Factors Influencing Consumers' Intention to Avoid Fast Fashion: A Comparative Study of Milan and Shanghai

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Authors: Sara Di Lorenzo, Ying Wang, Fengting Li, Qian Jia
Cited by: 1

Abstract

The fast fashion industry contributes significantly to environmental degradation, contributing to primary microplastics entering water bodies through synthetic fiber shedding. Understanding consumer intentions to avoid fast fashion requires examining both psychological and cultural determinants. This study explores the factors of consumers’ behavioral intentions to avoid plastic-based fast fashion garments in Milan, Italy (n=151) and Shanghai, China (n=148). Employing an extended Theory of Reasoned Action (TRA) framework that includes environmental concern and biospheric values as antecedents, we investigated how attitude, subjective norms, environmental concern, and biospheric values influence avoidance intentions. Structural equation modeling revealed that all hypothesized relationships were significant in both cultural contexts, with the model explaining 57.9% of the variance in Milan and 76.8% in Shanghai. Notably, the effect of attitude on behavioral intention was stronger in Shanghai (β=0.598) compared to Milan (β=0.494), while biospheric values more strongly predicted environmental concern in Milan (β=0.433) in contrast to Shanghai (β=0.291). The key innovation of this study lies in its comparison of attitudes toward microplastic effects from fast fashion across cultures, revealing that while universal psychological mechanisms drive sustainable consumption intentions, cultural contexts shape the relative strength of value-based versus attitude-based pathways. These findings suggest that interventions to reduce fast fashion consumption should be culturally tailored, focusing on personal attitudes in collectivistic contexts and value-based environmental education in individualistic settings.

Fields of Study & Subjects

Environmental Sustainability in Business Environmental Education and Sustainability Sensory Analysis and Statistical Methods

Publication details

Journal / source
European Journal of Innovative Studies and Sustainability
Publisher
AMO Publisher
Volume
2
Issue
2
Pages
13–27
Publication date
15 February 2026