Advancing circular economy assessments for sustainability benchmarking in resource and manufacturing supply chains: A scalable dynamic network framework

Evaluating sustainability and establishing benchmarks in multi-stage resource and manufacturing supply chains (SCs) through circular economy (CE) principles is challenging, especially when transitioning from theoretical to actual appraisals. Real-world interactions of time-varying components and bid...

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Bibliographic Details
Published in:Journal of environmental management Vol. 393; p. 127180
Main Authors: Shabanpour, Hadi, Lieske, Scott N., Dargusch, Paul, Wadley, David, Farzipoor Saen, Reza
Format: Journal Article
Language:English
Published: England Elsevier Ltd 01.10.2025
Subjects:
Benchmarking
Circular economy
Conservation of Natural Resources
Dynamic network DEA
Mining
Real-world measures
Resource and manufacturing supply chains
Sustainability benchmarking
Sustainable decision-making
Sustainable decision-making
Circular economy
Sustainability benchmarking
Real-world measures
Dynamic network DEA
Resource and manufacturing supply chains
ISSN:0301-4797, 1095-8630, 1095-8630
Online Access:Get full text
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Summary:Evaluating sustainability and establishing benchmarks in multi-stage resource and manufacturing supply chains (SCs) through circular economy (CE) principles is challenging, especially when transitioning from theoretical to actual appraisals. Real-world interactions of time-varying components and bidirectional loops inside SC networks are often overlooked in existing approaches. This study proposes a novel framework to evaluate the sustainability of resource and manufacturing SCs in a CE context using dynamic network data envelopment analysis (DN-DEA). To this end, the research introduces a three-stage DN-DEA framework which integrates intra-stage bidirectional links, dual-role indices, and real-world periodic interactions, such as mid-term green investments and research and development (R&D) costs. By incorporating intra-stage and inter-period circular measures, the framework addresses the dynamic complexities of SCs, enhancing benchmarking reliability and offering actionable insights for decision-making. This method affords average efficiency and sustainability growth trends which allow for sustainability ranking of the SCs for accurate decision making. The dynamic applicability and benchmarking reliability of the framework are illustrated through a three-stage (mining, iron smelting, and distribution) case study. The framework's capacity for scalability allows different levels of resource and manufacturing configurations for both the series and series-parallel periodic approaches. •Practical benchmarking tool developed for optimizing sustainable supply chains.•Novel dynamic network model with bidirectional restorative CE principles.•Multi-period framework captures sequential and non-sequential SSC interactions.•New ranking method assesses both efficiency levels and growth trajectories.•Applied to a three-stage supply chain case with resource and production flows.
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ISSN:0301-4797
1095-8630
1095-8630
DOI:10.1016/j.jenvman.2025.127180