Large cities around the globe are facing an alarming growth in traffic congestion, to which a significant contributor are the private cabs operated by ride-hailing platforms. Pooled transportation options such as shuttle services are cheaper and greener alternatives but are still new to many customers and policy makers. In this work, we build a structural model to study customers’ preferences on prices and service features when choosing between private taxis and a scheduled shuttle service. Using the estimated model, we evaluate the efficacy of congestion surcharge policies in reducing congestion on the road. We find that a 20% congestion surcharge leads to 4% of customers switching from the cab to the shuttle service. We show that providing a 20% discount on shuttle rides achieves one-fourth of this effect. We also compare the efficacy of these policies with policies that reduce inconveniences associated with the shuttle service. We find that a 20% decrease in the walking inconvenience can achieve 35% of the total number of customers substituting from cabs to shuttles achieved as compared to the congestion surcharges. Our findings suggest that, by changing operations levers such as pooled service features, cities can achieve a substantial amount of the benefit from reducing congestion, without sacrificing customer welfare, compared with congestion surcharge policies. Moreover, as the majority of the effect comes from new users of the shuttle service, our finding highlights the importance of incorporating customer preference heterogeneity in designing effective policies to manage congestion.


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    Title :

    Private vs. Pooled Transportation: Customer Preference and Congestion Management


    Additional title:

    Springer Proceed. Business, Economics


    Contributors:
    Yang, Hui (editor) / Qiu, Robin (editor) / Chen, Weiwei (editor) / Arora, Kashish (author) / Zheng, Fanyin (author) / Girotra, Karan (author)

    Conference:

    INFORMS International Conference on Service Science ; 2020 ; Beijing, China December 19, 2020 - December 21, 2020



    Publication date :

    2022-01-03


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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