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Examining the difference between park and ride and kiss and ride station choices using a spatially weighted error correlation (SWEC) discrete choice model

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  • Weiss, Adam
  • Habib, Khandker Nurul

Abstract

This paper presents a novel discrete choice model formulation: the spatially weighted error correlation (SWEC) logit model for spatial location choices. This model captures both the correlation between spatially distinct alternatives based on the relative distance between them and the heteroskedasticity of the errors of the alternative as a function of their relative distance to the decision maker. The SWEC model is applied for the estimation of models of transit station choice for P-and-R as well as kiss and ride (dropped off at transit station) transit commuters in the Greater Toronto and Hamilton Area (GTHA). The kiss and ride model has particular relevance due to its ability to capture household tradeoffs made by both the driver and the passenger. The tradeoffs are captured by utilizing the subsequent trip made by the driver in the utility function specification. The proposed model structure provides additional insights into how station choice occurs for such complex trips. Finally, the application of the SWEC model for both choice contexts provides a fundamental improvement over conventional approaches, as it is able to capture non-proportional substitution patterns and heteroskedasticity inherent with spatial choices.

Suggested Citation

  • Weiss, Adam & Habib, Khandker Nurul, 2017. "Examining the difference between park and ride and kiss and ride station choices using a spatially weighted error correlation (SWEC) discrete choice model," Journal of Transport Geography, Elsevier, vol. 59(C), pages 111-119.
    • Handle: RePEc:eee:jotrge:v:59:y:2017:i:c:p:111-119
    DOI: 10.1016/j.jtrangeo.2017.01.010
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    1. Denis Bolduc & Bernard Fortin & Stephen Gordon, 1997. "Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques," International Regional Science Review, , vol. 20(1-2), pages 77-101, April.
    2. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    3. W. Lythgoe & M. Wardman, 2004. "Modelling passenger demand for parkway rail stations," Transportation, Springer, vol. 31(2), pages 125-151, May.
    4. Bhat, Chandra R. & Srinivasan, Sivaramakrishnan, 2005. "A multidimensional mixed ordered-response model for analyzing weekend activity participation," Transportation Research Part B: Methodological, Elsevier, vol. 39(3), pages 255-278, March.
    5. Higgins, Christopher D. & Kanaroglou, Pavlos S., 2016. "A latent class method for classifying and evaluating the performance of station area transit-oriented development in the Toronto region," Journal of Transport Geography, Elsevier, vol. 52(C), pages 61-72.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    7. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    8. Lin, Ting (Grace) & Xia, Jianhong (Cecilia) & Robinson, Todd P. & Goulias, Konstadinos G. & Church, Richard L. & Olaru, Doina & Tapin, John & Han, Renlong, 2014. "Spatial analysis of access to and accessibility surrounding train stations: a case study of accessibility for the elderly in Perth, Western Australia," Journal of Transport Geography, Elsevier, vol. 39(C), pages 111-120.
    9. Gutiérrez, Javier & Cardozo, Osvaldo Daniel & García-Palomares, Juan Carlos, 2011. "Transit ridership forecasting at station level: an approach based on distance-decay weighted regression," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1081-1092.
    10. Jun, Myung-Jin & Choi, Keechoo & Jeong, Ji-Eun & Kwon, Ki-Hyun & Kim, Hee-Jae, 2015. "Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul," Journal of Transport Geography, Elsevier, vol. 48(C), pages 30-40.
    11. Sener, Ipek N. & Pendyala, Ram M. & Bhat, Chandra R., 2011. "Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior," Journal of Transport Geography, Elsevier, vol. 19(2), pages 294-303.
    12. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
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    Cited by:

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    2. Liu Pai & Tomonobu Senjyu, 2022. "A Yearly Based Multiobjective Park-and-Ride Control Approach Simulation Using Photovoltaic and Battery Energy Storage Systems: Fuxin, China Case Study," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    3. Hasnine, Md Sami & Graovac, Ana & Camargo, Felipe & Habib, Khandker Nurul, 2019. "A random utility maximization (RUM) based measure of accessibility to transit: Accurate capturing of the first-mile issue in urban transit," Journal of Transport Geography, Elsevier, vol. 74(C), pages 313-320.
    4. Xia Li & Zhenyu Liu & Xinwei Ma, 2022. "Measuring Access and Egress Distance and Catchment Area of Multiple Feeding Modes for Metro Transferring Using Survey Data," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    5. Robert Rijavec & Nima Dadashzadeh & Marijan Žura & Rok Marsetič, 2020. "Park and Pool Lots’ Impact on Promoting Shared Mobility and Carpooling on Highways: The Case of Slovenia," Sustainability, MDPI, vol. 12(8), pages 1-19, April.

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