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With the rapid advances in technology, the service sector is currently experiencing huge transformations. Among other technologies, service robots are expected to profoundly change the service encounter. This promising technology is making its way into various service industries and is said to have the ability to enhance customer experience, offer faster services, optimize operations, and reduce labor costs. However, the integration of service robots poses a new challenge: their adoption by frontline employees (FLEs). Despite the growing knowledge regarding customers’ acceptance of service robots, little is known about the perceptions of FLEs. Yet, it is crucial that FLEs adopt a positive attitude toward service robots in order to work successfully alongside them. This study therefore aims to understand FLEs’ acceptance of and resistance to service robots by determining the predictors of their attitude toward working with them. Based on a review of the existing literature on technology infusion in customer service, FLEs, and service robots, this work presents an integrative framework which builds upon the technology acceptance model (TAM) and examines the influence of potential drivers, barriers, and other FLE-based factors on FLEs’ attitude. The results of an online survey revealed that perceived usefulness and perceived sociability positively influenced attitude, while job insecurity negatively influenced it. Nevertheless, perceived ease of use, anthropomorphism, and anxiety were not found to be significant predictors of attitude. Furthermore, significant evidence was found regarding the influence of gender on attitude. In contrast, the influence of innovativeness, robot-related experience, and age on attitude was not supported. This research concludes with a number of implications that can possibly enhance the adoption of service robots by FLEs and adequately prepare them for potential changes. The limitations of this study and suggestions for further research are also discussed.

service robots --- frontline employees --- human-robot interaction --- technology acceptance and resistance --- customer service --- Sciences économiques & de gestion > Marketing