In this paper, we analyse how a peer-to-peer sharing platform should price its service to maximize profit, when user participation increases the value of the service to others by causing positive externalities. Modelling the service as an excludable public good, we propose a bounded utility model to capture many infrastructure sharing applications with bounded network value, in which complete coverage generates finite user valuation (e.g., WiFi or hotspot). Unbounded utility models are used to capture the large-scale user interactions in social media, where the network value follows Metcalfe’s or Zipf’s law. For these utility models, we analyze the optimal pricing schemes in the case of heterogeneous users under complete and incomplete information of users’ service valuations. We propose the concept of ‘price of information’ ( $PoI$ ) to characterize the profit loss due to lack of information, and present asymptotic $PoI$ bounds for different utility models. We also show that the difficult-to-implement differentiated pricing scheme, which is optimal under incomplete user information, can be replaced by a simple uniform price scheme that is asymptotic optimal. Finally, we extend our pricing schemes to a two-sided market by including a new group of ‘pure’ service users who do not contribute to the public good, and show that the platform may charge zero price to the original group of users in order to attract this pure user group.

中文翻译：

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具有网络外部性的对等共享的最优定价

在本文中，我们分析了当用户参与通过引起积极的外部性而增加了对他人的服务价值时，对等共享平台应如何为服务定价以实现最大的利润。我们将服务建模为可排他的公共物品，我们提出了一种有限制的效用模型，以捕获具有有限网络价值的许多基础设施共享应用程序，其中完整的覆盖范围会产生有限的用户评估（例如，WiFi或热点）。无限效用模型用于捕获社交媒体中的大规模用户交互，其中网络价值遵循梅特卡夫定律或齐普夫定律。对于这些实用新型，我们在用户服务估价的完整和不完整信息下，分析了异构用户情况下的最优定价方案。我们提出“信息价格”的概念（ $ PoI $ ）来表征由于缺乏信息而呈现的渐近性 $ PoI $ 不同实用新型的界限。我们还表明，难以实现的差异化定价方案（在不完整的用户信息下是最优的）可以由渐近最优的简单统一定价方案代替。最后，我们将定价方案扩展到了两面市场，包括了一组新的“纯”服务用户，这些用户不会为公共利益做出贡献，并表明该平台可以按顺序向原始用户组收取零价格吸引这个纯粹的用户群。