IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v50y2016icp29-36.html
   My bibliography  Save this article

Cluster analysis of fare evasion behaviours in Melbourne, Australia

Author

Listed:
  • Delbosc, Alexa
  • Currie, Graham

Abstract

Fare evasion on transit can reduce revenue by millions of dollars, undermining financial viability. Research has examined how design solutions, such as ticket barriers and ticket inspections, can reduce fare evasion. However little research examines how transit users think about fare evasion or attempts to understand why people fare evade. This research uses a quantitative cluster analysis to segment fare evasion behaviours into three categories which show distinct personality and behavioural characteristics. A web-based survey of was administered to residents of Melbourne, Australia with a total sample size of 1561. The questionnaire was introduced as a survey about transit travel and ticketing but included questions about various aspects of fare evasion behavior. Notably, three broad types of fare evasion were explored: ‘accidental’ fare evasion (e.g. meant to pay but machines were not working), ‘unintentional’ fare evasion (e.g. meant to validate but I was in a hurry or I forgot) and ‘deliberate’ fare evasion (e.g. decided not to pay because I was only going a few stops). A two-step cluster analysis was conducted using a range of categorical and continuous variables including fare evasion behavior, predicted likelihood of continuing to fare evade, age and frequency of transit use. Three clusters of fare evaders emerged: deliberate evaders, unintentional evaders and never-evaders. Deliberate evaders were the smallest cluster but the most frequent transit users. In contrast, unintentional evaders were more common but only fare evaded infrequently. The clusters also had distinct personality differences; deliberate evaders were more likely to be sensation-seekers and believed it was acceptable to bend the rules to save money. Implications for transit policy and practice are discussed.

Suggested Citation

  • Delbosc, Alexa & Currie, Graham, 2016. "Cluster analysis of fare evasion behaviours in Melbourne, Australia," Transport Policy, Elsevier, vol. 50(C), pages 29-36.
  • Handle: RePEc:eee:trapol:v:50:y:2016:i:c:p:29-36
    DOI: 10.1016/j.tranpol.2016.05.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X16300282
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tranpol.2016.05.015?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. Daunt, Kate L. & Harris, Lloyd C., 2011. "Customers acting badly: Evidence from the hospitality industry," Journal of Business Research, Elsevier, vol. 64(10), pages 1034-1042, October.
    2. Bucciol, Alessandro & Landini, Fabio & Piovesan, Marco, 2013. "Unethical behavior in the field: Demographic characteristics and beliefs of the cheater," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 248-257.
    3. 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.
    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.
    5. 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.
    6. 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.
    7. Guarda, Pablo & Galilea, Patricia & Paget-Seekins, Laurel & Ortúzar, Juan de Dios, 2016. "What is behind fare evasion in urban bus systems? An econometric approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 55-71.
    8. Reynolds, Kate L. & Harris, Lloyd C., 2009. "Dysfunctional Customer Behavior Severity: An Empirical Examination," Journal of Retailing, Elsevier, vol. 85(3), pages 321-335.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2019. "On evasion behaviour in public transport: Dissatisfaction or contagion?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 626-651.
    5. Celse, Jérémy & Grolleau, Gilles, 2023. "Fare evasion and information provision: What information should be provided to reduce fare-evasion?," Transport Policy, Elsevier, vol. 138(C), pages 119-128.
    6. Ayal, Shahar & Celse, Jérémy & Hochman, Guy, 2021. "Crafting messages to fight dishonesty: A field investigation of the effects of social norms and watching eye cues on fare evasion," Organizational Behavior and Human Decision Processes, Elsevier, vol. 166(C), pages 9-19.
    7. Åse Jevinger & Jan A. Persson, 2019. "Exploring the potential of using real-time traveler data in public transport disturbance management," Public Transport, Springer, vol. 11(2), pages 413-441, August.
    8. 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.
    9. 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.
    10. Currie, Graham & Delbosc, Alexa, 2017. "An empirical model for the psychology of deliberate and unintentional fare evasion," Transport Policy, Elsevier, vol. 54(C), pages 21-29.
    11. Martina Manfre' & Viola Angelini, 2018. "Does The Financial Situation affect Cheating Behavior? An Investigation through Financial Literacy," Working Papers 06/2018, University of Verona, Department of Economics.
    12. 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.
    13. Porath, Keiko & Galilea, Patricia, 2020. "Temporal analysis of fare evasion in Transantiago: A socio-political view," Research in Transportation Economics, Elsevier, vol. 83(C).
    14. Chung, Yi-Shih & Chiou, Yu-Chiun, 2017. "Willingness-to-pay for a bus fare reform: A contingent valuation approach with multiple bound dichotomous choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 289-304.
    15. Troncoso, Rodrigo & de Grange, Louis, 2017. "Fare evasion in public transport: A time series approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 311-318.

    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. 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.
    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. 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.
    4. 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.
    5. 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.
    6. Porath, Keiko & Galilea, Patricia, 2020. "Temporal analysis of fare evasion in Transantiago: A socio-political view," Research in Transportation Economics, Elsevier, vol. 83(C).
    7. 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.
    8. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2019. "On evasion behaviour in public transport: Dissatisfaction or contagion?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 626-651.
    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. Troncoso, Rodrigo & de Grange, Louis, 2017. "Fare evasion in public transport: A time series approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 311-318.
    11. Benedetto Barabino & Cristian Lai & Alessandro Olivo, 2020. "Fare evasion in public transport systems: a review of the literature," Public Transport, Springer, vol. 12(1), pages 27-88, March.
    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. 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).
    14. Celse, Jérémy & Grolleau, Gilles, 2023. "Fare evasion and information provision: What information should be provided to reduce fare-evasion?," Transport Policy, Elsevier, vol. 138(C), pages 119-128.
    15. 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.
    16. 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.
    17. Currie, Graham & Delbosc, Alexa, 2017. "An empirical model for the psychology of deliberate and unintentional fare evasion," Transport Policy, Elsevier, vol. 54(C), pages 21-29.
    18. Cantillo, Angel & Raveau, Sebastián & Muñoz, Juan Carlos, 2022. "Fare evasion on public transport: Who, when, where and how?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 285-295.
    19. Guarda, Pablo & Galilea, Patricia & Paget-Seekins, Laurel & Ortúzar, Juan de Dios, 2016. "What is behind fare evasion in urban bus systems? An econometric approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 55-71.
    20. Minjeong Kang & Taeshik Gong, 2019. "Dysfunctional customer behavior: conceptualization and empirical validation," Service Business, Springer;Pan-Pacific Business Association, vol. 13(4), pages 625-646, December.

    More about this item

    Statistics

    Access and download statistics

    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:eee:trapol:v:50:y:2016:i:c:p:29-36. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    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.