge acquisition attributes (see Table 2). As expected, the dimensions of power measured by Nesler et al. (1993) scale provided small but statistical significant incremental validity for the knowledge acquisition attributes. For example, it was found that the coefficient of determination for the structural equations for communication was 0.39 (R2 = 0.39). In other words, the combined effect of the five managerial power dimensions and the dimension of interpersonal trust (predictor variables) explains 39 per cent of the variation in communication. The remaining 61 percent are not explained. As shown in Table 2, the results revealed that the measures of managerial power provided a small but statistically incremental validity for the dependent variables of communication (9 percent), personal traits/control (2 percent), problem understanding (4 percent), and organisation (10 percent), supporting H3.

Table 2 Coefficient of determination (R2) of knowledge acquisition attributes Dependent Variables With relational (interpersonal) trust dimensions

2

With the addition of of managerial power dimensions

Coefficient of Determination (R ) Incremental predictive power

Communication

0.30

0.39

0.09

Personal Traits/Control

0.04

0.06

0.02

Problem Understanding

0.04

0.08

0.04

Organization

0.19

0.29

0.10

7. Discussion The aim of this study was to extend the field of research by investigating the combine effect of managerial power and relational (interpersonal) trust on the skills and traits of knowledge acquisition. Furthermore, the predictive power of the factors of managerial

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power in the set of the predictor variables was examined. To a large extent the results are consistent with the realm of power and organisational performance literature, in that managerial power is necessary to produce effective results (Fairholm, 1993), and to increase performance output (Kipnis & Schmidt, 1988). The findings

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are also consistent to those of previous studies in which Politis (2003) found that some power dimensions are positively related to knowledge acquisition attributes. The results showed that coercive power, referent power, and expert power are important determinants of communication, personal traits/control, problem understanding, and organisation (i.e. dimensions of knowledge acquisition). Specifically, the results suggest that those leaders who provide employees with special knowledge, i.e. expert power, can encourage and facilitate specific behavioural skills and traits of knowledge workers (i.e. problem understanding) that are essential for knowledge acquisition. In that regard, Politis (2001) chose to refer to those leaders as ‘knowledge-enabled leaders’, while Brenneman, Keys and Fulmer (2000) describe then as ‘servant leaders’. Such leaders encourage personal traits, negotiation, and other learning activities and act as servants to others in order to stimulate and inspire organisational learning. Furthermore, referent power (personality power) does facilitate negotiation between knowledge workers. In other words, the ability of leaders to develop followers from the strength of their own personalities does encourage followers’ problem understanding, viz. open-minded; probing; conceptualising; rational thinking; and hindsight, and organisation, viz. leadership; speaking; writing; management; and domain knowledge, all of which being essential ingredients for knowledge acquisition and knowledge sharing. Moreover, the findings are not consistent with the literature of relational trust and knowledge management. The study failed to identify strong relationships between the dimensions of interpersonal trust and knowledge acquisition attributes, not supporting previous empirical findings. It is implied in these results that organisations may acquire and share knowledge via technology and through individuals who never develop strong interpersonal relationships, thus interpersonal trust (Ford, 2001). These organisations may run into a risk of developing a culture whereby employees through words, actions, or decisions, act ‘opportunistically’ (Robbins, 2003), in a way that individuals are steeped as being strongly antagonistic to knowledge sharing. This type of culture raises the concern of emebeddedness, that is, the type of behaviour embedded in structures of social relations (Granovetter, 1985). This should be

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examined through a series of field studies or experimental studies. Finally, it was found that the dimensions of managerial power provided statistically significant additional predictive power, after having statistically controlled for the predictive effects of interpersonal trust dimensions. This implies that managers in countries with high power distance (i.e. approximately 82 out of 110 points in Hofstede’s (1991) Power Distance Index) are more likely to be paternalistic towards employees, thereby, facilitating their skills and traits for knowledge acquisition. An issue that has been raised by this paper is that it may be possible for cultures with high power distance (i.e. Arab, Far Eastern and Latin countries) to do some, if not all the knowledge processes without interpersonal trust (i.e. solely through organisational trust and managerial power); an argument supported by Ford (2001). In conclusion, managers can exercise power through their position and rewards, but cannot force relational (interpersonal) trust to occur. They can actively encourage and facilitate however, a knowledge-sharing environment, and discourage industrial age thinking and opportunistic behaviours.

7.1

Limitations and future work

The present study limited its focus to a key set of managerial power, relational trust and determinants (skills and traits) of knowledge acquisition. Although the variables of relational (interpersonal) trust and managerial power used in this study were considered important in facilitating a knowledge-sharing culture, future research models should examine the relationship of knowledge acquisition to other factors, such as task complexity, organisational trust (Ford, 2001), culture and leadership (Davenport, DeLong & Breers, 1998), and organisational and social networks (Lincoln & Miller, 1979; Granovetter, 1985). Although from the analytical perspective structural equations modelling has a number of advantages in testing statistical causal relationships, actual causality cannot be tested directly. So ideally future research must test causality using experimental or longitudinal data for more define results. Finally, the crosssectional nature of the study renders it vulnerable to problems typically associated with survey research (common method variance). To account for the common method variance problems, it would have been

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advantageous for future researchers to gather data from multiple sources.

7.2 [1]

[2]

Notes Stephanie Pursley, Knowledge Management Partner at Freehills, Sydney Office, Australia (www.freehills.com). Sir Francis Bacon, (www.brainyquote.com/quotes/quot es/s/q100764.html).

References Arbuckle, J. L. (1997). Analysis of moment structures (AMOS), User’s Guide Version 3.6, Chicago, IL: SmallWaters Corporation. Bath, S. (2003) “A framework for personal knowledge management tools”, KMWorld, Vol 12, No. 1, pp 20-1. Bagozzi, R. P., Yi, Y. & Phillips, L. W. (1991) “Assessing construct validity in organisational research”, Administrative Science Quarterly, Vol 36, pp 421-58. Bailey, C. & Clarke, M. (2001) “Managing knowledge for personal and organisational benefit”, Journal of Knowledge Management, Vol 5, No. 1, pp 58-67. Bollinger, A. S. & Smith, R. D. (2001) “Managing organisational knowledge as a strategic asset”, Journal of Knowledge Management, Vol 5, No.1, pp 8-18. Brenneman, W. E., Keys, J. B. & Fulmer, R. M. (2000) “Learning across a living company: The Shell Companies’ experience”, In the Knowledge Management Yearbook 20002001, Cortada, J. W. and Woods, J. A. (Eds.), Butterworth Heinemann, Boston, p. 175. Browne, M. W. & Cudeck. R. (1993) “Alternative ways of assessing model fit”, In Bollen, K. A. and Scott Long, J. (Eds.), Testing structural equations models (pp.136-162). Newbury Park, California: Sage. Campbell, D. T. & Fiske, D. W. (1959) “Convergent and discriminant validation by the multi-method matrix”, Psychological Bulletin, Vol 56, pp 81-105. Clark, T. & Rollo, C. (2001) “Corporate initiatives in knowledge management”, Education and Training, Vol 4, No.4, pp 206-41. Connelly, C. & Kelloway, K. (2000) Predictors of knowledge sharing in organisations. Unpublished MSc Thesis, Queen’s School of Business, Queen’s University, Kingston, ON.

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Cook, J. D. & Wall, T. D. (1980) “New work attitude measures of trust, organisational commitment and personal need nonfulfilment”, Journal of Occupational Psychology, Vol 53, pp 39-52. Davenport, T. & Prusak, L. (1998) Working Knowledge: How Organisations Manage What They Know, Harvard Business School Press. Davenport, T. H., DeLong, D. W. & Breers, M. C. (1998) “Successful knowledge management projects”, Sloan Management Review, Winter, pp 43-57. Fairholm, G. W. (1993) Organisational power politics: Tactics in organisational leadership, Praeger, Westport, CT. Ford, D. (2001) “Trust and knowledge management: The seeds of success”, Working Paper 01-08, Queen’s KBE Centre for Knowledge-based Enterprise, Kingston. French, J. R. P. & Raven, B. H. (1959) “The basis of social power”, in D. Cartwright (ed.), Studies in Social Power (Ann Arbor: University of Michigan, Institute for Social Research, pp 150-167. Galagan, P. (1997) “Smart companies (knowledge management)”, Training and Development, Vol 51, No. 12, pp 20-5. Granovetter, M. (1985) “Economic action and social structure: The problem of embeddedness”, American Journal of Psychology, Vol 91, No.3, pp 481-510. Hinkin, T. R. & Schriesheim, C. A. (1989) “Development and application of new scales to measure the French and Raven (1959) bases of social power”, Journal of Applied Psychology, Vol 78, pp 561-67. Hofstede, G. (1991) Cultures and organisations: Software of the mind, McGraw-Hill, London, UK. Hunt, J. W. (1986) Managing people at Work, 2nd ed., McGraw-Hill, London, UK. Iivonen, M. & Huotari, M. L. (2000) The Impact of Trust on the Practise of Knowledge Management. In: Proceedings of the 63rd ASIS Annual Meeting, Vol 37. Chicago, IL, November 12-16, pp 421-29. Ivancevich, J. M. & Matterson, M. (1993), Organisational Behaviour and Management, Irwin, Boston. Kanter, R. M. (1979) “Power failure in management circuits”, Harvard Business Review, Vol 24, pp 65-75 Kipnis, D. Es. & Schmidt, S. M. (1988) “Upward-influence styles: Relationship with performance evaluations, salary and stress”, Administrative Science Quarterly, Vol 33, pp 528-42.

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Kotter, J. (June, 2003) “Trust is the key”, Agenda, Australian Institute of Management, pp 1-4. Lang, J. C. (2001) “Managerial concerns in knowledge management”, Journal of Knowledge Management, Vol 5, No. 1, pp 43-57. Lincoln, J. R. & Miller, J. (1979) “Work and friendship ties in organisations: A comparative analysis and relational networks”, Administrative Science Quarterly, Vol 24, No. 2, pp 181-99. Loehlin, J. (1992) Latent Variables Models, Erlbaum, Hillside, N. J. Marsh, H. W., Balla, J. R. & McDonald, R. P. (1988) “Goodness-of-fit indexes in confirmatory factor analysis: the effect of sample size”, Psychological Bulletin, Vol 103, No.3, pp 391-410. Morgan, G. (1986) Images of Organisation, Sage, Beverly Hills, CA. Mykytyn, P. P., Mykytyn, K. & Raja, M. K. (1994) “Knowledge acquisition skills and traits: a self-assessment of knowledge engineers”, Information and Management, Vol 26, pp 95-104. Nesler, M. S., Aguinis, H., Quigley, B. M. & Tedeschi, J. T. (1993) “The effect of credibility on perceived power”, Journal of Applied Social Psychology, Vol 23, pp 1407-25. Nonaka, I. (1998) The knowledge creating company, Harvard Business Review on knowledge Management, Harvard Business Scholl Press, Boston. Podsakoff, P. M. & Organ, D. W. (1986) “Selfreports in organisational research: Problems and prospects”, Journal of Management, Vol 12, No.4, pp 531-44. Politis, J. D. (2003) “Power and knowledge acquisition: the implications for team performance”, in the proceedings of the conference on Organisational Knowledge, Learning and Capabilities (OKLC), pp 62. IESE Business School, University of Navarra, Barcelona, Spain, 13-14 April. Politis, J. D. (2002) “Interpersonal trust predictor of knowledge acquisition in selfmanaging teams: the consequences for performance”, in the proceedings of 3rd European Conference on Knowledge Management, pp. 552-562. Trinity

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College, Dublin, Ireland, 24 - 25 September. Politis, J. D. (2001) “The relationship of various leadership styles to knowledge management”, The Leadership and Organizational Development Journal, Vol 22, No. 8, pp 354-64. Probst, G., Raub, S. & Romhardt, K. (2000) Managing knowledge: Building blocks for success, John Wiley & Sons, Ltd., Chichester. Rastogi, P. N. (2000) “Knowledge management and intellectual capital – the new virtuous reality competitiveness”, Human Systems Management, Vol 19, No.1, pp 39-48. Robbins, S. P. (2003) Organisational Behaviour (10th ed.). Prentice-Hall Inc., Upper Saddle River, NJ. Rolland, N. & Chauvel, D. (2000) “Knowledge transfer in strategic alliances”, In Despres, C. & Chauvel, D. (Eds.), Knowledge Horizons: The Present and the Promise of Knowledge Management, Butterworth Heinemann, Boston, MA, pp 225-36. Ruppel, C. P. & Harrington, S. J. (2000) “The relationship of communication, ethical work climate, and trust to commitment and innovation”, Journal of Business Ethics, Vol 25, pp 313-28. Sommer, S., Bae, S-H. & Luthans, F. (1995) “The structure-climate relationship in Korean organisations”, Asia Pacific Journal of Management, Vol 12, No. 2, pp 23-36. Stephenson, T. (1985) Management: A political activity, Macmillan, London. Tanaka, J. S. (1987) “How big is enough? Sample size and goodness-of fit in structural equation models with latent variables”, Child Development, Vol 58, pp 134-46. Toffler, A. (1990) PowerShift: Knowledge, wealth, and violence at the edge of the 21st Century, Bantam Books, New York. Tucker, L. R. & Lewis, C. (1973) “The reliability coefficient for maximum likelihood factor analysis”, Psychometrika, Vol 38, pp 1-10. von Krogh, G., Ichijo, K. & Nonaka, I. (2000) Enabling knowledge creation: How to unlock the mystery of tacit knowledge and release the power of innovation, Oxford University Press, New York, NY.

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Towards Understanding KM Practices in the Academic Environment: The Shoemaker’s Paradox Gary R Oliver The University of Sydney, Australia [email protected]

Meliha Handzic and Christine Van Toorn The University of New South Wales, Sydney, Australia [email protected] [email protected] Abstract: One area of omission in knowledge intensive studies is within higher education/research where there is the virtuous circle of teaching, research and consulting professional work. Using a model adapted from Handzic (2001) and a survey modified from Arthur Andersen (1998) the perceived importance and perceived implementation to faculty members is explored. The discrepancy between results of the two forced the researchers to confront their own biases. Guidance was sought from ethnographic accounts which allowed allows the researcher to state personal feelings in a confessional accompaniment to the formal findings. Keywords: Knowledge management processes, Organisational environment, Knowledge management technologies; Confessional ethnography.

1. Introduction The literature in management and organisation indicates a widespread recognition of the association of knowledge and organisational success. Despite early awareness of the construct (Drucker, 1967) and comprehensive overviews (Despres and Chauvel, 2000; Earl, 2001) there remains little overall advance in understanding the construct itself (Drucker, 1993; Stewart, 1997). Specific applications of knowledge to work have been explored by industry practitioners (eg Collison and Parcell, 2001 at BP; Mann et al, 1991 in power utilities), management commentators (O’Dell and Grayson, 1998) and researchers (eg Carneiro, 2000; Newell et al 2003). This produces the distinction that knowledge is associated with skills (eg Macintosh et al 1999) or making judgements and decisions in particular circumstances (Carr, 1999) so it is not surprising that differences exist among scholars as to what constitutes useful knowledge and the ways in which it is created. Some theorists show more interest in codified repositories and information processing as enablers of ‘explicit’ objective and systematic knowledge (Budzik et al, 1999), Carr, 1999, Den Hartog and Huzinga, 1997 in Huysman and de Wit, 2002; Klösgen (1996). Others focus on the ‘tacit’ knowledge that people derive from their experiences and from social interaction with others (Nonaka and Takeuchi, 1995; Malhotra, 2000). The shift in emphasis from sharing knowledge to making productive use of knowledge is reflected in the shift from individual focus to that of communities (Wenger, et al, 2002).

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As organisations become more knowledgebased, their success will increasingly depend on knowledge workers becoming successful at contributing to effective decision making and creating innovation. It is therefore not surprising that there is a growing recognition amongst researchers and practitioners alike for the need to better understand what knowledge is, the value of knowledge, and how it should be managed. In some cases this is formalised as Knowledge management (KM) and in other cases as the learning organisation (DiBella et al, 1996) or organisational memory (Weick, 1979). Both are recent responses to the need to better understand and manage knowledge for success or survival. The central task of those concerned with knowledge management is to determine best ways to cultivate, nurture and exploit knowledge at individual and organisational levels. In other words, it needs to ensure to get the right knowledge to right people just in time (Snowden, 2002) and help people share and put knowledge into action in ways that strive to improve organisational performance (Dixon, 2000; O’Dell and Grayson, 1998). A distinctive application of KM is applying knowledge to knowledge itself. Knowledge intensive firms focus on the commercialisation of knowledge (eg Starbuck, 1992; Gibbons et al, 1999), innovation and creativity (eg Gerlach and Lincoln, 2000; Brown and Duguid, 2000) or the work of experts (eg Albert and Bradley, 1997). Consulting firms are a particular example of KM practitioners (Savary, 1999). One area of omission in knowledge intensive studies is within higher education/research where there is the virtuous circle of teaching, research and consulting professional work.

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The objective of this study is to examine this issue in a particular academic environment from the twin perspective of the individuals and expert in KM.

2. Knowledge management framework An integrated model of knowledge management is presented in Figure 1. This illustrates the essential components of knowledge management and their interrelationships. The model (adapted from Handzic, 2001) proposes two types of organisational factors; organisational

140

environment (notably leadership and culture) and technological infrastructure (the information and communication resources), which may act as an enabler or constraint on knowledge processes (eg. creation, transfer, utilisation) and foster the development of organisational knowledge. The model allows the overall organisational environment to influence the choice of the technological infrastructure to support knowledge processes. Finally, the model incorporates a feedback loop to suggest the need for continuous knowledge measurement and potential adjustment of strategies over time.

Organisational environment Knowledge processes Technological infrastructure

Organisational knowledge

Measurement

Figure 1: An Integrated Knowledge Management Framework Although there have been many individual case studies of various knowledge management initiatives in organisations (eg Collison and Parcell, 2001; Fruin, 1997; Galliers, 2002; Gerlach, and Lincoln, 2000) there is little empirical evidence regarding the actual penetration and impact of knowledge management (Kluge et al, 2001; Machlup, 1962; Porat, 1977). The studies available emphasised the introduction of KM programmes and therefore considered factors such as facilitators of, and barriers to, success. Therefore there was scope for a study that examined perceptions (Likert, 1932) from both the individual and organisation points of view. The aim of the study was to investigate several aspects of knowledge management including; organisational environment, technological infrastructure, knowledge processes, and knowledge measurement. In light of the foregoing commentary the first stage this paper is to outline the organisational environment and specific factors to assess the approach and extent to which a semi-autonomous university school manages its organisational knowledge.

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3. Organisational description The university school studied is a highly renowned institution teaching and research institution. It offers both undergraduate and postgraduate programs of study. It operates a research centre, plans and conducts a series of research seminars, and, produces scholarly articles. Wiig (1995) and Liebowitz (2000) discuss the use of surveys to explore a professional’s thoughts about managing knowledge and solicit perspectives on the adequacy and efficiency of KM. The survey instrument employed in this study was based on a previously available instrument (Arthur Andersen, 1998). (A copy of the survey instrument and coding sheet is available from the authors). It provides the benefits of consistency, balance in coverage and capture of individual attitudes. Modifications were made to the wording to reflect specifics of the organisation being studied and to achieve consistency in framing among questions (Oppenheim, 1992; Schulman and Presser, 1981). The survey design allows the respondent to rate the importance of particular KM practices in a parallel set of questions the perceived extent to which they are implemented. Prior to administration the survey

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items were assigned to the four aspects in two independent inter-rater exercises. Reliability is in excess of .9. Participants in the study were academic staff with full time (continuing and contract) employment. To minimise potential threats to validity, questionnaires were distributed to all academics who satisfied the specified criteria and a brief explanation was provided. Responses were anonymous and participation was voluntary. 24 distributed questionnaires were distributed. Surveys were completed without the researchers being present. 17 surveys were returned, achieving a return rate of 71%. This level of response and the profile across positions ensures that the sample is representative of the population. While the formal survey sought specific responses, the researchers also considered their own organisational environment. The researchers recognised the potential for bias in the study in view of their role and responsibilities within the school. Guidance was sought from well-regarded ethnographic accounts (Geertz, 1974, Van Maanen, 1988; Trauth, 1997). Their ethnographic approaches present the problem of presenting a convincing

result (Crapanzo, 1986). As the current research involves an audit of the corporate culture of a specific real-world organisation it becomes necessary to consider the results themselves and their meaning in the social context to the researcher. Proponents of this approach also argue that the results can provide a greater level of depth and understanding of self image (Pratt, 1986). As the design generates insufficient data to investigate cause-and-effect relationships it requires careful planning and attention in order to establish validity (Cook, 2000). In short the survey required a personal perspective account as well a positivist count in reviewing the results.

4. Research results A descriptive analysis of data was performed as suggested by Tukey (1977) to identify prevailing patterns and ensure plausibility of findings. In order to identify a central tendency in participants’ perceptions, the average scores of their responses to relevant questionnaire items were calculated. These scores are presented in Table 1, the scale for questionnaire items being 1-7 (7 being the maximum and 1 being the minimum).

Table 1: Summary results of knowledge management practices survey Knowledge Management Practice Organisational Environment Technological Infrastructure Knowledge Processes Knowledge Measurement

Perceived Importance Mean Score 5.32 4.84 4.66 4.75

With respect to the perceived importance of the four knowledge management practices studied, the mean scores obtained ranged from 4.66 to 5.32. Participants rated a mean score of 5.32 for organisational environment, 4.84 for technological infrastructure, 4.66 for knowledge processes, and 4.75 for knowledge measurement practices. With a seven point scale, scores greater than four indicated that participants tended to perceive all four practices as being quite important, but the most important of all was the organisational environment. With respect to the perceived implementation of these practices, the mean scores obtained were 3.16 for organisational environment, 3.38 for technological infrastructure, 2.39 for knowledge processes, and 2.11 for knowledge measurement practices. Scores less than 4 indicated that participants perceived the level

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Perceived Implementation Mean Score 3.16 3.38 2.39 2.11

of implementation of these knowledge management practices in their organisation as being rather low, particularly with respect to knowledge measurement practices.

5. Discussion The key finding from the survey of knowledge management practices in the school studied is the variance between the perceived importance and implementation. This was demonstrated by low scores obtained for participants’ perceptions of the implementation of knowledge processes and their sociotechnological enablers, as compared to their perceptions of their respective importance. Each of the factors in the model is now considered. The participants perceived organisational environment as a particularly important knowledge management practice. This view is

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supported by the KM framework, which suggests that knowledge processes are facilitated by a conducive organisational environment. Such an environment is usually demonstrated in terms of strong leadership support and a collaborative organisational culture. Examples of good leadership support may include: recognition of the cental importance of managing knowledge to organistional strategy, encouraging learning to support existing and create new competencies, developing human resource plans and reward schemes based on the contribution to the development of organisational knowledge. The high level of awareness of KM importance found in this study is an encouraging finding. Evidence of a collaborative culture may include an environment that enables and facilitates knowledge sharing, where a climate of openness and trust exists, and where service value creation is the main objective of knowledge management practices. In addition, there will be flexibility and a desire to innovate and drive the learning process, and an environment where employees take responsibility for their own learning. Our analysis of people’s perceptions regarding these aspects of KM appear to suggest that there is an emerging collaborative culture and some support for knowledge management to be implemented within the school. With respect to technology, the findings indicate that it was also considered as quite important KM practice. It is generally believed that technological infrastructure has the potential to enable or facilitate knowledge processes by providing a platform for knowledge capture or sharing. Some examples where technology can be successfuly used to facilitate knowledge processes include; linking all members of the firm to one another and to all relevant external parties, creating an institutional memory that is accessible to the entire organisation, linking the organistion with its customers and partners, supporting collaboration amongst employees, fostering human-centered, real-time, integrated and smart systems. Findings of this study indicate that there may be a need for further investment in technological infrastructure in order to fully facilitate knowledge management processes. In addition, the study highlighted a low level of implementation of knowledge processes. Facilitated or not, organisational knowledge is enhanced through a series of interrelated processes of knowledge creation, transfer and utilisation. Organisations that implement these

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processes may exhibit some of the following characteristics; systematic identification of knowledge gaps and well-defined processes to address and close them, the development of sophisticated and ethical intelligence-gathering mechanisms and the involvement of all workforce members in looking for ideas. Formalising the process of capturing and transferring knowledge including documentation and lessons learnt, valuing and transferring tacit knowledge across the organisation through encouraging experimentation and socialisation. Our findings indicate that academics recognise the importance of these processes quite well, as shown by their high response scores. However, once again these findings indicate an emerging level of implementation of many of the above processes. Finally, findings indicate that participants tended to view the school’s knowledge measurement practices as being in the formative stages of development. Our proposed framework clearly suggests the need for continuous knowledge measurement in order to monitor and adjust an organisation’s knowledge management strategy over time. Implementing good knowledge measurement practices is usually evidenced in finding ways to link knowledge management to results, developing specific sets of indicators to manage knowledge, including a balanced set of soft and hard, financial and non-financial indicators, as well as by allocating resources towards efforts that measurably increase organisational knowledge base. The results of the study indicate that these areas need to be addressed by the school. In considering how to offer perspective on the findings, the authors considered their own position in relation to the survey. This approach parallels that suggested and practised by Schultze (2000). In this section therefore the authors adopt a confessional mode, appraising their motivations, practices and reactions to the findings. After returning to early western conceptions of knowledge, Snowden (1999) concludes that trust, naiveté and curiosity are key words in knowledge management. This unlikely combination provided the researchers with useful insights. As KM researchers and practitioners themselves, the authors were concerned that there was a lack of recognition of the contribution of KM in education given government expectations for innovation and competitiveness in a global market (Carneiro, 2000; Cronin and Davenport, 2001; Kidwell, et

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al 2001). Unlike other countries, the Australian government commitment to the knowledge economy can be described as mild given the latest knowledge economy policy documentation at www.fed.gov.au at the deadline for submission is dated 2001. Thus any organisational commitment to KM will default to policies and champions within the governing body. This double absence is clearly distressing to the authors as they are acutely aware that members of the school tacitly hold considerable institutional knowledge (Stein, 1995). The authors had a number of experiences where they wasted time on administrative matters or made suboptimal decisions through lacking access to that knowledge. Following several of the tenets of KM the authors adopted an informal knowledge sharing approach with regard to curriculum and course advising. It is noteworthy that on a personal basis other faculty members in the school belonged to small groups which practised knowledge sharing. The pressures of teaching and research prevented codification and sharing on a wider basis. Kidwell’s (2001) simple dichotomy of ‘what’s in it for me?” versus ‘what’s in it for our customer’ is therefore regarded as simplistic. The ‘customer’ does not become the focus simply because profit is absent. One attractive view centres on a broader view of human resource development (Stern, 1996).

6. Conclusions The empirical findings of the current study provide an insight into the penetration of knowledge management practices into a typical knowledge intensive organisation such as a university school. In particular, our findings demonstrate a high level of awareness of importance with a low level of actual implementation. This suggests that the school is in the formative stages of embracing knowledge management practices. From the results presented in this paper, one may conclude that KM is an important aspect of organisational management success that needs to be carefully considered. The high level of awareness of its importance found in this study is an encouraging finding. If planned and implemented carefully, in alignment with organisational objectives and core competencies, it may enable the release of the organisational knowledge resources that will bring ultimate success. In terms of the implementation of knowledge management practices, our findings indicate

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that a major challenge exists in this area. The results of the study identify an organisation in the formative stages of this process. The low level of implementation found with respect to the four types of knowledge management practices investigated, are the major indicators of this being an emerging area. Findings also indicate and highlight areas where issues need to be further addressed within the school being studied. Further research is proposed to explore these issues including a follow-up survey to ascertain any change in perception without there having been any change in the management. When considering the nature of the organisation being studied, the findings indicate that a major challenge exists for the school. Whilst operating in an ever-changing world and environment, the challenge will be to find and implement the most appropriate mix of knowledge management practices in alignment with the school’s goals and strategies. This challenge must be embraced and faced headon in order to ensure the school’s continued success. Again, turning to a confessional mode, there are different personal reactions to the organisational implications. Recognising the evidence of management disinterest in KM gives impetus for considering external linkages to obtain sustenance and support for KM. Given the affinity of KM and consulting it raises the question of future possibilities. Rather than waiting for KM to be adopted, perhaps as a management fad or with a technology emphasis, the informal tactics practised centre on using small internal communities of practice supplemented by linkages to external networks. This latter approach may not necessarily provide examples of best practice however it confirms an ever present awareness of both deficiencies and potentialities while stimulating the members to provide teaching and research within the ability of their resourcing.

7. Acknowledgements We are indebted to Jay Leibowitz for the subtitle, from a chapter in his volume, (1998) Information technology management: A knowledge repository: CRC Press, NY.

References Albert, S. and K. Bradley (1997) Managing knowledge: Experts, agencies and organizations, Cambridge University Press, Cambridge.

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Arthur Andersen (1998) The Knowledge Management Practices Book, Arthur Andersen, January, 1998. Bassi, L. J. and M. E. van Buren (2000) New measures for a new era, in (Eds): Morey, D; M. Maybury and B. Thuraisingham. Knowledge management: Classic and contemporary works, MIT Press, Cambridge, Massachusetts, pp 355-373. Brown, J. S. and P. Duguid (2000) The social life of information, Harvard Business School Press, Boston, Massachusetts. Budzik, J. and K. Hammond (1999) A system for the capture, organisation and re-use of expertise, in (Ed) Woods, L: ASIS ’99 Proceedings of the 62nd annual meeting. Knowledge creation, organisation and use, Washington DC 31 October to 4 November, 1999. Information today, Medford, NJ. Carneiro, A. (2000) How does knowledge management influence innovation and competitiveness, Journal of Knowledge Management, Vol 4 (2), pp 87-98. Carr N. G. (1999) A new way to process knowledge, Harvard Business Review, September-October, 1999, pp 24-25. Collison, C. and G. Parcell (2001) Learning to fly: Practical lessons from one of the world’s leading knowledge companies, Capstone, Oxford. Cook, T. D. (2000) Toward a practical theory of external validity in (Ed) Bickman, L Validity and social experimentation: Donald Campbell's legacy Volume 1, Sage Publications, Thousand Oaks, California, pp3-43. Crapazano, V. (1986) Hermes dilemma: The masking of subversion in ethnographic description in (Ed) Clifford, J and G. E. W. Marcus, Writing culture: The poetics and politics of ethnography, University of California, Berkeley, pp51-76. Cronin, E. and E. Davenport (2001) Knowledge management in higher education in (Ed) Bernbom, G: Information alchemy: The art and science of knowledge management, Jossey-Bass, San Francisco, pp25-42. Despres, C. and Chauvel, D. (2000): A thematic analysis of the thinking in knowledge management in (Eds) Despres, C. and Chauvel, D. Knowledge horizons: The present and the promise of knowledge management, ButterworthHeinemann, London, pp55-86 DiBella, A. J.; E. C. Nevis and J. M. Goiuld (1996) Organizational learning style as a core capability in (Eds) Moingeon, B. and A. Edmondson, Organizational learning

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and competitive advantage, Sage Publications, London, pp38-55. Dixon, N. M. (2000) Common knowledge: How companies thrive by sharing what they know, Harvard Business School Press, Boston, Massachusetts. Drucker, P. F. (1967) The effective executive, William Heinemann, London. Drucker, P. F. (1993) Post-Capitalist Society, Harper Business, New York. Earl, M. J. (2001) Knowledge management strategies: Towards a taxonomy, Journal of Management Information Systems, Summer, 2001, vol 18 (5), pp218-233. Fruin, W. M. (1997) Knowledge works: Managing intellectual capital at Toshiba, Oxford University Press, Oxford. Gerlach, M. L. and J. R. Lincoln (2000): Economic organization and innovation in Japan: Network spin-offs and the creation of enterprise, in (Ed) von Krog, G; I. Nonaka and T. Nishiguchi (2000) Knowledge creation: A source of value, Macmillan Press, London, pp151-196. Geertz, C. (1974) From the native’s point of view. Bulletin of the American Academy of Arts and Sciences, 28, pp27-45. Gibbons, M; C. Limoges; H. Nowotny; S. Schwartzman; P. Scott and M. Trow (1999) New production of knowledge, Sage Publications, London. Handzic, M. (2001) "Knowledge Management: A Research Framework", in Proceedings of the 2nd European Conference on Knowledge Management (ECKM 2001), 8-9 November, Bled. Huysman, M and D. de Wit (2002) Knowledge sharing in practice, Kluwer, Dordrecht. Kidwell, J; Vander Linde, K M and Johnson (2001): Applying corporate knowledge management practices in higher education. (Ed) Bernbom, G: Information alchemy: The art and science of knowledge management. Jossey-Bass, San Francisco, pp1-24. Klösgen, W and Zytkow, J. M. (1996) Knowledge discovery in databases terminology, in (Eds) Fayyad, U M; G. Piatesky-Schapiro; P Smyth and R Uthurusamy, Advances in knowledge discovery and data mining, AAAI Press/MIT Press, Menlo Park, California, pp573-592. Kludge, J.; W. Stein and T. Licht (2001) Knowledge unplugged: The McKinsey and Company global survey on knowledge management, Palgrave, London. Lickert, R. (1932/1967) The method of constructing an attitude scale, in (Ed) Fishbein, M. Readings in attitude theory

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and measurement, John Wiley, NY, pp9095. Liebowitz, J. (2000) Building organisational intelligence: A knowledge management primer, CRC Press, N Y. Machlup, F. (1962) The production and distribution of knowledge in the United States, Princeton University Press, Princeton. Macintosh, A. and J. Stader (1999): Knowing who know what – skills and capability ontologies. International symposium on the management of industrial and corporate knowledge. ISMICK99 Preproceedings. School of management of Erasmus University of Rotterdam, Rotterdam. Malhotra, Y. (2000) From information management to knowledge management: “Beyond the hi-tech hidebound” systems. (Eds) Srikantaiah, T K and M. E. Koenig Knowledge management for the information professional, pp37-61. Mann, M. M.; R. M. Rudman; T. A. Jenckes and B. C. McNurlin (1991) EPRINET: Leveraging knowledge in the electric utility industry in (Ed) Prusak, L. (1997) Knowledge in organizations, ButterworthHeinemann, London, pp73-97 Newell, S; J. C. Huang, R. Galliers and S. L. Pan (2002) Implementing enterprise resource planning and knowledge management systems in tandem: Fostering efficiency and innovation complementarity, Information and Organization, vol 13(1), January 2003, pp25-52. Nonaka, I. and H. Takeuchi (1995) The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Press, New York. O’Dell, C. and C. J. Grayson (1998) If Only we knew what we know, Free Press, NY. Oppenheim, A. N. (1992) Questionnaire design, interviewing and attitude measurement, New edition, Pinter, London. Porat, M. (1977) The information economy: Definition and measurement, OT Special Publication 77-12(1), US Department of Commerce, Washington DC, May 1977. Pratt, M. L. (1986) Fieldwork in common places, in (Ed) Clifford, J. and G. E. W. Marcus, Writing culture: The poetics and politics of ethnography, University of California, Berkeley, pp27-50. Schuman, H. and Presser, S. (1981/1996) Questions and answers in attitude surveys: Experiments on question form,

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wording and context, Sage Publications, California, Thousand Oaks. Savary, M. (1999) Knowledge management and competition in the consulting industry, California Management Review, 1999, 41 (2), pp95-107. Schultze, U. (2000) A confessional account of an ethnography about knowledge work, MIS Quarterly, 24 (1), March, 2000, pp341. Snowden, D. (1999) A framework for creating a sustainable programme, in (Ed) Rock, Stuart: Knowledge management: A real guide. Caspian Publishing and IBM, London, pp7-17. Snowden, D. (2002) Complex acts of knowing: paradox and descriptive self-awareness, Journal of knowledge management, 6 (2), pp100-111. Starbuck, (1992) Knowledge by knowledge intensive firms in (Ed) Prusak, L. (1997) Knowledge in organizations, ButterworthHeinemann, London, pp147-175. Stein, E. W. (1995) Organisational memory: Review of concepts and recommendations for management. International Journal of Information Management, 15 (1), pp17-32. Stern, D. (1996) Human resource development in the knowledge-based economy: Roles of firms, schools and governments, in (Ed) Neef, D. The knowledge economy, Butterworth-Heinemann, London, pp249265. Stewart, T. A. (1997) Intellectual Capital: The New Wealth of Organisations, New York, Doubleday. Trauth, E. M. (1997) Achieving the research goal with qualitative methods: Lessons learned along the way, in (Eds): Lee, A. S. Liebenau, J. and DeGross, J. I. Information systems and qualitative research, Chapman and Hall, London, pp225-245. Tukey, J. W. (1977) Exploratory data analysis, Addison-Wesley, Reading, Massachusetts. Van Maanen, J. (1988) Tales from the field: On writing ethnography, University of Chicago Press, Chicago. Weick, K. E. (1979) The social psychology of organizing, Second edition, AddisonWesley, Reading , Massachusetts. Wenger, E.; R. McDermott and W. M. Snyder (2002) Cultivating communities of practice, Harvard Business School Press, Boston, Massachusetts. Wiig, K. M. (1995) Knowledge management: The central management focus for

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intelligent-acting organisations, Schema

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Press, Arlington, Texas.

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A New Insight into the Valuation of Start-ups: Bridging the Intellectual Capital Gap in Venture Capital Appraisals Blanca María Martins Rodríguez Polytechnic University of Catalonya, Barcelona, Spain [email protected] Abstract: The emergence of a New Economy has brought consensus to the idea that innovation skills and capabilities are the main drivers of a firm’s wealth generation capacity. The principal role that venture capital played in boosting American economic productivity and growth during the 1990s, fuelling innovation and the creation of new firms is well known. However, the huge number of bankruptcies among high-tech companies in 2000 generated general distrust in financial markets worldwide. In particular, it caused great reluctance to invest in start-up companies and led investors and academics to question and take an in-depth look at existing valuation procedures. Building upon the concept of competitiveness of Man et al. (2002) and the premise that a firm’s success is the result of appropriate strategy formulation and implementation (Grant, 2002), the present paper develops the start-up general valuation model (SGVM) as a first step to improving the investment appraisal of start-up companies and promoting a more effective allocation of resources in the economy. Keywords: start-ups, valuation, venture capital, business model, top management team, intellectual capital.

1. Introduction The “technology bubble burst” of April 2000 has marked a significant change in the behaviour of world stock exchanges, causing investors to question the transparency of information regarding the risks involved and, in particular, the way in which firms are evaluated when going public. Moreover, the period of analysis and reflection that began after venture capital investments plummeted has also indicated a need for revision of traditional financial valuation methods (discounted cash flow, price to earnings, net present value, etc.). Academics and practitioners alike have yet to provide new evaluation methods and tools that allow for more systematic methods of appraising the possible success of new ventures. The start-up general valuation model (SGVM) is an attempt to fill this gap. Because the present business environment is one in which a firm’s competitiveness and capacity to create value is very much dependent on its ability to deploy and re-create its intangible knowledge assets in innovative ways (Lev, 2001; Sullivan, 2000), and because a start-up is so dependent on intangibles (a business formula and the top management team’s capabilities and personalities), any such new valuation approach must be based on intellectual capital. Furthermore, the turbulence and complexity of the environment demands an approach that allows for a better understanding of the specific dynamics of a given start-up company. An improved estimation of a company’s value must combine several theories and approaches, including strategy, entrepreneurship, and psychology.

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The SGVM consists of two parts: (i) the startup business model benchmark (SBMB); and (ii) the top management team scoreboard (TMTS). The SBMB builds upon Hedman and Kalling’s (2001) work and Viedma’s (2000) intellectual capital benchmarking system (ICBS), and aims to predict a start-up’s competitive capability and value-creating capacity vis-à-vis the best world-class competitor. The TMTS aims to evaluate the most decisive factor in the success of any start-up – the top management team (TMT). The TMTS thus appraises the TMT’s competencies, commitment, values, and attitudes – not only in terms of the abilities and experience of the members of the team, but also in terms of their personality characteristics. In doing this it relies on Cattell’s 16 personality factors – commonly known as “the 16PF” (Karson et al., 2002). In addition, the work of Erikson (2002), Mayo (2001), Ulrich (1998), and Herron and Robinson (1993) is of significance. The remainder of the paper is structured as follows. Section 2 is a short review of venture capital firms’ functions and objectives and common valuation methods. Section 3 briefly outlines the new business environment and the need for more integrative approaches. Section 4 introduces the SGVM (including its theoretical framework, components, and general functioning). Section 5 notes the main limitations of the study and possible future research lines. Section 6 presents the main conclusions.

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2. Venture capital value added and valuation methods Start-ups’ own characteristics (lack of history, a promising idea, a bundle of competencies, among others) make venture capital the natural refuge for new ventures in search of financial support. This being the case, there are some elements relating to the functioning, objectives and valuation methods of these firms that we must understand before aiming to improve the latter and ultimately the investment cycle and allocation of resources. According to Triantis (2001), a venture capitalist or a venture capital firm is a financial intermediary between investors and start-up firms that are too small and too volatile, and have insufficient history to be able to secure financial resources directly from the capital markets. For early stage firms, venture capital is a source both of financing and of strategic advice. This advice and the active coaching of the firms in which they invest is probably what distinguishes venture capital financing from other, more traditional mechanisms such as capital markets or debt contracting (Gompers and Lerner, 1999). Furthermore, those who invest in start-ups (characterised by extreme volatility and operations in new or emerging market segments) aim to obtain a return on their investment around five times the capital initially invested over a period that averages 56 years. Such high returns in turn demand some special features at start-up including: i) potential to grow rapidly and generate gross margins of around 40%, ii) the ability to go public or merge in the mid-term at a high P/E, and iii) a strong leader and a top management team with entrepreneurial and managerial experience, perseverance, commitment, imagination, and integrity. The aforementioned aspects, generally screened through business plans, financial statements, projected cash flows, and other financial tools (internal rate of return, net present value, economic value added, etc.) together with other informal sources (potential clients, suppliers, etc.) and insider information, guide venture capitalist investment decisions. However thorough this screening is, there is clearly a lack of systematic analysis of the whole valuation process. Therefore, if investors and analysts learned anything from the share price collapse of the year 2000 (especially that of the Nasdaq), it was the imperative of turning attention to the firm’s true sources of sustainable competitive advantage and value creation (Koeller, 2001). The development of “sustainable” competitive advantage is by no

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means only a matter of competencies and good strategy formulation (the content of the business plan) but also one of leadership capability, staying power, commitment, and the values and attitudes of the people in charge of bringing the business venture to fruition. A survey of sustainability carried out by the New Economic Foundation (The ∑ Project, 2001) highlighted in section 3.5 “… shareholders concerned about risk management will increasingly demand evidence linking the quality of leadership with the creation of longterm shareholder value. They will want to know about the purpose, values and strategy of the organisation in order to form their judgement of the company’s long-term potential (the socalled ‘success jigsaw/recipe’)” (p.30). Venture capital (VC) played an important role in the economic growth, cultural change and financial “exuberance” experienced by the United States during the last decade (especially in the period 1997-2000). Although, to a lesser extent, Europe was also affected by this VC boom (i.e. early-stage investment rose to €6.7 billions in 2000, an amount 15 times greater than that of 1995), the European Venture Capital Association (EVCA, 1996 and 2001) argues that venture capital-backed companies stimulate the economy through creation of jobs, exceptional growth rates, heavy investment, and international expansion. A recent survey carried out by Hellmann and Puri (2000) across 149 recently formed companies in the Silicon Valley suggests that VC stimulates innovative activity. Thus, a startup financed by venture capital needs less time to bring a product to market. The report of the EVCA (2001) also shows that venture-backed companies’ commitment to R&D expands Europe’s technical expertise and resources, and strengthens its competitive position in world markets. International competitiveness is also enhanced by significant growth in export sales. With this brief discussion of some VC figures and their impact on innovation and economic expansion we intended to highlight the importance, not only for start-ups, but also for a nation’s growth and prosperity, of investment flowing back to venture capitalists and to new ventures. We believe that improving the way in which these firms are appraised could contribute to restoring investors’ trust and increasing the level of financial inflows allocated to these activities.

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3. The new business environment and the need for more integrative approaches The business environment at the beginning of the twenty-first century is characterised by an acceleration of changes already present in the preceding decade – global markets, shorter innovation cycles, knowledge-driven organisations, the leading role of end consumers, the importance of new information and communication technologies in intra-firm and inter-firm relations and so on. In such a context, the rapidity with which new knowledge must be assimilated makes it difficult for a firm to generate such knowledge internally, forcing it to create networks with suppliers, clients, and even competitors (Venkatraman and Subramaniam, 2002). The external pressures of the environment thus push organisations towards an increasing internal complexity (Lowendahl and Revang, 1998). In the Knowledge Age, when products and firms survive or die depending on their capacity to effectively and efficiently manage their intangible assets, knowledge and innovation capability have become the main value drivers of organisations. However, the increasing importance of knowledge considerations does not simply mean that a new variable ought to be introduced when developing or analysing the firm’s value chains and strategies. It also means that market and competence rules have been substantially modified making us rethink completely the firm’s whole value chain. In this sense, the capacity of a firm to manage its knowledge assets has become a key factor in the firm’s potential for success and survival (Bontis, 1996), as well as its wealth creation capacity, which is a sign of its people’s knowledge and competencies. While this fact is particularly relevant for start-ups (because of their intangible nature), from a venture capital viewpoint, the huge gap between book values and market values recognises that the market also puts a premium on these capabilities. This change in strategic orientation towards knowledge assets requires a recognition that the creation of a competitive advantage depends on the ability of a firm to create, use, transfer, and protect its intangible assets – assets that are scarce, non-tradeable, and difficult to imitate (Grant, 1996, 2002; Barney, 1991). In these changed times, the resourcebased view (RBV) of assets emerged as the natural answer within management theory, and with this view came a series of models (including Skandia Navigator, Balanced

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Scorecard, and Intangibles Assets Monitor) designed to manage this new form of capital. Venture capital firms pursued this process with particular intensity. They were the great drivers and enablers of the innovative thrust of the mid-1990s (Lerner, 2001) and they produced (generated?) unprecedented growth in stock exchanges worldwide. However, when the economic “bubble” was dramatically punctured in 2000, these same firms became the scapegoats. Questions arose as to whether the information systems and methodologies in use produced realistic evaluations of the likely success of start-up companies, and this led to a recognition of the need to create sustainable business models (Aidar et al., 2001).

3.1

The need for a new strategic approach

The RBV, at least as it was conceived initially, does not offer a satisfactory answer to the creation of sustainable competitive advantage, because it is notably static (Eisenhardt and Sull, 2001; Eisenhardt and Martin, 2000) and/or because of its lack of a suitable treatment of the firm-industry duality (Foss and Knudsen, 2001). A more dynamic view therefore began to emerge (Spanos and Lioukas, 2002; Teece et al., 1997). A similar process was observed in the field of intellectual capital – giving rise to management and measurement models that were based on the concept of dynamic capabilities (Teece et al., 1997), which gave greater relative weight to the competitive business context in its evaluations. These models approached this either through benchmarking the firm’s essential competencies against those of the best world-class competitor (Viedma, 2000) or through the introduction of a competitiveness factor in the valuation calculus (Andriessen and Tissen, 2000). However, the extreme centrality of both the RBV and these early intellectual capital measurement models in the firm’s resources and capabilities internally harms the concept of a firm’s success in terms of good strategy formulation and implementation (Grant, 2002) as it attempts to explain the creation of sustainable competitive advantage as a causeand-effect relationship between the “stock” of these resources and the firm’s ability to generate such resources. To build a corporate strategy with the RBV as the only theoretical foundation focuses the firm unilaterally (and dangerously) on ”formulation” when, in fact, what the market values is the result of the

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deployment of these unique resources and capabilities through the firm’s specific actions. This is essentially a problem of implementation and the activity-based view (ABV) of a firm as a main theoretical approach. Although the present resources and capabilities of a firm play a major role in the development of strategies for the creation of competitive advantage (Spanos and Lioukas, 2002), being able to explain at a given point in time a firm’s superior performance and greater market value hardly orients that firm towards sustainability – unless there is an appropriate consideration of what the company actually does with those resources. Such an analysis requires other theories and approaches. The concept of competitiveness, which is inseparable from the concept of competitive advantage, demands a consideration not only of what assets are necessary to generate a superior performance, but also of the process required to carry this out (Man et al., 2002). Finally, the fact that firms transcend their own apparent boundaries (and those of their particular industries) in searching for new opportunities means that the natural unit of strategic analysis is no longer that of ”the firm”. Rather, it is a more comprehensive unit that allows new configurations of value-creating factors and processes. Amit and Zott (2001), for example, have proposed the “business model” as an alternative unit, and have spoken of a new paradigm anchored in strategy (value chains, strategic networks, and specific resources and capabilities) and entrepreneurship.

4. The SGVM: theoretical framework, main components, and functioning The start-up general valuation model (SGVM) is applied to a start-up firm without history, and to its bundle of intangibles. The SGVM seeks to systematise a process whereby an estimation of the probable success of such a start-up can be made with greater confidence. Any consideration of a firm’s performance and its potential to obtain rents and create greater value must take into account the presence of sustainable competitive advantage and the concepts of competitiveness and competency. Competitiveness is usually taken to mean superior performance vis-à-vis competitors, evaluated in the long term. Competency is usually taken to mean the TMT’s individual and collective competencies to lever the existing resources and competencies, and to develop

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new ones, in a process of continuous learning. Although the term ”competitive advantage” has a relative and external nature, its construction has mainly an internal focus – either on the firm’s stock of resources and capabilities and/or on the actions it decides to carry out. In a global knowledge economy, it is less easy to explain the differences among the performances of firms only by differences in the possession of resources (tangible or intangible). It is not only what the firm has (RBV), but what the firm does (ABV) (Haanes and Fjestaldt, 2000) that will have an impact on the value perceptions of consumers and other stakeholders, and ultimately on the firm’s value. In the case of start-ups, the high failure rate observed during the early years means that these considerations acquire an even greater importance. Because a start-up does not have a history, and because it has not yet developed ties with the environment, the deployment of resources and capabilities that it effects today will more than any other factor determine its potential to attain success. Therefore, any evaluation model used to capture the potential of a given start-up to generate market opportunities, and to take advantage of those opportunities, must necessarily involve both an RBV approach and an ABV approach. The SGVM takes into account these different streams of thought and systematically improves the start-up valuation process by considering its value-creation mechanisms. The general scheme of the SGVM was developed as follows: The premise that a firm’s success results from good strategy formulation and implementation (Grant, 2002); For the purposes of the model, strategy was defined, in its formulation and implementation aspects, as the ”leading wire” around which resources, capabilities, and activities are aligned in a dynamic exchange of information and knowledge with the environment for the attainment of sustainable competitive advantage that contributes to superior performance (Spanos and Lioukas, 2002; Amit and Shoemaker, 1993); and These elements were deployed in two constructs that represent the SGVM’s basic instruments of evaluation and analysis: (i) the SBMB, which evaluates the start-up’s business model vis-à-vis the best world-class competitor (Viedma, 2000; Hedman and Kalling, 2001); and (ii)

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the TMTS, which aims to determine the TMT’s potential to make the proposed business formula work effectively and be correctly implemented, thus taking the start-up to fruition and profitable growth (Erikson, 2002; Mayo, 2001; Ulrich, 1998; Herron and Robinson, 1993). In broad terms, SGVM’s content and objectives do not differ much from those deemed to be significant by venture capitalists or investment banks. For the latter, the focus in the due diligence stage is on the firm’s corporate strategy execution, followed by management

quality and credibility, strategy quality, innovation capability, and finally the firm’s ability to attract and retain a competitive and talented workforce (Andriessen and Tissen, 2000). All these elements are at the very core of both SBMB and TMTS. Thus, SGVM’s main contribution is to identify, deploy, and measure a bundle of intangibles that might account for the start-up’s possible success, in a way that allows a systematic and competitive assessment. Figure 1 illustrates this scheme.

Fig. 1 – Strategy and a start-up’s success

INTERNAL SCOPE

Location Formulation

Vision & Mission

Industry Business Model (SBMB)

SUCCESS STRATEGY

?

Implementation

Top Management Team (TMTS)

EXTERNAL SCOPE

Why do we value separately the start-up’s business model and the top management team? After all, the founding team is a part (albeit an essential one) of the organisational resources and capabilities and therefore figures among the SBMB’s objects of analysis. However, there exists a powerful reason that is directly linked to the role the TMT plays in a start-up. The success of a start-up is totally dependent on the competencies and commitment of the TMT, and this capacity conditions the potential value created in the first instance by the firm’s business formula. The TMT has the capacity to lever or destroy the possible value embedded in the start-up’s business formula; it does not matter how good the start-up’s strategy formulation is if the

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people in charge of executing this do not have the competencies, personality characteristics, and values required to bring the firm to fruition. Both the SBMB and the TMTS are established by extensive questionnaires that give rise to two indices: the Start-up’s Business Model Index (SBMI) and the Top Management Team’s Index (TMTI). These are later combined into a single measure, the Start-up’s General Index (SGI). The evaluation is thus a two-stage eliminatory process whereby the non-approval of the start-up’s business formula (as determined by the SBMB) stops the whole process, thus precluding TMT evaluation. (See Figure 2.)

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Fig. 2 – Valuation indexes obtention and the investment’s decision

Business Model (SBMB)

SBMI

(X)

Top Management Team (TMTS)

TMTI

SGI

INV.

? Others

SUBMI = Startup Business Model Index TMTI = Top Management Team Index SGI = Startup Global Index

Note: The “others” in the circle refers to other elements, apart from the start-up’s potential, that could be taken into account in the investor’s final decision (i.e. risk profile, a particular investment portfolio structure, etc.).

4.1

Start-up business model benchmark (SBMB)

The SBMB aims to evaluate the business model in terms of its consistency with the firm’s internal and external strategy. In doing so, it departs from the start-up’s mission and strategic vision and develops an evaluation process in two stages: It identifies the start-up’s potential core competencies from the resources, capabilities, and activities that the TMT intends to develop; it then evaluates them against the present core competencies of the best world-class competitor’s business formula (internal view); and It evaluates a series of factors, most of them common to those of the industry competitive analysis of Porter (1985), with a special emphasis on the networks that the firm develops (external view). Identification and evaluation of the start-up’s potential core competencies thus constitute the main body of the analysis. This assesses the consistency or ”fit” between the start-up’s intangible assets and the business model it has proposed; in brief, identification and evaluation of the start-up’s potential core competencies give credibility to the proposal. Nevertheless, the unit of analysis and comparison is the business model. The index that is obtained at the end of the process of benchmarking refers to this unit of analysis, and the other components of the system of which the competencies are an essential part, and has a largely explanatory value.

