Authors: Stević, Željko
Miškić, Smiljka
Vojinović, Dragan
Huskanović, Eldina
Stanković, Miomir 
Pamučar, Dragan
Affiliations: Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Development of a Model for Evaluating the Efficiency of Transport Companies: PCA–DEA–MCDM Model
Journal: Axioms
Volume: 11
Issue: 3
First page: 140
Issue Date: 1-Mar-2022
Rank: ~M22
ISSN: 2075-1680
DOI: 10.3390/axioms11030140
Abstract: 
The efficiency of transport companies is a very important factor for the companies them-selves, as well as for the entire economic system. The main goal of this paper is to develop an integrated model for determining the efficiency of representative transport companies over a period of eight years. An original model was developed that includes the integration of DEA (Data Envelopment Analysis), PCA (Principal Component Analysis), CRITIC (Criteria Importance Through Inter criteria Correlatio), Entropy and MARCOS (Measurement Alternatives and Ranking according to the COmpromise Solution) methods in order to determine the final efficiency of transport companies based on 10 input–output parameters. The results showed that the most efficient business performance was achieved in the period 2014–2017, followed by slightly less efficient results. Then, extensive sensitivity analysis and comparative analysis were performed, which confirmed, to some extent, the previously obtained results. In the sensitivity analysis, 30 scenarios with changes in the weights of criteria were created, while the comparative analysis was carried out with three other MCDM (Multi-Criteria Decision-Making) methods. Finally, the rank correlation index was deter-mined using the Spearman and WS (Wojciech Salabun) correlation coefficients. According to the final results, very efficient years can be separated that can be the benchmark for furthering the business.
Keywords: costs | efficiency | logistics | MARCOS | PCA–DEA | transport
Publisher: MDPI

Show full item record

SCOPUSTM   
Citations

21
checked on Apr 24, 2024

Page view(s)

34
checked on Apr 24, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.