A methodology to assess value creation in ...

A methodology to assess value creation in communities of innovation

Michele Grimaldi, Livio Cricelli, Francesco Rogo, (2012),"A methodology to assess value creation in communities of innovation", Journal of Intellectual Capital, Vol. 13 Iss: 3 pp. 305 – 330. Livio Cricelli 1, Michele Grimaldi 2 Francesco Rogo 3 1

University of Cassino, Faculty of Engineering, Via G. Di Biasio, 43, 03043, Cassino (FR), Italy [email protected] 2 University of Cassino, Faculty of Engineering, Via G. Di Biasio, 43, 03043, Cassino (FR), Italy [email protected] 3 Finmeccanica S.p.A., Product Policy, Piazza Monte Grappa, 4, 00195 Rome, Italy [email protected]

Abstract Purpose – The purpose of this paper is to present a methodology to assess the capacity of communities of innovation (CoI) to improve the value creation process. The methodology consists of a sequence of successive steps, which aim at identifying the characteristics, the influence, and the relationships between the intellectual capital (IC) elements, and finally evaluating their performance. Design/methodology/approach – The proposed methodology has been defined through the joined activity of academic researchers, experienced consultants, and community managers and is grounded on an interview-based approach. The methodology has been implemented into the CoI of Finmeccanica, the Italian leading company in the industry of high technology for aerospace, defence and security. Findings – The methodology has been shown to be suitable in singling out the factual contribution of every IC element and its direct and indirect influence on the economic performance of the CoI. Originality/value – The implementation of the methodology into the CoI of Finmeccanica has encouraged the development of a more distributed leadership which has supported the dissemination of new knowledge. The building of a sort of “knowledge marketplace” has aimed to foster a systemic open innovation by exchanging continuous learning activities from inside and outside the organization and attracting excellence into the network of CoIs. Keywords: Knowledge management, Intellectual capital, Value creation, Community of innovation, Assessment, Intellectual capital management

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A methodology to assess value creation in communities of innovation 1. Introduction The rapid evolution of information and knowledge era has forced firms to ground their value creation primarily on the intangible assets besides the traditional physical assets. Although physical and financial assets remain important, Intellectual Capital has been identified as one of the most significant key drivers of firm-level performance (Teece, 1998). Intellectual Capital and Knowledge Management theorizations share the same principles (Seleim and Khalil, 2011) while a similar conceptual foundation binds the resource-based view of the firm, the dynamic capability of the firm, and the knowledge-based view of the firm. In fact, all these three frameworks agree in asserting that the only source of sustainable competitive advantages depends on the firm’s ability to develop, use, and benefit from its knowledge and intellect through learning (von Tunzelmann, 1995; Spender, 1996; Loof and Hashmati, 2002). Another factor has shown to be decisive for the firm’s competition in the global market: the innovation. Particularly, continuous innovation is able to sustain the competitive edge in the market. The concept is not new (Shumpeter, 1934) and throughout recent years literature about innovation has been enriched with several contributions (Galanakis, 2006; Xu et al., 2010). Innovation can be regarded to as a tool of entrepreneurship (Drucker, 1993; Rothwell, 1994), or viewed as a process or as the outcome of a process (OSLO, 2005; Trott, 2005). The process perspective of innovation considers innovation as a series of interrelated activities, where new knowledge is created and used through these activities (Kline and Rosenberg, 1986). Undoubtedly, only a suitable knowledge management can help promote knowledge creation and innovation (Chu et al., 2006). Recently, some organizations have found it advantageous to put into action particular entities where individuals/employees could generate, share and utilize knowledge, both internally and externally (McFadzean et al., 2005). Reference is made to structures as Communities of Practice, X-teams and Communities of Innovation (Fuller et al., 2006; Bergman et al., 2009) which constitute the major building blocks in creating, transferring, and applying organizational knowledge in order to create value (Dahlander and Wallin, 2006). The organizations in which CoPs and CoIs are implemented can be labelled as learning organizations. CoPs and CoIs are organizational forms able to anticipate, react and lead change, complexity and uncertainty (Teece, 2007). In a learning organization, value is generated by nurturing informal relations and encouraging a free, horizontal flow of knowledge across organizational boundaries by opening new channels of communication and sustaining propagation of new ideas. A learning organization promotes native open innovation approach, explores and exploits knowledge acquired from external sources (competitors, universities, partners), and retains the best talents. The ability to become a learning organization is based on four strategic pillars (Cross et al., 2002, Cohen and Prusak, 2001): problem solving, creativity and risky behaviour, knowledge sharing, learning from experience. In literature, the management and evaluation of IC in Communities of Practice (CoP) and Communities of Innovation (CoI) in terms of their ability to contribute to value creation have been recently analyzed by researchers and practitioners (Kodama, 2002a; Lemon and Sahota, 2004; Coakes and Smith, 2007; Purani and Satish, 2007). Organizational tools and drivers of innovation of organizations have determined the proposition of suitable management and assessment of IC (van de Vrande et al., 2009). Moreover, another aspect, which has not been sufficiently explored in the assessment of the strategic impact to the value creation process, is the necessity of combining qualitative and quantitative methods and taking into account managers' opinions besides the specificity of the context (Binder and Clegg, 2007). Thus, it resulted necessary to provide assessment of how knowledge is produced and accumulated, how knowledge can be transformed into innovation and how knowledge assets are added to the firm portfolio of intangibles (Zheng et al., 2001). 2

In the light of these considerations, this research is based on the issue of assessing and managing the value creation process in CoIs. In particular, this paper aims at providing an innovative managerial methodology designed and developed to assess the performance of IC in the value creation process by singling out the real contribution of IC elements. The paper is organised as follows. Section 2 provides a literature review about the main building blocks of the methodology: the organizational model represented by the CoI; the impact of IC on the value creation process; the difference between a stock and a flow approach. Section 3 defines and analyses the methodology split into four non linear and related steps. Section 4 describes the application of the methodology on MindSh@re by Finmeccanica, which is an organizational model based on eight CoIs. Finally, section 5 highlights and summarizes the application of the methodology. 2.

CoI as an organizational tool to support value creation process

2.1 From Communities of Practice to Community of Innovation Communities of Practice (CoPs) are defined as informal networks of individuals joined in creating knowledge and sharing work roles and common contexts (Kodama, 2002b, Coakes and Smith, 2007; Kimble and Hildret, 2005; Wenger and McDermott, 2002). CoPs differ notably from conventional units of organization, such as teams or working groups. Teams and groups are task oriented and their membership is formally established; by contrast, CoPs have an informal membership and a self-organizing nature (Lesser and Prusak, 2000). A Community of Innovation (CoI) is a particular form of CoPs. A group of highly motivated individuals, made up of components from both inside and outside an organization, share a common goal, without any directives from superiors. In a CoI, several practitioners and scholars have identified the common collaborative nature of innovation in generating new products, new services and new business structures. CoIs can be considered one of the most relevant organizational forms which support innovation (Coakes and Smith, 2007; MontoroSánchez et al., 2011). In CoI, as in every knowledge-based organization, the expressions of value creation refer to intangible assets and IC. 2.2 Resources and value creation In the last two decades, the competitive environment where firms have been operating has undergone a continuous change. The variables have become numerous and today it appears ever more difficult for the firms to predict a behaviour which could adapt to the essential features of such dynamic arena. However, the problem of aiming at the reach of the best performance has not changed: firms should develop strategic measures and select those factors which could ensure - both in the short and in the long run - the achievement of their objectives. Of course, understanding how firms can compete is still of the utmost importance to apply the right strategy. In fact, organizations should follow that path which could guide them toward the superiority of their economic results respect to their competitors and pursue the value creation. Two main theorizations accounting for the modalities by which firms could acquire a competitive advantage have been proposed. The former approach assumed that the competitive advantage depended on the typology of the adopted strategies (Caves and Porter, 1977; Porter, 1980), following the vein of the Structure-Conduct-Performance paradigm (Mason, 1949; Bain, 1956). The latter, the Resource-Based Theory also defined as ResourceBased-View (RBV), affirmed that the competitive advantage relied on the characteristics of the resources detained by firms, on the firm’s capability of exploiting them, and on their distinctive competences (Penrose, 1959; Rumelt, 1984; Wernerfelt, 1984; Itami, 1987; Dierickx and Cool, 1989; Barney, 1991; Hall, 1992; Peteraf, 1993; Collis and Montgomery, 1995). This theory claimed for the resources to fulfil the criteria referred to as valuable, rare, 3

