Skip to main content
Log in

Moving Towards a More Accurate Level of Inspection Against Fare Evasion in Proof-of-Payment Transit Systems

  • Published:
Networks and Spatial Economics Aims and scope Submit manuscript

Abstract

This paper proposes an accurate economic framework to determine the optimum inspection level—the number of ticket inspectors—in a long time window, in order to maximize the system-wide profit when fare evasion occurs. This is the first framework that introduces: i) a refined characterization of the passenger demand, ii) a profit function with new constraints, iii) an alternative estimation of the percentage of passengers who choose to evade, and iv) a new formulation accounting for inspectors who cannot fine every passenger caught evading. The implementation of this framework is illustrated by using six years of data gathered from an Italian public transport company. Based on 57,256 stop-level inspections and 21,827 on-board personal interviews, the optimum inspection rate maximizing the profit is in the range of 3.4%-4.0%. This outcome provides more accurate results, which are discussed and compared to previous research. Finally, the framework is flexible, and it may be applied to any urban context in which proof-of-payment systems are adopted.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. Function ξ(X) can be modelled by plotting on a diagram, along the x-axis, the value of the level of inspection and, on they-axis, the ratio of non-fined passengers to fined passengers.

References

  • Abrate G, Fraquelli G, Meko E, Rodia G (2008) L’Evasione Tariffaria nel Trasporto Pubblico Locale: un’Analisi Empirica. Conferenza Società Italiana di Economia Pubblica, XX Riunione Scientifica, Pavia

    Google Scholar 

  • Avenhaus R (2004) Applications of inspection games. Math Model Anal 9(3):179–192

    Article  Google Scholar 

  • Barabino B, Salis S, Useli B (2013) A modified model to curb fare evasion and enforce compliance: Empirical evidence and implications. Transp Res A 58:29–39

    Google Scholar 

  • Barabino B, Salis S, Useli B (2014) Fare evasion in proof-of-payment transit systems: Deriving the optimum inspection level. Transp Res B 70:1–17

    Article  Google Scholar 

  • Barabino B, Salis S, Useli B (2015) What are the determinants in making people free riders in proof-of-payment transit systems? Evidence from Italy. Transp Res A 80:184–196

    Google Scholar 

  • Benoit K (2011) Linear regression models with logarithmic transformations. London School of Economics, London

    Google Scholar 

  • Beyleveld DA (1980) A Bibliography on General Deterrence Research. Saxon House, Westmead

    Google Scholar 

  • Bijleveld C (2007) Fare dodging and the strong arm of the law. J Exp Criminol 3(2):183–199

    Article  Google Scholar 

  • Bonfanti G, Wagenknecht T (2010) Human factors reduce aggression and fare evasion. Public Transport International 59(1):28–32

    Google Scholar 

  • Bootheway GBP (2009) On the optimality of fines when enforcement is risky. ASBBS E-Journal 5(1):33–39

    Google Scholar 

  • Borndörfer R, Omont B, Sagnol G, Swarat E (2012) A Stackelberg game to optimize the distribution of controls in transportation networks. Game Theory for Networks (Springer Berlin Heidelberg), 224-235

    Google Scholar 

  • Boyd C, Martini C, Rickard J, Russell A (1989) Fare evasion and non-compliance: A simple model. Journal of Transport Economics and Policy 23(2):189–197

    Google Scholar 

  • Bucciol A, Landini F, Piovesan M (2013) Unethical behaviour in the field: Demographic Characteristics and beliefs of the cheater. J Econ Behav Organ 93:248–257

    Article  Google Scholar 

  • Cantor G (1874) Ueber eine Eigenschaft des Inbegriffs aller reellen algebraischen Zahlen. Journal für die reine und angewandte Mathematik 77:258–262

    Google Scholar 

  • Clarke RV, Contre S, Petrossian G (2010) Deterrence and fare evasion: results of a natural experiment. Secur J 23(1):5–17

    Article  Google Scholar 

  • Corporation HR (2002) Metropolitan Transit Authority: Fare Evasion Study. Horizon Research Corporation, Los Angeles

    Google Scholar 

  • Correa JR, Harks T, Kreuzen VJ, Matuschke J (2014) Fare Evasion in Transit Networks. arXiv preprint arXiv:1405.2826

  • CTM (2017) Carta della mobilità 2016-2017. http://www.ctmcagliari.it/

  • Dauby L, Kovacs Z (2007a) Fare evasion in light rail systems. Transportation Research E-Circular E-C112

  • Dauby L, Kovacs Z (2007b) Fare evasion in light rail systems. Public Transport International 56(2):6–8

    Google Scholar 

  • Del Castillo V, Lindner C (1994) Fare evasion in New York City transit system: A brief survey of countermeasures. Secur J 5(4):217–221

    Google Scholar 

  • Delbosc A, Currie G (2016) Cluster analysis of fare evasion behaviours in Melbourne, Australia. Transp Policy 50:29–36

    Article  Google Scholar 

  • Gneezy U (2005) Deception: The role of consequences. Am Econ Rev 95(1):384–394

    Article  Google Scholar 

  • Guarda P, Galilea P, Handy S, Muñoz JC, Ortúzar JD (2016a) Decreasing fare evasion without fines? A microeconomic analysis. Res Transp Econ 59:151–158

