Understanding Researchable Issues in Knowledge ...

Understanding Researchable Issues in Knowledge Management: A Literature Review Sanghamitra Brahma* and Sumita Mishra**

Knowledge and Knowledge Management (KM) practices have been recognized as valuable means for tapping collective intelligence and skills of employees to create greater organization knowledge. Further, promoting conducive work culture improves productivity and enhances performance. Researches, both industrial and academic, have been undertaken to explore KM concepts, frameworks, technologies, applications, knowledge-based work culture, etc. This paper explores the development of KM through review and categorization of research papers published during the past 15 years into seven broad categories. The categories have been chosen to track the development in the field of KM from basic, foundational research to integrated research with the areas of Organization Culture (OC) and Organization Performance (OP). The objective of the researcher is to identify and define significant gap in the existing literature and suggest a direction for future research.

Introduction The emergence of Knowledge Management (KM) happened with Peter Drucker’s famous quote in Post-Capitalist Society (1993)... The basic economic resource—the means of production—is no longer capital, nor natural resources nor labor. It is and will be Knowledge. Knowledge and KM practices have been steadily gaining prominence as a decisive factor affecting the organizations’ ability to gain competitive advantage globally in the last couple of decades. It has been recognized as a valuable resource for tapping collective intelligence and skills of employees to create a greater organization knowledge base. KM practices serve not only to preserve past legacies but also to learn new things and initiate new situations for both individuals and organizations in the present and the future. Further, it is recognized that promoting conducive work culture, empowering individuals for innovativeness and encouraging an open and sharing environment facilitate knowledge to be effectively used and managed. This, in turn, improves productivity and enhances performance. * **

Assistant Professor, Heritage Business School, Heritage Group of Institutions, Kolkata, West Bengal, India; and is the corresponding author. E-mail: [email protected] Assistant Professor, KIIT School of Management, KIIT University, Bhubaneswar, Odisha, India. E-mail: [email protected]

Understanding Issues in Knowledge Management: A Literature Review © 2015 IUP. AllResearchable Rights Reserved.

43

In the past two decades, a wide range of technologies and applications have been introduced in various segments of business and services, including academics. Researches, both industrial and academic, have been undertaken to explore further the KM concepts, frameworks, technologies, applications, knowledge-based work culture, etc. This paper is an outcome of the ongoing research on KM practices and their effectiveness. The paper has focused on the various avenues of KM development through a review and classification of articles and research papers published in the late 1990s to today, i.e., more than ten years.

Objective The objective of this paper is to analyze and understand the extant literature on KM concepts and technologies, knowledge-based performance outcomes, Organization Culture (OC) and KM practices, Knowledge Management Performance Index (KMPI), etc. The researcher aims to identify probable researchable areas which require further study.

Methodology The papers published during the last 15 years have been selected, systematically categorized and classified to track the conceptual development in the field of KM, from the time that papers started appearing in publications in reputed international journals, in the integrated field of KM, OC and Organization Performance (OP). Quintessentially, the review process has been delimited to articles and papers focusing on KM concepts, KM technologies and outcomes, OC and KM practices, and OP. The analytical review has drawn from papers, articles, revealing case studies, business reports and survey findings. Based on the scope of the published materials read, the paper has identified seven broad categories, each one of which is a well-defined avenue for research in KM, namely: 1. Foundations of Knowledge Management; 2. Knowledge: A Key Organizational Resource; 3. Knowledge Directions: Technologies for Knowledge Management; 4. Knowledge Directions: Outcomes of Knowledge Management; 5. Role of Organization Culture in Knowledge-Based Performance (OC-KM paradigm); 6. Impact of Knowledge Management on Organization Performance (KM-OP paradigm); and 7. Metrics to measure the impact of Knowledge Management Practices. The first two categories are core and related to foundational research. The third category is core to information technology, whereas the rest are integrated with other behavioral parameters and their combined impact on organization. 44

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

Foundations of Knowledge Management The concept of KM originated in the early 1990s. It was initiated from the difficulty of dealing with complexities, ever increasing competition spurred by technology and the growing sophistication of customers’ demands. Polanyi’s (1966) discussion on the distinction between explicit and Tacit Knowledge (TK) was one of the germinal tasks which led researchers to develop management definitions, concepts, processes, stages, circulations and procedures. All these helped to lay a concrete foundation to the theory on KM. Working definitions on KM, frameworks, propositions, perspectives, measurements and impacts describe investigations on the question of KM, its methods and techniques, its value/worth, its functions supporting individual and organizations to manage their knowledge, etc.—Nonaka et al. (1996); Heijst et al. (1997); Wiig (1997); Wiig et al. (1997); Wilkins et al. (1997); Drew (1999); Hendriks and Vriens (1999); Johannessen et al. (1999); Leibowitz and Wright (1999); Leibowitz (2001); Rubenstein-Montano et al. (2001); Liao (2002); and Liao (2003). McKeen and Staples (2003) enlisted the key characteristics responsible for designing the organization’s KM initiatives and also make them successful. KM is a risk with a huge payoff and the risk-return balance is the prime condition under consideration. Schultze (2003) described Knowledge Work (KW) from three perspectives: economic-classification of occupations on the basis of the nature of the KW; labor process-position and alignment of the knowledge workers within the classification; and work practice based on what knowledge workers are supposed to know to do their work. Spender (2003) considered organization as a knowledge field, which is a dynamic synthesis of inherently limited and fragmented bodies of knowledge that comprise its K-inventory. Also, the K-field is structured and contoured by the emotions and feelings of those who inhabit it. Romer (2003), best known for his theories about dynamics of growth, has added knowledge and technology to the classical mix of production along with land, labor and capital. He has also affirmed that the law of diminishing returns in the physical economy reverses in the case of knowledge economy. Holsapple and Joshi (2003) said that knowledge-based organizations host KM episodes which are triggered by a knowledge need/opportunity and culminate with the satisfaction of that need. Within each such episode, the knowledge processors manipulate the knowledge resources in various ways.

Category-Wise Gap While the above-mentioned studies suggest directions and scope for further research, certain research gaps may be worked upon in the following directions: • Adopting a 360-degree approach to determine the most appropriate individuals/ traits in the knowledge managers which will lead to efficient KM process and related change in an organization. A longitudinal field research may add to the dynamism of the research. • The changing requirements in processes, activities and outcomes of KM over time require subsequent changes in what the knowledge workers do, what they know Understanding Researchable Issues in Knowledge Management: A Literature Review

45

and what they are supposed to know. This aspect may also be studied in different segments of the developing economy. • Working out newer strategies for categorizing/structuring the knowledge literature remains a big challenge in literary research in KM. • The evaluation of the knowledge processes and their increasing returns may be studied in the present-day context for specific industrial segments and sectors. • The ontological changes in KM that have happened in the last one decade may be investigated in the context of specific sectors in the industry.

