Abstract
The erosion of high-end fashion brands by fast-fashion copycats (e.g., Zara, H&M) has stirred controversies and unceasing legal attempts to copyright fashion designs. Despite the purported negative impact of copycats, the effect of fashion copycats on high-end brands remains empirically unclear. Research on this topic has been impeded by the absence of a modeling framework to quantify fashion and by the lack of consumer-level data on fashion choices. The authors collect data on the posting behaviors of consumers on a fashion-specific social media platform and develop a dynamic structural model with deep learning image analytics to characterize consumers’ choices of brands and styles. Results suggest that fast-fashion copycats can both harm high-end brands (a cannibalization effect) and help them (a market expansion effect). The authors also identify both static and dynamic mechanisms that contribute to the market expansion effect: The affordability of mixing copycats with high-end brands boosts the number of high-end items featured in posts by financially constrained consumers (a static mechanism). In addition, good styles from copycats enable users to build their popularity on social media over time, which may increase the users' valuation of high-end brands and reduce the users' future costs via sponsorship opportunities (dynamic mechanisms). The results could inform policy makers about the potential consequences of prohibiting fashion copycats.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.