A data-driven hierarchical model of circular supply chain management in the Indonesian manufacturing industry: a hybrid approach

Purpose This study aims to develop a data-driven circular supply chain management (CSCM) hierarchical model under an extended resource-based view–ecological modernization theory (RBV-EMT), as CSCM requires the restructuring and modification of various resources while focusing on improving technological capabilities and achieving the harmonious integration of economic and environmental practices through enhanced policies and institutional development. Design/methodology/approach Grounded in an extended RBV-EMT framework, this study employs a hybrid approach incorporating data-driven analysis, the entropy weighted method, the fuzzy Delphi method, the fuzzy synthetic evaluation-decision-making trial and evaluation laboratory, and goal programming to identify valid CSCM attributes and develop a valid CSCM hierarchical model under uncertainty. Findings The findings identify valid CSCM attributes under the extended RBV-EMT framework, with technological capabilities and eco-efficient supply chain processes from technological and economic perspectives as the highest-priority resources. In practice, the cooperation and support of stakeholders, resource recovery systems, environmental policies, industrial symbiosis and artificial intelligence are essential for optimizing resource utilization and reducing waste across supply chain stages for improved CSCM. Originality/value Prior studies have failed to provide exhaustive and sufficient CSCM attributes, particularly those that simultaneously account for technological capabilities and external institutional factors. This study fills this gap by developing a data-driven CSCM hierarchical model under an extended RBV-EMT, incorporating eco-efficient supply chain management and technological capabilities as a measurable dimension, offering practitioners and policymakers a validated framework for operationalizing CSCM, particularly within the Indonesian manufacturing industry.