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.
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Notes
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
Avenhaus R (2004) Applications of inspection games. Math Model Anal 9(3):179–192
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
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
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
Benoit K (2011) Linear regression models with logarithmic transformations. London School of Economics, London
Beyleveld DA (1980) A Bibliography on General Deterrence Research. Saxon House, Westmead
Bijleveld C (2007) Fare dodging and the strong arm of the law. J Exp Criminol 3(2):183–199
Bonfanti G, Wagenknecht T (2010) Human factors reduce aggression and fare evasion. Public Transport International 59(1):28–32
Bootheway GBP (2009) On the optimality of fines when enforcement is risky. ASBBS E-Journal 5(1):33–39
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
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
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
Cantor G (1874) Ueber eine Eigenschaft des Inbegriffs aller reellen algebraischen Zahlen. Journal für die reine und angewandte Mathematik 77:258–262
Clarke RV, Contre S, Petrossian G (2010) Deterrence and fare evasion: results of a natural experiment. Secur J 23(1):5–17
Corporation HR (2002) Metropolitan Transit Authority: Fare Evasion Study. Horizon Research Corporation, Los Angeles
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
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
Delbosc A, Currie G (2016) Cluster analysis of fare evasion behaviours in Melbourne, Australia. Transp Policy 50:29–36
Gneezy U (2005) Deception: The role of consequences. Am Econ Rev 95(1):384–394
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
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
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
Hauber AR (1993) Fare evasion in a European perspective. Studies on Crime and Crime Prevention 2:122–141
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
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
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
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
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
Oliver A (2002) The economics of crime: an analysis of crime rates in America. The Park Place Economist 10(1):30–35
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
Pricewaterhouse Coopers (2007) TransLink Fare Evasion Audit. Pricewaterhouse Coopers LLP, Canada
Reddy AV, Kuhls J, Lu A (2011) Measuring and Controlling Subway Fare Evasion. Transp Res Rec 2216:85–99
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
Sasaki Y (2014) Optimal choices of fare collection systems for public transportations: Barrier versus barrier-free. Transp Res B 60:107–114
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
Suquet JB (2010) Drawing the line: how inspectors enact deviant behaviors. J Serv Mark 24(6):468–475
Thorlacius P, Jens C (2009) Scheduling of inspectors for ticket spot checking in urban rail transportation. DSB S-tog, Copenhagen
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
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
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.
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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
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DOI: https://doi.org/10.1007/s11067-019-09468-3