inimitable, and non-substitutable and that only if all these four characteristics of the resources were present the sustainable competitive advantage could be achieved. Successively, Amit and Schoemaker (1993) added a distinction: resources could be divided into resources and capabilities, the former being non-specific of the firm and therefore tradable, the latter, instead, pertaining exclusively to the firm (Conner and Prahalad, 1996; Barney et al., 2001). Suggestions about how it has been possible to sustain the competitive advantage at the rapid evolution of the market have derived from research work carried out by some authors, who considered as critical resources for competitiveness those characterized by a knowledge nature and knowledge processes (Barney et al., 2011). The knowledge-based view (KBV) highlighted really this kind of resources (Grant, 1991; Grant, 1996; Grant, 1997; Spender and Grant, 1996; Chaharbaghi and Lynch, 1999; Hitt et al., 2007). Following the KBV principles, firms have been encouraged to generate new resources while using the resources available within their own organizations, at the same time accomplishing activity of resource management and resource development (Teece and Pisano, 1994; Teece et al., 1997; Davenport and Prusak, 1998). Undoubtedly, the above mentioned frameworks have endorsed innovative strategic perspectives by highlighting the importance of matching any external opportunities with internal resources and capability. Intangible assets have been considered, in addition to traditional physical assets, as key resources and sources of value creation (Itami, 1987; Nahapiet and Ghoshal, 1998; McGaughey, 2002; Marr, 2005). Consequently, the acknowledgment of the role of intangible assets with their potential to create value have driven firms to reassess their capability-based strategies and integrate these complementary strengths into their resources (Molloy et al., 2011). 2.3 The impact of intellectual capital on value creation Intangible assets are also known as intellectual capital (IC) or knowledge assets. Various different terms to define either the same or different information used in relating to intangibles are spread in the literature (Kauffmann and Schneider, 2004; Choong, 2008). Intangible assets include intellectual property rights, trademarks, certain information technologies such as databases, networks with customers, academia and suppliers, and “skills” in terms of capabilities, employee competencies, routines and culture (MERITUM, 2002). More deeply, the IC constitutes the whole set of intangible assets often grouped into three components: the Human Capital (HC), which represents the knowledge, generated and owned by individuals; the Structural Capital (SC), which includes the available capabilities and the acquired knowledge mastered by the organizational structure itself; and the Relational Capital (RC), which relates to all the external relationships with stakeholders (Edvinsson and Malone, 1997; Stewart, 1997; Sveiby, 1997; Roos and Roos, 1997; Petty and Guthrie, 2000; Bontis et al., 2000; Bontis, 2001; Tan et al., 2008). Intangibles can be regarded to as knowledge assets from two different perspectives: static and dynamic. In the static perspective, intangibles represent the available level of knowledge within the organization (stocks) (Edvinsson and Malone, 1997, Sveiby 1997); in the dynamic one, intangibles represent the outcome of knowledge processes in the stock interactions (flows) (Roos and Roos, 1997; Roos et al. 2005). In broad terms, IC is comprehensive both of resources that exist at a particular point in time (a stock of IC) and of the more fluid interaction with physical and intangible resources (a flow concept) (Ricceri, 2008). Of course, strategic management of organizational knowledge should include not only IC stocks and organizational learning flows (Bontis, 1996), but also the capacity of reconfiguring and transforming the available intangible assets and of creating new knowledge concurrently (Cohen and Prusak, 2001; Teece, 2007). In this sense, IC can be considered as a basis for strategic innovation and is fundamental in the management of innovation itself (Roos et al., 2005). Thus, in advancing from a static view of firms, looking at knowledge and its assets as 4

merely participating to outline the value of the organization like any other organizational resources, towards a dynamic perspective, knowledge assumes the role of an evertransforming matter, characterized by flows. Differences between the two perspectives are identifiable in IC evaluation criteria in relation to the value creation process (Dierichx and Cool, 1989; Bassi and Van Buren, 2000; Kianto, 2007). In the former, attention should be paid to the evaluation of stocks of intangibles existing in an organization; in the latter, deep consideration should be taken in understanding how stocks are utilized and which kind of interaction verify among them (Kianto, 2007). Therefore the output of the stock approach consists of an inventory of IC elements, which provides a measure of their qualitative and quantitative contributions, while the output of the flows approach improves on the stock value of intangibles by aiming at the identification of the value they produce or create, directly or indirectly; consequently, interrelationships among knowledge stocks are examined, focusing on their influence on economic performance and managerial effectiveness, and on the value creation process itself (Cricelli and Grimaldi, 2008). As for the flow approach, a number of frameworks have been developed to interpret the mechanism by which IC components contribute to the value creation and to explain how knowledge assets are assembled and how the inter-relationships existing among stocks add value to the organisations’ performance (Ahn and Chang, 2004; Chu et al., 2006). Through this path the static analysis of IC components has given way the dynamic perspective to manage and support the value creation process (Andriessen, 2006; Carlucci et al., 2004; Martinez-Torres, 2006). Following this trace, measurement and management of knowledge assets dynamics have been proposed in order to extend the traditional method of analysis into a dynamic systemic approach (Nissen et al., 2000; Cricelli and Grimaldi, 2008; Schiuma, 2009; Solitander and Tödstrom, 2010). For the same purpose of better understanding the value creation potential and its strategy for knowledge management, firms have been recommended to specify in their reports which knowledge resources are vital value drivers through IC statements (Mouritsen et al. 2003). Hence, methodologies and guidelines adopting a flow approach to study the cause-effect dynamics among IC elements have been developed (MERITUM, 2002; FMEL, 2004; Ricceri, 2008; Incas Consortium, 2008). More specifically, some authors consider IC as the missing link between the management of intangible assets and organizational performance, and assess the firm value creation by making use of IC concept (Roos et al., 2005; Marr and Spender, 2004). This paper proposes a methodology where innovation is seen as the main catalyst of knowledge and of IC components, as well as the main source of the competitive advantage and of value creation. And this has been proven mainly for the high technologic context of the firms relying on innovation as the main strategic leverage. In consequence of the fact that innovative contributions should be carefully evaluated on the ground of their efficacy, a strategic guide has been considered necessary to address any efforts toward innovation. Managers have been therefore required for their perceptions about the most relevant value drivers of innovation. Numerous models existing in literature about IC management have been focused mainly on the quantitative analysis of the stock level. However, few of them have taken into account the quantitative analysis of the flow level and of the strategic relevance of intangible assets (Andriessen, 2006; Carlucci et al., 2004; Martinez-Torres, 2006). A quantitative analysis both of stock and flow level is herein explained and a numerical expression of the reciprocal influence of IC elements is described. Also, the methodology accounts for the strategic importance of IC elements as perceived by managers as it is up to managers to meet the dynamic evolution of value drivers properly. Moreover, the methodology allows to single out the real contribution of every IC element and its direct and indirect influence on the economic performance of the organization. 5

3. The methodology The methodology has been defined through the joined activity of researchers, experienced consultants, and community managers and is organized in four successive steps. The methodology follows an interview-based approach as it has been shown by experience that face-to-face interviews are the best tool to capture personal opinion about shared organizational aspects. This is particularly true for organizational structures like CoIs, where informality and lack of hierarchical links encourage members to achieve common objectives. The whole process is accomplished by means of the direct support of experienced external consultants (or academic researchers) together with the direct participation of CoI managers. The methodology takes into accounts managers' perception about the importance of the IC elements, their inter-relationships, and the strategic objectives of the value creation process. In details, the methodology is made of four steps. Table 1 shows the intended results of each step of the methodology.

