Whose Investment in Pollution Abatement Is Better for the Environment in a Textile and Garment Supply Chain When Considering Risk Attitudes?

The environmental pollution problem in the textile and garment industry has become increasingly severe, necessitating urgent mitigation. This study examines which supply chain member’s pollution abatement investment generates greater benefits for both the supply chain and the environment, particularly under demand uncertainty. We consider a three-tier textile and garment supply chain and employ uncertainty theory to model member risk attitudes via confidence levels. Based on this, uncertain demand and profit functions are formulated under different investment scenarios—single investment and joint investment. Our comparative analysis reveals that pollution abatement investment by either the fabric manufacturer or the garment manufacturer contributes to environmental sustainability. Which member’s investment is more advantageous for both the environment and supply chain performance depends on their respective cost coefficients. Interestingly, under certain conditions, the fabric manufacturer may derive greater benefit from the garment manufacturer’s investment than from its own. Furthermore, while both the fabric manufacturer and the garment retailer gain more from joint manufacturer investments than from a single manufacturer’s investment, the same does not hold for the garment manufacturer. Finally, as the three members become more risk-averse, both the optimal pollution abatement level and the profits of all members decrease.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2025-10-18
DOI
https://doi.org/10.3390/math13203326
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Whose Investment in Pollution Abatement Is Better for the Environment in a Textile and Garment Supply Chain When Considering Risk Attitudes?

Jianfeng Hu, Hua Ke, Jinjin Liu, Qigui Lang
Mathematics
Sustainable Supply Chain Management
article

Whose Investment in Pollution Abatement Is Better for the Environment in a Textile and Garment Supply Chain When Considering Risk Attitudes?

Jianfeng Hu, Hua Ke, Jinjin Liu, Qigui Lang
article en

Abstract

The environmental pollution problem in the textile and garment industry has become increasingly severe, necessitating urgent mitigation. This study examines which supply chain member’s pollution abatement investment generates greater benefits for both the supply chain and the environment, particularly under demand uncertainty. We consider a three-tier textile and garment supply chain and employ uncertainty theory to model member risk attitudes via confidence levels. Based on this, uncertain demand and profit functions are formulated under different investment scenarios—single investment and joint investment. Our comparative analysis reveals that pollution abatement investment by either the fabric manufacturer or the garment manufacturer contributes to environmental sustainability. Which member’s investment is more advantageous for both the environment and supply chain performance depends on their respective cost coefficients. Interestingly, under certain conditions, the fabric manufacturer may derive greater benefit from the garment manufacturer’s investment than from its own. Furthermore, while both the fabric manufacturer and the garment retailer gain more from joint manufacturer investments than from a single manufacturer’s investment, the same does not hold for the garment manufacturer. Finally, as the three members become more risk-averse, both the optimal pollution abatement level and the profits of all members decrease.

MathematicsVol. 13(20)
Tongji University (CN), Zhejiang Sci-Tech University (CN), Yangzhou University (CN)
Openalex Percentile: Top 56%
Sustainable Supply Chain Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.