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Understanding older adults’ adoption of facial recognition payment: An integrated model of TAM and UXT

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  • Mingzhou Liu
  • Caixia Wang
  • Jing Hu

Abstract

The dual challenges of digitalization and population aging highlight the need to improve the well-being of older adults. Facial recognition payment (FRP), an innovative “face-to-pay” technology, has gained widespread adoption in commercial applications due to its convenience. However, existing research has primarily focused on younger users, leaving a significant gap in understanding FRP adoption and user experience among older adults. To address this gap, this study integrates the Technology Acceptance Model (TAM) with User Experience Theory (UXT) to develop a comprehensive framework for examining FRP adoption among older users. By incorporating both cognitive and affective dimensions, the proposed model systematically investigates key determinants of FRP acceptance. Data were collected through a questionnaire survey of 387 older adults in China, and hypotheses were tested using structural equation modeling (SEM). The findings reveal that TAM-based factors, including perceived convenience, facilitating conditions, and technology anxiety, significantly influence perceived ease of use (PEOU), perceived usefulness (PU), and user attitudes, with perceived convenience identified as the most influential determinant. From a UXT perspective, perceived enjoyment, personal innovation, and privacy risk also play a crucial role in FRP adoption. Specifically, personal innovation and perceived enjoyment positively affect user attitudes, whereas privacy risk poses a barrier to adoption. Additionally, while technology self-efficacy does not directly impact user attitudes, it indirectly enhances PEOU and PU by increasing personal innovation. By integrating TAM and UXT, this study advances the understanding of older adults’ technology acceptance behavior and offers theoretical and practical implications for the development of age-friendly FRP systems. The findings provide valuable guidance for technology developers, policymakers, and stakeholders in designing user-centered payment technologies that enhance usability, security, and overall user experience, ultimately improving the quality of life for aging populations.

Suggested Citation

  • Mingzhou Liu & Caixia Wang & Jing Hu, 2025. "Understanding older adults’ adoption of facial recognition payment: An integrated model of TAM and UXT," PLOS ONE, Public Library of Science, vol. 20(7), pages 1-29, July.
  • Handle: RePEc:plo:pone00:0325291
    DOI: 10.1371/journal.pone.0325291
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