Climate change adaptation and disaster risk reduction in the garment industry supply chain network. (March 2023)
- Record Type:
- Journal Article
- Title:
- Climate change adaptation and disaster risk reduction in the garment industry supply chain network. (March 2023)
- Main Title:
- Climate change adaptation and disaster risk reduction in the garment industry supply chain network
- Authors:
- Bag, Surajit
Sabbir Rahman, Muhammad
Rogers, Helen
Srivastava, Gautam
Harm Christiaan Pretorius, Jan - Abstract:
- Highlights: MNE customers have a positive association with the compliance of local suppliers to CCA and DRR goals. MNE customers have a positive association with the commitment of local suppliers to CCA and DRR goals. Non-MNE customers do not show any association with compliance and commitment of local suppliers to CCA and DRR goals. AI-SRM capability is found to exert a moderating effect. Mitigating climate change and disaster risks among sub-supplier are critical for enhancing social sustainability. Abstract: This study empirically tested the relationships of multinational enterprises (MNE) and non-MNE customer pressures with the compliance and commitment of garment industry suppliers to climate change adaptation (CCA) and the disaster risk reduction (DRR) goal (sustainable development goal 13). It further investigated the effect of mitigating climate change and disaster risks among sub-suppliers in the supply chain (SC) network on SC sustainability performance under the moderating effect of artificial intelligence-powered supplier-relationship management. The study applied a mixed-methods research approach. The literature review led to the development of the theoretical model and hypotheses generation and further testing, using structural equation modeling, which was followed by the qualitative investigation completed during the second phase. This study highlights the motivation behind CCA and DRR-related practices that can guide SC managers when creating effectiveHighlights: MNE customers have a positive association with the compliance of local suppliers to CCA and DRR goals. MNE customers have a positive association with the commitment of local suppliers to CCA and DRR goals. Non-MNE customers do not show any association with compliance and commitment of local suppliers to CCA and DRR goals. AI-SRM capability is found to exert a moderating effect. Mitigating climate change and disaster risks among sub-supplier are critical for enhancing social sustainability. Abstract: This study empirically tested the relationships of multinational enterprises (MNE) and non-MNE customer pressures with the compliance and commitment of garment industry suppliers to climate change adaptation (CCA) and the disaster risk reduction (DRR) goal (sustainable development goal 13). It further investigated the effect of mitigating climate change and disaster risks among sub-suppliers in the supply chain (SC) network on SC sustainability performance under the moderating effect of artificial intelligence-powered supplier-relationship management. The study applied a mixed-methods research approach. The literature review led to the development of the theoretical model and hypotheses generation and further testing, using structural equation modeling, which was followed by the qualitative investigation completed during the second phase. This study highlights the motivation behind CCA and DRR-related practices that can guide SC managers when creating effective sustainability policies. … (more)
- Is Part Of:
- Transportation research. Volume 171(2023)
- Journal:
- Transportation research
- Issue:
- Volume 171(2023)
- Issue Display:
- Volume 171, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 171
- Issue:
- 2023
- Issue Sort Value:
- 2023-0171-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-03
- Subjects:
- Climate change -- Disaster risks -- Normative isomorphism -- Supply chain -- Garment industry
Logistics -- Periodicals
Transportation -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13665545 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tre.2023.103031 ↗
- Languages:
- English
- ISSNs:
- 1366-5545
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274640
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British Library HMNTS - ELD Digital store - Ingest File:
- 26001.xml