Online shopping is becoming increasingly important in the current era, rendering comprehension of consumer online shopping habits crucial. This notion rings true in the context of users and companies alike, thereby emerging as a big concern for e-commerce managers and researchers. One may assume that only by understanding the factors influencing consumer buying intentions for fashion items online will companies be better-positioned for meeting consumer needs. In this analysis, the relationship between customer online purchasing intentions and selected factors was investigated, specifically consumer innovativeness, fashion innovativeness, and fashion involvement. Quantitative research was implemented in the process, involving fashion online shoppers in Malaysia as the respondents after being selected via quota sampling from the ten most popular fashion shopping websites in Malaysia. The statistical method of Partial Least Square – Structural Equation Modelling (PLS-SEM) was then employed for the proposed model testing. The findings subsequently revealed the positive effects of consumer innovativeness, and fashion involvement on online purchase intention, whereas any significant relationship between the variable with fashion innovativeness was absent. However, this analysis was conducted in Malaysia; therefore, the results could be different if tested in other countries. Hence, similar studies related to fashion online purchase intention should be replicated in other Asian countries in the future.

Online shopping is becoming increasingly important in the current era, rendering comprehension of consumer online shopping habits crucial. This notion rings true in the context of users and companies alike, thereby emerging as a big concern for e-commerce managers and researchers. One may assume that only by understanding the factors influencing consumer buying intentions for fashion items online will companies be better-positioned for meeting consumer needs. In this analysis, the relationship between customer online purchasing intentions and selected factors was investigated, specifically consumer innovativeness, fashion innovativeness, and fashion involvement. Quantitative research was implemented in the process, involving fashion online shoppers in Malaysia as the respondents after being selected via quota sampling from the ten most popular fashion shopping websites in Malaysia. The statistical method of Partial Least Square – Structural Equation Modelling (PLS-SEM) was then employed for the proposed model testing. The findings subsequently revealed the positive effects of consumer innovativeness, and fashion involvement on online purchase intention, whereas any significant relationship between the variable with fashion innovativeness was absent. However, this analysis was conducted in Malaysia; therefore, the results could be different if tested in other countries. Hence, similar studies related to fashion online purchase intention should be replicated in other Asian countries in the future.