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Understanding IT professionals’ knowledge sharing intention through KMS: a social exchange perspective

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  • Ming-Tien Tsai
  • Hsiu-Ching Chang
  • Nai-Chang Cheng
  • Chung-Chang Lien

Abstract

Knowledge sharing is the behavior of disseminating acquired knowledge to other members of an organization, and often presents major challenges, because some employees resist sharing their knowledge with others. In this paper, we investigate the knowledge sharing behavioral intention based on social exchange theory (SET). SET emphasizes non-material exchange, and people share their knowledge by weighing the potential benefits and risks of social relationships. The research presented in this study includes various constructs based on SET and social cognitive theory. This study examines the role of social exchange factors (perceived organizational support, organizational trust and reciprocal relationship expectancy) in explaining IT professionals’ knowledge sharing intentions through KMS. Based on a survey of 251 IT professionals in STSP, this study applies structural equation modeling to verify the research model. The results showed that trust, self-efficacy and reciprocal relationship expectancy are significantly associated with knowledge sharing through KMS. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Ming-Tien Tsai & Hsiu-Ching Chang & Nai-Chang Cheng & Chung-Chang Lien, 2013. "Understanding IT professionals’ knowledge sharing intention through KMS: a social exchange perspective," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(5), pages 2739-2753, August.
    • Handle: RePEc:spr:qualqt:v:47:y:2013:i:5:p:2739-2753
    DOI: 10.1007/s11135-012-9685-4
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    References listed on IDEAS

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    1. Gee W. Bock & Young-Gul Kim, 2002. "Breaking the Myths of Rewards: An Exploratory Study of Attitudes about Knowledge Sharing," Information Resources Management Journal (IRMJ), IGI Global, vol. 15(2), pages 14-21, April.
    2. Dimitris Assimakopoulos & Jie Yan, 2006. "Sources of knowledge acquisition for Chinese software engineers," Post-Print hal-02313393, HAL.
    3. King, William R. & Marks, Peter Jr., 2008. "Motivating knowledge sharing through a knowledge management system," Omega, Elsevier, vol. 36(1), pages 131-146, February.
    4. Daniel Z. Levin & Rob Cross, 2004. "The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer," Management Science, INFORMS, vol. 50(11), pages 1477-1490, November.
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    1. Leon, Ramona – Diana & Rodríguez-Rodríguez, Raúl & Gómez-Gasquet, Pedro & Mula, Josefa, 2017. "Social network analysis: A tool for evaluating and predicting future knowledge flows from an insurance organization," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 103-118.
    2. Supriya Kumar Ghatak & Biswajit Mahanty, 2021. "Evaluating intra-project knowledge growth and its effect on co-located software team output," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1727-1750, October.
    3. Jiahe Chen & Yi-Chen Lan & Yu-Wei Chang & Po-Ya Chang, 2019. "Exploring Doctors’ Willingness to Provide Online Counseling Services: The Roles of Motivations and Costs," IJERPH, MDPI, vol. 17(1), pages 1-12, December.
    4. Debasisha Mishra & M. Ramkumar, 2022. "Study of project type and team structure in the Indian software outsourcing industry," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 324-349, March.

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