IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v184y2024ics0191261524000729.html
   My bibliography  Save this article

Network-based representations and dynamic discrete choice models for multiple discrete choice analysis

Author

Listed:
  • Tran, Hung
  • Mai, Tien

Abstract

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application intractable. To overcome this challenge, we introduce directed acyclic graph (DAG) based representations of choices where each node of the DAG is associated with an elemental alternative and additional information such as the number of selected elemental alternatives. Our innovation is to show that the multi-choice model is equivalent to a recursive route choice model on the DAG, leading to the development of new efficient estimation algorithms based on dynamic programming. In addition, the DAG representations enable us to bring some advanced route choice models to capture the correlation between subset choice alternatives. Numerical experiments based on synthetic and real datasets show many advantages of our modeling approach and the proposed estimation algorithms.

Suggested Citation

  • Tran, Hung & Mai, Tien, 2024. "Network-based representations and dynamic discrete choice models for multiple discrete choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
  • Handle: RePEc:eee:transb:v:184:y:2024:i:c:s0191261524000729
    DOI: 10.1016/j.trb.2024.102948
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261524000729
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2024.102948?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Esther-Mirjam Sent, 2018. "Rationality and bounded rationality: you can’t have one without the other," The European Journal of the History of Economic Thought, Taylor & Francis Journals, vol. 25(6), pages 1370-1386, November.
    3. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    4. Bhat, Chandra R., 2022. "A closed-form multiple discrete-count extreme value (MDCNTEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 65-86.
    5. Mai, Tien, 2016. "A method of integrating correlation structures for a generalized recursive route choice model," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 146-161.
    6. van der Lans, Ralf, 2018. "A simultaneous model of multiple-discrete choices of variety and quantity," International Journal of Research in Marketing, Elsevier, vol. 35(2), pages 242-257.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, November.
    8. Crawford, Gregory S. & Griffith, Rachel & Iaria, Alessandro, 2021. "A survey of preference estimation with unobserved choice set heterogeneity," Journal of Econometrics, Elsevier, vol. 222(1), pages 4-43.
    9. Takuya Satomura & Jaehwan Kim & Greg M. Allenby, 2011. "Multiple-Constraint Choice Models with Corner and Interior Solutions," Marketing Science, INFORMS, vol. 30(3), pages 481-490, 05-06.
    10. Melo, Emerson, 2012. "A representative consumer theorem for discrete choice models in networked markets," Economics Letters, Elsevier, vol. 117(3), pages 862-865.
    11. Mai, Tien & Fosgerau, Mogens & Frejinger, Emma, 2015. "A nested recursive logit model for route choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 100-112.
    12. 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.
    13. Mouter, Niek & Koster, Paul & Dekker, Thijs, 2021. "Contrasting the recommendations of participatory value evaluation and cost-benefit analysis in the context of urban mobility investments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 54-73.
    14. Maëlle Zimmermann & Emma Frejinger & Patrice Marcotte, 2021. "A Strategic Markovian Traffic Equilibrium Model for Capacitated Networks," Transportation Science, INFORMS, vol. 55(3), pages 574-591, May.
    15. Tien Mai & Fabian Bastin & Emma Frejinger, 2018. "A decomposition method for estimating recursive logit based route choice models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 253-275, September.
    16. 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.
    17. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    18. 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.
    19. John R. Howell & Sanghak Lee & Greg M. Allenby, 2016. "Price Promotions in Choice Models," Marketing Science, INFORMS, vol. 35(2), pages 319-334, March.
    20. Igal Hendel, 1999. "Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(2), pages 423-446.
    21. Mai, Tien & Frejinger, Emma & Bastin, Fabian, 2015. "A misspecification test for logit based route choice models," Economics of Transportation, Elsevier, vol. 4(4), pages 215-226.
    22. Sanghak Lee & Sunghoon Kim & Sungho Park, 2022. "A sequential choice model for multiple discrete demand," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 141-178, June.
