Harnessing financial advice and literacy for financial well-being in the digital age

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Under complex financial circumstances, individuals are empowered to improve financial decision-making by trusting financial advice and utilizing digital technology and resources. Though the extant research has explored numerous factors impacting financial well-being, the specific influence of financial advice and digital financial literacy remains underexamined in the Indian context. Thus, grounded on Social Cognitive theory, this study aimed to examine how insights gained from financial advice and digital financial literacy integrate into individual’s decision-making and, subsequently, influence their financial well-being. The data were collected using purposive sampling from Southern India, with 508 respondents recruited using social media platforms. The research hypotheses were empirically validated through hierarchical regression and mediation analysis using the Hayes Process Macro. The study’s findings reveal that financial advice positively predicted financial decision-making (β = 0.667; p < .000). Similarly, digital financial literacy has a positive impact on financial decision-making (β = 0.369; p < .000). Additionally, financial decision-making (β = 0.105; p < .065) positively predicted financial wellbeing. Thus, both factors emerged as transformative predictors of an individual’s financial well-being. Moreover, the findings reveal the mediating role of financial decision-making between financial advice, digital financial literacy, and financial well-being. Therefore, the study underscores that by leveraging the cumulative effect of professional financial advice and digital technologies, policymakers and government regulatory bodies can augment the critical ability of informed decision-making. Thus, these factors could navigate overcoming individual financial challenges and benefit the overall well-being of a diverse population.

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    • Figure 1. Conceptual framework of the study
    • Table 1. Mean statistics of the scale
    • Table 2. Descriptive statistics
    • Table 3. Validity and reliability of the item
    • Table 4. Regression results
    • Table 5. Hierarchical regression result
    • Table 6. Mediation analysis results
    • Conceptualization
      Anju Gupta, Abhilash Abhilash
    • Data curation
      Anju Gupta, Abhilash Abhilash
    • Formal Analysis
      Anju Gupta, Shekhar Mishra, Abhilash Abhilash
    • Investigation
      Anju Gupta, Shekhar Mishra, Abhilash Abhilash
    • Methodology
      Anju Gupta, Abhilash Abhilash
    • Resources
      Anju Gupta, Shekhar Mishra, Deepak Kumar Behera, Abhilash Abhilash
    • Validation
      Anju Gupta, Shekhar Mishra, Deepak Kumar Behera, Abhilash Abhilash
    • Visualization
      Anju Gupta
    • Writing – original draft
      Anju Gupta, Abhilash Abhilash
    • Writing – review & editing
      Anju Gupta, Shekhar Mishra, Abhilash Abhilash
    • Funding acquisition
      Shekhar Mishra, Deepak Kumar Behera, Abhilash Abhilash
    • Project administration
      Shekhar Mishra
    • Supervision
      Shekhar Mishra, Deepak Kumar Behera