团队

Problem definition: Ride-hailing platforms face a supply-demand imbalance. During peak periods, the demand from passengers far exceeds the supply of drivers, whereas during off-peak periods, there is an abundance of supply but weak demand. The well-studied surge pricing can be challenging to implement in markets where prices are subject to regulation and are inflexible to adjust. We study an alternative operational approach that shifts the supply of drivers from off-peak to peak periods to address the supply-demand imbalance. Methodology/results: We propose two novel incentive schemes: the qualification scheme and the prioritization scheme. Specifically, the platform sets a work target for the peak period. Under the qualification scheme, the platform assigns off-peak service requests only to drivers who meet the peak period target. Under the prioritization scheme, the platform prioritizes off-peak requests for drivers who meet the peak period target. We analyze the effectiveness of these schemes, considering the openness of the platform’s supply system. For platforms with a closed system that only allows full-time drivers to provide service, the qualification scheme improves the total matching volume to a greater extent but hurts full-time drivers more than the prioritization scheme. For platforms with an open system that also allows the abundant part-time drivers to serve off-peak requests, the prioritization scheme outperforms the qualification scheme in improving total matching volume. Furthermore, the implementation of an incentive scheme in an open system may benefit both the platform and full-time drivers. Managerial implications: Our study suggests an alternative to surge pricing for on-demand platforms to address the supply-demand imbalance when prices are inflexible. It provides insights for platforms with varying levels of supply system openness in choosing appropriate incentive schemes. The welfare results offer guidance for platforms and policymakers regarding both matching volume and worker welfare.

Customer reviews help communicate product information, but their effectiveness may suffer from selection bias (i.e., depending on factors, such as the individual experience and price, not all consumers may voluntarily write reviews). Consequently, a seller may have to resort to additional means (e.g., signaling through price in the context of an experience good) to convey its quality. This paper develops an analytical model to investigate the interaction of customer reviews and price with the presence of selection bias in marketing an experience good with uncertain quality to consumers. Our analysis reveals the dual roles played by both customer reviews and price in communicating quality information. On one hand, customer reviews may either directly convey product information with unbiased distribution of reviews or facilitate price signaling when reviews are biased because of selection. On the other hand, price may be adjusted to mitigate the selection bias of reviews to make them more informative, and it may also signal quality directly in the presence of review bias. As a result, we show that bias in reviews may actually benefit consumers without compromising information communication as the incentive to reduce review selection bias makes it credible and profitable for the high-quality seller to signal its type by undercutting the price that would be set if it is of low quality. We then extend our analysis to examine the information, profits, and welfare impacts of several important design elements of a review system as well as the impact of consumers’ aversion to risk. Finally, the implications of our findings on the management of user-generated content and pricing are discussed.

Media platforms generate revenue by bringing consumers and advertisers together. Although advertisers like to promote their services and products to consumers, consumers dislike advertisements to varying levels. Given heterogeneity in consumers’ dislike for ads, platforms could adopt either a uniform pricing strategy or a tiered pricing strategy for consumers. In this paper, we examine competing media platforms’ equilibrium pricing strategies in the presence of cross-side externalities between consumers and advertisers and their endogenous homing decisions. We find that symmetric platforms may adopt asymmetric pricing strategies in an attempt to focus on different sides of the market and soften interplatform competition if the incremental value that consumers derive from multihoming is large. However, they pursue only symmetric pricing strategies if this value is small. Counter to the intuition based on one-sided markets, our analysis shows that tiered pricing strategies need not improve the profits of platforms competing in a media market. In fact, when the incremental value that consumers derive from multihoming is large, competing platforms may earn lower profits from tiered pricing and yet pursue it (Prisoner’s dilemma). In contrast to standard results on tiered prices, we find that high-type consumers may not pay as much as their full willingness-to-pay for ad avoidance, implying that the incentive-compatibility constraint of high-type consumers may not be binding. Finally, we extend the model to allow for heterogeneous advertisers, vary the decision sequence, permit platforms to compete on ad capacity (rather than ad price), entertain an alternative formulation of transportation cost, and consider correlated advertising reach.

为用户提供主动匹配搭建平台的企业在提高匹配效率和保证匹配质量方面面临着巨大的挑战。本文研究了当用户从匹配的垂直属性（即质量）及其水平属性（即异质性匹配）中获得效用时，信息设计如何用于改善匹配结果。我们考虑一个博弈论模型，其中互相竞争的发送者向互相竞争的接收者提出匹配请求，并且两侧的用户在水平和垂直方向上都有差异。我们首先证明用户对垂直属性的偏好会加剧竞争并损害匹配效率，并且为了避免竞争，发送者可能会从近距离接收者切换到远距离接收者，即便对匹配的水平接近度更加看中。其次，我们研究了四种信息设计，每种设计隐去来自市场一侧的一种类型的信息。隐去任何一侧的垂直信息的设计增加了匹配的数量，这其中隐去接收者信息的改进更大。相比之下，隐去任何一侧水平信息的设计可能导致所有请求都集中在一个接收者上，并导致最严重的匹配失败。第三，匹配数量的增加是以牺牲某些用户福利为代价的，因为隐去一侧的垂直信息不仅会伤害双侧的高质量用户，也会伤害另一侧的低质量用户。尽管在某些条件下隐去一侧的水平信息可能会增加匹配量，但隐去一侧的垂直信息的设计可以做到帕累托改进。第四，在配过程中用户的自行策略定价不仅重新分配了用户福利，而且纠正了匹配失真。最后，与没有用户定价的结果对比，当用户可以策略定价时，平台隐去一侧的纵向信息可以使另一侧的所有用户受益，而隐去一侧的横向信息可以使同一侧的所有用户受益。

一些媒体平台从消费者及广告商双方赚取利润（例如Spotify、Hulu），而另一些平台的利润则单方面来自广告商（例如Jango、Tubi）或消费者（例如Tidal、Netflix）。因此，根据如何将有限的版面空间分配给内容和广告，媒体平台的策略不尽相同。在本文中，我们考虑到多边媒体市场的跨边网络相应以及内容提供商的竞争特性，考察媒体平台的内容提供策略及其对媒体平台和内容供应商在利润方面的影响。为了帮助分析，我们建立了一个媒体平台与内容供应商、消费者和广告商三方互动的模型。首先，我们关于完全竞争的内容市场的分析表明，尽管消费者对内容的渴望可以提高其支付意愿，却同时可以伤害到媒体平台的利润。其次，和人们的预期相反，平台的利润可以因获取内容成本的提高而增长。第三，当平台使用付费内容加广告的策略时，广告商对于触达消费者的意愿会降低垄断市场的内容供应商的利润。第四，一个垄断市场的内容供应商无法从榨取竞争平台的全部利润。此外，互相竞争的内容供应商可能会收取比垄断市场的内容供应商更高的价格。最后，我们阐述了内容市场的竞争特性如何影响平台对于无广告策略的选择。