Özdemir, Mustafa2025-06-232025-06-23202522105395https://hdl.handle.net/11494/5599Performance evaluation studies conducted for the logistics sector can help managers take efficient and effective actions and achieve success in their strategies. In this study, a fuzzy-based model that considers a wide range of uncertainties for global logistics performance measurement is proposed. The logistics performance of 112 countries was examined in a Fermatean fuzzy environment by combining the Logistics Performance Index presented by the World Bank and the Liner Shipping Connectivity Index published by the United Nations. In the first stage of the two-stage application, the importance level weights of the variables used in logistics performance measurement were calculated based on expert opinions. In the second stage, the recently proposed Compromise Ranking of Alternatives from Distance to Ideal Solution method was expanded into the Fermatean fuzzy environment, and the logistics performance scores of the countries were measured. According to the study results, the Liner Shipping Connectivity Index (0.420) was identified as the most important variable in logistics performance measurement. Singapore achieved the highest logistics performance score across all applied method parameters, highlighting its exceptional performance. Singapore stands out as a best-practice example for countries aiming to improve their logistics performance. The measurement results of logistics performance in the new model, which considers the widest level of uncertainty through various sensitivity analyses, are promising. The study results provide valuable insights for researchers, decision-makers, and policymakers regarding performance measurement in the logistics sector. The proposed model for global logistics performance measurement is expected to make a significant contribution to the literature.eninfo:eu-repo/semantics/embargoedAccessFermatean fuzzyLogisticsLPILSCIMulti-criteria decision makingArticle6110.1016/j.rtbm.2025.1014152-s2.0-105005576581Q1WOS:001499523400001Q2