To Adopt or Not: The Paradox of AR Fitting Technology in Retail Channels - Li, Yongjian; Yao, Song; Wang, Zhongbin; Guo, Yanqiong (Information Systems Research, 2026)
As brick-and-mortar retail rebounds, congestion in fitting rooms has reemerged as a critical operational challenge. Augmented reality (AR) fitting applications offer a scalable solution by enabling rapid virtual trials and reducing in-store delays, yet imperfect assessments may increase product mismatches. This study provides actionable guidance for retailers on AR adoption and pricing strategies by clarifying the economic roles of the substitution and complementarity effects. Our findings underscore the importance of a market-contingent approach to AR adoption and system upgrades. Rather than presuming that improvements in accuracy or usability will uniformly enhance performance, retailers and IT managers should rigorously evaluate how technological capabilities interact with market size, price fluctuations, and congestion dynamics. We also inform targeted marketing by demonstrating how heterogeneity in consumer technology preferences shapes channel selection and effective transaction outcomes. More broadly, our results caution policymakers that emerging digital technologies—while intended to reduce friction—may generate unintended welfare losses if mismatch risks and strategic responses are overlooked. These insights provide actionable guidance for digital transformation initiatives in retail and other capacity-constrained service systems characterized by heterogeneous consumers.