Revisiting knowledge transfer: Effects of knowledge characteristics on organizational effort for knowledge transfer
Introduction
Knowledge is a critical resource for organizations’ competitive advantage (Grant, 1996a, Kogut and Zander, 1992). Organizations have to create new knowledge continuously to maintain their competitive advantage in rapidly changing environments. However, knowledge creation is not a process that necessarily creates completely new knowledge but an operation that recombines and reorganizes existing knowledge. The knowledge that transfers from knowledge sources becomes the raw material in knowledge creation for a recipient organization, and successful knowledge transfer is an important driving force in knowledge creation.
With the emphasis on the importance of knowledge transfer for knowledge creation and sustainable competitive advantage, various research topics have been explored such as knowledge sourcing, methods of knowledge transfer, and the effect of knowledge transfer on innovation (Grant, 1996a, Grant, 1996b, Lane and Lubatkin, 1998, Lord and Ranft, 1998, Powell et al., 1996, Szulanski, 1996, Zander and Kogut, 1995). In particular, the effects of knowledge characteristics on knowledge transfer has been studied extensively (Inkpen and Dinur, 1998, Lord and Ranft, 1998, Zander and Kogut, 1995).
However, previous research on the relationships between knowledge characteristics and knowledge transfer focuses on the topics that analyze the effects of knowledge characteristics on the speed or performance of knowledge transfer. The effects of knowledge characteristics on organizational effort have not been sufficiently explored despite their theoretical and practical importance. Therefore, the present study analyzes the effects of knowledge characteristics on the extent of organizational effort to achieve knowledge transfer.
In this study, we suggest that the frequency of contact with a knowledge source represents the extent of organizational effort required for knowledge transfer. We empirically analyze the effects of important knowledge characteristics such as tacitness, difficulty, and importance on the frequency of contact with knowledge sources. This study employs the survey dataset gathered through face-to-face interviews with project managers in a large multinational consulting firm with many business divisions.
This paper aims to overcome the limitations of previous research which only analyzed the effects of knowledge characteristics on the speed or performance of knowledge transfer and this paper provides a deeper insight into the effects of knowledge characteristics on organizations’ behavior. Strategic implications are also provided to firms to help them manage the knowledge transfer process.
Section snippets
Knowledge characteristics and knowledge transfer
Knowledge is the most important strategic resource to a firm and has enormous effects on organizations’ competitive advantage. Thus acquiring, integrating, storing, and sharing knowledge are critical capabilities to sustain an organization’s competitive advantage (Grant, 1996b, Kogut and Zander, 1992, Penrose, 1959, Spender, 1994, Teece et al., 1997, Winter, 1987, Zack, 1999). In particular, the ability to transfer knowledge from external knowledge sources to a recipient’s organizational
Data collection and research site
Data for this study were gathered through personal interviews based on responses to a structured survey. Project managers of a multi-departmental consulting firm based in the United States were interviewed to answer questions regarding knowledge characteristics, and the frequency of contact with knowledge sources. Prior to the interviews, pre-tests were given to a smaller sample within the population. Then the survey was revised and interview technique refined based on the pre-test results. The
Results
Table 1 contains descriptive statistics and correlations. Because the correlation values between independent and control variables are very low, there is no multicollinearity problem. Correlation between the DIFFICULTY and IMPORTANCE variables is relatively high compared with other relationships. This implies that important knowledge is more likely to be difficult. Correlation between the DURATION and the SIZE variables is also relatively high. This implies that it requires a long time to
Discussion
The result shows that the hypothesis asserting that the tacitness of knowledge has a positive effect on the effort for knowledge transfer is weakly supported. Because tacit knowledge is unique and relatively less mobile, it becomes the basis of organizations’ competitive advantage (Grant, 1996a). It is difficult to imitate and transfer tacit knowledge and thus hard to transfer and acquire. However, if organizations successfully transfer the tacit knowledge once through sufficient effort, then
Conclusions
Knowledge can be copied and reproduced without a loss in value, and knowledge transfer is a device to maximize the benefit from knowledge. Although to some organizations, knowledge may be of little value or even rendered useless, it can be valuable to other organizations. Thus, knowledge transfer plays an important role in creating value from knowledge. Because innovations are generated by a recombination of knowledge, it can be a driving force of innovation to acquire new knowledge from
References (49)
Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy
Research Policy
(1986)- Alavi, M., & Leidner, D. E. (1999). Knowledge management systems: Issues, challenges, and benefits. Communications of...
- et al.
Strategic assets and organizational rent
Strategic Management Journal
(1993) - et al.
The impact of US company internationalization on top management team advice networks: A tacit knowledge perspective
Strategic Management Journal
(1999) Knowledge, knowledge work and organizations: An overview and interpretation
Organization Studies
(1995)- et al.
Competing on the edge – Strategy as structured chaos
(1998) Transferring, translating, and transforming: An integrative framework for managing knowledge across boundaries
Organization Science
(2004)Open innovation: The new imperative for creating and profiting from technology
(2003)- et al.
Measures for clinical practice: A sourcebook
(1987) Essentials of psychological testing
(1984)
Patterns of discovery in the social sciences
Coevolving: At last, a way to make synergies work
Harvard Business Review
Knowledge-based view: A new theory of strategy
Transferring core manufacturing technologies in high technology firms
California Management Review
Toward a knowledge-based theory of the firm
Strategic Management Journal
Prospering in dynamically-competitive environments: Organizational capability as knowledge integration
Organization Science
Knowledge flow within multinational corporations
Strategic Management Journal
The search-transfer problem: The role of weak ties in sharing knowledge across organizational subunits
Administrative Science Quarterly
Measuring competence? Exploring firm effects in pharmaceutical research
Strategic Management Journal
Scale, scope, and spillovers: The determinants of research productivity in drug discovery
RAND Journal of Economics
Knowledge management processes and international joint-ventures
Organization Science
Something old, something new: A longitudinal study of search behavior and new product development
Academy of Management Journal
External corporate venturing: Strategic renewal in rapidly changing industries
Knowledge of the firm, combinative capabilities, and the replication of technology
Organization Science
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