Daily deals platforms such as Amazon Local, Google Offers, GroupOn, and LivingSocial have provided a new channel for merchants to directly market to consumers. In order to maximize consumer acquisition and retention, these platforms would like to offer deals that give good value to users. Currently, selecting such deals is done manually; however, the large number of submarkets and localities necessitates an automatic approach to selecting good deals and determining merchant payments. We approach this challenge as a market design problem. We postulate that merchants already have a good idea of the attractiveness of their deal to consumers as well as the amount they are willing to pay to offer their deal. The goal is to design an auction that maximizes a combination of the revenue of the auctioneer (platform), welfare of the bidders (merchants), and the positive externality on a third party (the consumer), despite the asymmetry of information about this consumer benefit. We design auctions that truthfully elicit this information from the merchants and maximize the social welfare objective, and we characterize the consumer welfare functions for which this objective is truthfully implementable. We generalize this characterization to a very broad mechanism-design setting and give examples of other applications.
翻译:亚马逊本地、谷歌出价、GroupOn、Living Social等日常交易平台为商人直接销售消费者提供了一个新的渠道。为了尽量扩大消费者的收购和保留,这些平台希望提供对用户有良好价值的交易。目前,这类交易是手工进行的;然而,由于次市场和地点众多,因此有必要采用自动办法选择好交易和确定商人的付款。我们将此挑战视为市场设计问题。我们假设商人已经很好地了解其交易对消费者的吸引力以及他们愿意支付的交易金额。我们的目标是设计一个拍卖,最大限度地将拍卖商的收入(平台)、投标人的福利(商人)和第三方(消费者)的积极外在性结合起来,尽管关于消费者利益的信息不对称。我们设计拍卖,真实地从商人那里获取这种信息,最大限度地实现社会福利目标,我们把消费者福利功能定性为可以真正执行的目标。我们把这种描述概括化为非常广泛的机制设计设置,并举出其他应用实例。