Steps 1. Identifying the intellectual capital 2. Defining the strategic impact of value drivers

Main activities To characterize the IC and determine the relevance of IC to the value creation process of CoI. To define KPI for the IC factors and to assess the importance of value drivers in the value creation.

Intended findings - Value creation model - CoI IC factors - Value drivers definition and representation. - KPI system - Strategic impact of value drivers

3. Evaluating performance and cross-relationships of value drivers

To analyze value drivers performance and to measure the cross-relationships among value drivers.

- Performance of value drivers - Cross-Relationship of value drivers

4. Reporting on the intellectual capital

To communicate the value of IC to internal and external stakeholders and to develop management insights.

- Strategic impact – performance view - Cross relationship – performance View - IC report

Table 1- The four steps of the methodology

3.1 Step 1: Identifying the intellectual capital The first step of the methodology is based on the identification of IC components; only once they are identified it is possible to assess their value. The identification of the elements of IC and the understanding of their strategic importance require the full knowledge of firm’s strategic direction and goals. In this first step of the methodology, a CoI should determine its strategic objectives and, more specifically, which knowledge assets are essential for the business aim, in order to select the most decisive IC components for its value creation process. IC elements can be identified through conducting interviews, facilitated workshops, via mail or online surveys. This results in the identification of the so-called “IC factors”, which are those components of IC that affect the efficiency and effectiveness of the CoI value creation model (Marr, 2008). Subsequently, the critical IC factors are selected and grouped into homogenous sets, named “Value Drivers” (Andreou et al., 2007; Chu et al., 2006). In particular, by means of a bottomup process, a cycle of specific interviews allows to cluster IC factors into homogeneous sets on the basis of their pertinence to the value drivers lists of the three categories of the IC:

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human, relational and structural. The process ends only when all the IC factors are grouped into the value drivers. It is important to highlight that each IC factor could be assigned more than a value driver in consequence of their occasional slightly different meaning. However, particular attention should be focused on limiting the number of value drivers per each category (HC, SC, RC) to 3-5, in order to ease the successive steps reasonably. As a result, the representation of value drivers of a CoI (Figure 1) provides the community with an accurate picture of critical intangible resources and activities related to its strategic objectives (Andriessen, 2006; Martinez-Torres, 2006).

Figure 1 - The hierarchical structure of Value Drivers, IC Factors and KPIs.

3.2 Step 2: Assessing the strategic impact of value drivers The second step of the process deals with the assessment of the Strategic Impact (SI) of value drivers. To this purpose, the members of CoI are interviewed to express their evaluation about the importance of IC factors/value drivers for the achievement of the strategic objectives. Specifically, a numerical value is associated to each IC factor belonging to a category (HC, RC, or SC); a scale from 1 to 5 measures its influence on each value driver pertaining to that category. Then, the SI of every value driver is obtained by combining the values of IC factors belonging to each value driver i.e. by summing the relative SI of the influencing IC factors (values in the row in Figure 2).

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VD1 VD2

Human Capital Relational Capital

VD5

VD9

Structural Capital

VD8

Strategic Impact

Impact Score

IC Factor #XX

…

…

…

…

…

…

IC Factor #06

IC Factor #05

IC Factor #04

IC Factor #03

IC Factor #02

Value Driver 2 for HC

Value Driver 2 for RC Value Driver 3 for RC Value Driver 4 for RC

VD6 VD7



VD3 VD4

IC Factor #01

"Strategic Impact"

Value Driver 1 for SC Value Driver 2 for SC Value Driver 3 for SC

IC Factor Impact Value Scale: 1..2 = weak impact 3 = medium impact 4..5 = strong impact

S.I. Scale: - Low - Medium - High

Figure 2 – The assessment of Strategic Impact of value drivers.

3.3 Step 3: Assessing the performance and the cross-relationships among value drivers The third step of the methodology relates to the assessment of the performance of each value driver and refers to the hierarchical structure illustrated in Fig. 1. For each IC factors a number of Key Performance Indicators (KPIs) are identified. KPIs are specific indicators serving as direct or indirect proxy measures for evaluating the stock level of each IC factor. In virtue of their experienced role, CoIs members suggest KPIs for each IC factor. The definition of KPIs supports the understanding of IC factors and their relationships with the value creation process. Moreover, KPIs characterize and measure the performance of the IC factors, in this way indirectly determining the stock levels of those value drivers which IC factors are referred to. A bottom-up approach is carried out to assess the Performance of value drivers (Incas Consortium, 2008). More specifically, each interviewed member expresses a qualitative evaluation of every specific KPI by assigning a value from 1 to 9. Then, the evaluation assigned to KPIs are grouped into IC factors and then into value drivers to express the assessment of the performance of every value driver (Figure 3). As a consequence, the Performance of a value driver is the status of its current amount of stock. The Performance level of a value driver represents its capacity of successfully achieving the strategic objectives and of supporting the value creation process.

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VD1 VD2


VD5

VD9

Structural Capital

VD8

Performance

Level of

Performance Score

Interviewer #XX

…

…

…

Interviewer #06

Interviewer #05

Interviewer #04

Interviewer #03

Interviewer #02


Value Driver 2 for RC Value Driver 3 for RC Value Driver 4 for RC

VD6 VD7



VD3 VD4

Interviewer #01

"Performance"

Value Driver 1 for SC Value Driver 2 for SC Value Driver 3 for SC

↘ Score Scale: 1-9

LoP Scale: - Low - Medium - High

Figure 3 – The assessment of Performance of value drivers.

Successively, a Cross-Relationship (CR) assessment is carried out. This analysis helps examine the interrelationships among the different elements of the IC to evaluate value drivers as for their influence on all other value drivers (Figure 4). Managers and lower level representatives of the CoI assign every value driver a direct or an indirect influence. Broadly, the results of the CR evaluation consist in the quantification of the knowledge flows exchanged among the value drivers (Coakes and Smith, 2007; Dahlander and Wallin, 2006). The CR of each value driver is represented by the sum of the numerical values of the relationships and appears in the last column of the matrix.

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VD1 VD2


VD5

VD9

Cross Relationship

Number of Relationships

Value Driver 3 for SC



Value Driver 4 for RC




Value Driver 2 for RC Value Driver 3 for RC

Value Driver 1 for SC Structural Capital

VD8



VD6 VD7



VD3 VD4



"Cross Relationship"

Value Driver 2 for SC Value Driver 3 for SC

↗ →

Direct Influence Indirect Influence

CR Scale: - Low - Medium - High

Figure 4 - The assessment of Cross-Relationship of value drivers

3.4 Step 4: Reporting on Intellectual Capital In the final step of the methodology, all relevant information from the previous steps is gathered for further interpretation and for the deduction of other specific measures related with organisational and strategic needs. By analyzing Performance, SI, and CR of value drivers, it is possible to assess their strengths and weaknesses with respect to the value creation process. Two strategic views obtain to support the evaluation and interpretation of the data collected in the previous steps of the methodology. The first view is the “SI-Performance” matrix, which represents the synthesis between SI and Performance for each value driver (Figure 5). Each value driver is positioned within the matrix, according to its SI and Performance values. As a consequence, this view graphically expresses the amount of stock for each value driver. The positioning in the view suggests corrective actions or improvement strategies to achieve the strategic objectives from the stocks point of view.

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Figure 5 – Example of “Strategic Impact – Performance" view

The second view is the “CR-Performance” matrix, which represents the synthesis between CR and Performance (Figure 6). By comparing these two aspects this view allows to recognize which are the critical and influential value drivers. The aim of this analysis is to understand which value drivers need investment, before establishing strategic actions. As a consequence, this view graphically expresses the knowledge flows among value drivers to be leveraged. Each value driver is positioned within the matrix, according to its CR and Performance values. The positioning in the view suggests corrective actions or improvement strategies to achieve the strategic objectives from the flows point of view.

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Figure 6 – Example of "Cross Relationship – Performance" view

The main output of the last step of the methodology, which summarizes the results of the previous steps, is the final “IC Report”. This is a document containing information about the work carried out by CoIs in order to manage, sustain, and develop its contributions to the value creation process. The IC report aims at providing an internal and external account about the monitoring and the assessment of IC within the value creation process.

