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A diverse, unbiased group decision-making framework for assessing drivers of the circular economy and resilience in an agri-food supply chain

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Authors
Ramos, Edgar
Rabiee, Meysam
Tarei, Pradeep Kumar
Chavez, Melissa
Coles, Phillip S.
Issue Date
2024-01-01
Keywords
agri-food supply chain
Circular economy
Grey-DEMATEL
group decision-making
supply chain resilience

Metadata
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Publisher
Taylor and Francis Ltd.
Journal
Production Planning and Control
URI
http://hdl.handle.net/10757/676249
DOI
10.1080/09537287.2024.2370988
Abstract
The circular economy (CE) and supply chain resilience have received significant scientific attention in the recent supply chain literature. Incorporating CE practices and resilience practices into a supply chain enables companies to address their sustainability goals. This research explores the joint impact of implementing CE practices and resilience practices in an agri-food supply chain in Peru. The synergetic assessment of CE practices and resilience practices in a supply chain constitutes a multi-criteria decision-making challenge, requiring the involvement of subject-matter experts. Most studies have selected subject-matter experts based on the researchers’ convenience, which may lead to biased evaluations by some experts, resulting in unreliable study results. To mitigate potential bias, this research introduces a new framework named Diverse and Unbiased Group Decision-Making (DUGDM). Subsequently, the study examines the interaction between the drivers of CE and resilience using the Grey-DEMATEL method. The results indicate that drivers, such as the economic growth level, agricultural contamination, and collaborative operation of multiple firms are most influential in the successful integration of circular economy and resilience into a Peruvian agri-food supply chain system.
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
ISSN
09537287
EISSN
13665871
ae974a485f413a2113503eed53cd6c53
10.1080/09537287.2024.2370988
Scopus Count
Collections
Ingeniería Industrial

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