在线健康社区知识转移粘滞:从隐私计算视角分析

Online Health Communities Knowledge Transfer Stickiness:Analysis of Privacy Calculus Theory Fused

[目的/意义]旨在探析隐私计算视角下在线健康社区知识转移粘滞影响因素,构建理论模型,为完善在线健康社区健康信息隐私安全保护机制、交互性服务建设与运营管理提出建议。[方法/过程]采用质性研究方法,借助软件NVivo12对访谈资料进行内容分析与编码,归纳影响在线健康社区知识转移粘滞的4个主要因素以及14个子因素,并构建在线健康社区知识转移粘滞影响因素模型。[结果/结论]感知风险、社会收益、情感收益和主观规范对在线健康社区知识转移粘滞都有不同程度的影响。据此,总结相关启示。

[Purpose/significance]This paper aims to analyze the influencing factors of knowledge transfer stickiness in online health communities from the perspective of privacy computing,and construct theoretical models to provide suggestions for improving the privacy protection mechanism of health information,interactive service construction and operation management of online health communities.[Method/process]Using qualitative research methods,the software NVivo12 is used to encode and analyze the interview data.Then 4 main influencing factors and 14 sub-categories of knowledge transfer stickiness in the online health communities is summarized,and an influence factor model of knowledge transfer stickiness in online health community based on the theory of privacy calculation is constructed.[Result/conclusion]Perceived risk,social benefits,emotional benefits,and subjective norms have varying degrees of impact on knowledge transfer stickiness in online health communities.Based on this,summarize the relevant revelations.