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Bundling Strategies for Ride-Hailing Platforms Based on Price and Service Level

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The increasing popularity of ride-hailing applications has given rise to a new channel in which ride-hailing platforms are bundled into aggregation platforms to earn additional orders by charging commissions and slotting fees. Such bundled channels, unlike traditional reseller electronic ones, may flutter prices, service levels, market demands, and then further affect their profits. These divergent attitudes raise an interesting and key question about whether and under what conditions bundled channels should be introduced to ride-hailing platforms. In this paper, we provide an analytical framework for ride-hailing and aggregation platforms in unbundled and bundled scenarios, respectively. We build a Stackelberg game model in which ride-hailing and aggregation platforms as leaders obtain prices by constructing Nash equilibria, while drivers as followers determine service levels given to two platforms. Drivers’ best responses in terms of service levels for two platforms, as well as platforms’ optimal pricing strategies and profits are achieved. To capture access conditions of the ride-hailing platform and the profit contention between two platforms, we further conduct sensitivity analysis on cost coefficients of service levels, price and cross-price substitutions, service level and cross-service level substitutions, revenue-sharing ratio, cost, as well as commission and slotting fee. Based on numerical examples and analysis of the results, some interesting managerial insights about bundling strategies are gained for ride-hailing platforms.
Title: Bundling Strategies for Ride-Hailing Platforms Based on Price and Service Level
Description:
The increasing popularity of ride-hailing applications has given rise to a new channel in which ride-hailing platforms are bundled into aggregation platforms to earn additional orders by charging commissions and slotting fees.
Such bundled channels, unlike traditional reseller electronic ones, may flutter prices, service levels, market demands, and then further affect their profits.
These divergent attitudes raise an interesting and key question about whether and under what conditions bundled channels should be introduced to ride-hailing platforms.
In this paper, we provide an analytical framework for ride-hailing and aggregation platforms in unbundled and bundled scenarios, respectively.
We build a Stackelberg game model in which ride-hailing and aggregation platforms as leaders obtain prices by constructing Nash equilibria, while drivers as followers determine service levels given to two platforms.
Drivers’ best responses in terms of service levels for two platforms, as well as platforms’ optimal pricing strategies and profits are achieved.
To capture access conditions of the ride-hailing platform and the profit contention between two platforms, we further conduct sensitivity analysis on cost coefficients of service levels, price and cross-price substitutions, service level and cross-service level substitutions, revenue-sharing ratio, cost, as well as commission and slotting fee.
Based on numerical examples and analysis of the results, some interesting managerial insights about bundling strategies are gained for ride-hailing platforms.

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