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The SBMB’s main components are shown in Figure 3. The present discussion considers only those elements that represent a change from existing models, or those that assume special relevance in the case of start-ups. For the remaining elements, readers are referred to the two basic models that served as a source for the development of certain aspects of the SBMB (Hedman and Kalling, 2002; Viedma, 2000). The factors that deserve some special attention are: Industry. Of special importance are considerations of the stage of the industry life cycle and the environment’s relative stability or dynamism. Location. This evaluates the proximity to the market, whether the firm belongs to a cluster, and so on. The social structure of the location’s surroundings plays a key role in the opportunities perceived by the firm, and in the strategic actions that it ultimately takes (Gulati, 1999). These matters are even more significant in the case of start-ups – given given their recent creation. Complementary business assets (Sullivan, 2000). The embryonic nature of a start-up, without an established product and with an image under construction, makes commercialisation an especially delicate process and a matter of great importance for its future performance. Networking. This refers to the framework of relations that the firm weaves with its environment in determining the scope of

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its products and in evaluating market factors. “Network resources” (Gulati, 1999) have the capacity to lever the total value created by the firm, in addition to being a permanent flow of knowledge acquisition and source of learning, allowing it to share risks and thus reach its objectives (Gulati et al., 2000). Business model. This has a somewhat different nature from those noted above,

in that it is a derived component. Its value could therefore be different from that which results from the sum of its components – that is, it can increase as its configuration becomes more difficult to imitate, to transfer, and to substitute, (Zott and Amit, 2002). It is a key indicator of the TMT’s strategic capacity.

Fig. 3 – SBMB main components SUCCESS (1) (profitable growth) Demand

PRODUCTS MARKET NETWORKING

Industry / Location

Market business opportunities

STARTUP’S BUSINESS MODEL (SBM)

GAP

BEST COMPETITOR’S BUSINESS MODEL (BCMB)

Potential supply

Supply

Processes and Activities

Processes and Activities

Value chain (core activities)

Value chain (core activities)

Potential core competencies

Infrastructure

Core competencies

Complementary business assets

Infrastructure

Complementary business assets.

FACTORS MARKET / NETWORKING

(1) This “success” refers exclusively to the start-up’s business formula superiority. The model is completed with TMT’s appraisal.

4.2

Top management team scoreboard (TMTS)

When venture capitalists speculate on a startup, they are, in fact, speculating on the TMT and its ability to formulate and execute the business strategy. The TMTS is therefore an instrument that is intended to contribute to venture capitalists’ investment decisions by providing the information required to determine whether the TMT has the competencies, values, and attitudes necessary to succeed in the implementation of the business formula (that has already ”proved” to be effective) – such that the investor stays within his or her “return for risk” parameters.

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Traditionally, the evaluation of the potential of a start-up’s TMT includes an assessment of such aspects as: (i) proven antecedents of its experience; (ii) capacity to execute the business plan; (iii) known background; (iv) areas of expertise; (v) leadership capability; (vi) industry knowledge and contacts; (vii) integrity; and (viii) passion and dedication to the job. All of these elements are easily transferable to the duality of competencies and commitment as reflected in more structured theoretical approaches – under the concepts of intellectual capital (Ulrich, 1998), talent (Jericó, 2001), or entrepreneurial capital (Erikson, 2002). Any attempt to evaluate the potential of

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the TMT to take the start-up to fruition must incorporate an assessment of two elements: (i) the successful implementation of the business model; and (ii) the presence of the necessary vision and enthusiasm for establishing and maintaining the firm’s competitiveness. In turn, the set of competencies and commitment that the TMT brings to the start-up depends upon the values and attitudes of each of its members. This constitutes the third and last component valued by the TMTS. (See Figure 4.).

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potential success, considers “commitment” to be a different factor from that of “competencies”, and analyses it within the separate factor “commitment”. In relation to the measurement of the influence of the TMT in the start-up’s performance, we consider Ulrich’s (1998) creation of a multiplicative function of competencies and commitment to be more accurate – for example, when compared with that of the sum of both elements as stated in Mayo’s "Human Capital Monitor" (HCM) (2001). The achievement of a superior performance requires the simultaneous presence of both elements. The TMT’s competencies are the starting point of the firm’s success but its commitment is the component that determines whether those competencies will be effectively channelled to produce the expected results.

The TMTS is organised around the axis of “competencies x commitment” of Ulrich (1998), and the content of each factor is fundamentally an adaptation of the competency areas of Man et al. (2002). The main difference from the approach of Man et al. (2002) is that the TMTS, because it takes Ulrich’s definition of intellectual capital as a proxy of the TMT’s Fig. 4 – TMTS global functioning

TMT’s POTENTIAL SUCCESS

Competencies

f1 C1

H1

P1

f2 C2

H2

f3 C3

f4 C4

f5 C5

P2

Values

Commitment

X

H5

P5

Attitudes

X

fi : competency adjustment factor; (fi = o, ..., 1) Ci: competency areas in which TMT’s members have to be competent Hi: skills, knowledge and experience Pi: TMT’s personality characteristics necessary for the development of Ci

4.2.1 Competencies and commitment The great majority of attempts to measure the influence of the TMT on a firm’s performance fall into one of two groups: (i) those that are exclusively based on the behaviour of the TMT’s demographic variables (sex, age, experience, education); and (ii) those that analyse the characteristics of personality in an attempt to establish a cause-and-effect relationship between both types of variables

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(those relating to demography and personality and those of performance). However, the lack of conclusive results within both the first group (van Olfen and Boone, 1997) and the second (Herron and Robinson, 1993) makes it difficult to justify a model that evaluates the TMT’s probable success only on the basis of the predictive capacity of these variables considered in isolation.

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In contrast, the TMTS adopts a process approach and defines the competencies as the basic unit of evaluation – an approach similar to that of Man et al. (2002) who analysed the influence of the entrepreneur on the competitiveness of small to medium enterprises (SMEs). This approach means that the model possesses greater conceptual clarity and explanatory potential in assessing a firm’s potential because it takes into account the personality characteristics, skills, knowledge, experience, training, education, and background of individual TMT members – rather than mere demographics. Apart from the conceptual differences noted above, and other minor ones of denomination; the areas that the TMTS evaluates are essentially those of Man et al. (2002). However, its contents (abilities, experiences, knowledge, and personality) are the result of having adapted these components to the startup’s specific reality. The TMTS begins by identifying which abilities and personal characteristics have greater influence on the start-up’s performance, and then transfers them to five selected competency areas. Finally, the personality characteristics that sustain that set of abilities are translated to Cattell’s 16PF to allow measurement. Because the model focuses on anticipating the startup’s performance, and because the degree to which a certain behaviour (competency in action) leads to a better performance depends, in part, on whether the firm’s specific environment demands that type of behaviour (Herron and Robinson, 1993; Cooper et al., 1994), the TMTS introduces the concept of a ”competency adjustment factor” – a factor that weighs the relative importance of each competency according to the objectives of the SBM and the start-up’s environment. In favour of this ”adjustment factor” we could cite Baron and Markman’s (2003) recent findings on entrepreneurs’ social competency and their relevance to financial success. Interestingly, the authors conclude not only that social competency does matter to the entrepreneurs’ financial success but also that the type of abilities that are significant for that competency varies according to the industry to which the firm belongs (i.e. social adaptability was relevant for the cosmetics industry but it was not significant for high-tech industry). The TMTS reflects the fact that the TMT, to be successful in translating the business formula to a business recipe, must show competency in the following areas:

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Opportunity. The promptness of the TMT to commit themselves to a new objective and to take concrete action rapidly whenever a better opportunity emerges (Brown et al., 2001). Innovation. Man et al. (2002) include this within the broad category of “conceptual competencies”. Innovation evaluates the TMT’s knowledge and abilities with respect to new products and technologies, and its capacity to create an appropriate environment for innovation. Networking. This evaluates the TMT’s capacity to develop the start-up’s social capital, as much as its own social capital. The importance of this competency is greater the higher the level of networking in the start-up industry, which reflectsthe factors assessed by the SBMB. Management. This is similar to the organisational competencies of Man et al. (2002). In the case of a start-up, the TMT’s competencies in the financial, technical, market development, and managerial areas are of great importance. Strategic. This refers mainly to the capacity of the TMT to establish, evaluate, and implement the start-up’s strategy, and also its ability to introduce the necessary strategic changes to maintain success. Its evaluation includes the final score obtained by the SBMB. Commitment is the other key variable in the evaluation of the TMT’s likelihood of success. By analogy with the SBMB (above) in which it was asserted that resources and capabilities, in themselves, do not have the capacity to generate sustainable competitive advantage (but that these result from the application of strategic activities to the start-up’s core resources and competencies), it can be said that the TMT’s level of commitment as applied to its set of competencies determines the potential success of this group of people and, ultimately, of the start-up. This second factor of commitment poses greater difficulties from an evaluation point of view. Ulrich (1998) did not explore the measurement of this factor in any detail. Commitment, per se, is not measurable, and it can be assessed only through behaviour. It is a reflection of the abilities and the personality of an individual faced with a specific objective or situation. Thus, the TMTS’s method of approaching this assessment was to identify possible means of estimating commitment in the theory and to relate these to Cattell’s 16PF

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to allow measurement. Two factors are assessed in the model: (i) the professional and personal strategic priorities of each of the TMT’s members at the moment of start-up; and (ii) the sustained effort of which each individual is capable. The first allows a determination of the extent to which the startup project is perceived to be capable of satisfying the person’s priorities. Individual motivation is thus taken to be an approximation of individual commitment. As Herron and Robinson (1993: 289) observed, “motivations determine what abilities are exerted, when each one is exerted, and in what amount it is exerted”. With respect to the second factor, the estimation of the TMT’s sustained effort provides a measure of the capacity of individuals to implement the startup’s business model successfully, even in the face of adversity. The evaluation of both elements gives rise to a commitment index that is later incorporated in the TMTS final index. 4.2.2 Values and attitudes The incorporation of values and attitudes creates a sort of ”supporting platform” that adds consistency to the evaluation of competencies and commitment. In this, the TMTS follows the HCM of Mayo (2001: 90) who stated that “The way in which the core (personal behaviours, business and professional know-how and networks of contacts) is demonstrated is then conditioned by the attitudes and values that the person holds – these these being the most difficult to change.” The values and attitudes of the managers of a start-up have a direct influence on the strategic decisions they make, and hence on the future of the organisation. The inclusion of these two components (values and attitudes) into the general scheme allows venture capitalists to determine whether the instrumental values that underlie the TMT are consistent with the development of an organisational culture that fits the business formula and the demands of the start-up’s new competitive environment, and whether the values of the TMT are consistent with those of the venture capitalist who is contemplating investment. The latter is not a minor consideration, because an investment decision marks the beginning of a long relationship – and the key to such a relationship is a shared set of values to sustain this union. With regard to the TMT members’ personal values, we gave special attention to “integrity” as it plays an essential role in

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shaping the organisation’s proceedings and culture, and contributes to its smooth functioning and strengthening of stakeholders’ confidence in the organisation (Shaw, 1997), which is particularly relevant for a start-up, whose image and reputation are just beginning to develop. On this particular point, Kaptein’s (2003) “Diamond of managerial integrity”, through its conceptualisation of ”the manager as a person of integrity”, as someone authentic, reliable, and constructive, was of great help in the process of identifying and depicting the “right” personality characteristics that might contribute to measure this key element. The main instruments used to evaluate these factors are: (i) a questionnaire on values; and (ii) a composition of personality factors (16PFbased) intended to assess the presence of a positive attitude in the TMT’s members.

5. Limitations and future research One of the main limitations of this work is the almost total absence of empirical research in the field of start-ups. This means that many of the variables included in the present analysis of start-ups (core competencies of TMTs and organisations, commitment, attitudes) had to be deduced. Further research could therefore be oriented towards in-depth studies of the development of start-ups from conception to initial public offering or sale. Empirical evidence from such studies would enable improvements to be made in the SGVM methodology. Some of the issues to be addressed include: (i) the relevant competencies of a TMT for this stage of the firm’s life; (ii) the relative weight to be accorded to commitment in an estimation of the TMT’s success; (iii) the most appropriate elements in a TMT’s profile; (iv) the adequacy and predictive capability of the chosen personality characteristics to deduce TMT’s competencies in each competency area; and (v) whether the overall approach of the SBMB (especially the emphasis put on the identification of core potential competencies) is the most appropriate approach to take for accurate prediction of a start-up’s likely performance. Moreover, these points should be addressed if possible in relation to both successes and failures. More in-depth research and analysis of the dynamics and specificities of start-ups is necessary if the goal is to improve venture capitalists’ assessment processes and valuation methods. The benefits are two-fold:

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At a macro-economic level, it could be said that the relevance of the subject is established by the research scope itself (venture capital and start-ups). Venture capital investment (especially at an early stage) is a particularly dynamic subset of financial markets and of great strategic significance given its positive impact on a region’s innovation capabilities, economic growth, employment and quality of life. At the micro level of the venture capital firm, we could simply say that improving knowledge in this area responds to a specific requirement of financial markets – to be able to rely on better assessment and valuation methods.

6. Conclusion The huge number of bankruptcies among hightech companies in 2000 turned the spotlight on start-ups and the ways in which venture capitalists were making their investment decisions. The weaknesses of the evaluation process included the lack of a systematic approach, absence of rigour in gathering basic information and excessive use of intuition. The SGVM, through its two instruments (SBMB and TMTS), is an attempt to address the problem of evaluation by assessing the same sources that are used in a start-up’s value-creation process – the business formula and the TMT’s competencies and commitment. In addition, because one of the main contributions of venture capitalists to the healthy development of a start-up is the provision of professional know-how and support to strategic decision making, the systematic application of the SGVM could be a helpful tool which contributes to a reduction in the financial risks associated with new ventures. Special emphasis has been placed on the TMT as a set of competencies and a source of commitment that has the power to lever or to destroy the potential value created by the startup’s business model. The major improvement of the TMTS compared with extant models is its incorporation of the measurement of personality factors within the top management team, in addition to traditional estimation of members’ skills and abilities. The rapidity with which globalisation and new technologies have changed the basis of competition has confronted organisations with complex problems. The tackling of these problems demands a combination of different approaches and theories. In such a setting, a framework that brings together different

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streams of thought (RBV, AVB, social capital, entrepreneurship, psychology, and so on) is likely to have a better chance of correctly predicting the success or failure of a start-up. The multidisciplinary nature of the SGVM is thus likely to improve the risk-management capabilities of investors, and, ultimately, to improve the allocation of economic resources for the well being of the global society in which we live. Finally, the collapse of share prices in the second half of 2000, which still persists, makes us believe that we could reasonably expect a higher level of commitment and effort from academics, investors and entrepreneurs in order better to understand firms’ value creation processes in the Knowledge Economy.

References Aidar, F., Gallagher, R., Grieve, A., Willer, B. and Cho, M. (2001) “Lessons for venture capitalists. A new disciplined approach”. Kellogg Tech Venture 2001 Anthology, [online] Kellogg Institute, Northwestern University, http://www.ranjaygulati.com/new/research /LESSONS.pdf Amit, R. and Schoemaker, P. (1993) “Strategic assets and organizational rent”. Strategic Management Journal. Vol. 14, pp. 33–46. Amit, R. and Zott, C. (2001) “Value creation in e-business”. Strategic Management Journal. Vol. 22, pp. 493-520. Andriessen, D. and Tissen, R. (2000) Weightless Wealth. London, Prentice Hall. Barney, J. (1991) “Firm resources and sustained competitive advantage”. Journal of Management, Vol. 17, pp. 99–120. Baron, R.A. and Markman, G.D. (2003), “Beyond social capital: The role of entrepreneurs’ social competence in their financial success”. Journal of Business Venturing. Vol. 18, pp. 41-60. Bontis, Nick. (1996) “There’s a price on your head: Managing intellectual capital strategically”. Business Quarterly. Summer, pp. 41-47 Brown, T. E., Davidsson, P. Y. and Wiklund, J. (2001), “An operationalization of Stevenson’s conceptualisation of entrepreneurship as opportunity-based behavior”. Strategic Management Journal. Vol. 22, pp. 953-968. Cooper, A.C., Gimeno-Gascon F.J. and Woo, C.Y. (1994) “Initial human and financial capital as predictors of new venture performance”. Journal of Business Venturing. Vol. 9, pp. 371-395.

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Eisenhardt, K.M. and Martin, J. A. (2000) “Dynamic capabilities: What are they?” Strategic Management Journal. Vol. 21, pp. 1105-1121. Eisenhardt, K.M., and Sull, D.N. (2001), “Strategy as simple rules”. Harvard Business Review. Jan., pp. 107-116. Erikson, T. (2002), “Entrepreneurial capital: The emerging venture’s most important asset and competitive advantage”. Journal of Business Venturing. Vol. 17, pp. 275–290. EVCA. (1996), “The economic impact of venture capital in Europe, in collaboration with Coopers & Lybrand Corporate Finance”, mimeo. EVCA. (2001), “Policy priorities for private equity: Fostering long-term economic growth”, EVCA White Paper, mimeo. Foss, N., and Knudsen, T. (2001), “The resource-based tangle: Towards a sustainable explanation of competitive advantage”, [online] Department of Industrial Economics and Strategy, Copenhagen Business School, http://www.cbs.dk/staff/nicolaifoss/Foss_Knudsen_nyeste.doc Gompers, J. and Lerner, P. (1999), The Venture Capital Cycle. MIT Press. Grant, R.M. (1996), “Prospering in dynamically-competitive environments: Organizational capability as knowledge integration”. Organization Science. Vol. 7, No. 4, pp. 375-387. Grant, R.M. (2002), Contemporary Strategy Analysis: Concepts, Techniques, Applications. 4th ed. Main, MASS., Blackwell Publishing Ltd. Gulati, R. (1999), “Network location and learning: The influence of network resources and firm capabilities on alliance formation”. Strategic Management Journal. Vol. 20, pp. 397-420. Gulati, R., Nohria, N. and Zaheer, A. (2000), “Strategic Networks”. Strategic Management Journal. Vol. 21, pp. 203215. Haanes, K. and Fjestaldt, Ø. (2000) “Linking intangible resources and competition”. European Management Journal. Vol. 18, No. 1, pp. 52–62. Hedman, J. and Kalling, T. (2001), “The Business Model: A means to understand the business context of information and communication technology”, [online] Institute of Economic Research. Lund University, http://swoba.hhs.se/lufewp/abs/lufewp200 1_009.htm

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resource-based perspective”. Strategic Management Journal. Vol. 22, pp. 907934. Sullivan, P. (2000), Value-Driven Intellectual Capital. NY, John Wiley and Sons. Teece, D., Pisano, G., and Shuen, A. (1997) “Dynamic capabilities and strategic management”. Strategic Management Journal, Vol. 18, No. 7, pp. 509–533. The ∑ Project. (2001), “Economic sustainability. The business of staying in business”. The New Economic Foundation. “Economic sustainability: Systems, methods & approaches. Beyond profit, dividends and capital growth” (Section 3.5). March, [online], http://www.projectsigma.com/RnDStream s/RD_economic_sustain.pdf Triantis, G. (2001), “Financial contract design in the world of venture capital”. University of Chicago Law Review, Vol. 68, Winter, p.305, [online] www.law.uchicago.edu/Publications/Worki ng/index.html Ulrich, D. (1998), “Intellectual capital = competence x commitment”. Sloan Management Review, Vol. 39, No. 4, pp. 15–27.

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Van Olfen, W., and Boone, C. (1997), “The confusing state of the art in top management composition studies: A theoretical and empirical review”, [online] Netherlands Institute of Business Organization and Strategy Research, NIBOR/RM/97/11, http://wwwedocs.unimaas.nl/ Venkatraman, N., and Subramaniam, M.(2002), “Theorizing the future of strategy: Questions for shaping strategy research in the knowledge economy”. The Handbook of Strategy and Management. pp. 461-474, Sage Publications, U.K . Viedma, J. M. (2000), “ICBS Intellectual Capital Benchmarking System”. International Journal of Technology Management, Interscience Enterprises and UNESCO, England, Vol. 20, Nos. 5/6/7/8. pp. 799–818. Zott, C. and Amit, R. (2002), “Business Model design and the performance of entrepreneurial firms” [online] INSEAD, http://knowledge.insead.edu/docs/2002128.pdf

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Case-Based Reasoning as a Technique for Knowledge Management in Business Process Redesign Selma Limam Mansar and Farhi Marir London Metropolitan University, UK [email protected] [email protected] Hajo A. Reijers Eindhoven University of Technology, The Netherlands [email protected] Abstract: Business Process Redesign (BPR) helps rethinking a process in order to enhance its performance. Practitioners have been developing methodologies to support BPR implementation. However, most methodologies lack actual guidance on deriving a process design threatening the success of BPR. In this paper, we suggest the use of a case-based reasoning technique (CBR) to support solving new problems by adapting previously successful solutions to similar problems to support redesigning new business processes by adapting previously successful redesign to similar business process. An implementation framework for BPR and the CBR’s cyclical process are used as a knowledge management technical support to serve for the effective reuses of redesign methods as a knowledge creation and sharing mechanism. Keywords: Business process redesign, Case-based management, Workflow, Best practices, Knowledge management.

1. Introduction Business Process Redesign (BPR) addresses the reengineering of one specific process within the firm. It distinguishes itself from Business Process Reengineering where the focus is rather on developing a “business architecture”, which later requires in depth rethinking and re-assessment of the firm’s mission and of the processes required in order to fulfil it, (Edward and Peppard 1994). So BPR helps rethinking a process in order to enhance its performance. Academics and Business practitioners have been developing methodologies to support the application of BPR principles (for an overview: see Kettinger et al. 1997). However, most methodologies generally lack actual guidance on deriving a process design threatening the success of BPR. Indeed a survey has proved that 85% of projects fail or experience problems (Crowe et al. 2002). In this paper, we suggest the use of a casebased reasoning (CBR) technique. CBR solves new problems by adapting previously successful solutions to similar problems (Marir and Watson 1994). It is a cyclical process comprising the four Res: Retrieving the most similar case, Reusing the case to attempt to solve the problem, Revising the proposed solution if necessary, and Retaining the new solution as a part of a new case (Aamodt and Plaza 1994). In the context of BPR, CBR can be applied to assist the decision-making process. On the other hand, the case-based reasoning technique can serve for the effective reuses of

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redesign methods in an attempt to improve the level of success of BPR implementation. Using the proposed framework and a CBR tool will help supporting knowledge transfer strategies in business process reengineering consultancy firms. As (Wiig et al. 1997) explain it, organisations may pursue five different knowledge management (KM) strategies: KM as business strategy, Intellectual asset management strategy, personal knowledge asset responsibility strategy, knowledge creation strategy and knowledge transfer strategy. The latter is defined as a focus on knowledge systematic approaches to transfer knowledge to points of action where it will be used to perform work. It also includes knowledge sharing and adopting best practices (Wiig et al. 1997). This present work provides the consultancy firms or any organisation that needs to redesign its processes with a tool that supports such knowledge creation, sharing and transfer mechanisms. Indeed, building up cases within the CBR tool helps to organise, restructure and memorize the knowledge acquired after redesigning a process. The memorisation process is a good technical support for sharing the knowledge and adopting the best practices in business process redesign as our framework (see section 5) describes it. In this paper we investigate how CBR can be applied to BPR as a support for knowledge transfer. The paper is structured as follows: Section 2 first introduces Business Process Redesign and the context of this study. Section 3 introduces case-based reasoning and its cyclical process. This part also includes

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a brief definition of case representation, indexing, storage, retrieval algorithm and adaptation. Section 4 is a state of the art of CBR or knowledge-based systems applied to business process redesign. Section 5, focuses on the construction of a case for BPR implementation. It describes the development procedure for a CBR project with a focus on the knowledge acquisition and representation. In that perspective, the framework for BPR that we have developed will be described and, briefly, the thirty best practices included in this framework. On their basis we will develop a domain-dependant case hierarchy. Section 6 explains how CBR can be used as a tool for knowledge management in Business Process redesign. Finally, in section 7, conclusions and future research orientations are provided.

2. Business Process Redesign and context of the study The purpose of this research is to develop a technique that would allow practitioners (consultants and senior managers in enterprises) to access previous redesign projects and, possibly, reapply some of the best findings. CBR should support BPR implementation in the following perspective: the starting point is the acknowledgment of a need to redesign a business process (or an organisation). Knowing the current process and knowing the problems those need to be

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addressed (reducing costs, improving the quality, etc.), a consultant might wish to know whether similar processes with similar problems (weak performance) have been already redesigned. He might wish to find out which rules (best practices) have been applied to solve that problem and the technical and organisational solutions adopted in that previous case. Another situation might be that the consultant has already an idea about some rules he wished to apply but he is not sure about the impact of applying them, or he wants ideas about possible adopted solutions. CBR can help in finding a similar business process, with a similar problem and similar rules applied. In the sequel we describe what is CBR and how it helps in the context of Business Process Redesign.

3. Case Based reasoning CBR is a computer technique, which combines the knowledge-based support philosophy with a simulation of human reasoning when past experience is used, i.e. mentally searching for similar situations happened in the past and reusing the experience gained in those situations (Leake 1996). The concept of casebased reasoning is founded on the idea of using explicit, documented experiences to solve new problems. The decision-maker uses previous explicit experiences, called cases, to help him solve a present problem. He retrieves the appropriate cases from a larger set of cases. The similarities between a present problem and the retrieved case are the basis for the latter’s selection (Gonzalez and Dankel 1993).

Input Indexing

Problem

Elaborate

Target case

Retrieve

Historical cases

Case Base

Reuse Retain Revise Confirmed Solution: New case Figure 1: The CBR cycle, Adapted from Choy et al. 2003. Figure 1 shows the process involved in CBR represented by a schematic cycle. In CBR, the knowledge cases are structured and stored in a case base, which the user queries when trying to solve a problem. Actually, a new problem is matched against historical cases in the case base using heuristically cased

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Adapted cases

indexed retrieval methods with one or more similar cases being retrieved (in fact the system evaluates the similarity between each case in the case base and the problem. The most similar case(s) are presented to the user as possible scenarios for the problem at hand). A solution suggested by the matching cases is

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then reused and tested for success (Namely, the user decides if the solution retrieved is applicable to the problem). At this stage, if the best-retrieved case is the best match, then the system has achieved its goal and finishes. However, it is more usual that the retrieved case matches the problem case only to a certain degree. In this situation, the closest retrieved case may be revised using some predefined adaptation formulae or rules. Many of the most successful CBR systems however do not perform adaptation. They either simply reuse the solution suggested by the best matching case or they leave adaptation to people. When the user finds a solution (automatically or manually), and its validity has been determined, it is retained with the problem as a new case in the case base for future reuse ((Choy et al. 2003), (Haque et al. 2000)). From a technical point of view, there are many arguments supporting using CBR against other knowledge-based methodologies (Luger 2002). Researchers have claimed that CBR provides the potential for developing knowledge-based systems (KBS) more easily than with rule- or model-based approaches. They argue that the concrete examples provided by cases are easier for users to understand and apply in various problemsolving contexts than complex chains of reasoning generated by rules or models and that record-like representations of cases used in some CBR systems allow for straightforward storage in relational databases and entry and update by end users. As a result it combines the efficiency of data management and retrieval of database systems with the intelligence and the power of inference engine of KBS. Another benefit is that the presence of the validation and update steps provides a framework for learning from experience, thus incorporating knowledge acquisition as part of the day-to-day use of a CBR application (Allen 1994). However CBR may not be as effective as rule- or model-based approaches for applications where theory, not experience, is the primary guide to problem solving, and where solutions are unique to a specific problem instance and not easily reusable (Allen 1994).

4. CBR applied to BPR Implementation 4.1

State of the art

In the sequel, examples of CBR systems applied to business process reengineering or redesign are described and discussed.

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(Allen 1994) reports two examples of commercial CBR applications to business process reengineering (and not redesign). The use of case retrieval in both examples can be viewed as a special instance of the application of case retrieval to the automation of business processes: SMART is a CBR customer services application developed by Compaq Computer in 1992. The system analyses incoming Compaq’s customers problems and retrieves the most similar cases from its case base and present them to the customer service analyst, who then uses them to resolve the problem. Prism telex classification system is a CBR system developed by Cognitive Systems, Inc in 1990. The system is used in several banks to route incoming international telex communications to appropriate recipients. (Min et al. 1996) have developed a commercial CBR Intelligent Bank reengineering System (IBRS) that is used by Battelle Company. The system is based on three stages. A generation stage that identifies BPR alternatives based on user requirements and strategic goals, an evaluation stage that applies the workflow analysis and functional economic analysis to compare BPR alternatives and finally a choice stage where the user selects the combination of BPR alternatives based on the generated evaluation statistics. On the business process reengineering perspective, (O’Leary and Selfridge 2000) describe a Knowledge-Based System Approach to reengineering. The system was built to test the notion that best practices reengineering process knowledge could be captured as a knowledge-based system for analysis and reuse. Though this application is not a CBR system, it exploits the notion of “Best Practices” in business process reengineering. The system targets procurement reengineering and applies the seven principles of reengineering listed by (Hammer 1990). Similarly, in (Nissen 2001) a knowledge-based, process-redesign system called KOPeR-lite. This is not a CBR system. However, it provides automated redesign support through measurement-driven inference system. The system targets similar generic processes as described in (Limam et al. 2003) and summarised in section Domain knowledge acquisition for BPR implementation). The fundamental difference with our BPR/CBR approach is that we target to exploit previous

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consultants’ knowledge using CBR. The underlying hypothesis being that reasoning is reminding (problem solving utilises past experiences (Madhusudan and Zhao 2003)). CBR has also been employed successfully to other similar activities such as: Workflow design: (Kim et al. 2002) using a clean-sheet approach, (Madhusudan and Zhao 2003) using previous redesigned processes, Concurrent product development (Haque et al. 2000), And business automation (Cheung et al. 2003).

4.2

BPR-CBR approach

The state of the art shows clearly that the above CBR systems were targeting reengineering business processes, either with the purpose of automating tasks (as an application of BPR principles), or with the purpose of retrieving similar cases that can be adapted to design a new business process. However in all systems, the emphasis was on specific types of business processes or specific types of business activities. The systems cannot thus be reused to support the redesign of any type of business process. The aim of this paper is to study the relevance of developing a BPR/CBR system which role would be to support organisations in redesigning their processes. The present work is targeting consultants in the field. CBR can be used to collect, store and reuse the knowledge and best practices from previous redesign efforts. Its application to BPR should improve the decision-making abilities of workers. Indeed, BPR relies on designers’ experiences. Best practices in the field are often used and combined to redesign similar processes. In this context, our main interest in CBR relies in that it allows a system to avoid past errors and exploit past successes. This is a key issue in Business Process Redesign where practice has proved that successes are few and failures quite common (Crowe et al. 2002). Another argument in favour of using CBR for BPR implementation is that, traditionally, redesign has been the area of consultants and “experts” in the field. Thus, redesign is often the result of the application of so-called “best practices” rather than on the use of analytical methods (theoretical models and heuristics) to derive improved or redesigned processes (Reijers et al. 2003). Some authors are working on the development of such analytical tools. However none of them

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is currently capable of dealing with every particular aspect of a redesigned business process. In fact much of the redesign still rely on past experiences and on the application of the aforementioned best practices. In this context, CBR can be viewed as a good compromise between a completely empirical study and redesign of business processes and a pure analytical method. CBR can support the redesign process by finding similar cases: experts or consultants can then compare and learn which best practices to apply and also, hopefully avoid past mistakes.

5. Case construction for BPR implementation To undertake a CBR project it is important to set up a clear development procedure. The steps for developing a BPR-CBR system are usually as follows and are represented in Figure 2. In this paper we focus on steps one and two only. 1. Step 1: Domain Knowledge acquisition: in this step, every effort is made in order to understand the problem domain and the symptoms. Information about the diagnostic of the problem and the solutions adopted are also collected in this step. For BPR implementation, this means (a) conceptually defining a business process that needs to be redesigned, (b) identifying the goals and targets behind the redesign effort, (c) defining the rules to apply to redesign the process and (d) the technical or organisational solutions adopted as a result of the redesign. To undertake this step we have based our research on studying previous methodologies and frameworks used in the literature for BPR. The results of this section are summarised in sections 5.1.1, 5.1.2 and 5.1.3. A complete study should also include interviews with experts and consultants and a collection of some initial cases. 2. Step 2: Case representation: in this step, the software to be used for knowledge representation should be selected. The next step is to describe the case. The results of this section are summarised in section 5.2. 3. Step 3: System implementation: this describes the final system including the database of cases and the indexing and retrieval process within the chosen software. This is a future research development.

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4.

Step 4: Verification and validation: in this step, some informal verification and validation should be conducted (Chan et al. 2000). Verification aims at “demonstrating the consistency, completeness and correctness of the software” (Adrion et al. 1982), that is, it aims at “building the system right” (O’Leary 1993). Hence, the question posed in verification is: “do the cases correctly represent the experience and knowledge we obtained?” Validation is the “determination of the correctness of the final program or software produced from a development project with respect to the user needs and requirements” (O’Leary 1993). This implies showing the system to practitioners not involved in the development of the system and see whether they are satisfied of the tool or not. Step 1: Knowledge Acquisition (experts and data)

5.1.1 The BPR framework The idea behind a framework is to help practitioners by identifying the topics that should be considered and how these topics are related (Alter 1999). In this perspective, the framework should identify clearly all views one should consider whenever applying a BPR implementation project. For BPR, we suggest to use the framework described in Figure 3. It is derived as a synthesis of the WCA (Work-Centred-Analysis) framework (Alter 1999), the MOBILE workflow model (Jablonski and Bussler 1996), the CIMOSA enterprise modelling views (Beriot and Vernadat 2001) and the process description classes of (Seidmann and Sundarajan 1997). In this framework, six elements are linked as shown in Figure 3. EXTERNAL ENVIRONMENT

Customers

Step 2: Knowledge representation (Identify cases)

Step 3: System implementation (Set up case base in CBR tool)

Step 4: Verification and Validation (System verification and validation)

Products

Business process Operation view

Organisation -Structure -Population

Behavioural view

Information

Technology

Figure 2: Case-Based system development procedure (Adapted from Chan et al. 2000).

5.1

Domain knowledge acquisition for BPR implementation

Our approach to Business process redesign relies on the prior definition of an implementation framework. Its role is to provide guidelines towards which important elements should be redesigned. Within each defined element, consultants and practitioners have been applying a set of best practices for redesign purposes. We have reviewed on a previous paper (Limam and Reijers 2002) these best practices and classified them according to our BPR framework. The framework and the related best practices serve as a guidance to which rules should be considered when implementing BPR.

Figure 3: Framework for BPR implementation. 5.1.2 BPR Best practices Knowledge acquisition for BPR implementation is based on the framework described in The BPR framework) and on a set of BPR best practices. Over the last twenty years, best practices have been collected and applied in various areas, such as business planning, healthcare, manufacturing, and the software development process (e.g. (Martin 1978); (Butler 1996); (Golovin 1997)). In this section we describe such best practices, which can actually support the redesigned of a business process in facing the technical BPR challenge: the implementation of an improved process design. Improving a process is a matter of improving any of the components of the framework we

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adopted in the BPR framework section. Thus we classify the best practices in a way that respects the framework we have adopted.

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Organization, which considers both the structure of the organization (mostly the allocation of resources) and the resources involved (types and number). Information, which describes best practices related to the information the business process uses, creates, may use or may create. Technology, which describes best practices related to the technology the business process uses or may use. External environment, which try to improve upon the collaboration and communication with the third parties

Table 1 summarises the identified best practices within the implementation framework). We identify best practices that are oriented towards: Customers, which focus on improving contacts with customers. Business process operation, which focus on how to implement the business process, Business process behaviour, which focus on when the business process is . executed, Table 1: BPR best practices classified according to our BPR implementation framework Framework elements

Best practice name

Framework elements

Best practice name

Customers

Control relocation Contact reduction Integration

Organisation: structure

Products

NONE.

Organisation: Population

Operation view

Behavioural view

External environment

Order types Task elimination Order-based work Triage Task composition Resequencing Parallelism Knock-out Exception Trusted party Outsourcing Interfacing

Examples: Example 1: illustrates how the Task composition best practice can be applied to a conference registration process to improve the operation view. In the initial process, the conference is organised in a way that attendees are invited to register, to pay the fees and to book for an accommodation as separate steps. The task composition rule can be applied by sending a single email where the attendees are invited to proceed with the three tasks at the same time. This improves the quality of the registration process. Example 2: illustrates how the Control addition best practice can be applied to

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Order assignment Flexible assignment Centralisation Split responsibilities Customer teams Numerical involvement Case manager Extra resources Specialist-generalist Empower Control addition

Information

Buffering

Technology

Task automation Integral Business Process Technology

mortgages applications processes to improve the Organisation view. The rule promotes adding controls before sending materials for customers. Mortgages for buying homes involve constituting a file with numerous documents and papers. Checking the list of requirements against applicants’ specifications before sending them can save the organisation the hassle of numerous correspondences. 5.1.3 BPR goals and targets For the construction of a case we still need to define the "problem". Yes a practitioner might wish to retrieve cases of similar business processes and similar best practices but he also would like to do it in order to achieve a

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target. Different goals might lead to completely different redesign options. (Brand and Van der Kolk 1995) demonstrate this issue using their "devil's quadrangle". The authors distinguish four main dimensions in the effects of redesign measures: time, cost, quality, and flexibility. Ideally, a redesign of a business process decreases the time required to handle an order, it decreases the required cost of executing the business process, it improves the quality of the service delivered, and it improves the ability of the business process to react to variation. The attractive property of their model is that, in general, improving upon one dimension may have a weakening effect

on another. In order to reflect this difficult reconciliation between the targets and goals of the BPR implementation, it is important to include it as part of a case's characteristics. Goals and targets can be classified as simply "reducing cost or time", "improving flexibility or quality", or a broader range of goals and targets can be used depending on the type of processes that are being redesigned. The classification by (Guimaraes and Bond 1996) offers a wider range of goals and targets that can be used as an initial vocabulary for the CBR cases. Error! Reference source not found. shows some of these targets and goals.

Table 2: Possible goals and targets for BPR implementation (adapted from (Guimaraes and Bond 1996)). Possible targets and goals Increase own competitiveness by improving the quality Increase own competitiveness by reducing costs Increase own competitiveness by shortening product development Focus on end results and objectives Set aggressive business process goals Use Information and Technology Operate across organisational units Reduce production times…

The impact of the initial target and goal on a redesign can be illustrated by revisiting both examples provided in the previous section: Example 1: we have applied the “task composition” rule to a conference registration process. The target here is clearly to “reduce the production times”. However if the target was to “improve the quality” then it is very unlikely that this rule would have been applied as it results in less flexibility to participants to decide, later on, on accommodation for example. Example 2: We have applied the “Control addition” rule to a mortgage application process. The target here was clearly to “reduce the costs”. It is unlikely that this rule would have been applied if the target were “focus on end results and objectives”. In the latter case, the focus would have rather been on redesigning the product in itself (mortgage) rather than on the process. This first step, knowledge acquisition, is now complete. According to Figure 2, the next step is to define the knowledge representation.

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5.2

Case representation for BPR implementation

In this section we describe the case base, i.e. how the storage scheme needs to be structured in a systematic fashion. We adopt, for case-base description, the formalism used in (Kim et al. 2002) and (Suh et al. 1998). Our case base is organised in the form of a hierarchical case tree from the top layer (business area) to the bottom layer (Applied rules); see Figure 4. It has a structure of is-a hierarchy, called a domain-dependent case hierarchy. If a new BPR Solution is created, it is saved in the relevant location according to the hierarchical path from the business layer to the BPR Solution layer. The upper three floors (business area, sub-business area, processes) represent more abstract generic features of the cases, while the three lower layers (BPR solution, goals and targets and applied rules) represent more specific features to the current BPR case.

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Business area

Banking, Finance

….

Sub-Business area

Processes

… …

BPR Solution



Goals and targets

Applied rules

Cars

….



Invoicing Invoicing BPR solution

Improve quality

Split responsibilities

Manufacturing

Aeronautics

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Mining, Oil

Textile

Advertising Advertising BPR Solution

….

….

Inventory management Inventory management BPR Solution

Reduce cost

Use IT

Parallelism

Task automation

…. ….

….

….

Figure 4: A domain-dependent case hierarchy. Our case base can be represented by the use of the notations for class diagrams of UML. A BPR solution has relationships with the initial goals and targets and the applied rules; i.e. a BPR solution consists of a set of goals and targets for which some rules have been applied. The shaded parts (processes, goals and targets and Applied rules) should have indexes for case retrieval. They may have similar terms, which will constitute the principle indexes for retrieving similar cases from the case base. Further details are available in (Limam et al. 2003). For both examples described in sections 5.1.2 and 5.1.3, the cases are indexed as follows: Example 1: “Education”, “Research”, “Conference registration process”, “Conference registration process BPR Solution”, “Reduce the Production Times”, “Task composition”. Example 2: “Banking, Finance”, “Financial products”, “Mortgage”, “Mortgage BPR Solution”, “Reduce the Costs”, “Control addition”.

6. CBR as a technique for knowledge management in Business Process redesign In the sequel we explain how the CBR/BPR tool can be used to enhance knowledge

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transfer strategies Redesign.

in

Business

process

The CBR/BPR tool plays the role of a knowledge-handling tool. The information (which best practices are used for business processes) is first collected from practitioners and then stored in the case database and organised logically (see section 5.2). Basically, Our implementation framework and the set of best practices are the basis for cases classification for CBR. They can be used in two ways: A practitioner wishes to apply a given set of best practices to a specific process and would like to retrieve cases where similar best practices were applied. In this situation the best practices are used to characterise a case, A practitioner doesn't know which rule to apply. He would like to retrieve cases where similar business processes have been redesigned. In this case the rules are an intrinsic part of the solution used in the historical case to solve a similar problem. The information is then made accessible to practitioners to be used. The knowledge can be shared through the CBR/BPR tool by entering new cases to the case-base system or informally by people sharing the knowledge, talking and socialising with one another or exchanging information in digital or analogue form. The CBR/BPR tool thus supports the stages of knowledge management as described in figure 3.

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Collecting information

Storing information

Making the information available

Using the information

Figure 5: The stages of Knowledge Management, (Martensson 2000).

7. Conclusion

References

According to a study conducted with 11 organisations participating in the arena of knowledge management and published in (Sadri et al. 1999), the practice of knowledge management starts by creating, finding and collecting internal knowledge and best practices, then sharing and understanding those practices so they can be used and finally adapting and applying those practices to new situations. In this paper we have discussed the use of case-based reasoning for the reuse of previous Business process redesign projects to similar processes (sharing and adapting previous practices). This includes collecting the knowledge and storing it into the CBR case base and making it available so that knowledge about BPR is shared, adapted and applied to new situations. We have demonstrated through knowledge acquisition and knowledge representation that applying CBR is possible for BPR implementation and would benefit for (re) designers in the following way: Knowing the current process and knowing the problems those need to be addressed, similar processes with similar problems might be retrieved to find out which best practices have been applied and which technical and organisational solutions were adopted. Another situation might be that the consultant has already an idea about some rules he wishes to apply but he is not sure about the impact of applying them, or he wants ideas about possible adopted solutions. CBR can help in finding a similar business process, with a similar problem and similar applied rules.

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Suh, M S, Jhee, W C, Ko, YK and Lee, A ‘A case-based expert system approach for quality design’ Expert systems with applications, Vol 15 (1998) pp 181-190. Valiris, G and Glykas, M ‘Critical review of existing BPR methodologies’ Business

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Determinants of Successful Knowledge Management Programs Mohamed Khalifa and Vanessa Liu City University of Hong Kong [email protected] [email protected] Abstract: The main objective of this paper is to investigate and identify the main determinants of successful knowledge management (KM) programs. We draw upon the institutional theory and the theory of technology assimilation to develop an integrative model of KM success that clarifies the role of information technology (IT) in relation to other important KM infrastructural capabilities and to KM process capabilities. We argue that the role of IT cannot be studied in isolation and that the effect of IT on KM success is fully mediated by KM process capabilities. The research model is tested with a survey study involving 191 KM practitioners. The empirical results provided strong support for the model. In addition to its theoretical contributions, this study also presents important practical implications through the identification of specific infrastructural capabilities leading to KM success. Keywords: Knowledge Management Success, Infrastructural Capabilities, Process Capabilities, Institutional Theory, Technology Assimilation

1. Introduction Knowledge management has become an important topic for both research and practice. The adoption of KM has accelerated in recent years1. The success of the new KM initiatives, however, is not obvious. There is a need for a better understanding of the prerequisites of successful KM programs. Several frameworks for KM implementation have been proposed in the literature, mainly by practitioners. For instance, Gupta and Govindarajan (2000) proposed a set of practice notes on the use of strategy and organizational culture in achieving KM success. Another example is the model developed by Leonard-Barton (1995), which identified several core capabilities crucial to successful KM initiatives. The former Arthur Andersen and The American Productivity and Quality Center (1996) set forward the major institutional enablers of various KM processes. Most proposed frameworks, however, lack theoretical underpinning and empirical validation. Information technology is often cited in the literature as an important KM infrastructural capability, enabling or supporting core knowledge activities such as knowledge creation, knowledge distribution and knowledge application (Gold et al., 2001). Holsapple and Whinston (1996), for example, studied the effect of IT on knowledge acquisition and representation. Purvis et al. (2001), on the other hand, investigated the general impact of IT on KM. Most of these studies examined the role of IT in isolation, overlooking its relationships with other KM success factors and the effect of IT assimilation within KM processes. 1

According to an IDC survey in 2002, 90% of fortune 500 companies have started formal KM programs.

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The research objective of this study is therefore to develop a better conceptual model of KM success, capturing the complex interrelationships between IT and other key determinants. We include IT, KM infrastructural capabilities and KM process capabilities as the main success drivers based on the institutional theory (Orlikowski, 1992). To account for the importance of technology assimilation (Fichman and Kemerer, 1997), we postulate that the effect of IT on KM success is not direct but rather fully mediated through KM process capabilities. This approach represents a departure from previous KM studies, which modeled IT as a direct determinant of KM success. To validate the proposed model, we conducted a survey study involving 191 KM practitioners. In the next section, we present the research model and its theoretical foundation. We then describe the research methodology, followed by a discussion of the empirical results and their implications. In conclusion, we summarize the key findings and suggest directions for future research.

2. The research model According to the knowledge-based views of the firm (Spender, 1996), organizational effectiveness is an outcome of knowledge creation, explication, communication and application (King, 2003). KM objectives should therefore be derived from general organizational goals. Common benchmarks of KM success include innovativeness, coordination, time-to-market, adaptability and responsiveness to changes (Gold et al., 2001). In this research we define KM success by the extent to which the intended KM objectives are

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achieved. Our research model (see Figure 1) applies the institutional theory and the theory of technology assimilation in explaining KM success. The institutional theory (Orlikowski, 1992) postulates that individual behavior within an organization is guided by the institutional structures. These structures take the form of, for instance, organizational norms, culture and corporate policies. Previous studies identify three main categories of institutional structures according to their nature, functions and objectives. One type of structures signifies the value of the desirable behavior by ensuring that individuals understand the acts required to accomplish organizational objectives. Another type of structures constitutes normative governing mechanisms that verify and legitimize personal conducts. Any actions that are within the scope of the firm goals are legitimate. Finally, structures of domination represent regulations with which individuals comply to ensure they do not violate the prescribed firm practice. The institutional structures influence individual behavior through structuring actions introduced at the individual level (i.e. individual structuring) or at the top management level (i.e. metastructuring). The application of the institutional theory in the KM context implies that KM infrastructural capabilities are major factors that align individual behavior with KM goals and hence KM success. Consistent with Gold et al. (2001), we therefore hypothesize that H1: KM infrastructural capabilities have a significant positive effect on KM success. IT has been identified by a number of studies as a major determinant of KM success (e.g. Purvis et al., 2001). The quality and speed of knowledge transfer, for example, is considerably improved with the support of technologies (Ruggles, 1998). Common IT applications employed by firms include intranets, knowledge repositories and group decision support systems. KM tools can be classified into three general categories: generation, codification, and transfer (Ruggles, 1997). Knowledge generation requires tools that enable the acquisition, synthesis, and creation of knowledge. Knowledge codification tools support the representation of knowledge so that it can be accessed and transferred. The capabilities of these tools vary depending on the targeted knowledge – i.e., process knowledge, factual knowledge, catalog knowledge, and cultural knowledge – and on whether that knowledge is explicit or tacit. Types of codification tools include knowledge

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bases, knowledge maps, organizational thesaurus/dictionaries, and simulators. Knowledge transfer tools alleviate the temporal, physical, and social distances in knowledge sharing. An alternative framework for classifying KM tools and technologies consists of five categories: business intelligence, collaboration, transfer, expertise, and discovery/mapping. Such frameworks can help organizations to select the appropriate technology for a given KM task. Mere adoption of information technologies, however, does not necessarily achieve its intended purposes. According to the theory of technology assimilation (Cooper and Zmud, 1990; Fichman and Kemerer, 1997), technologies must be infused and diffused into business processes to enhance organizational performance. Assimilation is defined as “the extent to which the use of a technology diffuses across organizational work processes and becomes routinized in the activities associated with those processes” (Tornatzky and Klein, 1982; Chatterjee et al., 2002). It is a key factor that explains the influence of IT adoption on organizational performance (Jarvenpaa and Ives, 1991; Armstrong and Sambamurthy, 1999; Chatterjee et al., 2002). In the initial adoption stage, it is challenging yet users need to reconceptualize business process activities in order to use the technology effectively (Saga and Zmud, 1994; Fichman and Kemerer, 1997; Purvis et al., 2001). These challenges constitute ‘assimilation gaps’, i.e. the lag of rates of adoption between the organization and individuals (Chatterjee et al., 2002). Successful utilization hence requires, among other things (e.g. ease of use and reduced complexity etc.), mutual adaptation of the technology and the organizational context (Leonard-Barton, 1988; Purvis et al., 2001). In other words, IT must be adapted to the organizational and industrial arrangements (Van de Ven, 1986), while structures and norms may also need to be reformed to facilitate the use of the technologies (Kwon and Zmud, 1987). In the context of KM, IT should therefore become the enablers of KM processes to exhibit its effect on KM success. Without such assimilation within the KM processes, IT alone is not sufficient to improve firm performance. We hence hypothesize that IT does not affect KM success directly. Instead, its effect is fully mediated through KM process capabilities H2: Information Technology does not have a significant direct effect on KM success

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H3: Information Technology has a significant positive effect on KM Process Capabilities.

empirically validated using surveys. Analysis of the results indicated that knowledge infrastructural capabilities and knowledge process capabilities have independent and direct effects over organizational effectiveness. The underlying assumption of this study is that successful KM essentially leads to firm competitiveness (Gray, 2001). Though their study represents one of the few endeavors in the development of a comprehensive framework on KM success, they yet did not account for the interrelationships between the KM infrastructure and KM process capabilities.

Most prior studies focused on the relationship between the different KM infrastructural capabilities and KM success. Little has been done to capture the relative importance of the various infrastructural capabilities in relation to KM process capabilities. KM processes are defined as “an ongoing set of practices embedded in the social and physical structure of the organization with knowledge as their final product” (Pentland, 1995). Capabilities of KM processes are essential to leverage the KM infrastructure capabilities. Effective KM processes should be conducted frequently, consistently and flexibly (Grant, 1996). Numerous attempts have been made to provide a categorization for KM processes. For example, DeLong (1997) classified the processes into capturing, transfer and use of knowledge. Leonard-Barton (1995), on the other hand, distinguished between acquisition, collaboration, integration and experiment. Nevertheless, these studies failed to capture the relative roles of KM infrastructural capabilities among these processes.

As the capabilities of KM infrastructure cannot be fully leveraged without the presence of KM process capabilities (Gold et al., 2001), the presence of both KM process and infrastructural capabilities is critical to reach the intended KM objectives. Appropriate KM processes should be implemented to routinize KM values and practice and to enhance knowledge application in daily business procedures (Grant, 1996). We therefore stipulate that KM process capabilities directly affect KM success. More specifically, we hypothesize that

More recently, Gold et al. (2001) modeled both KM process capabilities and KM infrastructural capabilities as direct determinants of organizational effectiveness. Their model was

H4: KM Process Capabilities have a significant positive effect on KM success

Leadership

Culture

KM Infrastuctural Capabilities

H1

KM Strategy Information technology

KM Success H2

H3

KM Process Capabilities

H4

Insignificant Significant Figure 1: Research model

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3. Research methodology and data analysis We conducted a survey study with existing KM practitioners to validate our research model. The survey instrument consists of both formative items measuring KM process capabilities and reflective items for all other constructs (i.e. KM success, KM infrastructure capabilities and IT). The reflective items were generated from a comprehensive review of the literature and verified following the card sorting procedure proposed by Moore and Benbasat (1991) to ensure face and discriminant validity.

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We also conducted tests on the measurement model. According to the standard approach, path loadings from constructs to measures are required to exceed 0.70. Internal consistency of the measures was verified using the composite reliability measures (ρ) (Chin, 1998) and the average variance extracted (AVE) (Fornell and Larcker, 1981). Discriminant validity was tested by comparing the square root of the AVEs for a particular construct to its correlations with the other constructs (Chin, 1998).

4. Results and discussion

We measured KM infrastructure capabilities using formative items to identify a list of specific key KM infrastructure. This also facilitates and the assessment of their relative importance on KM success, which should be of particular interest to KM practitioners. We derived an initial pool of formative items from previous literature. We then performed a belief elicitation process with existing KM practitioners and added/removed some items based on their comments. Consistent with Gold et al. (2001) and Khalifa et al. (2001), we ended up with three main KM infrastructural capabilities, namely, culture, leadership and KM strategy.

The measurement model statistics are presented in Table 1. The loadings of all reflective items are high (above 0.7) with significance at 1% level, confirming convergent validity. The composite reliability scores of all constructs are higher than the recommended benchmark of 0.80 (Nunnally, 1978), verifying internal consistency. The weights and their significance of all formative measures indicate that the items contribute significantly to the formation of the construct of KM infrastructural capabilities. A comparison of the square roots of the AVE scores with the correlations among the constructs provided support for discriminant validity.

All items are measured using a five-point Likert scale ranging from “strongly agree” to “strongly disagree”. The resulted instrument was pilot tested with current active KM practitioners to ensure its wordings are understandable and its length is appropriate. The final instrument was administered online to 1,000 KM practitioners randomly selected from various online KM discussion forums. After eliminating those with missing values, we totally collected 191 usable observations, amounting to an overall response rate of over 19%.

