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To increase or to decrease the price? Managing public transport queues during COVID-19 in the presence of strategic commuters

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  • S Srivatsa Srinivas

    (Indian Institute of Technology Jodhpur)

Abstract

The impact of COVID-19 on urban travel behavior has been unprecedented. It has significantly influenced the travel mode choices of different urban commuters in various countries across the globe. Given that the public transport providers need to tradeoff between minimizing the spread of COVID-19 and providing an affordable travel choice in this environment, we develop a strategic queueing model to analyze the effect of different pricing strategies on the commuter behavior. In particular, we consider a Markovian queue in front of a public transport ticket counter wherein strategic commuters arrive at the service facility and make joining or balking decisions based on their derived utilities. In contrast to conventional wisdom, we suggest that the public transport provider needs to decrease the price to filter out the wealthy commuters who possess feasible alternative travel options from using public transport and promote the commuters with no alternatives in using public transport.

Suggested Citation

  • S Srivatsa Srinivas, 2023. "To increase or to decrease the price? Managing public transport queues during COVID-19 in the presence of strategic commuters," Public Transport, Springer, vol. 15(1), pages 275-285, March.
  • Handle: RePEc:spr:pubtra:v:15:y:2023:i:1:d:10.1007_s12469-022-00314-3
    DOI: 10.1007/s12469-022-00314-3
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    1. Goel, Rajeev K. & Saunoris, James W. & Goel, Srishti S., 2021. "Supply chain performance and economic growth: The impact of COVID-19 disruptions," Journal of Policy Modeling, Elsevier, vol. 43(2), pages 298-316.
    2. Liping Ge & Stefan Voß & Lin Xie, 2022. "Robustness and disturbances in public transport," Public Transport, Springer, vol. 14(1), pages 191-261, March.
    3. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    4. Wang, Jinting & Zhang, Xuelu & Huang, Ping, 2017. "Strategic behavior and social optimization in a constant retrial queue with the N-policy," European Journal of Operational Research, Elsevier, vol. 256(3), pages 841-849.
    5. Sube Singh & Ramesh Kumar & Rohit Panchal & Manoj Kumar Tiwari, 2021. "Impact of COVID-19 on logistics systems and disruptions in food supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 1993-2008, April.
    6. Naor, P, 1969. "The Regulation of Queue Size by Levying Tolls," Econometrica, Econometric Society, vol. 37(1), pages 15-24, January.
    7. Mark M. Dekker & Rolf N. Lieshout & Robin C. Ball & Paul C. Bouman & Stefan C. Dekker & Henk A. Dijkstra & Rob M. P. Goverde & Dennis Huisman & Debabrata Panja & Alfons A. M. Schaafsma & Marjan Akker, 2022. "A next step in disruption management: combining operations research and complexity science," Public Transport, Springer, vol. 14(1), pages 5-26, March.
    8. Yazdekhasti, Amin & Wang, Jun & Zhang, Li & Ma, Junfeng, 2021. "A multi-period multi-modal stochastic supply chain model under COVID pandemic: A poultry industry case study in Mississippi," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    9. Sanjoy Kumar Paul & Priyabrata Chowdhury, 2020. "Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 283-293, September.
    10. Dong, Hongming & Ma, Shoufeng & Jia, Ning & Tian, Junfang, 2021. "Understanding public transport satisfaction in post COVID-19 pandemic," Transport Policy, Elsevier, vol. 101(C), pages 81-88.
    11. Michał Wielechowski & Katarzyna Czech & Łukasz Grzęda, 2020. "Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic," Economies, MDPI, vol. 8(4), pages 1-24, September.
    12. Laurens G. Debo & Christine Parlour & Uday Rajan, 2012. "Signaling Quality via Queues," Management Science, INFORMS, vol. 58(5), pages 876-891, May.
    13. Christian Martin Mützel & Joachim Scheiner, 2022. "Investigating spatio-temporal mobility patterns and changes in metro usage under the impact of COVID-19 using Taipei Metro smart card data," Public Transport, Springer, vol. 14(2), pages 343-366, June.
    14. Vickerman, Roger, 2021. "Will Covid-19 put the public back in public transport? A UK perspective," Transport Policy, Elsevier, vol. 103(C), pages 95-102.
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    More about this item

    Keywords

    Public transport; COVID-19; Strategic behavior; Queueing game; Pricing;
    All these keywords.

    JEL classification:

    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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