    Article  Google Scholar 

  • Guarda P, Galilea P, Paget-Seekins L, Ortúzar JD (2016b) What is behind fare evasion in urban bus systems? An econometric approach. Transp Res A 84:55–71

    Article  Google Scholar 

  • Guarda P, Ortúzar JD, Handy S, Galilea P, Munoz JC (2015) Optimal mixed strategies for dealing with fare evasion in public transport. Proceeding of Conference on Advanced Systems in Public Transport, Rotterdam

    Google Scholar 

  • Hauber AR (1993) Fare evasion in a European perspective. Studies on Crime and Crime Prevention 2:122–141

    Google Scholar 

  • Killias M, Scheidegger D, Nordenson P (2009) The effects of increasing the certainty of punishment: A field experiment on public transportation. Eur J Criminol 6(5):387–400

    Article  Google Scholar 

  • Kooreman P (1993) Fare evasion as a result of expected utility maximisation. Some empirical support. Journal of Transport Economics and Policy 27(1):69–74

    Google Scholar 

  • Li ZC, Lam WH, Wong SC (2009) The optimal transit fare structure under different market regimes with uncertainty in the network. Netw Spat Econ 9(2):191–216

    Article  Google Scholar 

  • Mazar N, Amir O, Ariely D (2008) The dishonesty of honest people: A theory of self-concept maintenance. J Mark Res 45(6):633–644

    Article  Google Scholar 

  • Multisystems Inc, Mundle & Associates Inc, Parsons Transportation Group Inc (2002) A Toolkit for Self-Service, Barrier-Free Fare Collection. Transit Cooperative Research Program TRB, Washington, DC Report 80

    Google Scholar 

  • Oliver A (2002) The economics of crime: an analysis of crime rates in America. The Park Place Economist 10(1):30–35

    Google Scholar 

  • Pourmonet H, Bassetto S, Trépanier M (2015) Vers la maîtrise de l’évasion tarifaire dans un réseau de transport collectif. 11e Congrès International De Génie Industriel, Québec

    Google Scholar 

  • Pricewaterhouse Coopers (2007) TransLink Fare Evasion Audit. Pricewaterhouse Coopers LLP, Canada

    Google Scholar 

  • Reddy AV, Kuhls J, Lu A (2011) Measuring and Controlling Subway Fare Evasion. Transp Res Rec 2216:85–99

    Article  Google Scholar 

  • Salis S, Barabino B, Useli B (2017) Segmenting fare evader groups by factor and cluster analysis. WIT Transactions on The Built Environment 176:503–515

    Article  Google Scholar 

  • Sasaki Y (2014) Optimal choices of fare collection systems for public transportations: Barrier versus barrier-free. Transp Res B 60:107–114

    Article  Google Scholar 

  • Smith MJ, Clarke RV (2000) Crime and public transport. In: Tonry M (ed) Crime and Justice. A Review of Research, vol 27. University of Chicago Press, Chicago, pp 169–233

    Google Scholar 

  • Suquet JB (2010) Drawing the line: how inspectors enact deviant behaviors. J Serv Mark 24(6):468–475

    Article  Google Scholar 

  • Thorlacius P, Jens C (2009) Scheduling of inspectors for ticket spot checking in urban rail transportation. DSB S-tog, Copenhagen

    Google Scholar 

  • Torres-Montoya M (2014) Tackling fare evasion in Transantiago: an integrated approach. In Transportation Research Board 93rd Annual Meeting (No. 14-4641)

  • Von Hirsch A, Bottoms AE, Burney E, Wikström PO (1999) Criminal Deterrence and Sentence Severity: An Analysis of Recent Research. Hart Publishing, Oxford

    Google Scholar 

  • Yin Z, Jiang AX, Johnson M, Tambe M, Kiekintveld C, Leyton-Brown K, Sandholm T, Sullivan J (2012a) TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems. Proceedings of the Twenty-Fourth AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI). AAAI Press, Menlo Park

  • Yin Z, Jiang AX, Johnson M, Tambe M, Kiekintveld C, Leyton-Brown K, Sandholm T, Sullivan J (2012b) TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems Using Game Theory. AI Mag 33(4):59–72

    Article  Google Scholar 

Download references

Acknowledgments

This work has been partially supported by the Italian Ministry of University and Research (MIUR), within the Smart City framework (project: PON04a2_00381 “CAGLIARI2020”). The authors are very grateful to the CTM senior management for its support of this work and the opportunity to illustrate the results and to two reviewers for their very helpful suggestions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sara Salis.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1

Table 7 Notational glossary for the passenger demand

Appendix 2

Table 8 Notational glossary for the mathematical formulation of the model

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Barabino, B., Salis, S. Moving Towards a More Accurate Level of Inspection Against Fare Evasion in Proof-of-Payment Transit Systems. Netw Spat Econ 19, 1319–1346 (2019). https://doi.org/10.1007/s11067-019-09468-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11067-019-09468-3

Keywords

Navigation