A Process Analysis Framework to Adopt Intelligent Robotic Process Automation (IRPA) in Supply Chains

Sandali Waduge, Ranil Sugathadasa, Ashani Piyatilake and Samudaya Nanayakkara ()
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Sandali Waduge: Department of Transport Management and Logistics Engineering, Faculty of Engineering, University of Moratuwa, Katubedda, Moratuwa 10400, Sri Lanka
Ranil Sugathadasa: Department of Transport Management and Logistics Engineering, Faculty of Engineering, University of Moratuwa, Katubedda, Moratuwa 10400, Sri Lanka
Ashani Piyatilake: Department of Transport Management and Logistics Engineering, Faculty of Engineering, University of Moratuwa, Katubedda, Moratuwa 10400, Sri Lanka
Samudaya Nanayakkara: Centre for Smart Modern Construction, Western Sydney University, Penrith, NSW 2751, Australia

Sustainability, 2024, vol. 16, issue 22, 1-18

Abstract: Intelligent Robotic Process Automation (IRPA) combines Artificial Intelligence (AI) and Robotic Process Automation (RPA) to automate complex unstructured tasks, improve decision-making, and cope with changing scenarios. A process analysis framework for IRPA adoption was developed by identifying key factors through a literature review and semi-structured expert opinion survey. The employed experts in the survey comprised RPA/IRPA consultants, RPA/IRPA initiative team leaders, and RPA/IRPA developers with three years or more experience. For the initial factor collection phase, there were a total of eighteen (18) responses, and for the factor evaluation phase, a total of twenty-six (26) experts were used to collect responses. Identified factors were shortlisted and evaluated using a Relative Importance Index (RII) analysis. The study’s findings are presented through a Causal-Loop Diagram (CLD) to illustrate the relationships between factors. The framework provides practical guidance for organizations planning to adopt IRPA, informing decision-making, resource allocation, and strategy development. The final process analysis framework highlights the importance of accuracy, level of human involvement in a task, and standardization as the main three primary factors for successful IRPA adoption. Three major secondary factors were identified: digital data input, integration with existing systems, and the cost of adopting new technologies. This research contributes to the added value to existing knowledge and serves as a foundation for future research in IRPA adoption.

Keywords: robotic process automation; intelligent robotic process automation; process analysis framework; relative importance index; causal loop diagram (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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