Effect of gender as a moderating variable on financial vulnerability using hierarchical regressions: Survey evidence from Indonesian traditional market traders

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Market traders have a significant contribution to GDP in Indonesia; however, their level of education is still low. This leads to a high level of financial vulnerability, so it is important to study this issue, and there is still not enough research on financial vulnerability. Market traders are considered to be more vulnerable to fraud and poor financial management, and this is more common among female traders who have a relatively high level of consumption and economic dependence on men. This study aims to determine the effect of financial behavior and digital financial literacy on financial vulnerability. In addition, the gender interaction between the two relationships was also tested to better understand whether gender weakens or strengthens the relationship. Using a survey method on 278 market traders in Indonesia and hierarchical regression analysis, the results show that digital financial literacy and financial behavior have a negative significant influence on financial vulnerability of market traders. This means that low digital financial literacy and poor financial behavior lead to high financial vulnerability of market traders. In addition, the results of the interaction test show that the negative effect of financial vulnerability is greater for men than women. This is because men usually provide for their families, so they will always try to improve their financial performance and productivity. An important implication of this study is to provide recommendations to the government and associations to further improve the digital literacy skills of market traders, especially female traders through training or mentoring.

Acknowledgment
This research was funded by the Directorate of Research, Technology and Community Service (DRTPM) of the Indonesian Ministry of Education and Culture in 2022 with the National Competitive Basic Research Grant scheme.

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    • Figure 1. Research model
    • Table 1. Demographic data
    • Table 2. Descriptive statistics
    • Table 3. Hypothesis testing result
    • Conceptualization
      Dody Hapsoro, Atika Jauharia Hatta, Muhammad Sabandi
    • Funding acquisition
      Dody Hapsoro
    • Investigation
      Dody Hapsoro, Julianto Agung Saputro, Cahyo Indraswono
    • Methodology
      Dody Hapsoro, Atika Jauharia Hatta, Muhammad Sabandi
    • Resources
      Dody Hapsoro, Atika Jauharia Hatta
    • Supervision
      Dody Hapsoro
    • Validation
      Dody Hapsoro, Julianto Agung Saputro, Cahyo Indraswono, Atika Jauharia Hatta, Muhammad Sabandi
    • Writing – original draft
      Dody Hapsoro, Atika Jauharia Hatta, Muhammad Sabandi
    • Data curation
      Julianto Agung Saputro, Cahyo Indraswono
    • Formal Analysis
      Julianto Agung Saputro, Cahyo Indraswono, Atika Jauharia Hatta
    • Project administration
      Julianto Agung Saputro, Cahyo Indraswono
    • Software
      Julianto Agung Saputro, Cahyo Indraswono, Atika Jauharia Hatta
    • Visualization
      Julianto Agung Saputro, Cahyo Indraswono
    • Writing – review & editing
      Atika Jauharia Hatta, Muhammad Sabandi