The online website privacy disclosure behavior of users based on concerns-outcomes model

被引:0
|
作者
X. I. E. Weihong
Zhang Qian
机构
[1] Guangdong University of Technology,School of Management
[2] Guangdong University of Technology,School of Economics and Trade
来源
Soft Computing | 2022年 / 26卷
关键词
Online websites; Online privacy concerns; Privacy disclosure behaviors; Privacy calculations; APCO model;
D O I
暂无
中图分类号
学科分类号
摘要
Reducing users’ online privacy concerns and encouraging users’ privacy disclosure behaviors are the important prerequisite for online websites to use data to obtain economic value. Based on the theory of clue utilization and privacy calculation theory, this paper uses the APCO model to intermediate online privacy concerns and adjust privacy calculations to explore the influence mechanism of online website users’ privacy disclosure behaviors in China. Using the questionnaire survey method, SPSS 20.0 and AMOS 23.0 were used to conduct structural equation path analysis on the collected 966 valid data to verify the proposed research hypothesis. Research results show that website reputation and website trust have a significant positive impact on privacy disclosure; users’ online privacy concerns will play a mediating role in website reputation, website trust, and privacy disclosure; when users with online privacy concerns are doing privacy calculations of perceived risks and perceived benefits are carried out during privacy disclosure. However, privacy calculations are contextual. On the premise of website trust, the benefits of information disclosure can reduce users’ online privacy concerns and increase users’ privacy disclosure behaviors. This article exposes that users will adopt privacy disclosure decisions with different levels of cognitive effort based on the degree of online privacy concerns, enriches research on privacy disclosure behavior, and exposes the contextual nature of privacy calculus, which further enriches and expands the theory of privacy calculus. Promote online websites to obtain user data and provide relevant countermeasures and suggestions.
引用
收藏
页码:11733 / 11747
页数:14
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