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Pursuing the impossible (?) dream: Incorporating attitudes into practice-ready travel demand forecasting models

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  • Mokhtarian, Patricia L.

Abstract

Despite the fact that our existing models are not up to the job of predicting travel behavior in today’s rapidly changing landscape, and despite considerable evidence that attitudes help us explain behavior more completely and more meaningfully, attitudes are nowhere to be found in practice-oriented travel demand forecasting models. Two main objections have been raised to their inclusion: they are too cumbersome to measure, and difficult-if-not-impossible to forecast. This paper reports on the considerable progress that has been made toward overcoming the first objection, through the use of machine learning methods to train a prediction function on smaller-scale research-oriented survey datasets, and then applying that function to impute attitudes into large-scale household travel survey datasets. Internal evaluations show that we can estimate attitudinal factor scores with moderate fidelity when using socioeconomic/demographic, land use, and targeted marketing variables, and with high fidelity when using just a few attitudinal marker variables. External evaluations demonstrate that the imputed attitudes lead to improved behavioral insight and predictive ability for forecasting-oriented models. With respect to the second objection I have only sketched some ideas for moving forward, but there are clearly some practical steps that could be taken at very little marginal cost, such as including as few as 10 attitudinal marker statements in future household travel surveys.

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  • Mokhtarian, Patricia L., 2024. "Pursuing the impossible (?) dream: Incorporating attitudes into practice-ready travel demand forecasting models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
  • Handle: RePEc:eee:transa:v:190:y:2024:i:c:s0965856424003021
    DOI: 10.1016/j.tra.2024.104254
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    1. Choi, Sungtaek & Mokhtarian, Patricia L., 2020. "How attractive is it to use the internet while commuting? A work-attitude-based segmentation of Northern California commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 37-50.
    2. Blanchflower, David G. & Oswald, Andrew J., 2004. "Well-being over time in Britain and the USA," Journal of Public Economics, Elsevier, vol. 88(7-8), pages 1359-1386, July.
    3. Xinyu Cao & Patricia L Mokhtarian & Susan L Handy, 2007. "Cross-Sectional and Quasi-Panel Explorations of the Connection between the Built Environment and Auto Ownership," Environment and Planning A, , vol. 39(4), pages 830-847, April.
    4. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    5. Malokin, Aliaksandr & Circella, Giovanni & Mokhtarian, Patricia L., 2019. "How do activities conducted while commuting influence mode choice? Using revealed preference models to inform public transportation advantage and autonomous vehicle scenarios," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 82-114.
    6. Golob, Thomas F., 2001. "Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(6), pages 495-514, July.
    7. Coltman, Tim & Devinney, Timothy M. & Midgley, David F. & Venaik, Sunil, 2008. "Formative versus reflective measurement models: Two applications of formative measurement," Journal of Business Research, Elsevier, vol. 61(12), pages 1250-1262, December.
    8. 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.
    9. 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.
    10. Mokhtarian, Patricia L. & Salomon, Ilan, 1997. "Modeling the desire to telecommute: The importance of attitudinal factors in behavioral models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(1), pages 35-50, January.
    11. Spears, Steven & Houston, Douglas & Boarnet, Marlon G., 2013. "Illuminating the unseen in transit use: A framework for examining the effect of attitudes and perceptions on travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 58(C), pages 40-53.
    12. Patricia L. Mokhtarian, 2019. "Subjective well-being and travel: retrospect and prospect," Transportation, Springer, vol. 46(2), pages 493-513, April.
    13. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    14. Horowitz, Joel L., 1991. "Reconsidering the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 433-438, December.
    15. Mehdizadeh, Milad & Nordfjaern, Trond & Klöckner, Christian A., 2022. "A systematic review of the agent-based modelling/simulation paradigm in mobility transition," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    16. 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.
    17. 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.
    18. Stopher,Peter, 2012. "Collecting, Managing, and Assessing Data Using Sample Surveys," Cambridge Books, Cambridge University Press, number 9780521863117, January.
    19. 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.
    20. 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.
    21. Xinyi Wang & F. Atiyya Shaw & Patricia L. Mokhtarian & Giovanni Circella & Kari E. Watkins, 2023. "Combining disparate surveys across time to study satisfaction with life: the effects of study context, sampling method, and transport attributes," Transportation, Springer, vol. 50(2), pages 513-543, April.
    22. Kroesen, Maarten & Handy, Susan & Chorus, Caspar, 2017. "Do attitudes cause behavior or vice versa? An alternative conceptualization of the attitude-behavior relationship in travel behavior modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 190-202.
    23. Shaw, F. Atiyya & Wang, Xinyi & Mokhtarian, Patricia L. & Watkins, Kari E., 2021. "Supplementing transportation data sources with targeted marketing data: Applications, integration, and internal validation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 150-169.
    24. Stopher,Peter, 2012. "Collecting, Managing, and Assessing Data Using Sample Surveys," Cambridge Books, Cambridge University Press, number 9780521681872, January.
    25. Handy, Susan & Cao, Xinyu & Mokhtarian, Patricia L., 2005. "Correlation or causality between the built environment and travel behavior? Evidence from Northern California," University of California Transportation Center, Working Papers qt5b76c5kg, University of California Transportation Center.
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