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Motivation and barriers to participation in virtual knowledge‐sharing communities of practice

Ardichvili, Alexander, Page, Vaughn, Wentling, Tim·2003·Journal of Knowledge Management

Abstract

This paper reports the results of a qualitative study of motivation and barriers to employee participation in virtual knowledge‐sharing communities of practice at Caterpillar Inc., a Fortune 100, multinational corporation. The study indicates that, when employees view knowledge as a public good belonging to the whole organization, knowledge flows easily. However, even when individuals give the highest priority to the interests of the organization and of their community, they tend to shy away from contributing knowledge for a variety of reasons. Specifically, employees hesitate to contribute out of fear of criticism, or of misleading the community members (not being sure that their contributions are important, or completely accurate, or relevant to a specific discussion). To remove the identified barriers, there is a need for developing various types of trust, ranging from the knowledge‐based to the institution‐based trust. Future research directions and implications for KM practitioners are formulated.

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Metadata

Authors
Ardichvili, A., Page, V., & Wentling, T.
Venue
Journal of Knowledge Management
Publisher
Emerald
Published
2003-03-01
Volume
7
Issue
1
Pages
64-77
ISSN
1367-3270 (ISSN-L)
OpenAlex
W2147643079
Cited by
1,549
References
6
FWCI
144.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Motivation and barriers to participation in virtual knowledge‐sharing communities of practice. https://app.cochat.ai/papers/10.1108/13673270310463626
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Ardichvili, A., Page, V., & Wentling, T. (2003). Motivation and barriers to participation in virtual knowledge‐sharing communities of practice. Journal of Knowledge Management. https://doi.org/10.1108/13673270310463626

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.