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

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.