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Digital Payment

Shopping Without the Fuss: The Effect of Curation Type in Clothing Subscription Adoption on Cognitive Dissonance and Consumer Responses

By Dr. Angie Lee, Updated on  July 25, 2024

🕙 3-minute read

To address the volatile nature of the retail industry, retailers have adopted clothing subscription services (CSS) to meet the demanding needs of consumers. This study provides insights into consumers’ perceptions and attitudes toward different types of CSS (i.e., non-curated vs. partially curated vs. fully curated). Our experimental study uncovered that consumers with high aesthetic perception experience more cognitive dissonance (i.e., psychological discomfort in a consumer’s mind resulting from contradictory cognitive elements) towards a fully compared to a partially curated CSS, thereby impacting their attitudes toward and intention to purchase CSS. Due to today’s rapidly evolving retail industry, retailers endeavoring to engage in this business model should develop strategies to turn visitors into subscribers and decrease hesitation in novice consumers. Based on the results, we suggested that retailers should ascertain consumers’ level of aesthetic perception as it plays an essential role in CSS adoption.

To read the full article from the Journal of Fashion and Marketing 

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Other iRACE Research Insights

Abstract Background

Dr. Angie Lee is an assistant professor at the department of consumer and design sciences in Auburn University. She aspires to advance discipline knowledge of retailing and consumer behavior to identify and create effective and sustainable business models. Her research focuses on consumer responses to cutting-edge and sustainable retail strategies and triggers and influences of consumer interactions in digital environments. Dr. Lee integrates both micro and macro perspectives in her research, utilizing experimental designs, digital footprints, and big data. Her analytical expertise spans both quantitative and qualitative methods, earning her a research excellence award for her dissertation.

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iRACE Research Areas

Makeup Store

VISUAL MERCHANDISING

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ARTIFICIAL INTELLIGENCE

Analytics

MARKET FORECAST

Website Elements

BRANDING

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AR/ VR/ METAVERSE

Installing Solar Panel

CSR /ESG / DEI

Mobile Payment

DIGITAL RETAILING

Analysing data

DATA SCIENCE

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