Adoption and Influence of Robotic Process Automation in Beef Supply Chains

Khushboo E-Fatima, Rasoul Khandan, Amin Hosseinian Far, Dilshad Sarwar, Hareer Ahmed

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This paper aims to critically examine the potential barriers to the implementation and adoption of Robotic Process Automation (RPA) in the beef supply chain. The beef supply chain has been challenging due to its complex processes, activities, and management. The beef industry has relied heavily on the human workforce in the past; however, RPA adoption allows automating tasks that are repetitive and strenuous in nature to enhance beef quality, safety and security. There are considerable potential barriers to RPA adoption as organisations have not focused on trying to eliminate them due to various reasons. Previous studies lack knowledge related to potential barriers to RPA adoption, so this creates a research gap and requires attention. Statistical data and information are extracted using secondary data relevant to RPA adoption in the beef supply chain. A business process model is formed which uses values or variables using existing statistical data and information. Simulation of the process model is carried out using Simul8 software and analyses of different scenarios help in choosing the best approach for RPA adoption. Results have identified the potential barriers in RPA adoption through the simulation process thus ensuring RPA performs with more potential. Analysis of ‘what-if’ scenarios allows organizational and employee-level improvements along with enhancing RPA’s accuracy. The process model is a generic model for use in real-life scenarios and can be modified by organisations according to their own business needs and requirements. The study contributes in theoretical and practical aspects as it allows decision-makers and managers to adopt RPA in a robust manner and adds to scientific knowledge by identification of potential barriers to RPA adoption.
Original languageEnglish
Article number6030048
Pages (from-to)1-20
Number of pages20
Issue number3
Publication statusPublished - 12 Jul 2022


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