Knowledge: A Key Organizational Resource In the knowledge era, the basic economic resources and means of production have been replaced by the knowledge resource. Any learning organization striving for sustainable growth and development must explore, exploit and enhance its knowledge resources. Knowledge Assets (KA) are resources used to support the storing, sharing and reuse of organizational knowledge. Nonaka and Takeuchi (2005) have grouped KA into four categories—experiential KA (tacit), routine KA (tacit), conceptual KA (explicit) and systematic KA (explicit). The questions answered through these studies include: How does knowledge resource make an organization more efficient and effective? How is knowledge produced and used in an organization as a resource? Knowledge and competence are the key drivers of competitive advantage in the developed nations. Teece attributed competitive advantage to ownership of KA. The firm’s knowledge base includes its technological competencies as well as its knowledge of customer needs and supplier capabilities. The essence of the firm is its ability to combine knowledge and complementary assets in ways so as to create value (Teece, 2003). Knowledge-intensive activities of a nation can be linked to the wealth of the nation. It is imperative for the leaders of the nation to recognize and cultivate the intellectual capital potential of their countries just as managers of the firms need to do for their organizations (Edvinsson, 2003). Edvinsson also addressed the concepts of corporate longitude, knowledge communities and societies, social entrepreneurship, etc. Knowledge navigation and quest for new wealth of nations will guide the national leaders towards building their nations. Holsapple (2003) considered several perspectives of knowledge, like systems/representations view, states view, stocks and flows/ production view and knowledge-versus-information view. He has discussed the relationship between knowledge and technology, and advocated a middle path in which computer-based technology is the enabler of KM. Eppler (2003) explored the knowledge maps [an innovative instrument for Corporate Knowledge Management (CKM) as ways for making organization’s knowledge resource visible. This is done by outlining the rationale for knowledge mapping, i.e., providing a common context to access expertise and experience. He has presented five types of maps that an organization may use to manage its knowledge resources, namely, knowledge-source, -asset, 46

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

-structure, -application and -development maps. Jennex and Olfman (2003) labeled Organizational Memory (OM) as knowledge captured in accessible repositories such as documents, people, computers and culture. They discussed the forms and functions of OM and how it relates to organizational learning, discussed OM systems, and how to design and manage them in the context of a nuclear power plant case. Kayworth and Leidner (2003) inferred that culture is a significant knowledge resource by virtue of its potential to facilitate knowledge creation, storage, transfer and use. They have discussed ways in which OC serves as a knowledge resource and also proposes several hypotheses along the way. For a long time, the field of accounting has been interested in valuation and tracking of organizational resources and related changes. However, this had not included knowledge as a major organizational resource, traditionally. Stone and Warsono (2003) described the economic and institutional forces that shape current knowledge accounting efforts. The authors have outlined and compared six alternative approaches to knowledge accounting, namely, total value creation, accounting for future, balanced scorecard, Skandia Navigator, intangible asset monitor and value chain scoreboard. Swan (2003) remarkably converged the various academically dominant perspectives of KM and industrial practice with reference to a case to establish that knowledge is perhaps the most valuable resource that organizations and societies have. However, he has conceived that knowledge is worth only when it is linked to specific activities, tasks and purposes. He highlights the importance of integrating the distributed knowledge and addressing rational action concerns such as social identity, power, conflict and motivation. Rahe (2009) established that probability of misunderstanding increases with increase in overlap of individual mindsets. Even if there are sophisticated technologies to support the management of knowledge, the knowledge product by itself can neither be managed nor effectively controlled. The practical implication suggests that value of KM depends on the accuracy of data gathered but the probability of misunderstanding increases with increase in overlap of individual mindset. Due to subjectivity filter, individual cognition denies the creation of objective knowledge. KM deals with a disparate bundle of mental models trying to codify and transmit subjective knowledge. The conclusion derived is that KM is far from management of true reality. Instead it is management of reality manipulated through individual perception. Dahooie et al. (2011) show how KW can be defined and segmented based on two dimensions, i.e., knowledge intensity score for a job (JKIS) and communication intensity score for a job (JCIS), through a six-step framework. The study attempts to identify the different types of activities comprising a worker’s job and provides a framework for quantitative definition and segmentation of KWs.

Category-Wise Gap The research gaps may be worked upon in the following directions: • Conduct analytical case studies to establish empirical models of various categorical assets’ components (knowledge and other tangible assets) and their relative significance in specific sectors and industry. Understanding Researchable Issues in Knowledge Management: A Literature Review

47

• Identify and investigate certain knowledge organization-intensive geographical territories and conduct macro-level studies to establish the relation between knowledge activities and wealth generation in the Indian context. • Structure different perspectives of knowledge, namely, systems/representations view, states view, stocks and flows/production view and knowledge-versus-information view, etc. for the subject of study and suggest the best approach for it, depending on its nature of business—adopt an attribute-based scale for evaluating knowledge resource to study the comparative implication of various attributes in the different sectors of industry. • Study the changing criteria for knowledge mapping in the context of present-day requirement in India. • Evaluate the organization memory systems, designs and their managing strategies and also suggest better, efficient and more relevant models for the same. • Study the probable constructs of OC as a knowledge resource in the context of specific business/service sector. • Analyze and evaluate the implementation of various knowledge accounting models in the specific industrial sectors. • Study the link between KM and its specific activities, tasks and purposes in the context of various sectors in India. • Develop a scale to measure cognition, awareness, motivation and communication of culturally diverse samples and their influence on the organizational KM resource. • Develop a framework for knowledge workers to cluster them based on the nature of their job.

Knowledge Directions: Technologies for Knowledge Management Technology is an important implementation factor on how KM is or could be conducted in an organization. It complements, supplements, and amplifies the essential roles that humans play in an organization’s KW. The researcher has thoroughly studied the following research papers to understand the use of technology as an enabler or facilitator for KM initiatives of an organization. Tsui (2003) provided an overview of the evolution of commercial KM software and also traced the progress of Artificial Intelligence (AI) and information retrieval research in the decade of 1990s and early 2000s. He structured a process and function-based framework to understand the types and roles of commercial KM software. He deduced that a majority of the KM tools available in the market have enterprise-wide application. There is a shortage of software to assist an individual knowledge worker in performing Personal Knowledge Management (PKM). O’Leary (2003) regarded the critical issue of knowledge assimilation in KM. He considered that knowledge may be gathered, created or converted, but if it is not assimilated, the organizations will not actualize all its potential values. He organized key 48

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

technologies for knowledge assimilation along six dimensions, namely, knowledge storage, knowledge massaging, knowledge organizing, knowledge integration, knowledge filtering and navigation. Staab et al. (2003) researched the ontological importance of incorporating knowledge in an organization and its subsequent selection from the organization’s knowledge base. They have discussed how organization’s ontology ties together the processes of knowledge generation, acquisition, assimilation/internalization, and use. According to them, there are two dimensions to analyze knowledge processes—first, Knowledge Meta Process, which is needed to introduce Knowledge Management Solution (KMS) in an enterprise; and second, Knowledge Processes that are performed while running a KMS. During the knowledge meta process, ontology is developed that acts as the conceptual glue between different steps of KM proper. Conway (2003) discerned how search methods for KM are constructed and what key components KM systems must focus on. KM systems must make the KA easy to find and retrieve so that the users can intuitively access stored knowledge and connect to experts. The author has outlined strategies that aid in initiating effective repository searches; apply general techniques (like search engines, expertise finders, personalization and subscription services, etc.) for connecting information and knowledge available throughout the enterprise. The author highlighted how web services like .NET and other web technologies may be integrated into programming logic of a KM system to provide benefits of integrating external source information dynamically with internal KM information. Malafsky (2003) explains how algorithmic foundations of KM systems technologies impact their functional capabilities and limitations for acquiring and sharing KA. He also discusses future KM tools, giving examples from leading government and commercial R&D programs. The author has concluded that although the IT tools provide ever increasing capability, they are still a long way from being able to adequately replicate human understanding of information need to make a decision. Current state-of-the-art technology cannot adequately automate the required system functions with common level of uncertainty and information volume. Gray and Tehrani (2003) concentrated on the technology of disseminating knowledge like use of telephones, World Wide Web, e-mails, groupware, intelligent agents, information portals, etc. The discussion has been organized into three dimensions and the relation among them, namely: • Dissemination technology; • Method of knowledge sharing and dissemination (push, pull and point); and • Method of retrieval (search, organize, interface and feedback). They have also considered implementation issues with case examples and non-computerbased dissemination methods. They inferred that technology must be accompanied by changes in OC, structure and how people behave. Technology can create the infrastructure needed for knowledge culture and distribution. It provides access to get the right information to the right people at the right time. Tools for capturing knowledge can make TK explicit. However, without a favorable knowledge culture, operational benefits of technology cannot be achieved. Understanding Researchable Issues in Knowledge Management: A Literature Review

