Knowledge as a Contingency Variable: Do the Characteristics of Knowledge Predict Organization Structure?

Julian Birkinshaw (), Robert Nobel () and Jonas Ridderstråle ()
Additional contact information
Julian Birkinshaw: London Business School, Sussex Place, Regents Park, London, United Kingdom NW1 4SA
Robert Nobel: Stockholm School of Economics, P.O. Box 6501, 5113-83, Stockholm, Sweden
Jonas Ridderstråle: Stockholm School of Economics, P.O. Box 6501, 5113-83, Stockholm, Sweden

Organization Science, 2002, vol. 13, issue 3, 274-289

Abstract: This paper examines the validity of knowledge as a contingency variable. Building on recent advances in thinking about the dimensions of knowledge assets (Winter 1987, Zander and Kogut 1995), we argue that such dimensions might have an important influence on organization structure. More specifically, we focus on two dimensions of knowledge—observability and system embeddedness—and their influence over the level of unit autonomy and interunit integration in an international network of R&D units. Statistical analysis of questionnaire responses from 110 R&D unit managers show strong association between the dimensions of knowledge and organization structure. It also indicates partial support for the “fit” hypothesis in contingency theory.The paper makes two important contributions to the knowledge management literature. First, we find support for the contingency logic, suggesting that effective organization design has to take into account the underlying characteristics of the firm's knowledge base. Second, we shed light on a relatively neglected dimension of knowledge that we call system embeddedness . This is the extent to which knowledge is a function of the social and physical system in which it exists. In the statistical analysis it emerges as a strong predictor of organization structure. Moreover, it also appears to be conceptually distinct from the tacit-articulate dimension that is normally emphasized. This allows us to speculate on four generic forms that a firm's knowledge might take, that we label integrated, isolated, opaque, and transparent. These are discussed using examples from the data.

Keywords: Knowledge Management; Contingency Theory; R&D Management (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (83)

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