Exploring Determinants of Consumer Motivations for Secondhand Fashion, Using Yelp Data Analysis
Abstract
The global secondhand fashion market has grown rapidly, becoming a significant economic sector. This study aims to identify the key factors driving consumer motivations toward secondhand fashion and how retailers can attract more customers. Utilizing Yelp reviews for 32 secondhand fashion stores in New York City, the study employs Latent Dirichlet Allocation for topic modeling and multiple regression analysis to explore these motivations. Four main themes emerged: "Location," "Product Value," "Safety," and "Exclusive Environment." The regression analysis showed a strong relationship between "Product Value" and consumer ratings, highlighting the importance of economic and fashion motivations. However, factors like "Location," "Safety," and "Exclusive Environment" were found to have insignificant impacts on ratings. These findings highlight the importance of product value in attracting consumers and offer practical insights into retail management. Further research is needed to examine broader motivations.
Keywords: Consumer motivations, secondhand fashion, Yelp data analysis, Latent Dirichlet Allocation
How to Cite:
Choi, K., (2025) “Exploring Determinants of Consumer Motivations for Secondhand Fashion, Using Yelp Data Analysis”, International Textile and Apparel Association Annual Conference Proceedings 81(1). doi: https://doi.org/10.31274/itaa.18900
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