4. MindSh@re experimentation and results The methodology has been implemented in order to test its adoption on an environment characterized by CoIs. The implementation of the methodology has been developed on an inter-disciplinary and inter-company organizational model of CoIs, named MindSh@re. Two implementations have been conducted in MindSh@re: the former in 2009, the latter in 2010. 4.1 MindSh@re of Finmeccanica: a complex patchwork of different companies Finmeccanica is the Italian leading group in supplying high technology solutions for Aerospace, Defence and Security and is one of the top ten players in the world in this sector. Finmeccanica’s intangible resources consist of high level engineers and scientists, technological partners, such as universities and centers of excellence, internal relationships, processes and brands. The activities of technological and innovation governance of Finmeccanica involve over 75.000 people spread among several multinational companies. In Finmeccanica, the transition phases from technology to products and from products to strategies are constantly focused on the need to keep aligned strategies, organization, processes, and human resources. This is what prompts the desire to connect people in a fertile knowledge network aimed at multiplying the possibilities of sharing know-how and enabling the generation of new ideas, new products and new talent. In 2002, Finmeccanica created MindSh@re to back up this policy. MindSh@re is an extended organizational model, based on CoIs and designed to add value to the existing technological 12

knowledge within the Finmeccanica Companies, to assess knowledge resources and competencies, to share best practices, and to develop a “culture of innovation”. This project harnesses the skills and the creativity of people through several companies which share a common focus. The MindSh@re project is a disciplined, repeatable and scalable “innovation engine” by which the CoIs support knowledge management and innovation. Eight CoIs have been created, involving about 1000 experts from many disciplines on different cutting edge topics: Radar Technologies, Software Technologies, Advanced Materials, Intellectual Properties, Simulation and Training Technologies, Engineering Capabilities, Logistic Services and Homeland Security. MindSh@re has been designed as a structure which connects people within a network of units each representing public or private institutions, such as universities, research centres, defence institutions, suppliers, SMEs and competitors. Within MindSh@re new ideas, products, and talents are multiplied continuously and drive energy oriented to an innovation strategy. 4.2 The first implementation of the methodology to MindSh@re The first implementation of the methodology described above has been conducted in MindSh@re between January and April 2009 at the end of the designing phase. Thirty-two managers coming from the corporate and the operating companies have been involved. The assessments have been conducted in many forms of interactions: interviews with managers of companies, web-surveys of CoIs' members, questionnaires and workshops to receive feedbacks and to review the analysis. In the next sub-sections, the results obtained from the first implementation of the methodology are step by step presented. 4.2.1 Step 1 Following the first step of the methodology, MindSh@re value creation model has been defined, the value drivers have been singled out and its relationships with the vision and the strategy of Finmeccanica have been outlined. Then, the value drivers have been grouped into three strategic objectives that express the aims of MindSh@re. Figure 7 shows the relationships between the value drivers and the objectives of Finmeccanica.

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IC

IC FACTORS

VALUE DRIVERS

Figure 7 – MindSh@re Value Creation Model and value driver representation.

Subsequently, the list of the IC factors has been defined, as illustrated in Figure 8. In particular, for each category of IC, the IC factors have assigned to a specific value driver. As explained in the second step of the methodology, an IC factor could pertain to two different value drivers. It is important to take into account this possibility in the definition of the SI of value drivers.

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STRUCTURAL CAPITAL

RELATIONAL CAPITAL

HUMAN CAPITAL



Technology scouting and assessment Professional Competence  People technical training (VD1)  Growth of skills and vocational skills  Acquisition of strategic leadership Social Competence  Receptiveness to new technologies / (VD2) innovations, synergies, business opportunities  People creativity  Qualification and professional growth People Ability to be Innovative  People engagement & commitment (VD3)  Acquisition of flexibility  Cross fertilization External Networking  Image and increase of visibility for the (VD4) corporate  Sharing and exchange between companies  Relationships with universities and institutions Group's Companies Networking  Negotiating capacity with funding agencies (VD5)  Bargaining power (suppliers, customers, competitors)  Relationships with customers (loyalty etc.). Companies' Commitment  Relations 'less competitive' with competitors (VD6)  Relations with suppliers  Environmental policies Organizational Culture  Empowerment (VD7)  Team working  Sense of belonging to corporate  Systemic innovation Managerial Instruments,  Lateral thinking Practices & Routines  Selection criteria for people membership to CoI (VD8)  Information management  Developing a shared technical culture in the Group Knowledge Transfer Processes  Codified knowledge / best practices (VD9)  Trademarks, patents and copyrights Figure 8 – MindSh@re IC factors

Then, a definition reporting the explanation of each value driver is provided (Figure 9).

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RELATIONAL CAPITAL

HUMAN CAPITAL

C

VD

Value drivers

Definition

VD1

Professional Competence

The expertise gained within the organisation or in the employee’s career: professional training, higher education, training courses and seminars, as well as practical work experiences gained on-the-job.

VD2

Social competence

The ability to get on well with people, communicate and discuss in a constructive manner, nurturing trust-enhancing behaviour in order to enable a comfortable co-operation. Furthermore the learning ability, the self-conscious handling of critique and risks as well as the creativity and flexibility of individual participants are embraced in the term ‘social competence’.

VD3

People ability to be The ability to facilitate the innovation generation as flexibility, creativity, pro-activity etc. innovative

VD4

External Networking

VD5

Group's Companies It is the network of relationships, collaborations and co-operations between Companies inside the Group Networking

STRUCTURAL CAPITAL

VD6

VD7

VD8

VD9

It is the network of relationships, collaborations and co-operations outside the Group: Universities, Competitors, Costumers, Suppliers, Institutions etc.

Companies' Commitment

The motivation to play a part within the organisation, to take on responsibility, committed to the fulfilment of tasks and the willingness for an open knowledge exchange. Typical sub areas are for example satisfaction of achievement, being part of the organization.

Organizational Culture

The culture comprises all values and norms, influencing joint interaction, knowledge transfer and the working manner. Compliance to rules, good manners, "Dos and Don'ts" and the handling of failures are important aspects in the process. In a community of Innovation it also comprises decentralization, informality, no-hierarchical relationships and the team working, all part of the "BA" implementation.

Tools, instruments, practices and routines supporting the efforts of the leadership and therefore Managerial the success of the community activities (ex. Portal, IP@gora, MPM, Improvement Programme, Instruments, Practices & Routines the organisational structure of CFGs and Councils etc.)

Knowledge & Innovational Processes

The manner how participants exchange information, co-operate together to achieve the objectives of Knowledge Sharing and Generation of Innovation. The knowledge transfer between generations is noticeable.

Figure 9 – MindSh@re value driver definitions

4.2.2 Step 2 Following the second step of the methodology, KPIs have been determined for each value driver. The project team has selected those KPIs that best fitted with the available data to monitor the performance. Then, going ahead with the methodology, the SI of each value driver has been assessed. Specifically, Figure 10 illustrates an example of interview where one of the members has evaluated the influence of IC factors on value drivers.

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Impact Score

Strategic Impact

Social competence

2

3

2

1

1,9

LOW

VD3

People ability to be innovative

2

3

5

3

3,2

MEDIUM

VD4

External Networking

1

2

1

3

2

1,7

LOW

Group's Companies Networking

4

4

5

5

4

4,2

HIGH

VD6


3

2

4

2

3

2,6

MEDIUM

VD7


2

1

2

3

1,9

LOW

Managerial Instruments, Practices & Routines

2

2

1

4

2,3

LOW


5

3

4

3

3,9

HIGH

Human Capital Relational capital

VD2

Structural Capital

VD5

VD8 VD9

… … …

IC Factor #XX

MEDIUM

… … …

2,9

… … …

3

IC Factor #26

3

… … …

… … …

2

… … …

IC Factor #03

3

IC Factor #16

IC Factor #02


VD1

IC Factor #15

IC Factor #01

"Strategic Impact"

IC Factor Impact Value Scale: 1..2 = weak impact 3 = medium impact 4..5 = strong impact

S.I. Scale: - Low - Medium - High

Figure 10 – An example of assessment of the Strategic Impact of MindSh@re

4.2.3

Step 3

VD7 VD8 VD9

Structural Capital

VD6

Group's Companies Networking Companies' Commitment Organizational Culture Managerial Instruments, Practices & Routines Knowledge & Innovational Processes

Interviewer #06

Interviewer #07

Level of Performance

Interviewer #05

Interviewer #XX

Interviewer #04

Interviewer #YY

Interviewer #03

Relational capital

VD5

External Networking

Interviewer #02


VD3 VD4

Social competence

Interviewer #01 VD2

Professional Competence Human Capital

VD1

Interviewer #08

"Performance"

Performance Score

For the assessment of the Performance and Cross Relationship, the nine value drivers have been evaluated as described in the third step of the methodology. Figure 11 exemplifies an assessment form of the Performance of MindSh@re.

