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EMAC 2024 Annual


Adoption of Facial Pattern Recognition Applications by Fashion Retailers
(A2024-119716)

Published: May 28, 2024

AUTHORS

Amir Heiman, Hebrew University; Udo Wagner, University of Vienna

ABSTRACT

This study analyzes the adoption of facial pattern recognition technologies within the fashion digital retail sector. This technology utilizes computerized facial pattern recognition to cus-tomize product assortments offered to customers’ socio-demographic, and physical profile that include identification of color of skin, hair and eyes, and weight. In addition to segmen-tation the technology is capable to identify mood states, thereby potentially influencing mood-based unplanned purchases. However, while better product matching - which is based on facial recognition - can reduce the likelihood of returns, the increased probability of un-planned and uncontrolled purchases due to emotional manipulation raises the risk of purchas-ing unneeded products, which in turn affects the quantity of product returns. To address this dynamic, the current study develops a theoretical model to analyze the effects of adopting facial recognition technology on consumer choices and retailer profitability.