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The Effect of Community Type on Knowledge Sharing Incentives in Online Communities: A Meta-Analysis

Abstract

Online communities are computer mediated, self-organizing, open networks where people voluntarily communicate and share knowledge. Knowledge sharing in online communities requires exerting time and effort and hence community members need motivation to contribute in these communities. Prior research identified numerous incentives that can motivate knowledge sharing in online communities such as self-efficacy and trust. However, research did not consider the effects of community types on the effectiveness of these incentives. In this paper we use meta-analysis to examine the effects of community type on knowledge sharing incentives in communities of interest and communities of practice. We examined 24 papers focusing on knowledge sharing incentives and we found that the type of online community moderates the effects of trust, commitment, task enjoyment and reciprocity on knowledge sharing. The outcome of this research demonstrates that future research should consider community types in knowledge sharing models.

Authors

Abouzahra M; Tan J

Pagination

pp. 1765-1773

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

January 1, 2014

DOI

10.1109/hicss.2014.224

Name of conference

2014 47th Hawaii International Conference on System Sciences
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