关键词: C2C分享平台, 知识网络, 知识分享行为, 评价机制

Abstract: The online C2C sharing platform is one of the most important directions of the current sharing economy. In addition, for the knowledge sharing platform, how to establish a good platform operation mechanism is a very complicated problem, and in particular the C2C online knowledge sharing platform has a strong open feature, making the platform more difficult for the management of community members. At present, some domestic C2C knowledge sharing platforms mainly use the mutual evaluation mechanism of community members and the systematic evaluation of platform design as an important means to encourage community members to conduct knowledge sharing. However, in theoretical research, there is little research on the correlation mechanism between the evaluation mechanism and individual knowledge sharing behavior. This article uses the methods of content analysis, social network analysis, and regression statistical analysis to collect and analyze data for the 2 largest online professional communities in China′s management consulting industry, CMKT Management Consulting Club. The empirical study explores the moderating effects of systematic reviews and intra-group mutual evaluation mechanisms between members′ knowledge sharing behavior and individual knowledge network centrality. The results show that in a dynamic knowledge network, individual knowledge sharing decisions have a certain consistency in the time dimension, the choice of individual knowledge-sharing behavior (including frequency, originality and subject complexity, etc.) directly determines its position (node centrality) in the knowledge network of the current period. At the same time, the two mechanisms of systematic evaluation and mutual evaluation of members have different adjustment effects on the frequency, originality and theme diversity of individual knowledge sharing. Among them, systematic evaluation encourages individuals to share diversified real-time knowledge and information, while mutual evaluation of members encourages individuals to share more original knowledge. Based on the empirical analysis, this article further divides the knowledge sharing platform into an application-based knowledge sharing platform, an innovative knowledge-sharing platform, and a cooperative knowledge-sharing platform according to the similarities and differences of the two evaluation mechanisms, system evaluation and member mutual evaluation. This study further improves the relevant research on individual knowledge sharing behavior from the perspective of individual interest driving in the knowledge network, and supplements the relevant theories of the existing knowledge sharing incentive mechanism. Besides, in the application-based knowledge sharing platform, system evaluation dominates the overall evaluation system, and non-original, high-frequency sharing has become the main behavior strategy for individuals to continuously improve the centrality of sharing networks on the platform. In an innovative knowledge-sharing platform, feedback from other members of the community (user evaluation) is the main content of the platform evaluation mechanism to encourage knowledge-sharing people to conduct original knowledge sharing and communication. The cooperative knowledge sharing platform is more complete than the evaluation mechanism of the first two types of knowledge sharing platforms, taking into account the advantages of system evaluation and community member evaluation. It can encourage the middle-aged members of the platform to be more willing to achieve their own position in this knowledge network through frequent, relatively focused and highly original knowledge sharing. At the same time, the improvement of node centrality in this knowledge network also means more cooperative resources. In addition, this study only takes CMKT, a typical knowledge network community as an example, and considers all members of the community as indistinguishable individuals, it ignores the understanding and reaction of each member′s external characteristics to different evaluation mechanisms before joining this knowledge common platform. In future research, we can conduct a larger sample of empirical analysis of the sample object through the knowledge network of multiple different types of knowledge sharing platforms, and consider the study of factors such as the user′s external characteristics and knowledge of the evaluation system before entering the community.

Key words: C2C sharing platform, knowledge network, knowledge sharing behavior, evaluation system