49

Susarla et al. (2003) analyzed the potential offered by peer-to-peer networking in managing organizational knowledge in the direction of improved search capabilities, content-sensitive addressing and community aspect of knowledge transfer. They have discussed the pitfalls along the path to realizing this potential and the need for incentive alignment in creating and disseminating knowledge. They have also recognized that the potential of P2P networking is severely limited by the holdup problem. Effective functioning of P2P KM requires appropriate coordination and control of the participants. Davenport and Sena (2003) focused on Online Analytical Processing (OLAP), a technology for knowledge derivation. Decision makers frequently need high-level knowledge in order to make their decisions from the transaction processing databases. OLAP transforms raw data into higher-level knowledge useful to the decision makers, thereby deriving new knowledge. They provided a theoretical framework for knowledge derivation in a decision support context and then located OLAP technologies within that framework. Knowledge quality becomes more important as information systems become more integrated with the decision support pyramid and knowledge is passed on to customers via web technologies. Wei et al. (2003) provided a reasonably comprehensive review of knowledge discovery and its associated data mining techniques. The dramatic expansion of data has generated an urgent need for new analysis techniques that can intelligently and automatically transform the processed data into useful information and knowledge. As a result, knowledge discovery (referring to the overall process of discovering useful knowledge from data) and data mining (referring to extraction of patterns from data) have increased in importance and economic value. Based on the types of knowledge that can be discovered in the databases, the data mining techniques can be broadly structured into categories like classification, clustering, dependency analysis, data visualization and text mining. The authors concluded that knowledge discovery and data mining applications should be treated more as a business issue rather from purely technological perspective. Organizations need to identify core business questions and analyze opportunities and then find out where organization data can provide value. Subsequently, the business strategies to target the business question should be developed. Once the strategies have been devised, each one of them is further decomposed into an array of data mining tasks.

Category-Wise Gap The research gaps may be worked upon in the following directions: • Work out strategies and designs to integrate and bridge the gap between CKM objective and individual TK (PKM). • Study the effectiveness and impact of the popular KM software’s knowledge assimilation features and work on it. • Study the KM implementation and maintenance process to understand the efficiency and conversion of the continuously changing knowledge meta process into the KM process solution in a continuous order. 50

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

• Study newer strategies to integrate the recent web and networking technologies and applications with KM system to meet the objective of increasing the dynamism of KM systems with respect to the sources of information. • Study the disparities in the increasingly capable KM tools and the information need of the user and work out effective AI-based algorithms to bridge the gap between the two. • Establish that successful implementation of technology, i.e., KM systems, depends on the favorable changes in the OC, structure and people’s behavior. • Study the behavioral problems which severely limit the potential of P2P networking technology. Also, systematic alignment of the benefits to the participants in the P2P network and the benefits thereof may be studied. • Work out the development of more advanced technology to facilitate transformation of low level data into structured information.

Knowledge Directions: Outcomes of Knowledge Management ‘Knowledge Outcomes’ are the outcomes based on learned activities. The studies discussed in this section are from the compilation on knowledge management—Knowledge Directions. This section points to some of the foundational researches on KM dynamics, i.e., KM applied. Teece and Pisano (2003) presented a dynamic capability paradigm to understand a firm’s source of competitive advantage. This paradigm emphasizes on the shifting character of the environment and the role of strategic management in appropriately adapting, integrating and reconfiguring internal and external organizational skills, resources and functional competencies towards a changing environment. It sees three major influences on the conduct of KM, namely, resource, management and environmental influences as crucial in determining an organization’s competitive stand. The authors have argued that competitive advantage of firms stem from dynamic capabilities rooted in high performance routines operating inside the firms. Holsapple and Singh (2003) presented the knowledge chain model that identifies five primary and four secondary Knowledge Management Activities (KMA) that can be sources of competitive advantage. It is possible for an organization to perform one or more of these knowledge activities in a manner that yields competitiveness. The model is analogous to Porter’s Value Chain and is also grounded in a descriptive KM framework developed via a Delphi study involving international KM experts. O’Dell et al. (2003) outlined six strategies for achieving KM outcomes and provided a quiz for assessing an organization’s current KM progress. They identified, described and illustrated important landmarks in the journey towards achieving KM outcomes: value proposition, culture, infrastructure, technology, tactics and measurement. Wiig and Jooste (2003) distinguished between types of productivity: macro-productivity vs. micro-productivity vs. nano-productivity (personal level) and performance productivity vs. economic productivity. They explained that improved application of knowledge at the nano and micro level may result in improved performance productivity with no apparent effect on Understanding Researchable Issues in Knowledge Management: A Literature Review

51

economic productivity. They explained several ways in which improved knowledge and knowledge processing can increase productivity, examine related problems and discusses what must be done differently to successfully exploit knowledge for productivity gains. Dove (2003) shared the results of a decade-long study on the relationship between KM and an organization’s responsibility, and the agility that results from achieving an appropriate balance between the two, in highly adaptable enterprise systems. He discussed the role of KM in achieving agility in dual terms of a top-down directed component based on knowledge portfolio management and a bottom-up grassroots component based on collaborative learning. Amidon and Mahdjoubi (2003) explored the connections between KM and innovations based on integrating knowledge as an interdependent variable with conventional business methods and perspectives. They presented a framework for analyzing innovation effectiveness in which knowledge value emerges at the balance of performance, behavior and technical factors. They have offered guidance on the transition of an organization from traditional business planning to innovation strategy. Smith and McKeen (2003) measured the contribution of knowledge and its processing to an organization’s success. They examined the current state of theory and practice related to measuring the impact of KM. Their work is based on views and interactions of a focus group of knowledge managers from a wide assortment of industries, including consulting, telecommunications, finance, healthcare, manufacturing and government. Hanley and Malafsky (2003) presented a practical framework to measure the value of KM investments to guide managers with implementation of KM initiatives and also measure their progress and outcome. They explained how to design a measurement process for KM performance. Both qualitative and quantitative metrics have been discussed in three categories, i.e., system measures, output measures and outcome measures. Chen et al. (2010) studied the top 5,000 Taiwanese firms listed in the yearbook published by the China Credit Information Service Incorporation to investigate the relationships among organizational context of climate and structure, KM and innovativeness from the perspective of social capital and social network. The findings suggest that KM is positively related to firm innovativeness. Further, this effect is positively moderated by supportive climate and decentralized, integrated and less formalized structure. It indicates that innovative and supportive climate and less formal structure are positively related to KM as it allows more decentralization and integration. Oluikpe (2012) explored the development of a KM strategy at the Central Bank of Nigeria (CBN). The need to align KM strategy with business strategy was identified as critical to the success of KM. It was discovered that focusing KM on the bank’s payments system process helped create value and drive business results. A combined approach of codification and personalization was adopted for the KM program of CBN. The strategy adopted involved using a two-pronged approach of communities of practice and a functional portal to drive KM. The paper identifies that this strategy is adding value to the organization and increasing knowledge flows across a dispersed and distributed work environment. According to Trehan and Kushwaha (2012), educational institutions play a key role in knowledge creation. The TK that academic staff creates or gains is embedded in their minds and constitutes the 52

