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Protecting privacy in Pokémon Go: A multigroup analysis

Mathupayas Thongmak

Technology in Society, 2022, vol. 70, issue C

Abstract: Location-Based Services (LBSs) and Augmented Reality (AR) technologies are extensively adopted in various contexts such as Location-Based Games (LBGs). However, those technologies could increase information privacy concerns and perceived risks for users. Thus, privacy protection mechanisms are important. This study aims to explore the direct or indirect effects of self-efficacy to protect information privacy, privacy knowledge, privacy concerns, and perceived risks on privacy protection behaviours of an LBG's players and to investigate the different effects among two-player groups (full-time students and full-time employees). Three types of privacy protection behaviours are explored: fabricate, seek, and refrain behaviours. Data are gathered from 259 Pokémon GO's players. Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM), and Multi-group analysis are applied to test the research hypotheses. Privacy knowledge, self-efficacy, privacy concerns, and perceived risks are confirmed as salient factors directly or indirectly influencing the privacy protection behaviour of players one way or another.

Keywords: Pokémon GO; Location-based; Augmented reality; Mobile game; Information privacy; Protection motivation theory (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:70:y:2022:i:c:s0160791x22001403

DOI: 10.1016/j.techsoc.2022.101999

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