ICES: Small: Collaborative Research: Selling to Networked Markets

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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.