Examining the Role of Artificial Intelligence in Influencing Consumer Preferences and Purchase Intentions toward Green Fashion - Kanika Rana; Sonali P. Banerjee; Vaishali Agarwal; Priyanka Chadha (Metallurgical and Materials Engineering, 2025)
The study investigates pivotal function of artificial intelligence (AI) in promoting sustainable fashion practices and influencing customer behavior. The garment business contributes 10% of global carbon emissions and produces substantial textile waste; thus, AI is a vital answer for mitigating environmental impact while preserving profitability. The study examines AI applications in industry (predictive analytics diminishing overproduction by 20-30%), design (virtual sampling minimizing material waste by 80%), and retail (AI-driven recommendations enhancing sustainable purchasing by 35%). The study uses Structural Equation Modeling (PLS-SEM) with information from 212 fashion customers to test a framework based on the Theory of Planned Behavior and the Stimulus-Organism-Response model. The important results show that what consumers know (β=0.482, p=0.045) and their trust (β=0.536, p=0.013) are key factors in their sustainable preferences, along with a very strong link between preference and intention (β=20.139, p<0.001). The measuring model has robust reliability (Cronbach's α > 0.88) and validity (AVE > 0.74); however, motivation displays minimal direct impact (β = 0.031, p = 0.735). The practical consequences underscore the necessity for honest AI communication, tailored sustainability suggestions, and investment in circular design tools. The limitations encompass the cross-sectional methodology and possible cultural disparities in AI adoption. Future studies should investigate longitudinal behavioural effects and do net sustainability evaluations of AI installations.