在线产品创新社区用户识别机制与用户贡献行为研究:基于亲社会行为理论视角

发布时间：2018-04-21 18:05

本文选题：识别机制 + 亲社会行为理论　；参考：《南开管理评论》2017年03期

【摘要】：构建在线产品创新社区成为越来越多企业的选择。本文在国内外文献分析基础上,从社区用户识别机制角度,归纳分析了基于数量和基于质量的两种社区用户识别机制,分别选择海尔和星巴克在线产品创新社区为调研对象,借鉴亲社会行为理论提出研究假设,收集3个月的客观数据,运用Logit模型分析方法实证研究。结果显示,在基于数量的用户识别机制社区,同行认可和社区形象激励对用户主动贡献行为会产生正向的积极影响;在基于质量的用户识别机制社区,同行认可和社区形象激励分别会对用户主动贡献和反应贡献行为产生正向的积极影响。两种用户识别机制的社区用户活跃程度存在明显差异。研究证实了社区用户识别机制对用户贡献行为的影响作用,丰富了在线社区用户行为研究的理论视角,给出了社区管理建议和未来研究方向。
[Abstract]:Building online product innovation community has become the choice of more and more enterprises. On the basis of literature analysis at home and abroad, this paper summarizes and analyzes two kinds of community user identification mechanisms based on quantity and quality from the perspective of community user identification mechanism, and selects Haier and Starbucks online product innovation community as the research objects, respectively. Based on the prosocial behavior theory, this paper puts forward the research hypothesis, collects the objective data for 3 months, and applies the Logit model analysis method to the empirical research. The results show that peer recognition and community image incentives have positive and positive effects on user active contribution behavior in the quantity-based user identification mechanism community, while in the quality-based user identification mechanism community, peer recognition and community image incentives have a positive impact on the user's active contribution behavior. Peer recognition and community image incentive have positive effects on user's active contribution and response contribution respectively. There are significant differences in the community user activity between the two user identification mechanisms. The research confirms the influence of the community user identification mechanism on the user contribution behavior, enriches the theoretical perspective of online community user behavior research, and gives the community management suggestions and future research directions.
【作者单位】：江西师范大学管理科学与工程研究中心;纽约摩根大通;
【基金】：国家自然科学基金项目(71262023) 江西省软科学研究计划重点项目(20161BBA10015)资助
【分类号】：F273.1

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