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Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates

Author

Listed:
  • Luis Márquez

    (Universidad Pedagógica y Tecnológica de Colombia)

  • Víctor Cantillo

    (Universidad del Norte)

  • Julián Arellana

    (Universidad del Norte)

Abstract

Hybrid discrete choice (HDC) modeling requires indicators to allow for the identification of latent variables. An indicator usually expresses the level of agreement of a respondent with a given statement, generally based on a Likert scale response. Literature exhibits remarkable variations regarding indicators’ complexity, expressed by the number of indicators for each latent variable, the type of scale, and granularity. Dealing with different levels of complexity implies that respondents require different cognitive efforts when choosing a relevant Likert point. Further, as a Likert item is undoubtedly a set of ordered categories, modelers face the challenge of estimating a large number of threshold parameters resulting from greater complexity when using ordered models for measurement equations. This paper studies the influence of indicators’ complexity on the estimation of HDC models based on an experiment that systematically varies the number of indicators, the granularity and the type of scale. We specified a proper parameterization of the scale factor of the measurement component for capturing potential effects of complexity in measurement equations. Findings revealed that granularity and its quadratic effect, as well as the interaction between granularity and number of indicators, affect the error variance of the measurement component and have a substantial impact on the goodness-of-fit of the discrete choice sub-model. Modeling results also showed that using odd-numbered scales, widely used in transportation choice studies, contribute to a lower error variance of the measurement component.

Suggested Citation

  • Luis Márquez & Víctor Cantillo & Julián Arellana, 2020. "Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates," Transportation, Springer, vol. 47(1), pages 373-396, February.
  • Handle: RePEc:kap:transp:v:47:y:2020:i:1:d:10.1007_s11116-018-9891-6
    DOI: 10.1007/s11116-018-9891-6
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    1. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    2. Weijters, B. & Cabooter, E. & Schillewaert, N., 2010. "The effect of rating scale format on response styles: the number of response categories and response category labels," Vlerick Leuven Gent Management School Working Paper Series 2010-07, Vlerick Leuven Gent Management School.
    3. André Duarte & Camila Garcia & Grigoris Giannarakis & Susana Limão & Amalia Polydoropoulou & Nikolaos Litinas, 2010. "New approaches in transportation planning: happiness and transport economics," Netnomics, Springer, vol. 11(1), pages 5-32, April.
    4. B. Weijters & E. Cabooter & N. Schillewaert, 2010. "The effect of rating scale format on response styles: the number of response categories and response catgory labels," Post-Print hal-00787535, HAL.
    5. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    6. 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.
    7. Swait, Joffre & Adamowicz, Wiktor, 2001. "The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching," Journal of Consumer Research, Oxford University Press, vol. 28(1), pages 135-148, June.
    8. 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.
    9. Caussade, Sebastián & Ortúzar, Juan de Dios & Rizzi, Luis I. & Hensher, David A., 2005. "Assessing the influence of design dimensions on stated choice experiment estimates," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 621-640, August.
    10. Rose, John M. & Hensher, David A. & Caussade, Sebastian & Ortúzar, Juan de Dios & Jou, Rong-Chang, 2009. "Identifying differences in willingness to pay due to dimensionality in stated choice experiments: a cross country analysis," Journal of Transport Geography, Elsevier, vol. 17(1), pages 21-29.
    11. Kim, Jinhee & Rasouli, Soora & Timmermans, Harry, 2017. "Satisfaction and uncertainty in car-sharing decisions: An integration of hybrid choice and random regret-based models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 13-33.
    12. Arentze, Theo & Borgers, Aloys & Timmermans, Harry & DelMistro, Romano, 2003. "Transport stated choice responses: effects of task complexity, presentation format and literacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 229-244, May.
    13. 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.
    14. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, April.
    15. 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.
    16. Di Ciommo, Floridea & Monzón, Andrés & Fernandez-Heredia, Alvaro, 2013. "Improving the analysis of road pricing acceptability surveys by using hybrid models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 302-316.
    17. Chao Chen & Caspar Chorus & Eric Molin & Bert Wee, 2016. "Effects of task complexity and time pressure on activity-travel choices: heteroscedastic logit model and activity-travel simulator experiment," Transportation, Springer, vol. 43(3), pages 455-472, May.
    18. Márquez, Luis & Pico, Ricardo & Cantillo, Víctor, 2018. "Understanding captive user behavior in the competition between BRT and motorcycle taxis," Transport Policy, Elsevier, vol. 61(C), pages 1-9.
    19. Nowlis, Stephen M & Kahn, Barbara E & Dhar, Ravi, 2002. "Coping with Ambivalence: The Effect of Removing a Neutral Option on Consumer Attitude and Preference Judgments," Journal of Consumer Research, Oxford University Press, vol. 29(3), pages 319-334, December.
    20. Cervero, Robert & Golub, Aaron, 2007. "Informal transport: A global perspective," Transport Policy, Elsevier, vol. 14(6), pages 445-457, November.
    21. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    22. 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.
    23. 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.
    24. Weijters, Bert & Cabooter, Elke & Schillewaert, Niels, 2010. "The effect of rating scale format on response styles: The number of response categories and response category labels," International Journal of Research in Marketing, Elsevier, vol. 27(3), pages 236-247.
    25. Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
    26. Small, Kenneth A., 2012. "Valuation of travel time," Economics of Transportation, Elsevier, vol. 1(1), pages 2-14.
    27. Márquez, Luis & Cantillo, Víctor & Arellana, Julián, 2014. "How are comfort and safety perceived by inland waterway transport passengers?," Transport Policy, Elsevier, vol. 36(C), pages 46-52.
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