Benchmarking of rail transport service performance through DEA for Indian railways

Abstract

© Emerald Group Publishing Limited.

Purpose - Railway transport being a "service" is 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 parameters can have important implications for the industry. The choice, incorporation, and interpretation of the parameters of this study can be adopted for rail transportation industry. This also summarizes 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.