大数据公共管理情境下的个人信息披露态度

Research on Public Attitudes Towards Personal Information Disclosure in the Context of Big Data Public Management

文章在大数据公共管理背景下,以新冠疫情防控期间的个人信息披露态度为例,研究个人内在因素和外在环境因素对个人信息披露态度的影响,以期为建构大数据公共管理中个人信息和谐的“披露-采集”关系提供理论支撑。研究设计综合保护动机理论和调节定向理论,引入隐私顾虑作为中介变量,构建结构方程模型;通过问卷调查法,收集覆盖16个城市4,800份大规模样本进行分析。研究发现:自我效能负向影响隐私顾虑,主观规范正向影响隐私顾虑,隐私顾虑负向影响个人信息披露态度;促进定向个体比预防定向个体隐私顾虑水平更低,更倾向于支持公共管理中的个人信息披露,同时调节定向特质在自我效能与隐私顾虑之间具有显著调节效应。

The wide application of big data and intelligent technologies in public management has brought about public concerns about privacy disclosure.This paper makes an analysis of public attitudes towards personal information disclosure during the COVID-19 pandemic,aiming to provide a theoretical support for constructing a more harmonious personal information“disclosure-collection”relationship in big data-driven public management.It first proposes a structural equation model by integrating protection motivation theory and regulatory focus theory,and adopting privacy concerns as a mediating variable.Then,through online survey,4,800 valid samples from 16 Chinese cities are collected.The analysis of such samples shows that self-efficacy exerts a negative influence on privacy concerns,while subjective norms yield a positive impact on privacy concerns.Additionally,privacy concerns has a negatively effect on personal information disclosure attitudes.Compared to individuals with a prevention-focused orientation,those with promotion-focused orientation experience a lower level of privacy concerns,they also have a greater tendency to support personal information disclosure in the realm of public management.Meanwhile,regulatory focus has a significant moderating effect on the relationship between selfefficacy and privacy concerns.