Pricing of Platforms in Two-Sided Markets with Heterogeneous Agents and Limited Market Size

We study a two-sided market represented by network platforms and heterogeneous agents. Our setup departs from Armstrong (2006)’s monopoly model by assuming both (1) a continuum of agents of limited size on each side of the market and (2) heterogeneous utility of agents with Hotelling specification. We show that the monopoly’s optimal pricing strategy always results in a corner solution in terms of the equilibrium market share. We also solve for the social planner’s optimization problem and obtain a similar corner solution result. In addition, the exact values for the equilibrium in the case of duopoly for a two-sided market on two platforms are obtained.

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Optimal pricing strategy for a service provider in the presence of repetitive usage

International Transactions in Operational Research ◽

10.1111/itor.13017 ◽

2021 ◽

Author(s):

Ping Cao ◽

Wenli Zhou ◽

Jie Wu

Keyword(s):

Service Provider ◽

Pricing Strategy ◽

Optimal Pricing ◽

Optimal Pricing Strategy

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Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

Journal of Advanced Transportation ◽

10.1155/2020/8890233 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Xiaomin Xu ◽

Dongxiao Niu ◽

Yan Li ◽

Lijie Sun

Keyword(s):

Electric Vehicles ◽

Optimization Problems ◽

Power Grid ◽

Economic Benefits ◽

Pricing Strategy ◽

Optimal Pricing ◽

Electricity Pricing ◽

Optimal Pricing Strategy ◽

Charging Stations ◽

The Impact

Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.

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