    23. Sanghak Lee & Greg M. Allenby, 2014. "Modeling Indivisible Demand," Marketing Science, INFORMS, vol. 33(3), pages 364-381, May.
    24. Bhat, Chandra R. & Castro, Marisol & Pinjari, Abdul Rawoof, 2015. "Allowing for complementarity and rich substitution patterns in multiple discrete–continuous models," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 59-77.
    25. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.
    26. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens & Bastin, Fabian, 2017. "A dynamic programming approach for quickly estimating large network-based MEV models," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 179-197.
    27. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hung Tran & Tien Mai, 2023. "Network-based Representations and Dynamic Discrete Choice Models for Multiple Discrete Choice Analysis," Papers 2306.04606, arXiv.org.
    2. Sanghak Lee & Sunghoon Kim & Sungho Park, 2022. "A sequential choice model for multiple discrete demand," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 141-178, June.
    3. Mai, Tien & Bui, The Viet & Nguyen, Quoc Phong & Le, Tho V., 2023. "Estimation of recursive route choice models with incomplete trip observations," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 313-331.
    4. Mai, Tien & Yu, Xinlian & Gao, Song & Frejinger, Emma, 2021. "Routing policy choice prediction in a stochastic network: Recursive model and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 42-58.
    5. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
    6. Oyama, Yuki & Hato, Eiji, 2019. "Prism-based path set restriction for solving Markovian traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 528-546.
    7. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens & Bastin, Fabian, 2017. "A dynamic programming approach for quickly estimating large network-based MEV models," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 179-197.
    8. Song, Yuchen & Li, Dawei & Liu, Dongjie & Cao, Qi & Chen, Junlan & Ren, Gang & Tang, Xiaoyong, 2022. "Modeling activity-travel behavior under a dynamic discrete choice framework with unobserved heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    9. Kuriyama, Koichi & Shoji, Yasushi & Tsuge, Takahiro, 2024. "The integer programing extreme value (IPEV) model: An application for estimation of the leisure trip demand," Transportation Research Part B: Methodological, Elsevier, vol. 186(C).
    10. Kidokoro, Yukihiro, 2016. "A micro foundation for discrete choice models with multiple categories of goods," Journal of choice modelling, Elsevier, vol. 19(C), pages 54-72.
    11. Yao, Rui & Bekhor, Shlomo, 2022. "A variational autoencoder approach for choice set generation and implicit perception of alternatives in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 273-294.
    12. Chandra R. Bhat & Subodh K. Dubey & Mohammad Jobair Bin Alam & Waleed H. Khushefati, 2015. "A New Spatial Multiple Discrete-Continuous Modeling Approach To Land Use Change Analysis," Journal of Regional Science, Wiley Blackwell, vol. 55(5), pages 801-841, November.
    13. Pinjari, Abdul Rawoof & Bhat, Chandra, 2021. "Computationally efficient forecasting procedures for Kuhn-Tucker consumer demand model systems: Application to residential energy consumption analysis," Journal of choice modelling, Elsevier, vol. 39(C).
    14. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
    15. 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.
    16. Mai, Tien, 2016. "A method of integrating correlation structures for a generalized recursive route choice model," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 146-161.
    17. Oskar Blom Västberg & Anders Karlström & Daniel Jonsson & Marcus Sundberg, 2020. "A Dynamic Discrete Choice Activity-Based Travel Demand Model," Transportation Science, INFORMS, vol. 54(1), pages 21-41, January.
    18. Yuki Oyama, 2022. "Capturing positive network attributes during the estimation of recursive logit models: A prism-based approach," Papers 2204.01215, arXiv.org, revised Jan 2023.
    19. Oyama, Yuki & Hara, Yusuke & Akamatsu, Takashi, 2022. "Markovian traffic equilibrium assignment based on network generalized extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 135-159.
    20. Pellegrini, Andrea & Pinjari, Abdul Rawoof & Maggi, Rico, 2021. "A multiple discrete continuous model of time use that accommodates non-additively separable utility functions along with time and monetary budget constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 37-53.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:184:y:2024:i:c:s0191261524000729. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.