ICES: Small: Collaborative Research: Selling to Networked Markets

在最近的信息技术进步的推动下，现代市场正变得更加复杂、动态和相互联系。客户越来越多地了解他们可以获得的信息，从而能够做出更好的决策。对公司来说，这既带来了机遇，也带来了挑战。积极的一面是，该公司拥有比以往任何时候都更多的工具，使其能够更好地向客户销售产品。这些工具本质上既是计算性的(定价算法、客户定位数据、社交网络信息)，也是经济的(动态机制)。该公司面临的挑战是，现代技术还能让消费者很容易地了解其他客户的意见，并在他们的决策中具有战略性。拥有这样的战略和网络客户对公司来说并不一定是净负面的，但它肯定会使公司如何销售其产品的问题变得更加复杂。这个项目旨在开发一个框架，以了解如何在从根本上动态和相互关联的市场中销售商品。该项目将研究在客户可以相互学习的动态环境中，哪些机制是收入最优(或接近最优，同时简单且易于计算)。PI将研究网络学习对公司行为的影响，以及它是否迫使公司分担与消费者学习相关的一些成本。该项目还将重点研究社会网络结构如何影响最优机制，并试图了解这种网络学习效应是否会导致公司收入减少(或增加)和总体消费者福利。网络市场动态的基础研究为包括公司、消费者群体和监管机构在内的广大受众提供了更深入的知识。运筹学、信息系统和计算机科学交界处的课程开发将从这一研究经验中受益。

Modern marketplaces, enabled by recent advances in informationtechnology, are becoming ever more complex, dynamic andinterconnected. Customers are increasingly more informed about thechoices available to them and are thus able to make better decisions.For firms, this presents both opportunities and challenges. On thepositive side, the firm has a bigger than ever array of tools at itsdisposal that enable it to better sell to its customers. Such toolsare both computational (pricing algorithms, customer targeting data,social networking information) and economical (dynamic mechanisms) innature. The challenging aspect for the firm is that modern technologyalso allows consumers to easily learn the opinions of fellow customersand to be strategic in their decision-making. Having such strategicand networked customers is not necessarily a net negative for thefirm, but it certainly makes the firm's problem of how to sell itsproducts a more complex one.This project aims to develop a framework for understanding how tosell goods in markets that are fundamentally dynamic andinterconnected. The project will research what mechanisms are revenue-optimal(or near-optimal, while being simple and computationally tractable) indynamic settings where customers can learn from each other. The PIs willstudy the effect of network learning on the firm's behavior andwhether it forces the firm to share some of the costs associated withconsumer learning. The project will also focus on how the socialnetworkstructure affects the optimal mechanism and will try tounderstand whether such network learning effects lead to lower (orhigher) revenue for the firm and aggregate consumer welfare.Fundamental research in the dynamics of networked markets providesdeeper knowledge to a broad audience that includes firms, consumergroups and regulators. Curriculum development at the interface ofoperations research, information systems and computer science willbenefit from this research experience.