Highlights Aggregate taxi market equilibrium under hybrid modes is modeled. Existence and stability of taxi market equilibrium are examined. Impacts of platform’s pricing strategies on taxi market performance are revealed. Properties of desirable price perturbations are characterized.

    Abstract Taxi hailing apps that facilitate taxi-customer matching quickly become popular in recent years. By combining the theories of two-sided market and taxi market, this paper models the taxi market in the presence of a single taxi hailing app through an aggregate and static approach. Based on the equilibrium model, the existence and stability of equilibria are examined, and a partial-derivative-based sensitivity analysis is conducted to quantitatively evaluate the impacts of the platform’s pricing strategies to the taxi market performance. The features of desirable price perturbations that improve social welfare and/or the platform’s profitability are also characterized.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Pricing strategies for a taxi-hailing platform


    Contributors:
    Wang, Xiaolei (author) / He, Fang (author) / Yang, Hai (author) / Oliver Gao, H. (author)


    Publication date :

    2016-05-22


    Size :

    20 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Pricing strategies for a taxi-hailing platform

    Wang, Xiaolei | Online Contents | 2016


    TAXI HAILING SYSTEM AND TAXI HAILING METHOD

    NAKAMURA KAZUTO | European Patent Office | 2019

    Free access

    Research on Collaborative Pricing Strategy Between Taxi and Online Car-Hailing

    Si, Yang / Yu, Bin / Qu, Guixian | Springer Verlag | 2022


    Research on Collaborative Pricing Strategy Between Taxi and Online Car-Hailing

    Si, Yang / Yu, Bin / Qu, Guixian | British Library Conference Proceedings | 2022


    Taxi-hailing platforms: Inform or Assign drivers?

    Sun, Luoyi / Teunter, Ruud H. / Hua, Guowei et al. | Elsevier | 2020