Loot Box Pricing and Design

41 Pages Posted: 5 Aug 2019

See all articles by Ningyuan Chen

Ningyuan Chen

University of Toronto at Mississauga - Department of Management; University of Toronto - Rotman School of Management

Adam N. Elmachtoub

Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University

Michael Hamilton

University of Pittsburgh - Katz Graduate School of Business

Xiao Lei

Columbia University - Department of Industrial Engineering and Operations Research (IEOR)

Date Written: August 1, 2019

Abstract

In the online video game industry, a significant portion of the revenue generated is from microtransactions, where a small amount of real-world currency is exchanged for virtual items to be used in the game. One popular way to conduct microtransactions is via a loot box, which is a random bundle of virtual items whose contents are not revealed until after purchase. In this work, we consider how to optimally price and design loot boxes from the perspective of a revenue-maximizing video game company. Our paper provides the first formal treatment of loot boxes, with the aim to provide customers, companies, and regulatory bodies with insights into this popular selling strategy.

We consider two types of loot boxes: a traditional one where customers can receive (unwanted) duplicates, and a unique one where customers are guaranteed to never receive duplicates. We show that as the number of virtual items grows large, the unique loot box strategy is asymptotically optimal, while the traditional loot box strategy only garners 36.7% of the optimal revenue. When designing traditional and unique loot boxes, we show it is asymptotically optimal to allocate the items uniformly, even when the item valuation distributions are highly heterogeneous. We also show that when the seller purposely lies about the allocation probabilities, then the revenue may increase significantly and thus strict regulation is needed. Finally, we show that even if the seller allows customers to salvage unwanted items, then the customer surplus can only increase by at most 1.4%.

Keywords: e-commerce, bundling, video games, loot boxes, probabilistic selling

Suggested Citation

Chen, Ningyuan and Elmachtoub, Adam and Hamilton, Michael and Lei, Xiao, Loot Box Pricing and Design (August 1, 2019). Available at SSRN: https://ssrn.com/abstract=3430125 or http://dx.doi.org/10.2139/ssrn.3430125

Ningyuan Chen

University of Toronto at Mississauga - Department of Management ( email )


Canada

University of Toronto - Rotman School of Management ( email )

105 St. George st
Toronto, ON M5S 3E6
Canada

Adam Elmachtoub

Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University ( email )

535F S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

HOME PAGE: http://www.columbia.edu/~ae2516/

Michael Hamilton

University of Pittsburgh - Katz Graduate School of Business ( email )

Pittsburgh, PA
United States

Xiao Lei (Contact Author)

Columbia University - Department of Industrial Engineering and Operations Research (IEOR) ( email )

331 S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

HOME PAGE: http://www.columbia.edu/~xl2625/

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