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Fare evasion in proof-of-payment transit systems: Deriving the optimum inspection level

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  • Barabino, Benedetto
  • Salis, Sara
  • Useli, Bruno

Abstract

In proof-of-payment systems, fare evasion represents a crucial topic for public transport companies (PTCs) due to lost fare revenues, damaged corporate image, and increased levels of violence on public transport, which might also have negative economic repercussions on PTCs. Therefore, there is a need to establish the level of inspection (i.e. the number of inspectors) to tackle fare dodgers as a possible option. By building on previous models, this paper develops a formal economic framework to derive the optimum inspection level in a long time window, based on system-wide profit maximization when fare evasion exists. The framework takes into account: (i) the refined segmentation of passengers and potential fare evaders, (ii) the variability of perceived inspection level by passengers, and (iii) the fact that an inspector cannot fine every passenger caught evading. Its implementation is illustrated by using three years of real data from an Italian PTC. Based on 27,514 stop-level inspections and 10,586 on-board personal interviews, the results show that the optimum inspection level is 3.8%. Put differently, it is sufficient to check 38 passengers out of every 1000 to maximize profit in the presence of fare evasion. This outcome is very useful, because it improves the one obtained in previous formulations. Indeed, profit maximization is achieved with a lower number of inspectors, thus reducing inspection costs, which are relevant determinants in proficient PTCs. Finally, the framework is flexible and may be applied to public transport modes other than buses as long as proof-of-payment systems are in use.

Suggested Citation

  • Barabino, Benedetto & Salis, Sara & Useli, Bruno, 2014. "Fare evasion in proof-of-payment transit systems: Deriving the optimum inspection level," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 1-17.
    • Handle: RePEc:eee:transb:v:70:y:2014:i:c:p:1-17
    DOI: 10.1016/j.trb.2014.08.001
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    References listed on IDEAS

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    1. Barabino, Benedetto & Salis, Sara & Useli, Bruno, 2013. "A modified model to curb fare evasion and enforce compliance: Empirical evidence and implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 58(C), pages 29-39.
    2. Tirachini, Alejandro & Hensher, David A., 2011. "Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 828-844, June.
    3. Alessandro Bucciol & Fabio Landini & Marco Piovesan, 2012. "Unethical Minds: Individual Characteristics that Predict Unethical Behavior," Working Papers 24/2012, University of Verona, Department of Economics.
    4. Sasaki, Yasuo, 2014. "Optimal choices of fare collection systems for public transportations: Barrier versus barrier-free," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 107-114.
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    1. Benedetto Barabino & Sara Salis, 2019. "Moving Towards a More Accurate Level of Inspection Against Fare Evasion in Proof-of-Payment Transit Systems," Networks and Spatial Economics, Springer, vol. 19(4), pages 1319-1346, December.
    2. Ramos, Raúl & Silva, Hugo E., 2023. "Fare evasion in public transport: How does it affect the optimal design and pricing?," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
    3. Barabino, Benedetto & Salis, Sara & Useli, Bruno, 2015. "What are the determinants in making people free riders in proof-of-payment transit systems? Evidence from Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 184-196.
    4. Guzman, Luis A. & Arellana, Julian & Camargo, José Pablo, 2021. "A hybrid discrete choice model to understand the effect of public policy on fare evasion discouragement in Bogotá's Bus Rapid Transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 140-153.
    5. Oscar Egu & Patrick Bonnel, 2020. "Can we estimate accurately fare evasion without a survey? Results from a data comparison approach in Lyon using fare collection data, fare inspection data and counting data," Public Transport, Springer, vol. 12(1), pages 1-26, March.
    6. Meng, Meng & Rau, Andreas & Mahardhika, Hita, 2018. "Public transport travel time perception: Effects of socioeconomic characteristics, trip characteristics and facility usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 24-37.
    7. Elmar Wilhelm M. Fürst & David M. Herold, 2018. "Fare Evasion and Ticket Forgery in Public Transport: Insights from Germany, Austria and Switzerland," Societies, MDPI, vol. 8(4), pages 1-16, October.
    8. Brotcorne, L. & Escalona, P. & Fortz, B. & Labbé, M., 2021. "Fare inspection patrols scheduling in transit systems using a Stackelberg game approach," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 1-20.
    9. Boyd, Colin, 2020. "Revisiting the foundations of fare evasion research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 313-324.
    10. Felipe González & Carolina Busco & Katheryn Codocedo, 2019. "Fare Evasion in Public Transport: Grouping Transantiago Users’ Behavior," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    11. Zis, Thalis P.V., 2021. "A game theoretic approach on improving sulphur compliance," Transport Policy, Elsevier, vol. 114(C), pages 127-137.
    12. Benedetto Barabino & Sara Salis, 2023. "Segmenting fare-evaders by tandem clustering and logistic regression models," Public Transport, Springer, vol. 15(1), pages 61-96, March.
    13. Munizaga, Marcela A. & Gschwender, Antonio & Gallegos, Nestor, 2020. "Fare evasion correction for smartcard-based origin-destination matrices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 307-322.
    14. Guarda, Pablo & Galilea, Patricia & Handy, Susan & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2016. "Decreasing fare evasion without fines? A microeconomic analysis," Research in Transportation Economics, Elsevier, vol. 59(C), pages 151-158.
    15. Delbosc, Alexa & Currie, Graham, 2016. "Cluster analysis of fare evasion behaviours in Melbourne, Australia," Transport Policy, Elsevier, vol. 50(C), pages 29-36.
    16. Nourinejad, Mehdi & Gandomi, Amir & Roorda, Matthew J., 2020. "Illegal parking and optimal enforcement policies with search friction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    17. Porath, Keiko & Galilea, Patricia, 2020. "Temporal analysis of fare evasion in Transantiago: A socio-political view," Research in Transportation Economics, Elsevier, vol. 83(C).

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