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Knowledge heterogeneity, social capital, and organizational innovation

Purpose Observing across four comparative case organizations, the purpose of this paper is to identify two sources of contingency (i.e. construct and contextual contingency) for the relationship between knowledge heterogeneity and innovation. Design/methodology/approach The contingencies was explore...

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Bibliographic Details
Published in:Journal of organizational change management 2018-04, Vol.31 (2), p.304-322
Main Author: Tsai, Fu-Sheng
Format: Article
Language:English
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Summary:Purpose Observing across four comparative case organizations, the purpose of this paper is to identify two sources of contingency (i.e. construct and contextual contingency) for the relationship between knowledge heterogeneity and innovation. Design/methodology/approach The contingencies was explored by conducting a comparative case analyses with rich qualitative data extracted and interpreted from four case companies. Findings First, the construct contingency is examined by refining knowledge heterogeneity into three dimensions: domain, process, and context heterogeneity. Specifically, the author proposed that knowledge heterogeneity in domain is associated with innovation in an inverted U-shape, while heterogeneity in process and context dimensions both negatively influence innovation. Second, contextual contingency is studied. The author proposed that: trust positively moderates the relationship between knowledge heterogeneity and innovation; depending on the knowledge owner attributes, centralization positively or negatively moderates the relationship between heterogeneous knowledge and innovation; shared knowledge vision positively moderates the relationship between knowledge heterogeneity and innovation. Originality/value The influences of knowledge heterogeneity on innovation have yet been inconsistent. The present study set to reconcile such inconsistency with a solution of contingencies that intervene the heterogeneity-innovation relationship. These results offer useful references for future large-scaled, quantitative studies.
ISSN:0953-4814
1758-7816
DOI:10.1108/JOCM-03-2017-0047