The results of the PLS analysis are presented in Figure 2. Each hypothesis is plotted as a specific path in the figure. The estimated path coefficients are generated, along with the associated t-statistics. Significant paths are denoted with two asterisks (**) at the 99% confidence interval and with one (*) at the 90% interval. The R2 statistic is available next to each dependent variable. Significant links are represented by solid lines while insignificant ones are represented by broken lines.

The data analysis was conducted with Partial Least Squares (PLS) procedure (Wold, 1989), using the technique of PLS Graph (Chin, 1994). These statistical techniques are appropriate for analyses of measurement models with both formative and reflective items. Specifically PLS facilitates a concurrent analysis of 1) the relationship between measures and their corresponding constructs and 2) whether the theoretical hypotheses are empirically confirmed.. The significance of all paths was tested with the bootstrap resampling procedure (Cotterman & Senn, 1992).

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Our research model demonstrates good explanatory power for KM success, with over 75% of the variance explained (R2 = 75%). As hypothesized in H1 and H4, both KM infrastructural capabilities and KM process capabilities are significant drivers of KM success. The effect of KM infrastructural capabilities is, however, more dominant, with a direct path coefficient of 0.540 significant at the 1% level in comparison to KM process capabilities (path coefficient = 0.376; t = 4.05). These results represent a confirmation of the institutional theory (Orlikowski, 1992) that stipulates that knowledge capabilities must be leveraged to achieve organizational effectiveness (Gold et al., 2001).

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Table 1: Measurement model statistics Constructs KM Infrastructural Capabilities KM Success (ρ =0.86) Technology Fit (ρ = 0.89) KM Process Capabilities (ρ = 0.88)

Variables Culture Leadership KM Strategy Item 1 Item 2 Item 3 Item 1 Item 2 Item 3 Item 1 Item 2 Item 3 Item 4

Weights 0.3312 0.1200 0.6733

Our research model demonstrates good explanatory power for KM success, with over 75% of the variance explained (R2 = 75%). As hypothesized in H1 and H4, both KM infrastructural capabilities and KM process capabilities are significant drivers of KM success. The effect of KM infrastructural capabilities is, however, more dominate, with a direct path coefficient of 0.540 significant at the 1% level in comparison to KM process capabilities (path coefficient = 0.376; t = 4.05). These results represent a confirmation of the institutional theory (Orlikowski, 1992) that stipulates that knowledge capabilities must be leveraged to achieve organizational effectiveness (Gold et al., 2001). Contrary to the results of previous studies (Gold et al., 2001; Goodhue and Thompson, 1995) there is no significant direct effect of IT on KM success, hence verifying H3 (path coefficient = 0.031; t = 0.63). As hypothesized earlier (H2), IT affects significantly KM process capabilities, explaining over 32% of the variance of the construct. These results confirm our argument that the effect of IT on KM success should be studied in the presence of KM process capabilities to better assess its relative importance. An important implication of these findings is that IT assimilation within KM process capabilities is critical to the achievement of KM success. Since the effect of IT is fully mediated through KM process

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Loadings

0.8888 0.8941 0.7807 0.9119 0.8993 0.8544 0.8753 0.8830 0.8470 0.9002

Std. Error 0.0734 0.0694 0.0656 0.0208 0.0163 0.0427 0.0167 0.0183 0.0259 0.0224 0.0202 0.0276 0.0184

T - statistics 4.5152 1.7296 10.2588 42.6722 54.8529 18.2889 54.5346 49.2204 33.0280 39.0618 43.6549 30.6649 48.9532

capabilities, it should therefore be selected based on the requirement of these processes. The weights and t-statistics of the formative items are presented in Table 1. KM strategy emerges as the most important infrastructure capability (weight = 0.673). These findings highlight the important role of KM strategy in the implementation of KM initiatives. KM strategy is “the balancing act between the internal capabilities of the firm (strengths and weaknesses) and the external environment (opportunities and threats)” (Zack, 1999). Its formulation involves identifying and assigning value the required KM initiatives. It is an important guideline for prioritization of KM investments (Alavi, 1997; Gopal and Gagnon, 1995). To enhance KM success, a KM strategy should be developed based on the overall business strategy to ensure the KM goals are in congruence with the strategic goals of the firm (Davenport, 1999; Hansen et al., 1999). Such congruence is essential for maximizing KM success and hence organizational performance (Liebowitz and Beckman, 1998). The emergence of KM strategy as the chief infrastructural capability also provides strong support for the adoption of a top-down approach of KM implementation. In other words, the starting point for KM is not some scattered initiatives, but rather a well-defined KM strategy (Horwitch and Armacost, 2002).

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Leadership 0.120** t=1.73

Culture

0.331** t=4.52

KM Infrastructural Capabilities

0.540**

Information Technology

0.031

t=5.89

0.673** KM Strategy

t=10.26

t=0.63

R2 = 0.324

KM Success

R2 = 0.753

0.569** t=10.1215

KM Process Capabilities

0.376** t=4.05

Insignificant Significant

Figure 2 – Results of PLS Analysis Culture emerges as the second important KM infrastructural capability (weight = 0.331). Organizational culture is “the set of shared, taken-for-granted implicit assumptions that a group holds and that determines how it perceives, thinks about, and reacts to its environment” (Schein, 1985). It shapes the behavior of organizational members through driving the norms and practices within the firm (Delong and Fahey, 2000). As suggested by many previous studies (e.g. Gopal and Gagnon, 1995), a supportive culture is essential for the successful implementation of KM initiatives. Appropriate norms and values motivate knowledge sharing and collaboration. This is particularly important for motivating the sharing of tacit knowledge, which is not likely to be transferred through predefined formal means (O’Dell and Grayson, 1998). Many practitioners, however, considered culture to be one of the most uncontrollable capabilities (Glasser, 1999). To foster a supportive culture for KM, employees must be able to appreciate and recognize the value of KM initiatives (Alavi, 1997; Gopal and Gagnon, 1995). Corporate vision statements and value systems are some effective means for

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communicating the individual and organizational benefits of KM (Gray, 2000). A vision states and defines unambiguously the desirable organizational goal (Kanter et al., 1992; Nonaka and Takeuchi, 1995). In promoting KM, the corporate vision provides a sense of purpose for getting involved in and contributing to KM initiatives (Leonard-Barton, 1995). Corporate value systems are complimentary to vision statements, determining the type of desirable KM activities (Miles et al., 1997). Another important KM infrastructure capability is leadership (weight = 0.120). As suggested by the institutional theory, a management champion sets overall directions for the KM programs and assumes accountability for the related activities (Orlikowski, 1992; Purvis et al., 2001). More importantly, he/she obtains commitment from employees by operating metastructuring actions to achieve the desirable KM objectives. The role of leadership is usually embodied in the position of chief knowledge officer (CKO), which is implemented by more and more organizations nowadays. The CKOs are responsible for the

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development and accomplishment of KM vision through introducing various metastructuring actions (Orikowski, 1992). For instance, they assign strategic values to KM initiatives and revise business policies/practice in adherence to KM goals. They may also be involved in creating the appropriate culture and gaining commitment from top executives (Davenport and Prusak, 1998; Earl and Scott, 1999; Manasco, 1998).

5. Conclusion and implications for future research In this study, we propose a conceptual model on KM success that integrates the effects of IT with those of other KM infrastructural capabilities and in relation to KM process capabilities. We rely on the institutional theory (Orlikowski, 1992) and the theory of technology assimilation (Fichman and Kemerer, 1997) as theoretical foundation. To test the model, we conducted a survey study involving 191 KM professionals. Confirming the theory of technology assimilation (Fichman and Kemerer, 1997), our findings demonstrate that IT does not have any direct effect on KM success. Rather, the IT effect is fully mediated through KM process capabilities. In other words, IT capabilities cannot be fully leveraged to lead to KM success without being assimilated within KM processes. These result present important implications for research. Studies reporting direct effects of IT on KM success without considering the mediation role of KM processes should be interpreted carefully. Our study also identifies KM strategy as the principal dimension of KM infrastructural capabilities driving KM success, followed by culture and leadership. In adopting KM programs, managers should therefore enforce the implementation of these capabilities to enhance the success of their efforts. The weights of these infrastructural capabilities provide useful guidance to KM practitioners for prioritizing KM activities. Our research model can be extended in future research to consider the interrelationships among the infrastructural capabilities. Future research should also identify the main KM process capabilities and assess their significance and relative importance.

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Nonaka, I. and Takeuchi, H. (1995) The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation , Oxford University Press, New York. Nunnally, J.C. (1978) Psychometric Theory, McGraw-Hill, New York. O’Dell, C. and Grayson, C. (1998) “If only we knew what we know: Identification and transfer of internal best practices,” California Management Review Vol. 40, No. 3, pp. 154-174. Orlikowski, W. J. (1992) “The duality of technology: Rethinking the concept of technology in organizations,” Organization Science, Vol. 3, No. 3, pp. 398-427. Pentland, B. T. (1995) “Information Systems and Organizational Learning: The Social Epistemology of Organizational Knowledge Systems”, Accounting, Management & Information Technology, Vol. 5, No. 1, pp. 1-21. Purvis, R. L., Sambamurthy, V. and Zmud, R. W.(2001) “The assimilation of knowledge platforms in organizations: An empirical investigation,” Organization Science, Vol. 12, No. 2, March-April, pp. 117-135. Ruggles, R. (1997) Tools for Knowledge Management: An Introduction (Knowledge Management Tools), ButterworthHeinemann, Boston. Ruggles, R. (1998) “The state of the notion: Knowledge management in practice,”

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California Management Review, Vol. 40, No. 3, Spring, pp. 80-89. Saga, V. and Zmud, R. (1994) “The nature and determinants of information technology acceptance, routinization and infusion,” in Diffusion, Transfer and Implementation of Information Technology (ed. Levine, L.), North-Holland, Amsterdam, pp. 67-86. Schein, E.H. (1985) Organizational Culture and Leadership, Jossey-Bass, San Francisco. Spender, J. C. (1996) “Making knowledge the basis of a dynamic theory of the firm,” Strategic Management Journal, Vol. 17, Winter , pp. 45-62. Tornatzky, L. G. and Klein, K. (1982) “Innovation characteristics and innovation implementation: A meta-analysis of findings,” IEEE Transactions on Engineering Management, Vol. 29, No. 1, pp. pp. 28-45. Van de Ven, A. H. (1986) “Central problems in the management of innovation,” Management Science, Vol. 32, No. 5, pp. 590-607. Wold, H. (1989) “Introduction to the Second Generation of multivariate Analysis” in Theoretical Empiricism( H. Wold eds.), Paragon House, New York, pp. vii–xl. Zack, M. H. (1999) “Developing a knowledge strategy,” California Management Review, Vol. 41, No. 3, pp. 125-145.

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Towards Process Modelling in ‘Knowledge Management’ Work John Kawalek and Diane Hart Sheffield University, UK [email protected] [email protected] Abstract: This paper draws from the experience of undertaking what has been termed ‘knowledge management’ work, and outlines the approach being taken, which has focused on the conceptual design of human processes. This paper presents a way of thinking about knowledge management as a set of processes involving (for example) (i) the human process to which human knowledge is applied (e.g. an ‘operation’ of some sort), (ii) the human process in which knowledge is encouraged to be developed (e.g. a course of study, application of techniques, thinking, reflection etc), (iii) a process of reviewing a the experience in problematic situation in order that learning can be derived (e.g. an ‘after action review’), (iv) the integration of all the above processes which is in some way ‘managed’ and ‘co-ordinated’ through the process of undertaking work as a ‘knowledge manager’. The approach being taken assumes that it is the processes that are being managed, rather than the knowledge per se. The paper outlines the approach taken which draws upon the experiences, difficulties and anxieties of taking responsibility for a knowledge management initiative associated with the EU funded MEDFORIST project. Keywords: Knowledge, process, methodology, design, management.

1. Introduction The MEDFORIST project is an EU funded project with the objective of helping e-business practitioners in the Mediterranean region to become more able to exploit the potential benefits of information and communications technologies (ICT) in regional organisations. An effective knowledge management process was considered by the project designers to be a key aspect in (i) enabling some key practitioners to come together to improve their knowledge, thinking, ideas, assumptions etc., about how to exploit ICT’s in their own regions, and in their own organisations; (ii) disseminating new ideas through a variety of forms of training and communications programmes. The community members were chosen because of their own high profile status in their own countries in the area of ICT and initially consisted of approximately fifty people from twelve countries. One of the components of the work has been to develop a knowledge management process, and since the community members are geographically dispersed, the use of ICT is seen to be an important enabler. This component of the project was termed ‘knowledge management’ for want of a better description, although at the outset, there were some reservations about use of this term because early in the project it was recognised that knowledge is something that is uniquely human, and thus management of it could be conceived as being tantamount to telling people how and what to think! Nonetheless, it was also recognised that there was a potential benefit in sharing experiences, ideas, methods, techniques, approaches etc., in how to apply and use ICT in organisations in the region, because of the high potential that this new field (i.e. ‘e-business’) has for regional organisation development.

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There has been substantial preliminary work that has been undertaken, which has involved: (i) A highly critical ‘best practice’ analysis from other sectors, and (ii) A highly critical analysis of the literature on the nature of knowledge management. Certain conclusions from this work are drawn out in section 2 of this paper, although they are articulated in more detail in other publications (see for example Kawalek & Hart 2003, Kawalek 2004). This paper focuses on the challenges of design of the human processes in knowledge management, and in particular our search for a set of conceptual structures, which fitted with our conclusions on ‘best practice’ and the nature of knowledge management as detailed in section 2. It was a search, which required finding a way of thinking to help ground and guide the future work of the MEDFORIST project and its service to its community. The outline of this thinking forms the main body of the paper (section 3). The conclusions drawn are, we feel, fairly significant, in that they provide a ‘process’ approach to knowledge management, with some tentative ideas about guiding methodologies. Whilst the paper only outlines some preliminary work on the project, we feel that this work is sufficiently significant for publication at this early stage, because practice based organisations in the field have been searching for the practical guidance, grounded in methodology, so that serendipitous policy, designs, actions and investments can be replaced by a more grounded view of knowledge management initiatives (see for example Heisig & Iske (2003)). By being focused on human processes, we argue that it is not the knowledge that is being managed, but a set of

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integrated human processes. In section 4, the paper proposes a number of these as a starting point, ready for further refinement. This refinement is considered to be a process in its own right, and is envisaged to involve ‘design’ type thinking and activities, and iterative process modelling. At this stage, this is envisaged to be a core aspect of methodology in knowledge management. The next stages of the MEDFORIST project is seen to be the vehicle upon which this approach, and potential methodology, is to be further refined and developed. Section 5 considers the relevance of the approach and how it fits in with other recent and current attempts to provide guidance to those responsible for implementing knowledge management initiatives.

2. Lessons from the preliminary work A selection of sectors and projects were analysed via cases, existing literature, and also from the experience of undertaking an action-based piece of work in the humanitarian sector. The purpose was to try to learn as much as possible about how knowledge management is practiced, and the issues, constraints and problems that are faced by practitioners. There were many learning points that came out of this work, and these are articulated in Kawalek & Hart 2003. Some key points are selected and summarised here. (i) Technology in ICT based learning initiatives might be considered to be a key enabler, and must always play a secondary, support role if the objective is to develop human knowledge. This is based on the assumption that no technology holds knowledge. Only humans hold knowledge, although human interaction with data (which may be stored and/or transmitted electronically) can form part of a knowledge development process. (ii) In the humanitarian sector, there is a perception that it has been traditionally poor at learning from past experiences, with change being limited to narrowly defined operational activities (see for example Suhrke, 2000). Structural, political and cultural dimensions to operational effectiveness have been often ignored (Minear 1998, Van Brabant 1997). We perceive this to be a constraint that limits knowledge development and the potential for operational improvement. This also demonstrated to us that structural, political and cultural

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dimensions could not be separated from human knowledge, because these have influence on what people perceive to be ‘valuable’ knowledge. (iii) The military sector relies heavily on learning from the effectiveness of its operational activities. Its After Action Review (‘AAR’) process demonstrates how open and honest debate encourages learning about both the problems of operations, and the individuals’ role in those operations (see Morrison and Meliza 1999). The after action review process also highlights the importance of the role of facilitator. For example, it is said that in the AAR process the role is very influential on the outcome. Some key recommendations are that the role must be undertaken adeptly, focussing proceedings according to the perceived intended learning outcomes, without necessarily prescribing the issues. The success of the process also depends on the extent to which all participants understand the purpose of the activities or the issues under review, and conditions that foster a culture of trust rather than blame. (iv) Unlike the military sector, in the UK health sector there is much more ambivalence and ambiguity as certain changes have been occurring. For example, sometimes there is an assumed transition from a single, national organisation with what could be perceived to be a ‘command and control’ structure into a complex set of autonomous organisations, (or Trusts). Since the health services are highly focused on service targets, issues of learning and knowledge can only be justified by reference to the targets. One knowledge management initiative involves developing virtual communities of practice (see www.ecommunity.nhs.uk). However, observations of unfacilitated online discussions have shown these to be unstructured and lacking in real learning or ‘knowledge’ outcomes. This demonstrated to us that there was a need for facilitation, which may need defining in online situations, and may be an important consideration in defining a knowledge management role. This is not to say that discussion forums always need specific facilitators, but there is need for guidance of some sort. Otherwise the sessions can degenerate into ‘pub talk’ that lacks focus. Furthermore, there are other challenges because learning activities must be justified against service

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targets, which is something that can be difficult given the broad nature of knowledge development activities. (v) The construction industry is characterised by groups of technical teams coming together from a range of different organisations, (mostly small, but some big), and the workforce is often transitory, brought together for fixed-term projects. In a situation quite similar to the MEDFORIST project, the construction industry workforce also has disparate learning needs. The COLA initiative (http://is.lse.ac.uk/b-hive) attempts to bring together these learners, using ICT to form virtual communities of practice to conduct reviews of operations and practices when there is a perceived need. These processes emphasise the importance of using critical reflexive techniques in the review process, and the need for community rules for the use of information and data to engender a culture of trust within the community. In addition to the analysis of practice, a deep critique of the literature on knowledge management was undertaken. The purpose was to evaluate what, if anything, the literature could help with in terms of furthering the objectives of the MEDFORIST project. Much of the more recent work on knowledge management offered interesting and useful insights, concepts and definitions, but was largely devoid of methodology, in the sense that it seemed to lack a focus on justifiable guidelines on how to undertake the task. Also missing was guidance on how to undertake the role of ‘knowledge manager’. One explanation of this was the problematic nature of knowledge itself, and a corresponding ambiguity in the literature about its ‘management’ (see Kawalek & Hart 2003). In doing a literature search, we were able to develop our own ideas about the nature of knowledge management and its implications for the MEDFORIST project. We present here some a short summary of our reasoned assertions and principles: (i) Computer databases cannot hold knowledge. They can only hold data, and it is the human interaction with it that is important; (ii) Human knowledge is teleological (i.e. it has purpose). Questions which attempt to ascertain (a) what people say is ‘knowledge’; (b) what people take knowledge to be; (c) how knowledge is applied into practice; (d) how knowledge is acquired or developed …etc, each can

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be analysed for their teleological characteristics; (iii) Knowledge is considered to be largely “tacit or rooted in tacit knowledge” (Polanyi 1964, p.144). ‘Explicit knowledge’ (i.e. knowledge that is communicated, written down, expressed in some way) is only ever a limited representation of human knowledge; (iv) From the perspective of the user, explicit knowledge might best be seen as data, because one person’s explicit knowledge does not necessarily mean another can use it to guide their actions. For example, a recipe is data in particular form, which could also be considered to be explicit knowledge, (i.e. it is a representation of some sort of the knowledge of an experienced cook). However, it remains data because novice cooks may not be able to interpret the recipe as the experienced cook intended it to be interpreted. The human knowledge of the novice cook and the conditions (of the kitchen) in which they work, (e.g. availability of utensils, measuring devices, time, social-political support for the cooking activity), play a key role in guiding the actions of the novice. The ‘explicit knowledge’ is only a component, and can be considered to be data because it may have limited meaning and a limited role in guiding the actions of the novice. (v) Critical reflection has a significant role to play in improving action and the knowledge required for action (see Kolb 1984, Schön 1983); (vi) Knowledge development through sharing experiences in communities of practice depends on common understanding of the context and language used (see also Brown and Duguid 1991, Lave and Wenger 1991). Thus knowledge and the context from which it is constructed cannot be separated; (vii) These perspectives also consider knowledge development to be a dynamic process, in which, through knowledge sharing and critical reflection, the current state of knowledge is constantly being cross-referenced with new experiences and contexts to generate new knowledge; (viii) An environment which encourages learning through dialogue and critical reflection is not one which imposes knowledge and values, but is one in which learners learn to question the underlying values and processes of their learning (see also Freire 1972).

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The constructs and ideas outlined in both the ‘best practice’ and literature review highlighted some very useful and interesting points, and helped to question many issues, but ultimately failed to provide ‘methodological guidance’ (i.e. a set of abstractions that can help guide action in range of different situations) for designing, implementing and evaluating a knowledge management process. Much of the literature focused on certain elements (e.g. technology, characteristics of knowledge), but did not see those elements as a component of a bigger human activity set (or ‘process’), or their ‘design’. It was almost as if the elements were not cohesively integrated as a set of human processes with a set of principles, ideas, methods etc. Instead most of the ‘design’ focus was on technology designs, but not on human organisational designs. The MEDFORIST project has brought with it the challenge of finding some integrating process, and some of the thinking associated with this challenge is outlined in the following sections.

3. The challenge of the design of processes in knowledge management If we were to start try to have an intelligent discussion about the nature of knowledge management, it might be seen to be necessary to clarify (i) what we mean by ‘management’, and (ii) what we mean by ‘knowledge’. Thus, if we take knowledge to be something, then we might be able to work out how to ‘manage’ it! In the following subsections, we will characterise some aspects of both of these.

3.1

Management as a process of designing organisation and intervention

If we take the activity of managing to involve monitoring, intervention and changing organisations, then it would also be reasonable to argue that managers are ‘designers’ of organisations to some extent. Thus, the process of design might be considered to be an aspect of the activity involved in managerial work; the work that is involved in practice can be facilitated by a stream of conscious or subconscious thinking that might be informed by design work in other domains. It might be possible to outline what is involved in design work, and learn by abstracting the similarities and differences in other design activities (e.g. in designing physical things such as a bridge, car, building, robot etc). For example, design work often involves some sort of ‘design vision’ and we might argue that this is also needed in managerial work (e.g. a ‘design vision’ of how

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organisation works, or a ‘design vision’ of how to make intervention in organisation, to help make it work). The challenge in knowledge management is that unlike with the design of physical things the design involves the design of ‘organisation’, including physical entities like people, technologies, machines but also including activities, tasks, attitudes, data, knowledge, power – things that are non physical, but might be considered to be of importance. If we consider the analogy with the design of physical entities further, the ‘design vision’ in knowledge management work, might be considered to be a ‘model’ for integrating the necessary components of the process (people, tasks, activities, technologies etc.) in order to achieve the specific purposes knowledge development or learning. As in any design vision, a model of an organised set of activities must be the product of human thinking and have the purpose of simplifying, communicating and/or summarising in some way the features of the designs that are involved. As in the design work of physical things, the process of deriving an organisational model might follow the consideration of alternative models, in a process of refinement of the models. By selecting from a set of alternative conceptual organisational models, it may be possible to assess their desirability in order to meet intended outcomes, in a given situation, in this case the MEDFORIST community. Organisational models may be represented as a set of explicit expressions, dialogues, arguments, prose or drawings, and can be either communicated or written down. However, they may also be implicit, remaining in the mind of a human (e.g. a ‘knowledge manager’). In either situation, their purpose is to give clarity and purpose to the actions and decisions taken in everyday situations. The process of the construction, refinement and selection of models is a typical process of thought associated with teleological behaviour (i.e. it is purposeful) and, for the purposes of this paper, is termed “conceptual modelling”. It is a process which: (i) In some way describes the characteristics of an activity, or set of activities, and describes the organisation and characteristics of the elements needed to produce specific outcomes; (ii) Attempts to distinguish (at a conceptual level) the difference between the various alternative models; (iii) Assesses the various potential outcomes of each alternative model for a specific

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situation, in order to achieve a specific purposeful objective; (iv) Will have sufficient clarity for others to understand them; (v) Includes an evaluative analysis of how the modelling has informed action in practice in a given situation; (vi) Will attempt to develop general rules, abstractions or methodology, so to avoid the necessity of repeating the same thought processes when faced with similar goal seeking activities (see also Churchman 1971).

3.2

Knowledge, teleology and human processes

If we take knowledge to be humanly constructed, then it is also a reasonable assumption that knowledge has teleological characteristics. For example if we know a bit about what is needed in the human process of ‘constructing a boat’ then it is possible to abstract some key characteristics about the knowledge needed in order to ‘construct a boat’. In this example, the purposefulness of knowledge is connected to one or more aspects of the process of ‘constructing a boat’. The teleological characteristics of knowledge however, are often not quite as simple as this. For example a research process may produce knowledge, which is seen to be an explanation or re-interpretation of worldly phenomena of some sort, and in this case, the teleology of knowledge is connected to both of the following: (i) The purposefulness of the research process and findings, (e.g. what the researchers believe1 to be the importance of the explanation or re-interpretation); and (ii) The knowledge that the researchers themselves possess in order to undertake the process of research. Further, knowledge is a product of human processes, and as such, in all circumstances, must be teleological, if we assume that the processes themselves are teleological. Perhaps another way of expressing this, is that human knowledge can be seen to be derived from, and to support, one or more humans in ‘doing something’ (i.e. as part of a ‘human process’). We are using the term ‘human process’ to mean a grouping of human activities, structured and organised in particular ways, in order to achieve particular outcomes. 1

There is a difference of course between what an individual or social group ‘believe’ and what they say they believe.

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This is not to argue that a human process is ‘rationally’ organised, but it does have a form, which is analysable in terms of how its components are integrated to achieve intended, unintended, known or hidden outcomes. The link between knowledge and human process seems obvious in some ways, but from our critical analysis of the literature in knowledge management, there is often relatively scant integration between these: in much of the literature, focus tends to be on the ‘knowledge’ but not on the process. It is strikingly obvious that starting with the knowledge, and excluding the ‘process’, is tantamount to stripping something fundamental away: using the earlier example, it is as if meaningful discussion can take place on the knowledge needed in constructing the boat, without having any understanding of what is involved in boat construction! Thus, the starting point must be on the ‘construction of the boat’, or to make it more generalisible, any ‘operational process’. If this view of knowledge is considered to be reasonable, then the process of knowledge management must involve the integration between knowledge, its purposefulness and one or more human processes. Further, since human processes can be subjected to ‘design’ thinking, in order to implement the designs, or change current processes by comparing the conceptual designs with ‘real-world’ human processes, then it follows that the process of knowledge management involves careful consideration about the design of the human process in which knowledge is (or is potentially) applied. We will term this human process an ‘operational process’ for want of a better term. However, the careful consideration that is involved has its own challenges, because in the design of any one operational process, there are often very different viewpoints, interpretations and priorities of what that process is (or could or should be). It is also a challenge because an ‘operational process’ might involve non-physical things, and often human processes are not ‘designed’ consciously in quite the same way as physical things. Despite such difficulties, it remains that the knowledge and the operational process cannot be meaningfully separated2. As such, design thinking, conceptual modelling, or thinking carefully and with precision about the operational process is a starting point for 2

Hence the assertion that both human actions and human knowledge can be considered to be ‘teleological’ (i.e. they will be purposeful).

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undertaking the management.

work

in

knowledge

4. A process modelling approach to knowledge management The preparatory work highlighted a number of potential challenges for a knowledge management process for the MEDFORIST community. For example, since the community is widely distributed around the Mediterranean area, technology enables the members to participate in the process, but it must be carefully designed to support the human processes that result in the development of human knowledge that enables that human to improve their role in operational activities. Of course, the technology needs to be designed, but it needs to be integrated into the design of the human processes, and this required developing further conceptual clarity. The development of human knowledge occurs in many forms and in many ways. However, there are structures and activities (or ‘human processes’) that might be purposely designed to help people develop their knowledge. We will term these ‘knowledge development’ processes. In a school for example, children are taught a foreign language, using a range of techniques, methods and technologies etc. The children are being prepared for some potential human activity (an ‘operational process’) in which they might operationalise their knowledge (communication in a different language). The techniques, methods and technologies used in a process of developing children’s capabilities at using a foreign language are components of a human process, but are not in themselves the designed process because it involves other additional components or elements. For instance, in order to achieve desired outcomes the process needs other things such as appropriate attitudes, beliefs, and behaviours, of the human groups involved. Such a human process can be subjected to design thinking, modelled, developed and changed, and can be considered to be one of many different possible knowledge development process designs. Hence, if a knowledge manager designs a process by which humans come together to develop their knowledge (in order to undertake a role in an operational process), this can be considered to be a ‘knowledge development’ process. Modelling the operational process, and the interlinked models of development is seen to be fundamental to design, implementation and evaluation in the process of knowledge management.

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There are a number of points that might be derived from this: (i) In many circumstances there are significant challenges involved in modelling the (a) ‘operational process’, (b) the ‘knowledge development’ process, or (c) the integration of the two. It is recognised that there will often be very different perspectives on how these should or could be designed and operated. As such, the process of modelling is itself problematic. (ii) In designed processes that are supported by technology, the available technologies may place constraints and give opportunity to undertake the process in a particular way, but are not themselves ‘the process’. From the discussion about processes, and how they might be conceived, constructed, designed etc., we could tentatively consider a range of different process models in order to commence a debate about how they might help in the thinking that is necessary to undertake the human process of knowledge management in practice. An example is given in figure 1. Figure 1 outlines some example human processes that might help structure the thinking about the processes that are involved in knowledge management. For example, if we are considering the design features of a ‘knowledge development’ process, we are also concerned with the ‘operational’ process in which and with which the human knowledge is connected. That is to say, if we are concerned with knowledge development, we are also concerned with the purposefulness of the human process that it might be considered to serve or derived from. Human knowledge development processes can take on many different forms, and therefore their designs require particularly creative and conceptual thinking. For example, a process of knowledge development might be in a form similar to that of an ‘after action review’ as discussed in section 2 (see process 3 in figure 1). We have termed this a process of an ‘after action review’ where there is knowledge that is developed from the reflexive analysis of experience. There are many different forms and designs of an ‘after action review’ process, but they serve the purpose of improving knowledge about certain aspects of operational activities, and the individual’s own role in them. It is a form of knowledge development in order that future problems in situations can be dealt with, and that the designs of operations fit their purpose.

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Process 4 : A designed model of the ‘knowledge management’ process, in which the ‘sub-processes’ (1,2,&3) play some role Process 2 : A designed model of a ‘knowledge development’ process

(b) Process 3 : A designed model of an ‘after action review’

(a) (c)

Process 1 : A model of an operational process in which knowledge is applied and developed

Process 5 : A designed model of the evaluation process of the ‘knowledge management’ process

Figure 1: Some examples of potential conceptual process models that are integrated in some way There are some very important points to make about the example process models in figure 1. Firstly, that the models outlined are conceptual, in that they are a product of thinking (they exist in the mind). As such they are not representations of reality, but might be considered to be useful for structuring the thinking about reality (e.g. the undertaking of the task of ‘managing knowledge’ in the MEDFORIST project). At first sight, this may appear pedantic, but it has some significant implications. For instance, if the models are taken to ‘represent’ the real world, then both the models and the process of modelling will have little meaning, because they could be taken to be ‘in the world’ as opposed to ‘in the mind’: as such, the process of modelling will be taken to be ‘organising the real world’ rather than organising the mind to tackle the ‘real world’, and these two are significantly different. Secondly, the tentative examples given in figure 1 are not designs as yet. There are many design features that might be considered important in the refinement of them. For example, it is possible to conceptually apply a variety of alternative constructs that are drawn from other literatures (e.g. the systems literature, or from the process modelling literature). For example, it is possible to think carefully about things such as:

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(i)

(ii)

(iii)

(iv)

(v)

(vi)

Inputs, outputs and the transformations that are potentially made in each of these human processes (i.e. the process that is ‘doing something’); What would be expected in terms of content of each of the human activities (how the ‘transformation’ is achieved); The nature of control, communication and feedback that would need to be in place to make them work; What would the humans who are involved in each of these ‘activity sets’ need (e.g. a given set of motives, attitudes, knowledge, trust, security, incentives, skills etc); How can integration of the different models be seen to be interconnected to the others, e.g. how might output of one human activity be linked to another activity (the undertaking of an ‘after action review’ might feed into other ‘knowledge development’ activities for instance), or how a ‘high level’ view of one process might be linked to lower level processes in a hierarchical structure; Evaluation of the usefulness of process modelling techniques such as ‘role activity diagrams’ or IDEF for assisting design and implementation;

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(vii) Evaluation of the operationalisation of one or more process designs which may bring with it (a) purposely designed outcomes, and (b) other outcomes which were not purposely designed; (viii) The inclusion of the socio-political context in which the work of operationalising the different human processes is being undertaken. Thirdly, the constructs that are being used are to help “clarify” in an area of work, (i.e. ‘knowledge management’) which seems to be problematic in that there is relatively little guidance regarding the practicalities of undertaking the task. It is the next stage that will involve design work of different conceptual process models which may or may not fall into the ‘categories’ of (i) the operational process to which knowledge is applied or used in some way (process 1), (ii) the designs of the various knowledge development processes (represented in figure 1 as processes 2 and 3), (iii) the designs of the human process of knowledge management as might be undertaken by a ‘knowledge manager’ (process 4), and (iv) the design of the evaluation process as depicted in ‘process 5’ in figure 1.

5. The importance of a ‘process’ in knowledge management In our preliminary work (see Kawalek & Hart 2003), we identified a number of major problems in knowledge management and concluded that whilst there were many useful ideas in the field, and there seemed to be an increasing need to take advantage of the opportunities afforded by new ICT technology, there was at the same time, poor focus on guiding principles on how to undertake the task. It means that knowledge management would have no credibility, because there is no way of guiding practice. These conclusions fit with the findings of others. For example Rubenstein-Montano et al (2001) note that there has not yet been a holistic approach for developing a methodology for designing and implementing knowledge management initiatives. In their review of many existing frameworks, they note that they are not consistent with systems thinking because they do not holistically “consider the entire knowledge management process” (p.8) e.g. purpose, knowledge, technology, learning, people, and culture etc., but instead fall into one of two classifications, either: (i) Prescriptive, i.e. that certain actions should be undertaken, (for example ‘acquire’,

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‘store’, ‘share’ knowledge). The majority of frameworks fall into this category; (ii) ‘Descriptive’, i.e. they select and describe the necessary attributes of good practice in knowledge management. They also note that although some frameworks had recognised the importance of the learning process, this had not been adequately addressed. They recommend that a framework should integrate both prescriptive and descriptive elements, and include processes that allow both single-loop and double-loop learning as defined by Argyris and Schön (1978). The problem of a lack of adequate methodological guidance is also recognised by those responsible for setting standards. The British Standards Institute is of the opinion that it is too early in the stage of knowledge management as a discipline to impose rigid standards, but recognises that development and adoption of knowledge management in a variety of sectors, without a reference framework, “has caused unnecessary and avoidable lack of clarity” (see Farmer 2002 p5). Its preferred approach is to build on earlier work (BSI, 2001) in identifying common approaches and understandings in good practice leading to a “KM Framework of Good Practice and Analysis”. It is also working closely with CEN/ISSS in developing the “European guide to good practice in knowledge management” (see Heisig and Iske, 2003). This guide currently outlines a threelayer framework consisting of: (i) The organisational operational context in which the knowledge is to be applied (i.e. its purposes, processes); (ii) The knowledge processing activities (e.g. identify, store, share, apply); (iii) The knowledge capabilities within an organisation (at individual and organisational level, including issues such as motivation, culture, knowledge, skills, strategy, IT infrastructure). This framework attempts to integrate both prescriptive and descriptive elements, prescribing the knowledge processing activities required (identify, create, store, share, and use knowledge), and describing those characteristics perceived as enablers to the processes (e.g.skills, behaviour, tools, culture). It also goes as far as attempting to provide some step-by-step guidance for SME’s when using the framework to implement knowledge management initiatives.

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In this respect the draft framework provides some useful insights into the necessary processes of a knowledge management initiative. Perhaps what is still not adequately addressed in this draft are the learning processes necessary for enabling those who use the framework to know how to identify, create, store, share and use the knowledge that is identified as appropriate to improving their operations. The CEN/ISSS draft framework bears some resemblance to the dynamic model proposed by Nonaka et al (2000) for creating, maintaining and exploiting knowledge. This consists of three main elements: (i) Knowledge creation processes (through didactic interaction between tacit and explicit knowledge); (ii) Shared context for knowledge creation; (iii) Knowledge assets (inputs, outputs, moderators of the knowledge creating process- e.g. trust). In this model, the context for knowledge creation to which Nonaka et al (2000) refer, is the context in which interaction takes place to develop knowledge. This ‘place’ is not a concept associated with a particular time or space, and has an affinity with the concept of communities of practice. The main difference is considered to be that in communities of practice “members learn knowledge that is embedded in the community, ba is a living place where new knowledge is created (p15)”. They also consider that the boundary of a community of practice is firmly defined by the shared purpose, culture and history. This perspective of a community of practice is consistent with the work of those in the field (see Lave and Wenger, 1991). However, it is not clear where an emerging community of practice such as MEDFORIST fits in to such a perspective, since it has no history and its domain of interest, e-business, is also an emerging discipline, the nature of which is itself not yet clearly defined. The Nonaka model (e.g. Nonaka, 1994) has in any case been recently challenged as a model for knowledge creation (Gourlay, 2003), but notwithstanding this the model does not consider the context in which the knowledge created is to be applied.

6. Conclusion We have presented what we believe to be some fundamental and exciting ideas on methodology for knowledge management, based on ‘process’ thinking. Whilst the research is far from complete, we hope that some of the foundational ideas, concepts and

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thinking have been explained. The approach recommended for the MEDFORIST project is around process thinking and modelling, and the research aspect to this is focused on a generalisible methodology for knowledge management. The work intends and attempts to take an holistic and integrative view of the set of human activities involved in knowledge management, which is both relevant and important, as recognised by others (see section 5). The conceptual structure in figure 1, and the thinking that it is based upon, allows the integration of many useful ideas from the knowledge management literature, and in particular enables a process whereby the assumptions about the teleology of knowledge are integrated into a debate about the nature of the operational activities that it is assumed to serve. This linkage is strong in much of the classic literature where experience, learning and reflection are integrated (see for example Kolb, 1984, or perhaps even more fundamentally Singer, 1959). The knowledge management initiative for the MEDFORIST project is being undertaken as an action based piece of research, in a manner akin to ‘mode 2’ in which the researcher is not simply observing and documenting, but is engaged in an everyday sense, in the challenge of undertaking a particular role within the project (see Starkey and Madan, 2001). This enables the testing of methodology, ideas, principles, concepts, frameworks etc., to critique and inform action that can maximise the chances relevance and realism to the research process. It means that the work can be both intellectually rigorous, but it has also the possibility of a highly practical and relevant outcome, which is of course, required in disciplines such as Management, which has an ‘applied’ component. ** Please note ** We would be very pleased to hear from the readers of this paper. Questions, comments, critical or otherwise would be kindly welcomed. Please e-mail us [email protected], or [email protected].

References Argyris, C., & Schön, D., (1978), Organisational learning : a theory of action perspective, Addison-Wesley, Reading. BSI, 2001, (British Standards Institute), “Knowledge Management PAS 2001: A Guide to good practice”. Brown, J.S. and Duguid, P. (1991) “Organizational learning and communities of practice: Toward a unified view of

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working, learning and innovation”, Organisation Science, Vol 2, pp40-57. Churchman, C.W. (1971) The Design of Inquiring Systems, Basic Books, New York. Farmer, T (2002) “BSI position statement on standardization within knowledge management.” London: British Standards Institute. Freire, P. (1972) The Pedagogy of the Oppressed, Penguin Books Ltd., London. Gourlay, S. (2003) “The SECI model of knowledge creation: Some empirical shortcomings”. In Proceedings of the Fourth European Conference on Knowledge Management, 18-19 September 2003, Oriel College, Oxford. pp377-386. Heisig, P. and Iske, P. (2003) European knowledge management framework. In European Guide to Good Practice in Knowledge Management (Work in in progress, Draft Version 3.0), Berlin, Amsterdam: CEN/ISSS Kawalek, J (2004), Systems thinking and knowledge management, positional assertions and preliminary observations, Systems Research and Behavioral Science, in print. Kawalek, J. and Hart, D. (2003) “Designing knowledge management systems for a Euro-Mediterranean network of practitioners: Preparatory work for the MEDFORIST project.” In Proceedings of the Fourth European Conference on Knowledge Management, 18-19 September 2003, Oriel College, Oxford. pp557-566 Kolb, D.A. (1984) Experiential Learning: Experience as the source of learning and development, Prentice Hall Inc., New Jersey. Lave, J. and Wenger, E. (1991) Situated Learning: Legitimate peripheral participation, Cambridge University Press, Cambridge. Nonaka, I. (1994) “A dynamic theory of organisational knowledge creation.”

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Organization Science, Vol 5. No.1, pp1437. Nonaka, I., Toyama, R. and Konno, N. (2000) “SECI, Ba and leadership: a unified model of dynamic knowledge creation”, International Journal of Strategic Management, Vol 33, No 1, pp5-33. Minear, L. (1998) “Learning to learn”, [online], discussion paper prepared for OCHA, http://www/reliefweb.int/library/documents/ stock.htm. Morrison, J.E., and Meliza, L.L., (1999) Foundations of the After Action Review Process, United States Army Research institute for the Behavioural and Social Science, Special Report 42. Polanyi, M. (1964) “The Logic of Tacit Inference” in Knowing and Being: Essays by Michael Polanyi, Grene, M. (Ed) (1969), Routledge and Kegan Paul Ltd, London, pp138-158. Rubenstein-Montano, B., Liebowitz, J., Buchwalter, J., McCaw, D., Newman, B., Rebeck, K. (2001) A systems thinking framework for knowledge management, Decision Support Systems, Vol. 31, pp.516. Schön, D.A. (1983) The Reflective Practitioner: how professionals think in action, Basic Books, New York. Singer, E.A. (1959) Experience and Reflection, Oxford University Press, London. Starkey, K., and Madan, P. (2001) “Bridging the relevance gap: aligning stakeholders in the future of management research”, British Journal of Management, Vol 12, Special Issue, ppS3-S26. Suhrke, A. (2000) From one crisis to another: Organisational learning in UNHCR. In Wohlgemouth, L. and Carlsson, J., (Eds) (2000) Learning in Development Cooperation, EGDI Study. Van Brabant, K. (1997) Organisational and institutional learning in the humanitarian sector, opening the dialogue, a discussion paper for the Active Learning Network on Accountability and Performance in Humanitarian Assistance, ODI, London.

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KM Infrastructure and Electronic Services with Innovation Diffusion Characteristics for Community Economic Development Dawn Jutla Saint Mary’s University, Halifax, Canada [email protected]

Steven Feindel Nova Scotia and Municipal Relations, Nova Scotia, Canada [email protected]

Peter Bodorik Dalhousie University, Halifax, Canada [email protected] Abstract: Building knowledge management (KM) infrastructure involves reuse and refocus of several existing infrastructure components, and awareness around future visions and conditions of infrastructure. We present a community perspective using a staircase metaphor for conceptualizing government supported KM infrastructure and services. Additionally we illustrate a model for government’s role in providing and leveraging infrastructure components from all tiers of government. With examples, we build a case for adding diffusion of innovation characteristics, and features from innovation networks analysis in KM infrastructure. Observability and trialability are important to knowledge acquisition, while compatibility are central to knowledge application, packaging, and creation. Ease of use, and perceived usefulness affects knowledge use in all its forms. Keywords: KM infrastructure model, SME, small business, economic development, e-Government, knowledge services, diffusion characteristics, community

1. Introduction More sophisticated services than are currently available are required to serve the noble goals of many web sites set up to make information and knowledge available to all. As a sector example, sites such as www.canlli.org, www.austlii.org, and www.law.cornell.edu all share a similar mandate to make legal information available and freely accessible to ordinary citizens. However, a current search on, say, privacy law on these sites is not useful or easily decipherable to most of us. Needed are real technological advances in methods for natural language processing, context-sensitive text mining, and image and voice processing to realize full technology-enabled KM. In recent years, Web sites, Intranets, and search engines such as google and kartoo have become markers on the course to the future of KM. The cycle of technology research, invention, adoption, and use is only one facet of KM. Keep It Simple Stupid (KISS) is a guiding principle to knowledge diffusion. Such principles are rooted in the diffusion of innovation literature which identifies characteristics such as ease of use, perceived usefulness, observability, trialability, and compatibility as critical success factors. Nonaka and Takeuchi’s (1995) famous model for knowledge creation in companies identifies the two key forms of knowledge, tacit and

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explicit, which characterize various conveyance means for knowledge and thus motivate the combination of vehicles through which we acquire knowledge and skills. Additionally, the field of research on innovation networks analyzes topological issues such as the relation between the strength of the linkages in the networks through which we transfer knowledge, and network homogeneity that can degrade innovation capability. It is our thesis that knowledge management infrastructure and related services should be built from the ground up with learnings from various fields. In this paper, we particularly focus on KM infrastructure that governments build with the intent for small and medium sized enterprises (SMEs) in communities to leverage for economic development. We illustrate our thesis using as an example the government of Canada’s work in this area. Motivated to increase the country’s productivity, the Canadian government issued a 10-year innovation strategy agenda in January 2001. Canada’s innovation strategy identifies goals, targets, and government priorities in four key areas: knowledge performance, skills, innovation environment, and community clusters. In this paper, we describe knowledge management (KM) infrastructure to support Canada’s four key strategic areas from the perspective of three tiers of government: federal, provincial, and

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municipal. Within the tiers, we illustrate the KM infrastructure in terms of innovation network theory (Allee 2000, Ahuja, 2000; Baum and Ingram, 2000; Benassi and Gargiulo, 2000, Burt 1992) and innovation diffusion theory (Mahajan and Muller, (1979); Davis, 1989; Mahajan, Muller and Bass, 1990; Mathieson, 1991; Moore and Benbasat, 1991; Rogers 1995; Hu et al, 1999; Agarwal and Prasad, (1998); Durrington et al., 2000) with respect to knowledge management. Both fields of study facilitate the knowledge and innovation creation and diffusion process. Furthermore, we map many of the findings in these two fields to Nonaka and Takeuchi’s (1995) knowledge creation framework thereby showing why findings in these two fields are important to knowledge management.

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2. The community cluster perspective for knowledge infrastructure and service We present a conceptual community view of a country’s knowledge management infrastructure in this section. This perspective helps us to visualize community clusters. Community clusters are not limited to spatial proximity in our view. Figure 1 illustrates our community cluster perspective, shown from the view of someone standing at the top of a wide staircase and looking down. The top stairs represent the communities in a country. Some citizens view the entire staircase as one community. Some citizens only see one tile in one stair at the spot where the citizen is standing. It is important when managing knowledge for governments to take a wideangle view from the top of the staircase – the community focus. The top staircase level in Figure 1 represents KM infrastructure for all the communities in a country. The level beneath represents that for all the municipalities and counties; the one just below represents the provincial KM infrastructure. The bottommost rung and the KM infrastructure common to all is the federal KM infrastructure. We propose not to duplicate the common infrastructure provided at bottom steps at higher levels. Rather, federal infrastructure should be leveraged and efforts at the top of the staircase should be targeted to knowledge not easily available at the bottom of the staircase.

We organize the paper as follows. Section 2 presents communities’ clustering from a KM infrastructure view. Section 3 reviews a model for federal and provincial government to use as a guide for building KM infrastructure, as well as provide illustration of the model with best practices in Canadian KM infrastructure. In section 4, we make a recommendation for a provincial KM infrastructure piece that is still missing from the Canadian governments efforts. Section 5 targets how communities build their own KM infrastructure and use it. Finally, section 6 provides a summary and conclusion.

Looking Down

A

A

B B

A A

A

B

A B

Figure 1: A Staircase Metaphor for Knowledge Management Infrastructure

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Knowledge management infrastructure for community clusters form from slicing and dicing the stairs, according to themes, or industry sector, or other common criteria. For example, a community cluster (see A in Figure 1) could consist of the historical rural shipbuilding communities of River John in Pictou County, and Shelburne in Yarmouth county, both in the province of Nova Scotia, plus the past shipbuilding city of Saint John in the province of New Brunswick. Another example of a community cluster (see B, in Figure 1) may be all the communities belonging to one county where geography and political leadership are the common ingredients. Although we place emphasis on knowledge management infrastructure for economic development in urban and rural communities, our model clearly shows that local KM infrastructure does not exist in a vacuum. Indeed, local infrastructure is greatly impacted and often path dependent on higher tier government KM infrastructure. The KM infrastructure at the national/federal level is pervasive in a bottom-up fashion and is accessible by all tiers of government. Integrated service delivery is a frequently-used term in government that refers to the integration of services across layers of government departments, agencies, communities, and jurisdictions. Using the staircase metaphor, we can effortlessly conceptualize horizontal-only vertical-only, and then combinations of horizontal and vertical usage of infrastructure. Horizontal-only integration is more apt to occur at the bottom rungs of the staircase, at the federal level for instance. In contrast, innovative community services may require higher degrees of both vertical and horizontal integration of infrastructure services.

3. Federal and Provincial KM infrastructure model The Canadian federal government summarizes the challenges of creating and maintaining a knowledge economy in the four key areas of priorities as follows (GoC, 2001): “Knowledge performance: Finding better ways to create knowledge and for firms to bring these ideas to the market. Skills: Ensuring that in years to come that Canada has enough highly qualified people

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with the skills for a vibrant, knowledgebased economy. The Innovation Environment: Modernizing business and regulatory policies to support and recognize investment and innovation excellence. Community clusters: Supporting innovation at the local level so that our communities continue to be magnets for investment and opportunity.” We capture these federal government priorities in the following model (Jutla et al 2002, Jutla 2003), illustrated in Figure 2, which guides governments in building infrastructure for a knowledge-based society. Keeping in mind that a major government role is the building and maintaining of many types of infrastructure, we will show that each of the six components in our model require knowledge assets, and hence a layer of knowledge management runs through them. We present a working definition of the term infrastructure before we introduce the different areas of infrastructure to support services that are essential to knowledge-based societies. We adopted Slootweg and Verhoef’s (1999) definition of infrastructure, and modified it to include assets such as workforce, and skills; in electronic society, physical facilities include physical network backbones, databases, and hardware/software. “An infrastructure is a large-scale technological system, consisting of physical facilities and knowledge assets, and delivering (an) essential public or private service(s) through the storage, conversion and/or transportation of certain commodities/services. The infrastructure includes those parts and subsystems necessary for fulfilling the primary storage, transportation and/or conversion function(s) as well as those supporting a proper execution of the primary function(s).” The model in Figure 2 suggests that a knowledge and innovation based economy is the desired outcome of effectively building the following six components’ infrastructures and processes. Each component has associated process inputs and outputs, as infrastructure is set up to support a particular flow (e.g. content, regulation, e-government service, communication, skill).

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Societal Knowledge and Innovation Organizational (KI&O)Infrastructure EXTERNAL INPUTS (including from KI&O Infrastructure) (e.g, collections and those listed below) (0) Multi-disciplinary input (2) (3) B.Human 2.Learning A.Comm/IS Technology Tech. Skills Infraand other systems infrastructure info new structure processes Infrastructure uses & practices Tech advances (1) 1.Build (1) comm. & ISs (1) New knowledge & innovations 0. Create Knowledge and Innovation

Other-needs driven (6) (4) (5) New 3. Build tacit Content C. eContent models, 4. Create policies e-content& knowInfrastructure & business and mechanisms processes how and processes for intangible content mgmt. (7) (5) expertise Existing content

(1)

(9)

(1)

(1) (10) Positive E. e-gov’t E-business Services Readiness infrastructure climate

(9) Integrated 5. Create Private-public e-gov. Sector services services and/or convenience e-services

(8) Policies

Policies (7) And mechanisms D. Regulatory, Financial, And Trust Infrastructure

(0)

Input to K&I Output/use of K &I

EXTERNAL INPUTS (including from KI&O Infrastructure (e.g. patents, new partnerships, research, stakeholder needs, existing bodies of knowledge)

Figure 2: KM Infrastructure [adapted from Jutla 2003].

We conceptualize dependencies in the model at a high-level in Figure 2, and refer the reader to Jutla et al (2002) for details on the conceptual literature surrounding this model. We provide visibility in Canada’s work in building each major infrastructure component, shown in the model in Figure 2, in the subsequent sections of this paper. Knowledge management relies on the following six infrastructure components. 1. Communications and information systems infrastructure (A) 2. Human infrastructure (B) 3. Content infrastructure (C ) 4. Regulatory, trust, and financial infrastructure (D) 5. e-Government infrastructure (E) 6. Organizational infrastructure for knowledge and innovation (F) Some notes for reading the model shown in Figure 2 are given:

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a)

All infrastructure components (A, B, C, D, E, F) output (see broken lines) to the “create knowledge and innovation” process (complex aggregate of many processes) which then provide inputs (see double lines) to all other processes used to build the six infrastructure components. b) Each infrastructure component has many complex processes inputting to it and accepting output from it. For simplicity, we show only one aggregate process per infrastructure component as input. c) The KI&O organizational infrastructure (shown as the cloud) connects and “oils” the rest of the infrastructure components. d) Information flows are labeled with numbers (0), (1), (2)…(10) in brackets. e) Processes are also numbered (0, 1, …5) without brackets.. Although there appears to be a linear sequence among components in our proposed model, it is possible, to have different orders and priorities of building infrastructure components; and it is recommended, to build

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components in parallel whenever possible. The order we present in our model was the naturally occurring and logical ordering found in most government facilitation to date. Indeed, organizational infrastructure often appeared quite late in many countries’ e-government efforts, grafted on when change management in the workplace was identified as critical to success. Indeed, in many countries, first-generation knowledge infrastructure at a national/federal level involves getting citizens’ access to government information and codified knowledge on government Web pages. Thus, information and communications technologies (ICT) infrastructure is among the first KM infrastructure components we build. It is a good case for priority since ICT infrastructure serves more than KM purposes. Provinces, municipal, and urban and rural communities are being encouraged by the central government to (1) partner and collaborate, (2) serve sophisticated and global markets with demanding customers, and create unique products/services, and (3) meet global standards in order to promote and sustain economic development. Thus, steps are being made to address the fact that many communities often lack both the absolute and comparative competitive advantage to participate in the world market place (Sieber, 2003). e-Government strategies are pioneering a second generation of knowledge management infrastructure to support the communities’ economic goals. Secondgeneration knowledge infrastructure includes creating innovation networks by connecting existing networks, digitized content, and knowledge repositories. This rest of this section illustrates how the Canadian government is satisfying theoretical characteristics of diffusion of innovation and creating core features of social networks found in literature in the practical setting of providing KM infrastructure. We organize the KM infrastructure according to six components in the model for building knowledge and innovation infrastructure illustrated in Figure 2.

