论文标题
信息产品的最佳广告
Optimal Advertising for Information Products
论文作者
论文摘要
销售信息产品时，卖方可以提供一些免费的部分信息来改变人们的估值，以便可以增加总收入。我们通过揭示部分信息来研究广告信息产品的一般问题。我们认为是决策者的买家。决策问题的结果取决于买家未知的世界状况。买家可以做出自己的观察，因此可以对世界状况保持不同的个人信念。有一个信息卖家可以进入世界状态。卖方可以通过揭示一些部分信息来促进信息。我们假设卖方选择了长期的广告策略，然后对此进行承诺。卖方的目标是最大化预期收入。我们在两个设置中研究问题。 （1）卖方针对某种类型的买家。在这种情况下，找到最佳的广告策略等同于找到简单功能的凹面。该功能是两个数量的产物，即可能性比和不确定性成本。基于此观察结果，我们证明了最佳机制的某些特性，这使我们能够通过有限尺寸的凸面程序来解决最佳机制。如果世界状态具有恒定的可能实现，或者买家面临持续数量的选项，则凸面计划将具有多项式规模。对于一般问题，我们证明找到最佳机制是NP-HARD。 （2）当卖方面对不同类型的买家并且只知道其类型的分布时，我们提供了一种近似算法，而当不太难以预测将购买购买的买家的类型类型时。对于一般问题，我们证明找到一个恒定因子近似是NP-HARD。
When selling information products, the seller can provide some free partial information to change people's valuations so that the overall revenue can possibly be increased. We study the general problem of advertising information products by revealing partial information. We consider buyers who are decision-makers. The outcomes of the decision problems depend on the state of the world that is unknown to the buyers. The buyers can make their own observations and thus can hold different personal beliefs about the state of the world. There is an information seller who has access to the state of the world. The seller can promote the information by revealing some partial information. We assume that the seller chooses a long-term advertising strategy and then commits to it. The seller's goal is to maximize the expected revenue. We study the problem in two settings. (1) The seller targets buyers of a certain type. In this case, finding the optimal advertising strategy is equivalent to finding the concave closure of a simple function. The function is a product of two quantities, the likelihood ratio and the cost of uncertainty. Based on this observation, we prove some properties of the optimal mechanism, which allow us to solve for the optimal mechanism by a finite-size convex program. The convex program will have a polynomial-size if the state of the world has a constant number of possible realizations or the buyers face a decision problem with a constant number of options. For the general problem, we prove that it is NP-hard to find the optimal mechanism. (2) When the seller faces buyers of different types and only knows the distribution of their types, we provide an approximation algorithm when it is not too hard to predict the possible type of buyers who will make the purchase. For the general problem, we prove that it is NP-hard to find a constant-factor approximation.
