Loot Box Pricing and Design

49 Pages Posted: 5 Aug 2019 Last revised: 7 Apr 2021

See all articles by Ningyuan Chen

Ningyuan Chen

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

HKU Business School, The University of Hong Kong

Date Written: August 1, 2019

Abstract

In the online video game industry, a significant portion of the revenue is generated 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 allocation 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, and analyze customer surplus under such selling strategies. 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 box strategy is asymptotically optimal among all possible strategies, while the traditional box strategy only garners 36.7% of the optimal revenue. On the other hand, the unique box strategy leaves almost zero customer surplus, while the traditional box strategy leaves positive surplus. Further, 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 heterogeneous. We also show that when the seller purposely misrepresents the allocation probabilities, their 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 - Rotman School of Management ( email )

Adam Elmachtoub

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

535G 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)

HKU Business School, The University of Hong Kong ( email )

Hong Kong
China

HOME PAGE: http://www.xiao-lei.org

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