9

8

8

8

6

8

7

4… … … …

8

6 8,3

HIGH

9

6

7

7

8

6

2

3… … … …

6

7 5,7

MEDIUM

7

7

6

6

5

6

5

7… … … …

6

6 4,3

MEDIUM LOW

2

5

6

6

7

7

2

8… … … …

5

7 3,8

9

7

6

8

7

7

4

6… … … …

7

8 8,1

HIGH

3

3

1

9

3

2

4

2… … … …

6

5 2,5

LOW

7

8

7

8

6

4

4

4… … … …

7

7 7,1

HIGH

6

6

5

9

7

4

6

3… … … …

6

6 5,5

MEDIUM

6

7 6,5

MEDIUM

9

7

6

8

7

Score Scale: 1-9

4

5

4… … … …

LoP Scale: - Low - Medium - High

Figure 11 – An example of assessment of the Performance of MindSh@re. 17

VD4 VD5

VD7 VD8 VD9

Structural Capital

VD6

People ability to be innovative External Networking Group's Companies Networking Companies' Commitment Organizational Culture Managerial Instruments, Practices & Routines Knowledge & Innovational Processes

↗ ↗

↗


Managerial Instruments, Practices & Routines




External Networking

Social competence

Social competence

→ ↗ → ↗

↗

↗ ↗ ↗ → ↗ → ↗ → ↗ ↗ ↗ ↗ ↗ ↗ ↗ → → ↗ ↗ → ↗ →

Direct Influence Indirect Influence

Cross Relationship

VD3

→ ↗ ↗ ↗ ↗ ↗


Numeber of Relationship

VD2

Relational capital

VD1

Human Capital


"Cross-Relationship"


Similarly, Figure 12 illustrates the assessment form of the Cross-Relationship of MindSh@re.

1,0

LOW

5,0

HIGH

1,5

LOW

3,0

MEDIUM

2,0

LOW

3,5

MEDIUM

4,0

MEDIUM

6,0

HIGH

3,5

MEDIUM CR Scale: - Low - Medium - High

Figure 12 – An example of assessment of the Cross-Relationship of MindSh@re

4.2.4 Step 4 In the fourth step of the methodology, for every value driver the SI-Performance and CRPerformance matrixes have been generated. For each of these two views, it has been possible to assess strengths and weaknesses of the value drivers with respect to the value creation process. In this phase, corrective actions or improvement strategies can be put into action in consequence of the positioning of the value drivers. By analyzing the SI-Performance view (Figure 13), it is evident that the highest impacts are given by the “Group’s Companies Networking” (VD5) and “Knowledge Transfer Processes” (VD9), which are the crucial value drivers directly related both to Finmeccanica's strategy of integration and to MindSh@re CoIs, through many initiatives, such as promotion of R&D projects, IT platforms and joint initiatives about defence. Moreover, it is clear that also non strategic value drivers (VD2, VD7, VD8) need to be evaluated about their resource allocation and investment. Finally, “People ability to be innovative” (VD3) and “Companies' Commitment” (VD6) should receive attention for their growth to strengthen performances that are below average.

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Figure 13 – “Strategic Impact - Performance” view of MindSh@re

By analyzing the CR-Performance view (Figure 14), it is evident that the highest influence is given by “Social Competence” (VD2) and “Managerial Instruments, Practices & Routines” (VD8). These two value drivers are related to the mindset of MindSh@re, but are characterized by an average performance. The analysis of this view highlights the need of strengthening VD2 and VD8 in order to achieve a positive effect on all the other values drivers. On the contrary, although its Performance value is the highest, "Professional Competence" (VD1) has the lowest CR value. This can be explained by the fact that, even if excellent, people competencies are considered only as an enabling condition to the innovation and the value creation processes.

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Figure 14 – “Cross Relationship - Performance” view of MindSh@re

4.3 Implications and first results obtained from the implementation of the methodology Once the first implementation of the methodology has been completed, an internal version of the IC Report has been generated. The actions decided at the end of the first implementation are summarized in Figure 15.

VD1

VD2

Human Capital

Improvement Strategy

VD4

VD5

Relational capital

VD3


VD9

Structural Capital

VD8

Cross Relationship

Performance


Actions

Priority

no actions

LOW

HIGH

LOW

HIGH

MEDIUM

MEDIUM

LOW

MEDIUM

no actions

LOW

MEDIUM

LOW

no actions

HIGH

LOW

HIGH

no actions

MEDIUM

MEDIUM

LOW

- Introduction of Community Leader and Technical Advisor - Change the mission of Chairmen

LOW

MEDIUM

HIGH

no actions

LOW

HIGH

MEDIUM

- Review of access rights to MindSh@re Web-Portal - Newsletter for the CTO and Heads of Engineering Depts

4

HIGH

MEDIUM

MEDIUM

Launch of "Laboratorium", the web portal for the IP and Technologies marketplace

1

- Coaching and team building sessions; - Board of Mentors

3

External Networking




Managerial Instruments, Practices & Routines Knowledge & Innovational Processes

/

MEDIUM

Social competence

VD6

VD7

Strategic Impact

/ / / 2 /

20

Figure 15 – Improvement strategy of MindSh@re

Improvement actions on IC MindSh@re structure and way of operating, suggested by the Project Team and then decided by the management of the CoI, have been prioritized on the basis of their impact on the strategic objectives:  Priority 1 – creation and launch of the web portal "Laboratorium" which has shifted from the traditional end users toward the national industrial institution (Italian Confindustria).  Priority 2 – the mission of the chairmen has been changed to encourage a higher commitment from companies; therefore two new posts were created: the “CoI leader”, a sort of community general manager with expertise in talent valorisation, and the “Technical Advisor”, a scientific external expert. This fact should enable the chairmen to devote more effort in interfacing with the top management of the Operating Companies.  Priority 3 – enhanced action of coaching and team building techniques.  Priority 4 – removal of barriers for accessing to the intranet of MindSh@re, from outside and inside. Every member of MindSh@re has been authorized to access all the web-folders of all CoIs. The creation of a joint Newsletter to be sent to high level managers of operating companies, for advertising and reporting of community activities. In this connection, it is important to note that considerations about improving the behaviour of some value drivers, for instance VD9, which obtained the highest priority, have been related to the costs of the operation. In fact, the implementation of the web-portal Laboratorium and its back-office resulted more expensive than those related to the other value drivers. In summing up, the characterization of MindSh@re and its main results in terms of value creation and innovation were then made known through the official issue of the“ MindSh@re - IC Reports” at the end of the 2009. 4.4 The second implementation of the methodology to MindSh@re The second implementation of the methodology has been carried out between March and April 2010, in order to check the impact of the actions undertaken during the previous year and assess the evolution of the MindSh@re’s IC during that time. The second assessment has been completed in the same way as the first one, but the number of managers was doubled. A total of sixty-four managers of corporate, operating companies and universities participated in the second application. The procedure has been the same as in the first assessment. The most relevant changes between the two different assessments are highlighted in Figure 16, where it is possible to appreciate how some important impacts on the decisions that have been undertaken have been grasped by the methodology. Most of the attention has been paid to the changes of SI and CR values, rather than to those of the Performance values.

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Figure 16 – The view of the evolution of MindSh@re over the time.

