Service transformation under industry 4.0: Investigating acceptance of facial recognition payment through an extended technology acceptance model

Technological development has drastically changed customers' daily lives by offering them new ways to shop. It also creates more opportunities for business to achieve sustainable success; however, both scholars and managers are still having relative difficulty in fully grasping customer behavior in terms of technology acceptance during the Industry 4.0. This study aims to investigate the possible factors that drive Chinese customers' willingness to utilize facial recognition payment. The findings showed that factors such as perceived enjoyment, facilitating conditions, personal innovativeness, coupon availability, perceived ease of use (PEOU), perceived usefulness (PU), and users' attitude are main drivers of customers' decisions to use facial recognition payment. Also, we found that gender differences exist in the adoption of facial recognition payment. Facilitating conditions have stronger effects on men's attitude towards usage, while coupon availability shapes female users' perception of usefulness more powerfully. By testing the extended technology acceptance model (TAM), this study seeks to gain more insight into technological change within society. Overall, investigation of the drivers of customer intention to use facial recognition payment, and exploration of their internal relationships will fulfil theoretical requirements and lead to a better understanding of customers' technology acceptance behavior, which in turn will provide greater theoretical and practical guidance for scholars and managers.