Erdoğan, Hilal H.KIRBAÇ, GÖKHAN2023-01-312023-01-312021ERDOĞAN H, KIRBAÇ G (2021). Financial Performance Measurement of Logistics Companies Based on Entropy and Waspas Methods. İşletme Araştırmaları Dergisi, 13(2), 1093 - 1106. 10.20491/isarder.2021.1186https://doi.org/10.20491/isarder.2021.1186https://hdl.handle.net/11413/8285Purpose – The aim of this study is to measure financial performance of the logistics companies in the Fortune500 list. Companies' financials are used to enlighten the logistics sector and supply chain operations byrevealing the developments between 2015 and 2019. Design/Methodology/Approach – The performance of the companies is evaluated by utilizing multi-criteriadecision-making techniques. As the best performance criteria affecting the companies’ performance isdetermined by Entropy Method, the company with the best performance is determined by WASPASMethod. Selected financial measurements are net sales, earnings before interest and taxes (EBIT), total assets, totalequity, and the amount of export. Findings – It can be reached from the results that Export was determined as the best performance criteriaaffecting the logistics companies’ performance for all the years between 2015 and 2019. On the other hand,while Netlog is the best alternative in the year of 2015, 2016 and 2019, Borusan is the best alternative in theyear of 2017. Discussion – Supply chain and logistics processes have critical importance in delivering the goods andservices of businesses to the final consumers. Hence, logistics companies need to determine performancemeasurements while performing these services. It is believed that this study will be useful for the companieswho trade in different sectors and will contribute to the finance literature as a reference for further studies.In this context, because of their quite comprehensive natures, both Entropy and WASPAS methods can beconducted to any manufacturing-related decision-making processes.eninfo:eu-repo/semantics/openAccessFinancial PerformanceLogistics PerformanceSupply ChainEntropy WeightsWASPASArticle1309-0712