Forecasting High-Speed Railway Demand in the Absence of Air Competition – A Case Study

  • Amine BARZEGAR TILENOIE School of Railway Engineering, Iran University of Science and Technology
  • Melody KHADEM SAMENI School of Railway Engineering, Iran University of Science and Technology
  • Meeghat HABIBIAN School of Civil and Environmental Engineering, Amirkabir University of Technology
Keywords: multinomial logit, mixed logit, high-speed rail, demand, travel behaviour

Abstract

The main competitor of air transportation is High-Speed Railway (HSR). However, in an oil-exporting country with low fuel prices and strong car dependence, HSR can face fierce competition with private cars and even buses. There is little previous research that forecast modal share in this situation. The case study of this research is the Tehran-Hamedan route in Iran that has high travel demand due to several historical and economic reasons and in the absence of air transportation, building the HSR in this route attracted foreign investment. To analyse the travel behaviour of passengers after the introduction of HSR, 409 stated and revealed preferences were collected in a self-designed questionnaire. Multinomial logit (MNL) model and mixed logit (ML) model were developed and modal share of each mode of transportation were forecasted up to 2045. HSR modal share is compared with other routes of the world to see the impact of air competition. The overall modal share of railway in this route is estimated to reach 64%, which is close to the average of major HSR routes globally (around 60%). Therefore, private cars can be a fierce competitor for HSR when there is no air link on the route and fuel is rather cheap.

References

Statistical Center of Iran. Statistical Yearbook. 2018. https://www.amar.org.ir/english/Iran-Statistical-Yearbook [Accessed 18th Sep. 2020].

UNESCO. Tentative Lists. 2019. https://whc.unesco.org/en/tentativelists/state=ir [Accessed 18th Sep. 2020].

Ministry of Road and Urban Development. Statistical Yearbook. 2018. https://www.mrud.ir/ [Accessed 18th Sep. 2020].

Roads Maintenance and Transportation Organization. Statistical Yearbook. 2019. http://rmto.ir/ [Accessed 18th Sep. 2020].

Bakhtiyari M, et al. The road traffic crashes as a neglected public health concern; an observational study from Iranian population. Journal of Traffic Injury Prevention. 2015;16(1): 36-41. doi: 10.1080/15389588.2014.898182.

Ministry of Road and Urban Development. Master Plan of Transportation Sector. 2016. https://www.mrud.ir/ [Accessed 18th Sep. 2020].

Railway Pro. Italy to participate in Iranian EUR 3bn high speed rail projects. 2016. https://www.railwaypro.com/wp/italy-to-participate-in-iranian-eur-3bn-high-speed-rail-projects/ [Accessed 18th Sep. 2020].

Mancuso P. An analysis of the competition that impinges on the Milan–Rome intercity passenger transport link. Journal of Transport Policy. 2014;32(0): 42-52. doi: 10.1016/j.tranpol.2013.12.013.

Raturi V, et al. Analyzing inter-modal competition between high speed rail and conventional transport systems: A game theoretic approach. Journal of Procedia - Social and Behavioral Sciences. 2013;104(0): 904-913. doi: 10.1016/j.sbspro.2013.11.185.

Liu J, Zhang N. Empirical research of intercity high-speed rail passengers' travel behavior based on fuzzy clustering model. Journal of Transportation Systems Engineering and Information Technology. 2012;12(6): 100-105. doi: 10.1016/S1570-6672(11)60236-5.

Nurhidayat A, et al. Aircraft and high speed train using the logit model a case study of the Jakarta-Surabaya route. Atlantis Press. 2019.

Tinessa F, et al. Evaluating the choice behaviour of high-speed rail passengers in Italy: A latent class structure with alternative kernel models to the multinomial logit. 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe); 2020.

Danapour M, et al. Competition between high-speed rail and air transport in Iran: The case of Tehran–Isfahan. Journal of Case Studies on Transport Policy. 2018;6(4): 456-461. doi: 10.1016/j.cstp.2018.05.006.

