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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Sandali Waduge & Ranil Sugathadasa & Ashani Piyatilake & Samudaya Nanayakkara, 2024. "A Process Analysis Framework to Adopt Intelligent Robotic Process Automation (IRPA) in Supply Chains," Sustainability, MDPI, vol. 16(22), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9753-:d:1516863
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    References listed on IDEAS

    as
    1. Laurence Viale & Dorsaf Zouari, 2020. "Impact of digitalization on procurement: the case of robotic process automation," Post-Print hal-03695535, HAL.
    2. Marta Bottero & Giulia Datola & Elena De Angelis, 2020. "A System Dynamics Model and Analytic Network Process: An Integrated Approach to Investigate Urban Resilience," Land, MDPI, vol. 9(8), pages 1-26, July.
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