To Adopt or Not: The Paradox of AR Fitting Technology in Retail Channels

Fitting rooms in brick-and-mortar stores play a critical role in shaping the consumer experience. Unlike online retailing, the long service times in fitting rooms often lead to congestion in a physical store, which lowers the service satisfaction of consumers. To address this challenge, a growing number of fashion brands are adopting augmented reality (AR) fitting technologies, enabling consumers to virtually try on garments and thus bypass traditional waiting periods. Despite these advancements, AR technologies often fall short of providing an accurate representation of how clothing fits, resulting in potential mismatches between consumer expectations and the actual product. This paper investigates the impact of integrating AR fitting technologies into physical retail stores—an area that remains underexplored in the current literature. We introduce a queueing-game-theoretic model that captures the operational dynamics of AR applications in congestion-prone systems, wherein both the substitution and complementarity effects are considered. Our results are as follows. First, although AR technology serves as a complementary service to traditional fitting rooms, its adoption may lead to a decline in retailer revenue—even when implementation costs are excluded—particularly in markets of intermediate size. Second, for fixed-price clothing (e.g., luxury brands), adopting AR fitting applications can simultaneously enhance both retailer revenue and consumer surplus when the market size is large, leading to a win-win situation. However, for adjustable-price clothing (e.g., fast-fashion brands), adopting AR technology may trigger a higher price, reversing the benefits of AR on the consumers. As a result, a lose-lose situation may be caused by introducing the AR channel: an analog to the Downs-Thomson paradox. Furthermore, we caution that a higher level of AR technology may inadvertently intensify its negative impact. To validate the robustness of our main insights, we further extend our analysis to settings with online AR, retailer competition, and dynamic decision making, among others.

History: Karthik Kannan, Senior Editor; Zhengrui Jiang, Associate Editor.

Funding: Financial support from the National Natural Science Foundation of China [Excellent Young Scientists Fund Grant 72322017, Major Research Plan Grant 92467302, and Key Programme Grant 72132007] is gratefully acknowledged.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2024.1425.