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Unobserved heterogeneity analysis of rail transit incident delays

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  • Agbelie, Bismark
  • Libnao, Kathleen

Abstract

Passenger rail transit systems are frequently subjected to disruptions from incidents resulting in increased passenger waiting times, and loss of revenue to operators. The objective of the present study is to investigate the impacts of rail transit-related factors on the duration of delay, if an incident takes place. In order to account for the unobserved heterogeneity for each factor and the data generation process, a random-parameters hazard-based duration approach that accounts for these heterogeneities was employed in the present study. Out of the fourteen estimated parameters found to be statistically significant at the 1% significance level, seven parameters were found to vary across observations. This indicates that if the model was restricted and only fixed parameters were estimated, the inferences from the seven random parameters will not be accurate.

Suggested Citation

  • Agbelie, Bismark & Libnao, Kathleen, 2018. "Unobserved heterogeneity analysis of rail transit incident delays," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 39-43.
    • Handle: RePEc:eee:transa:v:117:y:2018:i:c:p:39-43
    DOI: 10.1016/j.tra.2018.07.009
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    1. Kavalec, Chris & Setiawan, Winardi, 1997. "An analysis of accelerated vehicle retirement programs using a discrete choice personal vehicle model," Transport Policy, Elsevier, vol. 4(2), pages 95-107, April.
    2. Gorman, Michael F., 2009. "Statistical estimation of railroad congestion delay," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 446-456, May.
    3. Yuan, Jianxin & Hansen, Ingo A., 2007. "Optimizing capacity utilization of stations by estimating knock-on train delays," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 202-217, February.
    4. Gudmundsson, Sveinn Vidar & Rhoades, Dawna L., 2001. "Airline alliance survival analysis: typology, strategy and duration," Transport Policy, Elsevier, vol. 8(3), pages 209-218, July.
    5. Agbelie, Bismark R.D.K., 2014. "An empirical analysis of three econometric frameworks for evaluating economic impacts of transportation infrastructure expenditures across countries," Transport Policy, Elsevier, vol. 35(C), pages 304-310.
    6. Hensher, David A. & Li, Zheng, 2010. "Accounting for differences in modelled estimates of RP, SP and RP/SP direct petrol price elasticities for car mode choice: A warning," Transport Policy, Elsevier, vol. 17(3), pages 191-195, May.
    7. Meester, Ludolf E. & Muns, Sander, 2007. "Stochastic delay propagation in railway networks and phase-type distributions," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 218-230, February.
    8. Olsson, Nils O.E. & Haugland, Hans, 2004. "Influencing factors on train punctuality--results from some Norwegian studies," Transport Policy, Elsevier, vol. 11(4), pages 387-397, October.
    9. Gilbert, Carol C. S., 1992. "A duration model of automobile ownership," Transportation Research Part B: Methodological, Elsevier, vol. 26(2), pages 97-114, April.
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