Green manufacturing performance improvement under uncertainties: An interrelationship hierarchical model

Tat-Dat Bui, Thi Tuong Vy Nguyen, Kuo-Jui Wu, Ming K. Lim and Ming-Lang Tseng

International Journal of Production Economics, 2024, vol. 268, issue C

Abstract: Green manufacturing is a developing industrial trend that addresses environmental issues and has a long-term, realistic, and sustainable future. However, previous studies involving the attributes that are essential for green manufacturing performance improvement, particularly, in the textile industry, are lacking. Identifying a set of green manufacturing attributes and hierarchical causal interrelationships that deliver insights into performance improvement under uncertainties is necessary. Hence, this study aims to create a reliable hierarchical model and to identify the causal interrelationships between green manufacturing attributes using a hybrid approach consisting of the fuzzy Delphi method (FDM), fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and analytic network process (ANP). The green manufacturing model, which includes five aspects and 23 criteria, is verified. Green operational practices, government policy and environmental management constitute the group that strongly affects manufacturing performance. In terms of practices, manufacturers should focus on clean technology, green processes, lifecycle management, waste recycling, and textile waste generation and management. These criteria will help the textile industry in Vietnam to become more sustainable and environmentally friendly since the most important criteria involve realizing green manufacturing.

Keywords: Green manufacturing; Government policy; Green operational practices; Fuzzy Delphi method; Fuzzy decision-making trial and evaluation laboratory; Analytic network process (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:268:y:2024:i:c:s0925527323003493

DOI: 10.1016/j.ijpe.2023.109117

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