3.1

Organizational infrastructure and services

Organizational and social science factors are often afterthoughts in technology diffusion processes. However, organizational infrastructure to support e-business diffusion needs to be built and woven into the fabric of society and business from the very beginning

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and governments can play an important role here. Organizational infrastructure, consisting of innovation networks and governance structures for coordination, aggregation, funding decisions, and bridging innovation networks, is a key factor in knowledge performance. Innovation networks are vehicles for diffusion of information, knowledge and innovation across many different individuals and groups in organizations, governments, and among countries. Researchers define diffusion of innovation as the process by which an innovation is communicated through certain channels over time among the members of a social system (Rogers, 1995). Innovation diffusion theories split commonly into two groups, with researchers focusing on either innovation characteristics’ analysis or social network analysis (Higa et al, 1997). Diffusion theories have many parallels in KM. The most popular innovation characteristics are relative advantage, compatibility, observability, trialability, and complexity (Rogers, 1995). Observability is the extent to which the results of an innovation are observable to others. We can immediately map the observability construct to Nonaka and Takeuchi’s (1995) model of knowledge creation. For example, a primary vehicle for the flow of tacit knowledge occurs through socialization (Nonaka and Takeuchi, 1995) or behavior/innovation observation, and beliefs copying. Trialability is the extent to which an innovation can be experimented with before adoption We map trialability to knowledge internalization in Nonaka and Takeuchi’s (1995) flow of explicit to tacit knowledge quadrant. Complementary research into social network analysis explores the strength of the relationships in the network, and the network topologies. Social capital in the relationships among network participants assists in coordinating and integrating knowledge from many diverse fields. Often the knowledge that is transferred among individuals, groups, teams, and others is tacit and can only be learned through communication, articulation, or personal interaction – combining the externalization and socialization quadrants in Nonaka and Takeuchi’s (1995) knowledge creation framework. Networks ease the knowledge transfer and absorption process within and among stakeholder organizations (Allee, 2000), thus also assisting internalization (Nonaka and Takeuchi, 1995). Additionally, innovation networks enable a stakeholder to draw on knowledge from external sources that

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the stakeholder would not have been able to access otherwise (Gargiulo and Benassi, 2000, Ryecroft & Kash, 2000). These networks create flexible systems enabling communities of practice or “informal and semi-formal networks of internal employees and external individuals based on shared concerns and interests” (Malhotra, 2000). Networks can also facilitate lobbying, representing, marketing, promotion, sector alliances, and international alliances, all activities important to economic development. Governance structures to support various communities of practice form another part of organizational infrastructure. At the federal level, the Canadian government created an Organizational Readiness Office (ORO), under the Chief Information Officer Branch of the Treasury Board of Canada Secretariat, to provide such governance. The ORO develops community work plans, and research and demographic-analysis capacity for knowledge sharing networks or communities of practice. Currently, the ORO supports three communities in the public service of Canada: information management, information technology, and service management communities of professionals. According to the ORO’s web site (www.cio-dpi.gc.ca/orobgc/index_e.asp), “..the ORO is also being recognized as a center of excellence in nurturing informal workplace learning and knowledge sharing networks...” The ORO networks establish a normative environment that allows community members to expect a certain code of conduct from other network members. ORO community members bond through the increased perception of the similarity among community members’ goals and values. Rogers’ (1995) innovation diffusion characteristic of compatibility or the extent to which an innovation is perceived to be compatible with current values, needs, and past experiences of potential adopters is present in the ORO’s efforts. As evidence, the ORO site publishes the results of community exercises to identify and relate the similarities among the group and individual’s goals and values for each supported community. Federal-level Industry Canada plays an active role in creating partnerships between public research sector and private sector, often sponsoring workshops and conferences for facilitation. Behind the scenes, the Canadian government has enabled a network of government departments and agencies that service industry to co-ordinate and exchange

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research projects, experiences, and programs as an initiative under its “e-Business Growth Strategy.” To complement the public sector activities, a Canadian e-Business Opportunities Roundtable (eTeam, 2002) comprising of mainly private sector representatives was formed in mid-1999 to “accelerate Canada’s leadership in the digital economy.” In 2002, the Roundtable morphed into the Canadian e-Business Initiative ( www.cebi.ca). A good example of the contribution to innovation networks and governance, at the provincial level, is the knowledge infrastructure that the Integrated Services Delivery Division (ISDD) of the Ministry of Consumer and Business Services maintains to support the Ontario Public Service. Several publications (Socitm 2002, ICCS-ISAC 2003) identify that turf tension, organization culture clashes, resistance to change, and tunnel vision are some of the key organizational barriers around providing better e-service delivery to provinces, municipalities and citizens. In 2003, the ISDD addressed the barrier by Web publishing an excellent, and pragmatic, Partnership Workbook that contains the “concepts, knowledge, and experience garnered from research, workshop, and consultations” (ISDD 2003) on the topic of partnerships. This 77 page workbook resource and others, such as a template for a funding agreement between the federal government and a provincial business services society targeted for community economic development, can be found through the Institute for Citizen-Centred service Web site. See figure 3 for a web of other knowledge resources relating to using electronic means for service delivery as well as community economic development. Other provinces in Canada, such as Nova Scotia and New Brunswick, centralized service delivery by creating a Department solely responsible for this function. Nova Scotia created the Department of Service Nova Scotia and Municipal Relations (SNSMR) incorporating the former Business and Consumer Services portfolio. Unique to Nova Scotia’s centralized model is the elevation and recognition of the importance of municipal relations as demonstrated in the Department’s name. The department actively supports innovative service deliveries from a wide variety of federal agencies, municipal and intra-provincial partners. More recently, the Nova Scotia Justice department, Halifax Regional Municipality (HRM), and the Registry of Motor Vehicles function of SNSMR

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partnered to allow citizens to pay parking fines through a single service access point hosted by Service Nova Scotia as opposed to going to 3 separate access points including Justice and HRM. Building on e-government service delivery, SNSMR actively participate in knowledge creation, transfer, use and delivery by sharing their expertise in facilitation, integrated processes, best practices, and knowledge around Web sites portals with municipal partners such as the e-government award winning Cape Breton Regional Municipality, and communities such as Pictou County’s River John (www.riverjohn.com). The province enhances knowledge transfer through an informal “loan “ of a skilled person resource for a few days in whatever IT capacity the partnering community requires.

3.2

Access to communications and information systems infrastructure and services

The first generation of access to a firstgeneration online knowledge infrastructure was driven from the federal tier of government from the mid-nineties onwards. Since then, Canada has made many advances in increasing access of its citizens to a communications infrastructure for knowledge diffusion. For example, through the community access program (CAP), Canada connects 10,000 communities. The VOLNet initiative connects a further 10,000 voluntary organizations. In terms of communications infrastructure, Canada has the world’s longest purely optical network at 6000 km. It has the capacity to exceed 40Gbps. According to the OECD (2001), the country is also second in the OECD in terms of broadband penetration. Com Score Metrix Canada and Nielsen Ratings report that approximately two-thirds of Internet home users in Canada are currently subscribing to broadband services in 2003. The Canadian figure is almost twice the broadband penetration of US households. Current deployment of broadband infrastructure can support access from 80% of the population. In the world connectedness index, Canada ranks second with respect to availability, third in price, and first in reach and use (Conference Board of Canada, 2002). To further support community economic development, Canada has the second largest number of community “freenets” behind the US (see http://www.lights.com/freenet). The freenets intend to provide free email and Web space to individual users. Many freenets are charging a small fee now but it is still possible to find some free service providers for dial-up

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and DSL services, and to connect mobile personal device assistants (PDAs) to the Internet. The freenets are a low cost solution for hosting the Web sites of small businesses in distressed yet connected communities. A theme throughout supporting knowledge management in this paper is reuse of existing infrastructure elements. In the physical ICT world, technology advances such as ad hoc networks (Malek, 2003) are reusing existing devices such as personal computers, printers, and even toasters as relay devices for mobile communication packets. Through the vision and eventual realization of the Semantic Web, we expect some refinement of ICT infrastructure with standardization around platforms supporting user agents’ communication for useful Web services. Examples of potential Web services include: easily seeking out useful knowledge, automating the integrating of information and knowledge from various stakeholders, automating the visualization of information and knowledge according to a range of user profiles, and managing collaborative stakeholder updates to distributed assets containing domain knowledge. Provincially, there has been a move towards the standardization of ICT infrastructure. Nova Scotia has over 8000 licenses for SAP financial and human resource applications. When the Cape Breton Regional Municipality (CBRM) had a successful, low-cost implementation of SAP R/3™, providing activity based accounting and customer relationship management, CBRM was well on its way to providing its communities with infrastructure on which to develop community services. CBRM achieved low-cost implementation through knowledge transfer around SAP™ from the Halifax Regional Municipality and Services Nova Scotia and Municipal Relations, thus reaping one of the main benefits of standardization – access to an existing pool of skilled resources and proven procedures. Such standardization links to the compatibility characteristic in the diffusion of innovation literature. Its benefit shows relative advantage. Another government effort emerging from Denmark (DK 2003) to standardize open source software links very closely to compatibility with respect to alignment in country’s values. We have not yet seen the diffusion to communities of the next generation of ICT infrastructure that will provide powerful visualization of complex phenomenon, and

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integration of voice capabilities. Emerging ICT paradigms such as the Semantic Web and computer grids are expected to provide interoperability and plug and play capability of software applications running on optimal configuration of hardware, and knowing where to access appropriate data. The application of knowledge supported by these powerful systems could revolutionize many fields. Some predict that in the next 50 years, all information about objects including humans, processes, and organizations will be online (Brown and Dugald, 2000). Perhaps all meta-information will also be available so that machine agents will be able to help humans sift through the vast volumes of data, and to reason to produce useful knowledge.

3.3

Human infrastructure and services

Human infrastructure consists of a workforce with the skills to effectively and efficiently acquire, apply, create, and transfer knowledge. A preliminary study shows that most employees create knowledge within scope of his/her expertise, and most package existing (versus creating) information and knowledge, whereas all interviewees apply knowledge in their job (Daigle-LeBlanc, 2001). Knowledge transfer to students, SMEs, and communities is being done on several fronts. Infrastructure comprises skills distribution channels, not only over the Internet, but also through existing channels including the faceto-face channel. Strategists agree that using existing, branded, skills distribution infrastructure is effective and recommend modifying or adding new programs to deliver over them. Adding complementary Internet delivery channels to these delivery systems increases their reach and provides material to support their programs in a cost effective manner. Governments, associations, and communities transfer knowledge to citizens and members through services such as educational seminars, practice sharing, and job training. One of the more useful mechanisms for transferring knowledge and innovation to the SME sector is through distribution channels such as university business development centres, and government business service centres. These provide pertinent e-business development skills at very low cost to SMEs. Traditional services have included writing business plans, developing new products, and assisting with complex accounting and taxation issues. These centres and/or networks have

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existing client bases that they can influence directly and hence increase the rate of ebusiness adoption by SMEs. In 2000 and 2001, agencies of Industry Canada conducted dozens of workshops and seminars on ecommerce for the SMEs across Canada. Supporting Canada’s Innovation Strategy is Industry Canada’s Student Connections Program (SCP). Running out of provincial business service centers, community colleges, and university business centers, the SCP (http://www.scp-ebb.com) hires and trains post secondary students and recent graduates from universities and community colleges as small business advisors. Although the Students Connection Program trains on a whole variety of business services, it has been responsive to the government’s desire to e-business enable its SMEs, and currently offer face-to-face courses on Internet training, customized Internet training for seniors, electronic commerce implementation, and electronic commerce strategy at beginner and advanced levels. Supplementary, free online course materials are also available. Generally, government support for the development of e-business knowledge and innovation has focused on setting up research centers, helping e-business ventures in key national industrial sectors, and on facilitating the adoption of e-business by the SME sector. Research institutes have been encouraged to combine expertise from multiple disciplines such as engineering, computer science, business, law, and policy. Other research institutes have set up associated e-business incubators to facilitate the transfer of innovation to the commercial SME sector. Infusing existing infrastructure for research and development with additional funding for strengthening and expanding multidisciplinary research, and for creating additional places for higher education in targeted disciplines, is another way of expanding knowledge assets. According to (FF4, 2003) “the skills gap in Canada is most severe in the core occupational disciplines of computer science, microelectronics design, photonics and wireless design, software design, and systems analysis.” Thus, demand for skills is still high in subsets of the computer science (CS), management of information systems (MIS), and electronics and electrical engineering (EE) disciplines. These are among the disciplines that tend to create skill sets to invent new technologies, techniques, and processes.

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Colleges and universities aid in skills’ development and extend the reach of certain skill development services through making them available through online learning and distance education. Online courses are rapidly becoming a commodity accessible to many employees. However, the current workforce generations are not sufficiently familiar with online communication technologies to yet benefit from e-learning programs. FF4 (2003) reports that over “20% of SMEs cannot find the skilled employees they require to implement ebusiness.” Specifically, there are not enough trained personnel with a hybridization of technical and business skills. A recent British survey of health professional students conducted at the University of Sheffield shows that most had never used Internet Relay Chat, message forums, and videoconferencing although they regularly surfed the Web and used email. The conclusion of that study was “ most students do not have sufficient experience of on-line learning environments and therefore future use of Continuing Professional Education material in this environment is likely to be limited (Stokes et al, 2003)”. Fortunately, current groups of highschool students are skilled in the use of on-line chat rooms and message forums. These technologies have diffused in much the same way as hotmail and yahoo mail accounts did (Judge, 2002), through observing friends and colleagues using the media and then trying it out themselves, thus utilizing two powerful

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innovation of diffusion characteristics observability and trialability.



This interdependence of ICT and human infrastructure components is just example of the interdependencies that exist in a knowledge-based economy. We hypothesize that the next generation of university students who are currently growing up with the Internet will be better prepared for training through multimedia and distance. Rich multimedia can facilitate knowledge use in all its forms (acquisition, application, creation, and packaging for transfer). Tacit to tacit, explicit to tacit, and tacit to explicit knowledge transfer is taking place in health training centers around the world where footage of procedures can be played, paused, analyzed, and assimilated before internship or apprenticeship begins.

3.4

Content infrastructure and services

According to a study targeted to measuring knowledge use (Daigle-LeBlanc, 2001), “surf the Web” ranked almost equally to the most popular answer “ask someone” as the most common methods of knowledge acquisition by managers and professionals. The Canadian and other governments have created many Web sites for use as governmental knowledge resources (see a sample in Figure 3) to facilitate the vision of building strong communities that effectively participate in a world knowledge economy.

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Figure 3: A Segment of Canadian Web Sites hosting e-Government Knowledge Resources (source:www.kartoo.com using search keyword: ”Institute for Citizen Centred Service”)

Knowledge portals facilitate access to content: the repositories and other digital collections that contain domain knowledge. Content management software is necessary to maintain up-to-date and relevant information, intelligence, and knowledge. Currently many communities consider a portal as an access point for members as well as for the external world to learn about them, but a fully functional portal can be a knowledge source. Knowledge portals, as vehicles to knowledge delivery, may support tacit to explicit knowledge transfer (Vitales, 2002). The knowledge portal is only one piece of the KM infrastructure; the other piece is the actual knowledge repositories and ontologies. In Canada, we find digital collections for organized content focused on culture, science, geography and other areas at http://collections.ic.gc.ca/. Youth Employment programs create many of the collections, as well as SchoolNet initiatives where students aged 15-30 create web sites using content from Canadian museums, and other archives. A digital repository comprising modernized work descriptions and desired and actual skills for and of government employees across Canada is a knowledge asset that would facilitate recruitment and the optimizing of mobility across the largest workforce in most nations – the government employees. Private sector already have such repositories at http://jobs.gc.ca/itworkopolis.com, ti/index_e.htm, http://www.jobsetc.ca/ , http://www.scp-ebb.com/, and www.ecorps.ca. Canada’s efforts at organizing content for SMEs are best found in the strategis (http://strategis.ic.gc.ca) web site – a site that provides databases of information for trade, supply, export, legal research, business financing, patents, and matches on private sector and university-based expertise to name just a few. These databases also power the www.CanadaInternational.ca site. For more sophisticated community economic development, providing hands-on models with incubator style online marketplaces (Jutla et al, 2003) will be the way forward. In June 2001, the then Minister of Industry launched a service called SourceCAN billed as “.. Canada’s public and private sector emarketplace, connecting Canadian businesses and their capabilities for the domestic and global e-marketplace and exposing

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opportunities through local and international ebusiness partnerships. “ Free access is provided to an up-to-date database of Canadian companies and their capabilities, business opportunities matching, posting, ecatalogues, and virtual trade shows. Five major feeds are input to the e-marketplace. Federal and provincial governments request for bids represent a major feed as the largest proportion of SME economic activity in Canada comes from servicing the government. Business members form another major feed into the e-market. Three major feeds come from the US government. One feed provides general procurement information including sales of US government property, procurement actions, and contract awards. Another US feed is from the Trade Opportunity Program (TOP), a daily feed that lists all procurement opportunities with the US government. The third US feed is from the US department of agriculture listing procurement opportunities in the US agricultural sector. Canadian businesses can display their catalogues free of charge in GE’s Express Marketplace, a B2B digital marketplace that is currently administered by GE Global exchange Services (GXS). However, SMEs do have to pay service charges to GE for selection, procurement, requirements, and transaction payment/billing (settling) services. According to a press release from GXS (2001), the Webbased GE Global eXchange Services' (GXS) Express Marketplace “supports SourceCAN by making supply chain services - such as reverse auctions, procurement workflow, purchase order status tracking, turning purchase orders into invoices, and tracking invoice payment status - available to SourceCAN member companies on a subscription and/or per-transaction basis.” An online demonstration of the Express Marketplace can be found at https://www.gexmp.com/docs/en/demo1.html. Statistics on SME usage of SourceCan are not currently available. One year after the SourceCAN release, in November 2002, the Canadian province of New Brunswick (NB) launched SourceNB – a syndicated, localized version of SourceCAN focusing on the Atlantic provinces ( http://www.sourcenb.ca/E/press_nov20_02.cfm ). With a higher profile to the local business than its parent, SourceNB lists requests for

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bids/tender from governments of several dozens of countries, including Australia, the Caribbean, Africa, Europe, Latin America, and Asia.

3.5

Regulatory, trust, and financial infrastructure and services

The management of technology literature states that online trust ranks as important as ease of use, and perceived usefulness when considering factors that affect e-commerce adoption (Gefen et al, 2003). The success of knowledge innovation networks for economic development will depend on trusted interactions among partners. Privacy, with respect to knowledge assets, including the nature and density of user actions, is a key piece to build into a trust infrastructure. The federal government has addressed this at a regulatory level with the Personal Information Protection and Electronic Documents Act (PIPEDA) which comes into force in January 1, 2004. It recognizes the equivalence of electronic signatures and documents to their physical counterparts. It also legislates the privacy aspect of security for businesses and their customers. By 2004, all Canadian businesses must comply with PIPEDA or equivalent provincial regulations. Additionally, PIPEDA will govern all inter-provincial or international exchanges of PII in the course of a commercial activity. Although Alberta and British Columbia have proposed equivalent privacy acts, they are not yet considered equivalent. In the near future, provinces will piggyback on the federallyprovided infrastructure. Indeed, there is probably little value added for duplicating privacy regulations at provincial levels. There are times when provinces and municipal business associations can play a part in creating trust services such as assurance seals. Evolving from the TrustInfo seal, the ChamberTrust B2B seal is a premier trust seal in use at the International Chambers of Commerce, the World Chamber of Commerce, the Paris Chamber of Commerce, and the British Columbia Chamber of Commerce in Canada. The seal is endorsed by the OECD, the government of Canada, SME chambers, and other key stakeholders in e-business among SMEs. The idea behind the security of the seal is the four-level check. In order for businesses to obtain the ChamberTrust seal, the business must be a member of a provincial government business registry, local chamber of commerce, a local bank, and must provide a contact person in the SME.

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Community portals can keep community members up to date on other regulatory changes that affect economic development outlooks. For many years, in comparison to its southern neighbor, the USA, Canada’s tax and regulatory structures were not as favorable for business. Comprehending the business and individual disadvantages to investing and staying in Canada, the government of Canada (GoC) created a five year Tax Reduction Plan in year 2000 which proposed the “largest tax cut in Canadian history”. The Canadian federal plan is that, provided the US tax legislation remains as is, by year 2006, Canadian corporate tax rate including capital taxes will by 5% lower than the US, and that the income tax rate will be 7.1 % lower than in the US.

3.6

e-Government and Knowledge Services

Accenture has ranked Canada’s efforts in eGovernment as the best out of leading countries in the last three years mainly because of maturity in service transformation. Canada has the largest percentage of citizen uptake of e-government services in the world, with continuing encouragement from their citizens for more online services. This statistic is very much unlike that in other “first-world” countries such as the UK where citizen uptake is hovering in the single digit figures (Pinder, 2003). Over and above providing specific egovernment services, is the importance of the government’s leadership role in showing how to use Internet-based knowledge and information services effectively. Not only can SMEs and communities view examples of best practices, but they can also leap-frog through their own innovative combinations of knowledge services. SMEs can incorporate e-government services to create new higher value aggregate services – the bouquet concept. A service example would be an SME travel company offering a seamless experience in providing the airline booking service, complete with fast online checks for the traveler’s passport expiry dates, online application for new passports, and checks with the department of health for what vaccinations are required to travel to a particular country (Regio, 2002). Furthermore, it is imaginable that the travel company can go online and acquire appropriate licenses (e.g. hunting/fishing licenses), U-pick reservations for strawberry or cherry picking (from Dept. of Agriculture and Fisheries), or book Bob’s Harbour Cruise (from Tourism, Nova Scotia)

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months before its client ever leaves home. Weather forecasts and maritime advisory alerts, or tide and water-level predictions (from Fisheries and Oceans Canada) can be pushed to devices on pleasure craft vessels, or received by email, a few days, or at any specified time(s) before a trip. The SME travel agency could “wrap” these individual services from the government in a neat service bundle for the consumer. Other imaginative services can be created on top of e-government offerings and other distributed knowledge repositories in communities. According to GOL (2003), the GOL initiative “includes over 130 services from 30 federal departments and agencies by 2005.” Many of these services will be integrated. It is up to the innovative SMEs and communities to create aggregate services by incorporating them in their own unique products and services.

4.

Communities creation and use of km services for economic development

Mosteller’s (1981) example of the diffusion of scurvy control through the British naval community classically illustrates why knowledge delivery and knowledge application is important. The system in the British Navy, social and otherwise, did not successfully diffuse medical findings of the positive results of treatment of scurvy with citrus fruits for decades. It was nearly 200 years before the knowledge was used. This often quoted example substantiates that knowledge management infrastructure should build in a heightened degree of “perceived usefulness” – another important diffusion of innovation characteristic. Perceived usefulness and ease of use are two constructs shown to be necessary for adoption of technological innovation in the widely adopted Technology Acceptance Model (TAM) (Davis, 1989). Both constructs are counterparts to Rogers’ (1995) relative advantage and complexity constructs. The province of Nova Scotia has captured these two characteristics in its deployment of the Google search service over its provincial information and knowledge assets. The service, renamed “Ask Joe Howe”, is a simple, yet highly effective search service which virtually created a provincial innovation network of easily locatable human contacts, and connected previously unlinked data stores across the province of Nova Scotia. The

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technological service filled many structural holes in Nova Scotia's previously weakly-linked innovation networks. In addition, the Department of Services Nova Scotia and Municipal Relations (SNSMR), responsible for the Ask Joe Howe service, now possesses and uses the capability to customize government content, keywords, and to train the search engine based on questions that citizens type. Ask Joe Howe is perceived as very easy to use – most citizens use Google search services for daily use and its interface is thus familiar, and consistent. Following on the heels of the provincial success, the e-Director of SNSMR loaned personnel resources out to a rural municipality for a day to participate in the re-deployment of the proprietary Google search engine service at a local library in a rural community in River John (see riverjohn.com). That deployment supported the creation of a "Business Room" in the local library where local citizens could find many online and offline resources to business questions they may have. In mere hours, search access became feasible over multiple municipal and localized businessrelated archives, as well as over provincial and federal business resources, such as the http://strategis.ic.gc.ca/ebizenable and www.businessgateway.ca sites. This example speaks to optimizing the mobility of human knowledge assets and hence enabling tacit/explicit knowledge transfer between tiers of government. Some of the more proactive communities in Nova Scotia are leveraging age-old knowledge source infrastructure such as community and town libraries to create central hubs around which citizens will adopt Internet technologies to support economic development. The library in River John is a source of pride for the community members. Over time, they donated hundreds of thousands of Canadian dollars to build it. According to one community supporter, it takes 30 seconds to drive through this community, which has no bank and one automated teller machine, but most striking is the beautiful, new library. The chief librarian for the Pictou county area is an innovation champion who follows the Keep It Simple Stupid (KISS) principle. He wanted to aggregate community resources for community SMEs, and he set up the partnership with the province to get the community the “Business Room”. He aims to make the picture collection of community history widely available through a simple knowledge portal. The e-director of SNSMR is transferring knowledge by

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encouraging the eventual development of a fully functional knowledge portal.

5. Integrating KM infrastructure for better service delivery Currently, informal, championing stakeholders, such as River John’s librarian, are approaching provinces or departments responsible for egovernment delivery to partner for innovative service delivery. We propose that more formal and timely KM infrastructure services may be achieved if a body is assigned responsibility for systematic examination of opportunities across communities. There is currently a gap at the provincial governments level with respect to having an entity similar to the federal–level Organizational Readiness Office to create, coordinate and maintain the knowledge infrastructure responsible for: 1. Identifying service opportunities 2. Coordinating and aligning strategies and tactics to transfer innovation across communities 3. Aggregating and optimizing resources, capabilities, and capacities of public and private sector infrastructure, human capital from local and state-level employees, public sector association employees, and private sector employees for optimizing knowledge use 4. Creating new knowledge transfer channels for communication among stakeholders 5. Measuring knowledge infrastructure and service success 6. Stimulating knowledge sharing and deploying knowledge protection mechanisms 7. Connecting municipalities and communities with funding mechanisms for creating innovations 8. Strengthening the ability of communities to absorb new knowledge 9. Strengthening cluster brands Such an entity could help close the gaps among tiers of infrastructure in government and to allow seamless slicing and dicing of the KM “staircase”. However there is debate in the research literature over tightly embedded relationships or strongly linked network ties resulting in network closure, and weakly-linked or open networks. Closed networks promote situational normality, trust, and unfortunately sometimes homogeneity. Some theorists view networks as most efficient when there exist weakly-linked ties and structural holes between network members (Ahuja, 2000; Burt 1992,

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Baum and Ingram, 2002, Gargiulo and Benassi, 2000). They argue that the knowledge becomes more diverse and nonredundant. Indeed some government practitioners choose to take a hands-off approach citing that in their experience too much governance stifles innovation and sometimes can cause the death of good ideas. Compromise between the closed and very open structures may eventually gain the most safety and flexibility. Research in innovation networks is still at an early stage. It may be promising for virtual community clustering that some research finds no correlation involving spatial or unit proximity and time of adoption of innovation in a social network (e.g. Durrington et al, 2000).

6. Summary and conclusions We present a model that is useful not only as a guide to building federal-level KM infrastructure, but allows other tiers of government to similarly organize, make decisions to rely or not to rely on nationallyprovided components, and/or focus on auxiliary and proprietary components at the community level. Organizations and communities can supplement government’s infrastructure in providing corresponding mechanisms at each level of KM infrastructure. For example, at the organizational infrastructure level, businesses can set up “affinity groups” which have been shown in the human resources and management literature (e.g. Davenport et al, 1996, Van Aken et al, 1994) to be an effective means of knowledge acquisition, alongside “asking someone” and “surfing the Web” (Daigle- LeBlanc, 2001). Modernizing and simplifying computer-based tools and services, recruiting and hiring skilled personnel, forming effective training policies, managing electronic content, creating governance and other regulatory frameworks for sharing knowledge, and inventing innovative ways to knowledge-mine external feeds are all business examples for complementing the matching types of infrastructure governments provide for knowledge management. Themes of reuse, keep it simple, and innovation championing are pervasive throughout community efforts at building KM infrastructure for economic development. It makes sense for the higher tiers of government to provide the more complex and costly infrastructure components, build a simple interface to these components, and let the masses build on top of them. In this paper, we have identified what infrastructure and services

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governments can provide to support KM in communities. Furthermore, we illustrate the role of characteristics of observability, trialability, ease of use, perceived usefulness, and compatibility when building KM infrastructure at several tiers of government. We discuss tradeoffs of strongly linked, trusted networks and weakly linked, but inherently more flexible networks. At this point, governments appear to be balancing the desire to fill gaps and to maintain a hands-off approach. In Canada, e-government strategies are pioneering a second generation of knowledge management infrastructure to support SMEs economic goals. One example of the emphasis on KM is the Nova Scotian acquisition of a proprietary Google engine service, renamed "Ask Joe Howe", which was first deployed at a provincial level, and then diffused to the community level to leverage community knowledge resources as well as provincial/federal knowledge resources for business. Governments are starting to take advantage of the mobility of an essential infrastructure element, and are temporarily placing skilled government workers in the communities that can most take advantage of their knowledge skills. Third generation KM infrastructure will emerge in the next decade with new challenges and opportunities. Until then, we expect involvement of multiple communities in creating localized e-content with possibly thematic connections (e.g. vintage trains, shipbuilding, quilt making) will grow as communities climb and add higher steps to the staircase of knowledge.

References Agarwal, R., and Prasad, J. (1998), The antecedents and consequents of user perceptions in information technology adoption. Decision Support Systems, pp.15–29. Ahuja, G. (2000), Collaborative networks, structural holes, and innovation: a longitudinal study. Administrative Science Quarterly, 45:3, 425-455. Allee, V. (2000), Reconfiguring the value network. Journal of Business Strategy, 21:4, 36-39. Barquin R.C., Bennet A., Remez. S.G. (2001), Building Knowledge Management Environments for Electronic Government. Management Concepts, Virginia. Baum J.C, and Ingram P., 2002. “Interorganizational learning and network

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social capital. Organization Science, 11:2, 183. Gefen D., Karahanna, E., Straub, D.W. (2003), Trust and TAM in online shopping: An integrate model, MIS Quarterly, 27,1:5190. GoC (2001), Achieving Excellence: investing in people, knowledge, and opportunity, Canada’s Innovation Strategy, available at www.innovationstrategy.gc.ca. GoL (2003), Government On-Line 2003. Retrieved June 2003 from www.tbssct.gc.ca/report/gol-ged/2003/ Higa, Kunihiko et al. “Organizational adoption and diffusion of technological innovation: a comparative case study on telemedicine in Hong Kong”. Proceedings of the 30th Hawaii International Conference on System Sciences (HICSS). IEEE. 1997. Hu, P. J., Chau, P. Y.K., Liu Sheng, O. R., and Tam, K. Y. (1999), Examining the Technology Acceptance Model using physician acceptance of telemedicine technology. Journal of Management Information Systems, Fall 1999, Vol. 16, No. 2. pp. 91 – 112. Judge G. (2002), Diffusion of collaborative tools in a learning environment, Masters of Business Administration, Saint Mary's University, Nova Scotia, Canada, Sept. 2002. Jutla D. N, Bodorik P., Dhaliwal, J (2002), Supporting the e-Business readiness of Small and Medium Sized Enterprises: Approaches & Metrics, Internet Research Journal: Electronic Networking Applications and Policy, Vol. 12, No. 2, pp. 139-164, 2002. Jutla D.N , Bodorik P., Feindel, S. (2003), Organizational infrastructure framework for information technology innovation : An Economic Development Example. International Federation for Information Processing (IFIP) Joint WG 8.2 and 9.4 Conference on IS Perspectives and Challenges in the Context of Globalization, Athens, Greece, pp. 49-58, June 15-17, 2003 Mahajan, V. and Muller, E. (1979). Innovation diffusion and new product growth models in marketing. Journal of Marketing. Fall 1979, Vol. 43. pp. 55 – 68. Mahajan, V., Muller, E., and Bass, F.(1990) New product diffusion models in marketing: A Review and Directions for Research. Journal of Marketing. January 1990, Vol. 54. pp. 1 – 26. Malek, M. (2003), Towards dependable networks of mobile arbitrary devices – diagnosis and scalability. In Future Trends

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in Distributed Computing. SpringerVerlag, 2003. Malhotra Y. (2000), Knowledge management and new organizational forms:a framework for business model innovation. Information Resources Management Journal, 13:1, 5-14. Mathieson, K. (1991), Predicting user intentions: comparing the Technology Acceptance Model with the Theory of Planned Behaviour. Information System Research. 1991, Vol. 2. pp. 173 – 191. Moore, G. C. (1987), End user computing and automation: A diffusion of innovations perspective. INFOR. 1987, Vol. 25, No.3. Moore, G. C. and Benbasat, Izak. (1991), Development of an instrument to measure the perceptions of adopting an information technology innovation.. Information Systems Research. 2:3, pp.192-222. Mosteller F.(1981), Innovation and evaluating. Science, 211, 881-886. Newstad, P. R., Huff, S. L., and Munro, M. C. “Survey instruments in Information Systems”. MIS Quarterly. Dec. 1998, 22:4, pp. 553-554. Nonaka I., and Takeuchi, H., (1995), The Knowledge Creating Company. Oxford University Press. Rogers, E. M. (1995), Diffusion of Innovations. New York, New York: Free Press. Ryecroft R.W. & Kash, D.E. (2000), Steering complex innovation. Research Technology Management, 43:3, 18-23. Socitm (2002), Local e-government now: a worldwide view. Joint publication of the Improvement and Development Society (IDea) and the Society of Information Technology Management (Socitm), September 2002, London, UK. Stokes, C.W., Walsh T.F., And Cannavina G., (2003), Web-based learning environments for health professionals: are we ready?, International Conference on Advances in Infrastructure for e-Business, Science, and Education on the Internet, Scuola Superiori G. Reiss Romoli (company of Telecom Italia), SSGRR 2003, L'Aquila, Italy, July 31-Aug 5, 2003. Van Aken E.M., Monetta, D.J., Sink, D.S., et al 1994 Affinity Groups: The Missing Link in Employee Involvement, Organizational Dynamics, 3-22. Vitalos E.C. (2001), Enterprise Information Portals: The Vehicle for Knowledge Delivery, In Building Knowledge Management Environments for Electronic Government. Barquin R.C., Bennet A., Remez. S.G (eds.) Management Concepts, Virginia.

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Knowledge Management System Building Blocks Georg Hüttenegger Vienna University of Technology, Austria [email protected] Abstract: This paper describes three building blocks of a technological Knowledge Management (KM) system that provides all relevant and practical means of supporting KM and thus differentiates itself from existing KM tools in goal and approach, as they usually deal with a limited range only. The three blocks described within this paper are: a virtual information pool, which utilizes Enterprise Application Integration (EAI), a single and central user interface providing ubiquitous access, and mechanisms to enrich the available data, essentially based on Artificial Intelligence and Data Mining techniques. Keywords: Knowledge Management System, Virtual Information Pool, Ubiquitous Access, Machine Learning / Data Mining

1. Introduction Many experts define Knowledge Management Systems as IT systems that support KM activities and hence are generally concerned with enhancing competitiveness by the appropriate use of all available knowledge (for further definitions of KM see Sveiby [Sveiby 2001]). There are two main issues to be addressed by IT: To provide users with access to as much relevant information in the most practical way possible and to capture as much information as feasible and add this to the available information. There are already a number of systems and technologies on hand, which provide a great deal of functionality in a wide range of (KM) fields. For further information on existing systems/tools, see Alavi and Leidner ([Alavi 1999] or [Alavi 2001]) as well as Marwick [Marwick 2001]. This paper proposes building blocks for an integrated system that provides as much functionality as possible within current IT constraints. The concept focuses on larger organizations that currently use diverse systems and beyond that is probably more suited for non-routine tasks such as project management, software development, or in general, development of new products. Although a resulting system would certainly address similar issues faced by smaller organizations, complexity and expenditure could prove as a limiting factor. Based on a paper describing the general architecture of the proposed KM system (presented at the ECKM 2003 [Hüttenegger 2003]), this paper provides detailed descriptions of the three major building blocks the solution substantially consists of. It is of utmost importance to bear in mind that no proposition is being made to introduce a KM system or even parts of it, which can be seen as a general solution for a company

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striving for KM. Instead, each organization should carefully review their KM needs and not before preliminary results are available, concern themselves with technological issues. This line of argument finds support by current research activities, stating, why purely IT driven KM initiatives have failed (for example McDermott [McDermott 1999] or Malhotra [Malhotra 2002]).

2. Requirements for a KM System Before describing the actual solution itself, requirements of such an IT system, reasoning on analysis of goals and needs of KM, shall be presented (primarily based on two KM research reports published by KPMG: [KPMG Consulting 1998] and [KPMG Consulting 1999]). The primary requirements identified are Capturing, Integrating & Connecting (technologically), Transforming, Storing, Flexible & Adaptable Permission System, Connecting People, Data Mining / Knowledge Discovery in Databases / Machine Learning, Handling & Capturing Context, Links, and History, Automation, Searching / Finding and Retrieving, and finally Embedding into Normal Workflow. Figure 1: shows how these requirements relate to one another. In addition to the requirements listed, importance of a few other issues shall be stressed: Providing Transparency, Providing Traceability/”History”, and NonFunctional Requirements (mainly performance, stability, usability). These requirements call for an integrated system and as a result reduce learning times and ease information access at the same time. The building blocks presented form the heart of such a system.

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Capture

Connecting People

Automation

Searching/ Finding

Permission System

Context/ Links/ History

Data Mining/ KDD/ML

Transforming

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Storage/DB

Integration/ Connection

Figure 1: Graphical depiction of system requirements

3. Virtual information pool and technical foundation The virtual information pool is a knowledge base that incorporates all relevant information while not necessarily storing it, thus forming a virtual pool of information, and allows all relevant data available to the organization to be found and accessed. As the needs of different organizations are very diverse, there can be no exact definition what "relevant data" actually is. However, some types of data will be common to virtually all organizations, including: 1. All sorts of documents (often found in Document Management Systems, databases, or file systems). 2. Project related data such as memberships, history, or lessons learned. 3. All types of communication data such as e-mails, chats, forums, etc. 4. A skills database. 5. Information on coordination, especially information related to meetings. The crucial task (from a purely IT point of view) is keeping the information up-to-date with as little manual input as possible, whereas the

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second most important task is to create an organizational culture and precise policies that foster sharing and helping (in practical terms: to encourage employees to help others instead of just optimizing their own team and/or project).

3.1

Providing ambiguity

This is another major issue faced by the knowledge base, and there are a number of ways of achieving this. One method is to allow users to add their own bi-directional links between stored pieces of information. However, one must bear in mind that many pieces of information will "belong" to multiple locations. This is quite natural for human beings but is not possible with simple file system hierarchies. However, users are already accustomed to this simple concept and will probably need to be "taught" how to work with this particular "feature". [Note: The fact that a single information item can belong in multiple locations often confuses people, e.g. when electing to delete it. The same holds true for shared folders where people perhaps just want to "remove" a piece of information from their personal view of the folder’s content.]

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3.2

Overview of the virtual information pool

Figure 2: Depiction of the virtual information pool Figure 2 shows the functions and features of the virtual information pool as well as the most important connections within. By integrating/importing external information, the pool is able to include high quality external databases, for example. To allow transparent access through the interface even to sources outside an organization such integration needs careful planning: One has to consider permission, potential cost, and performance issues and solve all of them in a satisfactory way. Integrating and importing all kinds of information and data forms the heart of the virtual information pool. Especially relevant sources are: standard business software (like human resources, enterprise resource planning, etc.), more specifically customer relationship management, unified messaging (with information about phone calls, faxes, etc.), and general existing ’tools’ and ’databases’. Not shown in this picture (as it will

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appear in Figure 3) is the CSCW/Groupware aspect that not only provides a user interface but is also needed as a data source. General DMS/DBMS and especially Data Warehouse functionality are managing/using/enriching all the available information to fulfill the promise of a consistent interface. On the bottom of Figure 2, one sees “Remaining direct User Interaction”. Generally, the approach calls for a complete replacement of such alternative ways of user interaction, on the other hand, as this will hardly ever be possible, at least in a first step, it is included as another data/information source.

3.3

Technical foundation and realization

Since I am focusing on larger organizations, a multitude of systems providing relevant features for the building blocks will be in use in

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each individual case. If necessary functions are not yet available, the necessity and possible financial implications of relevant systems should be discussed separately from the building blocks themselves. (One should consider the cost of basic functions separately as they have important merits of their own.) Important base systems include: A directory service of some kind (to hold user relevant information / user configuration) and a Single Sign-On based on the directory services. [Note: While not necessary from a technical point of view, a Single Sign-On function will automatically increase the user friendliness of the system, by eliminating the need to log-on to each of the numerous systems individually.] The pool itself clearly needs some data storage, in which any information not available through two-way integration needs to be stored. Additionally, all functions required to accomplish sophisticated operations on the organization's data store need to be available efficiently through the virtual information pool (thus disguising in which system the data is actually stored). This is another major issue for the pool: to hide the source of the data as far as possible (this in turn allows legacy systems to be replaced without the need to change functions above the virtual information pool themselves). Storing data is not the primary purpose of the pool (data should only be stored here if absolutely necessary). Rather, the aspects of integration and adding value to information are paramount (e.g. through integration with EAI). Therefore, this concept does not call for an additional Groupware or Document Management System (DMS), but instead recommends the integration and use of existing systems. Whilst this will inevitably pose some difficult challenges (e.g. some common Groupware systems do not even allocate unique keys to documents), reinventing the complex functionality of current systems is neither feasible nor desirable. There is a far greater selection of DMS available and therefore selecting an appropriate solution for both legacy systems and the new information pool should be easier to achieve. Unfortunately, a number of existing applications (e.g. Oracle Forms Applications) do not support this approach since they do not provide adequate interfaces (APIs). Integrating such legacy systems simply by extracting their data is rather awkward and leaves any functionality behind. Therefore, the primary objective must be to have adequate interfaces

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to all critical applications. Otherwise, they should be migrated and all new systems that are acquired or developed in the future should fit into the new architecture. It is important in the design stage to plan for a phased implementation of the resulting solution, starting with a major component and then gradually adding significant components in each phase. The actual first phase will ultimately depend upon the individual customer requirements and situation: one approach would be to start with the integration of the more accessible systems and thus demonstrate the realizable benefit; a second approach might be to introduce the building blocks at the same time as another large system is deployed and demonstrate the synergy benefits.

3.4

Conclusion

All this information together forms the knowledge base or virtual information pool— the single most important foundation for a complete and holistic KM system. The solution proposed places two major requirements on this pool: Firstly, the provision of ubiquitous access to the pool and, secondly, the automatic updating and enriching of the information it contains.

4. Providing ubiquitous access The need for a virtual information pool together with the importance of a Single Sign-On as an essential additional system component has already been adequately discussed. Another issue of similar importance is the provision of access to the system with full functionality for a variety of communication devices. Since most organizations will need separate areas within a resulting KM system, a powerful and flexible permissions system is of utmost importance. An eminently suitable basis would be a directory service. Nevertheless, the chosen permissions system has to allow for groups that may not share their documents (e.g. who are working for different – or even competing – customers), parts of the system should be accessible via Extranets (so that partners can use it), possibly even providing content for the company website. At the same time, as much information as possible must be available to every authorized user. [Note: This can be especially challenging when access restrictions on documents alone may not be secure. Imagine employees

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searching for documents containing information about "layoffs" and finding out that there are several recent documents containing this keyword created by top management]. Finally, yet equally important, the management of such controls must be kept as simple as possible. Important concepts here are access control lists, user groups, and administration rights for parts of the system (so that responsibility can be split and distributed). Establishing the need for a powerful permissions system, the "window" to the proposed solution: “The single, central User Interface (UI)” has to fulfill some complex requirements: Seamless integration of existing and newly introduced systems and their functions. Handling different access devices while taking into consideration any limitations imposed by the device itself (also to be addressed when entering/integrating information; sometimes particularly demanding with limited and/or mobile devices like smart phones). Providing powerful search mechanisms (full text retrieval and other capabilities supported by the integrated engine such as searching for all available attributes including context, document similarity, etc.). Providing hierarchical access to the information: This can be done through taxonomies, maps, directories, etc. For example, taxonomies could be generated automatically and therefore always up-todate. Providing context/links/history for the resulting pieces of information (when entered/updated; connected to which project; stored/modified by whom; show documents with similar content; etc.). Providing ways to add new information: This should be integrated into the normal workflow and actually save, instead of generate work Integrating Computer Supported Cooperative Work (CSCW) functionality

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(Groupware features): These systems often have elaborate clients that cannot be easily integrated into the interface; however, it is essential that key functionality is available through the common interface. This may involve integration at multiple levels: a bidirectional connection for the data itself; full integration of the selected key functionality and access to the remaining functionality via the “native” interface). Visualization: This is another powerful mean of providing users with a view of information in the virtual pool. This involves a range of issues such as how much information is presented, in what form, which additional navigational means are offered (star diagrams of the relations between information items are a good example). Optional: Off-line access is often another important issue. At the same time, monetary constraints and limited benefits can be arguments against this generally rather expensive functionality. One of the primary ideas behind the central UI is to provide access to as much functionality as possible from one single GUI. The main benefits are: Greater efficiency as a result of fewer and more consistent GUIs (ideally with complete integration of their functionality), more data available to the knowledge base, and possible savings due to synergies and reuse of available data when building new functionality. [At the same time, it becomes more difficult to use third party software, as it will not integrate nearly as well as individual solutions.] This central UI is also a viable way to realize a quick win. If the resulting KM system replaces (or completely integrates the functionality of) at least two existing systems, the users will have at least one system less to deal with. Furthermore, users will appreciate the benefits of a complete solution. From a technical point of view, complete integration also enriches the knowledge base.

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4.1 Overview of the Central User Interface

Figure 3: Depiction of the Central User Interface Figure 3 shows all the technologies and functions behind the user interface as well as how they work together to provide this second building block. Through the UI functions, all the functionality of the whole KM system is made available to the end user. Necessary adaptations for different access devices are an integral part of the system thus consistently offering the subset of functions that makes sense for limited devices (like PDAs, mobile phones, bandwidth-limited connections etc.). This figure also shows three conceptually different sets of functions: Capturing: As a rather broad function, there are no other examples of this set. It represents the aspect of acquiring additional information. Whilst using implicitly available information this aspect should minimize user input. Presenting/Delivering: This aspect includes: Visualization, Powerful Search/Retrieval, Handling Suggestions / Interests / Notification, and Topic Maps/Taxonomies/Ontologies. While a certain amount of interaction with the user and other parts of the resulting system is part of these functions, their

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primary issue is to deliver information to the user. To accommodate different types of users, multiple powerful mechanisms are offered and are accompanied by e.g. push mechanisms, in managing interest profiles together with suggesting possibly relevant new documents to the affected user. Interaction: Finally, interaction is the most important factor for both the CSCW/Groupware functionality and for Context/Links/History. These functions are similar to the previous ones as they deliver and present information. At the same time, they are providing means to communicate, capture current and provide past context. Summing up, they are essentially bidirectional, which is not the focus of the described functions so far. On the bottom of Figure 3, one can see “Other parts of KM System” together with the most important connections to the various functions. Please keep in mind that the arrows are indicating the important directions of data and information flows and are not meant to be exact descriptions.

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4.2

Conclusion

This section discussed the necessity and the most important benefits of the single and central UI, the two most important reasons are: To build one consistent UI at the top level of the virtual information pool, and To be able to integrate all functionality/systems where this is not possible at lower levels or at least only to a certain degree. This interface has to provide diverse access possibilities, such as powerful searching, hierarchical access, and access for limited and off-line devices. This interface is also a good chance to realize a quick win by replacing and integrating at least two previously used systems in the first phase of the implementation of the resulting KM system.

5. Automatic updating / enriching the knowledge base This section discusses the third major building block of the resulting KM system architecture. The necessity of a shared knowledge pool and a central and single UI has already been discussed. However, these could also be part of a "simple" EAI or CRM project, although taxonomies are already a step further and their importance for the UI has already been described. What distinguishes KM systems from information stores are the more sophisticated means of analyzing and enriching the available information, thereby providing insights not easily gained by other resources. Existing KM tools tend to address mainly one or several of these aspects and consequently, although they can rightfully claim to be KM software, do not attend to all the issues a system has to deal with in successfully supporting KM.

5.1 Overview of the Automation Aspect Utilizing the integrated knowledge base provided by the virtual information pool, automation is the key to go beyond a “mere” Information Management System (IMS). Situated between the knowledge base (thus being able to work on all available information) and the user interface, it provides functions and features that separate it from simpler and smaller solutions. The important issues and technologies as well as the most relevant connections between them are depicted in Figure 4. The central user interface – as the only part interacting with the end users – shields them from the automation aspects, whereas the virtual information pool

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provides diverse data and information necessary for all the automation functions. Let us now turn to the individual points of the automation aspect: Yellow Pages / Skills Database: Using the wealth of information available through the virtual information pool, this subsystem updates the skills database automatically. Whilst this may result in a lower quality than would have been achieved through human intervention/input, the information is always up-to-date and the updating process requires little or no manual input. Relevant information includes: Project membership, written documents, accessed information, hours booked on certain sub-projects, discussions via email, forum, chat, etc. [Note: Whilst this type of automatic update is by no means perfect, manual updates can also be unreliable and with the information available in the integrated system, an automatically generated informed guess might be quite acceptable.] General Data Mining: Expert users can make direct use of the data mining functionality, thus allowing direct exploration of possible correlations together with new insights etc. This positions it nearest to the user interface, as they need close integration. Base for Notifications, Interests, Push, Intelligent Hierarchies etc.: This issue represents all the automation items below and is relevant mostly from a conceptual point of view. It is up to an actual implementation whether this is a dividing line or not. Knowledge Maps / Clustering: This is the foundation of providing access to possibly related documents through various means. Users are offered or may search for similar documents and can browse in the available knowledge maps (e.g. being based on generated and automatically updated taxonomies). Classifying Messages: Especially interesting when information is not addressed personally and has to reach a correct recipient, taking e.g. holidays and substitutes into account. This can be used for customer messages but equally for internal ones (e.g. hotline etc.). AI/ML/DM/KDD:

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Perhaps the heart of the automation aspect is the utilization of the possibilities of various forms of AI/ML/DM/KDD. This is not only based on the knowledge pool directly but also on the following two points. These technologies allow the resulting solution to provide information not integrated or captured in a number of ways, automated summaries or providing “links” to similar documents being just two of the many possibilities. Speech Mining/Image Similarity/Analyzing Video: While these technologies are not yet fully mature they help to integrate speech, images and videos as resources into the resulting solution accessible to a certain degree. Especially speech mining has already proven its practical applicability for more than specialized requirements. Monitoring Usage/Constant Reevaluation: This aspect is especially important, as users will seldom provide the system with a rating of the information they accessed. Therefore, it is necessary to assess the usefulness of information automatically,

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thus showing the potentially most relevant information while at the same time reducing the assessed “value” of no longer relevant information. Re-evaluation can also be important to manage the volume of stored data by providing hints what could possibly be removed from online access (e.g. to an archive). Not directly depicted in the following figure are the following important functions: Handling interests/profiles: The resulting system automatically notifies users about pertinent new information items. To enable this, all new documents must be classified to the user's possible interests. Additionally, the system proposes new interests based on access data and other information (e.g. new role, joining new project, etc.). Collecting context and history for the information pieces: Automatically including all available information by the system when users create a new item/entry. This also holds for modifications to existing information.

Figure 4: Depiction of the Automation Aspect

5.2

Conclusion

This section describes the most demanding building block of the resulting KM system: Automation and Enrichment of the information

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within the system. Generally, these processes automatically capture and generate additional information and provide it to the users, in addition re-evaluating information is of equal

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importance. Although this is difficult without manual intervention, it is necessary to offer a working procedure to address this issue and prevent the KM system from becoming "crowded" and useless. Whilst automatically generated information might not provide the desired results, there are already a number of successful examples applying these underlying technologies. [Note: Most KM tools rely on one or more of these technologies.]

6.1

6. The big picture Having described the three major building blocks, namely the virtual information pool, the single and central user interface, and automation and enrichment, a short overview of how these building blocks form a KM system shall round up the big picture:

Putting it together Additional Capturing

Powerful Search

Directories (K-Map/...)

CSCW++ (Groupware)

Workflow Support

Permission System

OLAP / ad-hoc Analysis

AI/DM/KDD/ML intelligent Agents

At all levels

Portal (Single & Central UI)

Integrating diverse Business SW: CRM, Finance, Quality, Investments Controlling, Projects Human Resources Logistics, ...

Virtual Information Pool Integration/ Import

DMS/DBMS/ Data Warehouse

Figure 5: Overview of the System Architecture Figure 5 illustrates the resulting system architecture described above and the virtual information pool is immediately recognizable as the center of the solution. The single and central user interface is on top and some of the more important examples of automation and enrichment of the knowledge base are located in the middle. There is also a need to integrate diverse business software (not discussed). These systems, or more precisely, their data, form important parts of the knowledge base, and their relevance becomes clear when human resources data or ERP systems are taken into consideration.

6.2

Further aspects

Lacking space, many interesting issues, such as, why certain technologies have been included in a building block while others are

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missing, have not been addressed in this paper. As a matter of equal importance, any actual initiative striving to realize the proposed building blocks will have to approach the necessary design, implementation, and introductory issues with the greatest care.

7. Conclusion: Summary/Further Research This paper describes three major building blocks of a technological KM system that supports all the major needs of KM. This differentiates the approach from descriptions of “smaller” KM systems (such as the one described by Fagrell et al. [Fagrell 2000]), or KM tools designed to address a narrow set of requirements, or normal integration projects (e.g. CRM projects using EAI technologies).

