Pay with a smile? Modelling the continuance use intention of facial recognition payment

Purpose

This study synthesises the self-determination theory (SDT), expectation-confirmation model (ECM), and protection motivation theory (PMT) to formulate an integrated theoretical framework that elucidates the process of shaping the intention to continue using facial recognition payment (FRP) under the conditional impact of perceived technology security.

Design/methodology/approach

Data from 667 Beijing Winter Olympics visitors with FRP experience were collected through an online survey and analysed using variance based-structural equation modelling (VB-SEM).

Findings

This study reveals that the intention to continue using FRP evolves through three key stages. Initially, in the expectation stage, the multidimensional concept of artificial autonomy (sensing, thought, and action), which is underpinned by self-determination, is pivotal, strongly influencing perceptions of service enhancement and fostering trust in FRP. Subsequently, the confirmation stage underscores the importance of perceived service enhancement and trust as vital drivers in maintaining FRP usage, while also contributing to subjective well-being. Crucially, perceived technology security emerges as a key moderating factor, enhancing positive perceptions and intentions towards FRP, thus influencing its sustained adoption.

Originality/value

This study stands out by revealing the nuanced interplay between artificial autonomy and user perceptions, particularly concerning service enhancement, technology security, and trust, as they influence well-being and the continued adoption of FRP. Robustly grounded in the integrated theoretical framework of SDT, ECM, and PMT, the study’s findings are critical for comprehending the core elements and specific drivers that promote sustained FRP use, especially as we consider its potential widespread implementation. Therefore, this study not only advances theoretical understanding but also offers practical guidance for optimising FRP deployment strategies in a rapidly evolving technological landscape.