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

storehouse of an educational institution’s intellectual capital. The paper is an attempt to explain KM framework which can be used in different B-schools in order to utilize full capabilities of KM. The new breed of management professionals need to be more aware about latest developments in business and also efficiently tackle multidisciplinary problems in order to face global competition.

Category-Wise Gap The studies in this category particularly provide insight into the various approaches and related methods adopted to arrive at certain conclusions. They also provide a rich source of tools which may be subsequently adopted in the future researches to design a framework for research and implement subsequently. These may help the researcher in ideating the research design so as to derive conclusive outcomes with a preconceived research construct. The KM outcome-oriented direction for further research is as follows: • Study the soft asset-based dynamic capabilities of the firm to understand their role in diversification, adaptability and intransigence, etc. • Study the connections between KMA and competitiveness using Porter’s value chain and the like. • Study how organizations realize with time and experience the value and impact of KM. • Study the relation between duration of value for any piece of knowledge and the organization’s responsibility to understand the impact on effective deployment of KM, subjectively in an industry or region. • Study the implementation of futuristic, continuous measuring process for evaluating performance. • Study the organizations subjectively to understand, identify and apply appropriate metrics as per requirement. Due to the absence of well-established metrics and standard measures, knowledge managers are still struggling with justifying how their budgets are contributing to the corporate bottom line. • Study the relation between organization structure and dynamics on KM and firm’s innovativeness in the Indian context. • Evaluate for specific cases—how the combined approach of codification and personalization may add value to the organization through increased knowledge flows across dispersed work environment. Some tools proposed in the above studies may be adopted in diverse contexts for future research on KM-based practices and their outcomes: • The knowledge chain model that identifies five primary and four secondary KMA as sources of competitive advantage (analogous to Porter’s value chain and also grounded in a descriptive KM framework developed via a Delphi study involving Understanding Researchable Issues in Knowledge Management: A Literature Review

53

international KM experts), and organizing the outcomes of KM according to the PAIR model, i.e., competing via knowledge activities that yield better productivity, agility, innovation or reputation as suggested by Holsapple and Singh (2003). • The quiz for assessing an organization’s current KM progress designed by O’Dell et al. (2003) may be used as a guideline in further researches in determining the current status of KM in an organization. • The framework on knowledge required to deliver competent work of competitive quality at different task complexities; and intelligent capital matched with corresponding capability to act effectively as suggested by Wiig and Jooste (2003). • The dimensions of innovation strategy which an organization must focus on to transpire from traditional business planning to innovative strategizing and applying the idea of systematic presentation of the globe on a flat surface (as in Atlas) to business planning and innovation strategy using techniques of mapping, scaling and compass. This may be adopted in designing a KM system for any subject (industry/ company) of study, as suggested by Amidon and Mahdjoubi (2003).

Role of Organization Culture in Knowledge-Based Performance (OC-KM Paradigm) A knowledge organization must be a learning organization where the entire firm learns while it works and is able to quickly adapt to the market and the environmental changes. The work culture must value and encourage knowledge sharing. In the knowledge era, such requirements pose challenges/barriers/problems and finding solutions to them is an area of current research. Theriou and Chatzoglou (2008) proposed a conceptual framework on enhancing performance through best HRM practices, organizational learning and KM. They proposed how best HRM practices can influence performance and that KM and organizational learning play their unique role in creating OC, which leads to superior performance. The study focuses on the relationship between HRM practices and performance, KM, organizational learning capabilities and organizational capabilities. Supyuenyong et al. (2009) studied enterprise resource planning service providers in Thailand to understand the influence of Small and Medium-Sized Enterprises (SMEs) characteristics on Knowledge Management Processes (KMP). The analysis demonstrates that in general, ownership and management structure, culture and behavior characteristics of SMEs have a more positive effect than other SME characteristics on KMP. System, process and procedure, customer and market characteristics have a more moderate effect. Human capital management hinders rather than facilitating KMP. Tseng (2010) studied the correlation between organizational culture and knowledge conversion on corporate performance in a Chinese-centric set of societal, cultural and linguistic attitudes and behavior. The result of the study indicates that an adhocracy culture enables knowledge conversion and enhances corporate performance more than clan and hierarchical culture. Thus, if an organization can nurture an adhocracy culture, knowledge workers can learn, feel comfortable, be creative and improve corporate performance and increase organization’s value. 54

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

Jarrar and Zairi (2010) identified the Critical Success Factors (CSF) and best practices of KM through analysis of the experiences of several organizations, the methodologies pursued, IT support used, structures employed, and results achieved. They concluded that in this evolving knowledge environment, both individuals and organizations must have one source of competitive advantage: intellectual capital. This represents an individual’s (or organization’s) accumulated knowledge and know-how, coupled with the ability to decant this into a system to create value. The analysis resulted in a high level framework for KM implementation and a culmination of best practices. It is important to remember here that successful KM is 10% systems and IT and 90% people and culture. Siddique (2012) made the first systematic and comprehensive attempt at reporting baseline data on KM adoption in the UAE. A survey research design was used to collect data on KM practices of a sample of companies based in the Emirates of Dubai and Abu Dhabi. It is inferred that importance of KM practices is gradually being recognized in the UAE and several organizations have initiated a number of KM-related programs. Most KM initiatives are focused on explicit knowledge, and companies are investing significant resources in building their ICT infrastructure. The study documents the importance of a company-wide KM strategy, top management commitment, proactive HRM policies, and a supportive cultural environment as the CSF to advance KM practice and theory in the UAE. Khakhian et al. (2012) surveyed 150 employees of Saipa Malleable Company in Iran at different managerial positions to provide an initial understanding and pave the way for further research in this area. They investigated the predicting role of culture attributes (trust, open leadership climate, learning from failure and culture of altruism) with reference to KM practice. Organizational culture has an extremely huge impact on KM but it is underestimated, which may, as a result, even lead to a failure. Future research may focus on other important areas of organizational culture (autonomy, power sharing, expertise and mentoring) and KM process attributes (knowledge capitalization, sharing, transformation and capturing).

Category-Wise Gap The following issues have scope for further research: • Study how the interrelation between best practices, KM and organization learning helps to create a positive OC. • In the context of SMEs in India, the influence/impact of operational and management characteristics on KMP may be studied. • Study the impact of OC and structure on knowledge conversion process and ultimately OP, in the Indian context. • Develop a framework for KM best practices to establish how the intellectual capital of an organization, along with its ability to apply it, creates value. • Study the interplay of company-wide KM strategy, top management commitment, HR policy and OC for successful KM implementation. Understanding Researchable Issues in Knowledge Management: A Literature Review

55

• Focus on the dynamics between OC’s elements (autonomy, power sharing, expertise and mentoring) and KM process attributes (knowledge capitalization, sharing, transformation and capturing).

