Generate QR code
Open Access
Subscription Access
Designing public transportationtariff scale by modeling demand (the case of moscow region commuter railway)
https://doi.org/10.32609/0042-8736-2013-6-100-119
Abstract
Currently fares on public transport in Russia are calculated on the basis of carrier’s costs. The subsidies and tariffs are annually approved by the regulator on the basis of the costs’ structure. This paper presents another approach to the determination of tariffs, which is widespread in developed countries. It is based on modeling passengers’ reaction to fares and is able to create appropriate incentives for the carrier. We apply it to the case of commuter rail pricing in Moscow region. To do this, we model the revenue function and evaluate people’s reaction to fares to find an optimal tariff menu. These results can form the basis of a new methodology of tariff regulation of public transport in Russia.
About the Authors
M. Dodlova
University Paris Ouest Nanterre (Paris, France)
Russian Federation
Russian Federation
S. Kiselgof
National Research University Higher School of Economics (Moscow, Russia)
Russian Federation
Russian Federation
R. Menyashev
National Research University Higher School of Economics (Moscow, Russia); Department of Transportation of Moscow Government (Moscow, Russia)
Russian Federation
Russian Federation
K. Sorokin
National Research University Higher School of Economics (Moscow, Russia)
Russian Federation
Russian Federation
E. Khmelnitskaya
National Research University Higher School of Economics (Moscow, Russia)
Russian Federation
Russian Federation
E. Chernina
National Research University Higher School of Economics (Moscow, Russia)
Russian Federation
Russian Federation
References
1. Bychkov V. (2006). Economics of a Transport Company. Moscow: INFRA-M.
2. Golubkova E., Mukhina M. (1998). Air Transport Marketing (On the Example of “Aeroflot — Russian Airlines”) // Marketing v Rossii i ¬Za Rubezhom. No 5. P. 33—49.
3. Ilin V. (1998). Pricing Policy in the Passenger Urban and Suburban Transport // Marketing v Rossii i Za Rubezhom. No 5. P. 30—33.
4. Lavrikov I., Penshin N. (2011). Economics of Road Transport. Tambov: Tambov State Educational Institution TSTU Publishing.
5. Spirin I. (2003). The Organization and Management of Passenger Road Transport: The Textbook // Moscow: Academia.
6. Tereshina N., Lapidus B., Trihunkov M. (eds.) (2006). Economics of Rail Transport. Moscow: UMC ZHDT.
7. Shalnova N. (2011). Problems and prospects of the development of passenger transport // Molodoi Uchenii. Vol. 1, No 12. P. 61—64.
8. Berg van den V., Kroes E., Verhoef E. T. (2008). Choice of Season Cards in Public Transport: a Study of a Stated Preference Experiment // European Transport. Vol. 14, No 40. Р. 4—32.
9. Bonsall P., Marsden G. (2006) Performance targets in transport policy // Transport Policy. Vol. 13, No 3. Р. 191—203.
10. Bateman I. J. et al. (2002). Economic Valuation with Stated Preference Techniques: a Manual. Cheltenham: Edward Elgar.
11. Competition Commission Report (2010). Review of Stated Preference and Willingness to Pay Methods.
12. Gebeyehu M., Takano S. (2007). Diagnostic evaluation of public transportation mode choice in Addis Ababa // Journal of Public Transportation. Vol. 10, No 4. Р. 27—50.
13. Goodwin P. B. (1992). A Review of New Demand Elasticities with Special Reference to Short and Long Run Effects of Price Changes // Journal of Transport Economics and Policy. Vol. 26, No. 2. P. 155—169.
14. Kitagawa T., Terabe S., Saratchai O. (2005). Various Factors Affecting Modal Choice Behavior of the Inter-City Passenger Between Keihanshin and Fukuoka // Proceedings of the Eastern Asia Society for Transportation Studies. Vol. 5. Р. 199—208.
15. Litman T. (2004). Transit Price Elasticities and Cross-Elasticities // Journal of Public Transportation. Vol. 7, No 2. P. 37—58.
16. Makajuma G. A., Langen M. de (2010). Urban Transport Market Determinants in Kenya: Modal Choice Analysis // Journal of Civil Engineering Research and Practice. Vol. 7, No 1. Р. 47—60.
17. McFadden D. L. (1974). Conditional Logit Analysis of Qualitative Choice Behavior // P. Zarembka (ed.) Frontiers in Econometrics. N. Y.: Academic Press. P. 105—142.
18. Oum T. H., Waters W. G., Yong J. S. (1992). Concepts of Price Elasticities of Transport Demand and Recent Empirical Estimates: An Interpretative Survey // Journal of Transport Economics and Policy. Vol. 26, No 2. P. 139—154.
19. Rohr C., Daly A., Hess S., Bates J., Polak J., Hyman G. (2005). Modeling Time Period Choice: Experience from the UK and the Netherlands // Proceedings of the XXIIth European Transport Conference, Strasbourg.
20. Steimetz S. S. C., Brownstone D. (2005). Estimating Commuters’ “Value of Time” with Noisy Data: A Multiple Imputation Approach // Transportation Research. Part B: Methodological. Vol. 39, No 10. Р. 865—889.
21. Van Westendorp P. H. (1976). NSS-Price Sensitivity Meter: A New Approach to Study Consumer Perceptions of Prices // Venice ESOMAR Congress, Amsterdam. European Market Research Society. Р. 139—167.
22. Yang L. (2010). Modeling Preferences for Innovative Modes and Services: A Case Study in Lisbon. Thesis. Massachusetts Institute of Technology.
23. Wardman A. (1998). Comparison of Revealed Preference and Stated Preference Models of Travel Behavior // Journal of Transport Economics and Policy. Vol. 22, No 1. P. 71—91.
Review
For citations:
Dodlova M., Kiselgof S., Menyashev R., Sorokin K., Khmelnitskaya E., Chernina E. Designing public transportationtariff scale by modeling demand (the case of moscow region commuter railway). Voprosy Ekonomiki. 2013;(6):100-119. (In Russ.) https://doi.org/10.32609/0042-8736-2013-6-100-119
Views:
648
Email this article 
