Continuous intention to use e-wallets in Indonesia: The impact of e-wallets features

  • Received September 30, 2022;
    Accepted October 31, 2022;
    Published November 10, 2022
  • Author(s)
  • DOI
  • Article Info
    Volume 18 2022, Issue #4, pp. 74-85
  • Cited by
    3 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

Increased use of e-wallets in Indonesia has resulted in high competition among providers. Hence, companies must act to retain customers and impose continuous utilization of their services. This study aimed to investigate the determinants of continuous intention to use the preferred e-wallet in Indonesia. The framework was drawn from the technology continuance theory (TCT) with modifications to fit the e-wallet settings. This study assessed the effect of e-wallet features on continuous intention to use, with attitudes and satisfaction as intervening factors. Data were collected from the general population in Indonesia who uses e-wallets and possesses at least two accounts on different platforms. A total of 948 samples were generated using a web-based self-administrated survey. The data were analyzed using AMOS-SEM by assessing construct validity and reliability, as well as measurement and structural models. The analysis confirms the effect of attitudes and satisfaction on continuous intention. The findings also highlighted the positive impact of service compatibility and merchant networks on attitudes and satisfaction and the positive impact of perceived security toward satisfaction. Unexpected results revealed a strong and direct impact of value of reward programs and merchant networks toward continuance intentions. This study concludes that the modifications of TCT into the e-wallet settings can predict users’ post-adoption behavior.

This study is fully funded by the Directorate General of Higher Education of Indonesia with grant number 104/E4.1/AK.04.PT/2021; LPPM: T/37/UN.16.17/PT.01.03/PD UPT- Soshum/2021.

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    • Figure 1. Research framework
    • Figure 2. Final structural model
    • Table 1. Respondents’ profiles
    • Table 2. CFA and structural model fit
    • Table 3. Quality construct and correlation
    • Table 4. Hypotheses testing
    • Table A1. Items and factor loading
    • Conceptualization
      Arief Prima Johan, Niki Lukviarman, Rahmat Eka Putra
    • Formal Analysis
      Arief Prima Johan, Rahmat Eka Putra
    • Methodology
      Arief Prima Johan, Niki Lukviarman
    • Funding acquisition
      Arief Prima Johan, Niki Lukviarman
    • Project administration
      Arief Prima Johan
    • Writing – original draft
      Arief Prima Johan, Rahmat Eka Putra
    • Writing – review & editing
      Arief Prima Johan, Niki Lukviarman
    • Supervision
      Niki Lukviarman
    • Data curation
      Rahmat Eka Putra