Is Core-Periphery Network Good for Knowledge Sharing? A Structural Model of Endogenous Network Formation on a Crowdsourced Customer Support Forum

Yingda Lu, P. Singh, Baohong Sun
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Abstract

Many companies have adopted technology driven social learning platforms such as social CRM (crowdsourcing customer support from customers) to support knowledge sharing among customers. A number of these self-evolving online customer support communities have reported the emergence of a core-periphery knowledge sharing network structure. In this study, we investigate why such a structure emerges and its implications for knowledge sharing within the community. We propose a dynamic structural model with endogenized knowledge-sharing and network formation. Our model recognizes the dynamic and interdependent nature of knowledge-seeking-and-sharing decisions and allows them to be driven by knowledge increments and social status building in anticipation of future reciprocal rewards from peers. Applying this model to a fine grained panel data set from a social customer support forum for a telecom firm, we illustrate that a user in this community values being connected to other well connected individuals. As a result, a user is more inclined to answer questions of those who are in the core (well connected) than the ones who are in the periphery (not well connected). We find that users are taking into account the expected likelihood of their questions receiving a solution before asking a question. With the emergence of core-periphery network structure, the peripheral individuals are discouraged from asking questions as their expectation of receiving a solution to their question is very low. Thus, the core-periphery structure has created a barrier to knowledge flow to new customers who need the knowledge the most. Our counterfactuals show that hiding the identity of the knowledge seeker or making the individual contributions obsolete faster helps break the core-periphery structure and improves knowledge sharing in the community.
核心-外围网络有利于知识共享吗?众包客户支持论坛内生网络形成的结构模型
许多公司采用了技术驱动的社交学习平台,如社交CRM(客户的众包客户支持)来支持客户之间的知识共享。许多这些自我发展的在线客户支持社区已经报告了核心-外围知识共享网络结构的出现。在本研究中,我们探讨了这种结构出现的原因及其对社区内知识共享的影响。提出了一种内生性知识共享和网络形成的动态结构模型。我们的模型认识到知识寻求和共享决策的动态和相互依赖的本质,并允许它们受到知识增量和社会地位建设的驱动,以预期未来同行的互惠回报。将此模型应用于来自电信公司的社交客户支持论坛的细粒度面板数据集,我们说明了该社区中的用户重视与其他良好连接的个人的连接。因此,用户更倾向于回答那些处于核心(关系良好)的人的问题,而不是那些处于边缘(关系不佳)的人的问题。我们发现,用户在提出问题之前会考虑他们的问题得到解决的预期可能性。随着核心-外围网络结构的出现,外围个体不愿提出问题,因为他们对问题得到解决的期望很低。因此,核心-外围结构对知识流向最需要知识的新客户造成了障碍。我们的反事实表明,隐藏知识追求者的身份或使个人贡献更快地被淘汰有助于打破核心-边缘结构,并改善社区中的知识共享。
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