In Figure 16, VD1, VD2, VD3, VD5 and VD7 have remained unchanged, showing only some minor deviations, which are not highlighted in figure. The first two value drivers which show substantial deviations are VD4, VD6. With regard to "External networking" (VD4), the higher Performance and CR results have depended on two factors: firstly, the greater emphasis to the new initiatives of the joint Public/Private Laboratories, which represent an innovative form of collaboration with the universities; secondly, the beginning of the collaboration with the technology broker Nine Sigma. These actions have induced a perception of the higher importance for the "Company Commitment" (VD6) and influenced innovation and knowledge sharing activities inside and outside the group, which have impacted on “Knowledge & Innovation Processes” (VD9). Furthermore, the other two value drivers that show the most significant differences in terms of performances are VD8 and VD9. As for VD8, the removal of barriers to access the documentation and repository of all communities has automatically increased the number of visits and consultations, as well as blog posts and downloads of technical documents from the MindSh@re portal. As for VD9, the effect of several actions has substantially increased the information exchange about technologies and patents (WebPortal Laboratorium), by providing the guidelines to protect and exploit intellectual property (IPR guidelines). 4.5 The benefits After having described the two implementations, participants have been asked to comment the results over the time, comparing the 2009 with the 2010 survey. It is possible to illustrate the main tangible benefits of the methodology. A first relevant result achieved by the methodology has been to provide managers of MindSh@re with a practical, structured and well-established methodology to identify the IC of the eight communities essential to support the organizational model of the project. The presentation and dissemination of the project through the IC report has created internal and external awareness of the importance of intangible assets. Those crucial assets have been 22

identified and synthesized through the definition process of IC factors, KPIs and clustering of value drivers. It is worth pointing out that the time lapse between the two assessments has been really useful to arise discussion about the evaluation of the selected value drivers and has given opportunity to generate a common language about the strengths and the weaknesses of CoIs. In order to assess the benefits derived from the proposed methodology, an analysis on the results obtained by the implementation of the methodology has been performed on the base of its contribution to the four strategic pillars characterizing the learning organizations. To this purpose, by means of specific interviews, managers have been requested to match the main outcomes achieved through the methodology with each of the four strategic pillars mentioned above (Table 2). The table shows that such benefits are the direct consequence of the ameliorative choices derived by the corrective actions as suggested by the implemented methodology. COI SUCCESS PILLARS

VDs

MINDSH@RE MAIN RESULTS

to promote teamwork for group problem solving;

VD2 VD4 VD5

- Itinerants meetings. Focus groups meet on average every 2 months and the location changes every time. This allows the CoI to bring their results closer to the operating companies, increasing the level of motivation for top managers to invest in MindSh@re.

to experiment and reward risk taking behaviour;

VD3 VD9

- External funds acquired and brought to operating companies over 50 ML euro from the CoI established networks. - 20 Corporate Projects financed by directly the corporate towards companies, over 15 ML euro - Group and individual creativity. New CoI, focus groups and laboratories spontaneously emerge from individual’s proposals. 80 percent of them are then supported by the operating companies, the others directly by the corporate.

to quickly share knowledge;

VD1 VD6

- Dissemination workshops. 80 seminars with 2,500 Finmeccanica participants and more than 1000 external participants to illustrate the new frontiers of products development. - Biannual “Big” Event. The communication of mission and vision is continuously made through events organized by each CoI, and the bi-annual MindSh@re Event where all stakeholders meet to share the knowledge cogenerated with partners, clients, suppliers. - Newsletters and brochures. Examples are: “MindSh@re Inside Edition” (from the Security Community), “Open Connection” (from the IED2 community) and “MindSh@re News” at global level. - Chairmen meetings. To increase the sharing of knowledge across CoI. The CoI “Strategic Plan” is prepared by every council and then discussed during a meeting among all the chairmen, in order to align them to the technology

roadmaps of companies.

to learn from past experience, best practices and from others.

VD8 VD7

- Highly specialized workshops. To facilitate context-specific learning processes and technological scouting, several series of seminars for the crossfertilization of ideas, and resolution of common technological problems from the different operating companies. They are open to the participation of external stakeholders. - Technology appraisals. To share the technology plans and use the same reporting appraisal tools so that knowledge sharing and cross-monitoring of performance could be easier for the operating companies. - Life long leaning. The “MindSh@re Improvement Programme” is dedicated to continuously nurture the culture of knowledge sharing and innovation through new and older people. CoI members are supported by professional facilitators. Individual experts in social dynamics energize the community and the focus groups meetings as well as virtual activities.

Table 2 – Main Results of MindSh@re highlighted by the methodology. Moreover, the participating managers have acknowledged that the benefits drawn from the methodology had to be correlated with the evolution of value drivers through the time.

23

Therefore the implementation of the methodology has provided evidence of a relevant contribution to the improvement of the value creation process and of supporting the alignment between the applied initiatives and the strategic objectives. The more important benefits obtained can be synthesised into the following three main aspects:  Distributed leadership. Chairmen, mentors and council members have been officially appointed leaders within the CoI, but in each community everybody has been encouraged to launch ideas and promote joint laboratories to cultivate and realize new ideas. Strong emphasis has been devoted to keep track of a high level of shared leadership (VD1, VD2, VD3).  Systemic open innovation. The building of the “knowledge marketplace” has aimed to nurture the ability of continuously learning from inside and outside the organization. Stakeholders have been invited to participate in the activities of CoIs as active members. The technology scouting has pursued the goal to find out and attract excellences into the network of the CoIs. Clients and suppliers have been perceived as players in the same game within MindSh@re and not considered as external entities (VD4, VD5, VD9).  Intended development goals. They have included: the fosterage of collaboration between operating companies as members of a team by sharing the outcomes of the product technology appraisal; the promotion of network and other communities across the companies; the evaluation of the opportunity of setting up common technologic platforms (VD6, VD7, VD8).

5. Conclusions In the current economy, the success and value creation of any organization is mostly driven by intangible assets. The presented study increases the understanding of the capabilities of learning organizations of sharing available intangible assets and creating new knowledge. This research considers knowledge and IC as main catalysts of innovation, as well as major sources of the competitive advantage and of value creation. A methodology has been proposed to assess and develop the value creation process of community of innovation. In particular, this methodology evaluates the quantity (stock) and quality (flows) of the IC elements, in terms of strategic impact to value creation and innovation. A strategic guide has been considered necessary to evaluate contributions to innovation carefully. To this purpose, the direct involvement of managers has shown to be of primarily importance in assessing the relevancy of the drivers of value creation process. In particular the methodology allows to single out the factual contribution of every IC element and its direct and indirect influence on the economic performance. The proposed methodology has been applied, over a period of two years, to a large community of innovation organizational model of Finmeccanica. The methodology has demonstrated to be suitable in identifying, assessing and managing the IC elements that determine the performance of community of innovation. The effectiveness and the benefits deriving from the application of the methodology have been verified by taking into account the success pillars of learning organizations. By means of the implementation of the methodology in MindSh@re, the present research has proved to be of effective strategic support in assessing and managing IC. Moreover, the structure and the flexibility of the operational steps of the methodology show features of general applicability and, at the same time, ensure that systematic assessment and management of the value creation obtain throughout the time. The methodology has a wide range of possible applications. In particular, it can be finalized both to internal management purposes and to external reporting purposes. In the former case, 24

the approach can be tailored to the specific elements of IC, which characterize the business model. In the latter case, a standardised approach will allow to fulfil the analysis of external stakeholders, such as partners, institutions, customers, governments or other communities. Future research should be dedicated to adapt the methodology to different organizational business contexts in order to obtain a larger number of empirical evidences.

