IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v90y2016icp192-217.html
   My bibliography  Save this article

How, when and why integrated choice and latent variable models are latently useful

Author

Listed:
  • Vij, Akshay
  • Walker, Joan L.

Abstract

Integrated Choice and Latent Variable (ICLV) models are an increasingly popular extension to discrete choice models that attempt explicitly to model the cognitive process underlying the formation of any choice. This study was born from the discovery that an ICLV model can in many cases be reduced to a choice model without latent variables that fits the choice data at least as well as the original ICLV model from which it was obtained. The failure of past studies to recognize this fact raised concerns about other benefits that have been claimed with regards to the framework. With the objective of addressing these concerns, this study undertakes a systematic comparison between the ICLV model and an appropriately specified reduced form choice model. We derive analytical proofs regarding the benefits of the framework and use synthetic datasets to corroborate any conclusions drawn from the analytical proofs. We find that the ICLV model can under certain conditions lead to an improvement in the analyst's ability to predict outcomes to the choice data, allow for the identification of structural relationships between observable and latent variables, correct for bias arising from omitted variables and measurement error, reduce the variance of parameter estimates, and abet practice and policy, all in ways that would not be possible using the reduced form choice model. We synthesize these findings into a general process of evaluation that can be used to assess what gains, if any, might be had from developing an ICLV model in a particular empirical context.

