Dynamic Pricing of Ride-Hailing Platforms considering Service Quality and Supply Capacity under Demand Fluctuation

Abstract

Increasing attention is being paid to the pricing decisions of ride-hailing platforms. These platforms usually face market demand fluctuation and reflect supply and demand imbalances. Unlike existing studies, we focus on the optimal dynamic pricing of the platforms under imbalance between supply and demand caused by market fluctuation. Dynamic models are constructed based on the state change of supply and demand by using optimal control theory, with the aim of maximizing the platform’s total profit. We obtain the optimal trajectories of price, supply, and demand under three ride demand situations. The effects of some key parameters on pricing decisions, such as coefficient of demand fluctuation, service quality, and fixed commission rate, are examined. We find the optimal dynamic price can improve the match of supply-demand in ride-hailing market and enhance the revenue of platform.

Impacts of differentiated services and competition on the pricing strategies of ride‐hailing platforms

“…where ae Àdt indicates the initial demand of the market in a certain region at time t and d is the demand fluctuation factor, which describes three kinds of market demand: decreasing demand if d > 0, increasing demand if d < 0, and stable demand if d = 0 (Z. Sun et al, 2020). In practice, decreasing demand means a travel trough, such as a period of the day when passenger demand gradually decreases (e.g., after a peak period); increasing demand means a rush hour, such as a period of commuting or special weather (e.g., rain and snow) when passenger demand surges; and stable demand means a flat travel period, which corresponds to a period of relatively stable passenger demand.…”

“…Z. Sun et al (2020) have studied how demand fluctuation influences the optimal pricing decisions of the platform when there is only one platform; we extend to analyze whether the Bertrand price competition will change the effect of demand fluctuation on the optimal price of the platform.…”

“…Although some research has studied the different pricing strategies of ride-hailing platforms (Cachon et al, 2017;Yan et al, 2019), they usually only consider the pricing strategies of a single ride-hailing brand (i.e., without differentiated services) and do not consider demand fluctuation (Z. Sun et al, 2020). In this work, we propose three pricing strategies for ride-hailing platforms, including the dynamic price, differentiated price, and static price based on the market demand fluctuation.…”

“…First, following the research of Z. Sun et al (2020), we further propose three pricing strategies for both monopoly and duopoly ridehailing platforms based on the market demand fluctuation. We find that the demand fluctuation affects the three pricing strategies of the platform, but the competition between platforms will change this effect.…”

A Systematic Literature Review on Pricing Strategies in the Sharing Economy

“…As regards the pricing strategy, the intermediary can adopt dynamic pricing, surge pricing, or static pricing (see Table 3), among which dynamic pricing maximizes the profits of both the intermediary [150,152,153,158,159] and the drivers [159]. Meanwhile, surge pricing yields a nearly optimal profit for the intermediary [157] and also benefits both the intermediary and drivers [154]; furthermore, a more flexible price and payout ratio can bring more profit to the intermediary [162].…”