The pricing of ride-hailing platforms (e.g., Didi Rider and Uber) is heavily and simultaneously influenced by the cross-group network effect and congestion effect. To analyze the bilateral pricing of ride-hailing platforms under the influence of these two effects, in this paper we construct a game-theoretic model under four different scenarios and analyze the equilibrium outcomes. The results show that: (1) when both passengers and drivers are sensitive to hassle costs, if the cross-group network effect on the passenger side is higher than that on the driver side, then the platform’s pricing on both sides increases with the increase in the congestion effect, otherwise the prices on both sides of the platform decrease with the increase in the congestion effect; (2) when passengers are sensitive to hassle costs and drivers are sensitive to price, if the ratio for passengers’ and drivers’ different perceptions of price and hassle cost is greater than a certain threshold, then the platform’s pricing on the passenger side increases with the increase in the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect; (3) when passengers are sensitive to price and drivers are sensitive to hassle costs, if the ratio for passengers’ and drivers’ different perceptions of price and hassle costs is greater than a certain threshold, then the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side increases with the increase of the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect; (4) when both passengers and drivers are price-sensitive, if the cross-group network effect on the passengers’ side is larger than that on the drivers’ side, then the platform should decrease its pricing on both sides with the increase in the congestion effect, otherwise, if the cross-group network effect on the passengers’ side is less than that on the drivers’ side, the platform should increase its pricing on both sides with the increase in the congestion effect; (5) the platform is able to generate the highest profit in each scenario, and the results of the profit comparison between the four scenarios depends on the cross-group network effects and the congestion effects on both the passengers’ and the drivers’ sides.

中文翻译：

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考虑跨集团网络效应和拥堵效应的网约车平台双边定价

网约车平台（例如滴滴出行和Uber）的定价同时受到跨集团网络效应和拥堵效应的严重影响。为了分析这两种效应影响下的网约车平台双边定价，本文构建了四种不同情景下的博弈论模型，并分析了均衡结果。结果表明：（1）当乘客和司机都对麻烦成本敏感时，如果乘客侧的跨群体网络效应高于司机侧，则双方平台的定价均随着增加而增加。处于拥堵效应中，否则平台两侧的价格随着拥堵效应的增加而下降；(2)当乘客对麻烦成本敏感、司机对价格敏感时，如果乘客和司机对价格和麻烦成本的不同认知比例大于一定阈值，则平台对乘客侧的定价随着拥堵效应的增加而增加，而平台对司机侧的定价则随着拥堵效应的增加而减少。拥堵效应增大，否则平台对乘客端的定价随着拥堵效应的增大而减小，平台对司机端的定价随拥堵效应的增大而增大；(3)当乘客对价格敏感、司机对麻烦成本敏感时，如果乘客和司机对价格和麻烦成本的不同认知比例大于一定阈值，则乘客侧的平台定价随着拥堵效应的增加而减少，司机侧的平台定价随着拥堵效应的增加而增加，反之，乘客侧的平台定价随着拥堵效应的增加而增加并且平台对司机端的定价随着拥堵效应的增加而降低；(4) 当乘客和司机都对价格敏感时，如果乘客侧的跨群体网络效应大于司机侧，则平台应随着乘客侧的增加而降低双方的定价。拥堵效应，否则，如果乘客侧的跨组网络效应小于驾驶员侧的跨组网络效应，随着拥堵效应的增加，平台应提高双方的定价；（5）平台能够在每种场景下产生最高的利润，四种场景之间的利润比较结果取决于跨群体网络效应以及乘客和司机双方的拥堵效应。