Impact of Knowledge Management on Organization Performance (KM-OP Paradigm) Chen and Mohamed (2007), in an empirical study on interactions between four broad KMA— knowledge responsiveness, knowledge acquisition, knowledge dissemination and knowledge utilization—in construction business in Hong Kong, inferred that knowledge acquisition and utilization play a paramount role in the development of organizational KA. The higher the intensity of these two activities, the larger is the organizational knowledge pool which in turn demands greater knowledge dissemination capacity. This enables more active and intense response to market changes and client’s needs, thus facilitating and stimulating acquisition and utilization of new TK and improving organizational business performance. Sigala and Chalkiti (2007) through a study on improving performance through TK externalization and utilization in the context of Greek Hotel industry inferred that an increased unfamiliarity of the hotels with TK eliminated their activities for externalizing and utilizing TK and enhancing business performance. Khalifa et al. (2008) conceived a contingency perspective towards KMS success in the context of Chinese firms that had acquired KMS applications. The empirical results from the study provided strong support for the proposed research model— KMS usage has both direct and indirect effect on OP. Further, organizational agility and innovativeness were confirmed as important mediators (contingent factors) of KMS effect. Ho (2009) researched the relationship between KM enablers and performance conceptually to conclude that among KM enablers, the factors—strategy and leadership—appear to have the most positive relationship in the KM process performance indices. The importance of performance indices in knowledge creation and internalization, on the operational and customer side, show a positive significant relationship in judging the importance of financial performance index. Kruger and Johnson (2011) affirmed a correlation between KM maturity and Organizational Performance (OP) for a set of nine organizations distributed over three economic sectors (industrial groups) in South Africa. They evaluated the relationship between the two constructs in an extremely diversified setting to reveal that six out of eight companies which recorded positive growth in KM maturity also recorded positive year-on-year growth in OP. The company recording negative growth in KM maturity also recorded negative yearon-year growth in OP. Kamhawi (2012) developed a “Knowledge Management Fishbone: A Standard Framework of Organizational Enablers”, with reference to mid- and top-level managers from the top 81 Bahraini businesses. The fishbone model spine positioned KMA as the first level output, leading to innovation as the second, which in turn impacts the organization’s level of agility, and finally links to performance as the head of the skeletal model. He explained that building KM capabilities does not directly increase organization’s performance. Innovation and agility are the intermediate variables in between KMA and 56

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

performance. The CSF are OC and training for innovation, and KM strategy and Business Process Reengineering (BPR) for agility. Chang et al. (2012) studied “Factors Affecting Knowledge Management Success: The Fit Perspective”, in the context of an aerospace company’s 12 sub-units in Taiwan to conclude that the ‘fit’ among KMP, KMS capabilities and task characteristics can improve KM performance. It also reveals that the ‘fit’ significantly affects knowledge satisfaction, knowledge quality and creativity for sub-units performing focused, process-oriented and broad processoriented tasks. The findings reflect that individuals within organizational sub-units should use the four KMP (socialization, externalization, combination, and internalization) of appropriate level to generate new knowledge to accomplish their task. (KM-OP) organizations need to establish mechanisms to ensure their governance to establish and sustain their KM programs. KM programs require business integration, senior management involvement and decision-making authority.

Category-Wise Gap Certain constructs and directions identified from the above studies, which may be considered for future research in KM-OP paradigm are as follows: • Compare the relation/interaction between KMA (like knowledge acquisition and knowledge dissemination) and OP for a diverse set of organizations. • Study the relation of TK explication and utilization process with employees’ perception towards KM. • Study how organization’s innovativeness, agility and other contingent factors affect the impact of KMS on OP. • Study the role and impact of business strategy and leadership approach on knowledge-based performance in the Indian context/a specific industry. • Test the role and impact of organization enablers—innovativeness and agility— on knowledge-based OP. Also evaluate the CSF like OC, training and development, strategic issues and BPR. • A research construct for a fit among KMP, capabilities and KM performance may be tested in the context of a non-engineering firm/service-oriented company.

Metrics to Measure the Impact of Knowledge Management Practices The worth/value of knowledge and intellectual capital is difficult to measure and represent on the accounting systems of most businesses. Problems hidden in the ordinary accounting systems may be explored to yield valuable information. This information may be used to construct strategic decisions related to expenditure and income from new investments in different areas of business. Not many widely accepted measuring scales/metrics are available to establish the value/worth of KM in an organization. Development of metrics and technology-based implementation of the quantitative methods to analyze subjective data, acquire and represent human knowledge, and AI-based platforms to implement KM Understanding Researchable Issues in Knowledge Management: A Literature Review

57

development and analyze the impact of KM-based practices on OP/Outcome are some of the researchable issues in this direction. Lee et al. (2005) proposed a new metric, KMPI, for assessing the KM performance of a firm at any point of time in a study conducted in KOSDAQ market in Korea. They affirmed that when Knowledge Circulation Process (KCP) efficiency increases, a KMPI increase shows that the firm is knowledge-intensive. Statistical results show that the proposed KMPI can represent KCP efficiency through three financial performance measures. KMPI is defined by the researchers as a logistic function having five components that can be used to determine the efficiency of KCP: knowledge creation, knowledge accumulation, knowledge sharing, knowledge utilization and knowledge internalization. The empirical results show that the five components of KCP significantly affected the KMPI, which in turn represented the quality of organizational knowledge that was utilized in a wide variety of decision making in the firm. Further, the metric has been associated with three financial measures: stock price, price earnings ratio (PER), and R&D expenditure. Tseng (2008) further confirmed the validity of the KMS performance measure index, having studied a list of 500 large corporations in Taiwan using the new metric proposed by Lee et al. (2005) for assessing the KMS performance. The management-oriented conceptual framework describes the influence of KMS performance indicators (both financial and non-financial) in implementing the KMS. It infers that as the efficiency of the three critical factors, namely, KMS strategy, plan and implementation increases, KMS performance is enhanced. Crnkovic et al. (2006) explored the Knowledge Management Index (KMI) as a performance diagnostic tool with a purposive sample of European participants from the University at Albany/Zurich, Graduate School of Business Administration, Executive MBA program, who served as mid-level managers, upper-level executives and directors. He made a holistic approach to KM that relates key KMP and CSF needed to successfully implement it. They based the study on a metric which may depict the health of KM in an organization taking into account as many facets as possible. This metric is based on the following assumption in every organization: there is persistent interaction between KMPs (knowledge identification, knowledge elicitation, knowledge dissemination and knowledge utilization) under the influence of CSFs like technology, leadership, culture and measurement orchestrated by actors like employees, customers, partners and the environment of the organization. Grimaldi and Cricelli (2009) defined a theoretical model “Hierarchical Assessment Index (HAI)” that assesses and measures the intangible asset contribution to company performance, keeping in focus the elements that reflect success factors and are critical to business strategy and value creation. The strategic intangible assets of the company have been divided into value drivers and a series of measurement indicators to describe the characteristics of each aspect of performance. Singh and Soltani (2010) conducted a study in 10 IT companies in north India to reveal that KMI for awareness and commitment is very high as per the predefined rating scale, but involvement of top management in allocating the necessary resource flow to initiate and sustain the necessary KM practice is needed. It is clear that people are aware of the importance 58

