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GEV-based destination choice models that account for unobserved similarities among alternatives

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  • Bekhor, Shlomo
  • Prashker, Joseph N.

Abstract

This paper investigates the destination choice problem in transportation planning processes. Most models assume a Multinomial Logit (MNL) form for the problem. The MNL cannot account for unobserved similarities which exist among choice alternatives. The purpose of this paper is to investigate alternative destination choice model structures, focusing on closed-form models. The paper reviews recent GEV formulations and discusses the adaptation of these models to destination choice situation. In addition the paper presents a new model structure composed of three hierarchical levels: it assumes a choice process composed of a broad selection of zones based on a specific land use characteristic (in this case, presence of shopping center) and then a finer selection of zones based on a geographical characteristic (in this case, adjacent zones). To illustrate the similarity measures of selected GEV formulations and the new model structure the paper specifies, estimates and compares destination choice models for weekday shopping trips based on a revealed preference survey. The paper discusses the structure of the proposed choice models, similarity measures and implementation issues related to the GEV destination choice models.

Suggested Citation

  • Bekhor, Shlomo & Prashker, Joseph N., 2008. "GEV-based destination choice models that account for unobserved similarities among alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 243-262, March.
    • Handle: RePEc:eee:transb:v:42:y:2008:i:3:p:243-262
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    References listed on IDEAS

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    1. Small, Kenneth A, 1987. "A Discrete Choice Model for Ordered Alternatives," Econometrica, Econometric Society, vol. 55(2), pages 409-424, March.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    3. Koppelman, Frank S. & Wen, Chieh-Hua, 2000. "The paired combinatorial logit model: properties, estimation and application," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 75-89, February.
    4. Daly, Andrew, 1982. "Estimating choice models containing attraction variables," Transportation Research Part B: Methodological, Elsevier, vol. 16(1), pages 5-15, February.
    5. Daly, Andrew & Bierlaire, Michel, 2006. "A general and operational representation of Generalised Extreme Value models," Transportation Research Part B: Methodological, Elsevier, vol. 40(4), pages 285-305, May.
    6. Papola, Andrea, 2004. "Some developments on the cross-nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 38(9), pages 833-851, November.
    7. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    8. Michel Bierlaire, 2006. "A theoretical analysis of the cross-nested logit model," Annals of Operations Research, Springer, vol. 144(1), pages 287-300, April.
    9. Chandra Bhat & Frank Koppelman, 1999. "A retrospective and prospective survey of time-use research," Transportation, Springer, vol. 26(2), pages 119-139, May.
    10. 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. Yao, Jia & Chen, Anthony & Ryu, Seungkyu & Shi, Feng, 2014. "A general unconstrained optimization formulation for the combined distribution and assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 137-160.
    3. Hasnat, Md Mehedi & Faghih-Imani, Ahmadreza & Eluru, Naveen & Hasan, Samiul, 2019. "Destination choice modeling using location-based social media data," Journal of choice modelling, Elsevier, vol. 31(C), pages 22-34.
    4. David Boto‐García & Antonio Alvarez & José Baños, 2021. "Modelling heterogeneous preferences for nature‐based tourism trips," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1625-1653, December.
    5. Smirnov, Oleg A. & Egan, Kevin J., 2012. "Spatial random utility model with an application to recreation demand," Economic Modelling, Elsevier, vol. 29(1), pages 72-78.
    6. Yang, Liya & Shen, Qing & Li, Zhibin, 2016. "Comparing travel mode and trip chain choices between holidays and weekdays," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 273-285.
    7. Sadhu, S.L.N. Sarma & Tiwari, Geetam, 2016. "An activity pattern – destination land use choice model of low income households of informal settlements – Case study of Delhi," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 265-275.
    8. Giancarlos Troncoso Parady & Eiji Hato, 2016. "Accounting for spatial correlation in tsunami evacuation destination choice: a case study of the Great East Japan Earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 797-807, November.
    9. Ampol Karoonsoontawong & Dung-Ying Lin, 2015. "Combined Gravity Model Trip Distribution and Paired Combinatorial Logit Stochastic User Equilibrium Problem," Networks and Spatial Economics, Springer, vol. 15(4), pages 1011-1048, December.
    10. Chen, Roger B., 2018. "Models of count with endogenous choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 862-875.
    11. Smirnov, Oleg A., 2010. "Modeling spatial discrete choice," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 292-298, September.
    12. 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.

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