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This study aims to concern with Malaysian consumer involvement in fashion clothing. To achieve this, materialism, fashion clothing involvement and religiosity are examined…
This study aims to concern with Malaysian consumer involvement in fashion clothing. To achieve this, materialism, fashion clothing involvement and religiosity are examined as drivers of fashion clothing purchase involvement.
Gender, race and age are explored to have better understanding of fashion clothing purchase involvement in Malaysia. Data were gathered using a Malaysian university student sample, resulting in 281 completed questionnaires.
The results support the study’s model and its hypotheses and indicate that materialism, fashion clothing involvement and religiosity are significant drivers of fashion clothing purchase involvement. Also, materialism is a significant driver of fashion clothing involvement, and fashion clothing involvement mediates the relationship between materialism and fashion clothing purchase involvement. The results also show that Malaysian youth do not possess a high level of materialistic tendencies.
This study offers enormous opportunities for the international apparel marketers to formulate relevant business policies and strategies.
The purpose of this paper is to develop a model for studying the propensity towards indebtedness in Malaysia using behavioural factors.
A self-administered questionnaire was distributed among Malaysians who work in Klang Valley, Kuala Lumpur. The questionnaire contained several demographic variables and four behavioural factors: financial literacy, risk perception, materialism and emotions. A total of 201 completed questionnaires were received and the data were tested using structural equation modelling with partial least squares.
This study found that emotion and materialism are statistically significant for a propensity towards indebtedness, while financial literacy and risk perceptions are insignificant for a propensity towards indebtedness.
The results of this study would be useful in helping design better models for credit offerings and addressing credit problems in the long run.