Research On The Impact Of User’s Contribution Behavior In Open Innovation Community

With the dynamic changes in the market and the increasingly diverse demands of consumers,product innovation,as the lifeline of an enterprise,plays an important role in creating and maintaining competitive advantages for the enterprise.In the Internet era,users’ thoughts are being valued and accepted by more and more enterprises gradually.Therefore,it is obviously insufficient to rely merely on limited resources within an enterprise to innovate products,but instead,enterprises should give full play to the roles of users in the process of product innovation.In this context,being a typical platform for information exchange among users and users & enterprises,open innovation communities have attracted the attention of scholars and enterprises.Users are core resources of an open innovation community,while the interaction between users is the basis for the healthy development of an open innovation community.All information is based on users’ participation behavior.Actually,inactive user has been a problem existing in the operation process of open innovation communities.Therefore,how to motivate users has become one of the main concerns of enterprises.In this thesis,the author analyzes influencing factors of participating users’ contribution behaviors in open innovation communities where users share knowledge by publishing articles,while other users obtain knowledge by browsing those articles and leaving comments.Based on social exchange theory,the author puts forward five factors that affect users’ contribution behaviors in open innovation communities,namely,member recognition factor,image maintenance factor,self-efficacy factor,knowledge acquisition factor and social influence factor.Then the author sets up an influence factor model of open innovation community and conducts an empirical research,in which the author collects 21582 data about 981 users’ online behaviors on the new functional BBS of MIUI Module of Xiaomi Community.Next R software is used to carry out a statistical analysis on behavioral panel data and test the research hypothesis.Lastly,following conclusions are obtained: Member recognition factor,image maintenance factor,self-efficacy factor,knowledge acquisition factor and social influence factor all have a significantly positive impact on users’ contribution behaviors.According to experimental results,relevant management suggestions are proposed,which provides a theoretical basis and practical reference for enterprises to better maintain stable development of communities,and deficiencies of the researchand future development directions are also elaborated.The innovation of this thesis lies in that: First of all,research content is innovative.The author uses social exchange theory to explore influencing factors of user participation and supplements the research on users’ behaviors in open innovation communities.Secondly,the author utilizes community users’ actual behaviors as measurement indexes and objective data for an empirical analysis,which endows the research with high practical value.Lastly,the author selects a domestic representative open innovation community — Xiaomi Community as the research object and provides empirical evidence for how behaviors of users of open innovation communities in China are influenced and how to guide users’ contributions,which provides certain reference for other similar websites to attract and retain users.