Evaluating logistics sector sustainability indicators using multi-expert Fermatean fuzzy entropy and WASPAS methodology

Purpose This study has two objectives: to identify sector-specific sustainability indicators from the literature and industry and to evaluate their importance through expert input. Design/methodology/approach The analysis was conducted using the Fermatean fuzzy entropy and WASPAS method. Findings The study found that, according to experts, the most important sustainability dimension was economic, followed by environmental and social. However, the analysis conducted using the sub-indicators indicated a difference in the experts’ perceptions based on the three dimensions of sustainability and when examples were given of practical applications related to these dimensions. Practical implications To identify and prioritize logistics sector-specific indicators by integrating sustainability dimensions to support sustainable logistics practices. Also provides a methodological framework for improving and benchmarking sustainability performance in the sector by aligning these indicators with the SDGs. Originality/value Offers a holistic assessment of sustainability in logistics by integrating its three dimensions and aligning with SDGs to highlight their contributions. Provides valuable insights for countries with emerging sustainable logistics sectors and distinguishes itself methodologically. Also, experts were grouped and weighted based on prioritizing the input of highly qualified participants.

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Publication Details

Journal
Journal of International Logistics and Trade
Published
2025-03-07
DOI
https://doi.org/10.1108/jilt-10-2024-0078
Citations
5
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
10.53
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article

Evaluating logistics sector sustainability indicators using multi-expert Fermatean fuzzy entropy and WASPAS methodology

Bahadır Fatih Yıldırım, Ebru Demirci, İlknur Gizem Yazar Okur, Bükra Doğaner Duman
5 citations
Journal of International Logistics and Trade
Multi-Criteria Decision Making
10.53
article

Evaluating logistics sector sustainability indicators using multi-expert Fermatean fuzzy entropy and WASPAS methodology

Bahadır Fatih Yıldırım, Ebru Demirci, İlknur Gizem Yazar Okur, Bükra Doğaner Duman
article en
5 citations

Abstract

Purpose This study has two objectives: to identify sector-specific sustainability indicators from the literature and industry and to evaluate their importance through expert input. Design/methodology/approach The analysis was conducted using the Fermatean fuzzy entropy and WASPAS method. Findings The study found that, according to experts, the most important sustainability dimension was economic, followed by environmental and social. However, the analysis conducted using the sub-indicators indicated a difference in the experts’ perceptions based on the three dimensions of sustainability and when examples were given of practical applications related to these dimensions. Practical implications To identify and prioritize logistics sector-specific indicators by integrating sustainability dimensions to support sustainable logistics practices. Also provides a methodological framework for improving and benchmarking sustainability performance in the sector by aligning these indicators with the SDGs. Originality/value Offers a holistic assessment of sustainability in logistics by integrating its three dimensions and aligning with SDGs to highlight their contributions. Provides valuable insights for countries with emerging sustainable logistics sectors and distinguishes itself methodologically. Also, experts were grouped and weighted based on prioritizing the input of highly qualified participants.

Journal of International Logistics and TradeVol. 23(2)
Istanbul Commerce University (TR)
Openalex Percentile: Top 2%
Multi-Criteria Decision Making
10.53
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Evaluating logistics sector sustainability indicators using multi-expert Fermatean fuzzy entropy and WASPAS methodology — Bahadır Fatih Yıldırım, Ebru Demirci, et al. · Journal of International Logistics and Trade (2025) | TGRS Research Map | TGRS