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Multiple discrete-continuous choice models: a reflective analysis and a prospective view

In: Handbook of Choice Modelling

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  • Chandra Bhat
  • Abdul Pinjari

Abstract

Choice modelling is an increasingly important technique for forecasting and valuation, with applications in fields such as transportation, health and environmental economics. For this reason it has attracted attention from leading academics and practitioners and methods have advanced substantially in recent years. This Handbook, composed of contributions from senior figures in the field, summarises the essential analytical techniques and discusses the key current research issues. It will be of interest to academics, students and practitioners in a wide range of areas.

Suggested Citation

  • Chandra Bhat & Abdul Pinjari, 2014. "Multiple discrete-continuous choice models: a reflective analysis and a prospective view," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 19, pages 427-454, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:14820_19
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    References listed on IDEAS

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    4. Caleb Van Nostrand & Vijayaraghavan Sivaraman & Abdul Pinjari, 2013. "Analysis of long-distance vacation travel demand in the United States: a multiple discrete–continuous choice framework," Transportation, Springer, vol. 40(1), pages 151-171, January.
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    11. Pinjari, Abdul Rawoof & Bhat, Chandra, 2010. "A multiple discrete-continuous nested extreme value (MDCNEV) model: Formulation and application to non-worker activity time-use and timing behavior on weekdays," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 562-583, May.
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    14. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
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    16. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    17. Tatiane Menezes & Carlos Azzoni & Fernando Silveira, 2008. "Demand elasticities for food products in Brazil: a two-stage budgeting system," Applied Economics, Taylor & Francis Journals, vol. 40(19), pages 2557-2572.
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    19. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
    20. Castro, Marisol & Bhat, Chandra R. & Pendyala, Ram M. & Jara-Díaz, Sergio R., 2012. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 729-743.
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    Cited by:

    1. Bhat, Chandra R., 2022. "A new closed-form two-stage budgeting-based multiple discrete-continuous model," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 162-192.
    2. Lloyd-Smith, Patrick, 2018. "A new approach to calculating welfare measures in Kuhn-Tucker demand models," Journal of choice modelling, Elsevier, vol. 26(C), pages 19-27.
    3. Lu, Hui & Hess, Stephane & Daly, Andrew & Rohr, Charlene, 2017. "Measuring the impact of alcohol multi-buy promotions on consumers' purchase behaviour," Journal of choice modelling, Elsevier, vol. 24(C), pages 75-95.

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