The Selection of a Possible Organizational Structure of Railway Companies by Application Fuzzy-ARAS Method

Authors

DOI:

https://doi.org/10.54327/set2023/v3.i1.42

Keywords:

railway, Multi-Criteria Decision Making (MCDM) , fuzzy Additive Ratio ASsessment (ARAS) , organizational structure, triangular fuzzy numbers

Abstract

The European railway sector doesn't represent a single, generic type of organizational structure. The Directives from the 1990s offer the possibility for national interpretation giving a wide range of organizational structures for European railways. Different organizational structures of railways are present in the European railway market, and all of them are aligned with the national belief of the country - how to manage the railway. This paper focuses on Multi-Criteria Decision Making (MCDM) methods for ranking and selecting organizational structures of railways. In decision-making, we deal with different types of uncertainty and inaccuracy. For this purpose, we need to use some specific tools. In this paper, we use triangular fuzzy numbers to quantify linguistic data. To overcome the complexity of the decision-making problem, we propose the fuzzy Additive Ratio ASsessment (ARAS) method, which also includes linguistic variables and a group approach to decision-making. With the proposed methodology an evaluation of the alternatives to the organization structure of the railway company in Bosnia and Herzegovina is considered. Separation of railway transport from infrastructure management is ranked as the best organizational structure for this company.

Downloads

Download data is not yet available.

Downloads

Published

23.02.2023

Data Availability Statement

Supplementary materials and data used in this research are accessible upon request. For access, please contact the corresponding author.

Issue

Section

Research Article

Categories

How to Cite

[1]
N. Čabrić, N. Branković, and A. Kalem, “The Selection of a Possible Organizational Structure of Railway Companies by Application Fuzzy-ARAS Method”, Sci. Eng. Technol., vol. 3, no. 1, pp. 22–32, Feb. 2023, doi: 10.54327/set2023/v3.i1.42.

Similar Articles

1-10 of 36

You may also start an advanced similarity search for this article.