Electronic payment system use: a mediator and a predictor of financial satisfaction

  • Received May 25, 2020;
    Accepted September 18, 2020;
    Published September 28, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.17(3).2020.19
  • Article Info
    Volume 17 2020, Issue #3, pp. 246-262
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This work is licensed under a Creative Commons Attribution 4.0 International License

This study investigates the direct and indirect effects of financial capability, financial advice, financial anxiety, and the use of an electronic payment system (EPS) on financial satisfaction. In the current era of digitalization and financial innovations, it seems quite unlikely that an individual remains unaffected by its use. The research was conducted in northern India on individual level using a partial least square structural equation modeling statistical technique to analyze responses collected from a close-ended questionnaire using a 5-point Likert scale. The results show that financial capability, financial advice, financial anxiety, and EPS usage have a direct positive effect on an individual’s financial satisfaction. EPS usage plays a significant mediating role, as all the financial constructs depict a positive effect on financial satisfaction via EPS use. These findings contribute to the literature by offering an understanding of the determinants of financial satisfaction in the context of a low-income developing country, as well as the vital role of using EPS in an individual’s financial satisfaction in today’s digitally driven era. The results of this study could be a useful factor for policymakers and digital service providers for implementation and control.

Acknowledgement
“This paper was supported by Internal Grant Agency of FaME TBU No. IGA/FaME/2019/002”

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    • Figure 1. Proposed framework
    • Figure 2. SEM analysis
    • Table 1. Sample profile
    • Table 2. Measurement model
    • Table 3. Construct reliability and validity
    • Table 4. Discriminant analysis with the Heterotrait-Monotrait (HTMT) ratio and correlation matrices
    • Table 5. Path coefficient
    • Table 6. Variations of the dependent variable explained by independent variables
    • Table A1. Sample questionnaire
    • Table A2. Questions
    • Conceptualization
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Data curation
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Investigation
      Khurram Ajaz Khan
    • Methodology
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Software
      Khurram Ajaz Khan
    • Validation
      Khurram Ajaz Khan
    • Visualization
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Writing – original draft
      Khurram Ajaz Khan
    • Writing – review & editing
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Formal Analysis
      Mohammed Anam Akhtar
    • Resources
      Mohammed Anam Akhtar
    • Supervision
      Mohammed Anam Akhtar