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International Journal of Human-Computer Studies
Volume 65, Issue 2, February 2007, Pages 153-169
 
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doi:10.1016/j.ijhcs.2006.09.003    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2006 Elsevier Ltd All rights reserved.

Knowledge sharing behavior in virtual communities: The relationship between trust, self-efficacy, and outcome expectationsstar, open

Meng-Hsiang Hsua, Corresponding Author Contact Information, E-mail The Corresponding Author, Teresa L. Jub, Chia-Hui Yenc and Chun-Ming Changa

aDepartment of Information Management, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan bDepartment of Information Management, Shu-Te University, Kaohsiung, Taiwan cDepartment of International Business Management, Wufeng Institute of Technology, Chiayi, Taiwan

Received 28 January 2005; 
revised 11 September 2006; 
accepted 23 September 2006. 
Communicated by P. Zhang. 
Available online 13 November 2006.

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Abstract

There has been a growing interest in examining the factors that support or hinder one's knowledge sharing behavior in the virtual communities. However, still very few studies examined them from both personal and environmental perspectives. In order to explore the knowledge sharing behaviors within the virtual communities of professional societies, this study proposed a social cognitive theory (SCT)-based model that includes knowledge sharing self-efficacy and outcome expectations for personal influences, and multi-dimensional trusts for environmental influences. The proposed research model was then evaluated with structural equation modeling, and confirmatory factor analysis was also applied to test if the empirical data conform to the proposed model.

Keywords: Knowledge sharing behavior; Trust; Self-efficacy; Social cognitive theory; Virtual communities

Article Outline

1. Introduction
2. Theoretical background and research model
2.1. Self-efficacy and knowledge sharing
2.2. Outcome expectations and knowledge sharing
2.3. Trust development in VCs
3. Research methodology
3.1. Sample and procedure
3.2. Measurement instruments
4. Data analysis and results
4.1. Measurement model
4.2. Structural model
5. Conclusion
5.1. Findings and implications
5.2. Limitations and suggestions for further research
References



 
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