Identifying key influencing factors and their hierarchical structure for green supply chain management in China’s aerospace manufacturing using DEMATEL-ISM

Abstract Green supply chain management in the aerospace manufacturing industry is a complex systematic project, and it is decisive for implementing green supply chain management to clarify the hierarchical relationship and critical factors among influencing factors. First, this study considers the aerospace manufacturing industry as the research object and constructs an influencing factor system of green supply chain management in the aerospace manufacturing industry in context of Tripple Bottom Line (TBL) of sustainability which includes society, economic, and environmental perspective. Second, the Decision-making Trial and Evaluation Laboratory (DEMATEL) was used to calculate influence degree, influenced degree, degree of centrality, and cause degree of each influence factor to reveal the importance of each influence factor. Then, based on the Interpretative Structural Modeling (ISM), a multi-level hierarchical interpretation structure model of the influencing factors for green supply chain management (GSCM) in the aerospace manufacturing industry was constructed. Finally, combined with the analysis results of the DEMATEL-ISM model, the key influencing factors of green supply chain management in the aerospace manufacturing industry were identified. The factors affecting green supply chain management in the aerospace manufacturing industry can be divided into five levels, with seven key influencing factors: government subsidies and policy support, environmental culture guidance, corporate green strategy orientation, corporate executives’ environmental awareness, green cooperation degree, corporate internal environmental management, and corporate external environmental behavior. This study not only enriches the existing theoretical system of green supply chain management to a certain extent, but also provides a theoretical basis for government and aerospace manufacturing enterprises to implement green supply chain management practices. Specifically, the identification of key factors and their distinct hierarchical roles provides policymakers and aerospace enterprises with a clear roadmap for prioritizing interventions, allocating resources efficiently, and developing targeted strategies to enhance GSCM implementation.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-30
DOI
https://doi.org/10.1038/s41598-026-39587-0
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying key influencing factors and their hierarchical structure for green supply chain management in China’s aerospace manufacturing using DEMATEL-ISM

Xiaocui Li, Wang Fen, Jian Zheng, Yingzhen Chen et al.
Scientific Reports
Sustainable Supply Chain Management
article

Identifying key influencing factors and their hierarchical structure for green supply chain management in China’s aerospace manufacturing using DEMATEL-ISM

Xiaocui Li, Wang Fen, Jian Zheng, Yingzhen Chen, Cheng Wang
article en

Abstract

Abstract Green supply chain management in the aerospace manufacturing industry is a complex systematic project, and it is decisive for implementing green supply chain management to clarify the hierarchical relationship and critical factors among influencing factors. First, this study considers the aerospace manufacturing industry as the research object and constructs an influencing factor system of green supply chain management in the aerospace manufacturing industry in context of Tripple Bottom Line (TBL) of sustainability which includes society, economic, and environmental perspective. Second, the Decision-making Trial and Evaluation Laboratory (DEMATEL) was used to calculate influence degree, influenced degree, degree of centrality, and cause degree of each influence factor to reveal the importance of each influence factor. Then, based on the Interpretative Structural Modeling (ISM), a multi-level hierarchical interpretation structure model of the influencing factors for green supply chain management (GSCM) in the aerospace manufacturing industry was constructed. Finally, combined with the analysis results of the DEMATEL-ISM model, the key influencing factors of green supply chain management in the aerospace manufacturing industry were identified. The factors affecting green supply chain management in the aerospace manufacturing industry can be divided into five levels, with seven key influencing factors: government subsidies and policy support, environmental culture guidance, corporate green strategy orientation, corporate executives’ environmental awareness, green cooperation degree, corporate internal environmental management, and corporate external environmental behavior. This study not only enriches the existing theoretical system of green supply chain management to a certain extent, but also provides a theoretical basis for government and aerospace manufacturing enterprises to implement green supply chain management practices. Specifically, the identification of key factors and their distinct hierarchical roles provides policymakers and aerospace enterprises with a clear roadmap for prioritizing interventions, allocating resources efficiently, and developing targeted strategies to enhance GSCM implementation.

Scientific ReportsVol. 16(1)
Hubei University of Arts and Science (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
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.