Human–bot co-working: job outcomes and employee responses

Abstract

Purpose Robotic process automation (RPA) has been widely implemented to automate digital tasks. The resulting new type of human–bot co-working environment, however, has been understudied. This paper investigated how the depth and breadth of RPA deployment impact employees' job autonomy and work intensification, as well as perceived RPA performance. It further examined how job autonomy, work intensification, and perceived RPA performance predict burnout and continuance intention to use RPA. Design/methodology/approach Using data collected from online survey of 128 RPA users, whose organizations have already gone live on RPA, partial least squares is used in the validation of the conceptual model and analysis. Findings The analytical results indicate that RPA deployment breadth and depth affect work intensification differently, and RPA deployment breadth and depth significantly predict perceived RPA performance. While work intensification increases burnout, job autonomy alleviates the burnout of employees. Finally, job autonomy and perceived RPA performance are both positive predictors of continuance intention to use RPA. Originality/value This study contributes to the literature by investigating how co-working affects employees' autonomy and quality of work. It also advances the research on technology deployment by showing how deployment breadth and depth differently affect employees' evaluations of work-related aspects. Third, it extends the applicability of job demand-resource model into technology deployment and continuance technology use literature, by illustrating the importance of a job resource such as job autonomy. Finally, it provides firms with RPA implementation strategies.