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7.1

Summary

To conclude this paper, consider the issues that the building blocks and a resulting system should address: Supporting people in their daily work, Making them more efficient and faster, Helping them achieve, in terms of quality and – potentially – quantity, better output. This is the result of: Enabling members to find all relevant information in the organization quickly and easily (both by searching and by advanced directories/maps). Supplying a list of all available experts in a particular field. Providing information about the context and history of earlier and probably similar projects and documents (as examples of how things might be done). Enabling communication at all levels (internal experts, project teams, etc.). Managing employee interest profiles, suggesting updates, to include potential new interests and actively informing users of new, relevant information. Automatically classifying documents, especially incoming ones, and identifying and retrieving similar documents, to provide additional contextual information. Together, the building blocks address the need to include technological aspects in any wellplanned and complete KM initiative.

7.2

Further Research

While IT is definitely not necessary for KM in general, this paper has once again demonstrated the prospects of integrated support IT can provide. This is a major motivation to continue investigating the described building blocks and, given a broader view, a resulting system, together with analyzing, how effective they can be for real world KM problems. From a more general point of view, technology already offers many features of high relevance for KM. Sadly enough, when it comes to capturing tacit knowledge, it is still far from providing a satisfactory solution. [Note: One can be quite certain that this will not be achieved in the near future; indeed, doubt may be indicated, that it ever will be possible.] This remains an area of current research (see Brown et al. [Brown 2001]). Imagine the possibilities, when speech recognition, video analysis, or image similarity recognition become as useful as OCR is today – this may give you a small indication of what might eventually be possible.

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References Alavi, Maryam and Leidner, Dorothy E. “Knowledge Management Systems: Issues, Challenges, and Benefits”, Communications of AIS Volume 1, Article 7 (1999). Alavi, Maryam and Leidner, Dorothy E. “Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues”, MIS Quarterly, Vol. 25, (2001) pp. 107–136. Brown, Eric, Srinivasan, Savitha, Coden, Anni, Ponceleon, Dulce, Cooper, James, Amir, Arnon, and Pieper, Jan “Towards speech as a knowledge resource”, Proceedings of the Tenth International Conference on Conference on Information and Knowledge Management, Atlanta, ACM Press (2001) pp. 526–528. Davenport, T.H. and Prusak, L. “Working Knowledge: How Organizations Manage What They Know”, Boston Harvard Business School Press, USA (1998). Essers, Juup and Schreinemakers, Jos “The Conception of Knowledge and Information in Knowledge Management”, in: J. Schreinemakers (ed.) Knowledge Management: Organization, Competence and Methodology – Advances in Knowledge Management Vol. 1. Proc. 4th Int. ISMICK Symposium Würzburg (1996) pp. 93–104. Fagrell, Henrik, Forsberg, Kerstin, and Sanneblad, Johann “FieldWise: A Mobile Knowledge Management Architecture”, Proceedings of the ACM 2000 Conference on Computer supported cooperative work, Philadelphia, ACM Press (2000) pp. 211–220. Hahn, Jungpil and Subramani, Mani R. “A Framework of Knowledge Management Systems: Issues and Challenges for Theory and Practice”, Proceedings of the 21st international conference on Information systems, Brisbane, Association for Information Systems (2000) pp. 302–312. Hoffmann, Marcel, Loser, Kai-Uwe, Walter, Thomas, Herrmann, Thomas “A Design Process for Embedding Knowledge Management in Everyday Work”, Proceedings of the international conference on Supporting group work, Phoenix, ACM Press (1999) pp. 296–305. Hüttenegger, Georg “A Knowledge Management System Architecture” Proceedings of the 4th European Conference on Knowledge Management (ECKM 2003), Oxford, MCIL 2003, pp. 485–494.

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Johanessen, Jon-Arild, Olaisen, Johann, and Olsen, Bjørn “Mismanagement of tacit knowledge: Knowledge management, the danger of information technology, and what to do about it”, (2000) [online] http://program.forskningsradet.no/skikt/joh annessen.php3, visited November 3, 2003. KPMG Consulting “Knowledge Management: Research Report 1998”, (1998) [online] http://www.brint.com/papers/submit/know mgmt.pdf, visited November 3, 2003. KPMG Consulting “Knowledge Management: Research Report 2000”, (1999) [online] http://www.kpmg.nl/Docs/Knowledge_Advi sory_Services/KPMG%20KM%20Researc h%20Report%202000.pdf, visited November 3, 2003. Malhotra, Y. “Why Knowledge Management Systems Fail. Enablers and Constraints of

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Knowledge Management in Human Enterprises”, in: Handbook on Knowledge Management 1: Knowledge Matters, Springer, Heidelberg, Germany (2002) pp. 577–599. Marwick, Alan D. “Knowledge management technology”, IBM Systems Journal Vol. 40, No. 4 (2001) pp. 814--830, [online] http://www.research.ibm.com/journal/sj/40 4/marwick.pdf, visited November 3, 2003. McDermott, R. “Why Information Technology Inspired But Cannot Deliver Knowledge Management”, California Management Review, Vol. 41, No. 4, (1999) pp. 103– 117. Sveiby, Karl-Erik “What is Knowledge Management?”, (2001) http://www.sveiby.com/articles/Knowledge Management.html, visited November 3, 2003.

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Designing for Innovation or Adaptation: The Symmetry, Syntopy and Synchrony of Boundary Spanning Partnerships Sean Gadman International Business School, Isle of Man. [email protected] Abstract: The Internet is enabling a new economy based on the networking of human knowledge. While the benefits of using I.T. to connect people to people and people to information within a business are commonly understood, much less is known about the advantages of well-managed partnerships across corporate boundaries. Building on the findings of a recent study of knowledge creating collaborations (Gadman and Cooper 2003), and the growing interest in Open Source Software development communities, (Von Hipple and Von Krogh 2003), (Cole and Lee 2003), this paper addresses the importance of selecting the most appropriate collaborative strategy to meet business needs and the challenges of managing relationships which often span organizational cultures and boundaries. The findings are relevant to any company that depends on the free flow of ideas among smart people and provides a lens through which we can learn and discover new and creative possibilities for the future.. Keywords: Knowledge Management. Open Source Communities. Communities of Common Interest, Communities of Practice, Collaboration. Organisational Behaviour. Organisational Design.

1. Introduction In a recently formed collaborative partnership, Intel and IBM came together to speed up the development of wireless applications based on Intel’s servers and clients and IBM's WebSphere middleware. Having a panScandinavian focus the initiative also allowed teams located at IBM's Helsinki-based mobile e business centre and Intel’s wireless competence centre in Stockholm to work together with greater ease. The deal extended both company's existing relationship in the wired world, and paved the way for further partnerships with application developers. Increasingly, companies like Microsoft, Linux, IBM, Intel, BP, Benetton, 3M, Oracle, Dell and Proctor and Gamble are creating competitive advantage by collaborating inside and across their organizational boundaries to create new knowledge to take on and overcome complex business challenges. Over the past two decades, management innovations enabled by information technology (IT) have moved companies toward the ideal of the "boundary less" organization (Winograd and Flores 1987), (Morgan 1993). In these organizations, formal reporting structures and detailed work processes have a diminished role in the way important work is accomplished. Instead, informal networks of employees are encouraged to exist alongside the formal organization and these communities of common interest are increasingly at the forefront of new idea development. The general health and "connectivity" of these groups has a significant impact on their knowledge creating capability, strategy execution and organizational effectiveness. Many corporate leaders intuitively understand the benefits of this flexible approach, but few

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spend any real time assessing or supporting them. And because they do not receive adequate resources or executive attention, these groups are often fragmented, and their efforts disrupted by management practices or organizational designs that are biased in favour of task specialization and individual rather than collaborative efforts. (Gadman 1996) Not surprisingly, the best examples of I.T. enabled collaborative practices are to be found in companies where information technology both defines competitive strategy, as in the case of Microsoft, Intel, Linux and Dell and where it enables competitive strategy, as in the case of BP, Benetton, 3M and P&G. For example at BP, knowledge creation through collaboration is considered a critical factor in their ability to adapt to rapidly changing market forces. B.P. manages a vast range of activities including exploration and production of crude oil and natural gas; refining, marketing, supply and transportation; manufacturing and marketing of petrochemicals. The company used to be mired in procedures, but now has processes that foster learning and tie people’s jobs to creating value. It is flat and lean and every individual in the company has the basic capability to communicate, collaborate and share information routinely, without the underlying infrastructure acting as a barrier to information flow.

2. Integrating business and collaborative strategies Results showed that, when it comes to strategic collaboration, companies do not adopt a standard approach. They employ two very different strategies depending on their competitive focus, their financial goals, how

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they create value for their customers, their willingness to take risk and the degree of trust existing between members of the collaboration. In some companies, their strategy centres upon adaptation. Knowledge is required to deepen penetration of existing markets with existing products/services, or to extend into new markets. Adaptive strategies apply existing knowledge structures to new opportunities. Consequently, strategic partnering is predominantly closed or internally focused. For example, when GM introduced their Saturn line of automobiles they were targeted at a specific market. The attractive, inexpensive but high-value cars appealed to young adults just starting out in their careers. While initially assessing the tastes and values of that generation, Saturn subsequently introduced newer models that reflected the increasing affluence of its core customer base. This example illustrates the limited use of external collaboration as a source of knowledge creation and innovation. Similarly, Dell operates in the highly commoditized personal computer market where there is little to differentiate one PC from another. Consequently, they are constantly looking for ways to secure their future. Their strategy is not to innovate or spend on R&D. Instead, they adapt existing knowledge to build on the ideas of their competitors and then enter the market later with cheaper prices enabled by an extremely efficient in-house manufacturing process. Their strategy is to adapt within a well-defined strategic domain. Their intention is to deploy validated knowledge to another task. Consequently, Dell looks for markets where standards have emerged. It then innovates with its processes - the area where it does hold a large number of patents - and, perhaps most importantly, gives customers what they want, not what it thinks they need. By contrast, other companies studied adopted a business strategy centred upon innovation. In these companies, knowledge is required to introduce new products/services into existing markets or to introduce new products/services into new markets. This innovating strategy requires the application of new knowledge to new opportunities. It emphasizes experimentation as a natural and spontaneous way of working, whereas adaptation emphasizes a more planned and controlled approach. Consequently, innovative strategies are predominantly open or externally focused. Open Source is one extreme example of this approach where software development programmers are able to read, redistribute and modify the source code for a piece of software

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and the software evolves. (Raymond 1999) People improve it, adapt it and fix bugs and this all happens at a speed greater than that of conventional software development. By working together, a community of users and developers improve the functionality and quality of the software and it appears that this rapid evolutionary process produces better software than the traditional closed source process where a privileged few programmers have access to the source and others use an opaque block of bits. A less extreme, but equally effective innovating approach is adopted at Oracle when forming new technology partnerships to build new software applications. They are highly skilled at creating strategic partnerships with smaller companies. Their aim is to leverage and combine with their own, the unique knowledge and talent of these companies to create new products and to quickly exploit highly lucrative markets dominated by their competitors. While this approach is more radical than the fine-tuning of their adaptive counterparts it is less extreme than Open Source. The primary concern when making decisions about degrees of openness in the amount of risk involved in exposing proprietary assets to outside agents who could potentially put them to their own advantage. On the other hand the risk is balanced by the benefits to be gained from spreading their knowledge creating capacity among a wider community of people. While Open Source software development communities appear to be an idea whose time has come, it is important to remember that knowledge creating communities have been operating across a wide range of industry sectors for many years. (Amidon and Skyrme 1997) Companies like Xerox, Proctor and Gamble, Intel and 3M pretty much lead the way in intentionally creating and managing communities of common interest (Seeley Brown and Solomon Gray 1995). While there is growing interest (Von Hipple and Von Krogh 2003), (Lee and Cole 2003) in Open Source strategies, it is important not to hype them as the next wave, but to be informed by them as we continue to develop new and creative ways to increase a company’s ability to gain competitive advantage through strategic collaboration.

3. Balancing adaptive and innovative strategies The major distinction between innovating and adapting strategies is that the former approach requires the harnessing of learning & innovation through natural and spontaneous

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3.1

Finding the Best Fit

As the above examples show, a company’s choice of strategy is far from arbitrary and has a lot to do with their competitive strategy, an analysis of the risks and benefits associated with taking on any new venture, their knowledge creating capacity and, as Microsoft illustrates, the degree of trust existing between collaborating members. All of these factors have a significant influence on their ability to successfully exploit information to make better decisions that are highly knowledge intensive and entail significant business risk. This does not mean that adapting and innovating strategies are mutually exclusive but that one takes precedence and is supported by the other. It is the role of strategic management to understand the unique balance of each and to

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align financial and intellectual resources accordingly. Remarkable companies are those that have mastered the art and science of striking the fine balance between adapting and innovating. See figure 1. They are remarkable because they are made up of people who know how to live alongside one another even though their purposes are not obviously aligned. For example, when Apple Computers decided to develop the “Mac” they went out of the way to protect it from the traditional Apple culture. A new location was found and organizational processes; systems and structures were designed specifically to support its unique purpose and mission. The new facilities they occupied proudly flew the pirate skull and crossbones flag and its people, many of whom were new to the company considered themselves to be part of something very special. They also knew, however, that at some point they would have to involve people from the wider Apple community if they were to successfully transform their prototypes into product that could be manufactured by the existing organisation. The success of the Apple Mac was due, to a large part, to their ability to work alongside the original business with people who did not share the same interests or priorities. This did not happen by accident, it is the single most important aspect of any collaborative effort and the job of every manager and member of the collaboration to ensure that this is anticipated up front and managed throughout the life of the programme.

High

Discovery

experimentation. From a management perspective, this means ensuring and maintaining knowledge connectivity, recognizing patterns in environmental data, creating and supporting new ideas that don’t necessarily conform to corporate culture but provide options to pursue new challenges. (Savage 1996) This is enabled by knowledge creation from external knowledge sources working in concert with internal knowledge sources to form a community of innovation. As mentioned previously, in their purest form, Open Source strategies such as Linux and Apache take an innovative approach. But more typically businesses opt for a balance of adaptive and innovative approaches when it comes to managing their business. (Groves 1996) For example, in an attempt by Microsoft to make one of its operating systems more competitive with open-source software developers, the company introduced its "shared source" programme. This allows some governments and technology companies access to selected Microsoft code. In addition, Microsoft has added a new category to those eligible to view its code: so-called Most Valuable Professionals (M.V.P.’s), individuals who have been recognised by the software maker for their contributions to Microsoft's online support community. While there are obvious risks attached to giving people access to their most valuable proprietary asset, the benefit is that they increase reliance on the Windows platform. In an attempt to limit this risk, those eligible for Microsoft's various shared-source programmes are permitted to see some of Microsoft's code, but they can't make changes or use it for their own projects. Unlike open-source projects like Linux, where developers see the code, make changes and then distribute the modified product.

Low

Information Enabled

Knowledge Driven

Data Rich

Knowledge Transformed High

Complexity/Velocity Adapting

C1

Innovating

C3 C2 Collaboration

C4 ©2003 by Sean Gadman PhD, CIPD. All rights reserved.

Figure 1: Adaptive and Innovative Strategies C1 – In low complexity environments where knowledge creation is not considered mission critical, partnering of any kind tends not to be regarded as a priority. The objectives of strategic management in these situations is to maintain tight control by managing the input – output relationship between the company and its environment through ensuring clear product

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– market positioning, resource allocation, planning, organizing, human resource management, and control. Management practices and organizational design principles are biased in favour of task specialization and individual rather than collaborative endeavours. Consequently, self-organization among workers is discouraged. Detailed plans rather than guidelines tend to be the norm. Knowledge connectivity is low. Relationships are based on power, control, and hierarchy. Interaction essential to the generation of new knowledge and problem solving are captured, categorized and stored for retrieval. Knowledge networking is neither valued nor encouraged and access to networks via phone, Internet, face to face and videoconferencing are discouraged. There is a significant downside to this strategy, as many in the banking industry are realising. Their historical dominance in none cash transactions from debit cards to electronic transfers-is under assault from nimble competitors never before imagined. Companies like Tesco in the United Kingdom and Wal-Mart in the United States are ready to serve customers demanding choice, convenience, lower costs, and better service. Additionally, there is increasing competitive pressure from within their industry to “off shore” their back office work to low cost locations in India and the Far East. Failing to review pricing and partnering strategies, product ranges, infrastructure, and customer needs in the face of this challenge could have serious consequences. C2 – In situations where there is low environmental complexity yet high need for knowledge creation that cannot be delivered by people locked into formal structures, alternate collaborative strategies are formed within the four walls of the business. Known by a variety of names these communities of common interest or communities of practice (Seeley Brown 19??) are designed to create knowledge by encourage free idea exchange among their members. However, while both communities share this fundamental philosophy, their motivation is entirely different. In business, these communities exist predominantly within the boundary of the business. They are formed with the purpose of increasing competencies, reducing time to market, increasing the value of intangible assets. They are designed to appeal to our natural desire to take on a common challenge, the experience of working with high-calibre colleagues, the opportunity for learning and personal development, collaboration and teaming. Businesses create reward

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mechanisms for sharing knowledge; in some cases these are linked to the main performance review process, and therefore become a mechanism for penalty as well as reward. Typically, the individual’s knowledgesharing abilities are related to measurable contributions to “knowledge- bases”, the number of presentations given to fellow employees, participation in training courses. The reward is increased chance of promotion, an extra percentage of salary increase, or a bonus. These groups may range in size from small working groups of less than 20 members to full communities of hundreds of participating individuals. Their survival depends on how well interests are met by the community resources. In the course of a successful project, different communities will come and go. New ones will spring up, grow, and possibly become dormant or die. As long as thriving communities still exist, the larger project can be considered alive and well. The death of a community does not equal failure. Consider a community that arose to develop a new microchip process. After the standard process developed was tested and accepted by the firms lines of business the process development community, having achieved its purpose was no longer be necessary. If in the future revisions to the standard process are called for, the community might be resurrected. Information technology and the Internet enable these communities to gather for social and commercial interaction. Networks provide strategic and operational benefits by enabling members to collaborate effectively. Boundaries are permeable. The number and density of connections to the environment is increased to speed information flow and adaptation. Information is transparent and diversity of opinions and experience to speed innovation is promoted. The challenge is to recombine to reinvent and people are encouraged to borrow ideas and practices liberally, making every product upgradeable, breeding ideas and processes early and often, and viewing interchangeable modules for people and products essential for mass customization. These experiments are aimed at continuously upgrading the performance of services and products, understanding the requirements of customers, knowing where to target their products, how to market and sell their products and developing new channels to market. Dell and B.P. fit well into this category because

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they have successfully used their strategic knowledge to develop and run proprietary processes and practices that give them a significant competitive advantage over the competition. Sharing this with others outside the business would not be to their advantage. C3 – In high complexity environments where existing knowledge assets are in place and highly capable of creating new levels of knowledge required, partnering tends to be predominantly externally focused and designed to enable self-organization among workers. The objectives of strategic management are to balance control with experimentation. Consequently, guidelines rather than detailed plans tend to be articulated. Knowledge connectivity is also an essential aspect of relationship building because it enables interaction essential to the generation of new knowledge and problem solving. In such a culture, group memory is really the holy grail of knowledge management efforts. However, the effort to capture and categorize is often more hassle than workers and managers are willing to put up with. If the organization's or team's culture is suitable to a conversational working style, the best I.T. solutions offer a combination synchronous collaboration tools such as videoconferencing, instant messaging and screen sharing with asynchronous environments that allow teams to work across geographic and chronological boundaries. In this way, they can quickly produce both a highly effective online workspace and an instant archive that becomes searchable group memory. New team members coming on board can easily get up to speed and ask questions that haven't already been answered. Managers can tune in and get a solid pulse on the state of the project. Customers can be an integral part of the project team, viewing the process and giving feedback along the way. Trusting and stronger working relationships are established for future contracts. And everything is embedded in a clear context (the flow of the conversation), which makes for better, more integrated work and learning. Sun Microsystems fits well into this category. For example, in their recent NetBeans open source project, the company used an open source community to develop an integrated development environment for the Java language. The benefits company benefited because it was able to increase not only its own population of Java skilled programmers but that of its customers. Also, because their servers run well on Java, they were in a position to sell more of them. Lastly, an

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unexpected outcome from the community was an innovative idea that created the potential for a future geographic information systems market, which had never before been contemplated. C4 – Where environmental complexity is high, but requirements for knowledge creation are low having been already been established and held in patents etc., the C4 domain is that of the expert entrepreneur. These partnerships are characterized by highly knowledgeable people delivering products/services that are the result of extensive research and have become the de facto solution. For example, a biomedical start-up company focusing on the product development of biomaterials for orthopaedic applications might incorporate some key expertise in its founding team, this team might also include graduate students who had developed and refined some of the earlier key processing technology. This may also foster other relationships with the original laboratory, and with those who had tacit understanding of how the idea really works, by adding many of those people to its scientific advisory board this company would become adept at drawing complex ideas and external scientists into its R&D group without upsetting its existing ideas and culture. These partnerships are highly skilled at measuring, valuing and managing their intellectual assets. They acquire and retain highly skilled employees and they are knowledge driven in that they are able to embed individual-based knowledge in the company and make it accessible and useful across the organization. Typically, this category is occupied by companies that have been in some or all of the previous categories and are now able to benefit from the results of their experiences. The benefits of this are stable, safe and reliable products and services protected by time based patents like those seen in the aerospace, academic, pharmaceutical and nuclear sectors. The risk of being in this category is that of complacency and those who occupy this category must remain vigilant to replacement opportunities when patents run out.

4. Managing collaborative relationships The Buddhist principle of “dependent coarising,” states that, every recognizable entity on every scale of existence participates in the universal exchange of energies, supporting and being supported by the existence of others (Thich Nhat Hanh 1975). Successful collaborative relationships, whether

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predominantly adaptive or predominantly innovative follow this principle. They possess a potential source of wisdom, compassion and timing that allow their members to thrive in highly complex and fast changing environments. They do not come about by accident but are designed and managed to ensure they possess a balance of symmetry (unity of form), a syntopy (unity of field), and synchrony (unity of flow) (Richardson 2003) and that these elements form an integral, integrated and interactive part of the whole organization. Such integration is made possible through a strong foundation of valuing and trust where people in the partnership interact with one another in mutually dependent ways. The measure of an effective partnering relationship is how much they encourage intellectual, emotional and spiritual growth and personal insight through a deeper understanding of and tolerance for the perspectives of others.

4.1

The Business Benefits

The business benefits to be gained from adopting the most appropriate partnering strategy and organizational design are significant. Whether it’s a desire to tap expertise globally to solve problems locally, a wish to respond faster to changing customer demands or a desire to develop and launch new products/services faster than the competition, a company’s partnering strategy and its design and execution must be inextricably linked. Whether it’s a case of doing the same things better, doing better things or doing entirely new things a company’s choice of one of the four partnering strategies will be influenced by the nature of its business environment and its confidence in the knowledge of its people to successfully take on and overcome the challenge. In cases where environmental disruption is considered high and knowledge levels well suited to maintaining existing product/service offerings, a company will tend to favor a predominantly adapting strategy over an innovating one. Consequently, any efforts to innovate will be more controlled and iterative in nature with partnerships designed to foster knowledge creation, capture and dissemination inside and across the organization. On the other hand, in situations where environmental disruption is tolerable and knowledge levels high, a company might favour a more innovative approach to delivering its portfolio and take on a more experimental approach. In such cases, partnerships are more externally focused and designed to challenge existing knowledge with radically new ideas.

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Strategies aimed at adapting and innovating must be balanced with the right blend of partnering. If companies intend to stimulate knowledge development through external partnerships they have to consider the state of the organization when they decide how much experimentation is enough. To manage external partnerships, managers must continually assess when experimentation is moving away from the guiding values and core mission of the company. Such loose/tight control is essential if knowledge generation is to continue to feed the strategic aspirations of the firm. Managers should also be open to making use of new perspectives which might ultimately change the core mission of the company. They should carefully observe the impact of new ideas on existing culture and gauge the degree of stress people in the organization are willing and able to accept (Cooper and Sutherland 2000) (Meyer 2002) Ultimately, the difference between going it alone and going with others is a personal choice but I hope that the information presented here will make that choice more informed.

References Amadon D, and Skyrme D, “Creating the Knowledge Based Business,” Business Intelligence Ltd, London (1997) Cooper, C, and Sutherland, V, “Strategic Stress Management: An Organizational Approach” Macmillan Business London (2000) Gadman S. and Cooper C. “Strategies for Collaborating in an Interdependent Impermanent World” In press The Leadership and Organizational Development Journal Manchester, UK Gadman, S. Power Partnering: A Strategy for Business Excellence in the 21st. Century. Butterworth – Heinemann: Boston MA (1996) Groves, A, “Only the Paranoid Survive” Doubleday New York (1996) Lee R and Cole “The Linux Model of Software Quality Development and Improvement,” in International Association of Quality (ed) Quality in the 21st Century: Perspectives on Quality and Competitiveness Sustained Performance, ASQ press (2003) Lee R and Cole forthcoming “The Linux Kernel Development: Institutional, Cultural and Evolutionary Processes of Knowledge Creation,” Organizational Science (2003) Meyer, C. Survival Under Stress MIT Sloan Management Review: Mass (2002)

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Morgan G, “Imaginization” Sage California (1993) Nhat Hanh, Thich. Old Path White Clouds. California: Parallax Press (1991) Raymond, Eric, “The Cathedral and the Bazaar,” O’Reilly Associates (1999) Richardson R. The Universe’s Rules. www.DrRob.info Jackson: NH (2003) Richardson R. The Whole and its Parts. www.DrRob.info Jackson: NH (2003) Savage C, “Fifth Generation Management” Butterworth - Heinemann Boston MA (1996)

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Seeley Brown J, and Solomon Gray, E “The People are the Company” Fast Company (August 1995) Von Hipple, E and Von Krogh, G “Exploring the Open Source Software Phenomenon: Issues for Organization Science” Forthcoming (2003) Von Krogh, G. and Roos, J. (eds) Managing Knowledge: Perspectives on Cooperation and Competition London: Sage (1996) Winograd, T. and Flores, F. Understanding Computers and Cognition. Norwood, NJ: Ablex (1987)

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Knowledge Management Development Challenges of Transition Economy Organisations Representing Different Value Creation Models Tiit Elenurm Estonian Business School, Tallinn, Estonia [email protected] Abstract: This paper addresses knowledge management assumptions and development visions in the following

types of organisations: organic product-focused and organic service-focused organisations, mechanistic bureaucratic and mechanistic product-focused organisations that represent different models of value creation. These types of organisations are identified and examined in relation to the changing knowledge management context of the transition economy in Estonia. Knowledge management priorities assessed by representatives of 95 organisations are then discussed in the qualitative research and learning framework. Keywords: knowledge management, value creation, know-how, know-why, transition economy, learning organisation,

1. Introduction Organisational knowledge and core competences form the main foundation of competitive advantage and the basis for meeting business challenges in the 21st century (Drucker 2002, Hamel 2000). Recognising the importance of knowledge management is, however, not sufficient for choosing the appropriate knowledge management (KM) tools in order to increase the value of the organisation and its business by implementing KM initiatives. The significance of organisational capabilities as an interplay of knowledge, communication and technology has to be taken into consideration in the process of developing organisations (Braf and Goldkuhl 2002). The need to align knowledge management projects and strategic business goals is a key challenge for implementing knowledge management concepts in advanced market economies (Davenport and Prusak 1998, Tiwana 1999). Impact of diversified value creation frameworks and changing business opportunities should be also studied in transition economies as the bases for understanding knowledge management development priorities. The potential of KM can be utilised on a wider scale and with more substantial impact on operational and strategic business performance, if both environmental and organisational contingency factors are studied to facilitate the adaptation of KM concepts to suit different types of organisations. A typology that is relevant to organisations in a transition economy is used in the present paper for exploring KM assumptions and priorities in the context of different value creation opportunities. Essential contingency factor is the rapidly changing environment of the

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Estonian transition economy. Estonia as a small open economy has experienced during recent 10 years rapid economic reforms on its way towards the advance market economy. The challenges of different sectors in the field of international competitiveness and developing company core competencies, globalisation and European integration do not however coincide. We investigate how specific strategic challenges and problems in different types of organisations are reflected in knowledge management assumptions and development priorities.

2. Knowledge management in learning and changing organisations Development of the KM field has led to the discourse about stages, ages or generations of knowledge management. Dave Snowden (2002a) distinguishes the first age in which the word knowledge itself was not problematic and the focus was on distributing information to decision-makers through information technology and business process reengineering. The second age was initiated by the SECI model of Nonaka and Takeuchi (1995) and its focus was on the movement of knowledge between tacit and explicit states. The third age focuses on studying the paradoxical nature of knowledge in complex systems and understanding knowledge flows and transformations between complex, knowable, known and chaos domains (Snowden 2002a). Knowledge transformations between these domains can also be treated as organisational learning processes. In order to develop a KM strategy the management team, for instance, has to assess how the existing space of known best practices can be used for training programmes, what the role of internal

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competences and external experts will be in exploring the knowable space and the probability that the chaotic space will enhance learning by doing or even reframing existing business concepts. Understanding the impact of changes in the business environment and the strategic intent of decision-makers allows KM practitioners to assess the extent to which organisations really are ready to use the theory of complex and adaptive systems. Maybe tools offered by the first and second age of KM are suitable for solving some strategic tasks and there is still a long process of organisational learning ahead before the paradigm of complexity can be transformed from the knowable domain to the known domain? Mark McElroy (2003) distinguishes two, not three KM generations. First-generation supplyside KM is focused on capturing, codifying and sharing valuable knowledge and on getting the right information to the right people at the right time. Second-generation demand-side KM enhances the capacity of the organisation to produce new knowledge. McElroy (2003) also refers to explicit connections drawn between second-generation KM thinking and organisational learning. He sees secondgeneration KM as an implementation strategy for organisational learning. Peter Senge, the author of The Fifth Discipline (Senge 1990), has listed challenges common to knowledge management and organisational learning communities: understanding the nature of organisational knowledge, its generation and diffusion, the interface between acquiring information and generating knowledge, developing knowledge-based strategies (Karlenzig 1999). The goal to increase the capability of an organisation to learn by systematically processing new information about a changing environment and by critically reflecting upon past experience is especially relevant to business organisations in transition economies. These organisations have to deal with the challenge of radical and partly unpredictable changes in their immediate competitive environment and monitor changes in the larger socio-economic environment. It is however not self-evident if organisations that need the qualities of learning organisation in order to face radical changes have always time and resources to apply five disciplines of personal mastery, shared vision, mental models, team learning through reflection and inquiry and systems thinking in the coherent way. In the period of rapid societal and economic change an important factor

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influencing the KM agenda is the dilemma of exploiting the “windows of opportunity” for rapid business gains versus developing an organisation that is directed by a vision for sustainable competitiveness. Long-lived international corporations that were “built to last” are found to be sensitive to their environment, cohesive, with a strong sense of identity based on the ability to build a knowledge sharing community, tolerant of noncore activities on their periphery and conservative with their money (De Geus 1997). A company that is directed by owners following short-term profit horizon is less interested in investing into mutually beneficial knowledge sharing with clients and other stakeholders and into organisational memory. Sustaining momentum in a learning organisation is a challenge that has to be dealt with in the context of the life cycle of organisational change initiatives taking into consideration the interplay between reinforcing growth processes and limiting processes (Senge et al. 2001, p7). Opportunities and needs for introducing KM practices also depend on the life cycle of the total organisation and its market (Nonaka and Reinmoeller 1998). A small new greenfield venture at the non-saturated market may be in the situation, where applying the rule “first act, then sense and respond” is the best way to take advantage of the empty market. A growing enterprise at a more mature market has to devote more time and energy to sense changing customer needs and to monitor behaviour of competitors. That will influence how the potential of knowledge management is perceived. Rob Cross and Laurence Prusak (2002) describe how in informal networks interactions between central connectors, boundary spanners, information brokers and peripheral specialists make organisations go or stop. In a small venture a capable entrepreneur carries several of these roles and can directly communicate with persons carrying other roles. Systematic KM solutions that will take into consideration the potential of social networks are needed if an organisation grows. From the point of view of a KM expert introducing relevant knowledge “just-in-time”, right when you need it (Snowden 2002b), is a sound principle. Aligning organisational learning and change processes with KM development means avoiding premature and formal use of KM tools plus developing a sense of urgency, clear priorities and assumptions for implementing appropriate KM solutions if and when these support the strategy of the organisation.

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Knowledge management can be seen as a tool for putting the vision of a learning organisation into practice, but it is also important to understand the impact of organisational learning processes on KM practices and development priorities. What essential qualities of the learning organisation have to be created before investments to knowledge management applications become efficient? What types of organisational learning processes transform knowledge management ideas to the real agenda of managerial decision-making or change? To what extent the readiness to apply knowledge management and development priorities in this field are shaped by changing relations with clients and other stakeholders and what is the impact of developing new products and technological know-how? We use typology of organisations that relates different positioning of organisations in the Estonian business and institutional environments to organisational change capabilities for searching answers to these research questions

3. Typology of organisations for studying knowledge management priorities 3.1

Mechanistic and organic organisations as knowledge management environments

The comparison of mechanistic and organic organisations was already introduced some 40 years ago. The mechanistic organisation as more suitable for stable conditions was characterised (Burns and Stalker 1961, pp119122) by a specialised differentiation of functions; the use of a formal hierarchy for coordination, control and communication; the precise definition of rights and obligations; the centralised location of knowledge of actualities at the top of the hierarchy; insistence on obedience to superiors and vertical interactions; and greater importance and prestige attached to internal (local) rather than general (cosmopolitan) knowledge. Many structural and process-oriented approaches to organisational behaviour and organisational development techniques have for several decades explicitly or implicitly followed the vision of moving towards the organic organisation that was featured by Burns and Stalker. Organic organisation links special knowledge to common tasks, sets the realistic nature of the individual task according to the total situation of the organisation and

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enables adjustment and redefinition of individual tasks through interaction with others. It is based on an informal network of control, authority and communication, locating technical and commercial knowledge anywhere in the network; lateral consultationtype communication; commitment to the task and the importance and prestige attached to the affiliations and expertise valid in the industrial, technical and commercial environments outside the firm. Checklists characterising the mechanistic and organic organisation include features that are directly related to the knowledge management discourse. One could claim that the features of the organic organisation could be interpreted as good ground for introducing contemporary KM solutions. Mechanistic organisations are however, not a priori alien to some KM tools, especially if the focus is on the appropriate structuring and flow of information to decisionmakers.

3.2

Knowledge management in the context of a transition economy

Estonia has gone through the transition from the former Soviet command economy to the market economy that is in the process of integration to the European Union. During the transition process of 90-ies private business organisations as well as the public sector in Estonia have been exposed to intensive international knowledge transfer opportunities and learning challenges. Earlier studies of managers in Estonian companies have pointed out that market-driven changes in strategy, organisational culture, leadership style and the mission of the organisations can be seen as the increasing role of radical transformation factors in the 90’s as part of the transition to a market economy (Alas and Sharifi 2002, pp313-331). Further studies are needed, however, in order to understand the real influence of these changes upon organisational learning capabilities and the introduction of KM practices. New information and communication technology solutions have influenced the Estonian service sector. Estonia has been among the first countries to introduce mobile payment for parking and personal m-accounts that allow the use of mobile phones instead of a bankcards. Since December 2002 permanent wireless Internet connections through combined WLAN and GPRS solutions have been available practically all over the territory of Estonia. The study of innovation in Estonian enterprises 1998-2000 based on the

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sample of 3 490 enterprises with more than 10 intramural R&D, become more important as a employees and 777 enterprises with 2-9 part of the business strategy, the special KM employees indicated relatively advanced needs of know-how organisations will deserve innovation patterns in the Estonian service more attention in the Estonian innovation sector in general and more developed policy. cooperation strategies in service companies It is important to understand the influence on compared to industrial enterprises (Kurik et al. KM assumptions of market-driven changes, 2002, pp32-33). At present the readiness innovations driven by technology and new among service companies combining product product development within organisations. In and process innovations to develop and exploit order to reflect these factors a matrix that advanced KM solutions in cooperation with combines the dimension of mechanistic versus their clients could be better than the same organic organisations with the dimension of readiness among product-focused know-how product-focused versus service-focused organisations engaged in new product organisations (Nurmi 2000, p67) was selected development efforts. Only 2% of Estonian as the sense-making model for our research. enterprises use over 4% from their turnover for The meaning of the four spaces derived from research and development activities (Kurik et these dimensions is explained in table 1. al. 2002, p39). If R&D activities, including Table 1: Typology of organisations for studying KM assumptions and priorities

Mechanistic

Organic

Product-focused

Service-focused

Industrial organisation Value creation based on internal efficiency of relatively stable production processes

Bureaucratic organisation Value creation through following institutionally pre-determined routines in a reliable and rational way

Know-how organisation Value creation based on know-how generated through new product and technology development

Know-why organisation Value creation driven by monitoring and anticipating client needs and compiling complex solutions to suit clients’ problems

We added our interpretations of value creation to Raimo Nurmi’s matrix in order to clarify the meaning of the matrix in the context of knowledge management. Different ways of value creation influence prospects of long-term competitiveness in the framework of integration to the European Union and globalisation. Bureaucratic organisation in this typology does not have negative connotation. This term is used in the Max Weber (1947) ideal bureaucracy sense. Bureaucracy in this context can be efficient if it serves needs of stakeholders by following routines in reliable and transparent way. Service-focus of such organisation is however limited to avoiding mistakes and minimizing turbulent influence of the environment on relatively stable procedures. If a public organisation has to anticipate new client needs and even re-define its client segments we would position it as a know-why organisation. Bureaucratic organisations that correspond to the meaning used in the matrix can be found also in the private sector and public organisations can be positioned outside the bureaucratic space if the nature of their value creation corresponds to some other space. Industrial organisation

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processes material inputs and optimises the use of different resources for producing products. Innovating products or moving to new markets is however not the main challenge of this organisation type. Core competence of the know-why organisation is related to understanding changing markets and client needs. It is different from the knowhow organisation, where core competence is build around developing new products and technologies that can be commercialised either by selling the intellectual property or by implementing innovative product or technologies for enhancing own competitiveness of the know-how organisation. Borderlines between these four spaces of the matrix are indeed conditional. There are organisations that are engaged in producing know-how through new product development but also anticipate or even try to create new client needs or re-define client segments. An industrial organisation may have research and development unit that follows to the value creation path of a know-how organisation. In order to understand the strategic context of the knowledge management agenda it is however justified to place a decision-maker into the

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strategic choice situation by asking: “Which of these spaces reflects the position of your organisation at present and how it could change during next five years if your strategic vision is turned into reality?”

4. The learning community in the action research process The possibilities and limitations of approaches to quantitative and qualitative research change if we move between phases of scientific cognition: from explorative to descriptive and explanatory research. Quantitative questionnaire-based surveys are suitable for measuring such attributes of phenomena, which are understood in the same frame of reference by respondents. Knowledge management is, however, a relatively new concept. The researcher has to capture the pre-understanding and sense-making patterns of managers. Qualitative methods have strengths in descriptive and explorative research or where the context and the respondent’s frame of reference are important (Marshall and Rossman 1995). Qualitative research enables one to get close to the object of the study, to identify important variables, patterns and meaning structures for participants in order to investigate little understood phenomena (Remenyi et al. 1998, pp107-113). Evert Gummesson (2000, p35) treats action research as the most advanced step in qualitative research compared to interviews and observations. The full potential of action research, however, can only be used if the researcher manages to act as the change agent during the whole cycle of diagnosing the management problem, generating, assessing, selecting and implementing new solutions, checking outcomes and introducing corrective actions. The present study process does not cover the process of actual implementation of KM development strategies. The process of action research is limited to the following steps: 1. Introducing basic knowledgemanagement concepts through interactive learning supported by the WebCT elearning environment. Each participant had to search for knowledge-management and organisational learning publications or Internet sources and send an executive summary of his source to the virtual forum referring to the practical implications of the ideas reviewed. 2. Introducing and discussing the checklist of KM preconditions (appendix 1) as a tool for assessing KM assumptions and

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priorities. The checklist was a reflection of some consulting experience related to KM initiatives. 3. Assessing KM assumptions in organisations that were represented by managers or specialists participating in the action research process. Participants had to give their assessment by specifying and ranking 10 high priority preconditions for efficient KM in their organisations. They also explained to what extent these preconditions for efficient KM had already been created. In the assessment process, organisations were positioned to one or more of the spaces in table 1. Participants were encouraged to re-define KM assumptions presented in the checklist or to add new ones. A short written report was presented. 4. Creating subgroups following the typology of organisations. Members of each subgroup were asked to reflect on the results preceding from step 3 and to find common ground among KM priorities and tools in their group. 5. Each participant finally documented, in an essay, the strategic vision of KM development in his/her organisation and specified the main tools for putting the vision into practice. The main ideas of these essays were then presented orally to the other participants. In 2001 MBA students working as managers or specialists in 31 Estonian companies or public agencies participated in a limited format of this cycle. On this occasion however, the typology of organisations was not introduced and subgroups based on organic-mechanistic and product-focused versus service-focused types were not applied. The full research and learning cycle applying the typology was subsequently conducted in autumn 2002. Participants were also asked to present their vision and rationale for a possible repositioning of their organisation from one field of the matrix to another. It was possible to prove that their organisation combined features related to different fields of the matrix. In this cycle 52 organisations were analysed. In spring 2003 a smaller group of 14 MBA students analysed 12 organisations. We treated these groups as learning communities sharing their experience-based knowledge and their new knowledge acquired in the learning and research cycle.

5. Research results The comparison of the highest average importance rankings of assumptions of

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broader concept and received the highest rank knowledge management in table 2, from in the 2002-2003 study. In 2001, the experts in 2001, 2002 and 2003, indicates that subsidiaries of trans-national companies were assumptions related to trust, the free analysed separately. It was found that they circulation of information, the promotion of have a relatively good technological foundation information sharing and integration between for developing KM practices. databases have consistently been among the top five. Although, trust was treated as a Table 2: Assumptions of efficient knowledge management that received the highest priority rankings Priority rank (importance) Assumptions of efficient knowledge management

Trust between employees as a basis for knowledge sharing Free circulation of information. Product and client information easily accessible. Promoting information sharing between colleagues, linked to bonus schemes Integration between the databases of headquarters, suppliers and business partners

Virtual databases and colleagues are more valuable sources of information than paper documents The information search and retrieval system is efficiently used

for 31 organisations in 2001 V

for 52 organisations in 2002

for 12 organisations in 2003

I

I (broader interpretations than in 2001) II

I (broader interpretations than in 2001) II

II

III

III

IV (II – in subsidiaries of foreign companies) III

V

IV

IV

VII

VII-VIII

VII

V

The integration of local knowledge sharing tools in Estonian subsidiaries with data and knowledge bases from their international headquarters, suppliers and customers is, however, in many cases low. This is perceived by the local Estonian staff of these companies as a high-priority challenge in the area of KM development. While the efficient use of information search and retrieval systems received a higher priority in 2003 compared to 2002 and 2001, giving value to virtual databases and colleagues versus paper documents has received lower priority ranking in 2002 and especially in 2003 compared to 2001. It could be misleading, however, to interpret the differences between the priority lists in 2001, 2002 and 2003 as reflecting general trends of change. Organisations that belong to different sectors and strategic contexts were not represented equally in these three research and learning cycles. Following the logic of the qualitative research, we try to reflect differences in the patterns of KM assumptions depending on how participants positioned their organisation in regard to mechanistic versus organic and product-focused versus service-focused organisation types.

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In 2002 five out of 52 organisations and in 2003 two organisations out of 12 were positioned as mechanistic and productfocused. In both years one organisation was identified as being a combination of mechanistic, product-focused and bureaucratic. In this industrial type of organisation trust between employees and the free circulation of information were pointed out as important KM assumptions. Moving from paper documents to virtual databases was seen as the third most important priority. Links between KM, defining future core competences in the organisation, monitoring business processes, quality management and cost control were stressed in KM development visions. Among KM assumptions, in practice the free circulation of information showed the weakest level. Six organisations in 2002 and five in 2003 combined features of bureaucratic and knowwhy organisations and two organisations in 2002 were positioned as bureaucratic organisations. Some state offices but also private enterprises, where core sales or service processes are pre-determined by foreign headquarters or are by their nature quite routine, belonged to this type. The majority of organisations in this group already

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had information technology solutions that could support KM. In state offices one of the development challenges was the integration of IT-solutions used in different ministries. The problem of information overload was pointed out. The free circulation of information was considered to be the most important KM assumption in these organisations, but it was also linked to clearer procedures, the responsibility of information providers, information search tools and the analysis of existing information flows. The group of eight companies in 2002 and three companies in 2003 that combine the features of organic product-focused and organic service-focused organisations included Estonian subsidiaries of some international IT and telecommunication companies, but also small consulting firms and organisations involved in the import of sophisticated technology products, tourism and medical services. Although levels of experience and the availability of tools for KM are quite different in these organisations, one can find a common denominator reflected in the following question: How can one broaden the expertise of employees representing different functional roles so that, for instance, the serviceman is not only limited to repairing and the salesman to selling? Members of this group stated as a result of group discussion that information technology is necessary, but not sufficient on its own for creating the essential KM assumptions. Three high-ranking KM assumptions in this group of companies included the free circulation of information, virtual databases and colleagues as more valuable sources of information than paper documents, and trust between employees as a basis for knowledge sharing. Several experts in this group pointed out that interfaces for discussing features of new products with clients and partners was a development priority and full-text search and data mining tools for integrating different databases were the missing KM assumptions in practice. Twenty companies in 2002 and two in 2003 were positioned as organic and servicefocused organisations (know-why organisations). Links between customer relationship marketing and KM were stressed in this group. A common development challenge was the collecting of practical knowledge about interactions with clients and adding this to the knowledge base. Improving possibilities for clients to use existing databases and solving related compatibility problems were seen as part of the KM

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development agenda. Larger organisations pointed out the need to “link existing islands of knowledge-sharing”. E-learning was also seen as a field of KM development in this group. The ranking list of KM assumptions in this type of organisation started from the readiness of employees to share their expert information with others, followed by trust between employees as a basis for knowledge sharing and free circulation of information. Attitude change among the sales staff and other employees supporting client relations was linked to such development challenges as motivated teamwork and training systems but also to improving the quality of databases, information search and filtering tools. A vision for the future role of a chief knowledge officer was presented by some organisations in this group. Access to different sources of information, including central corporate knowledge bases at international headquarters, and institutionalising knowledgesharing practices on a daily basis were assessed as the weakest KM assumptions in some organisations belonging to this group. Nine organisations were positioned by participants as organic product-focused knowhow organisations in 2002 but there was none of this type in 2003. Their KM development agenda appeared to be quite similar to knowwhy organisations. It seems that organisations represented in this group were not involved in generating new products or technologies through intramural research and development. They were mainly adapting and diffusing new know-how that had been created elsewhere. Project management, risk analysis and the reflection of experience and mistakes in different process stages were pointed out as areas appropriate for applying KM methods. Knowledge management development needs were also related to improving transactions in the value chain. The readiness of employees to share their expert information with others, followed by trust between employees as a basis for knowledge sharing and recognising the knowledge of employees via bonus schemes were three high-ranking KM assumptions in this type of organisations. Access to different sources of information, the free circulation of information and virtual databases were pointed out as missing KM assumptions. There were also critical assessments of the situation in the area of fulltext search and data mining tools and institutionalising knowledge sharing practices on a daily basis.

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Virtual project team rooms and electronic cards or yellow pages describing education, competences and project experience among employees were assessed as missing KM assumptions in many organisations belonging to various types. These assumptions were, however, not ranked among the five most important in any group. Many experts explained that their organisations are still too small to generate value through such tools. The ability to use KM tools for participating in international project teams is an important challenge for managers and experts in business organisations under transformation. This will influence their chances of becoming a competence centre in a large trans-national company or of taking an active role in international knowledge-sharing networks among independent companies.

6. Lessons learned and conclusion It is difficult to arrange research and learning cycles in a format where the composition of the groups and learning processes are similar enough to make the results of different cycles fully comparable. If the learning effect in such research and learning cycles is substantial, as we indeed hope it is, the pre-knowledge of participants will be modified in the knowledgesharing process and in turn will influence their interpretation of KM assumptions. We have the opportunity, however, to monitor and interpret the learning process as it shapes the assessments of our sources of research information in a much better way than is possible in a classical questionnaire survey. This is especially evident when questionnaires are mailed to respondents who might have a different background, which may influence their interpretation of the terms used in such a questionnaire.

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reflecting successful or unsuccessful implementation of the KM vision presented earlier in the research cycle. A high quality case study should be a story that draws on multiple sources of evidence and their triangulation and provides meaning in context, among other characteristics explained in (Remenyi et al. 2002). Described learning and research cycles did not allow us to rely on sources of evidence from inside the organisations that would have been independent of the participants of the cycle; although, it did facilitate the discussion and challenging meanings and beliefs of participants in the interactive process. The documentation resulting from the cycle provides a good departure point for follow-up interviews inside the companies. We would prefer to continue within the action research framework, which would mean using consulting or in-house training opportunities to achieve access to management and organisation realities and development processes. Integrating research and learning processes is one way of understanding the specific contexts of KM development efforts. The learning community can become a tool for gaining insights from interpretivist research and for supporting smart knowledge management strategies.

From the interpretivist point of view an alternative to using the checklist of assumptions is to ask participants to start their story from “a blank white sheet of paper”. That however, would make knowledge sharing in sub-groups less structured and we would miss the opportunity to reuse knowledge created at earlier stages. In further research, however, we could test different checklists of enabling factors including the hierarchy of knowledge management activities (Stankeviciute 2002). Another spin-off opportunity for further research is to continue our co-operation with some participants of the action research cycle in order to produce case studies as stories

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Appendix 1: Knowledge management assumptions (based on the checklist by Tarmo Toiger, IBM Estonia) Free circulation of information. Product and client information, including information about new potential clients and related projects, is easily accessible. Regular monitoring of information about competitors. Employees are able to combine different sources of information, including the databases in their local unit, the central databases at headquarters and the integration of organisation-wide knowledge bases. Integration with the databases of suppliers and business partners. Virtual databases/knowledge bases, Intranet and colleagues are more valuable sources of information than paper documents. Relevant information in an electronic format is more actively used than paper documents. The information search and retrieval system is used efficiently. It is possible to use full-text search throughout the information system, including different databases and catalogues used in the organisation Information about the competences of all members of the organisation is accessible on electronic yellow pages. This information includes education, earlier work experience and knowledge profile. Links between employees and different projects and clients are also available. Employees have recognised fields where their expert knowledge can support others. They are ready for knowledge-sharing. Employees are aware of the information and knowledge their colleagues might be looking for and are sufficiently skilled to meet these expectations on time and in the right format. Special virtual project workrooms have been created for project teams. All project information and correspondence with internal and external clients is collected there. Virtual information processing and knowledge sharing tools are used actively. This is an essential part of normal daily behaviour. There are established rules for using the groupware, for sending and responding to e-mail messages. Everybody follows the rules to

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save time and to diminish irrelevant information. Promoting information sharing between colleagues. Such behaviour is valued and encouraged. Bonus schemes are created in order to further activate knowledge flows. Trust between employees as a basis for knowledge sharing. Employees trust each other and discuss any failures and mistakes they have made in the course of doing their job with other members of the organisation in case the lessons learned may also be useful for their colleagues.

References Alas, R., Sharifi, S. (2002) “Organizational Learning and Resistance to Change in Estonian companies”, Human Resource Development International, Vol 5, pp313331. Braf, E., Goldkuhl, G. (2002) “The Significance of Organisational Capability: The Interplay of Knowledge, Communication and Technology”, Third European Conference on Knowledge Management, Trinity college, Dublin, pp80-91. Burns, T., Stalker. G.M. (1961) The Management of Innovation, Tavistock Publications, London. Cross, R., Prusak, L. (2002) “The People Who Make Organizations Go-or Stop”, Harvard Business Review, June 2002, pp105-112. Davenport, Th., Prusak, L. (1998) Working Knowledge: how organizations manage what they know, Harvard Business School Press, Boston. De Geus, A. (1997) The Living Company, Nicholas Brealy Publishing, London. Drucker, P. (2002) Managing in the Next Society, St. Martin’s Press, New York. Gummesson, E. (2000) Qualitative Methods in Management Research, Sage Publications, London. Hamel, G. (2000) Leading the Revolution, Harvard Business School Press, Boston. Karlenzig, W. (1999) “Senge on Knowledge”, Knowledge Management, July 1999, pp22-24. Kurik, S., Lumiste, R., Terk, E., Heinlo, A. (2002) Innovation in Estonian Enterprises 1998-2000. Innovation Studies 2/2002, Foundation Enterprise Estonia, Tallinn. Marshall, C., Rossman, G. (1995) Designing Qualitative Research, Sage Publications, London. McElroy, M. (2003) The New Knowledge Management, Butterworth-Heinemann, Burlington.

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Nonaka, I, Takeuchi, H. (1995) The Knowledge-Creating Company, Oxford University Press, Oxford. Nonaka, I., Reinmoeller, S. (1998) “The Art of Knowledge: systems to capitalize on market knowledge”, European Management Journal, 6, pp673-684. Nurmi, R. (2000) Johtavatko johtajat?, Mermerus OY, Tampere. Remenyi, D., Money, A., Price, D., Bannister, F. (2002) “The Creation of Knowledge Through Case Study Research”, Third European Conference on Knowledge Management, Trinity college, Dublin, pp575-585. Remenyi, D., Williams, B., Money, A., Swartz, E. (1998) Doing Research in Business and Management, Sage Publications, London. Senge, P. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization, Randon House, London.

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Senge, P. et al. (2001) The Dance of Change, Nicholas Brealey Publishing, London. Snowden, D. (2002a) “Complex Acts of Knowing: paradox and descriptive Selfawareness”, Third European Conference on Knowledge Management, Trinity college, Dublin, pp1-13. Snowden, D. (2002b) “The Knowledge You Need, Right when You Need it”, Knowledge Management Review, Vol 5, Issue 6, pp24-27. Stankeviciute, J. (2002) “Conceptualising and Testing Enabling Conditions for KM: The hierarchy of knowledge management activities approach”, Third European Conference on Knowledge Management, Trinity college, Dublin, pp667-675. Tiwana, A. (1999) The Knowledge Management Toolkit, Prentice Hall PTR, Upper Saddle River. Weber, M. (1947). The Theory of Social and Economic Organisation, Oxford University Press: London.

