知识共享
知识管理
情感(语言学)
互惠(文化人类学)
结构方程建模
虚拟社区
忠诚
感知
心理学
互惠规范
业务
互联网
社会心理学
社会资本
计算机科学
营销
万维网
机器学习
社会学
神经科学
沟通
社会科学
作者
Ming‐Ji James Lin,Shiu‐Wan Hung,Chih‐Jou Chen
标识
DOI:10.1016/j.chb.2009.03.008
摘要
Professional virtual communities (PVCs), which are formed on the Internet, are expected to serve the needs of members for communication, information, and knowledge sharing. The executives of organizations should consider PVCs as a new innovation or knowledge pool since members share knowledge. However, many PVCs have failed due to members’ low willingness to share knowledge with other members. Thus, there is a need to understand and foster the determinants of members’ knowledge sharing behavior in PVCs. This study develops an integrated model designed to investigate and explain the relationships between contextual factors, personal perceptions of knowledge sharing, knowledge sharing behavior, and community loyalty. Empirical data was collected from three PVCs and tested using structural equation modeling (SEM) to verify the fit of the hypothetical model. The results show that trust significantly influences knowledge sharing self-efficacy, perceived relative advantage and perceived compatibility, which in turn positively affect knowledge sharing behavior. Furthermore, the study finds that the norm of reciprocity does not significantly affect knowledge sharing behavior. The results of the study can be used to identify the motivation underlying individuals’ knowledge sharing behavior in PVCs. By investigating the impacts of contextual factors and personal perceptions on knowledge sharing behavior, the integrated model better explains behavior than other proposed models. This study might help executives of virtual communities and organizations to manage and promote these determinants of knowledge sharing to stimulate members’ willingness to share knowledge and enhance their virtual community loyalty. As only little empirical research has been conducted on the impact of knowledge sharing self-efficacy, perceived relative advantage, and perceived compatibility on the individual’s knowledge sharing behavior in PVCs, the empirical evidence reported here makes a valuable contribution in this highly important area.
科研通智能强力驱动
Strongly Powered by AbleSci AI