Multi-criteria decision making to explore the relationship between supply chain mapping and performance
In today’s highly dynamic and volatile business environment, the performance of a supply chain significantly depends on its structure, technological capabilities, and the adaptability of its constituent stages. Supply chain mapping, an approach to represent complex supply chain networks, is crucial for enhancing supply chain performance by identifying critical linkages, flows, and relationships. Despite its strategic importance, the specific impacts of supply chain mapping attributes on various performance indicators remain underexplored. Addressing this research gap, this study investigates the relationships between key supply chain mapping attributes ( e.g ., information flow, lead-time, mode of transportation) and supply chain performance indicators ( e.g ., reliability, responsiveness, agility). To achieve this, the study employs a multi-step analytical approach: first, relevant attributes are identified through a systematic literature review; second, these attributes are validated using the Delphi method involving international supply chain experts; finally, the Grey Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) technique is applied to establish interrelationships among the attributes. Findings reveal that information flow is the most influential supply chain mapping attribute, significantly impacting multiple performance indicators, especially supply chain responsiveness. The novelty of this research lies in its integrative use of Delphi and Grey-DEMATEL methods, providing practitioners with actionable insights into effectively leveraging supply chain mapping to achieve strategic performance improvements. • Analyze the relationship between supply chain mapping and performance using decision analytics. • Identify information flow as the most critical factor influencing supply chain performance. • Utilize the Delphi method and Grey-DEMATEL technique for structured decision-making. • Highlight transportation mode and material flow as key drivers of operational efficiency. • Provide practical insights for managers to enhance supply chain responsiveness and strategy.
Authors
- Muhammad Shujaat Mubarik (ORCID: https://orcid.org/0000-0003-1207-6427)
- Angappa Gunasekaran (ORCID: https://orcid.org/0000-0002-6335-1962)
- Sharfuddin Ahmed Khan (ORCID: https://orcid.org/0000-0002-5822-0933)
- Md Ainul Kabir (ORCID: https://orcid.org/0009-0003-3648-6858)
Institutions
- University of Regina (CA)
- Heriot-Watt University (GB)
- Heriot-Watt University Malaysia (MY)
- Pennsylvania Department of Agriculture (US)
Publication Details
- Journal
- Decision Analytics Journal
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1016/j.dajour.2025.100577
- Citations
- 4
- Primary Topic
- Quality and Supply Management
- Type
- article
- Field-Weighted Citation Impact
- 9.14