6. References Ahn, J.H. and Chang, S.G. (2004), Assessing the contribution of knowledge to business performance: the KP3 methodology, Decision Support Systems, Vol. 36, No. 4, pp. 403-416. Allee, V. and Schwabe, O. (2008), Measuring the Impact of Research Networks in the EU: Value Networks and Intellectual Capital Formation, Proceedings of ECIC 2009, pp. 27-35. Amit, R. and Schoemaker, P. J. (1993), Strategic assets and organizational rent, Strategic Management Journal, Vol. 14, pp. 33-46. Andreou, A.N., Green, A. and Stankosky, M. (2007), “A framework of intangible valuation areas and antecedents”, Journal of Intellectual Capital, Vol. 8, No. 1, pp. 52-75. Andriessen, D. (2006), On the metaphorical nature of intellectual capital: a textual analysis, Journal of Intellectual Capital, Vol. 7, No. 1, pp. 93-110. Bain, J. (1956), Barriers to New Competition, Harvard University Press, Cambridge, MA. Barney, J.B. (1991), Firm resources and sustained competitive advantage, Journal of Management, Vol. 17, pp. 99-120. Barney, J. B., Wright, M. and Ketchen, D. J. (2001), The resource based view of the firm: Ten years after 1991. Journal of Management, Vol. 27, pp. 625-43. Barney, J.B., Ketchen, Jr. D.J. and Wright, M. (2011), The Future of Resource-Based Theory: Revitalization or Decline? Journal of Management, Vol. 37, No. 5, pp. 1299-1315. Bassi, L.J. and van Buren, M.E., (2000), New measures for a new era, in Morey, D., Maybury, M. and Thuraisingham, B. (Eds.): Knowledge Management: Classic and Contemporary Works, MIT Press, London, pp. 355–373. Bergman, J., Jantunen, A. and Saksa, J.M. (2004), "Managing knowledge creation and sharing-scenarios and dynamic capabilites in inter-industrial knowledge networks", Journal of Knowledge Management, Vol.8, No.6, pp. 63-76. Binder, M., and Clegg, B. (2007), Enterprise management: A new frontier for organisations, International Journal of Production Economics, Vol. 106, No. 2, pp. 409-430. Bontis, N. (1996), “There’s a Price on your Head: Managing Intellectual Capital Strategically”, Business Quarterly, Summer, pp. 40-47. Bontis, N., Chua, W. and Richardson, S. (2000), Intellectual capital and the nature of business in Malaysia, Journal of Intellectual Capital, Vol. 1 No. 1, pp. 85-100. Bontis, N. (2001), Assessing knowledge assets: a review of the models used to measure intellectual capital, International Journal of Technology Management, Vol. 3, No. 1, pp. 4160. Carlucci, D., Marr, B., Schiuma, G. (2004), The knowledge value chain—how intellectual capital impacts business performance. International Journal of Technology Management, vol. 27, pp. 575-590. Caves, R. E. and Porter, M. (1977), From entry barriers to mobility barriers: Conjectural decisions and contrived deterrence to new competition, Quarterly Journal of Economics, Vol. 91, pp. 241-262. Chaharbaghi, K. and Lynch, R. (1999), Sustainable competitive advantage: towards a dynamic resource-based strategy, Management Decision, Vol. 37 Iss: 1, pp.45 – 50. Chiesa, V., Gilardoni, E., Manzini, R. and Pizzurno, E. (2008), Determining the Value of Intangibles Assets – A study and an empirical application. International Journal of Innovation and Technology Management, Vol. 5 No. 1, pp. 123-147. 25

Choong, K.K. (2008), Intellectual capital: definitions, categorization and reporting models, Journal of Intellectual Capital, Vol. 9, No. 4, pp. 609-638. Chu, P.Y., Lin, Y.L., Hsiung, H.H. and Liu, T.Y. (2006), Intellectual capital: An empirical study of ITRI, Technological Forecasting & Social Change, Vol. 73, pp. 886–902. Coakes, E. W., and Smith, P. A. C. (2007), Developing Communities of Innovation by Identifying Innovation Champions, The Learning Organization, Vol. 14, No. 1, pp. 74-85. Cohen, D., Prusak, L. (2001), In Good Company. How social capital makes organizations work, Boston, Ma.: Harvard Business School Press. Collis D.J. and Montgomery C.A. (1995), Competing on resources: strategy in the 1990s. Harvard Business Review, Vol. Jul/Aug, pp. 118–128. Conner, K.R. and Prahalad, C.K. (1996), A resource-based theory of the firm: Knowledge versus opportunism. Organization Science, Vol. 7, pp. 477-501. Cricelli, L. and Grimaldi, M. (2008), A dynamic view of knowledge and information: a stock and flow based methodology, International Journal of Management and Decision Making, Vol. 9, No. 6, pp. 686-698. Cross, R., Parker, A. and Borgatti, S.P. (2002), Making Invisible Work Visible: Using Social Network Analysis to Support Strategic Collaboration, California Management Review, Vol. 44, No. 2, pp. 25-46. Dahlander, L. and Wallin, M. W. (2006), A man on the inside: Unlocking communities as complementary assets, Research Policy, Vol. 35, No. 8, pp. 1243–1259. Davenport, T.H. and Prusak, L. (1998), Working knowledge: how organizations manage what they know. Harvard Business School Press, Boston. Dierickx, I. and Cool, K. (1989), Asset stock accumulation and sustainability of competitive advantage, Management Science, Vol. 35, No.12, pp. 1504–1514. Drucker, P.F. (1993), Innovation and Entrepreneurship, Collins, New York, NY. Edvinsson, L. and Malone, M.S. (1997), Intellectual Capital: Realizing your Company's True Value by Finding its Hidden Brainpower, Harper Business, New York, N.Y. Federal Ministry of Economic and Labour (FMEL). (2004), Intellectual Capital statement Made in Germany – Guidelines, Harzdruckerei, Wernickerode. Fuller, J., Bartl, M., Ernst, H. and Muhlbacher, H. (2006), Community based innovation: How to integrate members of virtual communities into new product development, Electronic Commerce Research, Vol. 6, No. 1, pp. 57-73. Galanakis, K. (2006), Innovation process: make sense using systems thinking, Technovation, Vol. 26, No. 11, pp. 1222-32. Grant, R.M. (1991), The resource-based theory of competitive advantage: implications for strategy formulation, California Management Review, Vol. 33 No.3, pp.14-35. Grant, R. (1996), Toward a knowledge-based theory of the firm. Strategic Management Journal, Vol. 17 (Winter Special Issue), pp. 109-122. Grant, R.M. (1997), The knowledge-based view of the firm: implications for management practice. Long Range Planning, Vol. 30, pp. 450–454. Hall, R. (1992), The strategic analysis of intangible resources, Strategic Management Journal, Vol. 13 No. 2, pp. 135-44. Hitt, M. A., Beamish, P., Jackson, S. and Mathieu, J. (2007), Building theoretical and empirical bridges across levels: Multilevel research in management. Academy of Management Journal, Vol. 50, pp. 1385-1400. Kaufmann, L. and Schneider, Y. (2004), Intangibles: A synthesis of current research, Journal of Intellectual Capital, Vol. 5, No. 3, pp.366 – 388. Kianto, A. (2007), What do we really mean by dynamic intellectual capital?, International Journal of Learning and Intellectual Capital, Vol. 4, No. 4, pp. 342-56. Kimble, C. and Hildreth, P. (2005), Dualities, Distributed Communities of Practice and Knowledge Management, Journal of Knowledge Management, Vol. 9, No. 4, pp. 102-113. 26

