Abstract
The logistics industry is significantly important in international trade; European logistics market is worth over 1.1 trillion euros. There are 240 freight villages established in Europe, and the logistics sector ranked third. The value of freight village is increasing in the economic system and the logistics industry. Presenting information by measuring the efficiency of freight village is important to help companies investing in this area. It is deemed necessary to determine the level of efficient operation of the freight village, to increase their performance, and to analyze the efficient use of their resources. This study aims to determine the interactions between criteria and the criteria priorities for the freight village efficiency evaluation. After selecting the significant criteria from related literature, pairwise comparisons as data are obtained from experts’ views. The interactions between criteria via fuzzy DEMATEL method and priorities via fuzzy AHP method are determined. According to findings, “annual amount of freight transport” is determined as the general affecting and overwhelmingly the most important criterion; then, it is recommended to decision makers/researchers to consider that criterion with a high weight in the freight village efficiency evaluation. On the other hand, “number of employees” is observed as both the highly impressed and least important criterion; then, it may be ignored in freight village assessments or represented with a significantly too small weight, with its controversial position in the output or input. One of the originalities of this study is that considering the DEMATEL-AHP results together at the evaluation stage of each criterion; it provides an opportunity to present unique perspectives on the process of analyzing the criteria.
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Pekkaya, M., Keleş, N., Çakır, F.S. (2023). Freight Village Efficiency Criteria Evaluation via Fuzzy Multi-criteria Decision-Making Methods. In: Sahoo, L., Senapati, T., Yager, R.R. (eds) Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain. Studies in Fuzziness and Soft Computing, vol 420. Springer, Singapore. https://doi.org/10.1007/978-981-19-4929-6_30
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