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

of documentation to some extent, but a lot needs to be done in this field. Only very critical information is documented and maintained in archives, whereas general information (30%40% of daily work input) is not documented. There should be a mechanism through which the ideas of engineers/programmers can be implemented and translated into tangible benefits. Goldoni and Oliveira (2010) proposed a KM metric for software development companies for KM process phases of creation, storage, dissemination, utilization and measurement. The study infers that depending on KM objectives and motivations, different companies may select different implementation approach to handle specific challenges. Differences in Company A and Company B can be related to the KM process adopted. Based on the perception of the interviewees, it is possible to affirm that relevance of a metric depends on the organization’s context and the existence of a structured KM process. The process metrics can be linked to KM process phases and the organization should contemplate both quantitative and qualitative metrics. Sharma and Djiaw (2011) worked towards realizing the strategic impact of Business Intelligence (BI) tools in a BI unit of a global IT consultancy firm to establish that organizations can leverage BI tools effectively and transform their core competencies into a competitive advantage. A major finding in the study was that despite the use of Balanced Scorecard (BSC) as a service offering, the firm lacked a measurement system to manage and guide the effective use of BI tools internally. The BSC must align strategy and execution to increase the effectiveness of BI tools through mapping of each BI tool into the BSC. A measurement of each strategic objective of BI tool is a must to determine the level of success in achieving them and thus increase the corporate performance. Schroeder et al. (2012) investigated the KM governance mechanisms organizations use to guide and control their KM programs. The research seeks to contribute to a better understanding of the governance of KM and to support organizations in the development of their KM programs. The analysis identified a range of structural, process and relational mechanisms that are critical for governing an organizational KM program. Different patterns among the KM governance mechanisms are identified which lead to the development of generic KM governance typologies.

Category-Wise Gap Both KM and KM metrics implementation are in their infancy stage as compared to other organization processes. The research papers studied in the category may be used as a starting point to ideate parameters, constructs, etc., vital to measure KM performance at any specific industry/sector. The following directions may be considered for further research in the category: • Develop a comprehensive scale/index to evaluate the effective implementation of KCP in an FMCG company for financial and non-financial performance. Further, the CSF like suitable KMS strategizing, planning and implementation may also be evaluated. • Test the viability of the HAI proposed by Grimaldi and Cricelli (2009) in specific sectors of industry. Understanding Researchable Issues in Knowledge Management: A Literature Review

59

• The IT sector in India may be considered as the subject for study as it is essentially engaged in facilitating KM implementations in any sector/industry, being the sole enabler (KMS invariably requires an IT platform to operate). • Establish a metric/model to measure the KM performance of any organization/ industry through a study of the interaction between the KMP (knowledge identification, elicitation, dissemination and utilization), CSF (technology, leadership, culture and measurement) and actors (employees, customers, partners and environment). • Establish a qualitative-cum-quantitative approach to develop a metric to measure and evaluate the impact of KM process for software development companies. • Study the strategic impact of BI tools on the core competencies and strategic advantage of a company. • Analyze the structural, process and relational mechanisms of KM governance.

Discussions and Suggestions on the Researchable Issues KM issues and practices, and their implications are a broad area for research. Both academics and industry have been gaining interest in knowledge-based practices. Some specific dimensions, issues and methods have been suggested in this paper which have a vast scope for further research and developmental studies. Through an organized literature survey and review, as mentioned in the predetermined literary research objectives, certain gaps have been identified wherein further research may contribute both objectively and subjectively, and thereby towards the field of KM. The critical elicitation is stated below: In this paper, most of the studies discussed are from Social Sciences Journals on KM published on Emerald, Elsevier and Springer. We have narrowed down the focus of the literature review, as too broad a category on KM issues and practices would require extensive background knowledge for studying, classifying and comparing these studies. This paper makes a brief review of studies on KM from the late 1990s onwards to the present. The paper is based on the scope of the published materials read, i.e., the limited knowledge of the author has limited the scope of this paper. Besides, the other academic journals listed in the Social Sciences Citation Index (SSCI) and reports have not been reviewed. This has limited the exploration of information. Nevertheless, non-English publications have not been considered in the survey. Therefore, the influence of different cultures on the development of KM issues and practices has been ignored. The prominent research works in the area of KM, classified into seven broad dimensions are discussed in the paper. It is to be noted that the first three dimensions are quite fundamental and related to foundational research. Most of the radical works in these dimensions have been done in the late 1990s and early 2000s. However, the later four dimensions are processoriented dimensions. Most of the KM research in the last one decade has concentrated on 60

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

the process orientation where OC is an all-encompassing determinant for KM-based performance.

Suggested Directions for Further Research Understanding the dynamics of knowledge managers’ attitude and attributes vis-à-vis evolution of the meta-processes/business practices: Developing a framework to study KM, mapping of the organization’s knowledge process to identify the key actors and how they contribute to the ontological growth of the subject shall serve towards strong fundamental research. Case-based, industry-specific initiative: Adoption of a micro-level approach to undertake a sample survey/case analysis to identify the KM elements; establishing an empirical model to redefine the relationship among the KM elements/factors and study its impact on the organization’s performance may be considered to come up with viable research constructs. Further to this, one may structure a process-based/activity-based knowledge map for the organization. Corporate vs. Personal Knowledge Management: Future researches may study the gap, if any, between CKM and PKM posing a hindrance to the organization’s KM process efficiency. For this, one may study the factors responsible for KM system’s limitations (assimilation and dissemination features), process adaptability, i.e., conversion of meta-process to KMS process, inclusive of both individual level and corporate level. An integrated approach to both people and technology: In this paper, we have reviewed studies on KM issues categorically based on seven different dimensions. The success of KM process and KM-based practices depends on both technology and behavioral factors. The specific human problems or technical requirements of any trade, as the case is, must be investigated, identified and defined through Delphi technique, expert interviews, CSF method, questionnaire methods, statistical methods, etc. KM issues must be addressed as an integration of both technology and people. Most studies mentioned in this paper have dealt with any one aspect. In future, an integrated approach to research may be undertaken to include both technical and people aspects. Other constructs and contexts: Most studies considered in the review have undertaken qualitative or quantitative method applied on limited context and construct. Other sectors not included in the purview of the context of the studies, for example, professional and consultancy services, may be researched further. Integrated methodology: The methodology adopted for research into the KM issues is qualitative or quantitative. Some studies are case research-based. Some have presented their variables and models without expert advice or consideration of human behavior in the real-world situations. Such research outcomes are difficult to implement in individuals and organizations. Again, some studies have come up with concepts otherwise excellent but without any scientific or systematic approach. Therefore, a well-integrated method—a combination of various established methods—may be a vital direction of future work on KM issues. Understanding Researchable Issues in Knowledge Management: A Literature Review

61

Interdisciplinary research: KM being an interdisciplinary issue, future developments in the KM domain may be well integrated with different technologies and other cross-disciplinary issues. This may lead to innovative methodologies to investigate the KM problems. Change management: KM implementation involves social, behavioral and technical parameters which influence/impact the success of KM applications. The routine problemsolving procedures and stagnated knowledge tends to impede change/development for betterment, learning and innovativeness in the individuals and organizations. Therefore, a continuous approach to knowledge creation, sharing, learning and storing along with systematic change management may lead to knowledge development. Organization Culture and Knowledge Management: The value and impact of KM in relation to soft asset-based capabilities like OC, etc., in the organizations may be analyzed with industryspecific set of parameters. One may also understand the aspect of timelines in the implementation and continuous evaluation of the KMP. Conduciveness of OC increases the impact of KMA (OC-KM paradigm), impact of KMA on OP and competencies (KM-OP paradigm). Developing a model/metric to measure the impact of KMA on organization’s performance and competitiveness is another direction in the KM research.

