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Betweenness-Based Method to Identify Critical Transmission Sectors for Supply Chain Environmental Pressure Mitigation
Sai Liang1, Shen Qu1, Ming Xu1,2
1School of Natural Resources and Environment, University of Michigan , Ann Arbor, Michigan 48109-1041, United States.
This study introduces a new network analysis method to identify key sectors that transmit environmental pressures through supply chains. This approach complements existing methods for targeted environmental mitigation strategies.
Area of Science:
- Environmental Science
- Economics
- Network Analysis
Background:
- Existing methods for environmental pressure mitigation focus on direct (production-based) or indirect (consumption-based) sector impacts.
- Sectors acting as 'transmission centers' in supply chains are crucial but often overlooked for mitigation.
Purpose of the Study:
- To develop and apply a novel betweenness-based method for identifying critical transmission sectors.
- To complement existing approaches for economy-wide environmental pressure mitigation.
Main Methods:
- Utilized network analysis concepts, specifically 'betweenness centrality', to measure sector importance.
- Quantified sector betweenness by analyzing supply chain paths via structural path analysis.
- Applied the method to China's economy as a case study.
Main Results:
- Identified critical transmission sectors that are not always recognized by traditional production- or consumption-based methods.
- Demonstrated that the betweenness-based method offers unique insights into sector roles in environmental pressure generation.
- Highlighted the importance of improving production efficiency in these identified transmission sectors.
Conclusions:
- The betweenness-based method provides a valuable addition to existing tools for environmental pressure mitigation.
- This approach can guide more effective sector-level strategies by focusing on key transmission hubs.
- Findings underscore the interconnectedness of economic activities and their environmental consequences through supply chains.
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