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Data science and GIS-based system analysis of transit passenger complaints to improve operations and planning

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  • Yona, Moran
  • Birfir, Genadi
  • Kaplan, Sigal

Abstract

Transit user complaints support system resilience by serving as a data source for service improvements. This study shows how geographic information system (GIS)-based analysis, econometric models, and latent class analysis can improve system-wide understanding of passenger complaints. The analyzed dataset consists of 718 passenger complaints concerning the operation of municipal lines in Jerusalem as the study region. The analytical methods consists of GIS-based analysis and statistical modeling: mapping, recursive bivariate probit estimation, negative binomial model estimation, and latent class analysis. The GIS-based analysis showed that the spatial distribution of complaints changes over time as a function of service disruption type and geographical area. The recursive bivariate probit model results indicated that the most acute sources of frustration are service problem recurrence and monetary loss, with the former caused by overcrowding, delays and line cancellations. The negative binomial model results shows that the number of complaints increases with an increase in the passenger boarding to bus arrivals ratio. Latent class analysis reveals that, in terms of both prevalence and customer frustration, overcrowding delays and line cancellations are the most acute problems in the study region. The proposed interface between transit complaints and GIS databases can readily be implemented by transport operators and authorities.

Suggested Citation

  • Yona, Moran & Birfir, Genadi & Kaplan, Sigal, 2021. "Data science and GIS-based system analysis of transit passenger complaints to improve operations and planning," Transport Policy, Elsevier, vol. 101(C), pages 133-144.
  • Handle: RePEc:eee:trapol:v:101:y:2021:i:c:p:133-144
    DOI: 10.1016/j.tranpol.2020.12.009
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    References listed on IDEAS

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    1. Rainer Winkelmann, 2012. "Copula Bivariate Probit Models: With An Application To Medical Expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 21(12), pages 1444-1455, December.
    2. Hensher, David A., 2017. "Future bus transport contracts under a mobility as a service (MaaS) regime in the digital age: Are they likely to change?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 86-96.
    3. Friman, Margareta, 2004. "The structure of affective reactions to critical incidents," Journal of Economic Psychology, Elsevier, vol. 25(3), pages 331-353, June.
    4. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    5. Sarker, Rumana Islam & Kaplan, Sigal & Mailer, Markus & Timmermans, Harry J.P., 2019. "Applying affective event theory to explain transit users’ reactions to service disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 593-605.
    6. Thao, Vu Thi & Wegelin, Philipp & von Arx, Widar, 2017. "Are statutory passenger watchdogs effective in representing passenger interests in public transport?," Transport Policy, Elsevier, vol. 58(C), pages 1-9.
    7. Tamara Kerzhner & Sigal Kaplan & Emily Silverman, 2018. "Physical walls, invisible barriers: Palestinian women's mobility in Jerusalem," Regional Science Policy & Practice, Wiley Blackwell, vol. 10(4), pages 299-314, November.
    8. Wittman, Michael D., 2014. "Are low-cost carrier passengers less likely to complain about service quality?," Journal of Air Transport Management, Elsevier, vol. 35(C), pages 64-71.
    9. Yap, Menno & Munizaga, Marcela, 2018. "Workshop 8 report: Big data in the digital age and how it can benefit public transport users," Research in Transportation Economics, Elsevier, vol. 69(C), pages 615-620.
    10. Weng-Kun Liu & Chia-Chun Yen, 2016. "Optimizing Bus Passenger Complaint Service through Big Data Analysis: Systematized Analysis for Improved Public Sector Management," Sustainability, MDPI, vol. 8(12), pages 1-21, December.
    11. Jun, Chae Nam & Chung, Chung Joo, 2016. "Big data analysis of local government 3.0: Focusing on Gyeongsangbuk-do in Korea," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 3-12.
    12. Major, Wesley L. & Hubbard, Sarah M., 2019. "An examination of disability-related complaints in the United States commercial aviation sector," Journal of Air Transport Management, Elsevier, vol. 78(C), pages 43-53.
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