Fermatean fuzzy group decision model for agile, resilient and sustainable logistics service provider selection in the manufacturing industry
Abstract
Purpose
Logistics service provider (LSP) selection involves multiple criteria, alternatives and decision makers. Group decision-making involves vagueness and uncertainty. This paper aims to propose a novel fuzzy method for assessing and selecting agile, resilient and sustainable LSP, taking care of the inconsistency and uncertainty in subjective group ratings.
Design/methodology/approach
Eighteen agile, resilient, operational, economic, environmental and social sustainability criteria were identified from the literature and discussion with experts. Interval-valued Fermatean fuzzy (IVFF) sets are more flexible and accurate for handling complex uncertainty, impreciseness and inconsistency in group ratings. The IVFF PIvot Pairwise RElative Criteria Importance Assessment Simplified (IVFF-PIPRECIAS) and IVFF weighted aggregated sum product assessment (IVFF-WASPAS) methods are applied to determine criteria weights and LSP evaluation, respectively.
Findings
Collaboration and partnership, range of services, capacity flexibility, geographic coverage, cost of service and environmental safeguard are found to have a greater influence on the LSP selection, as per this study. The LSP (L3) with the highest score (0.949) is the best agile, resilient and sustainable LSP in the manufacturing industry.
Research limitations/implications
Hybrid IVFF-based PIPRECIAS and WASPAS methods are proposed for the selection of agile, resilient and sustainable LSP in the manufacturing industry.
Practical implications
The model can help supply chain managers in the manufacturing industry to easily adopt the hybrid model for agile, resilient and sustainable LSP selection.
Social implications
The paper also contributes to the social sustainability of logistics workers.
Originality/value
To the best of the authors’ knowledge, IVFF-PIPRECIAS and IVFF-WASPAS methods are applied for the first time to select the best agile, resilient and sustainable LSP in a developing economy context.
Keywords
Acknowledgements
Conflict of Interest: There are no relevant financial or non-financial competing interests to report.
Funding: This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.
Data availability statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
The authors would like to express sincere thanks to anonymous reviewers for their invaluable feedbacks which greatly improved the paper.
Citation
Akhtar, M. (2024), "Fermatean fuzzy group decision model for agile, resilient and sustainable logistics service provider selection in the manufacturing industry", Journal of Modelling in Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JM2-02-2024-0040
Publisher
:Emerald Publishing Limited
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