Conclusion Implementation of KM and knowledge-based practices is extremely limited in almost every sector, public and private, in India. Organizations that have implemented KM-based operations have rarely achieved their preset objectives due to faulty implementation strategies and nonconsideration of the factors driving the process. KM exploded into prominence in the mid1990s and is already a big business, growing explosively in the developed nations. KM issues have been widely discussed in literature. Yet there is less documentary evidence pertaining to KM adoption, practice and innovation in the Indian context, in particular. KM practices are still in their infancy stage in India. It is a relatively new and young research area in the Indian context. The researchers, through this paper, have identified relevant gaps in KM research based on a set of categorical dimensions. These gaps provide a direction for future research in the area of KM. Present and future research in India must aim to establish through empirical, qualitative and quantitative approach, the critical relevance of KM. Also, the focus of KM research must shift to context-specific identification of strategic enablers/influencers that ensure effective implementation of KM practices. Present and future researchers in various research contexts in the area of KM may focus on the proposition: Enablers like OC, organization leadership, management philosophy, performance management and IT infrastructure enable the effective implementation of KM. Further, various sub-factors/ components within each of these factors may also be considered.

References 1. Amidon Debra M and Mahdjoubi Darius (2003), “An Atlas for Knowledge-Innovation: Migration from Business Planning to Innovation Strategy”, Handbook on Knowledge 62

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 331-351. 2. Chang Chu-Ming, Hsu Meng-Hsiang and Yen Chia-Hui (2012), “Factors Affecting Knowledge Management Success: The Fit Perspective”, Journal of Knowledge Management, Vol. 16, No. 6, pp. 847-861. 3. Chen Chung-Jen, Huang Jing-Wen and Hsiao Yung-Chang (2010), “Knowledge Management and Innovativeness: The Role of Organizational Climate and Structure”, International Journal of Manpower, Vol. 31, No. 8, pp. 848-870. 4. Chen Le and Mohamed Sherif (2007), “Empirical Study of Interactions Between Knowledge Management Activities”, Engineering, Construction and Architectural Management, Vol. 14, No. 3, pp. 242-260. 5. Conway Susan (2003), “Knowledge Searching and Services”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 69-83. 6. Crnkovic Jakov, Belardo Salvatore and Asoh Derek A (2006), “Exploring the Knowledge Management Index as a Performance Diagnostic Tool”, Systemics, Cybernetics and Informatics, Vol. 3, No. 2, pp. 26-33. 7. Dahooie Jalil Heidary, Afrazeh Abbas and Hosseini Seyed Mohammad Maothar (2011), “An Activity-Based Framework for Quantification of Knowledge Work”, Journal of Knowledge Management, Vol. 15, No. 3, pp. 422-444. 8. Davenport Dan and Sena Mark (2003), “Technologies for Knowledge Derivation: OnLine Analytical Processing”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 141-156. 9. Dove Rick (2003), “Knowledge Management and Agility: Relationships and Roles”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 309-330. 10. Drew S (1999), “Building Knowledge Management into Strategy: Making Sense of a New Perspective”, Long Range Planning, Vol. 32, No. 1, pp. 130-136. 11. Edvinsson Leif (2003), “The Intellectual Capital of Nations”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp.153-163. 12. Eppler Martin J (2003), “Making Knowledge Visible Through Knowledge Maps: Concepts, Elements and Cases”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp.189-205. 13. Goldoni Vanessa and Oliveira Mirian (2010), “Knowledge Management Metrics in Software Development Companies in Brazil”, Journal of Knowledge Management, Vol. 14, No. 2, pp. 301-313. Understanding Researchable Issues in Knowledge Management: A Literature Review

63

14. Gray Paul and Tehrani Sean (2003), “Technologies for Disseminating Knowledge”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 109-127. 15. Grimaldi Michele and Cricelli Livio (2009), “Intangible Asset Contribution to Company Performance: The ‘Hierarchical Assessment Index’”, VINE, The Journal of Information and Management Systems, Vol. 39, No. 1, pp. 40-54. 16. Hanley Susan and Malafsky Geoffrey (2003), “A Guide for Measuring the Value of KM Investments”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 369-390. 17. Heijst G, Spek R and Kruizinga E (1997), “Corporate Memories as a Tool for Knowledge Management”, Expert Systems with Applications, Vol. 13, No. 1, pp. 14-54. 18. 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, pp. 113-125. 19. Ho Chin-Tsang (2009), “The Relationship Between Knowledge Management Enablers and Performance”, Industrial Management & Data Systems, Vol. 109, No. 1, pp. 98-117. 20. Holsapple Clyde W (2003), “Knowledge and Its Attributes”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 165-188. 21. Holsapple Clyde W and Joshi K D (2003), “A Knowledge Management Ontology”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 89-124. 22. Holsapple Clyde W and Singh Meenu (2003), “The Knowledge Chain Model: Activities for Competitiveness”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 215-251. 23. Jarrar Yasar F and Zairi Mohamed (2010), “Knowledge Management: Learning for Organisational Experience”, European Centre for Best Practice Management, Research Paper, RP-ECBPM/0021. 24. Jennex Murray E and Olfman Lorne (2003), “Organizational Memory”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 207-234. 25. Johannessen J A, Olsen B and Olaisen J (1999), “Aspects of Innovation Theory Based on Knowledge-Management”, International Journal of Knowledge Management, Vol. 19, No. 2, pp. 121-139. 26. Kamhawi Emad M (2012), “Knowledge Management Fishbone: A Standard Framework of Organizational Enablers”, Journal of Knowledge Management, Vol. 16, No. 5, pp. 808-828. 64

