Most research on exercise is dominated in the West and is seldom featured in the marketing literature. Efforts in examining the demographic differences with respect to social cognitive factors contained in the Theory of Planned Behavior (TPB) have been largely neglected. This paper aims to examine the relationship between gender, age, education level and the TPB sub-components of attitude, subjective norm, and perceived behavioral control. Conducted in Malaysia, this study employs a cross-sectional survey administered to a quota sample of 512 general adults. A fit measurement model with adequate evidence of convergent and discriminant validity is established using confirmatory factor analysis. Overall, the results show that gender, age, and education do exert a certain level of influence on the social cognitive factors and the subjects' exercise behavior. The application of socio-cognitive approach to examine the exercise behavior yielded contributions in terms of theory, methodology, and practice.

Most research on exercise is dominated in the West. Drawing on a socio-cognitive theory, this research aims at addressing methodological issues in an Eastern culture where recent developments of the theory of planned behaviour (TPB) applications have been limited. To answer the call for reinterpretation of the TPB measurement, we propose and test a more complex factor structure of TPB predictors. Cross-sectional data was collected from a quota sample of 512 adults in Malaysia. This study provides an empirical validation that the multidimensional, first-order model has achieved measurement validity and possesses better fit compared to the global, second-order TPB structure. Our investigation of the specific effects of social cognitive components on exercise intention and behaviour also improves the understanding of this theoretical relationship.

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.

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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.