Benchmarking of rail transport service performance through DEA for Indian railways

DOIhttps://doi.org/10.1108/IJLM-08-2014-0122
Pages629-649
Published date14 November 2016
Date14 November 2016
AuthorMohita Gangwar Sharma,Roma Mitra Debnath,Richard Oloruntoba,Sachinder Mohan Sharma
Subject MatterManagement science & operations,Logistics
Benchmarking of rail transport
service performance through
DEA for Indian railways
Mohita Gangwar Sharma
Department of Quantitative Techniques and Operations Management,
FORE School of Management, New Delhi, India
Roma Mitra Debnath
Indian Institute of Public Administration, Delhi, India
Richard Oloruntoba
Newcastle Business School, Callaghan, Australia, and
Sachinder Mohan Sharma
Department of Management,
National Academy of Indian Railways, Vadodara, India
Abstract
Purpose Railway transport being a serviceis provided in a space and time dimension. Providing a
better quality of service requires higher inputs, so evaluating the performance without these
considerations would give a biased result. The purpose of this paper is to assess the performance of the
rail transport service by including the service delivery perspective of railways and look at the holistic
concept of service delivery. The quality of service parameters have been chosen within the constraints
imposed by availability of data and the formulated data envelopment analysis (DEA). The quality of
service parameters include: punctuality; the level of consequential train accidents (safety); and the level
of public complaints (customer satisfaction). It evaluates the performance of 16 zones of Indian
railways (IR) on the basis of their efficiencies and identifies the exemplar zones. The results deduced
from these studies can serve as performance targets in reward systems, performance scorecards, and
control systems.
Design/methodology/approach DEA has been used as a benchmarking tool to evaluate the
relative efficiency of the 16 zones. The input parameters are working expenses, number of employees,
and equated track kilometers and the output parameters are loading of revenue, punctuality, passenger
traffic kilometers, consequential train accidents, and public complaints. Malmquist index has been
used to determine the temporal performance of each zone.
Findings IR can use DEA to assess the performance of various zones and for improvement
monitoring in the context of being a transport service provider. Inefficient zones can identify the
parameters for improvement across the zones and along the time dimension. A huge working force for
all the inefficient zones indicate over deployment of resources, which can be seen at the policy level.
A redundancy for equated track kilometers indicates a non-optimum use of resources. Not giving
enough importance to service quality could be one of the major findings of the inefficient zones.
Research limitations/implications The scope of the quality of service variables assessed could
not be enlarged in this study because of the limitation of the number of variables that can be chosen for
a given number of decision-making units in the model. It is not always possible to compare each zone
on an exactly equal basis as the work culture and challenges differ across zones, units, regions, and
states which poses a limitation to the study.
Practical implications The holistic evaluation of performance of IR by inclusion of the service
parameterscan have importantimplications forthe industry. The choice,incorporation, andinterpretation The International Journal of
Logistics Management
Vol. 27 No. 3, 2016
pp. 629-649
©Emerald Group Publis hing Limited
0957-4093
DOI 10.1108/IJLM-08-2014-0122
Received 9 August 2014
Revised 31 August 2015
28 September 2015
Accepted 29 September 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0957-4093.htm
The Infrastructural Support provided by FORE School of Management, New Delhi is deeply
acknowledged.
629
Benchmarking
of rail transport
service
performance
of the parameters of this studycan be adopted for rail transportation industry. This alsosummarizes the
essence of performance and quality of service in public rail transport sector.
Social implications The global public transport sector, and the rail mode in particular faces the
challenge of identifying, and using appropriate service quality indicators and financial parameters to
ascertain the efficiency and effectiveness of the transport system, rather than considering financial
parameters alone. The context of this study is IR which is an engine for the continued socio-economic
development of India. The overarching constraint is that the inputs are already established. Within this
socio-economic contextual framework the analysis has been done to have an efficient and effective
public transport system.
Originality/value This is the first study which incorporates the quality of service dimensions in
performance measurement and benchmarking of the railway zones that make up a national railway
system which is under public domain. Each of these characteristics offers its unique challenges and
dimensions which makes the problem complex.
Keywords Customer services quality, Asia, Transportation management
Paper type Research paper
1. Introduction
Transport systems are the lifeline of any country (Ortega et al., 2014; Parikesit and
Susantono, 2013). They enable economic exchange, maintain high standards of
consumption and quality of life, and confer territorial cohesion (Mazaheri et al., 2013;
Holmgren, 2007; Banister, 1996). Furthermore, efficient transport systems have a
multiplier effect on the national and international economy (Hazledine et al., 2013;
Banister, 1996). They enhance economic productivity, and contribute to increases in
national output, and national competitiveness (Blanke and Chiesa, 2013; Crescenzi and
Rodríguez-Pose, 2013).
However, the challenge of increasing the efficiency and effectiveness of public
transportation systems in order to reap these benefits extend beyond building
infrastructure, and increasing its capacity. It also has to do with intangible factors such
as improving the quality of service to satisfy users (Cascetta and Cartenì, 2014; Redman
et al., 2013; Beirão and Cabral, 2007; Nathanail, 2008; Du Plessis, 1984). In order to
realize such a goal, public transport systems need to become more user focused, market
oriented, and competitive as public transport services are increasingly been viewed by
users, and scholars as a service product (Molander et al., 2013; Edvardsson et al., 2013;
Lai and Chen, 2011). Therefore, it is important to offer public transport services of high
efficiency, quality, reliability, and customer orientation (Celik et al., 2013; Del Castillo
and Benitez, 2012; Friman and Fellesson, 2009; Tyrinopoulos and Antoniou, 2008;
Du Plessis, 1984). Thus, this study incorporates these rail transport performance
measurement issues in a rail transport context.
The paper measures the efficiency of Indian railways (IR)taking into account service
quality parameters using data envelopment analysis (DEA). The global public transport
sector, and the rail mode in particular faces the challenge of identifying, and using
appropriateservice quality indicators and financial parametersto ascertain the efficiency
and effectiveness of the transport system, rather than considering financial parameters
alone. In this context, efficiency is not merely an indicator of the manner in which
physical inputs of labor and capital are used to produce physical services such as train
kilometers of service, but also, service effectiveness. Examples of service effectiveness
include punctuality, safety, and user or customer satisfaction. On the other hand,
technical effectiveness is the relationship between inputs, and consumed services.
Benchmarking is accepted worldwide as a general, and versatile toolfor performance
improvementin a range of contexts (e.g. Edwards etal., 2014; Johnson and Sanders, 2013;
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