Market Knowledge Management, Innovation and Product Performance

In a business environment characterized by a high level of competitiveness, the impact of new products on an organization’s revenue is an important factor. This research was developed with the objective of examining empirically the relationships between market knowledge management, innovation and the performance of new products in the market. This chapter analyzes KM (Knowledge Management) success trough a market-oriented perspective because, at the end of the day, KM success must lead to better organizational performance. The research model was generated by the combination of market knowledge models and KM success and maturity models. By means of a survey, based on 387 medium and large industrial firms, and the use of structural equation modeling, the supremacy of the competitor knowledge management process over other constructs was verified, as the most important antecedent of new product performance in the market. The results also revealed that innovation was strongly impacted from technology knowledge management and customer knowledge management.

The Relevance of Integration for Knowledge Management Success

Many organizations pursue knowledge management (KM) initiatives with different degrees of success. One key aspect of KM often neglected in practice is following an integrated and holistic approach. Complementary, KM researchers have increasingly focused on factors that determine KM success and examined whether the metrics used to measure KM initiatives are reasonable. In this article, the importance of integration issues for successful KM is analyzed by means of a case study of a KM initiative at an international consulting company. The investigations demonstrate the importance of an integrated KM approach – an integrated view of KM strategy, KM processes, KM technology, and company culture – to ensure KM success.

Advancing the Success of Collaboration Centered KM Strategy

Knowledge is today more than ever the most critical resource of organizations. At the same time it is, however, also the least-accessible resource that is difficult to share, imitate, buy, sell, store, or evaluate. Organizations should thus have an explicit strategy for the management of their knowledge resources. In this chapter we pay special attention to a KM strategy called collaboration centered strategy. This strategy builds on the assumption that a significant part of personal knowledge can be captured and transferred, and new knowledge created through deep collaboration between the organization’s members. A critical element in the collaboration centered KM strategy is the facilitation process that involves managing relationships between people, tasks and technology. We describe how the Collaboration Engineering approach with packaged facilitation techniques called ThinkLets is able to contribute to this endeavour.

Strategies for Successful Implementation of KM in a University Setting

Research has identified enabling factors and inhibitors for implementing knowledge management successfully and to accomplish its strategic objectives. However, it is important to understand how these factors interact with each other to improve or inhibit the performance. With this in mind, this chapter presents a model, based on a research study, to determine underlying relations among these factors and develop strategies implementing KM initiatives.

DYONIPOS

Traditional knowledge management is often combined with extra work to recollect information which is already electronically available. Another obstacle to overcome is to make the content of the collected information easily accessible to enquiries, as conventional searching tools provide only documents and not the content meaning. They are often based on the search for character strings, usually resulting in many unnecessary hits and no or less context information. The research project DYONIPOS focuses on detecting the knowledge needs of knowledge users and automatically providing the required knowledge just in time, while avoiding additional work and violations of the knowledge worker’s privacy, proposing a new way of support. This knowledge is made available through semantic linkage of the relevant information out of existing artifacts. In addition DYONIPOS creates an individual and an organizational knowledge base just in time.

The Effect of Organizational Trust on the Success of Codification and Personalization KM approaches

Knowledge Management (KM) initiatives are expanding across all types of organizations worldwide. However, not all of them are necessarily successful mainly due to an unfriendly organizational culture. Organizational trust is often mentioned as a critical factor facilitating knowledge sharing. For this research we took an empirical approach to validate this assumption. The purpose of this research is to explore the relationships between organizational trust, a knowledge management strategy (codification vs. personalization) and its level of success. This study was conducted among 97 US companies involved in knowledge management. A survey tool was developed and validated to assess the level of trust, the level of success and the dominant KM strategy deployed by an organization. Nine main research hypotheses and a conceptual model were tested. The findings show the impact of trust on the choice of the KM strategy as well as on the level of success.

A Relational Based-View of Intellectual Capital in High-Tech Firms

The Resource-Based View (RBV) has tried to test the role of strategic resources on sustained competitive advantage and superior performance. Although this theory has found several flaws in order to reach its objective effectively (Priem & Butler, 2001), recent proposals have suggested that these problems can be overcome (Peteraf & Barney, 2003). This solution requires paying a greater attention to the analysis of knowledge stocks, developing a mid-range theory: the Intellectual Capital-Based View (Reed, Lubatkin & Srinivasan, 2006). This mid-range and pracmatic theory allows the hypotheses development and empirical testing in a more effective way that the RBV. There is a certain degree of general agreement about the presence of human capital and organizational capital as the main components of intellectual capital, as well as about the fact that the configuration of knowledge stocks will vary from one industry and firm to another one. Taking these assumptions as a starting point, this paper explores the configuration of intellectual capital that can be empirically found on a sample of high-technology firms. Our findings highlight the importance of relational capital, which must be divided into business and alliance capital, so the strategic alliances play a relevance role in the type of firms that have been included in our research.

Assessing Knowledge Management

With growing interest in KM-related assessments and calls for rigorous assessment tools, the objective of this study was to apply SEM techniques to refine and cross-validate the KMI, a metric to assess the degree to which organizations are engaged in knowledge management (KM). Unlike previous KM metrics research that has focused on scales, we modeled the KMI as a formative latent variable, thereby extending knowledge on formative measures and index creation from other fields into the KM field. The refined KMI metric was tested in a nomological network and found to be robust and stable when cross-validated; thereby demonstrating consistent prediction results across independent data sets. The study also verified the hypothesis that the KMI is positively correlated with organizational performance (OP). Research contributions, managerial implications, limitations of the study, and direction for further research are discussed.

Validating Distinct Knowledge Assets

Identification and measurement of organizational Knowledge Management capabilities is necessary to determine the extent to which an organization utilizes its knowledge assets. We developed and operationalized a set of constructs to measure capabilities associated with management of knowledge assets identified as distinct Knowledge Capabilities (KCs) comprising the overall Knowledge Management (KM) capability of an organizational unit. Each KC represents a distinct kind of knowledge that requires different organizational process and technological support. This delineation of knowledge allows targeted improvement to a specific KC. We present validation of these capability constructs with empirical evidence from two separate business units in a large semi-conductor manufacturing company, providing the basis of measurement standardization for KM Capability improvement. Confirmatory factor analysis affirmed four KCs, each identified as an overall factor influencing a set of latent descriptor variables. Second Order and General-Specific Structural Equation Models of each capability provide evidence as to the validity of measurement of these knowledge assets. A standardized instrument for measuring knowledge capabilities would not only allow benchmarking, but also allow tracking capabilities over time and linking them to those performance metrics that are deemed appropriate by the organization.

Does KM Governance = KM Success?

This chapter examines factors that contribute to KM success by differentiating between KM leadership through management and through governance. We look at governance as a structural mechanism that both embeds KM into organizational activity, and lifts it from a series of initiatives to a structured program of activities that are subject to authority, policy, risk management, financial fiduciary duty, and evaluation. Using evidence from 214 respondents to a global internet based KM survey; we find that having a recognized and defined authority for KM that is well-resourced leads to strategically aligned benefits realized from investment in KM. We demonstrate that governance through assigned authority strongly contributes to strategic KM success.