Study On The Knowledge Sharing In Academic Virtual Communities Based On CAS Theory

With the popularity and in-depth development of Internet, academic virtual communities have become the important academic knowledge and exchange sharing place. Although academic communities have lots of advantages such as knowledge updating and exchanging rate, but there are still some preblems including users'lack of participation and low willingness of knowledge sharing. Exploring the knowledge sharing feature and law in academic communities is significant. It will be helpful for community managers provide pertinent incentives and effective management. And it will help guide the academic activities and promote academic knowledge sharing under virtual environment. Meanwhile, it is also conducive to the rational use of virtual communities for knowledge management.Present research on the knowledge sharing of virtual communities is refering to in multidisciplinary areas. Based on the extensive literature study, the shortages of present study are found:(1) the discipline characteristics of virtual communities were ignored; (2) personal behaviors'impact on the environment of virtual communities was neglected.Based on Complex Adaptive System (CAS) theory, this dissertation taking academic virtual communities as research objects, study the characteristics and laws of knowledge sharing. In this study, the conception, process and pattern of knowledge sharing are defined firstly through literature research.The the constitute of knowledge sharing subjects in academic communities is analyzed, the motivation and impact factors of knowledge-sharing behavior are set forth, the interaction laws of knowledge-sharing is revealed, the professional characteristics of academic communities are systematically analyzed;and with the simulation of members'behavior, the dynamic evolution of knowledge-sharing procession in academic virtual community is explored.The main study content of this dissertion includes the following aspects:1. In this paper, with survey and the web page information collection, the basic data of neural science forum of Dingxiangyuan community are gathered, the main characteristic of knowledge-sharing subjects is analyzed, and Gini coefficient of knowledge sharing and social network analysis method is employed to study the the interaction between the knowledge-sharing subjects of academic communties. The results shows that even in the more successful academic virtual communities, members'participation are generally not high, but the relaxed atmosphere of free knowledge exchange is still attracting a large number of members to the community.2. According to the view that interactions among the agents are the driving force of evolution, the impact factors of knowledge sharing behavior are analyzed based on the existing research. At the same time, different from the existing research in which posting and replying acts are taken as knowledge-sharing behavior, browsing is also regared as knowledge-sharing behavior in this dissertion and the structural equation model of academic community sharing knowledge is subsequently established. Through questionnaires, the model is verified and analyzed. The result shows that:the familiarity between members and member's class has a positive impact on scanner; information motivation, the members altruism, knowledge-sharing self-efficacy significantly affected posting behavior; knowledge sharing self-efficacy, the members trust on the community management, motivation and reciprocity norms have a significant impact on repliers'behavior. At the same time the members confidence of the community management and the incentive of community significantly positively impact on the members information motivation and sharing motivation based on recognition factors.3. The emuch.net, dxy.cn, frchina.net and guoxue.com are selected as sample communities. The research found the members'common characteristics of the academic communities with the relative stability of identity, professional communication content, strict rationality of communication attitude. However, some differences between the communities of humanity-management and engineering-science are also found, such as the source of topics, the language style and the acceptance of knowledge authority. Gini coefficient is introduced to measure the level of imbalance in the knowledge sharing activities, and the value shows that the imbalance of humanity-management community is higher than that of-engineering-science community. The subject construction is analyzed by social network analysis and it is found that both the communities have the low network centralization and the community core is more easily formed in the humanity-managenrent community. Based on the descriptive statistical analysis and structural equation modeling, it is found that there are some differences between the two kind communities such as the preference knowledge sharing, knowledge sharing motivation, impact factors.4. A conceptual model of knowledge sharing behavior is built and the dynamic procession of knowledge sharing is simulated based on the above research. The result of simulation shows that the science engineering community and human management community have different types of knowledge sharing, that is, accordingly Q/A (question/answer) type and release type.The innovative points of this dissertation are mainly embodied in the following aspects:(1) Theoretical perspective:it is proposed that knowledge sharing in virtual community academic is the complex adaptive system. With the existing research results, the impact factors model of knowledge sharing behavior in academic communities is built. The In-depth research of influencing factors of knowledge sharing is done; meanwhile, the professional characteristics of knowledge sharing in academic communities are systematically analyzed. (2)Study path: multi-agent based modeling is used to explore the dynamic evolution process of knowledge sharing in academic communities. The simulation results not only verify some conclusion of the above investigation, but also sums up the differences of knowledge sharing organization form between humanity-management communities and engineering-science ones.