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The recent literature grounded on the resource and knowledge-based view of the firm, has widely outlined the importance of knowledge assets as well as of the management approaches of their development. However, only few contributions have investigated the mechanisms by which these resources interact to sustain company’s value creation dynamics. In particular, there is a lack of approaches suitable to disentangle those mechanisms and to explain how knowledge assets cluster and interplay in improving organisational performance. A clear understanding of how knowledge assets take part in value creation allows to identify those knowledge assets which, due to their critical role in achieving the company’s performance objectives, need to be managed and appropriately exploited. This paper proposes a model, based on the analytic network process (ANP) methodology, to disclose and assess how knowledge assets mutually interact and take part in company’s value creation dynamics. The application of the ANP allows to reveal and to evaluate the dependencies and inter-dependencies linking knowledge assets to organisational performance objectives and to set priorities among knowledge assets against targeted performance. The application of the model is tested by its application to the identification of the knowledge assets value drivers at the basis of NPD performances improvement within an engineering company located in South of Italy.

Increasingly, in today’s fast changing and complex economic scenario, the importance of the traditional economic and production factors considered as the engine of company’s value creation dynamics is decreasing. In particular, in the last decades, the growth of new knowledge intensive businesses and the lack of success of those companies, mainly relaying on traditional tangible assets, to comply with the new markets rules, have showed the importance of levering organization’s knowledge assets (Barney, 1991, Grant, 1991, Liebowitz, 1999, Rumelt, 1984 and Wernerfelt, 1984). In this regards, new theories of strategic management such as the resources-based view, the competence-based view and the knowledge-based view have argued that company’s sustainable competitive advantage is closely related to knowledge assets and their management. In such a prospect, managers have increasingly realised the importance of better understanding how to identify, combine, manage and deploy organisational knowledge assets in order to improve the most critical company’s performance and, as a result, to support company’s value creation dynamics. Recently, a number of theoretical and practitioner contributions stressing the strategic importance as well as the role of knowledge assets as key value drivers for company’s competitiveness has been produced (Boisot, 1998, Carlucci et al., 2004, Dierickx and Cool, 1989, Sveiby, 1997, Teece, 1998 and Teece, 2000); however only few contributions have investigated the mechanisms by which these assets contribute to create value. In particular, there is a lack of approaches suitable to disentangle those mechanisms and to explain how knowledge assets are clustered and how they interplay in improving organisational performance. Although it is almost intuitive that knowledge assets operate as a bundle of assets and as such impact on organisational performance, it seems difficult to understand how they interact and impact (Lippman & Rumelt, 1982). Grounded in the resource-based view and knowledge-based view of the firm, this paper proposes a network model, based on the application of the analytic network process (ANP) (Saaty, 1996), for disclosing and assessing how knowledge assets mutually interact and take part in company’s value creation dynamics. In a previous research, in order to analyse the links between knowledge assets and performance objectives, the analytic hierarchic process (AHP) methodology has been proposed to disclose the hierarchical relationships linking knowledge assets to organisational performance (Carlucci & Schiuma, 2007). The adoption of the AHP methodology to disclose the relationships between knowledge assets and organisational performances has shown the relevance and usefulness of adopting multicriteria decision methods to deal with the complex issue of assessing knowledge assets within organisation against performance objectives. However, the AHP methodology presents some shortcomings which are addressed by the ANP approach. In particular, one of the main shortcomings is related to the fact that AHP does not allow to handle the interactions and feedback dependencies between the elements of a decision problem. The proposed ANP-based model allows to evaluate the role and the relevance of knowledge assets for the achievement of targeted business objectives by dealing with both direct and indirect relationships linking knowledge assets to performance. The disclosure and evaluation of the intricate bundle of relationships linking performance objectives and organisation’s knowledge assets can have both theory and practice benefits. From a theoretical point of view, this can benefit the resource strategic management research mainstreams. In fact, as underlined by Carmeli and Tishler, (2004), the resource based view remains an area that lacks of practical approaches and tools to identify and manage organisational resources that may, separately and interactively, enhance organisational performances. While, from a practical point of view, this offers the development of approaches and tools to support managers in their decision making regarding the assessment and management of organisational knowledge assets. The paper is organised as follows. In the second Section, on the base of the resource-based view and knowledge-based view of the firm, the strategic relevance of knowledge assets is discussed. In particular, the interconnectedness and the dynamic nature of these assets in the value creation dynamics are addressed as well as the importance of knowledge assets for company’s competitiveness and value creation. In the third Section, an ANP-based model is proposed. The ANP is analysed as a methodology to investigate and analyse the inter-dependencies linking knowledge assets to organisational performance. In the fourth Section a case example of the application of the model is described. Finally, in the last Section conclusions and suggestions for future research are provided.