Yan YQ, Zhang HQ, Ye BH. Assessing the impacts of the high-speed train on tourism demand in China. Journal of Tourism Economics. 2014;20(1): 157-169. doi: 10.5367/te.2013.0260.

Delaplace M, et al. Can high speed rail foster the choice of destination for tourism purpose? Journal of Procedia - Social and Behavioral Sciences. 2014;111(0): 166-175. doi: 10.1016/j.sbspro.2014.01.049.

Chen Z. Impacts of high-speed rail on domestic air transportation in China. Journal of Transport Geography. 2017;62: 184-196. doi: 10.1016/j.jtrangeo.2017.04.002.

Jiménez JL, Betancor O. When trains go faster than planes: The strategic reaction of airlines in Spain. Journal of Transport Policy. 2012;23: 34-41. doi: 10.1016/j.tranpol.2012.06.003.

Adler N, Pels E, Nash C. High-speed rail and air transport competition: Game engineering as tool for cost-benefit analysis. Journal of Transportation Research Part B: Methodological. 2010;44(7): 812-833. doi: 10.1016/j.trb.2010.01.001.

Su M, Luan W, Sun T. Effect of high-speed rail competition on airlines' intertemporal price strategies. Journal of Air Transport Management. 2019;80: 101694. doi: 10.1016/j.jairtraman.2019.101694.

Cadarso L, et al. Integrated airline scheduling: Considering competition effects and the entry of the high speed rail. Journal of Transportation Science. 2017;51(1): 132-154. doi: 10.1287/trsc.2015.0617.

Jiang C, Zhang A. Effects of high-speed rail and airline cooperation under hub airport capacity constraint. Journal of Transportation Research Part B: Methodological. 2014;60(0): 33-49. doi: 10.1016/j.trb.2013.12.002.

Albalate D, Bel G, Fageda X. Competition and cooperation between high-speed rail and air transportation services in Europe. Journal of Transport Geography. 2015;42: 166-174. doi: 10.1016/j.jtrangeo.2014.07.003.

Socorro MP, Viecens MF. The effects of airline and high speed train integration. Journal of Transportation Research Part A: Policy and Practice. 2013;49(0): 160-177. doi: 10.1016/j.tra.2013.01.014.

Chiambaretto P, Decker C. Air–rail intermodal agreements: Balancing the competition and environmental effects. Journal of Air Transport Management. 2012;23: 36-40. doi: 10.1016/j.jairtraman.2012.01.012.

Román C, Martín JC. Integration of HSR and air transport: understanding passengers' preferences. Journal of Transportation Research Part E: Logistics and Transportation Review. 2014;71: 129-141. doi: 10.1016/j.tre.2014.09.001.

Blainey S, Hickford A, Preston J. Barriers to passenger rail use: A review of the evidence. Journal of Transport Reviews. 2012;32(6): 675-696. doi: 10.1080/01441647.2012.743489.

Shen Y, Silva JA, Martínez LM. HSR station location choice and its local land use impacts on small cities: A case study of Aveiro, Portugal. Journal of Procedia - Social and Behavioral Sciences. 2014;111(0): 470-479. doi: 10.1016/j.sbspro.2014.01.080.

Harvey J, et al. Public attitudes to and perceptions of high speed rail in the UK. Journal of Transport Policy. 2014;36(0): 70-78. doi: 10.1016/j.tranpol.2014.07.008.

Dobruszkes F, Dehon C, Givoni M. Does european high-speed rail affect the current level of air services? An EU-wide analysis. Journal of Transportation Research Part A: Policy and Practice. 2014;69(0): 461-475. doi: 10.1016/j.tra.2014.09.004.

International Union of Railways. High Speed Rail: Fast track to sustainable mobility. 2018. https://uic.org/IMG/pdf/uic_high_speed_2018_ph08_web.pdf [Accessed 18th Sep. 2020].

Davies W, et al. Case studies: Research methods. Teaching and Learning Unit. University of Melbourne, Faculty of Business and Economics; 2007. http://tlu.fbe.unimelb.edu. au.

Atkinson JP. Four steps to analyse data from a case study method. ACIS 2002 Proceeding; 2002. p. 38.

