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Accommodating flexible substitution patterns in multi-dimensional choice modeling: formulation and application to travel mode and departure time choice

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  • Bhat, Chandra R.

Abstract

The nested logit model has been used extensively to model multi-dimensional choice situations. A drawback of the nested logit model is that it does not allow choice alternatives to share common unobserved attributes along all the dimensions characterizing the multidimensional choice context. This paper formulates a mixed multinomial logit structure that accommodates unobserved correlation across both dimensions in a two-dimensional choice context. The mixed multinomial logit structure is parsimonious in the number of parameters to be estimated and is also relatively easy to estimate using simulation methods. The mixed multinomial logit model is applied to an analysis of travel mode and departure time choice for home-based social-recreational trips using data drawn from the 1990 San Francisco Bay Area household survey. The empirical results underscore the need to capture unobserved attributes along both the mode and departure time dimensions, both for improved data fit as well as for more realistic policy evaluations of transportation control measures.

Suggested Citation

  • Bhat, Chandra R., 1998. "Accommodating flexible substitution patterns in multi-dimensional choice modeling: formulation and application to travel mode and departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 455-466, September.
  • Handle: RePEc:eee:transb:v:32:y:1998:i:7:p:455-466
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    Cited by:

    1. Fredrik Carlsson, 2003. "The demand for intercity public transport: the case of business passengers," Applied Economics, Taylor & Francis Journals, vol. 35(1), pages 41-50.
    2. Munizaga, Marcela A. & Heydecker, Benjamin G. & Ortúzar, Juan de Dios, 2000. "Representation of heteroskedasticity in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 34(3), pages 219-240, April.
    3. Anastasia Pnevmatikou & Matthew Karlaftis & Konstantinos Kepaptsoglou, 2015. "Metro service disruptions: how do people choose to travel?," Transportation, Springer, vol. 42(6), pages 933-949, November.
    4. Peer, Stefanie & Knockaert, Jasper & Koster, Paul & Tseng, Yin-Yen & Verhoef, Erik T., 2013. "Door-to-door travel times in RP departure time choice models: An approximation method using GPS data," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 134-150.
    5. Srinivasan, Karthik K. & Mahmassani, Hani S., 2003. "Analyzing heterogeneity and unobserved structural effects in route-switching behavior under ATIS: a dynamic kernel logit formulation," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 793-814, November.
    6. Canales, Elizabeth & Bergtold, Jason S. & Williams, Jeffery & Peterson, Jeffrey, 2015. "Estimating farmers’ risk attitudes and risk premiums for the adoption of conservation practices under different contractual arrangements: A stated choice experiment," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205640, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    7. Bhat, Chandra R. & Steed, Jennifer L., 2002. "A continuous-time model of departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 207-224, March.
    8. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters,in: A Handbook of Transport Economics, chapter 8 Edward Elgar Publishing.
    9. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
    10. Useche, Pilar & Barham, Bradford & Foltz, Jeremy, 2006. "A Trait Specific Model of GM Crop Adoption by Minnesota and Wisconsin Corn Farmers," Working Papers 201525, University of Wisconsin-Madison, Department of Agricultural and Applied Economics, Food System Research Group.
    11. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    12. Hu, Shucheng & Saleh, Wafaa, 2005. "Impacts of congestion charging on shopping trips in Edinburgh," Transport Policy, Elsevier, vol. 12(5), pages 443-450, September.
    13. José Holguín-Veras & Iván Sánchez-Díaz & Benjamin Reim, 2016. "ETC adoption, time-of-travel choice, and comprehensive policies to enhance time-of-day pricing: a stated preference investigation," Transportation, Springer, vol. 43(2), pages 273-299, March.
    14. Kockelman, Kara Maria, 2001. "A model for time- and budget-constrained activity demand analysis," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 255-269, March.
    15. Vincent van den Berg & Eric Kroes & Erik T. Verhoef, 2010. "Biases in Willingness-To-Pay Measures from Multinomial Logit Estimates due to Unobserved Heterogeneity," Tinbergen Institute Discussion Papers 10-014/3, Tinbergen Institute.

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