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A Data Fusion Approach for Ride-sourcing Demand Estimation: A Discrete Choice Model with Sampling and Endogeneity Corrections

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  • Rico Krueger
  • Michel Bierlaire
  • Prateek Bansal

Abstract

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical models for ride-sourcing demand estimation at an aggregate level due to limited data availability. These models lack foundations in microeconomic theory, ignore competition of ride-sourcing with other travel modes, and cannot be seamlessly integrated into existing individual-level (disaggregate) activity-based models to evaluate system-level impacts of ride-sourcing services. In this paper, we present and apply an approach for estimating ride-sourcing demand at a disaggregate level using discrete choice models and multiple data sources. We first construct a sample of trip-based mode choices in Chicago, USA by enriching household travel survey with publicly available ride-sourcing and taxi trip records. We then formulate a multivariate extreme value-based discrete choice with sampling and endogeneity corrections to account for the construction of the estimation sample from multiple data sources and endogeneity biases arising from supply-side constraints and surge pricing mechanisms in ride-sourcing systems. Our analysis of the constructed dataset reveals insights into the influence of various socio-economic, land use and built environment features on ride-sourcing demand. We also derive elasticities of ride-sourcing demand relative to travel cost and time. Finally, we illustrate how the developed model can be employed to quantify the welfare implications of ride-sourcing policies and regulations such as terminating certain types of services and introducing ride-sourcing taxes.

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  • Rico Krueger & Michel Bierlaire & Prateek Bansal, 2022. "A Data Fusion Approach for Ride-sourcing Demand Estimation: A Discrete Choice Model with Sampling and Endogeneity Corrections," Papers 2212.02178, arXiv.org.
    • Handle: RePEc:arx:papers:2212.02178
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    References listed on IDEAS

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    1. Edwards, Mickey, 2020. "Nonstandard ridehail use in Austin," Journal of Transport Geography, Elsevier, vol. 86(C).
    2. Dean, Matthew D. & Kockelman, Kara M., 2021. "Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago," Journal of Transport Geography, Elsevier, vol. 91(C).
    3. Wen, Chieh-Hua & Huang, Chia-Jung & Fu, Chiang, 2020. "Incorporating continuous representation of preferences for flight departure times into stated itinerary choice modeling," Transport Policy, Elsevier, vol. 98(C), pages 10-20.
    4. Jerry Hausman & Gregory Leonard & J. Douglas Zona, 1994. "Competitive Analysis with Differentiated Products," Annals of Economics and Statistics, GENES, issue 34, pages 143-157.
    5. repec:adr:anecst:y:1994:i:34:p:06 is not listed on IDEAS
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    7. Malik, Jai & Bunch, David S. & Handy, Susan & Circella, Giovanni, 2021. "A deeper investigation into the effect of the built environment on the use of ridehailing for non-work travel," Journal of Transport Geography, Elsevier, vol. 91(C).
    8. 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.
    9. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2017. "Accounting for price endogeneity in airline itinerary choice models: An application to Continental U.S. markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 228-246.
    10. Hasnine, Md Sami & Hawkins, Jason & Habib, Khandker Nurul, 2021. "Effects of built environment and weather on demands for transportation network company trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 171-185.
    11. Lam, Chungsang Tom & Liu, Meng & Hui, Xiang, 2021. "The geography of ridesharing: A case study on New York City," Information Economics and Policy, Elsevier, vol. 57(C).
    12. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    13. Soltani, Ali & Allan, Andrew & Khalaj, Fahimeh & Pojani, Dorina & Mehdizadeh, Milad, 2021. "Ridesharing in Adelaide: Segmentation of users," Journal of Transport Geography, Elsevier, vol. 92(C).
    14. Bierlaire, M. & Bolduc, D. & McFadden, D., 2008. "The estimation of generalized extreme value models from choice-based samples," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 381-394, May.
    15. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    16. Yan, Xiang & Zhao, Xilei & Han, Yuan & Hentenryck, Pascal Van & Dillahunt, Tawanna, 2021. "Mobility-on-demand versus fixed-route transit systems: An evaluation of traveler preferences in low-income communities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 481-495.
    17. Lazarus, Jessica R. & Caicedo, Juan D. & Bayen, Alexandre M. & Shaheen, Susan A., 2021. "To Pool or Not to Pool? Understanding opportunities, challenges, and equity considerations to expanding the market for pooling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 199-222.
    18. Alejandro Tirachini, 2020. "Ride-hailing, travel behaviour and sustainable mobility: an international review," Transportation, Springer, vol. 47(4), pages 2011-2047, August.
    19. Haitao Yu & Zhong-Ren Peng, 2020. "The impacts of built environment on ridesourcing demand: A neighbourhood level analysis in Austin, Texas," Urban Studies, Urban Studies Journal Limited, vol. 57(1), pages 152-175, January.
    20. Koppelman, Frank S. & Coldren, Gregory M. & Parker, Roger A., 2008. "Schedule delay impacts on air-travel itinerary demand," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 263-273, March.
    21. Gopalakrishnan, Raja & Guevara, C. Angelo & Ben-Akiva, Moshe, 2020. "Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 45-57.
    22. Mirko Goletz & Francisco J. Bahamonde-Birke, 2021. "The ride-sourcing industry: status-quo and outlook," Transportation Planning and Technology, Taylor & Francis Journals, vol. 44(6), pages 561-576, August.
    23. Cristian Angelo Guevara & Moshe E. Ben-Akiva, 2012. "Change of Scale and Forecasting with the Control-Function Method in Logit Models," Transportation Science, INFORMS, vol. 46(3), pages 425-437, August.
    24. Habib, Khandker Nurul, 2019. "Mode choice modelling for hailable rides: An investigation of the competition of Uber with other modes by using an integrated non-compensatory choice model with probabilistic choice set formation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 205-216.
    25. Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2020. "Using machine learning for direct demand modeling of ridesourcing services in Chicago," Journal of Transport Geography, Elsevier, vol. 83(C).
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