Abstract

The COVID-19 pandemic has brought attention to the delicate balance between individual privacy concerns and the governance of public health emergencies. Governments are leveraging a wide range of digital methodologies to acquire individual-level data for purposes such as contact tracing, isolation protocols, and surveillance, all aimed at effectively mitigating the deleterious consequences of the epidemic. However, the surrender of individual health information depends on individuals’ perception of the legitimacy of governance. In this research, our objective is to examine how individuals’ perceptions of the legitimacy of governance impact their decisions regarding privacy disclosure. This study stands out by dissecting cognitive and moral legitimacy of governance, uniquely examining their influence on individuals’ altruistic privacy disclosure during a crisis. Unlike previous research, our approach offers a more nuanced understanding of the interplay between governance legitimacy and privacy concessions. From July 15th to August 14th, 2022, amid the 2022 lockdown in Shanghai, China, this study utilizes surveys with established measurement scales, alongside structural equation modeling (SEM), to explore the relationship between individuals’ perceptions of government legitimacy in managing the pandemic and their willingness to compromise health information. The study distinguishes between moral legitimacy (pathos) and cognitive legitimacy (logos). The results find that both cognitive and moral legitimacy positively influence altruism, thus enhancing the efficacy of voluntary disclosure of personal health information to government agencies for pandemic governance. However, it is noteworthy that education level moderates the impact of these two dimensions of legitimacy on altruism. This research provides empirical evidence to enhance our understanding of how different dimensions of citizens’ perceptions of governance legitimacy in crisis situations shape their attitudes and behaviors towards privacy trade-offs.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call