International Journal of Railway Research
Iran University of Science & Technology
Tue, Jul 16, 2024
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Volume 4, Issue 1 (3-2017)
IJRARE 2017, 4(1): 47-55 |
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Khadem Sameni M, Kashi Mansouri M R. Analyzing Efficiency of Railway Transportation by Considering Quality of Services: New
Data Envelopment Analysis Models. IJRARE 2017; 4 (1) :47-55
URL: http://ijrare.iust.ac.ir/article-1-176-en.html
URL: http://ijrare.iust.ac.ir/article-1-176-en.html
School of Railway Engineering, Iran University of Science and Technology
Abstract: (2261 Views)
Many studies have been conducted to analyze efficiency of railways for different
countries. However, these studies have mainly focused on quantitative aspects of
railway transportation and quality has been neglected. In this paper three new
data envelopment analysis (DEA) models are presented. The first model is
solved for assessing quality of passenger railway services in 71 countries of the
world by including perceived quality of railways among outputs of DEA models
for the first time in the literature. For the second model which is applied to 27
railways in Europe, a safety index is defined based on number of fatalities and
serious injuries and is added as another output. Both models are solved for
constant return to scale (CRS) as well as variable return to scale (VRS) setting
with output orientation. The follow-up Tobit regression for the first model shows
that efficiency results are positively correlated with quality of road and for the
second model negatively correlated with the number of level crossings. In the
third model which is applied to 19 train operating companies in the UK,
passenger-km is the input and stated passenger satisfaction derived from
questionnaires together with punctuality level are outputs which proved to be
helpful for ranking companies based on quality of their services.
countries. However, these studies have mainly focused on quantitative aspects of
railway transportation and quality has been neglected. In this paper three new
data envelopment analysis (DEA) models are presented. The first model is
solved for assessing quality of passenger railway services in 71 countries of the
world by including perceived quality of railways among outputs of DEA models
for the first time in the literature. For the second model which is applied to 27
railways in Europe, a safety index is defined based on number of fatalities and
serious injuries and is added as another output. Both models are solved for
constant return to scale (CRS) as well as variable return to scale (VRS) setting
with output orientation. The follow-up Tobit regression for the first model shows
that efficiency results are positively correlated with quality of road and for the
second model negatively correlated with the number of level crossings. In the
third model which is applied to 19 train operating companies in the UK,
passenger-km is the input and stated passenger satisfaction derived from
questionnaires together with punctuality level are outputs which proved to be
helpful for ranking companies based on quality of their services.
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