Research On The Factors Influencing Knowledge Contribution Behavior Of Open Source Communities Users

The maturity of the open source community and the diversification of open source projects have attracted more and more developers to participate in the open source community,but the operators of the open source community are faced with the problems of low user participation,insufficient maintenance of open source projects,and difficult project management.At present,many scholars have carried out research on the motivation of open source community users to participate,but ignore the environmental factors of the community and the heterogeneity of users.Therefore,based on the open source community platform,this paper is of great significance to the research on user knowledge contribution behavior and its influencing factors for the sustainable development of open source community.This paper sorts out the literature at home and abroad,summarizes personal factors and environmental factors,and uses social capital theory and self-determination theory to select specific variables to construct a model of the influencing factors of open source community users’ knowledge contribution behavior.This paper measures contribution behavior in terms of the quantity and quality of knowledge contribution.Among environmental factors,social connection is measured by the degree of introversion/extroversion centrality of the user’s social network,and trust and recognition are measured by the degree of user information display and the number of featured items.Among personal factors,income expectation,learning motivation and hobbies were measured by the number of external links,the number of favorite projects and participation in open source organizations,respectively,and the professional code level and community experience of users were measured by the number of public repositories and code age,and the type of user was used as a moderating variable to adjust the influence of motivational factors and community environmental factors on knowledge contribution behavior.The Gitee platform was selected to crawl the user behavior characteristic data,and the K-means clustering method was used to cluster users,and the platform users were divided into three different types according to contribution,influence and activity: core users,active users and secondary users.The results confirm that there is obvious heterogeneity between the knowledge contribution behaviors of developers in the open source community,and a few developers contribute most of the production behaviors.Finally,the data analysis software SPSS is used to perform descriptive statistics,regression analysis and moderating effect analysis of the data,and the influence of each variable on the user’s knowledge contribution behavior is tested.It is found that in terms of personal factors,high return expectations inhibit the quantity of contributions but improve the quality of knowledge contributions.Learning motivation and hobbies positively affect the quantity and quality of knowledge contribution;The level of professional code negatively affects the quantity and quality of knowledge contributions;High personal community experience,the knowledge contribution of users is small,but the quality is high.In terms of community factors,introverted centrality and trust positively affect the quantity and quality of knowledge contributions;Extraversion,centrality and community recognition positively affects the quantity of contributions,but negatively influences the quality of contributions.At the same time,it is verified that the motivational drivers of secondary users are stronger,and the utility of community environmental factors is different for different types of users.This study provides relevant evidence for distinguishing user types based on the behavioral characteristics of open source community users.At the same time,it helps the managers of the open source community understand the behavioral characteristics and influencing factors of users’ participation in the open source community,and provides a decision-making basis for the functional setting and management measures of the open source community.Finally,suggestions are made to the community as a whole and three types of users,and motivate users to contribute.