The influence of membership fluidity on the coevolution of the social and knowledge systems in online knowledge communities

Jiangnan Qiu, Wenjing Gu, Zhongmin Ma, Yue You, Chengjie Cai, Meihui Zhang
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Abstract

PurposeIn the extant research on online knowledge communities (OKCs), little attention has been paid to the influence of membership fluidity on the coevolution of the social and knowledge systems. This article aims to fill this gap.Design/methodology/approachBased on the attraction-selection-attrition (ASA) framework, this paper constructs a simulation model to study the coevolution of these two systems under different levels of membership fluidity.FindingsBy analyzing the evolution of these systems with the vector autoregression (VAR) method, we find that social and knowledge systems become more orderly as the coevolution progresses. Furthermore, in communities with low membership fluidity, the microlevel of the social system (i.e. users) drives the coevolution, whereas in communities with high membership fluidity, the microlevel of the knowledge system (i.e. users' views) drives the coevolution.Originality/valueThis paper extends the application of the ASA framework and enriches the literature on membership fluidity of online communities and the literature on driving factors for coevolution of the social and knowledge systems in OKCs. On a practical level, our work suggests that community administrators should adopt different strategies for different membership fluidity to efficiently promote the coevolution of the social and knowledge systems in OKCs.
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网络知识社区成员流动性对社会系统和知识系统共同进化的影响
目的在现有的在线知识社区研究中,很少关注成员流动性对社会系统和知识系统共同进化的影响。本文旨在填补这一空白。设计/方法/途径基于吸引-选择-消耗(ASA)框架,构建了一个仿真模型,研究了不同成员流动性水平下这两个系统的协同进化。通过向量自回归(VAR)方法分析这些系统的演化,我们发现随着共同演化的进行,社会系统和知识系统变得更加有序。此外,在成员流动性低的社区中,共同进化是由社会系统的微观层面(即用户)驱动的,而在成员流动性高的社区中,共同进化是由知识系统的微观层面(即用户的观点)驱动的。原创性/价值本文扩展了ASA框架的应用,丰富了网络社区成员流动性和网络社区社会和知识系统共同进化驱动因素的相关文献。在实践层面上,我们的研究表明,社区管理者应该针对不同的成员流动性采取不同的策略,以有效地促进俄克拉荷马社区社会和知识系统的共同进化。
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