Suggested Citation

  • Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
  • Handle: RePEc:eee:transb:v:90:y:2016:i:c:p:192-217
    DOI: 10.1016/j.trb.2016.04.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S019126151630234X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.trb.2016.04.021?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. Bergantino, Angela S. & Bierlaire, Michel & Catalano, Mario & Migliore, Marco & Amoroso, Salvatore, 2013. "Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators," Transport Policy, Elsevier, vol. 30(C), pages 77-91.
    2. Ricardo Daziano & Denis Bolduc, 2013. "Covariance, identification, and finite-sample performance of the MSL and Bayes estimators of a logit model with latent attributes," Transportation, Springer, vol. 40(3), pages 647-670, May.
    3. Kløjgaard, Mirja Elisabeth & Hess, Stephane, 2014. "Understanding the formation and influence of attitudes in patients' treatment choices for lower back pain: Testing the benefits of a hybrid choice model approach," Social Science & Medicine, Elsevier, vol. 114(C), pages 138-150.
    4. Raveau, Sebastián & Yáñez, María Francisca & Ortúzar, Juan de Dios, 2012. "Practical and empirical identifiability of hybrid discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1374-1383.
    5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    6. Maya Abou-Zeid & Moshe Ben-Akiva, 2014. "Hybrid choice models," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 17, pages 383-412, Edward Elgar Publishing.
    7. Chorus, Caspar G. & Kroesen, Maarten, 2014. "On the (im-)possibility of deriving transport policy implications from hybrid choice models," Transport Policy, Elsevier, vol. 36(C), pages 217-222.
    8. Akshay Vij & Joan L. Walker, 2014. "Hybrid choice models: the identification problem," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 22, pages 519-564, Edward Elgar Publishing.
    9. Stephane Hess & Nesha Beharry-Borg, 2012. "Accounting for Latent Attitudes in Willingness-to-Pay Studies: The Case of Coastal Water Quality Improvements in Tobago," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 52(1), pages 109-131, May.
    10. Daniel McFadden, 1986. "The Choice Theory Approach to Market Research," Marketing Science, INFORMS, vol. 5(4), pages 275-297.
    11. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
    12. Wang, Tingting & Chen, Cynthia, 2012. "Attitudes, mode switching behavior, and the built environment: A longitudinal study in the Puget Sound Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1594-1607.
    13. Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
    14. Maria Kamargianni & Moshe Ben-Akiva & Amalia Polydoropoulou, 2014. "Incorporating social interaction into hybrid choice models," Transportation, Springer, vol. 41(6), pages 1263-1285, November.
    15. Yasasvi Popuri & Kimon Proussaloglou & Cemal Ayvalik & Frank Koppelman & Aimee Lee, 2011. "Importance of traveler attitudes in the choice of public transportation to work: findings from the Regional Transportation Authority Attitudinal Survey," Transportation, Springer, vol. 38(4), pages 643-661, July.
    16. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
    17. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    18. Marcel Paulssen & Dirk Temme & Akshay Vij & Joan Walker, 2014. "Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice," Transportation, Springer, vol. 41(4), pages 873-888, July.
    19. Rafael Maldonado-Hinarejos & Aruna Sivakumar & John Polak, 2014. "Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach," Transportation, Springer, vol. 41(6), pages 1287-1304, November.
    20. James Steiger, 1979. "Factor indeterminacy in the 1930's and the 1970's some interesting parallels," Psychometrika, Springer;The Psychometric Society, vol. 44(2), pages 157-167, June.
    21. Train, Kenneth E & McFadden, Daniel L & Goett, Andrew A, 1987. "Consumer Attitudes and Voluntary Rate Schedules for Public Utilities," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 383-391, August.
    22. Cristian Domarchi & Alejandro Tudela & Angélica González, 2008. "Effect of attitudes, habit and affective appraisal on mode choice: an application to university workers," Transportation, Springer, vol. 35(5), pages 585-599, August.
    23. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
    24. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    25. Andrew Daly & Stephane Hess & Bhanu Patruni & Dimitris Potoglou & Charlene Rohr, 2012. "Using ordered attitudinal indicators in a latent variable choice model: a study of the impact of security on rail travel behaviour," Transportation, Springer, vol. 39(2), pages 267-297, March.
    26. Bhat, Chandra R. & Dubey, Subodh K., 2014. "A new estimation approach to integrate latent psychological constructs in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 68-85.
    27. Yáñez, M.F. & Raveau, S. & Ortúzar, J. de D., 2010. "Inclusion of latent variables in Mixed Logit models: Modelling and forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 744-753, November.
    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. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    2. Hélène Bouscasse, 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers hal-01795630, HAL.
    3. Hess, Stephane & Spitz, Greg & Bradley, Mark & Coogan, Matt, 2018. "Analysis of mode choice for intercity travel: Application of a hybrid choice model to two distinct US corridors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 547-567.
    4. Antonio Borriello & John M. Rose, 2021. "Global versus localised attitudinal responses in discrete choice," Transportation, Springer, vol. 48(1), pages 131-165, February.
    5. Schmid, Basil & Axhausen, Kay W., 2019. "In-store or online shopping of search and experience goods: A hybrid choice approach," Journal of choice modelling, Elsevier, vol. 31(C), pages 156-180.
    6. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    7. Joanna Mazur & Katarzyna Śledziewska & Damian Zieba, 2018. "Regulation of Geo-blocking: does it address the problem of low intraEU iTrade?," Working Papers 2018-20, Faculty of Economic Sciences, University of Warsaw.
    8. Wiktor Budziński & Mikołaj Czajkowski, 2018. "Hybrid choice models vs. endogeneity of indicator variables: a Monte Carlo investigation," Working Papers 2018-21, Faculty of Economic Sciences, University of Warsaw.
    9. Bahamonde-Birke, Francisco J. & Ortúzar, Juan de Dios, 2017. "Analyzing the continuity of attitudinal and perceptual indicators in hybrid choice models," Journal of choice modelling, Elsevier, vol. 25(C), pages 28-39.
    10. Francisco J. Bahamonde-Birke & Juan de Dios Ortúzar, 2015. "About the Categorization of Latent Variables in Hybrid Choice Models," Discussion Papers of DIW Berlin 1527, DIW Berlin, German Institute for Economic Research.
    11. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    12. Mikkel Thorhauge & Elisabetta Cherchi & Joan L. Walker & Jeppe Rich, 2019. "The role of intention as mediator between latent effects and behavior: application of a hybrid choice model to study departure time choices," Transportation, Springer, vol. 46(4), pages 1421-1445, August.
    13. Francisco J. Bahamonde-Birke & Uwe Kunert & Heike Link & Juan de Dios Ortúzar, 2017. "About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models," Transportation, Springer, vol. 44(3), pages 475-493, May.
    14. Munoz, Claudia & Laniado, Henry, 2021. "Airline choice model for international round-trip flights: The role of travelers’ satisfaction and personality traits," Research in Transportation Economics, Elsevier, vol. 90(C).
    15. Czajkowski, Mikołaj & Vossler, Christian A. & Budziński, Wiktor & Wiśniewska, Aleksandra & Zawojska, Ewa, 2017. "Addressing empirical challenges related to the incentive compatibility of stated preferences methods," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 47-63.
    16. Marley, A.A.J. & Swait, J., 2017. "Goal-based models for discrete choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 72-88.
    17. Francisco J. Bahamonde-Birke & Juan de Dios Ortúzar, 2015. "Analyzing the Continuity of Attitudinal and Perceptional Indicators in Hybrid Choice Models," Discussion Papers of DIW Berlin 1528, DIW Berlin, German Institute for Economic Research.
    18. Wiktor Budziński & Mikołaj Czajkowski, 2022. "Endogeneity and Measurement Bias of the Indicator Variables in Hybrid Choice Models: A Monte Carlo Investigation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 605-629, November.
    19. Enam, Annesha & Konduri, Karthik C. & Pinjari, Abdul R. & Eluru, Naveen, 2018. "An integrated choice and latent variable model for multiple discrete continuous choice kernels: Application exploring the association between day level moods and discretionary activity engagement choi," Journal of choice modelling, Elsevier, vol. 26(C), pages 80-100.
    20. Rose, J.M. & Borriello, A. & Pellegrini, A., 2023. "Formative versus reflective attitude measures: Extending the hybrid choice model," Journal of choice modelling, Elsevier, vol. 48(C).

    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:90:y:2016:i:c:p:192-217. 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.