文章基本信息

标题：The probability factor influences the level of financial well-being of workers in Malaysia
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作者：Zaimah R.
期刊名称：Geografia : Malaysian Journal of Society and Space
电子版ISSN：2180-2491
出版年度：2019
卷号：15
期号：3
语种：English
出版社：Universiti Kebangsaan Malaysia
摘要：Generally, the dual-income family households earn higher income than the single-income family households as both husband and wife are working and earning money for the family. Dual-income households should have more advantages in terms of better level of financial well-being in comparison to single-income households. The workers in dual-income family are also expected to have a better level of financial well-being. Therefore, this study aims to determine the probability factors affecting the workers’ level of financial well-being. The sample of the study was married workers in the public sector, with focus on workers who are in a dual-income family. The analysis unit in this study is the individual. A total of 415 married workers were analyzed in this study. Multinomial logistic regression analysis was applied in identifying the probability factors of various levels of financial well-being (low, moderate, high) which includes socioeconomic background, financial knowledge, financial behavior and financial decision making factors. The logistic regression analysis showed the socioeconomic background (age, monthly income, home ownership and financial product ownership), financial behavior and financial decision making of the husband have a significant relationship with the respondents’ various levels of financial well-being. Factors such as age, monthly income, home ownership, financial product ownership and financial behavior were found to have an impact on financial well-being. Financial education needs to be implemented in the workplace to encourage workers to have good financial practices. This is necessary in order to ensure the financial well-being of their workers.
关键词：behavior;decision making;dual-income families;financial well-being;knowledge;married workers