Kline, S. and Rosenberg, N. (1986), An overview of innovation, in: Landau, R. and Rosenberg, N. (Eds), The Positive Sum Strategy: Harnessing Technology for Economic Growth, National Academy Press, Washington, DC, pp. 275-305. Kodama, M. (2002a), Strategic Community Management with Customers: Case Study on Innovation Using IT and Multimedia Technology in Education, Medical and Welfare Fields, International Journal of Value-Based Management, Vol. 15, No. 3, pp. 203-224. Kodama, M. (2002b), Transforming an Old Economy Company Through Strategic Communities, Long Range Planning, Vol. 35, pp. 349-365. InCas Consortium (European Commission) (2008), Intellectual Capital Statement (InCaS) – Made in Europe, European Guideline, www.incas-europe.org. Itami, H. (1987), Mobilizing Invisible Assets. Harvard University Press, Cambridge, MA. Lemon, M. and Sahota, P. (2004), Organizational culture as a knowledge repository for increased innovative capacity, Technovation, Vol. 6, pp. 483-498. Lesser, E. L. and Prusak, L. (2000), Communities of practice, social capital and organizational knowledge. In: Lesser, E.L., Fontaine M.A. and Slusher J.A. Knowledge and communities, pp. 123-131, Boston: Butterworth Heinemann. Lev, B. (2001), Intangibles: Management, measurement, and reporting. Washington, DC: Brookings Institution Press. Lööf, H. and Heshmat, A. (2002), Knowledge capital and performance heterogeneity: A firmlevel innovation study, International Journal of Production Economics, Vol. 76, No. 1, pp. 61-85. Marr, B. and Spender, J.C. (2004), Measuring knowledge assets – implications of the knowledge economy for performance measurement, Measuring Business Excellence, Vol. 8 No.1, pp.18-27. Marr, B. (2005). Perspectives on intellectual capital. USA: Elsevier Inc. Marr, B. (2008), Impacting Future Value: How to Manage your Intellectual Capital, Management Accounting Guideline, jointly published by AICPA, CMA, CIMA. Martínez-Torres, M.R. (2006), A procedure to design a structural and measurement model of Intellectual Capital: An exploratory study, Information & Management, Vol. 43, No. 5, pp. 617-626. Mason, E.S. (1949), The current state of the monopoly problem in the United States, Harvard Law Review, Vol. 62, pp. 1265-85. McFadzean, E., O’Loughlin, A. and Shaw, E. (2005), Corporate entrepreneurship and innovation part 1: The missing link. European Journal of Innovation Management, Vol. 8, No. 3, pp. 350–372. McGaughey, S.L. (2002), Strategic interventions in intellectual assets flows, Academy of Management Review, Vol. 27, No.2, pp.248-74. MERITUM (2002), MERITUM Guidelines for Managing and Reporting on Intangibles, Measuring Intangibles to Understand and Improve Innovation Management - MERITUM, Madrid. Molloy, J., Chadwick, C., Ployhart, R. and Golden, S. (2011), Making intangibles “tangible:” A multidisciplinary critique and validation framework. Journal of Management, Vol. 37, pp. 1496-1518. Montoro-Sánchez, A., Ortiz-de-Urbina-Criado, M. and Mora-Valentín, E.M. (2011), Effects of knowledge spillovers on innovation and collaboration in science and technology parks, Journal of Knowledge Management, Vol. 15, No. 6, pp. 948-970. Mouritsen, J., Bukh, P.N., Flagstad, K., Thorbjørnsen, S., Johansen, M.R., Kotnis, S., Larsen, H.T., Nielsen, C. and Kjærgaard, I. (2003), Intellectual Capital Statements – The New Guideline, Danish Ministry of Science, Technology and Innovation, Copenhagen, available at: www.vtu.dk/icaccounts.

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Nahapiet, J. and Goshal, S. (1998), Social capital, intellectual capital, and the organizational advantage, Academy of Management Review, Vol. 23 No. 2, pp. 242-66. Nissen, M.E., Kamel, M.N. and Sengupta, K.C. (2000), Integrated Analysis and Design of Knowledge Systems and Processes, Information Resources Management Journal, Vol. 13, No. 1, pp. 24-43. OSLO (2005), Guidelines for Collecting and Interpreting Innovation Data, 3rd ed., OECD, Paris. Penrose, E. T. (1959), The Theory of Growth of the Firm, Basil Blackwell, London. Peteraf, M. A. (1993), The cornerstones of competitive advantage: A resource-based view, Strategic Management Journal, Vol. 14, pp. 179–192. Petty, R. and Guthrie, J. (2000), Intellectual Capital Literature Review: Measurement, Reporting and Management Journal of Intellectual Capital, Vol. 1, No. 2, pp. 155-176. Porter, M. E. (1980), Competitive Strategy: Techniques for Analyzing Industries and Competitors, The Free Press, New York. Purani, K. and Satish, N. (2007), Knowledge Community: Integrating ICT into Social Development in Developing Economies, Ai & Society, Vol. 21, No. 3, pp. 329-345. Ricceri F. (2008), Intellectual Capital and Knowledge Management, Routledge, London. Roos, G., Pike, S. and Frenström, L. (2005), Managing Intellectual Capital in Practice, Butterworth-Heinemann, USA. Roos, G. and Roos, J. (1997), Measuring your company’s intellectual performance, Long Range Planning, Vol. 30, pp. 325. Rothwell, R. (1994), Towards the fifth-generation innovation process, International Marketing Review, Vol. 11, No. 1, pp. 7-31. Rumelt, R. P. (1984), Toward a strategic theory of the firm. In: R. Lamb (ed.), Competitive Strategic Management, Prentice Hall, Englewood Cliffs, NJ, pp. 556-570. Schiuma, G. (2009), The managerial foundations of knowledge assets dynamics, Knowledge Management Research & Practice, Vol. 7, No. 4, pp. 290-299. Schumpeter, J. A. (1934), The theory of economic development. Harvard University Press, Cambridge, MA. Seleim, A.A.S. and Khalil, O.E.M. (2011), Understanding the knowledge managementintellectual capital relationship: a two-way analysis, Journal of Intellectual Capital, Vol. 12, No. 4, pp. 586 – 614. Solitander, M. and Tidström, A. (2010), Competitive flows of intellectual capital in value creating networks, Journal of Intellectual Capital, Vol. 11, No. 1, pp. 23-38. Spender, J. C. (1996), Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, Vol. 17, pp. 45–62. Spender, J.C. and Grant, R.M. (1996), Knowledge and the firm: overview, Strategic Management Journal, Vol. 17, pp. 5–9. Stewart, T.A. (1997), Intellectual Capital: The New Wealth of Organizations, Doubleday/Currency, New York, NY. Sveiby, K. E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-based Assets, Berrett-Koehler Publishers, San Francisco, CA. Tan, H.P., Plowman, D. and Hancock, P. (2008), The evolving research on intellectual capital, Journal of Intellectual Capital, Vol. 9, No. 4, pp. 585-608. Teece, D.J. (1998), Capturing value from knowledge assets: the new economy, markets for know-how, and intangibles assets, California Management Review, Vol. 40, pp. 55–79. Teece, D. J. and Pisano, G. 1994. The dynamic capabilities of firms: an introduction, Industrial and Corporate Change, Vol. 3, pp. 537–556. Teece, D. J., Pisano, G. and Schuen, A. (1997), Dynamic capabilities and strategic management, Strategic Management Journal, Vol. 18, pp. 509–533.

28

Teece D.J. (2007), Explicating dynamic capabilities: the nature and microfoundations of (sustainable) Enterprise performance, Strategic Management Journal, Vol. 28, pp. 1319–1350. Trott, P. (2005), Innovation Management and New Product Development, 3rd ed., Pearson Education Limited, New York, NY. van de Vrande, V., de Jong, J.P.J., Vanhaverbeke, W. and de Rochemont, M. (2009), Open innovation in SMEs: Trends, motives and management challenges, Technovation, Vol. 29, No. 6-7, pp. 423-437. von Tunzelmann, G. N. (1995), Technology and Industrial Progress, Edward Elgar, Aldershot. Xu, J., Houssin, R., Caillaud, E. and Gardoni, M. (2010), Macro process of knowledge management for continuous innovation, Journal of Knowledge Management, Vol. 14, Iss: 4, pp. 573 – 591. Wenger, E. and McDermott, R. (2002), Cultivating communities of practice: a guide to managing knowledge. Harvard Business School Press. Wernerfelt, B. (1984), A resource based view of the firm, Strategic Management Journal, Vol. 5, pp. 171-180. West, R. E. (2009), What is shared? A framework for understanding shared innovation within communities, Educational Technology Research and Development, Vol. 57, No. 3, pp. 315332. Zheng, S., Zhang, W. and Du, J. (2001), Knowledge-based dynamic capabilities and innovation in networked environments, Journal of Knowledge Management, Vol. 15, No. 6, pp. 1035 – 1051.

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