Thomas G. How to do your case study. SAGE Publishing; 2021.

Zheng J, Liu J. The research on ticket fare optimization for China's high-speed train. Journal of Mathematical Problems in Engineering. 2016. doi: 10.1155/2016/5073053.

Zhang R, et al. Game analysis on ticket pricing of high-speed railway and civil aviation based on influence of passenger selection. Journal of Railway Transport and Economy. 2015;37(1): 5-9. doi: 18.87df3a17.1633963370.44f37842.

Luan W, et al. Research on dynamic ticket pricing of high-speed railway and air transportation under influence of induced passenger flow. Journal of Railway Transportation and Economy. 2012;34(7): 8-13. doi: 18.87df3a17.1633963509.44fcaadb.

International Union of Railways. High Speed Railway System Implementation Handbook. 2012.

Johnson R, Orme BJ. Sample size issues for conjoint analysis. Getting started with conjoint analysis: Strategies for product design and pricing research. Madison: Research Publishers LLC; 2010. p. 57-66.

Train KE. Discrete choice methods with simulation. Cambridge University Press. 30 June 2009.

Berkson J. Application of the logistic function to bio-assay. Journal of the American Statistical Association. 1944;39(227): 357-365. doi: 10.1080/01621459.1944.10500699.

Rezaei A, Puckett S, Nassiri MH. Heterogeneity in preferences of air travel itinerary in a low-frequency market. Journal of Transportation Research Record. 2011;2214(1): 10-19. doi: 10.3141/2214-02.

McFadden D. Mixed MNL models for discrete response. Journal of Applied Econometrics. 2000;15(5): 447-470. doi: 10.1002/1099-1255.

Mehndiratta SR. Time-of-day effects in inter-city business travel. University of California, Berkeley; 1996.

Hensher DA, Greene WH. The mixed logit model: The state of practice and warnings for the unwary. Institute of Transport Studies, University of Sydney and Monash University; 2002.

Train K, Sonnier G. Mixed logit with bounded distributions of correlated partworths. In: Scarpa R, Alberini A. (eds) Applications of Simulation Methods in Environmental and Resource Economics. Dordrecht: Springer; 2005. p. 117-134.

Cortina JM. What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology. 1993;78(1): 98. doi: 10.1037/0021-9010.78.1.98.

Meydani AN, Davoudi A. Analysis of CO2 emissions in different transportation secorts of Iran during 1999-2011. Journal of Economic Research and Policy. 2015;23(74): 117-150. Persian.

Desmaris C, Croccolo F. The HSR competition in Italy: How are the regulatory design and practices concerned? Journal of Research in Transportation Economics. 2018;69: 290-299. doi: 10.1016/j.retrec.2018.05.004.

Cascetta E, et al. Analysis of mobility impacts of the high speed Rome–Naples rail link using withinday dynamic mode service choice models. Journal of Transport Geography. 2011;19(4): 635-643. doi: 10.1016/j.jtrangeo.2010.07.001.

Givoni M. Development and impact of the modern High-speed train: A review. Journal of Transport Reviews. 2006;26(5): 593-611. doi: 10.1080/01441640600589319.

Román C, Espino R, Martin JC. Competition of high-speed train with air transport: The case of Madrid–Barcelona. Journal of Air Transport Management. 2007;13(5): 277-284. doi: 10.1016/j.jairtraman.2007.04.009.

Cheng YH. High-speed rail in Taiwan: New experience and issues for future development. Journal of Transport Policy. 2010;17(2): 51-63. doi: 10.1016/j.tranpol.2009.10.009.

Clever R, Hansen MM. Interaction of air and high-speed rail in Japan. Journal of Transportation Research Record. 2008;2043(1): 1-12. doi: 10.3141/2043-01.

Published
2022-02-18
How to Cite
1.
BARZEGAR TILENOIE A, KHADEM SAMENI M, HABIBIAN M. Forecasting High-Speed Railway Demand in the Absence of Air Competition – A Case Study. Promet [Internet]. 2022Feb.18 [cited 2022Aug.11];34(1):79-0. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/3862
Section
Articles