Research On The Relationship Among Users’ Commitment, Self-efficacy And Knowledge Continuance Contribution Intention

Social question answering system is the combination of Q&A community and social network. The adoption the WIKI crowdsourcing and the Digg’s voting system changes the information docking model of previous Q&A product and therefore reconstructs the relationship between people and information.However, the related literature demonstrated that a great deal of participants do not contribute their knowledge and share it with others, and the phenomenon of “free-rider” is considerablly serious. Besides, with the passage of time, some active users have gradually lost their interest and no longer participate in knowledge sharing. Social capital theory, social exchange theory, technology acceptance model, expectation confirmation theory and flow experience are used to conduct users’ behavior research, but none of them explained the users’ continuance contribution intention from the psychological and emotional perspective. Concerning this issue, this paper introduces the commitment theory and social cognitive theory and constructs the theoretical model from four dimensions: affective commitment, continuance commitment, normative commitment and knowledge self-efficacy. Hence, pay attention to online Q&A community from the psychological and emotional perspective contributes to understand the process of knowledge sharing of users and therefore helps the operators provide better information service.According to the theoretical model, We design a scale to investigate the users from ZHIHU and verify the model with the statistical analysis software. The research shows that the affective commitment, continuance commitment and the knowledge self-efficacy have significant positive influence on users’ satisfaction and the knowledge self-efficacy has the utmost significance among the three mentioned. The normative commitment has no significance on users’ satisfaction and part of mediator effect of users’ satisfaction is significant between knowledge self-efficacy and knowledge continuance contribution intention. Referring to the research result, we put forward three suggestions to assist the operators offer better information service. First, control the quality of the answering and improve reward and punishment mechanism to increase the users’ continuance commitment and raise users’ continuance knowledge contribution intention. Second, increase the sense of belonging of users’ and stimulate their affective attachment to Q&A community. Third, integrate the resources and raise users’ knowledge self-efficacy to form a positive circulation of users’ continuance participation.