Privacy paradox for location tracking in mobile social networking apps: The perspectives of behavioral reasoning and regulatory focus

Shiyi Ying, Youlin Huang, Lixian Qian and Jinzhu Song

Technological Forecasting and Social Change, 2023, vol. 190, issue C

Abstract: Social networking services (SNSs) have been collecting and analyzing users' personal data for the sake of personalization and customization, raising massive privacy concerns. Among the various types of privacy, personal location data are considered most sensitive, but are critical for the location-based features in mobile SNS applications. Drawing on behavioral reasoning theory and accounting for the privacy paradox, this study investigates the heterogeneous psychological mechanisms supporting and discouraging mobile SNS users from enabling location tracking in SNS applications. Based on a survey of young internet users in China, our analysis shows that, first, reasons for location tracking are insignificantly associated with intention to allow location tracking but reasons against are negatively related to intention. Furthermore, for individuals with higher desire to share, reasons for and attitude have the stronger associations with intention, while the moderating effect of desire for privacy is insignificant. We make research contributions by examining the antecedents of the reasoning process, as well as the moderating role of desire to share, to account for the privacy paradox. We also contribute to behavioral reasoning theory by introducing regulatory focus-based antecedents to the reasoning process. We offer key practical suggestions for SNS providers and policymakers.

Keywords: Social network service; Location tracking; Regulatory focus theory; Privacy paradox; Privacy concern; Behavioral reasoning theory (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:190:y:2023:i:c:s0040162523000975

DOI: 10.1016/j.techfore.2023.122412

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