The importance attributed to the deployment and exploitation of knowledge assets to support and drive organizations’ performance improvements is proved by the attention that many companies have paid in the last decades on the implementation of knowledge assets management initiatives. The knowledge management research stream is rich of case studies and empirical researches investigating and illustrating the managers’ interest for managing knowledge within organizations against a wide range of managerial and strategic purposes. However, nevertheless the rich case record, it is still difficult to clearly assess why by managing knowledge assets companies can improve their performances and progress their value creation dynamics. In addition, it appears quite difficult to prove the return on investments of knowledge assets management initiatives due to the difficulty to rationally demonstrate and measure the benefits related to the development of knowledge assets. However, in order to fully understand if the development of knowledge assets can really make a difference within an organization, it is necessary to clarify the role of knowledge assets into the company’s value creation dynamics and to explore the direct and indirect network of relationships linking knowledge assets to organization’s performances objectives and strategic value propositions. This is an important issue first of all because not all organization’s knowledge assets have the same strategic relevance and their importance can change over time and accordingly to the evolution of the organization and of its business. Many knowledge assets within some organizations are just commodities, while in others organizations they can represent critical sources of value. The management attention has to be focused on those knowledge assets which represent strategic assets within the organization due to their relevance for the achievement of company’s business and performance objectives. This equals to understand what are the organizational knowledge assets, that is those knowledge resources which are organizational value drivers supporting the company’s ability to deliver the defined value propositions. Managers need to have in place management approaches to identify the knowledge assets grounding the achievement of the targeted value propositions. This involves the understanding of the relationships linking knowledge assets to the desired business and performance outcomes. By assessing the links between knowledge assets and value objects managers can better align investments in organizational knowledge capital for the greatest impact. In such a prospect this paper proposes a network model, based on the ANP decision making method, for disclosing and evaluating how knowledge assets take part in value creation dynamics. The model allows to disentangle the complex problem concerning the identification and the evaluation of knowledge assets driving organisation performance improvement. It lets decision makers to take into consideration that the contribution of the knowledge assets against specific performance objectives depends on both the set of performance objectives and inter-dependencies among knowledge assets as well as among performance objectives. The use of ANP through outer and inner dependencies guides decision makers to the best evaluation of the contribution of knowledge assets to performance improvement. Decision makers might intuitively feel that some knowledge assets are more important than others; however the application of a rigorous approach such as the ANP, which considers feedback and interdependency among decision factors, can help decision makers to revise their belief and, sometimes, to refocus their attention on knowledge assets more important than even the most intuitively one. This research enriches studies rooted in knowledge and resource based view mainstreams, by providing a model, established on an analytical method, for assessing weights and dynamics through which knowledge assets take part in performance improvement. It further enriches, in a complementary way, the insights of the application of the AHP methodology to map and assess knowledge assets against organisation performance objectives. The ANP-based model focuses on and solves the assessment both of interactions among knowledge assets as well as among performance objectives, driving the definition of the key knowledge assets value drivers. From the ANP perspective, the paper proposes a new exploratory application of the approach for managerial decision making. Despite the meaningful insights provided by the model, there are some limitations. One is related to the fact that ANP requires many comparisons and a bit of efforts in making judgments. For this reason, particular attention should be paid in designing the model. In order to reduce the complexity of the model, it is suggested to focus just on the relevant decisional elements, required for the evaluation. In fact even if, from an operative perspective, the use of software and group decision support systems may lessen the barriers to implementing ANP, it is always important to take into account the time ANP takes to obtain the results, the effort involved in making the judgments, and the relevance and accuracy of the results. In such a pragmatic prospect the method may appear complicated and time-consuming. However ANP is a valuable tool to management as it allows for participative inputs, provided by multiple evaluators by bringing the diverse belief systems together in a consistent and organized way. On the other hand, it should not be surprising that complex decisions may require complex methodology. About the results of the ANP application it seems important to stress that, as for any decision models, the final values that are determined should be critically analyzed. Obviously when managers make decisions based on the priorities and importance with which they have had experience, the results of ANP are particularly reliable. A suggestion for future studies concerns with the consideration of fuzziness of decision makers’ judgments. The proposed ANP-based model, ignores the fuzziness, therefore a further development of the research should be related to improve the model by introducing the concept of fuzzy set. The fuzzy extension should allow to address the issue of subjectivity particularly the fuzziness of judgment. Finally, the model is seen as open for future extension and development, especially on the basis of the results of a more widespread use in several cases.