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Developing Systems to Support Organisational Learning in Product Development Organisations Brian Donnellan, Analog Devices B.V., Limerick, Ireland. [email protected]

Brian Fitzgerald University of Limerick, Ireland. [email protected] Abstract: There are aspects of New Product Development (NPD) business processes that pose particularly difficult challenges to Organizational Learning systems. Short product and process life cycles compress the available time window for recouping the expenses associated with product development. Cross-functional collaboration in product development organizations requires the merging of knowledge from diverse disciplinary and personal skills-based perspectives. Cross-institutional collaboration leads a requirement for knowledge to be combined from participants across multiple collaborating organizations. Transient existence in teams and high turnover results in a reduction in organizational knowledge unless there is a repository for knowledge rather than a dependence on knowledge which is situated in the minds of individuals. High rates of change in turbulent industries, such as electronics, motivates participants in NPD processes to effectively overcome these Organizational Learning challenges. The potential payoff includes time saved by not repeating mistakes and reuse of knowledge that leads to successful products and processes. IS research has paid little attention to NPD processes despite the fact that some IS appears to have the potential to have an impact in that area. Recent research completed by these researchers in Analog Devices Inc identified Organizational Learning challenges encountered by engineering teams in product development. This paper will report on these challenges and will describe how systems were developed to support organizational learning to support the product development process. Keywords: Organizational Learning, New Product Development, Knowledge Management, Knowledge Management Systems

1. Introduction There are aspects of New Product Development (NPD) business processes that pose particularly difficult challenges to Knowledge Management Systems (KMS). Short product and process life cycles compress the available time window for learning lessons associated with product development. Cross-functional collaboration in product development organizations requires the merging of knowledge from diverse disciplinary and personal skills-based perspectives. Cross-institutional collaboration leads to a requirement for knowledge to be combined from participants across multiple collaborating organizations. Transient participation in teams and high turnover results in a reduction in organizational knowledge unless there is a repository for knowledge rather than a dependence on knowledge which is situated in the minds of individuals. When these challenges are not overcome they result in inefficiencies in NPD business processes. The inefficiencies may have several negative influences on the performance of NPD organizations. There can be a lack of shared understanding among the NPD team members. There may be an overreliance on transmitting explicit rather than tacit design information that can, in turn, lead to repeated mistakes or a re-invention of solutions during product evolution. Skills that had been developed due to collaboration may

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be also lost thereafter because of the inability to transfer existing knowledge into other parts of the organization. Inefficiencies also arise from inconsistencies in multiple versions of information located in different locations. High rates of change in turbulent industries, such as electronics, motivates participants in NPD processes to effectively overcome these KM challenges. The potential payoff includes time saved by not repeating mistakes and reuse of knowledge that leads to successful products and processes. IS research has paid little attention to NPD processes despite the fact that some IS appears to have the potential to have an impact in that area. Recent research completed by the authors of this paper in Analog Devices Inc. (ADI)1 identified KM problems encountered by engineering teams in product development. These challenges pointed to the need to adopt a dual approach to knowledge management. The approach demands (a) a supporting infrastructure of IS applications and (b) management initiatives to promote appropriate behavioural patterns that help create a one-company culture.

1

Analog Devices Inc. is a world leader in the design, manufacture, and marketing of integrated circuits (ICs) used in signal processing applications. Founded in 1965, ADI employs approximately 8,500 worldwide.

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This paper will report on the KMS challenges faced by engineering teams engaged in NPD and will outline the balanced approach to KM adopted by ADI that incorporates both Table 1: Structure of this Paper Section 1 2 3 4 5

technical and socio-technical systems to support the product development process. The paper is structured as follows:

Topic Introduction New Product Development and Knowledge Management Systems KM Challenges posed by NPD Processes ADI’s Response to KMS Challenges Summary, Conclusions

2. New product development and knowledge management systems This section will review current thinking on KM in the context of NPD and will describe some of the KMS models proposed for organizations engaged in NPD

2.1

34

Knowledge management and new product development

Seminal contributions to research into the role of knowledge in competition have come from Drucker and Grant. Drucker was one of the first to herald a knowledge-based economy by illustrating that knowledge was eclipsing traditional factors of production (i.e. land, labour and capital) as a primary resource. He was credited with coining the term “knowledge worker” and in (Drucker 1993) stated, “knowledge had become the basic economic resource”. Support for Drucker’s viewpoint came throughout the 1990’s as a more general view of the pervasive role of knowledge in business activities evolved from a number of management writers and practitioners. For example, (Quinn 1992) provides statistical support for the information and knowledgebased view of the economy (e.g. services sector accounts for 74% of value-added in the U.S. economy, estimating that 65-75% of those engaged in manufacturing employment are actually engaged in services). Similarly, (Stewart 1997) supports this assertion that information and knowledge are the economy’s primary resource with numerous statistics and examples in both his book’s foreword and first chapter. Grant proposed a “resource-based” view of the firm. This view emphasizes the importance of a firm’s resources, including intellectual capital, as its source of sustainable competitive advantage. In (Grant 2000) he states “what distinguishes the Knowledge Economy from previous economies is the sheer accumulation of knowledge by society, the rapid pace of innovation and, most important, the advent of digital technologies that have had far-reaching

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implications for the sources of value in the modern economy”. He identifies four aspects of management practice which are impacted by the dynamics of the emergent Knowledge Economy: a) Property rights in knowledge Recognition of the value of proprietary knowledge has increased the amount of intellectual property legislation by legislatures and judicial systems over the past two decades. The enforcement of intellectual property in the form of patents, copyrights, and trademarks has become a central asset-management activity (Grindley and Teece 1997). b) Accelerating knowledge creation and application Companies engaged in new product development have struggled to shorten their product development cycles. For example, the fundamental force behind Intel’s sustained success is its “time pacing” - the time pacing of product development though continual minor innovation with periodic “mid-life kickers”, together with nine-month fabrication cycle (Brown and Eisenhardt 1998). c) Converting tacit into explicit knowledge Kogut and Zander coined the term “paradox of replication” to describe where the codification of knowledge required for internal replication may also facilitate replication of that knowledge by other firms (Kogut and Zander 1992). The challenge facing KM practitioners appears to be how to build barriers to external replication through linking internal systems to knowledge that cannot be replicated by outsiders (Schultze 1998). d) Competing for standards Over the last two decades, there has been a change in attitude towards the role of industry standards. Firms are now more willing to sacrifice short-term financial gains for long-term benefits derived from standardization processes. These strategies can imply that firms have to form collaborative projects with customers, competitors and government agencies to

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achieve a standardization goal. These types of projects, by their nature, place a lot of emphasis on KM capabilities.

2.2

Knowledge management systems and new product development

There are three common applications of IS to KM initiatives: (1) the coding and sharing of best practices, (2) the creation of corporate knowledge directories, and (3) the creation of knowledge networks. There is much debate on the effectiveness of these IS contributions in supporting KM initiatives. Some argue that capturing knowledge in a KMS can inhibit learning and results in the same knowledge being applied to different situations even when it might not be appropriate (Cole 1998). Other researchers contend that the application of IS can create an infrastructure and environment for strengthening and accelerating KM initiatives by actualizing, supporting, augmenting and reinforcing knowledge processes by enhancing their underlying dynamics, scope, timing and synergy (Vance and Enyon 1998), (Hendriks and Vriens 1999). Research in KMS has paid little attention to NPD processes despite the fact that KMS technology appears to have the potential to have an impact in that area. Ramesh and Tiwana analysed the NPD process for a Personal Digital Assistant operating system, and went on to develop a prototype system to support collaborative NPD (Ramesh and Tiwana 1999).

product development process (Court, Culley et al. 1997). They analyzed the methods by which the NPD team members retrieve, apply and subsequently transfer their information. A significant finding was that even though team members have access to IS tools and services, they still preferred to use manual and verbal methods of communication and information retrieval. These preferred formats may suggest that computer information accessing and storage is still at the infancy stage and therefore used with some reluctance by design teams. A key challenge appeared to the researchers to be the extensive use of personal information stores and the absence of easy-to-use indexing systems. Scott proposed a framework that decomposed the NPD process into three phases and then classified the types of knowledge and IS appropriate for each phase (Scott 1996) (see Table 2). The first phase is the pre-product phase and the knowledge requirements at this phase are related to what has been learned about these types of products in the past and how that learning can be applied to the planned project. Groupware and intranets are seen as IS support systems that can help this phase. The second phase is concerned with the actual product design activity and focuses on the design decisions that are made and the IS that can provide decision support. The third and final phase focuses on production issues that arise after design. Product data management IS are seen are relevant at this stage, as well as Video Conferencing to help coordinate production planning.

Court, Culley et al. investigated the use of information in NPD teams and reported on the use of information technology to support the Table 2: Knowledge in New Product Development (Scott 1996)

Knowledge

IS

Pre-product Design Lessons learned Projects history Links to Experts Customer needs Supplier competence Market intelligence Groupware Intranets

Product Design

Post-product Design

Product design rationale Process design rationale Causes for problems and failures in product testing

Manufacturability Product testing Root causes for Engineering Changes

Simulations Prototypes Prod. Data Mgmt. Syst. Videoconferencing

Prod. Data Mgmt Syst. Video Conferencing

The same author used Nonaka’s SECI model, in combination with a model for crossdepartment coordination (Adler 1995) to develop a framework to describe IS support for New Product Development in the electronics industry. The framework is depicted in Figure 1.

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Nonaka’s “socialization” knowledge creation mode and Adler’s “teams”- type coordination mechanism requires face-to-face interaction for the transfer of tacit knowledge that is difficult to articulate, communicate, formalize and encode ((Nonaka 1991), (Adler 1995) (Winter 1987), (von Hippel 1994)). Software models of the product under development

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enhance the “externalization” knowledge creation mode by making tacit understandings of specifications explicit. The prototype becomes a source of discussion for “mutual adjustment” coordination mechanisms (Adler 1995) and prevents misunderstandings from perpetuating. The “internalization” knowledge creation mode depends on experimentation with multiple “plans”. Computer simulations help engineers convert explicit knowledge (originating across boundaries) to tacit knowledge with many iterations of “what if” scenarios. Engineers vary parameters and test performance creating new knowledge without the need to build physical models. In the “combination” mode of knowledge creation, Product Data Management Systems (PDMS) represent explicit knowledge, which is objective and easy to encode, and enables its transformation to further explicit knowledge using Adler’s “standards” type of coordination mechanism. Some empirical work has been done on analyzing knowledge management in new

Teams

Socialization VideoConferencing

Mutual Adjustment

Externalisation

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product development processes. Anderson et al. look at the design activity in Rank Xerox and illustrate how collaborative, inter-actional, and organizational ordering are not addressed by the information technology infrastructure in the Design Dept. at Rank Xerox (Anderson, Button et al. 1993). Adler et al. argue for a process-oriented approach to new product development and use a case study of a fictitious company, which represented a composite of a number of companies studied by Adler (Adler, Mandelbaum et al. 1996). He claims that the process oriented approach, which had cross-functional teams as a central element, led to the creation of best practice templates which in turn led to greater efficiencies in product development. Van de Ven and Polley empirically demonstrate how the early stages of product development projects can be accounted for by using principles drawn from chaos theory – providing potential future insight into the front end of new product development efforts that traditionally have proven elusive (van de Ven and Polley 1992). Internalisation

Combination Tacit Knowledge

Prototypes

Plans Simulations

Standards Tacit to Tacit

Tacit to Explicit

Explicit to Tacit

Product Data Management Systems Explicit to Explicit

Explicit Knowledge

Figure 1: IS to support New Product Development (Scott 1996)

The next section will identify and describe some of the KMS challenges encountered by organizations engaged in New Product Development.

3. The KMS challenges faced by NPD processes Todays NPD activities pose interesting challenges for KMS initiatives. This section will describe some of those challenges.

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3.1

Demands for increased productivity in new product development

NPD processes may have short product and process life cycles. These cycles are getting shorter and they are compressing the available time window for recouping the expenses associated with product development. This places a premium on the ability to effectively capture knowledge created during the process so that it can be re-used in the next generation of products to reduce development time. This capture-reuse cycle is a key enabler for productivity improvements in the design phase of product development.

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Figure 2: Rate of Product Development in Electronics (Moore’s Law) Figure 2 shows that the number of transistors per chip doubles every 18 - 24 months. However it has been estimated that productivity2 among electronic design engineers doubles every 36 months (Collett 1998). The competitive pressure to improve productivity and thereby reduce the product development cycle time is huge. Since the challenges associated with capturing and reusing knowledge are, by their nature, knowledge management challenges – this is one of the key KM challenges being posed by NPD. KMS responses to this challenge range from the application of knowledge “codification” systems to knowledge “personalization” systems [Hansen, 1999 #1262].

3.2

Internal knowledge transfer

Today’s NPD organizations need to facilitate knowledge transfer across internal organizational boundaries. The drive to enable this knowledge transfer may stem from any one of a number of factors: the existence of “virtual teams” that are geographically dispersed, the re-organization of NPD activities from a linear to a concurrent model or the need for stronger communication flow between organizational units that had been disconnected heretofore e.g. sales and manufacturing. 3.2.1 Virtual product development teams NPD organizations can be distributed across geographical boundaries. In the case of ADI, there are product development centers in the USA, Ireland, India, and China. The product 2

† Productivity = Dollar Value-add per Unit of Engineering Effort in the U.S. Semiconductor Industry 1986 – 1995. Source: U.S. Census and Bureau of Labor and Statistics

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development activity that spans these centers requires the teams to share their knowledge across team boundaries. It also creates a need for KMS infrastructure to support and promote knowledge sharing. The challenges posed by distributed teams may arise from cultural differences. The appreciation of cultural differences across geographically dispersed teams may be a key factor in the success of those teams. There are at least four ways in which culture influences the behaviours central to knowledge management in virtual product development teams: a) Culture shapes assumptions about what knowledge is and which knowledge is worth managing. Sackman empirically demonstrated four different kinds of cultural knowledge: “dictionary” knowledge, “directory” knowledge, “recipe” knowledge and “axiomatic” knowledge (Sackmann 1992). Hedlund and Nonaka contrasts U.S. and Japanese practices of managing knowledge (Hedlund and Nonaka 1993). The basis for the contrast is the cultural difference between U.S. and Japanese firms. b) Culture defines the relationships between individual and organizational knowledge, determining who is expected to control specific knowledge, as well as who must share it and who can hoard it. This relationship is influenced by what some researchers refer to as the presence of an atmosphere of “care” in a company. “Care” can be characterized by an active empathy, access to help and lenience in judgement. Organizations can foster helping behaviour in their workers by training them in pedagogical skills and intervention techniques. Help can become an element of their performance appraisals

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and talk about how people are helping each other can be encouraged. Von Krogh and Roos stress that knowledge nurturing and creating organizations should be caring organizations (von Krogh and Roos 1996). They are characterized for having a propensity to help, as well as lenience or a capacity to accept errors and for being reciprocal. Altogether, these characteristics give rise to a trustworthy, empathetic and helpful organization culture in which knowledge is the basic aspect. Culture can also promote unique attitudes toward communication and information, which in extreme cases can restrict knowledge transfer to the point of organizational demise as demonstrated by (Brown and Starkey 1994). c) Culture creates the context for social interaction that determines how knowledge will be shared in particular situations. Knowledge that is introduced to an organization is often purchased with cash, but for knowledge that is generated internally, the currency is reciprocity. Davenport and Prusak describe three different roles that workers assume in an organization’s knowledge market economy (Davenport and Prusak 1997): - Buyers in the market are seeking information to solve a complex problem. Buyers will look to people with knowledge and who are willing to share it and will also seek sellers who have exchanged knowledge with them in the past. - Sellers in the market have the information about a product or service that will benefit the buyers. In a market where hoarding knowledge is rewarded, the price for buying knowledge is too high because sellers are unwilling to sell. - Knowledge brokers spend a lot of time gathering their information through various means and channels. Reducing harsh bureaucratic structures and increasing informal communication may empower creativity and innovation by promoting spontaneity, experimentation and freedom of expression (Graham and Pizzo 1996). This culture entails an almost total removal of many of the values that underpinned the reengineering and “right sizing” management culture of the early 1990’s. For example, knowledge cultures value a “fat” middle management layer for professional support and a tolerance for the functional inefficiency that a messy, chaotic creative process implies (Baskerville and Pries-Heje 1998).

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Culture shapes the processes by which the new knowledge with its accompanying uncertainties is created, legitimated, and distributed in organizations. In this context Hayduck developed a framework of organizational practices to foster knowledge sharing that is based on sensitivities to the national culture in which a firm finds itself located (Hayduk 1998). She referenced Hofstede’s work and asserts that his work could be used to identify the dimensions of management that influence the success or failure of knowledge management initiatives. In particular, she referred to Hofstede’s identification of masculinity and individualism as the predominant “dimensions of management” endemic to American culture and describes how these cultural traits place a strong emphasis on the need to fulfill obligations of self-interest and selfactualization. She went on to describe a program of organizational practices - systems, structures and processes, which would help overcome cultural barriers to knowledge management. 3.2.2 Cross-functional collaboration Many NPD projects require cross-functional collaboration. The nature and importance of this collaboration is described by Wheelwright and Clark as follows: “Outstanding product development requires effective action from all of the major functions in the business. From engineering one needs good designs, wellexecuted tests, and high quality-prototypes; from marketing, thoughtful product positioning, solid customer analysis, and well-thought-out product plans; from manufacturing, capable processes, precise cost estimates and skilful pilot production and ramp-up. Great products and processes are achieved when all of these activities fit well together. The firm must develop the capability to achieve integration across the functions in a timely and effective way.” p.165 (Wheelwright and Clark 1992)

The patterns of communication are described in Table 3. The ends of the spectra represent opposites in integration. On the left is a communication pattern that is sparse, infrequent, one-way, and late. One the right, the communication is rich, frequent, reciprocal, and early. This is the preferred mode of communication for NPD organizations because collaborating engineers meet face to face with their colleagues early in the design process

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and share preliminary ideas with sketches, models, and notes. Table 3: Communication between Functional Groups in NPD (Wheelwright and Clark 1992) Dimension of Communication

Range of Choice

Richness of Media

Sparse: documents, computer networks

Rich: face-to-face, models

Frequency

Low: One-shot, batch

High: piece-by-piece, on-line, intensive

Directions

One-way: monologue

Two-way: dialogue

Timing

Late: completed work, ends the process

Early: preliminary, begins the process

3.3

External knowledge transfer

3.3.1 Cross-institutional collaboration Cross-institutional collaboration is also becoming quite common in NPD processes. The need for this type of collaboration arises when organizations seek to collaborate with sources of knowledge, which are external to it. For instance a firm may want to work with an internationally recognized centre-of-excellence in an academic institution with which it has no formal relationship. Cases where NPD teams want to work closely with external standards organizations are also becoming more prevalent. In such cases knowledge has to be combined from participants across multiple collaborating organizations.

3.4

Transient team membership

NPD teams are staffed with people who may possess much sought-after skills and expertise. Consequently there can be high turnover rates in NPD organizations, as firms compete for staff with highly rated R&D experience. The resulting transient existence of teams results in a reduction in organizational knowledge unless there is a repository for knowledge rather than a dependence on knowledge that is solely situated in the minds of individuals. There is also a requirement, however, that some staff turnover should exist for product development teams to be effective. The rate of movement of staff members across organizational boundaries has been shown to have an effect on NPD team output. Katz explored the relationship among the mean tenure of product development teams, the degree of external communication, and performance (Katz 1982). In his study of 50

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product development teams in a large American corporation, he found that initially group performance increased with increasing mean tenure of the group, but this relationship reversed and performance dropped off after five years. The decline in performance was significantly correlated with a decline in external communication and a growth in socalled Not-Invented-Here (NIH) behavior (Brown and Eisenhardt 1995).

3.5

Knowledge to support NPD stage gate processes

A stage-gate process is a conceptual and operational road map for moving a newproduct project from idea to launch (Cooper 1994). What differentiates stage-gate NPD processes from other NPD processes is that decision-making events follow each stage. Gates are meetings where the project undergoes a thorough examination and after which executive management decides whether to incur more R&D expense in the project or not. NPD teams complete a prescribed set of related cross-functional tasks in each stage before obtaining management approval to proceed to the next stage of product development. The gates represent control points where teams’ plans are repeatedly reassessed in the light of the additional information that emerges during the life-cycle of the project. Researchers who have recognized that different phases of the NPD process may demand different KMS requirements include (Adler, Mandelbaum et al. 1996), (Scott 1996), and (Yang and Yu 2002). The diagram in Figure 3 describes a typical NPD stage-gate process and indicates the critical decisions made at the different stages.

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Stage 1

“What should we do?”

Stage 2

Stage 3

“Can we do it?”

40 Stage 4

“How?”

“Just do it?”

Figure 3: NPD Stage-Gate Process (adapted from (Shake 1999)) There has been some attention paid by researchers to the identification of the types of knowledge required by a new product

development activity. Table 4 lists the main contributors and their categorization of NPD knowledge types.

Table 4: Knowledge needed in NPD Processes Researcher (Eder 1989) (Nonaka 1991) (Orlikowski 2000) (Rodgers and Clarkson 1998) (Scott 1996) (Rajagopalan and Subramani 2002) (Ullman 1992) (Vincenti 1990)

Types of NPD Knowledge Prescriptive (know-how), Descriptive (know-that) Explicit and Tacit with four knowledge conversion processes: socialization, externalization, combination and internalization. Knowing the organization, Knowing the players in the game, Knowing how to coordinate across time and space, Knowing how to develop capabilities, Knowing how to innovate Tacit, Explicit, Operative, Substantive, Heuristic, Algorithmic, Deep, Shallow Pre-project, product and process design, manufacturing Agents, Actions, Agency, Context, Purpose, Lessons for the Future General, Domain Specific, Procedural Fundamental Design Concepts, Criteria/Specifications, Theoretical tools, Quantitative/Physical data, Practicalities

The KMS challenge for NPD organizations is to recognize that different types of knowledge are appropriate for different phases of an NPD process. Once this realization has been achieved, the next challenge is concerned with ensuring that the sources of that knowledge are available to the NPD teams at the appropriate milestones in the stage gate process.

4. ADI’s response to KMS challenges in NPD 4.1

A portfolio of KMS applications to address different KM challenges

There are two common applications of IS to support codification and personalization in product development – the use of “codified” design libraries (codification) and the creation of corporate knowledge networks or “yellow pages” (personalization). These approaches are shown in Figure 4. The diagram shows three dimensions. The “explicitness” dimension shows the degree of tacitness vs. explicitness of the knowledge being addressed by a KMS.

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The “reach” dimension shows the range of effectiveness of the knowledge transfer mechanism. The “KMS” dimension shows the scope of the KMS application, ranging from personalization to codification. “Yellow Pages” are shown as spanning the communication space from individuals to groups in an organization. Such systems are not exported outside an organization because of the threat of loss of key individual contributors to competitors. The systems are positioned close to the tacit dimension because they enable people-to-people (tacit) knowledge transfer. “Design libraries” are shown at the other extremes of the diagram. The libraries span the communication space between groups and other organizations because they may be packaged in a format suitable to delivery as intellectual property to either internal groups or external groups (or both). They are close to the explicit dimension because they represent an attempt to codify the knowledge associated with a product i.e. a people-to-documents approach.

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“Meta-knowledge” is located between the two extremes and is focused on intermediation. Intermediation refers to the connection of people to people. It is the brokerage function of bringing together those who seek a certain piece of knowledge with those who are able to provide that piece of knowledge. It is interpersonal focus positions intermediation primarily within the realm of tacit knowledge transfer. It occupies the communication space between individuals and groups in an organization and lies between the tacit and explicit dimensions. Through the use of metaknowledge, the documents become more like databases where search, retrieval, and reuse of text elements (explicit knowledge) are promoted while also giving the reader the opportunity to contact the source of the knowledge so that they may have a dialogue to

enable tacit knowledge transfer (Braa and Sandahl 2000). A conceptual framework showing the relative contribution spaces of EnCore and docK is shown in Figure 4.. The vertical axis describes “knowledge” as it ranges from tacit, at one extremity, through metaknowledge, to explicit knowledge at the other extreme. The horizontal axis describes organizational “reach”, ranging from the individual, at one extremity, through group, organization and ultimately to other organizations. In this context, “reach” is intended to convey the range of applicability of different KMS. The Zaxis describes the spectrum of types of KMS, from personalization through harvesting to codification. The three KMS applications are mapped onto the framework in Figure 4.

Explicit

Knowledge

Tacit

Meta-knowledge

EnCore

docK

Yellow Pages Individual

Group

Organization

Inter-Organization Reach

Personalization Harvesting

Codification

The KMS shown in Figure 4 are: a) “Yellow Pages” are WWW-based systems used to locate employees in an organization based on attributes such as knowledge, affiliations, education, or interests (Carrozza 2000). Where these

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KMS Approach

systems are used, staff profiles are created (either by the staff themselves or by a facilitator). These profiles are structured in a manner that renders them easily searchable and retrievable across the organization. The central goal of the

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“metaknowledge” values on the KMS and knowledge axes respectively. The system may be most effectively used to create opportunities for knowledge flow across internal organization units and hence its location on the “reach” axis.

systems is to enable staff members to easily identify other staff members who share common interests. These types of systems are located close to the ”tacit” and “personalization” extremes of the conceptual framework because they are concerned with enabling direct human-tohuman knowledge exchange. b) “EnCore” is a repository for reusable product development IP. In Figure 4, it is located close to the “codification” and “explicit” values on the KMS and knowledge axes respectively because it is concerned with codified, explicit IP elements. These elements are capable of being reused across the organization or even exported to other organizations (hence its position on the “reach” axis). c) “docK” is a KMS designed to locate and retrieve metaknowledge. It is a catalog with entries describing knowledge creation events in ADI. In Figure 4 it is located close to the “harvesting” and

4.2

Peer reviews as “Knowledge Events” in NPD stage-gate processes

Each of the “gates” in an NPD process represents a peer review with a “go” or “no go” outcome. Since the majority of costs are incurred in the latter stages of a project, and since companies do not want to “spend good money on a bad idea”, the process should include a pause for reviewing all learnings after each stage. The outcome of each gate is a critical decision to either continue or abort the process. This citical decision is illustrated in Figure 5.

100% Risk Risk/Cost

Cost 50%

Critical Decision (Go/No Go)

0% Time Figure 5: Decisions in a Stage Gate Process (adapted from (Shake 1999))

Bergquist, Ljungberg and Snis draw attention to the potential offered by peer reviews as a mechanism for knowledge dissemination (Bergquist, Ljungberg et al. 2001). In particular, they conclude from their analysis of peer reviews in a pharmaceutical company, that the reviews “play an important coordination role in workers’ daily knowledge activities”. Furthermore, the collaborative effort involved in peer reviews has the effect of legitimizing new knowledge by “organizationally sanctioning it and thereby creating a platform for collective sensemaking.”

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4.3

Summary and conclusions

The challenges listed above have a significant effect on key NPD performance metrics and researchers (e.g. (Ramesh and Tiwana 1999), (Macintosh 1997)) are starting to identify the detrimental effects of poor knowledge management on NPD organization performance. Their research concludes that sub-optimum knowledge management in NPD teams can lead to situations where highly-paid workers spend too much time looking for needed information because essential knowhow is available only in the hands of a few employees or else is buried in piles of documents and data. To make matters worse,

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costly NPD errors are repeated due to disregard of previous experiences. Generally, there is an over-reliance on transmitting explicit rather than tacit design knowledge, leading to a lack of shared understanding and constant re-invention of solutions during product

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evolution. Skills that are developed due to collaboration may be lost after project completion because of an inability to transfer existing knowledge into other parts of the organization. The end result is that there is a gradual loss of tacit knowledge to the firm.

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APPENDIX A – KMS Infrastructure Requirements for Virtual Teams a) Distributed Systems Administration: Information Integrity: Site level backup and restore facilities such that each site can be individually backed up and restored. Usage Statistics: Ability to generate site statistics for usage and detect inactive sections of the site. Site Storage Quotas: Ability to set quotas for site storage size and generate automatic notifications for the site owner when a site reaches a certain limit. b) Ease of Use: User Interface: Web-based admin interface, easy to use and post data so that users can maintain access and post content with minimal effort and training Customization: Ability to create personalized views from a pre-defined list of web parts that provide specific functionality. c) Functionality: News: eMail notification to team members when new content has been added or changed. Document Revision Control: Ability to enable version control such that documents under control must be “checkout” and “checked-in” as part of the modification process. Also need to be able to disable this capability by team/project. Issues Tracking: Ability to post and track issues relevant to project team (assignment, priority, description, priority…etc). Check-in/Check-out: Enable users to lock a file while editing, to prevent others from overwriting or editing the file inadvertently. Search: Ability to initiate a structured search on documents, issues, lists and other site content respecting security rights. Templates: Ability to use pre-defined templates/themes to organize team site, maintain consistent look, feel and style Document Workflow: Ability to require route documents through a workflow for electronic approval. Discussion Boards: Users can create threaded discussions specific to the site or specific to a document or piece of content.

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Content Organization: Provide the ability to create folders and subfolders in a document library to organize content. Versioning: Create a backup copy of a file whenever it is checked in or modified. Mgmt Rollups: Ability to rollup & consolidate subteam issues/tasks into higher level consolidated summary. Surveys: Ability to create team specific surveys and automatically collect the results in a structured and organized manner Multi-language support: Ability to communicate in preferred language with international customers Announcements: Ability to post global announcements for individual team sites. Minutes: Ability to create & post minutes for individual projects. d) Integration Address Book Integration: Ability to browse enterprise address book to select users or groups that can access site. Calendaring: Integrate team site events with a common calendar e) Security Access Level Control: Ability to control who can access which information (down to the individual team/project level) So that customers, based on their identity, can view selected or customized NDA level content. Needs to be controls in place so that errors can't be made here! Role based security and Distributed Administration: Project Team areas are self administered with at least Administrator, Read-Only and Contributor Roles. Ability for both customers and firm to post/exchange information: Two-way Collaboration via portal with customers, suppliers or other business partners in a secure way over the Internet. Security standards compliance: Portal need to comply with ADI security issues, without giving up ease of access

References Adler, P. S. (1995). “Interdepartmental Interdependence and Co-ordination: The Case of the Design/Manufacturing Interface.” Organisation Science 6(2): 147-167. Adler, P. S., A. Mandelbaum, et al. (1996). Getting the Most Out of Your Product Development Process. Harvard Business Review: 134-152.

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Anderson, B., G. Button, et al. (1993). Supporting The Design Process Within An Organisational Context. ECSCW'93, Milan. Baskerville, R. and J. Pries-Heje (1998). Managing knowledge capability and maturity. IFIP 8.2 and 8.6 Joint Working Conference on Information Systems, Helsinki. Bergquist, M., J. Ljungberg, et al. (2001). “Practising peer review in organizations: a qualifier for knowledge dissemination and legitimization.” Journal Of Information Technology 16: 99-112. Brown, A. D. and K. Starkey (1994). “The Effect of Organisational Culture on Communication and Information.” Journal of Management Studies 31(6): 808-828. Brown, S. L. and K. M. Eisenhardt (1998). Competing on the Edge: Strategy as Structured Chaos. Boston, Harvard Business Press. Cole, R. E. (1998). “Guest Editor's Introduction to the Spring 1998 special issue on 'Knowledge and the Firm'.” California Management Review. Collett, R. (1998). A Strategic Analysis of the Emerging Market for IP and The Role Of Design Re-Use 1998-2002. Presentation to VSIA Membership. Cooper, R. G. (1994). “Developing New Products On Time, In Time.” Product Innovation Management 11(5). Court, A. W., S. J. Culley, et al. (1997). “The Influence of Information Technology in New Product Development: Observations of an Empirical Study of the Access of Engineering Design Information.” International Journal of Information Management 17(5): 359-375. Davenport, T. and L. Prusak (1997). Working Knowledge. Boston, Harvard Business School Press. Drucker, P. F. (1993). Post Capitalist Society. Oxford, Butterworth Heineman. Eder, W. E. (1989). Information systems for designers. International Conference in Engineering Design. Graham, A. B. and V. G. Pizzo (1996). “A question of balance: case studies in strategic knowledge management.” European Management Journal 14(4): 338-346. Grant, R. (2000). Shifts in the World Economy: The Drivers of Knowledge Management. Knowledge Horizons: The Present and the Promise of Knowledge Management. C. Despres and D. Chauvel. Boston, Butterworth-Heinemann: 27-55.

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Grindley, P. and D. Teece (1997). “Managing intellectual capital: licensing and crosslicensing in semiconductors and electronics".” California Management Review 39 (Winter): 8-41. Hayduk, H. (1998). Organizational Culture Barriers to Knowledge Management. Association for Information Systems Americas Conference. Hedlund, G. and I. Nonaka (1993). Models of Knowledge Management in the West and Japan. Implementing Strategic Process: Change, Learning and Cooperation. P. L. e. al. Oxford, Basil Blackwell: 117-144. Hendriks, P. H. J. and D. J. Vriens (1999). “Knowlege-based Systems and Knowledge Management: Friends of foes ?” Information & Management 35: 113125. Kogut, B. and U. Zander (1992). “Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology.” Organisation Science 3(3): 383-397. Leonard-Barton, D. (1995). Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation. Boston, Harvard Business School Press. Macintosh, A. (1997). “Knowledge Asset Management.” AIring 20: 4-6. Nonaka, I. (1991). “The Knowledge-Creating Company.” Harvard Business Review 69(6): 96-104. Orlikowski, W. J. (2000). “Knowing in Practice: Enacting a Collective Capability in Distributed Organizing.” Organization Science 13(3): 249-273. Quinn, J. B. (1992). Intelligent Enterprise: A Knowledge and Service Based Paradigm for Industry. New York, The Free Press. Rajagopalan, B. and M. Subramani (2002). “Lessons from New Product Development for Managing Knowledge in Software Engineering.” IEEE Software Special Issue on Knowledge Management in Software Engineering(2002). Ramesh, B. and A. Tiwana (1999). “Supporting Collaborative Process Knowledge Management in New Product Development Teams.” Decision Support Systems 27(1-2): 213-235. Rodgers, P. and P. Clarkson (1998). “An Investigation and Review of the Knowledge Needs of Designers in SMEs.” The Design Journal 1(3): 16-29. Sackmann, S. A. (1992). “Cultures and Subcultures: An Analysis of Organisational Knowledge.” Administrative Science Quarterly 37(1): 140-161.

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Schultze, U. (1998). Investigating The Contradictions In Knowledge Management. IFIP. Scott, J. E. (1996). The Role of Information Technology in Organizational Knowledge Creation for New Product Development. Second Americas Conference on Information Systems. Shake, S. (1999). Presentation "Articulating the New Product Development Process". Stewart, T. (1997). Intellectual capital: The new wealth of organisations. New York, NY, Doubleday. Ullman, D. G. (1992). The Mechanical Design Process. New York, McGraw-Hill. van de Ven, A. H. and D. Polley (1992). “Learning While Innovating.” Organisation Science 3(1): 92-116. Vance, D. and J. Enyon (1998). On the Requirements of Knowledge Transfer Using Information Systems: A Schema Whereby Such Transfer Is Enhanced. Association for Information Systems Americas Conference, 1998.

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Vincenti, W. G. (1990). What Engineers Know and How They Know It: Analytical Studies from Aeronautical Engineering. Baltimore, John Hopkins University. von Hippel, E. (1994). “'Sticky Information' and the Locus of Problem Solving: Implications for Innovation.” Management Science 40(4): 429-439. von Krogh, G. and J. Roos, Eds. (1996). Managing Knowledge : Perspectives on Cooperation and Competition. London, Sage. Wheelwright, S. and K. Clark (1992). Revolutionalizing Product Development. New York, Simon and Schuster Inc. Winter, S. G., Ed. (1987). Knowledge and Competence as Strategic Assets. The Competitive Challenge. Yang, J. and L. Yu (2002). “Electronic New Product Development - a conceptual framework.” Industrial Management and Data Systems 4(102): 218-225.

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Issues of Knowledge Management in the Public Sector Xiaoming Cong and Kaushik V. Pandya* University of Luton, UK [email protected] [email protected] *Author for Correspondence Abstract: The new economy not only poses challenges, but also offers opportunities for both private and public sectors alike. To meet the challenges and take the opportunities, government must take active initiatives to adopt new management tools, techniques and philosophies of the private sector and adapt to its circumstance. Knowledge management (KM) is such an area that needs to be further explored and exploited for its full benefits to be reaped. Key issues, challenges, and opportunities of KM in the public sector need to be addressed and better understood Keywords: knowledge sharing, NPM, public sector, strategy

1. Introduction We are living in a world of rapid change driven by globalisation, the knowledge-based economy coupled by ever-fast development of information, communication and technology (ICT). This change, however, not only poses some challenges, but also offers opportunities for both private and public sectors alike. In order to gain competitive advantage for their survival and competence against discontinuous environmental change, most of the large companies in the private sector have been actively taking initiatives to adopt new management tool, techniques and philosophies. Governments always follow suit. History shows that most of the management philosophies were first practiced in the large company (McAdam and Reid 2000). Once they gained foot in the field, then become adopted in the other sectors. Examples include; enterprise resource planning (ERM), business process re-engineering (BPR), and total quality management (TQM). Now comes the turn of KM. KM is no exception. However, decade of practicing in the private companies attests that KM is not just another management fad as some critics claimed. It has passed the fad stage and is here to stay. Therefore it is opportune time for KM to devolve into the public sector. KM has for sometime been at the core of government tasks – inseparable from strategy, planning, consultation and implementation (OECD 2001). However, evidence drawn from the existing literature suggests that public sector is falling behind in these practices. Governments are now realising the importance of KM to its policy-making and service delivery to the public and some of the government departments are beginning to put KM high on its agenda. However, it is not easy to implement, as it seems. The benefits to be reaped from KM will not be handed to

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governments on a plate, nor will the challenges be met without adjustment. Strategies and plans for implementing KM must be carefully thought-out in advance in order to succeed in the attempt and effort. There are concrete issues for government to consider and address. While there are many issues that need to be addressed in the public sector, this paper concentrates on three key issues currently relating to KM.

1.1

Awareness of KM in the public sector

A major component of successful KM practice is raising its awareness not only to managers at all levels, but also to frontline personnel. The concept of KM need to be better understood and benefits much talked about by everyone in the organisation in order for the organisation to be conducive to the KM practices. The concept of KM is nothing new (Hansen et al 1999). Organisations have always used KM practices (in various disguises) to make decisions, and to produce goods and services, though not in a deliberate and systematic manner. Essentially, what is new about KM is the act of being conscious about the existence of a KM process (Sarvary 1999). Organisations that use the KM practices without knowledge and awareness of it will not reap the benefits to its full, if any at all. Deliberately managing knowledge in a systematic and holistic way can increase awareness of benefits to both individuals and organisations. However, it is considered by the authors of this paper that there seems lack of awareness of KM in the public sector. This can be severely hinder to the effective implementation of KM initiatives in organisations in search of increased performance. Therefore, it is vital for an organisation to understand the concept of KM when starting a KM initiative in order to succeed.

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1.2

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Knowledge management In general, data are raw facts. For data to be of value, however, they must be processed (put in a given context) to obtain information, which decision can be made. Knowledge is perceived as meaningful information. The relationship between data, information and knowledge is recursive and depends on the degree of “organisation” and “interpretation”. Data and information are distinguished by their “organisation”, and information and knowledge are differentiated by “interpretation” (Bhatt 2001). So knowledge is neither data nor information. Knowledge is an understanding, and one gains knowledge through experience, reasoning, intuition and learning. Individuals expand their knowledge when others share their knowledge, and one’s knowledge is combined with the knowledge of others to create new knowledge (CIO Council, 2001).

The concept of KM has been in practice for a long time, and mostly in an informal manner. The lack of consensus in defining what is meant by the term has led to major confusion reflected in various studies in the field. Therefore, to understand KM concept, distinctions have to be made first between data, information, and knowledge to clear up confusion on the differences and relationships in this continuum. However, there has been much discussion of the topic in the literature, only simple and concise concepts have been given here. The term “knowledge” is one of the more confusing aspects of KM. The terms “information” and “data” are often used interchangeably with the term “knowledge”. In fact they have different meanings. And understanding the differences is essential to doing knowledge work successfully.

Wisdom

Knowledge

Information

Data

Figure 1: Continuum from data to wisdom. Knowledge is derived from information. It results from making comparisons, identifying consequences, and making connections. Some experts include wisdom and insight in their definitions of knowledge. Wisdom is the utilisation of accumulated knowledge. Knowledge also includes judgement and “rules of thumb” developed over time through trial and error.

values, contextual information, expert insight and grounded intuition that provides an environment of and framework for evaluating and incorporating new experience and information. It originates and is applied in the minds of knowers. In organisations, it is often embedded not only in documents or repositories but also in organisational routines, processes, practices and norms.

Davenport and Prusak (1998) defined knowledge as a fluid mix of framed experience,

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Many formal definition of KM abound in the literature. The definition used by the authors of this paper is: “An ability of an organisation to use its collective knowledge through a process of knowledge generation, sharing and exploitation enabled by technology to achieve its objectives”.

1.3

Types of knowledge: Explicit and tacit

Knowledge in organisations is often classified into two types: explicit and tacit. Explicit knowledge is knowledge that can be captured and written down in documents or databases. Explicit knowledge is formal and systematic, which can be easily communicated and shared (Nonaka 1991). This type of knowledge includes patents, instruction manuals, written procedures, best practices, lessons learned and research findings. It is shared with a high degree of accuracy. Explicit knowledge can be categorised as either structured or unstructured. Structured knowledge is the data or information organised in a particular way for future retrieval. This includes documents, databases, and spreadsheets, etc. In contrast, e-mails, images, training courses, and audio and video selections are examples of unstructured knowledge because the information they contain is not referenced for retrieval. Tacit knowledge is the knowledge that people have in their minds. It is much less ‘concrete’ than explicit knowledge. It is more of an 'unspoken understanding' about something, knowledge that is more difficult to write down. Tacit knowledge can be difficult to access as it is often not known to others. In fact, most people are not aware of the knowledge they themselves possess or of its value to others. Tacit knowledge is considered more valuable because it provides context for people, places, ideas and experiences. It generally requires extensive personal contact and trust to share effectively. Tacit knowledge is highly personal, hard to formalise, and therefore, difficult to communicate to others. As Michael Polanyi (Nonaka 1991) expressed, “We can know more than we can tell”. To give an example, Highway Code provides the explicit knowledge for the driver, but who uses his/her tacit to drive different cars, on different roads, in different countries, and with steering wheel on other side.

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1.4

Managing organisational knowledge

The essence of managing knowledge is concerned with deciding with whom to share, what is to be shared, how it is to be shared, and ultimately sharing and using it. Managing knowledge produces value when shared knowledge is used and reused. Consistent value occurs when there is an atmosphere of trust and motivation for people to share and use knowledge, when there are systematic processes to find and create knowledge, and, when needed, there is technology to store and make knowledge relatively simple to find and share. (CIO Council, 2001) KM involves systematic approaches to find, understand, and use knowledge to achieve organisational objectives. Managing knowledge creates value by reducing the time and expense of trial and error or the reinvention of the wheel (CIO Council, 2001).

1.5

Benefits of KM

There are many benefits to be reaped from KM. For example, foundation knowledge lists 44 generic benefits of KM on its website (Foundation Knowledge 2003). However, only key benefits of KM are addressed in this paper. In an organisational setting, benefits can occur at two level; Individual and organisational. At the individual level, KM provides employees opportunities to enhance skills and experience by working together and sharing other people’s knowledge and learn from each other, thereby improving personal performance, thereby leading to better career development. At the organisational level, KM provides two major benefits for an organisation: 1. Improving the organisation’s performance through increased efficiency, productivity, quality, and innovation. 2. Organisations that manage knowledge claim higher rates of productivity. By having greater access to their employees’ knowledge, organisations make better decisions, streamline processes, reduce re-work, increase innovation, have higher data integrity and greater collaboration (CIO Council, 2001). In other words, for public sector, managing knowledge could reduce the cost of operations and improves customer service 3. Increasing the financial value of the organisation by treating people’s knowledge as an asset similar to

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traditional assets like inventory and capital facilities (U.S. Department of Navy 2001) 4. As knowledge transfer is increasingly recognised as a source of value creation, organisations have come to identify KM initiatives as strategic facilitators of competitive advantages. According to a survey (KM magazine, 2001), an organisation’s main implementation challenge stems from the absence of a “sharing” culture and employees’ lack of understanding KM and the benefits it offers. Organisations can address these challenges by making; training, change management and process redesign primary components of KM initiatives.

2. Comparison of KM in the public and private sector While literature on KM has been addressing issues, challenges and opportunities for the private sector, little has been discussed for the public sector. Programs such as those associated with New Public Management (NPM) suggest that the public organisations should import managerial processes from the private sector, emulating their successful techniques. However, critics of NPM argue that the differences between public and private sectors are so great that business practices cannot be transferred across. Significant differences in human resource management policies and practices, the management of ethical issues and decision processes still exist between the two sectors. However, there is no established body knowledge on successful management strategies in the private sector that can be drawn upon by public agency either (Boyne 2002). Consequently, it is proposed that there is a need of strategy designed especially for the public sector to be developed to fill the gaps and for cross learning.

2.1

NPM and KM in the public sector

More than decades of development of NPM both theoretically and practically in the western world and its tendency to spread to the developing countries has paved the way and laid a solid foundation for KM initiatives to be implemented in the public sector. To better understand the relevance between NPM and KM, a brief introduction of NPM is discussed. NPM offers a set of new ideas and tools for government to run the public sector. Its key idea is the employment of private law contracts in order to provide public services. NPM started in the UK with Premier Thatcher in the

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early 1980s and since spread around the globe in countries like Australia, New Zealand, Finland, Sweden, France and Germany. In the USA another term ‘reinventing’ government is used, but the principles of NPM are applied (Lane 2000). According to Lane (2000), NPM is a general theory about how government can get things done; how government can get services organised and offered to citizens. NPM is not about politics, but about what happens after parliament has decided on the objectives. Its basic claims are that public administration is old fashioned and can be replaced by NPM. What NPM claims is twofold. First, bureaucracy is not the most efficient way to steer the public sector. Second, NPM states that ‘contractualism’ is the answer to the question of what is to be used instead of administrative law and budgetary appropriation. Contracting out by means of tendering/bidding, auction and leasing as new tools of governance for government to reduce costs and increase efficiency is the main characteristic of NPM. Among the advantages are efficiency, more services produced lower costs, and higher contractual transparency. This, at least in part, is in line with benefits offered by KM. But its disadvantages cannot be overlooked. One major disadvantage is that trust has decreased. Political democracy may be negatively affected and transactions costs may increase. This may run counter to KM in which trust is crucial factor in the culture of sharing knowledge. Nonetheless, the NPM experience of different countries, though varied, indicates that the advantages prevail over the disadvantages. The practice of NPM and its increasing acceptance by countries around the globe show that the concept and practice of KM stemming from the private companies can be adopted in the public sector. However, its success or failure will depend on how KM is adapted to the context of the public sector. There are some differences indeed existing between the two sectors as alluded above.

2.2

Importance and need of KM for government

The management of knowledge is of increasing importance for governments in dealing with the challenges created by the knowledge economy. These challenges are addressed in the following aspects (OECD 2003): 1. Knowledge has become a critical determinant of competitiveness for the

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2.

3.

4.

public sector. Service delivery and policy making are the main tasks for government. In a knowledge economy, governments are increasingly facing competition in these areas at both international level and national level. At the international level, for example (OECD 2003), NGOs and governments are in competition with foreign organisations delivering similar service. Research institutes compete to attract the best researchers and funding while universities are increasingly in competition to attract the most investments, the best students and the best professors. At the national level, competition among public bodies is also increased following the decentralisation processes. In the public sector, goods and capital is not as important as in the private sector, but knowledge is. Knowledge is an important element of competition and is a central resource of the government. Effective functioning of government rests on effective acquisition and dissemination of knowledge. Private firms produce goods and services that are increasingly intensive in intangible capital, directly competing with the public sector for the delivery of goods and services such as education, science, security and knowledge. For example (OECD 2001), through distance learning, coaching, information and courses on the Internet, private firm have increasing influence on the public education and training of citizens, which was traditionally offered by the public sector. As customers demand and receive more customisation from knowledge-oriented private firms, they would also expect similar benefits from the public sector. Retirement of civil servants and frequent transfer of knowledge workers across government departments also create new challenges for the retention of knowledge and preservation of institutional memory and the training of new staff. There is also competition for talent with an ability to share knowledge. According to a report (GAO 2001), approximately 71 % of U.S. government’s current employees will be eligible for retirement by 2005. This is not confined to the U.S alone. Most governments are facing the similar problems. It is estimated in Finland, for example, that until 2012 about 85% of the senior civil servants will leave and that nearly half of the civil servants will be leaving in 2001-2011

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(Jussilaninen, 2001). Public organisations need to tweak their KM initiatives now to start retaining the knowledge currently in the heads of these employees. Unless this is done, services to the public will suffer. Thus capturing tacit knowledge and then training the staff is important so that it can be passed on to new staff. Increasingly knowledgeable citizens require governments to be on top of newly created knowledge, as it is increasingly rapidly produced by more differentiated actors. KM is based on the idea that an organisation's most valuable resource is the knowledge of its people. This focus is being driven by the accelerated rate of change in today's organisations and in society as a whole. KM recognises that today nearly all jobs involve 'knowledge work' and so all staff are 'knowledge workers' (Drucker 1993) to some degree or another - meaning that their job depends more on their knowledge than their manual skills. This means that creating, sharing and using knowledge are among the most important activities of nearly every person in every organisation. One of the proper solutions to meet the challenges is to take proactive attitude towards KM practices prevalent in the private sector and adopt and adapt them to the public setting. KM has some potential to actually strengthen government effectiveness and competitiveness in the changing environment. Public sectors and NGOs have to face these challenges and make good use of opportunities offered by globalisation, the knowledge-based economy, and new development of ICT. If it does not, it will mean missing out on opportunities KM offers.

3. Generic KM framework in the public sector 3.1

Need for a generic KM framework for the public sector

Many researchers have proposed a variety of KM frameworks, models, and perspectives to help understand the concept of and conduct KM. Holsapple and Joshi (1999) have made a comparative analysis of key KM frameworks available in the literature and argued that none of these researchers appeared to subsume all of the others as each of them addressed certain KM elements. The authors of this paper leads to propose that there is a need for a more comprehensive and unified framework describing the nature of KM.

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While these frameworks are designed for the private sector, there are few, which are distinctive, for public sector. The public sector is widely accepted as being different from the private sector and has some unique features of its own. A framework for the public sector is different for two reasons: the public sector is ‘stakeholder’ dependent while the private sector is ‘shareholder’ dependent. Stakeholder approach involves multiple parties in the process and it is much more complex to deal with. In the public sector, the stakeholder can be citizens, state and local government, private firms, users, and lobby groups, just to name a few. When governments have to make policy decision and deliver services care and considerations must be taken of the interest of the stakeholders. In the private sector, firms are mainly responsible for their shareholder. Firms must provide shareholders for their returns on investment. Secondly, the private sector is competition based, while the public sector is dependent more on factors such as service delivery, information provision, and knowledge identification, sharing and, utilisation. Due to the survival issue, private firms are in constant vigilance to gain competitive advantage against discontinuous environmental change by adopting new management tool, techniques and philosophies such as KM. There is, however, no such threat in the public sector. In the core public service, organisational change has not traditionally been motivated by product competitiveness. However, traditional public service monopolies, to some extent, are increasingly challenged with the globalisation of information and increased people and capital. Even so, the public sector should focus more on identification, sharing and, utilisation of knowledge. These two main reasons have seriously altered the implementation of KM strategy. Therefore, it is considered that there is a need to develop a generic KM framework for the public sector, by understanding and implementing KM practices.

3.2

Elements to be considered for public sector KM framework

People, processes, and technology are the three key elements of the environment. KM focuses on people and organisational culture to stimulate and nurture the sharing and use of knowledge; on processes or methods to locate, create, capture and share knowledge; and on technology to store and make knowledge accessible and to allow people to work together without being together. People

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are the most important component, because managing knowledge depends upon people’s willingness to share and reuse knowledge. (CIO Council, 2001). 3.2.1 People Getting an organisation’s culture (including values and behaviours) ‘right’ for KM is typically the most important and yet often the most difficult challenge. KM is first and foremost a people issue. The success of KM initiatives depends upon people’s motivation, their willingness, and their ability to share knowledge and use the knowledge of others. People in organisation, processes and technology will at all times be acting as either enablers of, or barriers to, effective KM practices. Barriers need to be identified and removed. Existing enablers also need to be enhanced and additional ones created. This is often where the greatest KM challenges lie The structure of the public sector organisations has traditionally been compartmentalised. ‘Silo’ is probably the best word to describe it. ‘Need to know’ basis is part of public sector culture. ‘Knowledge is power’, ‘what’s in it for me’, and ‘not invented here’ syndrome are typical mindsets of the manager and staff in organisations. In such an environment, information and knowledge are hardly ever shared across different units and different organisational levels. However, people do share knowledge for some reasons such as reciprocity, reputation and prestige, or sometimes just for altruistic reasons. This suggests that knowledge sharing is not a natural act in organisations. It needs a mental model change. To change the attitude and behaviour of the people and reduce barriers, a knowledge sharing culture need to be created. The proposed framework suggests following to bring about necessary change: 1. Raise awareness of benefits of KM. Staff and managers should be aware of the changes and advantages that KM can bring to them and organisation. While they believe that knowledge is power, they must understand that sharing knowledge is power. 2. Build an environment of trust. People tend to share knowledge when they know each other. The level of trust has direct bearing on knowledge sharing. The more trust that exists, the more people are willing to share. 3. Develop leaders who foster sharing, as role model. A champion is needed to KM implementation.

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4.

5.

Establish a formal rewards and recognition system for knowledge sharing. Employees must be rewarded and recognised, not only for sharing their knowledge with others, but also for being willing to use others’ knowledge. This can be done by: 4.1. Acknowledging the contributor of ideas, knowledge, and time by linking this to their semi and annual performance evaluation, promotion, and pay. 4.2. Providing special recognition to volunteers, change agents, and role model and rewarding them. 4.3. Celebrating success stories and propagating tales of savings and contributions in order to gain acceptance among employees and engage them in further participation. 4.4. Making knowledge sharing a job requirement. 4.5. Hiring people with an ability to share knowledge Develop and nurture communities of practice (CoPs). CoPs are knowledge centres of an organisation wherein a group of individuals with similar work responsibilities but who are not part of a formally constituted work team; create, share and use knowledge. CoPs can be a broader means of sharing tacit knowledge. They can be effective in the public sector activities, either on generic or specific basis. To reap rewards from CoPs and sustain them over time, organisations need to nurture them by making resources available to them and by allowing members the opportunity to participate.

