Abstract:
The fast fashion industry, characterized by its reliance on rapid consumption cycles, and short-lived garment use, has raised major environmental concerns. This industry generates over 92 million tons of waste and consumes 79 trillion liters of water annually, driven by rising consumer demand for fast fashion. As such, there is a pressing need to transition from the current wasteful fast fashion purchasing behavior to more sustainable behavior. Despite extensive research on sustainable purchasing behavior, there is still a gap in our understanding of the predictors of consumers’ sustainable fast fashion purchasing behavior. To address this gap, our study utilized a survey questionnaire to collect data from a convenience sample of 123 South African consumers. We expanded the theory of planned behavior (TPB) by incorporating sustainability awareness as a background factor in the hypothesized theoretical model. We also investigated the relationships among the TPB constructs (attitude, subjective norm, and perceived behavioral control), sustainability awareness, and sustainable fast fashion purchasing behavior. By employing hierarchical regression within the extended TPB framework, we found that perceived behavioral control mediated the relationship between sustainability awareness and sustainable fast fashion purchasing behavior. Further, perceived behavioral control and its interaction with attitude significantly predicted sustainable fast fashion purchasing behavior, while sustainability awareness significantly predicted perceived behavioral control. Notably, our findings reveal that lower perceived behavioral control is associated with a stronger positive relationship between attitude and sustainable fast fashion purchasing behavior. These findings have important implications for theory and practice, and provide suggestions for future research directions.
Description:
DATA AVAILABILITY :
The data supporting the findings of this study are openly available at the Open Science Framework repository, accessible via the following link: https://osf.io/v9p42. This repository includes all relevant datasets necessary to interpret, replicate, and build upon this research.