Article
AN ITERATIVE MODAL SHIFT MODEL OF LONG DISTANCE RAIL PASSENGERS TOWARDS AIR TRANSPORT IN INDIA
DOI: 10.7708/ijtte.2020.10(4).04
10 / 4 / 449-455 Pages
Author(s)
Selvakumar Muthusamy - Department of Civil Engineering, Sri Venkateswara College of Engineering (SVCE), Sriperumbudur, India -
Abstract
In India, long distance (greater than 1,000 km trip length) travel is accomplished by air & rail transport modes. After initiation of ‘Open Sky Policy’, private airlines were enrolled in air travel market under the name of Low Cost Airlines (LCA). Due to stiff competition among carriers, all the airlines are reducing fares to bolster their markets. The aim of such cuts is, partially, to attract other mode users. Such reduced fares may be tempting upper class rail travellers, particularly I AC (most gorgeous coach) and II AC (2-tier AC) passengers who can spare the air fare. In this background, a modal shift model was developed to understand the driving forces and key factors influencing the shift from upper class rail to air by conducting a Stated Preference (SP) survey among upper class rail passengers in the year 2007 (then the air fare was 50-60% higher than I AC rail fare). A similar study was conducted in the year 2019 (air fare was 10-20% higher than I AC rail fare) and a model was developed with the same set of parameters that had been significant in 2007 by applying binary logit technique to understand the implications in the current economic outline. It was observed that the fare difference between rail & air arouses significantly in inducing switch to air mode in both the cases. However, segments like ‘high income passengers’ and ‘passengers had travel experience in air’ had exhibited denial behaviour under the current situation.
Number of downloads: 549
Keywords:
iterative model;
rail;
modal shift;
India;
air transport;
Acknowledgements:
Author expresses his profound gratitude to his research guides Prof. Thamizharasan Venkatachalam and Prof. Karthik K.Srinivasan, Transportation Engineering Division, Department of Civil Engineering, IIT Madras for their guidance and invaluable suggestions during the course of his research work (2002-2007). Also, he is indebted to Sri Venkateswara College of Engineering (SVCE), Sriperumbudur (India) for supporting his project work and providing all the necessary facilities.
References:
Ben-Akiva, M.E.; Lerman, S.R. 1985. Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press, 390 p.
Cohen, J. 1988. Statistical Power Analysis for the Behavioural Sciences. 2nd edition, Lawrence Erlbaum Associates, New York. 579 p.
Flath, D.; Leonard, E.W. 1979. A comparison of two logit models in the analysis of qualitative marketing data, Journal of Marketing Research 16(4): 533-538.
Ghareib, A.H. 1996. Evaluation of logit and probit models in mode-choice situation, Journal of Transportation Engineering 122 (4): 282-290.
Google Flights. 2019. Flights. Available from Internet: https://www.google.com/flights?. [Accessed on 09 Feb 2019].
Hussain, H.D.; Mohammed, A.M; Salman, A.D.; Rahmat, R.A.B.O.K.; Borhan, M.N. 2017. Analysis of transportation mode choice using a comparison of artificial neural network and multinomial logit model, ARPN Journal of Engineering and Applied Science 12(5): 1483-1493.
Indian Railways. 2019. Indian Railways Passenger Reservation Enquiry. Available from Internet: http://www.indianrail.gov.in/enquiry/FARE/FareEnquiry.html?locale=en. [Accessed on 09 Feb 2019].
Moschovou, T.P.; Giannopoulos, G.A. 2012. Modeling freight mode choice in Greece, Procedia – Social and Behavioral Sciences 48: 597-611.
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