Problem Definition: Two increasingly popular disciplines applied in operations management are (a) machine learning, such as deep learning techniques (“ML”), and (b) behavioral science, notably human-subject experiments and behavioral modeling (“BSci”). Despite the overlap in how they are...

Behavioral inventory-management research leverages ideas and methodologies commonly used in behavioral economics and psychology to advance our understanding of the role of human behavior in inventory management. In this chapter, we first review some of the early papers in this area organized by...

When bidders incur a cost to learn their valuations, bidder entry can impact auction performance. Two common selling mechanisms in this environment are an English auction, and a sequential bidding process. Bulow and Klemperer (2009) show, theoretically, that sellers should prefer the auction,...

Game theoretic models require strong informational assumptions that may not hold in operations applications. In such settings, how do uninformed players behave? We take a first step towards addressing this question by conducting a controlled human subject experiment. We focus on a simple...

We investigate how auctioneers set reserve prices in auctions. A well-established theoretical result, assuming risk neutrality of the seller, is that the optimal reserve price should not depend on the number of participating bidders. In a set of controlled laboratory experiments, we find that...

In this paper, we study a conditional upgrade strategy that has recently emerged in the travel industry. After a consumer makes a reservation for a product (e.g., a hotel room), she is asked whether she would like to upgrade her product to a higher-quality (more expensive) one at a discounted...