Investigation on users’ resistance intention to facial recognition payment: a perspective of privacy

Xusen Cheng (), Liyang Qiao (), Bo Yang () and Xiaoping Zhang ()
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Xusen Cheng: Renmin University of China
Liyang Qiao: Renmin University of China
Bo Yang: Renmin University of China
Xiaoping Zhang: Renmin University of China

Electronic Commerce Research, 2024, vol. 24, issue 1, No 10, 275-301

Abstract: Abstract Despite the convenience of facial recognition payment (FRP), many consumers hesitate to use FRP. Drawing on the antecedent-privacy concern-outcome (APCO) macro model, this study investigates antecedents of privacy concerns and privacy fatigue in the context of FRP and how privacy concerns and privacy fatigue influence user’s resistance intention of FRP. A mixed-methods is used to address these issues. A semi-structured interview is first used to identify the antecedents of privacy concerns and privacy fatigue for facial privacy information. According to the research results, we develop research hypotheses and build the research model. By analyzing survey data from 394 respondents using Amos, this study finds that privacy experience, privacy control, privacy policy effectiveness, peer influence, and reputation significantly influence users’ privacy concerns for facial privacy information; in addition, privacy experience, privacy control, and negative media exposure significantly influence users’ privacy fatigue. Moreover, privacy concerns and privacy fatigue are significantly related to users’ resistance intention to FRP.

Keywords: Facial recognition payment (FRP); Privacy concerns; Privacy fatigue; APCO macro model; Users’ resistance intention to FRP (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10660-022-09588-y

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