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

27. Kayworth Timothy and Leidner Dorothy (2003), “Organization Culture as a Knowledge Resource”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 235-252. 28. Khakhian Yokabed Beik, Asalalizadeh Pardis, Javanmardi Mohammad and Maleki Tahereh (2012), “A Case Study on the Relation of Organizational Culture and Knowledge Management Practices (Knowledge Creation)”, African Journal of Business Management, Vol. 6, No. 16, pp. 5587-5592. 29. Khalifa Mohamed, Yan Yu Angela and Shen Kathy Ning (2008), “Knowledge Management Systems Success: A Contingency Perspective”, Journal of Knowledge Management, Vol. 12, No. 1, pp. 119-132. 30. Kruger Cornelius Johannes (Neels) and Johnson Roy D (2011), “Is There a Correlation Between Knowledge Management Maturity and Organizational Performance?”, VINE, The Journal of Information and Knowledge Management Systems, Vol. 41, No. 3, pp. 265-295. 31. Lee Kun Chang, Lee Sangjae and Kang In Won (2005), “KMPI: Measuring Knowledge Management Performance”, Information & Management, Vol. 42, No. 3, pp. 469-482. 32. Leibowitz J (2001), “Knowledge Management and Its Link to Artificial Intelligence”, Expert Systems with Applications, Vol. 20, No. 1, pp. 1-6. 33. Leibowitz J and Wright K (1999), “Does Measuring Knowledge Make Cents?”, Expert Systems with Applications, Vol. 17, No. 2, pp. 99-103. 34. Liao S H (2002), “Problem Solving and Knowledge Inertia”, Expert Systems with Applications, Vol. 22, No. 1, pp. 21-31. 35. Liao S H (2003), “Knowledge Management Technologies and Applications—Literature Review from 1995 to 2002”, Expert Systems with Applications, Vol. 25, No. 2, pp. 155-164. 36. Malafsky Geoffrey P (2003), “Technology for Acquiring and Sharing Knowledge Assets”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 85-107. 37. McKeen James D and Staples D Sandy (2003), “Knowledge Managers: Who They Are and What They Do”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 21-41. 38. Nonaka I and Takeuchi H (2005), “SECI Model”, October, available at http:// www.12manage.com/methods/nonaka/seci.html 39. Nonaka I, Umemoto K and Senoo D (1996), “From Information Processing to Knowledge Creation: A Paradigm Shift in Business Management”, Technology in Society, Vol. 18, No. 2, pp. 203-218. 40. O’Dell Carla, Elliott Susan and Hubert Cindy (2003), “Achieving Knowledge Management Outcomes”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 253-287. Understanding Researchable Issues in Knowledge Management: A Literature Review

65

41. O’Leary Daniel E (2003), “Technologies for Knowledge Assimilation”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 29-46. 42. Oluikpe Paul (2012), “Developing a Corporate Knowledge Management Strategy”, Journal of Knowledge Management, Vol. 16, No. 6, pp. 862-878. 43. Polanyi M (1966), The Tacit Dimension, Routledge and Kegan Paul, London. 44. Rahe Martin (2009), “Subjectivity and Cognition in Knowledge Management—Literature Review”, Journal of Knowledge Management, Vol. 13, No. 3, pp. 102-117. 45. Romer Paul M, as interviewed by Kurtzman Joel (2003), “The Knowledge Economy”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 73-87. 46. Rubenstein-Montano B, Leibowitz J, Buchwalter J et al. (2001), “A Systems Thinking Framework for Knowledge Management”, Decision Support Systems, Vol. 31, No. 1, pp. 5-16. 47. Schroeder Andreas, Pauleen David and Huff Sid (2012), “KM Governance: The Mechanisms for Guiding and Controlling KM Programs”, Journal of Knowledge Management, Vol. 16, No. 1, pp. 3-21. 48. Schultze Ulrike (2003), “On Knowledge Work”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 43-58. 49. Sharma Ravi S and Djiaw Vironica (2011), “Realizing the Strategic Impact of Business Intelligence Tools”, VINE, The Journal of Information and Knowledge Management Systems, Vol. 41, No. 2, pp. 113-131. 50. Siddique C Muhammad (2012), “Knowledge Management Initiatives in the United Arab Emirates: A Baseline Study”, Journal of Knowledge Management, Vol. 16, No. 5, pp. 702-723. 51. Sigala Marianna and Chalkiti Kalotina (2007), “Improving Performance Through Tacit Knowledge Externalization and Utilization”, International Journal of Productivity and Performance Management, Vol. 56, Nos. 5 & 6, pp. 456-483. 52. Singh Abhilasha and Soltani Ebrahim (2010), “Knowledge Management Practices in Indian Information Technology Companies”, Total Quality Management, Vol. 21, No. 2, pp. 145-157. 53. Smith Heather A and McKeen James D (2003), “Valuing the Knowledge Management Function”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 353-368. 54. Spender J C (2003), “Knowledge Fields: Some Post 9/11 Thoughts about the KnowledgeBased Theory of the Firm”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 59-71. 66

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

55. Staab Steffen, Studer Rudi and Sure York (2003), “Knowledge Processes and Meta Processes in Ontology-Based Knowledge Management”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 47-67. 56. Stone Dan N and Warsono Sony (2003), “Does Accounting Account for Knowledge?”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp, 253-269. 57. Supyuenyong Varintorn, Islam Nazrul and Kulkarni Uday (2009), “Influence of SME Characteristics on Knowledge Management Processes: The Case Study of Enterprise Resource Planning Service Providers”, Journal of Enterprise Information Management, Vol. 22, Nos. 1 & 2, pp. 63-80. 58. Susarla Anjana, De Liu and Whinston Andrew B (2003), “Peer-to-Peer Enterprise Knowledge Management”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 129-139. 59. Swan Jacky (2003), “Knowledge Management in Action”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 271-295. 60. Teece David J (2003), “Knowledge and Competencies as Strategic Assets”, Handbook on Knowledge Management, Vol. 1, Knowledge Matters, Edited by C W Holsapple, Springer, pp. 129-152. 61. Teece David and Pisano Gary (2003), “The Dynamic Capabilities of Firms”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 195-213. 62. Theriou Georgios N and Chatzoglou Prodromos D (2008), “Enhancing Performance Through Best HRM Practices, Organizational Learning and Knowledge Management: A Conceptual Framework”, European Review of Business, Vol. 20, No. 3, pp. 185-207. 63. Trehan Alpana and Kushwaha Pooja S (2012), “The Implementation of Knowledge Management System in B-Schools”, Excel International Journal of Multidisciplinary Management Studies, Vol. 2, No. 2, pp. 252-260. 64. Tseng Shu-Mei (2008), “Knowledge Management System Performance Measure Index”, Expert Systems with Applications, Vol. 34, No. 1, pp. 734-745. 65. Tseng Shu-Mei (2010), “The Correlation Between Organizational Culture and Knowledge Conversion on Corporate Performance”, Journal of Knowledge Management, Vol. 14, No. 2, pp. 269-284. 66. Tsui Eric (2003), “Tracking the Role and Evolution of Commercial Knowledge Management Software”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 5-27. Understanding Researchable Issues in Knowledge Management: A Literature Review

67

67. Wei Chih-Ping, Piramuthu Selwyn and Shaw Michael J (2003), “Knowledge Discovery and Data Mining”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 157-189. 68. Wiig K M (1997), “Knowledge Management: Where Did It Come and Where Will It Go?”, Expert Systems with Applications, Vol. 13, No. 1, pp. 1-14. 69. Wiig K M and Jooste Adriaan (2003), “Exploiting Knowledge for Productivity Gains”, Handbook on Knowledge Management, Vol. 2, Knowledge Directions, Edited by C W Holsapple, Springer, pp. 289-308. 70. Wiig K M, Hoog R and Spex R (1997), “Supporting Knowledge Management: A Selection of Methods and Techniques”, Expert Systems with Applications, Vol. 13, No. 1, pp. 15-27. 71. Wilkins J, Wegen B and Hoog R (1997), “Understanding and Valuing Knowledge Assets: Overview and Method”, Expert Systems with Applications, Vol. 13, No. 1, pp. 55-72.

Reference # 29J-2015-10-03-01

68

The IUP Journal of Knowledge Management, Vol. XIII, No. 4, 2015

Copyright of IUP Journal of Knowledge Management is the property of IUP Publications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.