An integrated Fuzzy MCDM approach for modelling and prioritising the enablers of responsiveness in automotive supply chain using Fuzzy DEMATEL, Fuzzy AHP and Fuzzy TOPSIS

In this dynamic environment with unexpected changes and high market rivalry, supply chains focus more on executing responsive strategies with minimum costs. This research paper aims to identify the crucial enablers of responsiveness of the Indian automotive supply chain. Seventeen enablers were iden...

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Bibliographic Details
Published in:Soft computing (Berlin, Germany) Germany), 2023, Vol.27 (1), p.257-277
Main Authors: Sathyan, Rinu, Parthiban, P., Dhanalakshmi, R., Sachin, M. S.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computational Intelligence
Control
Engineering
Fuzzy Systems and Their Mathematics
Mathematical Logic and Foundations
Mechatronics
Robotics
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Summary:In this dynamic environment with unexpected changes and high market rivalry, supply chains focus more on executing responsive strategies with minimum costs. This research paper aims to identify the crucial enablers of responsiveness of the Indian automotive supply chain. Seventeen enablers were identified from the extensive literature and expert interview for supply chain responsiveness and an integrated methodology of Fuzzy multi-criteria decision-making (MCDM) using Fuzzy DEMATEL, Fuzzy AHP and Fuzzy TOPSIS is applied for modelling and prioritising the enablers. The proposed model revealed the most crucial responsiveness enablers for the supply chain. The top three significant causal enablers derived from Fuzzy DEMATEL are Commitment of management and Strategy decision making, Demand forecasting and Continuous improvement. The Fuzzy AHP–Fuzzy TOPSIS result imply that automotive manufacturer should pay close attention towards Commitment of management and Strategy decision making, Waiting period for vehicle's delivery and Demand forecasting. The proposed framework suggests strategic goals to guide different supply chain members and automotive industry decision-makers towards improved supply chain responsiveness.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-022-07591-x