Highlights Studied data sharing within a transit market with externality effects. Data availability modeled with Bayesian game with noncooperative frequency setting. Data sharing decisions modeled as partitions in a coalitional structure. Test results on competitive services, complementary services, Nguyen-Dupuis network. Results suggest voluntary data-sharing or require cooperation in market-wide sharing.

    Abstract In this study, various forms of data sharing are axiomatized. A new way of studying coopetition, especially data-sharing coopetition, is proposed. The problem of the Bayesian game with signal dependence on actions is observed; and a method to handle such dependence is proposed. We focus on fixed-route transit service markets. A discrete model is first presented to analyze the data-sharing coopetition of an oligopolistic transit market when an externality effect exists. Given a fixed data sharing structure, a Bayesian game is used to capture the competition under uncertainty while a coalition formation model is used to determine the stable data-sharing decisions. A new method of composite coalition is proposed to study efficient markets. An alternative continuous model is proposed to handle large networks using simulation. We apply these models to various types of networks. Test results show that perfect information may lead to perfect selfishness. Sharing more data does not necessarily improve transit service for all groups, at least if transit operators remain noncooperative. Service complementarity does not necessarily guarantee a grand data-sharing coalition. These results can provide insights on policy-making, like whether city authorities should enforce compulsory data-sharing along with cooperation between operators or setup a voluntary data-sharing platform.


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    Title :

    Efficient and stable data-sharing in a public transit oligopoly as a coopetitive game


    Contributors:
    Liu, Qi (author) / Chow, Joseph Y.J. (author)


    Publication date :

    2022-06-28


    Size :

    24 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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