Quantitative Analysis in Prioritizing Elements for Efficient Logistics Strategies: A Case Study in Eskişehir

Authors

https://doi.org/10.48314/ramd.v2i2.69

Abstract

Logistics strategies are essential elements in the concepts of designing and operating logistics processes and systems, identifying visions, selecting feasible goals, constructing plans, decisions, and policies that help businesses in achieving their goals. Also, the issues of implementing logistics services in a shorter time, customer suitability, low cost, and customer support from pre- to after-sales have an impact on the customers’ service perceptions. By this means, better customer satisfaction can be achieved. However, the importance of factors in logistics strategy according to the customer's perspective needs to be determined. Value-added elements of acquiring internal and external customer satisfaction, decreasing costs, strengthening visibility, and presenting the right product to the right customers in a suitable place, as promotion activity shows the importance of logistics strategies for businesses. In this study, elements effective in forming logistic strategies for manufacturing firms having more than 50 employees in Eskişehir are aimed to prioritize. DEMATEL, as a Multi-Criteria Decision-Making (MCDM) technique, examines the logical relationship of factors, and researching the direct influence matrix in a complex system is handled as a prioritization method. Pythagorean Fuzzy Sets (PFS) are preferred to better explain the judgments of decision-makers in uncertainty by giving more flexibility than fuzzy and Intuitionistic Fuzzy Sets (IFS). 

Keywords:

Logistics, Forming logistics strategy, Pythagorean fuzzy sets, DEMATEL

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Published

2025-06-14

Issue

Vol. 2 No. 2 (2025): Risk Assessment and Management Decisions (RAMD)

Section

Articles

How to Cite

Korucuk, S. ., Bayazit Bedirhanoğlu, Şule ., & Karamaşa, Çağlar . (2025). Quantitative Analysis in Prioritizing Elements for Efficient Logistics Strategies: A Case Study in Eskişehir. Risk Assessment and Management Decisions, 2(2), 95-106. https://doi.org/10.48314/ramd.v2i2.69