Information collection, public attitudes, and supportive behavior tendencies in the urban digital transformation: a survey experiment in a facial recognition scenario

Yingwei Wang and Hong Pan

Journal of Chinese Governance, 2024, vol. 9, issue 4, 483-510

Abstract: Information collection is key to digital governance, yet few studies have investigated how specific factors associated with information collection affect public attitudes and supportive behavior tendencies. Using information collection through facial recognition technology as the research scenario, this study explores the mechanism that drives public support of information collection on the basis of questionnaire data collected from 1,116 individuals in China via a 2 (government platform vs. enterprise platform) * 2 (explicitly informed vs. tacitly agreed) survey experimental design. It was found that information collection in urban digital transformation strengthened supportive behavior tendencies, and public attitudes played a mediating role in the relationship between the two. Specifically, information collection on a government platform is more likely to increase supportive behavior tendencies than information collection on an enterprise platform. Information collection via tacit agreement is more likely to increase supportive behavior tendencies than information collection via explicitly informed consent. This study has implications for understanding public behavioral choices under contrasting information collection strategies and for promoting the realization of coproduction between the government, the enterprise, and the public in a way that enhances the value of collected data.

Date: 2024
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DOI: 10.1080/23812346.2024.2378395

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