Title: Prioritisation of solutions to mitigate Industry 5.0-enable circular supply chain risks - a hybrid SF-Bayesian BWM and SF-EDAS approach

Authors: Hardik Majiwala; Ravi Kant

Addresses: Mechanical Engineering Department, School of Engineering, P.P. Savani University, Dhamdod, Kosamba, Surat – 394125, Gujarat, India; Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India ' Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India

Abstract: This research explores the integration of Industry 5.0 (I5.0) with circular supply chain (CSC) models, highlighting the need to address implementation risks that hinder widespread adoption. The study aims to identify and prioritise solutions to mitigate these risks by employing a novel spherical fuzzy Bayesian best-worst method (SF-BBWM) for risk assessment, and a spherical fuzzy evaluation based on distance from average solution (SF-EDAS) to rank solutions. Through an empirical case study of an Indian textile manufacturing company, the effectiveness of this framework is demonstrated. Sensitivity analysis further validates the robustness of the findings. This research offers a practical decision-making tool to assist practitioners, policymakers, and academicians in managing risks related to CSC implementation in the context of I5.0. The study provides valuable insights into how smart technologies and circular principles can be effectively harmonised to drive sustainability and innovation in supply chains.

Keywords: circular supply chain; CSC; Industry 5.0; SF-BBWM; SF-EDAS; CSC risks; sustainability.

DOI: 10.1504/IJSOM.2026.153871

International Journal of Services and Operations Management, 2026 Vol.54 No.1, pp.114 - 142

Received: 18 Sep 2024
Accepted: 13 Dec 2024
Published online: 29 May 2026 *

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