IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v23y2024i4d10.1057_s41272-023-00450-w.html
   My bibliography  Save this article

A dynamic pricing strategy model for Indian Railways

Author

Listed:
  • Kartikeya Singh

    (Indian Institute of Management)

  • Pushkaraj Dhake

    (Indian Institute of Management)

  • Sundaravalli Narayanaswami

    (Indian Institute of Management)

Abstract

The Indian Railways has adopted a dynamic pricing mechanism for its premium trains like Shatabdi, Rajdhani, and Duronto. This led to an increase in its revenue but also a fall in passenger traffic. In this paper, we have analyzed the existing dynamic pricing model. A major flaw in the existing system is that the present system is only a fare hike system rather than a dynamic pricing system as there is no provision for a decrease in prices when the demand is low. Considering this, we have developed a new model that incorporates both inter-temporal pricing and demand-based pricing to come up with the dynamic fares along with the provision of having a downside in case of low demand. We developed a route selection criteria based on the key parameters identified by us where dynamic pricing would yield good results. The model was then tested on these routes using real-time data to determine the feasibility of the dynamic pricing system.

Suggested Citation

  • Kartikeya Singh & Pushkaraj Dhake & Sundaravalli Narayanaswami, 2024. "A dynamic pricing strategy model for Indian Railways," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(4), pages 295-304, August.
    • Handle: RePEc:pal:jorapm:v:23:y:2024:i:4:d:10.1057_s41272-023-00450-w
    DOI: 10.1057/s41272-023-00450-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-023-00450-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1057/s41272-023-00450-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    2. Bharill, Rohit & Rangaraj, Narayan, 2008. "Revenue management in railway operations: A study of the Rajdhani Express, Indian Railways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(9), pages 1195-1207, November.
    3. Ahmad Faruqui & Sanem Sergici, 2010. "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, Springer, vol. 38(2), pages 193-225, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jin Qin & Wenxuan Qu & Xuanke Wu & Yijia Zeng, 2019. "Differential Pricing Strategies of High Speed Railway Based on Prospect Theory: An Empirical Study from China," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    2. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
    3. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    4. Sieg, Gernot & Wessel, Jan, 2022. "I would if I could: Passing through VAT reductions in the german rail industry," Economics of Transportation, Elsevier, vol. 32(C).
    5. Cosmo, Valeria Di & O’Hora, Denis, 2017. "Nudging electricity consumption using TOU pricing and feedback: evidence from Irish households," Journal of Economic Psychology, Elsevier, vol. 61(C), pages 1-14.
    6. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    7. Durmaz, Tunç, 2016. "Precautionary Storage in Electricity Markets," Discussion Papers 2016/5, Norwegian School of Economics, Department of Business and Management Science.
    8. Carsten Helm & Mathias Mier, 2020. "Steering the Energy Transition in a World of Intermittent Electricity Supply: Optimal Subsidies and Taxes for Renewables Storage," ifo Working Paper Series 330, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Weiss, Mariana & Chueca, J. Enrique & Jacob, Jorge & Gonçalves, Felipe & Azevedo, Marina & Gouvêa, Adriana & Ravillard, Pauline & Carvalho Metanias Hallack, Michelle, 2022. "Empowering Electricity Consumers through Demand Response Approach: Why and How," IDB Publications (Working Papers) 12133, Inter-American Development Bank.
    10. Schulte, Benedikt & Sachs, Anna-Lena, 2020. "The price-setting newsvendor with Poisson demand," European Journal of Operational Research, Elsevier, vol. 283(1), pages 125-137.
    11. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    12. Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," NBER Working Papers 29508, National Bureau of Economic Research, Inc.
    13. Dasci, A. & Karakul, M., 2009. "Two-period dynamic versus fixed-ratio pricing in a capacity constrained duopoly," European Journal of Operational Research, Elsevier, vol. 197(3), pages 945-968, September.
    14. Chen, Shaopei & Claramunt, Christophe & Ray, Cyril, 2014. "A spatio-temporal modelling approach for the study of the connectivity and accessibility of the Guangzhou metropolitan network," Journal of Transport Geography, Elsevier, vol. 36(C), pages 12-23.
    15. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    16. Jun Li & Serguei Netessine & Sergei Koulayev, 2018. "Price to Compete … with Many: How to Identify Price Competition in High-Dimensional Space," Management Science, INFORMS, vol. 64(9), pages 4118-4136, September.
    17. Xu, Xiaojing & Chen, Chien-fei, 2019. "Energy efficiency and energy justice for U.S. low-income households: An analysis of multifaceted challenges and potential," Energy Policy, Elsevier, vol. 128(C), pages 763-774.
    18. Escobari, Diego, 2014. "Estimating dynamic demand for airlines," Economics Letters, Elsevier, vol. 124(1), pages 26-29.
    19. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    20. Yiwei Chen & Vivek F. Farias, 2013. "Simple Policies for Dynamic Pricing with Imperfect Forecasts," Operations Research, INFORMS, vol. 61(3), pages 612-624, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorapm:v:23:y:2024:i:4:d:10.1057_s41272-023-00450-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.