情报科学 ›› 2023, Vol. 41 ›› Issue (1): 49-60.

• 理论研究 • 上一篇    下一篇

基于元分析的在线持续知识共享意愿影响因素研究

  

  • 出版日期:2023-01-01 发布日期:2023-04-06

  • Online:2023-01-01 Published:2023-04-06

摘要: 【目的/意义】持续知识共享对于信息与知识生成、数据价值创造以及平台健康发展至关重要,针对在线持
续知识共享意愿(Online Knowledge Sharing Continuance Intention,OKSCI)研究结果的不一致性问题,进行元分析
显得十分必要。【方法/过程】纳入 63篇研究文献,选择影响 OKSCI的 10个前因变量、6个调节变量所对应的 167个
独立效应值进行元分析。【结果/结论】利他(r=0.545)、情感价值(r=0.531)、社区认同(r=0.517)、期望确认(r=0.513)、
互惠规范(r=0.503)、知识自我效能(r=0.485)、人际信任(r=0.483)、社会交互(r=0.446)、声誉提升(r=0.411)以及外
在奖励(r=0.309)对OKSCI产生显著正向影响。性别、年龄、数据收集渠道、研究依托平台、平台使用时长以及测量
量表等级会对上述10个变量与OKSCI之间的关系产生调节。【创新/局限】厘清了OKSCI影响因素的作用机制,得
到更具普适性的研究结论。部分研究变量依据测量项相似原则合并而来,无法提供更准确的总体估计结果。

Abstract: 【Purpose/significance】Knowledge continuance contribution is crucial for information and knowledge generation, data value
creation, healthy development of platform. It is necessary to conduct meta-analysis to address the inconsistencies in the results of on?
line knowledge sharing continuance intention.【Method/process】In this paper, 63 research literatures were included, and 167 indepen? dent effect values corresponding to 10 antecedent variables and 6 regulatory variables of affecting online knowledge sharing continu? ance intention were selected for meta-analysis.【Result/conclusion】Altruism (r=0.545), emotional value (r=0.531), community identity (r=0.517), expectation confirmation (r=0.513), reciprocity norms (r=0.503), knowledge self-efficacy (r=0.485), interpersonal trust (r=0.483), social interaction (r=0.446), reputation promotion (r=0.411) and extrinsic reward (r=0.309) had significant positive effects on online knowledge sharing continuance intention. Gender, age, data collection channel, research platform, duration of platform use and scale grade moderated the relationship between the above 10 variables and online knowledge sharing continuance intention.【Innova?tion/limitation】The mechanism of online knowledge sharing continuance intention influencing factors is clarified and more general con? clusions were obtained. Some research variables are combined according to the principle of similar measurement items, which can not provide more accurate overall estimation results.