Marketplace Design

Whether done intentionally or out of habit, many behaviors are repeated. Prior research has demonstrated that past behavior is an excellent predictor of future behavior in contexts as varied as media use, eating and drinking, substance abuse, voting, and travel mode choice, just to name a few. Although no one denies the evidence regarding the prevalence of repeat behavior and the predictive power of past behavior, two issues remain intensely debated

Flow internalization is a prevalent feature of our markets. Broker dealers that internalize flow, defend the practice on the basis that it offers potential price improvement and lowers take fees. This paper studies a mathematical model of limit order book dynamics with and without flow internalization, and derives insights on the effect of the latter on price dynamics and long-run execution costs that are of interest in optimal trade execution and in policy considerations.

We propose and study a market microstructure model of a stochastic and dynamic matching problem. Sellers arrive over time supplying capacity to this market that is characterized by a feature set that includes its price. Sellers are also characterized by their delay tolerance and financial considerations. In turn, buyers arrive over time seeking capacity and are endowed with a choice model that allows them to compare and tradeoff options that differ in their features and price.

The measurement and timing of reported revenue is critical to performance measurement and the development of accurate forecasting models. GM used incentives to get customers to buy its vehicles. This case asks students to consider how GM should report the sales so that the data is a valid indication of performance and can be used to accurately forecast future sales.

We develop a theoretical model to investigate the incentives for coordinating the positioning and pricing of horizontally differentiated products in the context of a vertical trading relationship between a retailer and multiple suppliers. We also use the model to analyze various trading relationships, such as category management, and characterize the channel efficiency of each, leading to interesting insights about when such practices may be most effective.

We consider a pricing problem in an environment where the customers' willingness-to-pay (WtP) distribution may change at some point over the selling horizon. Customers arrive sequentially and make purchase decisions based on a quoted price and their private reservation price. The seller knows the WtP distribution pre- and post-change, but does not know the time at which this change occurs. The performance of a pricing policy is measured in terms of regret: the loss in revenues relative to an oracle that knows the time of change prior to the start of the selling season.

In this paper we conduct an empirical investigation of a large-scale combinatorial auction (CA); the Chilean auction for school meals in which the government procures half a billion dollars worth of meal services every year. Our empirical study is motivated by two fundamental aspects in the designof CAs: (1) which packages should bidders be allowed to bid on; and (2) diversifying the supplier base to promote competition. We use bidding data to uncover important aspects of the firms’ cost structure and their strategic behavior, both of which are not directly observed by the auctioneer.

Bill Grueskin, Ava Seave, and Lucas Graves spent close to a year tracking the reporting of on-site news organizations—some of which were founded over a century ago and others established only in the past year or two—and found in their traffic and audience engagement patterns, allocation of resources, and revenue streams ways to increase the profits of digital journalism.