Crowdsourcing Exploration

Motivated by the proliferation of online platforms that collect and disseminate consumers' experiences with alternative substitutable products/services, we investigate the problem of optimal information provision when the goal is to maximize aggregate consumer surplus. We develop a decentralized multi-armed bandit framework where a forward-looking principal (the platform designer) commits upfront to a policy that dynamically discloses information regarding the history of outcomes to a series of short-lived rational agents (the consumers). We demonstrate that consumer surplus is non-monotone in the accuracy of the designer's information-provision policy. Because consumers are constantly in "exploitation" mode, policies that disclose accurate information on past outcomes suffer from inadequate "exploration." We illustrate how the designer can (partially) alleviate this inefficiency by employing a policy that strategically obfuscates the information in the platform's possession -- interestingly, such a policy is beneficial despite the fact that consumers are aware of both the designer's objective and the precise way by which information is being disclosed to them. More generally, we show that the optimal information-provision policy can be obtained as the solution of a large-scale linear program. Noting that such a solution is typically intractable, we use our structural findings to design an intuitive heuristic that underscores the value of information obfuscation in decentralized learning. We further highlight that obfuscation remains beneficial even if the designer can directly incentivize consumers to explore through monetary payments

Cournot competition in networked markets

The paper considers a model of competition among firms that produce a homogeneous good in a networked environment. A bipartite graph determines which subset of markets a firm can supply to. Firms compete a la Cournot and decide how to allocate their production output to the markets they are directly connected to. We assume that markets have inverse linear demand and firms have quadratic production costs. First, we show that the resulting Cournot game has a unique equilibrium for any given network and provide a characterization of the production quantities at equilibrium. Our results identify a close connection between the equilibrium outcome and supply paths in the underlying network structure. In particular, we show that whether two firms see their output in different markets as strategic substitutes or complements depends critically on the paths between those markets in the line graph induced by the original bipartite network. Armed with a characterization of the equilibrium supply decisions, we explore the effect of changes in the network structure on firms' profits and consumer welfare. First, we study the question of a firm entering a new market. We show that entry may not be beneficial for either the firm or the consumers as such a move affects the entire vector of production quantities. The firm might face a more aggressive competition in its original markets due to its entry to a new market. Moreover, the effect on other firms and consumers also depends on their location in the network. This is in stark contrast with standard results in Cournot oligopoly where entry implies more competition in the market and thus higher consumer welfare. Similarly, the effect of a merger between two firms on profits and overall welfare largely depends on the structure of competition in the original Cournot market. In particular, we show that insights from analyzing mergers in a single market do not carry over in a networked environment. Market concentration indices are insufficient to correctly account for the network effect of a merger and one should not restrict attention to the set of markets that the firms participating in the merger supply to. Finally, we study the operations of a cartel including the entire set of firms. We show that the cartel maximizes its profits by appropriately segmenting the markets among its members so that a firm supplies solely to the ones allocated to it, and we provide an algorithm that computes the optimal production quantities for each firm in the cartel. © 2014 Authors

Innovation and Crowdsourcing Contests

In an innovation contest, an organizer seeks solutions to an innovation-related problem from a group of independent agents. Agents, who can be heterogeneous in their ability levels, exert efforts to improve their solutions, and their solution qualities are uncertain due to the innovation and evaluation processes. In this chapter, we present a general model framework that captures main features of a contest, and encompasses several existing models in the literature. Using this framework, we analyze two important decisions of the organizer: a set of awards that will be distributed to agents and whether to restrict entry to a contest or to run an open contest. We provide a taxonomy of contest literature, and discuss past and current research on innovation contests as well as a set of exciting future research directions