3.2.2 Process Drawing KM methodologies from the existing literature, the framework proposes to address issues in relation to the processes and techniques for managing knowledge, the following stages of KM: 1. Identify. Determine core competencies, recognise strategic capabilities and knowledge domains, assess the expertise level for each knowledge domain, and focus on bridging the gap between the existing and needed knowledge. 2. Capture. Attempt to obtain needed knowledge from both inside and outside sources and to formalise and document the obtained knowledge.

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3.

4.

5.

6.

7.

Select. Assess the value of the captured and formalised knowledge and filter it to obtain knowledge that seems appropriate. Store. Classify the filtered knowledge, get it organised in a standard format, add it to the organisational memory, and review and update it periodically. Share. Classify and retrieve knowledge from organisational memory, and make it available for the knowledge users. Apply. Utilise the knowledge in performing the tasks such as solving problems, making decisions, researching ideas, and learning. Create. Discover new knowledge through a variety of processes such as surveys, best practices, research, pilot studies, and data mining.

3.2.3 Technology Technology is employed in all the processes of KM and various technological solutions are already available in the market. The problem is actually a matter of selecting an appropriate technology (Asoh, et al 2002). However, one must bear in mind that technology is just a crucial enabler. It can help connect people with information, and people with each other, but it is not the solution. Along the technology dimension, the framework proposes the following tasks: 1. Identify the appropriate hardware and software for conducting KM and make sure any technology used must fit the organisation's people and processes. 2. Build a technological infrastructure as identified by employees’ needs in knowledge resources and right for the processes. 3. Establish an organisation wide intranet with extensive communicating and collaboration capabilities to share explicit knowledge. 4. Build a knowledge portal, virtual knowledge platform, that is accessible via the organisation wide intranet to share tacit knowledge without being face to face through means such as email, discussion groups, chat rooms, audio and videoconference. 5. Organ and store the knowledge assets in an electronic medium so as to enable efficient and faster access and retrieval. 6. Provide customised access to knowledge resources by pull or push technology to facilitate interaction with citizens, customers, suppliers, partners and others.

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4. Conclusions and further research KM as a discipline is still in its infancy, especially in the public sector, evidenced by little discussion in the current literature. Hence there are still many issues, which are not known. However, governments are realising its importance for running the public sector and starting to practice it. Issues, challenges, and opportunities exist in the process. Public sectors have to face these by taking a proactive attitude and make it happen in order to reap the benefits. To succeed in the attempt, special considerations to lack of awareness, public and private sector difference, and the need for a generic KM framework to be developed must be taken into account. This paper proposes the key issues and initial stages for development of a conceptual KM framework for public sector. A pilot study of KM in the public sector is currently being undertaken, based on which an in-depth research and result will follow. It is considered that this paper will be of interest to the researchers, academics and practitioners of KM, and especially to everyone in public sector.

References Asoh, D., Belardo, B., and Neilson, R. (2002), “KM: Challenges and Opportunities for Government in the New Economy”, Proceedings of the 35th International Conference on System Science. Bhatt, G.D. (2001), “KM in organisations: Examining the Interaction between Technologies, Techniques, and People”, Journal of Knowledge Management, Vol. 5, No.1, pp. 68-75. Boyne, G.A (2002), “Public and Private Management: What’s the Difference?” Journal of Management Studies 39:1 January, pp 97-122. CIO Council, (2001), “Managing Knowledge @ Work, An Overview of Knowledge Management”, Knowledge Management Working Group of the Federal Chief Information Officers Council, August. Davenport, T.H. and Prusak, L. (1998), Working knowledge: How Organisations Manage What They Know. Harvard Business School Press, Boston, Massachusetts, pp 5.

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Drucker, P. F. (1993), Post Capitalist Society, HarperBusiness, pp 6. GAO (2001), “Major Management Challenges and Programm Risks: A Governmentwide Perspective,” General Accounting Officer Report GAO-01-241 of January1. Hansen, M. T., Nohria, N. and Tierney, T. (1999) “What’s Your Strategy for Managing Knowledge”, Harvard Business Review, March-April, pp106-116. Holsapple, C.W., and Joshi, K.D. (1999), “Description and Analysis of Existing Knowledge Management Frameworks”, Proceeding of the 32nd Hawaii International Conference on System Science. Jussilaninen, M. (2001), “Knowledge Management at the Finnish Government”, OECD. Lane, J. E. (2000), The Public Sector Concepts, Models and approaches, Third Edition, Sage Publications, pp 304-305, 315-317. McAdam, R and Reid, R. (2000), “A Comparison of Public and Private Sector Perceptions and Use of Knowledge Management”, Journal of European Industrial Training 24/6, pp 317-329. Nonaka, I (1991), “The Knowledge-Creating Company”, Harvard Business Review, November-December, pp 96-104. Nonaka, I. and Takeuchi, H. (1995) The Knowledge-Creating Company, Oxford University Press, Oxford, pp vi, 225. OECD, (2001), “Knowledge Management: Learning-by-Comparing Experiences from Private Firms and Public Organisations”, Summary Record of the High Level Forum held in Copenhagen, 8-9 Feb. 2001, PUMA/HRM (2001) 3, CERI/CD (2001)2. OECD, (2003) “Conclusions from the Results of the Survey of Knowledge Management Practices for Ministries/Departments/Agencies of Central Government in OECD Member Countries”, February 3-4,2003, GOV/PUMA/HRM(2003)2 Sarvary, M. (1999), “Knowledge Management and Competition in the Consulting Industry”, California Management Review, Vol. 41, No.2, pp 95-107. The State of Knowledge Management, KM Magazine, May 2001. U.S. Department of the Navy, (2001), “Metrics Guide for KM Initiatives”, Version 1.0, Draft 9 May 2001.

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The Impact of Question Structure when Sharing Knowledge Heather Bircham University of Waikato, New Zealand [email protected] Abstract: This paper investigates how the structure of a question may hinder or assist in the knowledge sharing process. It presents a theoretical framework that posits the notion that the structure of the question asked of the source may have an effect on the recipient’s attitude toward the knowledge received. Question structure is examined from the perspective of knowledge articulation and attitude toward the knowledge received is considered from the position of relevance and value of the knowledge to the recipient’s decision-making processes. Keywords: Knowledge sharing; question structure

1. Introduction Perhaps the most perplexing aspect of knowledge in the business context is that it originates from individuals, but is realised in products or services promoted by organisations. In a business environment where the knowledge of an organisation is regarded by many as a resource that gives rise to competitive advantage (McEvily & Chakravarthy 2002; Spender & Grant 1996), it is reasonable to suggest that an organisation should exploit the knowledge of its employees. However, before the knowledge of individuals can be combined, utilised and/or exploited by the organisation it first must be articulated by those that possess it, shared and then transferred within the firm (Lubit 2001). Research into knowledge sharing and transfer at the unit level of the individual in an organisation is relatively underdeveloped, yet almost every day companies request their employees to share their knowledge on organisational matters. This sharing can occur through emails, reports, meetings, compliance and self-assessment surveys, audits, information and knowledge warehouses searches, etc. A number of recent studies suggest factors that can affect knowledge sharing and transfer in an organisation, including knowledge tacitness (Argote & Ingram 2000; McEvily, et al. 2002; Simonin 1999), internal stickiness of knowledge (Szulanski 1996), motivation for sharing (Kalling 2003), the ability of the source to share (Foss & Pedersen 2002) and the ability of the recipient to accept knowledge (Gupta & Govindarajan 2000). In general these studies have focused on the transfer process and the types of knowledge being transferred (tacit, explicit), with the a priori assumption being that individuals will share their knowledge. However, key to an individual sharing their knowledge is that the individual must first receive a stimulus or invitation to share, such as a chance remark, formal question or organisational requirement.

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Some consider that the asking of questions is the key to revealing and sharing new knowledge (Lloyd 2002, p 11) and that question formulation is an important component of the management of organisational knowledge (Meso, Troutt & Rudnicka 2002). More broadly, question structure (e.g. open or closed) has been found to influence a respondent’s answer and also the usability of the response (Dohrenwend 1965). If this is so, then there is the possibility that question structure may impact on the knowledge sharing process between a source and a recipient in an organisation. Furthermore, often the questions that are asked to gather organisational knowledge are presented to employees in a formal written format, such as those often found in compliance and self-assessment surveys or audit questionnaires, rather than interview style questions. In such circumstances, the structure of a question may affect the response and therefore, when attempting to glean knowledge on an organisational topic, irrespective of the subject matter, the question can be posed: “Does the structure of a question to which the source of the knowledge responds influence the recipient’s attitude toward the knowledge they receive?” This paper examines the proposed question and is organised as follows. The next section provides an overview of research on knowledge sharing and questioning, including factors that may inhibit individuals from sharing their knowledge or receiving the knowledge of others. The theoretical framework is then outlined, followed by a discussion of the possible implications of the framework for knowledge sharing in organisations. The paper concludes with a brief synopsis for future research directions.

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2. Background literature 2.1

Knowledge sharing and attitude

Sharing of knowledge between individuals in an organisation can occur both informally and formally, one on one or in a group situation. Informal knowledge exchange can take place either in response to a chance remark in the corridor or in the tearoom for example, or in response to a direct question. The individual who holds the knowledge either responds by sharing their knowledge or aspects of their knowledge or chooses not to respond. More formal knowledge exchange resides in organisational manuals, document warehouses, reports, emails and correspondence between employees and takes place in formal meetings, seminars and presentations, etc. When knowledge sharing occurs between two individuals, the individual whom is the source of the knowledge shares their knowledge with the recipient. The process of sharing has the presupposition that the recipient may or may not use the received knowledge. Yet, if the recipient makes use of the received knowledge, by way of incorporating it into a new product, process or even just simply making a decision, knowledge transfer is said to have occurred (Darr & Kurtzberg 2000). Knowledge transfer therefore is predicated on knowledge sharing; sharing has to occur prior to transfer. On the presumption that an individual in an organisation has been presented with a reason to articulate and share their knowledge, research suggests that there are clusters of factors that may affect knowledge sharing (Andrews & Delahaye 2000). These include the reluctance, willingness or even ability (Foss, et al. 2002) of the individual to share, the motivational disposition of the individual (Gupta, et al. 2000) and trust towards the recipient party (Andrews, et al. 2000; Davenport & Prusak 1998; Huemer, von Krogh & Roos 1998; McDermott & O'Dell 2001; McEvily, Perrone & Zaheer 2003). A source’s perceived trust in a recipient may also impact on the degree of openness they have towards sharing (Nahapiet & Ghoshal 1998). Further, if the source considers that their knowledge, if shared, is favourable to the organisation, this may foster the notion that retention of knowledge enhances bargaining power, through knowledge ownership and control (Davenport, et al. 1998). In some circumstances this may be related to the

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perceived value of the knowledge being shared (Gupta, et al. 2000). A contrasting perspective suggests game theory can be used to understand knowledge sharing behaviour (Chua 2003). For example, an individual’s perceived payoff for sharing their knowledge maybe contingent on the knowledge sharing behaviour of others in the organisation; if you share I will share, but it you do not share then I will not share. The relevance of game theory to organisational culture and climate can be debated, but there can be little doubt that organisational culture and climate can encourage or impede knowledge sharing. For example, if the source individual perceives the organisation climate to be one where mistakes are not well received and the required knowledge to be shared is about failures of projects or mistakes, then attitude toward sharing this type of knowledge may be negative (Husted & Michailova 2002). In the same way that the source of knowledge may have an attitude towards sharing their knowledge, a recipient may also have an attitude towards the knowledge they receive. Although the attitude of the recipient has not been examined in detail in the literature, it has been suggested that the recipient may form an attitude towards receiving knowledge from others given their current situation and perception of the sharing individual (Husted, et al. 2002). Some suggest that the more valuable the knowledge the more likely it is that the recipient will use it (Gupta, et al. 2000), but the value of the knowledge to the recipient may also depend upon the relevance of the knowledge to the decision-making requirements of the recipient (Schulz 2003). Knowledge that adds to that required by a recipient for their organisational duties and decision-making may be perceived to have more value than knowledge that does not contribute to their job domain. There also remains the aptitude of the recipient and whether or not he or she is willing to accept knowledge, irrespective of the relevance of the knowledge to their organisational decision-making requirements. The absorptive capacity of the recipient and the extent and depth of their prior understanding of the area of knowledge being shared may affect their ability to accept and comprehend the knowledge being provided (Cohen & Levinthal 1990). Further, beliefs such as the not-invented here syndrome (Katz & Allen 1982) may also result in the recipient being not willing to accept knowledge. The recipient of knowledge may also have a

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perception of the trustworthiness of the source, in the same way that the source of knowledge may or may not trust the recipient. That is, perceived trustworthiness may have some bearing on whether or not the recipient perceives they are receiving accurate, quality knowledge from the source. Irrefutably, research is revealing the significance and importance of the attitude of the source and recipient in knowledge sharing in an organisation. However, there is no exact indication of what individual beliefs constitute an attitude towards sharing or an attitude towards accepting knowledge. Nor does the knowledge management literature allude to how the attitude of the source or recipient can be operationalised. In an endeavour to clarify the effects of a source’s attitude to knowledge sharing and a recipient’s attitude to receiving knowledge, a brief consideration of the theory of reasoned action is appropriate. The theory of reasoned action (Fishbein & Ajzen 1975) has been used to assist in the prediction of the behaviour of an individual in contexts or circumstances similar to those of knowledge sharing or knowledge acceptance. Its fundamental and underpinning premise is that a person’s attitude is strongly based upon their beliefs about performing a particular behavioural act. If this theory is applicable to knowledge sharing then the attitude of an individual towards performing a behavioural act such as sharing knowledge, for example, could be expected to affect their intention to carry out that behaviour, to share their knowledge; intention both precedes and is predictive of actual behaviour. The theory also proposes that subjective norms or an individual’s beliefs about how peers consider that he or she should behave will influence intention and consequently behaviour. In the context of knowledge sharing, the theory of reasoned action has been examined in two studies (Bock & Kim 2002; Ryu, Hee Ho & Han 2003). The first (Bock, et al. 2002), used the theory of reasoned action model to examine beliefs, attitude and intention to share against actual knowledge sharing behaviour. Results found that actual knowledge sharing behaviour was highly correlated with intention to share knowledge and attitude toward sharing had a significant effect on intention. The second study presented a modified model of the theory (Ryu, et al. 2003) and found that subjective norms had the greatest effect on intention, both indirectly and directly through attitude. Although Ryu et al., (2003) included subjective

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norms which could be used as a proxy for an individual’s perception of the organisational climate towards sharing, both studies failed to consider the belief of many that trust towards the recipient party may impact on knowledge sharing (Andrews, et al. 2000; Davenport, et al. 1998; Huemer, et al. 1998; McDermott, et al. 2001; McEvily, et al. 2003). Further, neither the findings from the studies, nor the theory of reasoned action provide insight into what triggers an individual into sharing their knowledge. That is, individuals have no need to volunteer their knowledge unless asked to.

2.2

Questioning and question structure

The findings of Okhuysen and Eisenhardt (2002) suggest that asking individuals to question one another on their knowledge is more productive to new knowledge generation than just asking them to share their knowledge. Everyday individuals in an organisation are questioned about their knowledge of a domain of expertise etc. Responding to such questions may involve individuals searching for explicit and already documented organisational knowledge, inquiring of their internal knowledge domain and or, cognitively integrating knowledge from a number of different sources in an attempt to discover and articulate a reply. And, all too often neither the question nor the articulated response is communicated in face-to-face conversation; but in the form of a memo, request for a report, compliance or selfassessment survey or response, etc, where the structure of the question has the potential to influence the response. Open-ended and closed questions implicitly have different presumptions with respect to knowledge extraction (Vinten 1995). Underpinning open-ended questions is the assumption by the questioner that the respondent (the source), has an extent and depth of knowledge about the topic and can therefore respond appropriately. Further, a respondent may perceive that they have more control over an open-ended than a closed question as they can choose how they will respond by articulating and sharing variable amounts of knowledge. Although the openended question appears to allow for more scope and potential value to be extracted from the response since it permits almost unlimited knowledge to be provided by the source, openended question do not always possess an advantage of depth in response over questions of a closed structure (Dohrenwend 1965). For example, if a questioner is attempting to elicit

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predefined specific attitudes, then closed questions where the respondent may only select from fixed options may provide greater depth to the questioner; open questions may fail to properly direct the respondent to articulate their attitudes in the response. Closed questions on the other hand, implicitly assume that the questioner is already in possession of substantial information about the responding individual’s knowledge (Vinten 1995). In the context of sharing knowledge in an organisation, this implies that the recipient is already knowledgeable on the question subject matter. For example, the response to a closed question with an answer format of “yes” or “no” may only be intended to confirm that which the recipient already knows. Closed questions also allow the questioner to control the context of the response (Knippen & Green 1999), potentially focusing responses towards the knowledge and decision-making domain of the recipient. However, although closed question structures are considered to be easier to respond to (Foddy 1993), there remains the issue: “Do closed structure questions provide the respondent or the source of knowledge sufficient scope to articulate their knowledge to the extent to which they choose to share.” Schuman & Presser (1979) found that openended and closed types of questions of the same question content elicited two quite different responses, with answers to closed questions being influenced by the choices presented, whilst responses to open versions of the same question differed between respondents. If so, this difference in response has the potential to impact on the attitude that a recipient has towards the response. Anecdotal evidence from self-assessment surveys suggests that when respondents to closed questions are confronted with response options that do not conform to their knowledge and experience domains, they will select the option that has the least future impact upon

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them (Bircham 2003). For example, by responding affirmatively to a question to confirm compliance on an organisational issue the respondent may prevent further questioning. However, a non-affirmative response and thus non-compliance may result in the respondent being asked to explain why and clarification may not be the desire of the respondent. This brief review of the literature provides a basis for a theoretical framework for the articulation of knowledge in an organisational context, where the sharing of knowledge cannot realistically be achieved through chance remarks or opportunistic questions in tearoom or corridor interactions. In this context, large multi-layered and often disaggregated organisations, a structured and formal process is required, which in turn requires emphasis upon knowledge sharing using formal written rather than interview-style questions. In view of the fact that question structure is important it is appropriate to ask what impact question structure may have on the way that knowledge is shared in an organisation, and furthermore, how the structure of a question may impact a recipient’s attitude towards the knowledge they receive.

3. Theoretical framework The proposed framework is predicated upon the existence of a relationship between the articulation of an individual’s knowledge and the attitude a recipient has towards the knowledge received. Three main constructs are derived from the literature: question structure; the recipient’s attitude towards the knowledge received; and the source individual’s attitude towards sharing their knowledge. The relationships between these constructs are represented in the theoretical framework (Figure 1).

Question Structure

Attitude towards Knowledge Received (Recipient)

Attitude towards Sharing Knowledge (Source)

Figure 1: Theoretical Framework

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The principal relationship is between the structure of the question asked and the impact this may have on a recipient’s attitude towards the knowledge they receive. The framework proposes that this is potentially moderated by the attitude the source of knowledge may possess towards sharing their knowledge. Although the framework requires the source to have shared their knowledge, the quality of what the source shares may vary for example, with circumstance, environment, associations, and whether or not the recipient of the knowledge is known to the source. The two attitudinal constructs in the theoretical framework, that of the source and that of the recipient are independent of each other. The framework proposes that when the individual who is a potential source of knowledge is presented with a question of a certain structure (e.g. closed, open-ended) to which they respond with their knowledge, then the structure of the question and the corresponding response will have an effect on the recipient’s attitude towards the knowledge received. For example, if the source is confined to responding only to a closed ended question they may not be able to articulate all their knowledge and subsequently the response may not be complete. This incompleteness may result in a less than favourable attitude of the recipient towards the response since the response may not add value to the recipient’s knowledge domain and or, organisational decision-making requirements. In contrast, if a recipient receives a response that is underpinned by an open structured question the attitude of the recipient may vary. Without attempting to measure the behavioural act of the recipient using the newly acquired knowledge, as this would result in knowledge transfer rather than knowledge sharing, the framework proposes that a recipient can have an attitude toward the knowledge they receive. That is, the shared knowledge may be cognitively processed but not necessarily used until later, at a point in time when it is relevant and valuable to the recipient. Using the constructs of beliefs and attitude presented in the theory of reasoned action, an individual’s attitude is said to be strongly correlated with their beliefs. Therefore, as suggested in the literature, a recipient’s beliefs of perceived trustworthiness of the source (McEvily, et al. 2003) and the not-invented-here syndrome (Katz, et al. 1982) may assist understanding when examining attitude towards knowledge received. Further, since subjective norms are

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also considered to influence attitude (Ryu, et al. 2003), a recipient’s perception of the prevailing organisational climate or the opinions of peers towards accepting the knowledge may also be significant. Although the theoretical framework is underpinned by the a priori assumption that the recipient is already in possession of the knowledge and therefore the source has shared their knowledge, the attitude of the source towards sharing their knowledge is relevant and of importance. If the implicit suggestion in the knowledge literature that attitude factors and or, behavioural beliefs affect the quality or quantity of knowledge that the individual shares, then the act of sharing knowledge is in all likelihood subject to the source individual’s attitude towards sharing their knowledge. Attitude towards sharing knowledge is influenced by behavioural beliefs such as the perceived trustworthiness of the source (Andrews, et al. 2000; McEvily, et al. 2003), will they act with integrity etc. Further, subjective norms such as the prevailing organisational climate towards sharing (Sveiby & Simons 2002) may also affect an individual’s attitude towards sharing. The theoretical framework proposed has support from the literature, but lays no claim to have included all possible factors or behavioural beliefs that may affect the source sharing or recipient accepting knowledge. Nonetheless, the framework provides a basis for both empirical research and further theoretical analysis.

4. Implications for the organisation It is obvious that knowledge has to be shared in an organisation since no one individual can possess all knowledge. However, often the formal channels that are used to extract knowledge in organisations, such as reports, compliance, self-assessment and audit surveys fail to meet the expectations of those that commission them. Whilst some knowledge is extracted and shared, frequently the value of the responses to the recipient is less than that expected, making the recommendations or decisions the recipient is required to make difficult. Perhaps the wrong questions are being asked or maybe the structure of the questions limits the extent and depth of the responses. The framework presented in this paper highlights a number of key issues that are relevant to organisations that wish enhance knowledge sharing amongst employees; and

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there can be little doubt that question structure is both significant and important. The use of closed questions (yes-no format) in audit and compliance surveys is a relatively straightforward way of collecting knowledge from large numbers of employees. But this format makes no provision for the situation where the correct and accurate response is neither “yes” nor “no”; and the respondent is faced with having to make a choice when neither response option is really applicable. All too often the option chosen reflects the respondent’s perception of what the recipient expects, or what they perceive will have least future impact on them. The ramifications to organisational decision-making processes are self-evident. Not only has the knowledge sharing process been inhibited by the structure of the question asked, the recipients of the knowledge and the organisational decisionmakers do not know that their knowledge is incomplete or of suspect value. The attitudes and beliefs of both the employees that respond to the questions and those that receive the responses are also significant. If there is any disparity of trust between the two individuals then it is possible that the quality of what is shared and the willingness to accept the shared knowledge may also impede the knowledge sharing process and potentially impact organisational decision-making. Even when the source shares their knowledge, senior management may not be willing to accept knowledge they do not understand, or knowledge that they have not developed themselves. In an environment where knowledge of employees maybe key to sustainability, the challenge for organisations will be to assist employees to overcome such problems. Such a change is not only directed at the individual level, it must also be supported by the values of an organisation; does the culture promote knowledge sharing? Organisational decision-makers are often faced with having to make non-programmed rather than programmed decisions. Whereas programmed decisions tend to follow established routines and guidelines and have the implicit assumption of continuity of environment (Senge 1990), non-programmed decisions require a response to an unpredictable or discontinuous environment where knowledge for decision-making is often incomplete. All too often, those that have the required knowledge are not asked to articulate their knowledge because the decision-makers

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do not have the leadership skill of asking questions (Foster & Kaplan 2001). “Knowledge… is of little value if not supplied to the right people at the right time” (Teece 2000, p 38).

5. Conclusion For many, the imperative that knowledge be shared is just plain commonsense in any organisational context. However, before an organisation can acquire new knowledge, it first must be articulated into a form that can be cognitively processed by others, a process that is often initiated by a chance question or remark. If, however, the prompt for the articulation and sharing of knowledge is initiated with a formal question, then the brief survey of the literature reported in this paper gives credence to the view that the structure of the question may impact both the response and the attitude of the recipient towards the knowledge received. The inclusion of the attitudes of both the source and recipient of knowledge in the proposed framework is supported by empirical research into the validity and or applicability of the theory of reasoned action, which maintains that performing a behavioural act can be predicted by intention, pre-empted by attitude and beliefs. Then, from the perspective of the source of knowledge, beliefs surrounding trustworthiness and their perceptions of the prevailing organisational climate may influence attitude towards sharing knowledge given an organisational context. Further, the attitude of a recipient towards accepting knowledge may be strongly related to the beliefs, as described by their perception of the trustworthiness of the source of the knowledge, the relevance and value of the knowledge to their decisionmaking domain and their perception of the prevailing organisational climate to knowledge sharing inclusive of the not-invented here syndrome. The proposed framework is not without its limitations. It does not allow, for example, for the circumstance where the source and recipient have reciprocity and can question each other to obtain clarification on knowledge already shared. Opportunities for reciprocity include face-to-face interviewing or discussion where the recipient can question the source for further knowledge and vice-versa, or email communication over a period of time, etc. However, not all knowledge sharing scenarios have such reciprocity opportunity. Responses to formal requests for a report or compliance, self-assessment or audit questionnaires often

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only allow for knowledge to move in one direction, from the source to the recipient. If the questions comprising such questionnaires are not structured in a way that facilitates the sharing of knowledge by the source of the knowledge, then the quality and quantity of knowledge shared may not meet the expectations of the recipient thus impacting their attitude towards the knowledge received. As organisations become increasingly more global in their focus and outlook, disaggregated and operating in a number of different time zones, the requirement for more structured approaches to knowledge sharing and extraction could well increase. At the same time the opportunities for the chance question or remark to initiate the articulation process are likely to diminish even with increased audiovideo communication, primarily because such communication tends to be structured and not unstructured. But overriding the above is the need for the right person to be asked the right question at the right time to extract the knowledge that is required for decision-making and strategy formulation in today’s era of discontinuity engendered by globalisation. This cannot be left to opportunistic chance and question structure is a key element in sharing and transferring knowledge within an organisation to improve the prospects of knowledge-based competitive advantage.

6. Acknowledgements This research was funded in part by The Foundation of Research Science and Technology, New Zealand.

References Andrews, K. M. & Delahaye, B. L. (2000) "Influences on knowledge processes in organizational learning: The psychological filter", Journal of Management Studies, Vol 37, No.6, pp797-810. Argote, L. & Ingram, P. (2000) "Knowledge transfer: A basis for competitive advantage in firms", Organizational Behavior and Human Decision Processes, Vol 82, No.1, pp150-169. Bircham, J. (2003) "Personal Communication Discussion about the results from an organisational compliance survey", Melbourne, Australia. Bock, G. W. & Kim, Y.-G. (2002) "Breaking the myths of rewards: An exploratory study of attitudes about knowledge sharing", Information Resources Management Journal, Vol 15, No.2, pp14-22.

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Chua, A. (2003) "Knowledge sharing: A game people play", Aslib Proceedings, Vol 55, No.3, pp117-129. Cohen, W. M. & Levinthal, D. A. (1990) "Absorptive capacity: A new perspective on learning and innovation", Administrative Science Quarterly, Vol 35, pp128-152. Darr, E. D. & Kurtzberg, T. R. (2000) "An investigation of partner similarity dimensions on knowledge transfer", Organizational Behavior and Human Decision Processes, Vol 82, No.1, pp2844. Davenport, T. & Prusak, L. (1998) Working knowledge - How organisations manage what they know, Harvard Business School Press, Boston, MA. Dohrenwend, B. S. (1965) "Some effects of open and closed questions on respondents' answers", Human Organization, Vol 24, No.2, pp175-184. Fishbein, M. & Ajzen, I. (1975) Beliefs, Attitude, Intention and Behaviour: An Introduction to Theory and Research, Addison-Wesley Publishing Company, Philippines. Foddy, W. (1993) Constructing questions for interviews and questionnaires: Theory and practice in social research, Cambridge University Press, Foss, N. J. & Pedersen, T. (2002) "Transferring knowledge in MNCs: The role of sources of subsidiary knowledge and organisational context", Journal of International Management, Vol 8, pp4967. Foster, R. & Kaplan, S. (2001) Creative Destruction, Double Day, New York. Gupta, A. K. & Govindarajan, V. (2000) "Knowledge flows within multinational corporations", Strategic Management Journal, Vol 21, pp473-496. Huemer, L., von Krogh, G. & Roos, J. (1998) "Knowledge and the concept of trust", in G. von Krogh, J. Roos and D. Kleine, Knowing in firms: Understanding, managing and measuring knowledge, SAGE Publications, London. Husted, K. & Michailova, S. (2002) "Diagnosing and fighting knowledgesharing hostility", Organizational Dynamics, Vol 31, No.1, pp60-73. Kalling, T. (2003) "Organization-internal transfer of knowledge and the role of motivation: A qualitative case study", Knowledge and Process Management, Vol 10, No.2, pp115-126. Katz, R. & Allen, T. J. (1982) "Investigating the not invented here (NIH) syndrome: A look

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at the performance, tenure, and communication patterns of 50 R&D project groups", R&D Management, Vol 12, No.1, pp7-19. Knippen, J. T. & Green, T. B. (1999) "Clarifying communication", Journal of Workplace Learning, Vol 11, No.5, pp161-163. Lloyd, B. (2002) "Leadership and knowledge management", Leadership & Organization Development Journal, Vol 23, No.5, pp11. Lubit, R. (2001) "Tacit knowledge and knowledge management: The keys to sustainable competitive advantage", Organizational Dynamics, Vol 29, No.4, pp164-178. McDermott, R. & O'Dell, C. (2001) "Overcoming cultural barriers to sharing knowledge", Journal of Knowledge Management, Vol 5, No.1, pp76-85. McEvily, B., Perrone, V. & Zaheer, A. (2003) "Trust as an organizing principle", Organization Science, Vol 14, No.1, pp91103. McEvily, S. & Chakravarthy, B. (2002) "The persistence of knowledge-based advantage: An empirical test for product performance and technological knowledge", Strategic Management Journal, Vol 23, pp285-305. Meso, P., Troutt, M., D & Rudnicka, J. (2002) "A review of naturalistic decision making research with implications for knowledge management", Journal of Knowledge Management, Vol 6, No.1, pp63-73. Nahapiet, J. & Ghoshal, S. (1998) "Social capital, intellectual capital, and the organizational advantage", Academy of Management Review, Vol 23, No.2, pp242-266. Okhuysen, G. A. & Eisenhardt, K. M. (2002) "Integrating knowledge is groups: How formal interventions enable flexibility",

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Organization Science, Vol 13, No.4, pp379-386. Ryu, S., Hee Ho, S. & Han, I. (2003) "Knowledge sharing behavior of physicians in hospitals", Expert Systems with Applications, Vol 25, pp113-122. Schulz, M. (2003) "Pathways of relevance: Exploring inflows of knowledge into subunits of multinational corporations", Organization Science, Vol 14, No.4, pp440-459. Schuman, H. & Presser, S. (1979) "The open and closed question", American Sociological Review, Vol 44, pp692-712. Senge, P. (1990) The fifth discipline, Random House, Sydney, Australia. Simonin, B. L. (1999) "Ambiguity and the process of knowledge transfer in strategic alliances", Strategic Management Journal, Vol 20, pp595-623. Spender, J.-C. & Grant, R. (1996) "Knowledge and the firm: Overview", Strategic Management Journal, Vol 17, No.Winter Special Issue, pp5-9. Sveiby, K.-E. & Simons, R. (2002) "Collaborative climate and effectiveness of knowledge work - an empirical study", Journal of Knowledge Management, Vol 6, No.5, pp420-433. Szulanski, G. (1996) "Exploring internal stickiness: impediments to the transfer of best practice within the firm", Strategic Management Journal, Vol 17, No.Winter Special Issue, pp27-43. Teece, D. J. (2000) "Strategies for managing knowledge assets: The role of firm structure and industrial content", Long Range Planning, Vol 33, pp35-54. Vinten, G. (1995) "Open versus closed questions - an open issue?" Management Decision, Vol 33, No.4, pp27-31.

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Special Languages and Shared Knowledge Rafif Al-Sayed and Khurshid Ahmad University of Surrey, Guildford, UK [email protected] [email protected] Abstract: The transfer of knowledge between groups of individuals of different levels of expertise and orientation is

discussed with reference to the manner in which knowledge is disseminated using the specialist language of a given domain. A prototype system that allows access to knowledge at these different levels, through the automatic construction of keyword indexes, is outlined. The controversial relationship between knowledge and language is the basis of arguments in this paper. Keywords: Knowledge management, knowledge sharing, knowledge diffusion, best practice, terminology management, health care.

1. Introduction The transfer of knowledge within an organisation, across organisations, between an individual and an organisation, and between individuals is facilitated through a number of sign systems. Such systems include natural languages, mathematical equations, subject specific notations, and other conventions including graphical conventions. The term facilitation is a broad term, however, the key to facilitation is a common consensus on the meanings of words of natural language, kinds of mathematical equations, and agreement on notations and conventions. So, in some respects, the transfer of knowledge requires a consensus amongst organisations and individuals. Much knowledge management literature has focused on the “sharing” of know-how and expertise through protocols devised by managers (Nonaka and Takeuchi 1995, Davenport and Probst 2002) or the focussed discussion of problems related to the sociology of organisations (Scarbrough 1996). Some have even looked at this problem from a cybernetic point of view in terms of feedback and control systems (Morgan 1996). Management Studies, sociology, and cybernetic models address fairly high-level conceptual issues. However, the surface form of knowledge, the trace of knowledge left behind on a document, whether paper or electronic, is amongst the few discernible forms of knowledge. We will focus on how this trace is transferred. The long-standing controversy about the relationship between knowledge and language (see Baker and Hacker on Wittgenstein 1988) notwithstanding, it is almost universally true that the development of a subject or the development of a subdomain within a subject discipline invariably leads to the appropriation of certain words from the everyday natural

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languages of the emergent subject or subdomain workers. Words are given specialist interpretation; words like energy, mass and force existed in the English language prior to Isaac Newton. However after Newton propounded his theory relating to the material nature of being, these three words assumed a more specialist meaning and spawned a whole new discipline, i.e physics. Physicists, initially called natural philosophers, started discussing different kinds of forces, different sources of energy and problems relating to the metrication and instrumentation of quantities related to energy, mass and force. No journal of physics, standard textbooks or encyclopaedias of physics will accept an alternative term for these concepts. There is no obvious coercion but there is a consensus. The consensus is brought about partly through patronage, for instance having a degree in physics will allow one to write a doctoral dissertation or indeed obtain a job in various physics establishments but one has to speak and write in the specialist language of physics. Much the same is true of other disciplines. We mentioned the development of subdomains within a specialism. Sometimes the subdomain relates specifically to the application of principles and empirical results related to the parent domain. In our times, gene therapy is a good example of such a transfer. Starting from the rather abstract concept of the molecular basis of animal or plant life, originally a theoretical and experimental enterprise variously called biochemistry and molecular biology, one sees the development of industrial methods and instrumentation for extracting and harvesting so-called genetic material – an enterprise now called genetic engineering. From genetic engineering the notion developed that some genetic material can malfunction giving rise to sickness of various organs within an organism; by replacing the defective genetic material, the organ will recover - hence gene therapy. Each ©Academic Conferences Limited 2003

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of these different subjects i.e. nuclear biology and gene therapy has its own vocabulary and, indeed, writing styles for the discussion of theories and the reportage of experimental results. Consensus relating to terminology, and elements of other sign systems, is used to show a commitment to certain concepts within a particular domain. This commitment is, in one sense, philosophical, for example Newton’s notion of the material being of nature is a philosophical commitment to materialism articulated through words of the English language which were given specialist meaning. The commitment also relates to the basis of methods and techniques of the new science of the material being – physics – in that Newton chose differential calculus over algebra or geometry to describe the movement of material beings. A series of graphical conventions were adopted for displaying the results of experimental observations and tabulation protocols were set up to show the relationship between two or more variables. There is a third sense of this commitment which relates to the structure of knowledge – also referred to as epistemological commitment – in that Newton argued about the primacy of the three concepts, mass, force and energy, and emphasised that the other physical concepts could be derived from these three. The umbrella term for different kinds of commitment adopted by a domain community at a given time in their genesis relates to the existence of that community and of the ideas propounded by the community. This umbrella term is ontology – the study of the existence of being: the commitments could be called different kinds of ontological commitments. In this paper, we discuss some of the challenges and opportunities related to sharing knowledge between experts and practitioners within a specialist domain and the sharing between the two groups and the potential endusers of the knowledge of the domain or those upon whom the knowledge will have an impact. The case in point here is that of breast cancer therapy. This is an extensively researched topic involving major laboratories and academic departments working on cancer treatment. The results of their deliberations are published in learned journals, written in a formal style for peer-to-peer communication – if you are not an expert or aspiring to be one in oncology or radiation therapy, for example, learned papers in these disciplines will mean very little to you. The knowledge of the experts is refined, related to the knowledge of other

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experts, and then passed on to the practitioners including cancer therapists working in hospitals, some having close links with the laboratories/departments, and nurses specialising in cancer therapy together with technicians involved in the operation of complex radiotherapy machines, various imaging devices, and/or highly toxic drug treatments. This refined and correlated knowledge is documented in a peer-tooperative language and practitioners themselves write some of the documents. Another important development in recent times has been that of digital libraries and documentation archives that can be accessed through the Internet. Nowadays, the Internet is the first place people go to seek clarification and knowledge related to complex topics; sometimes cancer patients, especially those who have just been diagnosed or about to receive (novel) therapy, tend to consult the Internet. Major cancer charity organisations have devised documents in a language which is more accessible to this new audience. These documents are written in an operative/expert-to-lay person language. We report on the development of an information spider: a computer program that can allow access to a range of documents, for example learned papers, practice manuals, and fact sheets. The spider not only allows access but helps in creating a text archive and in extracting terms from documents for indexing purposes as well.

2. Shared concepts, terminology and knowledge spirals Early literature on knowledge management focused on sharing knowledge related to industrial innovation: there are two well-cited examples of this genre of sharing. The first relates to the development of new product lines by persuading researchers, product designers, manufacturing and sales personnel to work together across departmental and status boundaries (Nonaka and Takeuchi 1995:95-123). The second example relates to the sharing of ‘local innovation’ in the design of usable technology by sharing the knowledge of the end-users of the products (Seely-Brown 1998). Both of these classic examples describe how large organisations used brainstorming methods, and software systems for co-designing and for cross levelling the knowledge within the organisations. Knowledge sharing in more recent literature stresses more indirect interaction between the constituent members of a (geographically

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distributed) organisation. For instance, organisations keen on their staff sharing ‘best practices’ typically use a document repository – for example reports of past successful/failed projects, employee, product, and service profiles (e.g. the so-called Yellow Pages) – and tools for inputting and extracting knowledge from such repositories (Davenport and Probst 2002). The range of knowledge sharing systems includes document management systems, systems that manage documents which have been selected and annotated by experts for the use of others (Gibbert, Jonczyk and Völpel 2000), to the ambitiously-titled intelligent systems (Fisher and Ostwald 2001). Knowledge sharing within a community is a more recent phenomenon and appears to be supported by public-sector organisations. For example, the US National Cancer Institute, a US government agency, is ‘cross levelling’ knowledge across the sub-communities of cancer researchers, cancer-care professionals, and the public at large (Cancer 2003). Again, a document repository is at the heart of the National Cancer Institute’s system. The repository comprises newsletters, fact-files, journal papers, application notes for care workers, information specific to cancer for the public at large, and a glossary of terms.

2.1

Intra-organisational knowledge sharing and exchange

Classical knowledge sharing models suggest that the knowledge transfer/sharing process involves the conversion of tacit knowledge into explicit knowledge and vice versa. En route there are processes that help share explicit and implicit knowledge without conversion. These models focus largely on how knowledge is shared within an organisation or intraorganisationally. The sharing of knowledge within an organisation at one level should be part of the natural functioning of the organisation. At another level there are a number of bottlenecks prohibiting this transfer including physical problems of disseminating information, social problems related to prestige and power, and linguistic problems of sharing knowledge across different levels and kinds of expertise. As we show later, interorganisational transfer of knowledge can pose equally severe challenges. The terms implicit and explicit knowledge are ambiguous and subject to much philosophical debate. For Nonaka and Takeuchi (1995) the conversion of knowledge from implicit to explicit and finally to implicit is the basis of

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knowledge creation. Choi and Lee (2002) have observed a close relationship between the management strategies of Korean enterprises and the knowledge conversion modes suggested in Nonaka and Takeuchi. Generally, explicit knowledge is formalised consensually, and is articulated in the language of a specialist domain through texts. These texts are either informative (learned texts) or instructive (instruction manuals). Implicit knowledge is articulated mainly through the spoken word and is suffused with metaphors, similes, and analogies. Implicit knowledge is largely informal and idiosyncratic of individuals. Documents like inter-office memos, product catalogues, advertisements for goods and services, comprise both implicit and explicit knowledge. The knowledge conversion process involves a close interaction between, and understanding amongst, the key players - the knowledge crew of an organisation: these include the experts, professional workers, including production/marketing/sales staff, researchers and design engineers, the end-users of the artefacts created by the experts and professional workers. The artefacts may include goods and services. There are four modes of knowledge conversion, according to Nonaka and Takeuchi (1995:71-73), and we discuss these modes with reference to the exchange of terminology and concepts amongst the crew during each of the modes: (i) In the SOCIALISATION mode the crew works on an informal basis: verbal exchanges enable the crew to understand each other’s vocabulary. (ii) SOCIALISATION is followed by EXTERNALISATION. Here, an inventory of novel, revised, and abolished concepts is produced in a written document; (iii) SOCIALISATION and EXTERNALISATION produce fragmented knowledge. The knowledge crew then tends to fuse concepts and terminology in the socalled COMBINATION mode. The fusion is implicit in the development of new methods of working or new products. (iv) Once the method and products are established, the crew internalises the operational details, sometimes improving on it and at other times jettisoning some of the new knowledge. This is the INTERNALISATION mode of knowledge transfer. This ultimately leads to

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SOCIALISATION, COMBINATION.

EXTERNALISATION

and

The articulated public and consensual development of a shared conceptual system and its vocabulary is more vivid in a looselyorganised setting, e.g. systems for sharing best practice, than in the high-pressured setting as encountered in the creation of a new type of automobile, home bakery (Nonaka and Takeuchi 1995), or smarter and non-intrusive photocopiers (Seely-Brown 1998) where an organisation explicitly plans for a targeted change. Best practice is shared across an organisation and the recipients of collated/created knowledge are not as well defined as may be the case for design and production engineers sharing the ideas of an architect (product/services) and a marketing expert. Recent developments in knowledge creation are broad-spectrum. This we discuss next.

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precipitate lasting changes in the participating organisations, and the acquiring organisation undergoes changes when it takes over the other organisation. The example of Siemens’ Information and Communication Mobile (ICM) segment is quite apt here (Kalpers et al 2002). There are a number of tasks that involve the workers in the two (or more) organisations during a merger and acquisition: Kalpers et al describe the workers as a Business Community: ‘a [geographically and organizationally distributed] group of people who share existing knowledge, create new knowledge, and help one another on the basis of a common interest in a business-related topic’ (2002:197). The Business Community ‘was designed as socio-technical system’ for facilitating the ‘combination of knowledge and the creation of new knowledge’ (ibid:198). The five main activities of the Business Community suggest that the exchange of knowledge is primarily through social interaction and quadrimodal as per Nonaka and Takeuchi (Table 1).

Mergers and acquisitions (M&A) between organisations present a major challenge to knowledge management in that M&A Key Activities of the Business Community Sharing regular events: face-to-face and phone conference Urgent request forum: Discussion forum with email and Net-meeting sessions Information-platform process for knowledge packages and project information Merger and Acquisition (M&A) process improvement work-shops Disseminating information related to M&A projects through information brokering and debriefing

SOC a a a

EXT a a

COMB a a

INT

a a

Table 1: Activities of the Business Community and knowledge conversion modes. This multi-faceted information platform is The technical component of the Business called an information spider or an infospider. Community is an information system that helps There is a team of authors and editors involved in the storage, annotation and retrieval of in providing potentially ‘reusable knowledge’ to documents. Kalpers and colleagues talk about this document repository. According to Kalpers K(knowledge) Packs: clearly formatted et al ‘a sophisticated search engine allows the structures for encapsulating meta-level and user to keyword-search (sic) the K-Packs summarised contents of documents. The …[and there are facilities] to browse the most documents can be classified in different facets: popular and often used K-Packs’ (2002:201). (i) according to the type of change – merger, The initial evaluation of the Siemens’ M&A acquisition, divestment; (ii) according to the Knowledge Exchange (MAKE) appears to be relevant business process – human resources, encouraging. What interests us is how the logistics, product design; (iii) according to M&A M&A experts built up the knowledge of the processes and phases monitoring, mergers and acquisitions business. evaluation, integration/post closing; (iv) according to IT topics - data, applications, infrastructure, security; and (v) according to 3. Special language and the organisational structure of Siemens – knowledge sharing group-wide, business-unit wide, region-wide. The different modes of knowledge conversion K-Packs range from informative (contacts, help in the articulation, explanation, revision, project documentation, laws, contracts) to and acceptance/rejection of key concepts instructive documents (checklists, documents within a group with diverse interests: the templates, lessons learnt/annotated histories). players in the group ensure that the

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terminology they use in articulation and explanation of concepts is clearly understood by others. The group interaction helps the group in achieving a shared understanding of concepts by sharing the terminology of each other. There is anecdotal/case study evidence in Nonaka and Takeuchi suggesting that ‘speaking a common language and having discussions can assemble the power of the group. This is a vital point, even though it takes time to develop a common language’ (1995:99). The development of the understanding of the vocabulary of a specialism is discussed under the rubric of languages for special purpose (LSP) (Sager, Dungworth and MacDonald 1980; Schröder 1991): this subject has an active constituency in Northern Europe and North America as evidenced by academic journals (e.g. Fachsprache). The use of LSP in shaping specialist written knowledge is a subject of debate in pure and applied linguistics (Halliday and Martin 1993; Bazerman 1988). One major area of research in LSP is the growing gulf between language used by experts and by the layperson

3.1

Knowledge exchange and LSP terminology

Any specialist language is a part of the natural language of the authors of specialist texts: ‘Scientific English may be distinctive, but it is still a kind of English, likewise scientific Chinese is a kind of Chinese’ (Halliday and Martin 1993:4). Pejorative remarks that equate specialist talk with obfuscating jargon notwithstanding, specialist languages are an excellent example of parsimony that hallmarks human cognition: a small set of keywords is used to represent a large body of knowledge, or, more specifically, these keywords usually comprise a significant proportion of specialist texts. This parsimony is essential for reducing ambiguity and increasing precision. An even smaller set of single words is used by the community as their (specialist) signature: physicists will write around and about mass, energy, force, time and space, biologists around and about life forms, evolution, heredity, and environment for instance. The role of shared terminology in knowledge creation is perceptible in the MAKE system. Each K-Pack has associated keywords and MAKE has access to a search engine that presumably makes use of the keywords. Human editors append the keywords to the documents. The editors make a judgement about the suitability of the keywords for a given document and assume that a potential user will

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be familiar with the keywords. This is a timeconsuming and expensive process. In the following, we outline a method for automatically extracting candidate single word terms and compound terms, for automatically identifying relationships between terms based solely on the behaviour of the candidates in relation to other terms and words used in everyday discourse, the so-called general language discourse. Our method is domainindependent and relies only on a representative but random sample of texts used in a given specialism – cancer care for example – together with a sample of texts used in general language.

3.2

A text-based method for identifying shared knowledge

The introduction, usage, and obsolescence of words in a language is complex and creative. Language experts, particularly lexicographers, have advanced a plausible explanation in relation to the birth, currency, and death of words: they argue that the frequency of a word generally correlates with its acceptability by the language community (Quirk et al 1985). The frequency is computed by examining a collection of written texts (or speech fragments) randomly sampled from a universe of texts. Such sampling is essential especially since the language system is open-ended. Corpus linguistics is a branch of linguistics where the emphasis is on the use of systematically organised text collections – text corpora or text corpus (singular) – as a starting point of linguistic description or as a means of verifying hypotheses about a language. Machine-readable versions of such collections have been developed for major languages of the world. One major beneficiary of corpus linguistics is lexicography – and many individual dictionary publishers have their own in-house corpora. The British National Corpus (BNC) of 20th century English language comprises over 100 million words including written text (c. 90%) and speech fragments (10%) (Aston& Barnard 1998). The written component comprises 3,209 texts published mainly between 19751993: two-thirds of the texts belong to imaginative genres (novels, literary magazines), the arts, world affairs and leisure, and the other third to natural, pure, applied and social sciences. There are approximately 250,000 unique words including plurals of nouns and verbs in different tenses. Some of the words are used in most texts and most

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frequently - 6% of the BNC is the word the (6 million instances) - and yet others are used rarely; the word cancer is used 949 times in the BNC, neutron appears 247 times and radionuclide 40 times. Words like ‘the’ and other determiners (a, an), conjunctions (and, but), and prepositions (in, on) are the most frequent and comprise a quarter of the BNC. These are called closed-class words as English-language users seldom invent new determiners or prepositions. Words belonging to the open-class category, nouns, adjectives, adverbs, are not as frequent. Indeed, amongst the 100 most frequent words in the BNC comprising about half the words in the corpus there are only two nouns, time and people. 3.2.1

Language-related and subject-related signatures Recall that a specialist writing about his or her domain of specialist knowledge writes in a form of natural language. A specialist document typically has two signatures. The first signature signifies the natural language of the document and the second signifies the special domain. A corpus-based analysis of a number of individual subject domains, ranging from subjects as diverse as nuclear physics to dance studies, philosophy of science to sewer engineering, theoretical linguistics to cancer research, suggests the existence of the two signatures (Ahmad 2001 and references therein). A corpus was created for each domain usually by keying in a subject name on a search engine and selecting texts of different genres: journal papers, text books, advertisements for goods and services, conference announcements specifically dealing with topics in the domain. The corpora varied from 150,000 words to 750,000 words. The language-related signature of an English LSP shows itself in the distribution of closedclass words. This distribution is the same as that of the British National Corpus: the first 10 most frequent words in almost each of the domains included determiners, prepositions, and conjunctions. The subject related signature of an LSP is reflected in the profusion of open-class words, mainly nouns, in the 100 most frequent words: in some disciplines as many as 30 nouns comprise the 100 most frequent words and in others about 10 or so.

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The most frequent nouns refer to a small group of concepts in the domain: in nuclear physics the 100 most frequent words include the names of key objects of study in nuclear physics - the atomic nucleus, constituent particles of the nucleus, protons and neutrons and key concepts in physics - energy, force and mass. In linguistics, the 100 most frequent words include the names of the grammatical categories or words, noun, verb, adjective, together with important theoretical notions of transformation, structure and grammar. The subject-related signature discussed above refers to single words. Specialist language differs more sharply from general language in the usage of compound words, containing as many as six single words. It turns out that the most frequent single words, nucleus and nuclear, are the key ingredients of many of the most frequent compound terms in nuclear physics, i.e., nuclear structure and nuclear reaction, target nucleus, stable/unstable nucleus. 3.2.2 Automatic identification of terms It is the profusion of subject-related nouns that distinguishes a special language text from a text written in general language. For example, for one instance of the term nucleus in the BNC there may be as many as 300 instances in a typical nuclear physics corpus – the ratio rising to over 5000 for the plural nuclei. The ratio of the relative frequency of a word in a specialist corpus and in a general language corpus may suggest whether or not the word is a term. As closed-class words have a similar distribution in the two corpora, the ratio of relative frequencies of these words in the two corpora, one specialist and the other general language, is generally around unity. But the ratio of the relative frequency of subject-related nouns within a specialist text (corpus) to that in the BNC is generally greater than 1 and indicates a candidate term. This ratio is sometimes called the weirdness ratio. The computation of weirdness is the first step in automatic extraction. 3.2.3

Subject-related signatures and knowledge sharing One example of knowledge sharing is the emergence of an applied science or engineering science around a theoretical subject. The example of nuclear physics (NP) will illustrate this point. The systematic use of nuclear radiation in medicine and agriculture is discussed in the radiation physics (RP) literature. RP is based on key concepts in

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nuclear physics: concepts that help explain naturally radioactive elements, or unstable elements that emit nuclear radiation, or concepts that describe how stable elements can be made unstable, or radioactive, by bombarding or irradiating these elements with other radiation. The controlled use of emitted radiation is used in radiation therapy or diagnosis. Nuclear (reactor) engineering is a branch of engineering based on the theoretical concepts of nuclear fission in nuclear physics. The applied sciences and engineering are regulated by law to ensure the safety and well being of humans whilst promoting the use of potentially lethal artefacts like nuclear radiation. Radiation protection/safety has emerged as a discipline following the extensive use of radiation physics.

as subject-related signatures. A three-way comparison between the three subjects will show the influences of the parent and the progeny’s own identity. We have created three corpora to study these influences and identity: theoretical nuclear physics (151 texts comprising 444,540 words, published between 1970-1999), radiation physics (91 texts, comprising 286,676 words, published between 2001-2003), and radiation safety (16 texts, comprising 127704 words, published in 2003). The texts are written in American and British English and are drawn from journals, textbooks, public announcements and advertisements. Table 2 shows the ten most frequent single words in each of the corpora: nuclear physics and radiation physics ‘share’ two key terms: energy and neutron; radiation physics and radiation safety ‘share’ the terms dose and radiation. The other eight terms show the autonomy of the disciplines.

