A Bayesian Linear Regression Approach to Consumers’ Intention to Purchase Second-Hand Clothing

The fashion industry has gained recognition for its significant impact on society and the environment, particularly in terms of waste generation. Currently, a substantial amount of clothing is discarded due to consumers’ frequent purchases of new items and the disposal of perfectly usable ones. Adopting second-hand clothing (SHC) is recognized as an impactful measure in tackling textile waste and decreasing pollution. As a result, the Bayesian linear regression technique is used in this research to examine the determinants that affect customers’ interest in purchasing SHC. A Google form was used to gather information for the research from 274 customers in Ho Chi Minh City, Vietnam. The findings showed five significant characteristics that substantially affect consumers’ interest in purchasing SHC, with frugality being the most important element. Attitudes toward SHC, environmental awareness, subjective norms, and perceived behavioral control were also shown to be relevant determinants.