论文标题
垄断市场基于功能的定价的个人公平性
Individual Fairness in Feature-Based Pricing for Monopoly Markets
论文作者
论文摘要
我们在垄断市场中基于特征的价格歧视的背景下研究公平性。我们提出了一个新的个人公平概念，即α-fairness，该概念确保具有相似特征的个人面临着相似的价格。首先，我们研究离散估值空间，并为基于公平特征的最佳定价提供了分析解决方案。我们表明，公平定价的成本被定义为基于最佳功能的最佳定价与预期收入的预期收入的比率通常是任意大的。当收入功能在价格上是连续且凹入的时，我们表明，无论模型参数如何，人们都可以严格地实现COF少于2。最后，我们提供了一种算法来计算实现此COF的基于公平功能的定价策略。
We study fairness in the context of feature-based price discrimination in monopoly markets. We propose a new notion of individual fairness, namely, α-fairness, which guarantees that individuals with similar features face similar prices. First, we study discrete valuation space and give an analytical solution for optimal fair feature-based pricing. We show that the cost of fair pricing is defined as the ratio of expected revenue in an optimal feature-based pricing to the expected revenue in an optimal fair feature-based pricing (CoF) can be arbitrarily large in general. When the revenue function is continuous and concave with respect to the prices, we show that one can achieve CoF strictly less than 2, irrespective of the model parameters. Finally, we provide an algorithm to compute fair feature-based pricing strategy that achieves this CoF.
