Robotic process automation adoption: contextual factors from service sectors in an emerging economy

Purpose The study aimed to examine the robotic process automation (RPA) contextual (center of excellence and scalability) and the multidisciplinary (TOE) determinants of RPA adoption in service industries in the emerging economy. Design/methodology/approach Ten factors were identified through literature surveys and popular studies grounded in technology, organization and environment. SPSS AMOS SEM is used for scale measurement and hypotheses testing. A sample of 313 respondents was collected from middle to above middle management executives of service industries from India. The authors tested the hidden layers and non-linear relationships using artificial neural network (ANN) analysis. Findings The low complexity, center of excellence (CoE), and industry/business partner pressure were significant to the RPA adoption in service industries in emerging economies. Counterintuitively, the scalability showed a negative influence on the RPA adoption, and the process capability did not show influence. The results of SEM and ANN were consistent. Research limitations/implications This research can unfold the RPA adoption scholarly debate to multiple services industries beyond the telecom sector in emerging economies. Practical implications RPA is a disruptive technology on the artificial intelligence (AI) continuum. It has the potential to change the ways of working and enable technology-driven transformation. However, despite having thriving service industries that can benefit from RPA, emerging economies lag in adoption compared to the developed nations. Social implications The RPA and automation can bring transformation to human society. Large economies such as India and China have large-scale demand for services, and the waiting lines are a common issue struggled by society. RPA can address the scalability issues of several services. Originality/value This study is among the first to examine technology-organization-environment (TOE) with RPA, including RPA contextual variables such as the CoE and scalability. Literature reports TOE applications on several emerging technologies of Industry 4.0 such as cloud, blockchain, big data and 3 Dimensional Printing (3DP), but no or little reported studies around RPA in services industries in emerging markets.