In order to be autonomous disciplines, both radiation physics and radiation protection have to have their own concepts and associated terminology, a terminology that manifests itself Table 2: Subject-related signatures in three disciplines in physics Nuclear Physics N= 444540 Term energy nucleus neutron nucleon nuclear potential target scattering interaction mass TOTAL

f/N 0.57% 0.52% 0.41% 0.35% 0.32% 0.32% 0.25% 0.24% 0.21% 0.20% 3.390%

Radiation Physics N= 286676 Term dose neutron beam radiation energy system treatment image rays detector

f/N 0.79% 0.41% 0.40% 0.33% 0.30% 0.27% 0.24% 0.22% 0.22% 0.19% 3.356%

Radiation Safety N= 127704 Term mutation dose disease gene radiation risk rate exposure cancer radionuclide

f/N 0.91% 0.75% 0.60% 0.59% 0.57% 0.47% 0.45% 0.32% 0.31% 0.30% 5.254%

Let us now compare the distribution of five of the most frequent terms in each of our corpora and in the BNC (see Table 3). What one sees in the distributions is that the term energy is used 43 and 23 times more frequently in the NP and RP corpora respectively than in the BNC; more demonstrably, the term dose is used 337 and 291 times more in the RP and RS corpora respectively than in the BNC, and the term neutron is used 790, 1379 and 54 times more in NP, RP and RS corpora respectively than in the BNC. The term nucleon, the weirdest in the three corpora, is used only in our nuclear physics corpus. Table 3: Weirdness ratio for the most frequent open-class words in the three corpora Nuclear Physics N= 444540 Term fNucPhys/fBNC energy 43 nucleus 535 neutron 790 nucleon 6402 nuclear 39

Radiation Physics N= 286676 Term fRadPhys/fBNC dose 337 neutron 790 beam 218 radiation 125 energy 23

Radiation Safety N= 127704 Term fRadSafets/fBNC mutation 629 dose 291 disease 50 gene 309 radiation 409

The 10 subject-related signature terms help (in Table 2) in the formation of compound terms and illustrate the linguistic parsimony and linguistic productivity of specialist writers. The term nucleus is used as a head word for two frequent compound terms, target nucleus and halo nucleus, and the neologism nucleon acts as a modifier for the most frequent compound in our nuclear physics corpus,

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nucleon-nucleon amplitude. In radiation physics neutron is used as a head word for the frequently occurring thermal neutron, or as a modifier in neutron-capture therapy and the other noun in the nounnoun compound neutron fluence. Radiation acts as a dominant constituent in the radiation safety corpus, as a modifier in radiation exposure and radiation dose, in its derivative form radiological protection, and as a head word in ionizing radiation. Table 4: Most frequent compound terms in the three corpora. Terms in italics are neologisms Nuclear Physics nucleon-nucleon amplitude neutron star nuclear physics angular distribution target nucleus halo nucleus nuclear reaction nuclear structure angular momentum radioactive beam

Radiation Physics dose distribution thermal neutron neutron capture therapy radiation therapy neutron fluence spatial resolution fluorescence reabsorption maximum dose intensity matrix radiation physics

The theoretical notion of a structured and composite nucleus, and interaction between the constituents of two nucleons (as in n-n amplitude), shows the physico-philosophical bias of the subject and that of the terms. In radiation physics, the term dose (or the energy of the radiation), and its control, dominate the discussion and show the applied physics/engineering bias of the subject. Radiation safety deals with exposure to the risk of nuclear radiation – hence the most frequent terms radiation exposure, radiation dose and the current interest in breast cancer dominate the discussion in the RS corpus demonstrating the ethico-legal aspect aspects of the subject. We have attempted to describe how knowledge sharing can be monitored using a text and terminology management system by identifying the subject-related signature of specialist subjects, and particularly how the sharing of terminology across disciplines indicates the sharing of concepts. The explication of knowledge in nuclear physics resulted in the development of radiation physics, and explication of radiation physics knowledge led to the domain of radiation safety. Each of the two explications have led to the internalisation of knowledge which when explicated has its own terminology. The results in nuclear physics and related disciplines have been replicated in the transfer of knowledge in theoretical solid state physics to electron device engineering (Al-Thubaity and Ahmad 2003); in knowledge transfer from civil engineering to environmental planning systems (Ahmad and Miles 2001); and in a study of how concepts in cognitive psychology and structuralism found their way in theoretical linguistics (Ahmad 2002).

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Radiation Safety radiation exposure congenital abnormalities Multi-factorial disease ionising radiation air concentration genetic disease transfer coefficient radiological protection breast cancer radiation dose

In the next section we discuss how the automatic extraction of terminology for identifying the subject-related signature of a domain, and for identifying its impact on its application/applied domain, can be used to build an information spider semi-automatically. Such a method will facilitate the automatic annotation of key terms for each of the documents and the stronger and weaker cross-referencing between the parent and progeny domains. Our chosen domain is cancer care where experts are attempting to share their knowledge with professional workers, including therapists, nurses, and radiation workers, and where both experts and professionals are attempting to do the same with increasingly Internet-aware actual or potential cancer patients. Ours is a corpus-based study.

4. Monitoring and documenting change and differences: A health infospider Health-care is an all-pervasive domain where advances in medicine and the concomitant costs respectively encourage and discourage the use of new knowledge. In this domain documentation is the ‘main means of communication between care providers’ (Ruch et al 1999) and the effective healthcare delivery systems have become increasingly dependent on accurate and detailed clinical information based on best practices (Chute, Cohn and Campbell 1998). Knowledge of advances and best practice can be shared and refined by formal knowledge dissemination outlets, for example journal papers, workshops and seminars, and through learning-by-doing during encounters with patients. The Internet facilitates sharing of

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scientific results either through digital journals or through research notes posted on secure websites relating to drug trials, for example. The widespread use of the Internet has led to potential and actual patients, or their friends and relatives, going online for information after receiving news that the patient is or might be suffering from cancer. Health-care knowledge has to be shared between many organisations and increasingly that knowledge has to be shared with an openended audience. In health-care or its subdomain cancer care, as in any other specialist domain, terminology management is of the essence: including new terms and expunging old ones. Maintainers of controlled medical vocabularies recognize that such vocabularies are not static (Cimino 1996). The US National Cancer Institute (NCI) is attempting to provide up-to-date online information on cancer to two groups: healthcare professionals and patients. The NCI website provides a facility for searching the contents of its document base; there is also a glossary of cancer terms. The website is organised and is accessible according to different facets: users can look at individual types of cancer, at different types of treatments, and at the results of studies being carried out. Information for professionals is generally in the form of an extended abstract or summary about a specific topic together with an extensive bibliography. References to published journal articles in the bibliography of a given extended abstract are generally hyperlinked to the abstract of the cited article. Information for patients is provided without extensive references to journal articles and is mainly in the form of fact sheets: highlights of a recent diagnostic or therapeutic discovery, of a long-term study and other useful information. In addition to the US NCI, and other national cancer charities like Cancer Research UK, pharmaceutical companies also provide information about their drugs as fact sheets.

4.1

Building a cancer infospider

In order to ascertain the subject-related signature of the language used by experts for cancer-care professionals and for addressing laypersons, especially patients, we have created three text corpora. We are not considering the parent discipline - cancer research - rather focusing on its three progenies to determine the extent to which knowledge is shared between the three progenies by measuring terminological commonalities. In order to illustrate our ideas

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we have focused on aspects of diagnosis (specifically the breast cancer gene), therapy and after-care of breast cancer patients. The breast-cancer expert corpus comprised 300 texts, abstracts, and full papers (114,394 words). The texts were collected by navigating medical journals and websites (such as the breast-cancer research and nature.org web sites) using the keyword breast cancer gene (abbreviated as brca1 and brca2). The breast cancer care professional corpus, comprising 1,000 texts (226,464 words) was built by collecting texts from the US National Cancer Institute, US National Library of Medicine, and the Journal of American Medical Association. The keyword used to collect the texts was breast cancer. The cancer-patient corpus, comprising 800 texts (464,000 words) was collected by mainly focusing on texts made available by cancer charities – the American Cancer Society, Cancer Research UK, Alliance of Breast Cancer Organisations, and the California-based Bay Area Tumor Institute. (Recall that US NCI website has two sub-sites - one for professionals and the other for patients.) The subject-related signature of each of the corpora was compared to the British National Corpus. The terms breast and cancer dominate the three corpora and comprise 3.26 % of the expert corpus 3.3% of the professional corpus and 5% of the patient corpus. The word women dominates the three corpora and was among the most frequent words, but the term patient acted as a dominant constituent in the professional and patient corpora. The key differences in the corpora perhaps indicate the extent to which the experts think they are ready to share their current knowledge with professionals and patients. One can detect some differences in the most frequently used words in the these corpora – the experts have found new breast cancer genes, so new that they have not been given names, rather they are referred to as brca1 and brca2 and mutations; the rather high frequency in the professional corpus of these acronyms, as compared to the patient corpus, suggests that experts are almost ready to share this knowledge with the professionals. Of the established knowledge, the terms (breast) surgery, mastectomy that are preceded (or followed) by biopsy and radiation, occur more frequently in the patient corpus than in the professional, while biopsy is an not frequently used in the expert corpus. Comparison with the BNC is also instructive:

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the comparison of the use of the 14 most the BNC. There are certain terms that are used highest frequent terms in each of the three 5000 times more in our corpora than in the corpora with the frequency of the terms in the BNC - tamoxifen and ovarian in the expert BNC show how weird these terms are: even corpus, tamoxifen in the professional corpus the familiar word family is used 63 times and mastectomy in the patient corpus. (See (expert corpus), 4 times more frequently than Table. 5) Table 5: The contrastive distribution of scientific terms in the expert, professional and patient corpora compared to the BNC. Terms in bold provide a subject- related signature. Expert N=114,394

fExp/ NE

fExp/ fBNC

Professional fProf/NP fProf/fBNC N=226,464

cancer

1.87%

443

cancer

1.41%

320

breast

2.19%

745

breast

1.39%

831

breast

1.25%

430

cancer

2.18%

465

brca1

1.37%

INF

women

0.64%

11

women

0.96%

15

Patient N=464,000

fPat/NPat

fPat/fBNC

brca2

0.71%

INF

risk

0.56%

43

treatment

0.61%

47

mutation

0.49%

1014

patient

0.53%

24

risk

0.47%

33

families

0.53%

63

treatment

0.27%

22

therapy

0.32%

153

risk

0.50%

41

therapy

0.23%

116

surgery

0.28%

100

ovarian

0.39%

7893

tamoxifen

0.21%

7149

chemotherapy 0.26%

969

gene

0.33%

148

chemotherapy 0.20%

757

cells

0.30%

23

carriers

0.33%

512

estrogen

0.20%

INF

lymph

0.29%

1316

women

0.23%

7

disease

0.20%

19

radiation

0.20%

108

dna

0.23%

68

brca1 & brca2 0.20%

INF

biopsy

0.18%

177

protein

0.22%

76

ovarian

0.19%

3687

mastectomy

0.16%

5360

tamoxifen

021%

7242

family

0.13%

4

tamoxifen

0.15%

5265

The notion of weirdness helps us to establish whether or not a word has been appropriated by the specialists in their general languages and turned into a term that, in turn, becomes part of the specialists’ special language. Recall that weirdness is the ratio of the relative frequency of the term in a specialist corpus of texts and the relative frequency of the (source) word in the general language. Higher weirdness means that the word has been appropriated, and the key indicator of the appropriation is the (much) higher frequency of use in the specialist corpora than in the general language corpus. Let us see whether we can extend the metaphor of weirdness when we compare the language of the experts with that of the professionals or when we compare the language of the professionals, or the experts, with that of the patients. If a term is much more widely used in the expert corpus than in the professional corpus then one might infer that the concepts/artefact denoted by the term are in a state of evolution and hence not used as extensively by the professionals as by the experts. Similarly, a weird use of a term in a professional corpus, when compared with the patient corpus, may suggest that the concept/artefact related to the term is either not important to the patient or the

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concept/artefact is still being matured by the professional community. Contrastingly, if a term has a weirdness of ONE when we compare its relative frequency in the expert corpus with that of either professional or patient corpus, then we might infer that the concept/artefact denoted by the term is quite well established amongst the professional and the patients. A comparison of the distribution of 26 terms shows that terms like brca1, brca2, mutation, carrier, chromosome, gene are used over five times more in the expert corpus than in the professional corpus. The experts are less interested in chemotherapy, carcinoma, and surgery, as they use these terms 5, 14 and 16 times less than the equivalent use of the terms by the professionals. One way to illustrate the preference experts have for a term when compared to the professionals, and vice versa, is tabulate the logarithm of weirdness of the most weird terms for a professional when he or she reads an expert’s texts: positive values of the logarithm of the ratio of the relative frequency of the same term in an expert’s texts when compared to professional show preference use by experts. A negative value of the ratio shows the less frequent use of the term by the expert when compared to a professional.

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Table 6a: The contrastive distribution of relative frequency of the terms in the experts and the professional corpus. Words

Log(rExpert/rProfessional)

Words

Log(rExpertl/rProfessionl)

brca1

1.007

receptor

-0.08

tamoxifen

0.004

adjuvant

-0.24

chromosome

0.87

therapy

-0.63

brca2

0.85

chemotherapy

-0.69

carriers

0.84

diseases

-0.72

dna

0.82

clinical

-0.76

mutation

0.78

hormone

-1.09

gene

0.78

tumors

-1.09

protein

0.75

progestin

-1.15

germline

0.58

carcinoma

-1.15

susceptibility

0.39

metastatic

-1.15

ovarian

0.33

screening

-1.22

estrogen

0.01

surgery

-1.22

A comparison of the languages of the professionals and that used for patients shows similar disparity in the use of some of the terms (see Table 6b). Terms like irradiation, ovarian and the newly discovered brca1 and brca2 are used more in the professional corpus than in the patient corpus. Terms like biopsy and mammogram are used more extensively in the patient corpus than in the professional corpus. The inferences we may make are (a) professionals are involved in discussions about concepts/artefacts related to the terms they frequently use which are not yet common knowledge in the patient corpus and (b) having established concepts/artefacts some time ago, like mammograms, professionals are not actively involved in developing these concepts/artefacts further but these established concepts/artefacts are of considerable import to the patients. Table 6b: The contrastive distribution of relative frequency of the terms in the professional and the patient corpus. Words progestin

Log(rProfessional/rPatient) 1.35

Words lump

Log(rProfessional/rPatient) -0.06

carriers

0.91

cancers

-0.13

irradiation

0.67

tumor

-0.14 -0.16

ovarian

0.59

hormone

postmenopausal

0.56

diagnosis

-0.19

patients

0.50

screening

-0.34

brca1 & brca2

0.47

mastectomy

-0.45

metastatic

0.39

symptoms

-0.55

adjuvant

0.35

nodes

-0.64

mutation

0.34

lymph

-0.82

tamoxifen carcinoma

0.08 0.07

biopsy nipple

-1.00 -1.22

genetic

0.06

mammogram

-1.22

Whilst we can readily compare the use of single words, the comparison of the frequency distribution of compound words in two different corpora is not as straightforward. One method of comparison can be the rank correlation of two compound words: the rank of a compound term refers to its frequency in a given corpus. If the order is the same in the corpora, then the correlation will be +1; if the order is reversed in the other then the correlation will be -1. If there is no correlation then the value of the correlation coefficient will be zero. The first comparison will be between expert and professional corpora. We chose the two most frequent words brca1, and brca2 in the expert corpus that suppose sharing concepts with the professional corpus. Table 7 shows a comparison of ranks of compound terms in the expert corpus and the professional corpus. The dominant single term in the expert corpus is brca and it is the headword or modifier of many terms in the corpus. The correlation amongst the ranks of brca–based compounds in the two corpora is (coeff = 0.92) that is the relative rank-order of the compounds in the two corpora is the roughly the same.

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Table 7: The rank-order correlation coefficient of compound terms based on brca1 & brca2 where RankExpert, RankProfessional are the rank-order of the compound terms in both expert and professional corpora. Compound terms

RankExpert

RankProfessional

brca1 & brca2 mutations

3

10

brca1 & brca2 genes

4

27

brca1 & brca2 protein

14

47

Correlation

0.92

Similarly, therapy is a dominant term in the professional corpus and a root or stem of many compounds. However, the therapy-based compounds do not appear to have the same rank-order in the two corpora– the rank correlation is (coeff = 0.32) as Table 8 shows. What is important to point out is that some kinds of therapy such as estrogen therapy and radiation therapy were not discussed in the expert corpus at all, which supports the indication of weak relationship between the rank-order of the therapy-based compounds in the two corpora. On the other hand, the compound terms of cancer types that could be developed by having an inherited susceptibility or common genes such as breast, ovarian, prostate and family history indicate a relationship that could not be considered as a significant one between the two corpora (coeff =0.45). Table 8: The rank-order correlation coefficient of compound terms based on therapy where RankExpert, RankProfessional are the rank-order of the compound terms in both expert and professional corpora. Compound terms endocrine therapy hormone therapy adjavant therapy tamoxifen therapy systemic therapy

RankExpert 37 39 39 43 43

Correlation

0.88

RankProfessional 26 43 16 31 37

Consequently, experts conducted deep research related to discovering or verifying the genes that prove the inherited element considering high risk - when having a family history - in developing such types of cancer as the order frequency of these terms was quite high in the expert corpus, while professionals are focused principally on breast cancer and its linkage to other types such as ovarian. Professionals concentrate on the application of such results in their practices, such as therapies, diagnosis and treatments. However, the feedback from professionals and practitioners to the experts is a vital element because innovation that does not have a good application might be obsolete, and a theory that is not put into practice might vanish. The comparison of the breast cancer-based compound has shown a different distribution: the terms breast cancer, with risk, patient, carcinoma, families, susceptibility, cells. The correlation between the rank-order of these terms indicates a weak and negative relationship (coeff=-0.29) as the orders of breast cancer patients are roughly the same, while the terms metastatic breast cancer and breast cancer susceptibility have different order rank in these two corpora. The compound words related to breast cancer types and diagnosis have low rank in the expert corpus. And also the rank-order of breast cancer families and susceptibility is much higher than in the professional corpus as these concepts are related to other concepts such as the new discovered genes. And this can infer the negative weak relationship between these compound words (see Table 9). Table 9: The rank-order correlation coefficient of compound terms based on breast cancer in the expert and professional corpora. Compound terms metastatic breast cancer breast cancer patients invasive breast cancer breast cancer cells breast cancer families

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RankExpert

RankProfessional

42 15 42 42 22

8 13 20 31 44

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breast cancer susceptibility Correlation

We will now discuss the extent of knowledge transfer between professionals and patients. We selected two frequent single terms – therapy and breast in the two corpora. The established concepts relating to the terms chemo-, radio-, psycho- and cryo-therapy have the same frequency order in the two corpora (correlation coefficient=0.87). However, in the order of more recent forms of therapy, for example, hormone and estrogen replacement to breast conservation therapy, the correlation is not quite the same (correlation coefficient =0.5). The frequency order of the terms in which breast is the modifier is anti-correlated (correlation coeff =-0.5): the order in the professional corpus is breast carcinoma, btumors, b-tissue, b-reconstruction and breast implant, but in the patient corpus breast implant had the top rank.

4.2 A prototype information spider and automatic indexing

25 -0.29

47

reusable knowledge and to structure the knowledge’ following the infospider of Kalpers et al (2002). Recall that MAKE-infospider depends crucially on the attachment of keywords to be stored in the system for subsequent recall. The indexing scheme depends on keywords and on the ability to identify and extract proper nouns. The system we have designed deals with cancer-related information produced by experts, professionals and patients in order to facilitate sharing best practice documents concerning this disease. In this system, the spider has six facets each of which represents a dimension or category: knowledge package or document (K-D) type, scope, process, audience orientation, sharing, and renewable ontology sharing. Each knowledge package is allocated to the metainformation contained within each ‘leg’. An example of meta-information for a K-D document is displayed below:

We have created a knowledge-based system that was used for facilitating the ‘search for Header Information

Title: Best Practices Of Cancer Diagnosis K-Doc Type: best practice document Author: The National Cancer Institute NCI Publishers: www.Cancer.gov Description: Spider categories: Audience orientation: Health professional Established Terms: radiation therapy, chemotherapy, and hormone therapy, primary tumor Neologisms: estrogen-receptor, progesterone-receptor, HER2/neu gene amplification Scope: breast cancer Abstract: Breast cancer is commonly treated by various combinations of surgery, radiation therapy, chemotherapy, and hormone therapy. Prognosis and selection of therapy may be influenced by the age and menopausal status of the patient, stage of the disease, histologic and nuclear grade of the primary tumor, estrogen-receptor (ER) and progesterone-receptor (PR) status, measures of proliferative capacity, and HER2/neu gene amplification. K-elements: Full text view: \\Liberator\corpus\Breast_Cance: r\test2\1.txt OriginalSource: sourcehttp://www.cancer.gov/cancerinfo/pdq/treatment/breast/healthprofessiona/ Search: Link to related K-Document : http://medline.cos.com/ Link to others search engine: http://www.breastcancercare.org.uk/Professionalresources.htm Launch Search: gene amplification General information Date of publish: 10-10-2002 Total words: 5500 words ID: number:2 Cancer Institute NCI Cancer.gov

The system can index, store and retrieve knowledge packs or document packs including best practice in health-care. The system can also summarise documents to produce an abstract with a summariser developed at the University of Surrey. Further, the system gives practitioners the opportunity to be engaged in communication concerning the K-D document by opening discussion or adding comments to the document in order to share their knowledge. This study has a potentially important impact on the management of the health-care workforce, and is therefore being conducted in conjunction with the University of Surrey’s interdisciplinary Healthcare Workforce Research Centre.

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Audience orientation

Knowledge document Type

Renewable Ontology Keywords

Professional

Patient

Information

Top frequent words Relationships

Practitioners

Best practice Practitioners Guideline

Link to other search engines

Patient Portal

Health Care Spider interaction

Relevant Domain

Link to the original source

Sub Domain

comments

Full View

Domain

Description

discussion Mother Domain

K-D Sharing

Summary

K-D Scope

K-D process

Figure 1: The Surrey Health-care Infospider

5. Conclusion Knowledge sharing is facilitated through a number of different knowledge sharing or creation modes. We have argued that the successful completion of each of the modes manifests itself either through an understanding of terminology (for example the socialisation mode and internalisation mode) or through the production of documents as in externalisation and combination modes. The trace of knowledge of individuals and organisations, that is, written documents within the archives of a given domain, comprises much of the discernible knowledge of the domain. One of the major problems in knowledge sharing is the accessibility to documents within the archives, especially within a rapidly changing domain. For instance, terms used for indexing documents at an earlier stage of the evolution of the domain may become irrelevant to documents subsequently produced. Terms familiar to individuals at a given level of expertise may be quite opaque to individuals at a different level of expertise. Terminology of a specialist domain emerges over time. The terminology in itself is a part of the wider language of everyday use with specialist meanings. A systematic extraction of these terms will obviate some of the challenges in accessing documents and, when accessed, understanding them. Our Infospider perhaps demonstrates the synergy between language and knowledge in domains as diverse as cancer therapy.

6. Acknowledgment The computations reported here were carried out using System Quirk, a text and terminology

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management system that developed by University of Surrey to facilitate the creation and analysis of text corpora. Texts were captured by using the UK Universities Joint Academic Network and e-journal subscriptions of the University of Surrey. A number of public domain texts were also used Thanks should also be addressed to the British Council in acknowledgment of their research scholarship. This research was supported by the EU co-funded project Generic Information based Decision Assistant GIDA IST-200031123, and SOCIS project GR/M89041.

References: Al-Thubaity, A.B. and Ahmad, K. (2003). “Knowledge Maps as Lexical Signatures of Journal Papers and Patent Documents.” In Ebad Banissi et al. (eds.) Proc. of 7th International Conference on Information Visualisation (London, England, 16-18 July 2003). Los Alamitos: IEEE Computer Press. 582-588. Ahmad, K. (2002). “Writing Linguistics: when I use a word it means what I choose it to mean.” In Manfred Klenner and Henriëtte Visser (eds.). Computational Linguistics for the new millennium: divergence or synergy? Proceedings of the International Symposium held at the Ruprecht-KarlsUniversität Heidelberg, 21-22 July 2000 Festschrift in honour of Peter Hellwig on the occasion of his 60th birthday. Bern: Publishing Group Peter Lang. 15-38. Ahmad, K. (2001). “The Role of Specialist Terminology in Artificial Intelligence and Knowledge Acquisition.” In S.-E. Wright & G. Budin (eds.) Handbook of Terminology

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Management, Vol.2. Amsterdam: John Benjamin Publishers. 809-844. Ahmad, K. and Miles, L. (2001). “Specialist Knowledge and its Management”. Journal of Hydroinformatics 3(4) October 2001. 215-230. Aston, G. and Barnard, L. (1998). “The BNC Handbook: Exploring the British National Corpus with SARA”. Edinburgh: Edinburgh University Press. Baker, G.P. and Hacker, P.M.S. (1988). “Wittgenstein Meaning and Understanding”. Oxford: Basil Blackwell Ltd. 48-56. Bazerman, C. (1998). “Shaping Written Knowledge: The Genre and Activity of The Experimental Article in Science”. Madison: University of Wisconsin Press. Cancer. (2003) [ONLINE] http://www.cancer.gov accessed 27 July 2003. Choi, B. and Lee. H. (2002). “Knowledge Management Strategy and its Link to The Knowledge Creation Process.” Expert Systems with Applications, 23(3). 173– 187. Chute, C., Cohn, S. and Campbell, J. (1998). “A Framework for Comprehensive Health Terminology Systems in The United States: development guidelines, criteria for selection, and public policy implications”. Journal of American Medical Association, (JAMA) 5(6). 503–510. Cimino, J.J. (1996). “Formal Descriptions and Adaptive Mechanisms for Changes in Controlled Medical Vocabularies”. Methods of Information in Medicine 35(3). 202-210. Davenport, T., and Probst, G. (2002). “Knowledge Management Case Book Siemens Best Practises.” 2nd edition. Munich: Publicis Corporate Pub., and John Wiley & Sons. Fisher, G. and Ostwald, J. (2001). “Knowledge Management: Problems, Promises, Realities, and Challenges”, IEEE Intelligent Systems, 16(1). 62 .

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Gibbert, M., Jonczyk, C., & Völpel, S. (2000). “ShareNet – The Next Generation Knowledge Management”. In (Eds.) T. Davenport & G. Probst. 22-39. Halliday, M.A.K. and Martin, J.R. (1993). “Writing Science – Literacy and Discursive Power”. London and Washington: The Falconer Press. Kalpers, S., Kastin, K., Petrikat, K., Scheon, S., and Spath, J. (2002). “How to Manage Company Dynamics: An approach for Mergers and Acquisitions Knowledge Exchange”, In (Eds) T. Davenport and G. Probst. 187-206. Morgan, G. (1996). “Images of Organization”. 2nd edition, London: SAGE Publications. Nonaka, I. and Takeuchi, H. (1995.) “The Knowledge-Creating Company”. New York: Oxford University Press, Inc. Quirk, R., Greenbaum, S., Leech, G., and Svartvik, J. (1985). “A Comprehensive Grammar of the English Language”. London and New York: Longman. Ruch, P., Wanger, J., Bouillon, P., Band, R., Rassinoux, A., Scherrer, J. (1999). “MEDTAG: Tag Semantic for Medical Document Indexing”. American Medical Informatics Association (AMIA) Annual Symposium, November. Sager, J.C., Dungworth, D. and MacDonald, P.F. (1980). “English Special Languages – Principles and practice in science and technology”. Wiesbaden: Oscar Brandsetter Verlag–KB. Seely-Brown, J. (1998). “Research that Reinvents The Corporation”. Harvard Business Review On Knowledge Management. Boston: Harvard Business School Press. 153-180. Schröder, H. (1991). (Ed.) “Subject-Oriented Texts – LSP and text Theory”. Berlin and New York: Walter de Gruyter. Scarbrough, H. (1996). “The Management of Expertise”. Macmillan Business. London: Macmillan Business Press LTD. 83-89

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In Search of an Intellectual Capital General Theory José María Viedma Martí Polytechnic University of Catalonia, Barcelona, Spain. [email protected] http://intellectualcapitalmanagementsystems.com Abstract: The development of intellectual capital theory has been guided by the ideas and thoughts of a handful of influential practitioners, including Karl Erik Sveiby (1997), RS Kaplan (Kaplan and Norton, 1992) and Leif Edvinson (Edvinson and Malone, 1997). These pioneers established the basis of the “intellectual capital standard theory”. In the present paper the assumptions and principles that support the standard theory (the prevailing paradigm) are discussed. The paper then introduces other models and methodologies as alternatives to the standard theory—such as the “IC Accounting System” (Mouritsen et al., 2001), the “Value Explorer” (Andriessen and Tissen, 2000) and the “Intellectual Capital Benchmarking System (ICBS)” (Viedma, 2001)—and examines the foundations and principles on which the alternative new theory (the ‘new paradigm’) is based. Finally, the paper attempts to synthesise both of these theoretical approaches with other new views and contributions, and tries to develop the basis for a first general theory of intellectual capital. Keywords: intellectual capital; knowledge management; strategic management; models; paradigms; theory

1. Introduction Intellectual capital issues have undergone extraordinary development since the beginning of the 1990s. The increasing difference between company market value and company book value has prompted academics and practitioners to consider the concept of “intellectual capital” as a key determinant of the process of value creation for shareholders, managers, and society as a whole. The development of intellectual capital theory has primarily been guided by the ideas and thoughts of a handful of influential practitioners, including Sveiby (1997) and Edvinson (Edvinson and Malone, 1997). These pioneers established the foundations of the way in which intangible factors determine the success of companies. In the words of Andriessen (2001), the pioneers established the basis of the “intellectual capital standard theory”. Their respective models—“Intangible Assets Monitor” (IAM) (Sveiby, 1997) and “Skandia Navigator” (Edvinson and Malone, 1997)—are representative of the assumptions, principles, and foundations of the intellectual capital standard theory. However, later contributions from other academics and practitioners have developed and refined the standard theory. Today, this theory is the pre-eminent guide to the management of intangible assets, and has facilitated success through sustainable competitive advantage for leading companies and organisations.

discussed in the present paper because it is assumed that the reader is already familiar with the main features of these models. Section 2 also contains an explanation of the assumptions and principles that support the standard theory (or prevailing paradigm). In Section 3, other models and methodologies as alternatives to the standard theory are introduced. These include the “IC Accounting System” (Mouritsen et al., 2001), the “Value Explorer” (Andriessen and Tissen, 2000), and the “Intellectual Capital Benchmarking System” (Viedma, 2001). These models and methodologies are not discussed in the present paper because it is assumed that the reader will have easy access to their main features and characteristics. The three models share similar goals and, taken together, propose some new approaches that constitute an alternative theory to the standard theory described in Section 2. Section 3 also examines, in some depth, the foundations and principles on which the new theory is based. In Section 4, the paper attempts to synthesise both of these theoretical approaches with other new views and contributions. These new views and contributions are carefully discussed. Finally, in Section 4, the paper tries to develop the basis for a first general theory of intellectual capital. In Section 5, some of the most relevant conclusions are presented.

The present paper is structured as follows. Following this Introduction, Section 2 notes the representative models and methodologies from the standard theory (or “prevailing paradigm”)—the IAM, the “Balanced Scorecard”, and the “Skandia Navigator”. These models and methodologies are not

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2.1

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Classification of intangible assets

Although intangible assets cannot be touched, they can be identified and reasonably classified. One such simple classification is depicted in Figure 1

Intangible Assets (Stock price premium) Equity (Book value) Tangible assets minus visible debt

External Structure

Internal Structure

(Brands, customer and supplier relations)

(The organisation: management, legal structure, manual systems, attitudes, R&D, software

Individual Competence (Education, experience)

Figure 1: Intangible assets monitor(Sveiby, 1997). 2.1.1 Assets of individual competence This term refers to assets such as the employees’ education, experience, know-how, knowledge, skills, and values and attitudes. These assets are not owned by the company, but the use of those assets is accessed by the company’s hiring of employees. This type of asset is also known as “human capital”. 2.1.2 Assets of internal structure This term refers to the company’s formal and informal organisational structure, work methods and procedures, software, databases, research and development (R&D) systems, management systems, and culture. These assets are owned by the company and some can be legally protected (patents, intellectual property, and so on). They are also known as “structural capital”. 2.1.3 Assets of external structure This term refers to the company’s portfolio of customers (generally known as “goodwill”) and its relationships with suppliers, banks, and shareholders, its cooperation agreements and alliances (strategic, technological, production, and marketing), its commercial brands, and its image. These assets are owned by the company and some can be legally protected (commercial brands, and so on). They are also known as “relational capital”.

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2.2

Representative models of prevailing paradigm.

Because intellectual capital is the key source of wealth creation, it is logical that firms pay close attention to the effective management of such capital. Therefore, the ability to identify, audit, measure, renew, and increase these intellectual assets is a key factor for the success of companies in the modern environment. In this regard, significant effort has gone into the search for methodologies and models to improve the management of intellectual capital—although, it must be said, with mixed success. The main reason for this is the nature of these assets and the fact that each business has its own particular knowledge mix, specific objectives, and market environment. Three authors have been of special significance in this search for useful models of intellectual capital: Sveiby (1997) who designed the first intellectual capital model—the “Intangible Assets Monitor” (IAM); Kaplan (Kaplan & Norton, 1992, 1996a, 1996b) who devised the “Balanced Scorecard” methodology (especially with respect to effective strategy implementation); and Edvinson (Edvinson and Malone, 1997) who was the architect of the “Skandia Navigator” (followed by Ross et al. 1997,

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whose “Process Model” gave a strategic perspective to the “Skandia Navigator”). As noted above, these models and methodologies are not discussed in the present paper because it is assumed that the reader already knows their main features or has easy access to them.

2.3

Assumptions and principles of prevailing paradigm

The main assumptions and principles that support the standard theory (or the prevailing paradigm) can be summarised in seven points: The accounting view; Breakdown of intellectual capital; Cause-and-effect relationships; Relatively static approach to valuecreation processes; Limitation of concept of intellectual capital; Use of the same models and methodologies to manage and produce reports; and Attempts to treat intangible assets as if they were tangible. Each of these is discussed briefly below. 2.3.1 The accounting view Basically, the models noted above try to explain the causes of the difference between the company market value and the company book value. The aim is to establish an intangible assets accounts plan that allows identification of the relevant intangible assets and their later valuation. This is an accounting approach to intellectual capital. It identifies the company’s intangible assets and enters them in the books—complementing the financial balance sheets with another kind of balance sheet (of intangibles). It should be noted in passing that the “Balanced Scorecard” does not belong to this accounting approach—as it has a strategic approach. Although the “Balanced Scorecard” has been included among the intellectual capital models in this study, it is not a standard part of the literature on this subject. 2.3.2 Breakdown of intellectual capital This is a common denominator of all models. Despite the different terminology that they each use, the three models previously mentioned all break down intellectual capital into its distinct elements. These elements can be summarised as human capital, structural capital, and relational capital. For each of these elements, the company establishes a set

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of indicators that is used to take account, assess, and manage each specific type of capital. That is, each type of capital is deemed independent from the rest in the model’s intrinsic processes. The actual daily operations of firms show that this division is artificial because, in the valuecreation processes, all three types of intellectual capital act together, and such a division never arises. Furthermore, physical and financial assets act together with the intangible assets in the value-creation processes. 2.3.3 Cause-and-effect relationships The models of the prevailing paradigm examine cause-and-effect relationships between each of the three types of capital (human, structural, and relational) and each of the objectives (strategic and financial). These are extremely difficult to establish—due mainly to the artificial division of the model’s intangible assets. In the value-creation processes, the human assets act together with the structural and relational assets, making it difficult for directors and managers to determine such cause-and-effect relationships. 2.3.4

Relatively static approach to valuecreation processes The artificial categorisation of intellectual capital lacked consideration of how firms actually deploy their resources through their organisational core activities. Because of this, the above-mentioned models fall short in explaining how firms effectively compete, and how they recreate the sustainable competitive advantages that give rise to value creation. Although Sullivan (2000) deemed the IAM and the “Skandia Navigator” models to be oriented towards value creation, it should be emphasised that they lack the dynamism and flexibility required in the turbulence of the modern environment. By focusing on existing intangible assets (human, structural, and relational intellectual capital), these models become prisoners of a dangerous reductionism. Indeed, the most common reason for failure in firms today is deficient strategy implementation—which actually demands paying close attention to what the firm does (rather than what it has). In short, the prevailing paradigm lacks an activity-based view (ABV).

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2.3.5

Limitation of concept of intellectual capital Existing models limit discussion of intellectual capital to ideas of means of production, and do not take proper account of other nonintellectual intangibles—such as values, organisational culture, and so on. The models described above consider intangible assets as being mainly intellectual assets or knowledge assets—that is, those that psychologists ascribe to the left side of the brain. However, other intangible assets (such as values, organisational culture, talent, motivation, and employee commitment) also exist. Even if these other affective assets cannot be labelled as “intellectual”, they are of great importance to the success of companies and organisations. However, because the emphasis is on intellectual assets, other relevant intangible assets are neglected. 2.3.6

Use of the same models and methodologies to manage and produce reports The above-mentioned models are too often identified with the reports of intangible assets that they generate—reports that supplement the balance sheets of the company’s tangible assets. Usually, the same models and methodologies that are used to prepare such reports of intangible assets are also used to manage the same intangibles—even though the requirements of management are quite different from those of preparing a report. One exception is the “Balanced Scorecard”, which was especially conceived as a management tool. Moreover, the end users of intangibles reports are shareholders, suppliers, financial institutions, and so on—that is, external stakeholders in general. In contrast, the end users of management models and methodologies are the organisation’s internal managers. 2.3.7

Attempts to treat intangible assets as if they were tangible The use of the term “intangible assets” is dangerous—in that it induces people to think of “intangibles” as assets that can be entered in the books as if they were tangibles, using the extended accounting system of double entry. Several efforts have been made to assimilate intangible assets with tangible assets. For example, there have been attempts to establish a sort of general accounting plan in line with traditional accounting methods— including the utilisation of universal indicators that might serve to approach almost any situation. The most comprehensive list of such

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indicators corresponds to the “Universal Intellectual Capital Report” of Edvinson and Malone (1997). They attempted to apply to intangible assets similar procedures to those that have been universally applied to tangible assets—with the aim of generating balance sheets and earnings statements that could be used to make comparisons among any type of company, no matter its nature. Caddy (2000) followed a similar approach in his attempt to discover and assess not only intangible assets but also intangible liabilities.

3. Representative models and principles underlying the new theory (or new paradigm) 3.1

Representative models of new paradigm

In the late 1990s the problems encountered (particularly by small and medium enterprises) when trying to put into practice the prevailing intellectual capital models and methodologies led to the development of new methodologies and an alternative theoretical paradigm. Among these new methodologies, those that stand out because of the relevance of their empirical applications (especially successful among small and medium enterprises) are the “IC Accounting System” (Mouritsen et al., 2001), the “Value Explorer” (Andriessen, 2001), and the “Intellectual Capital Benchmarking System” (Viedma, 2001, 2003a, 2003b). These models and methodologies are not discussed in the present paper because it is assumed that the reader has easy access to their main features. However, the “Intellectual Capital Benchmarking System” is explored in a little detail because it represents an introductory methodology to the new theory of intellectual capital. 3.1.1

“Intellectual Capital Benchmarking System” (ICBS) The “Intellectual Capital Benchmarking System” (ICBS) has a strategic view—as does the “Value Explorer”. The starting point for the ICBS is the firm’s mission, strategy, and objectives—but, in this case, “the best in class” global competitor is also considered, thus allowing benchmarking to be undertaken in a systematic and permanent way. ICBS is also a management tool that allows companies to compare their core competencies or intellectual capital with those of the best world competitors from the same activity segment.

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ICBS is grounded in certain factors and criteria that determine competitiveness in the global market environment. Those principal factors are: Competitive environment: This refers to the specific business unit environment. It includes Porter’s competitive forces (customers, competitors, suppliers, entry barriers, and substitutive products), as well as demand evolution (past behaviour and foreseeable future), and the extent to which the activity in question is internationalised. Outcomes: Expected economic and financial outcomes of the specific business unit. Customer needs: Customer segment needs that the company expects to cover through the business unit activities. Products and services: Products and services with their attributes, characteristics, functions, and embedded knowledge and technologies. Processes: Value chain activities, primary as well as secondary, that are necessary to produce current products and services. These activities are made up of core business activities, outsourcing activities, and strategic alliances and cooperation agreement activities. Competitive advantages: Competitive advantages are generated mainly in the different value-chain core business activities. Company core competencies: Essential knowledge or core competencies that will produce competitive advantages. Personal competencies: Professionals, managers, and support staff competencies and capabilities that will generate core competencies. This eight-factor framework is a flexible framework that allows identification and evaluation of the core competencies or essential knowledge within each particular factor. The framework explains how sustainable competitive advantages are achieved in final products and services.

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Companies, if they want to be successful, need to produce competitive products and services. That is, they must focus on their core business activities, and outsource others. They must also work through carefully chosen cooperation agreements and strategic alliances with suppliers and other companies. Nevertheless, competitive products and services are not easily achieved. A lot of work is needed to be able to establish competitive advantages in each core business activity of the value chain. Core competencies in the value chain’s core business activities produce products and services with competitive advantages and high knowledge or intellectual capital content. Innovation and research and development play fundamental roles in those core business activities. They allow acquisition of new knowledge and new core competencies which, in turn, generates new products and services, intelligent products, new processes, new technologies, and so on—simultaneously improving both the present products and the processes and technologies that follow. Finally, the acquisition of core competencies and the accomplishment of all these competitive advantages are possible only by means of the actions of the different persons deemed to be crucial to the company in its technological and managerial scope. The personal competencies of these key people are responsible for the generation of core competencies, which in turn produce competitive advantages. The general model that has been described above is depicted in Figures 2 and 3. ICBS identifies the relevant factors and criteria for a specific activity segment. The systematic and continuous use of ICBS allows firms to generate intellectual capital balance sheets that complement the financial statements, and to improve their intellectual capital.

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F low ch art 1 C om p an y A

B .U . O b jectives

P rod u cts an d S ervices

C u sto m e r needs

C om p an y B

B en ch m ark in g G AP

B en ch m ark in g G AP

B en ch m ark in g

P rocesses

C ore C om p eten cies

P rofession als core com p eten cies

O p eration s in frastru ctu re

(h ) = H om ologou s B .U . = B u sin ess U n it

G AP

B en ch m ark in g G AP

B en ch m ark in g G AP

B en ch m ark in g G AP

B .U . O b jectives (h )

P rod u cts an d S ervices (h )

P rocesses (h )

C ore C om p eten cies(h )

P rofession als core com p eten cies (h )

O p eration s In frastru ctu re(h )

Figure 2: ICBS

Financial R esults

Professional C ore com petencies

C om petitive segm ent environm ent

C ustom er needs

C ore com petencies

V alue C hain

BU

Products and Services

• Competitive advantages core business activities • Competitive advantages outsourcing activities • Competitive advantages alliance activities B U = B usiness U nit

Figure 3: ICBS II

3.2

Assumptions and principles of the new paradigm

The main assumptions and principles that support the new intellectual capital theory (or

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the new paradigm) can be summarised in seven points: The strategic view; Not breaking down intellectual capital into its constituent parts;

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Core competencies as the only intangible assets to manage; Reality and dynamism in the valuecreation processes; Breaking down core competencies into their constituent intangible assets; Core competencies linked with core capabilities of professionals who work independently or in teams; and Evaluation and assessment of the valuecreation potential of future core competencies.

Each of these is discussed below. 3.2.1 The strategic view According to this view, a firm’s mission, strategy, and objectives are the principal points of reference for intellectual capital management. According to this approach, it is not important to determine and appraise every intangible asset—because only a few are relevant to a firm’s strategy formulation and implementation. These few relevant intangible assets are usually grouped according to the firm’s core competencies or core capabilities— which are the true intellectual capital and are therefore the key variables to manage. The theoretical background to the significance of core competencies is grounded in resources and capabilities theory (Barney, 1991, 1999; Grant, 1991, 1998; Teece, Pisano and Shuen 1997). In short, this view focuses on the fact that, in turbulent and changing environments, competitive sustainable advantages are due mainly to resources and capabilities—in particular, the core competencies or capabilities that Andriessen (2001) describes in terms of a “coordinated bundle” of intangible assets that constitute the roots of the firm’s competitive sustainable advantage. 3.2.2

Not breaking down intellectual capital into its constituent parts The new theory—freed from production of annual reports and statements, and accounting principles and rules conditionings—focuses on a strategic view in achieving the firm’s mission and objectives and in surpassing its “best in class” competitors. Thus, the artificial division of intellectual capital into human, structural, and relational capital is of little use because the products and services that result from a specific strategy have no relationship at all with these three types of capital considered independently. Rather, these products and services are associated with an integrated

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bundle of such assets as reflected in core competencies and capabilities. 3.2.3

Core competencies as the only intangible assets to manage From the above discussion, it can be concluded that, for each business unit in the operations value chain, and for each project in the innovation value chain, the only assets to manage are those grouped in the core competencies. A firm’s specific core competencies are not usually very numerous. Moreover, because a relationship between products and services and the core competencies that enable them is easily established, an appraisal of core competencies can be made by estimating the expected returns from the products in which they participate. 3.2.4

Reality and dynamism in the valuecreation processes One of the main questions that has always been at the core of the strategy theory is how firms compete in their industries or, more broadly, in the global markets. This leads to another question: ‘How do firms create and exploit value?’. This leads to an examination of what is deemed to be the essence of the entrepreneurial success—good strategy formulation and implementation. Seeking answers to these sorts of questions leads back to both the resource-based view and the activity-based view (because implementation is mainly about activities) to try to explain how firms deploy resources in order to create sustainable competitive advantages and to achieve superior performance. From a knowledge perspective, this is possible only if the models pertain to the new emerging paradigm of intellectual capital—the ICBS and the Value Explorer. The focus of these new models on a firm’s core competencies allows considerations not only of which intangible resources are crucial to achieving success, but also which core activities must be acted upon (if it is accepted that value creation and exploitation are both intrinsically resourceoriented and activity-oriented). As Haanes and Fjeldstad (2000) have stated, it is not only what the firm has, but what the firm does, that matters in value creation. The concept of sustainable competitive advantages that underlies the processes of value creation and exploitation presupposes a certain dynamism that is extremely difficult to capture if attention is paid only to resources, and if an assessment tool based on a false

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division of intellectual capital into three artificial categories is used in the analysis. As Man et al. (2002, p. 128) have stated, “… the dynamic nature [of the concept of competitiveness] involves the dynamic transformation of competitive potentials through the competitive process into outcomes”. Both resources (tangible and intangible) and activities exist in competitive and non-competitive processes, and this makes it impossible to appraise the firm’s intangible forces if only a resource-based view is taken—a view that requires the creation of competitive advantages for attaining superior performance and market value, but fails to take adequate consideration of the noncompetitive processes. 3.2.5

Breaking down core competencies into their constituent intangible assets Once the principle that core competencies constitute the firm’s authentic intellectual capital has been accepted, the improvement, strengthening, and enrichment of the intangibles “bundle” is enhanced if they are broken down into their constituent parts. This should be undertaken in a broader sense, including not only intangibles that are intellectually based but also intangibles that are affective in origin. To analyse and manage those intangible components the core competencies classification included in the “Value Explorer” is of assistance. 3.2.6

Core competencies linked with core capabilities of professionals who work independently or in teams. Core competencies are the result of aggregating intangible assets of different types. But each asset is made up of knowledge and skills, and skills are always generated by human beings—working either independently or in teams. Thus, core competencies management is essentially dependent upon the effective management of the core competencies of professionals who work either individually or in coordinated teams.

3.2.7

Evaluation and assessment of the value-creation potential of future core competencies Finally, the strong relationship between future products and services and the competencies that support them allows an assessment of the future potential of each core competency or core capability. The “Value Explorer” appraises the strength of each core competency by means of the following four criteria: (i) value-

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added to customers; (ii) future potential; (iii) sustainability; and (iv) robustness.

4. A General Theory of Intellectual Capital 4.1

Other new views and contributions

Following the above discussion, the present paper attempts to synthesise both of these theoretical approaches with other new views and contributions. The new views and contributions considered in this context are: The essential role of commitment and action; Intellectual capital as the difference between intangible assets and intangible liabilities; Intellectual capital as a dynamic concept; Intellectual capital identified with the concept of a ‘business recipe’ in action; Benchmarking as a strategic tool. Each of these is discussed below. 4.1.1

The essential role of commitment and action Commitment and action have an essential role in the process of wealth or intellectual capital creation. Firm competencies are the ultimate creators of intellectual wealth or intellectual capital. As such, they are a necessary but not sufficient condition for wealth creation. However, firm competencies must be established with the incorporation of certain personality characteristics and attitudes that reflect a strong commitment to convert competencies into competitive and profitable products and services. This positive emotionality embedded in the concept of commitment, together with an appropriate bundle of competencies, is what ultimately accounts for differences in human and organisational behaviour. Commitment is the ‘copper wire’ that leads human competencies through to superior organisational performance. It is the element that enables these competencies, purposefully aligned with the firm’s strategy and objectives, to find their way to market considerations. Furthermore, commitment accounts for the sustainability of the firm’s competitive advantages. The challenge of consistently delivering superior performance requires extraordinary effort and sustained commitment on the part of the key people in an organisation. The demands for innovation that the knowledge economy has exerted on firms

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has, in turn, emphasised talent as the main value-driver of capital creation (both wealth and intellectual capital). Given that talent is acknowledged as a key source of competitive advantage, the ability of a firm to manage this intangible also becomes a core competence that adds to the firm’s value. In such an environment, commitment needs to be managed as well as competencies (Mayo, 2001; Gubman, 1998). This view of commitment and action draws upon Jericó’s (2001) conceptualisation of talent as being the result of: competencies X commitment X action It also draws upon Ulrich’s (1998) definition of intellectual capital as being: competencies X commitment This view is also in accordance with the work of Man et al. (2002) and Mayo (2002) whose contributions emphasise that competencies alone cannot deliver superior performance in isolation from a more complex bundle of human capabilities (including personal values and attitudes). It is therefore apparent that intellectual capital theory needs to develop new ways of systematically including commitment in its appraisals. It has long been recognised by theorists in organisational behaviour that commitment is a basic driver of a firm’s performance, and its explicative power has been clearly demonstrated in entrepreneurship research (Beattie, 1999; Hood and Young, 1993). In particular, the concept of ‘utility’, as adopted in the economic views of entrepreneurship theory (Douglas and Shepherd, 2000), is important in this. Perhaps what is missing, as Hitt et al. (2001) called for, is an integration of entrepreneurial and strategic thinking. 4.1.2

Intellectual capital as the difference between intangible assets and intangible liabilities Practically all models (both those of the prevailing theory and those of the new paradigm) make reference only to intangible assets. Caddy (2000), in his article “Intellectual Capital: recognizing both assets and liabilities”, was the first to consider the existence of both intangible assets and liabilities in organisations. Whereas intangible assets are oriented towards wealth creation, intangible liabilities are oriented towards its destruction.

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The systematic application of the available intellectual capital measurement tools should provide hints as to what is going wrong in a given organisation, and should thus point to the presence of certain flaws (or intellectual liabilities) that are undermining the firm’s potential for intellectual value creation. According to Powell (2001), any assessment of a sustainable competitive advantage should consider competitive advantages and competitive disadvantages simultaneously. It is apparent that intellectual capital should be defined as the difference between intangible assets and intangible liabilities, such that positive and negative drivers of value creation are both considered—thus allowing effective intellectual capital management. Given that managing intangible assets is a difficult task, identifying and measuring intangible liabilities would appear to be an even more difficult task. However, intellectual capital theory is mature enough undertake this exercise. 4.1.3

Intellectual capital as a dynamic concept Most models approach intellectual capital only in terms of a static concept, without reference as to how intangible categories create and destroy wealth. They fail to consider wealth creation and destruction as taking place through virtuous circles (Knight, 1999) and vicious circles. A virtuous circle can be said to be in place when there is a good alignment of the personal and professional objectives of key people with those of the organisation, thus leading to an environment of creativity and positivity. In contrast, vicious circles reflect a malalignment of the objectives of employees and those of the organisation. It is possible to identify and manage these circles only through a dynamic approach to intellectual capital assets and liabilities. This identification of virtuous circles and vicious circles must be combined with the identification of intellectual assets and liabilities (as noted above). Vicious circles and virtuous ones can take a long time to become apparent and, once they are identified, it can take time for an organisation to reverse their effects. This is significant in a competitive global environment. Once the market starts giving signals of a misfit between its value parameters and the firm’s value offer, time for adjustment can be very short. The presence of strong competition, together with the time required to adjust internal vicious circles and intellectual

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liabilities, can mean that firms are simply unable to adjust in a timely fashion.

circles that will have to be subsequently managed.

All of this emphasises the need to include activity-based views (ABVs) within the new general theory of intellectual capital.

Markets are changing with increasing rapidity, making it very difficult for firms to keep track of the innovations and performance of competitors. In this context, strategic benchmarking, if applied systematically, becomes an effective and efficient tool to track the firm’s value-creation processes in creating sustainable competitive advantages. Benchmarking is effective because it focuses on what is strictly relevant to value creation: a superior BR and core competencies. It is efficient because it fosters a better assignment of organisational resources as long as the unit of analysis is essentially the firm’s BR. Benchmarking the firm’s BR with the best competitor’s BR informs its key people about how well they have been doing and whether an in-depth analysis is required.

4.1.4

Intellectual capital identified with the concept of ‘business recipe’ in action Core knowledge and core competencies are brought to bear in creating value through a successful ‘business recipe’ (BR). The difference between a successful business formula and a successful business recipe is the same as that between a successful formulated strategy and a successful implemented strategy. Superior performance that ends in value creation is a natural consequence of a firm’s success in bringing a superior business formula into the market. This emphasis on implementation is thus significant for any new general theory of intellectual capital—especially in view of the comments already made (above) about the importance of activity-based views in identifying intellectual liabilities and vicious circles. 4.1.5 Benchmarking as a strategic tool Recognising the importance of benchmarking as a strategic tool allows early identification of virtuous and vicious circles, and facilitates the management of intellectual capital in accordance with the new views and contributions outlined thus far. The only intellectual capital measurement tools that introduce benchmarking techniques in their appraisals are those of the Innovation Intellectual Capital Benchmarking System (IICBS) (Viedma 2003a) and the Operations Intellectual Capital Benchmarking System (OICBS) (Viedma 2003b). The objective of both the IICBS and the OICBS is to determine whether the firm possesses superior core competencies in relation to the world’s best competitor. This can be used to account for sustainable competitive advantages that might lead to superior performance and wealth creation.

However, a firm’s intellectual assets and liabilities, together with its virtuous and vicious circles, remain a matter for the firm’s internal management. The effectiveness of management will obviously influence performance—either transforming the firm’s BR to reach the point of being a superior BR that creates value, or never reaching that point and failing to create extra value.

4.2

The formulation of a general theory of intellectual capital

As a result of the above discussion, the main ideas of a general theory of intellectual capital can be depicted in simplified form (see Figure 4).

In terms of assessing world competitiveness, IICBS and OICBS benchmark a firm’s business recipe against that of its world’s best competitor. A firm will be able to create value in the long run as long as its BR has proven to be superior to the world’s best. A detailed and thorough process of benchmarking will enable the identification of superiority (or inferiority)— signalling the presence of virtuous (or vicious)

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José María Viedma Martí

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