Fintech, or big data analytics, is made possible by developments in financial technology in this day of complex technology. Financial services are being impacted by the emergence of this new Fintech, which is also setting off a new trend in the industry. Generation Z is propelling the fintech revolution with its inclination towards digital financial solutions, adopting technologies such as mobile banking, bitcoin, and peer-to-peer payment applications. Hence, the objective of this study is to identify the factors influencing generation Z’s intention to continue using fintech and to study is there any influence between gender. The Theory of Planned Behaviour combines with Technology Acceptance Model models will be the two pillars on which this study is built. Based on the models this study examines the association between five independent variables which are perceived benefit, perceived risk, perceived ease of use, perceived usefulness and gender. A total of 200 responses were analysed in the survey, and the distribution of the survey instruments was conducted via an online platform. To clarify details and pinpoint trends for the results, this study employed quantitative research techniques. The findings suggest that generation Z’s continuance intention to continue using Fintech is significantly influenced by perceived benefit, perceived ease of use and perceived usefulness. Gender and perceived risk were shown to have no significant relationship. The study provides valuable insights for Fintech developers, policymakers, and academics, emphasizing the importance of focusing on the beneficial and accessible aspects of Fintech platforms to enhance user retention. The limitations of this study are also highlighted, such as the respondents’ regional concentration and the small number of factors examined. To obtain more thorough and generalizable results, further study is advised to employ random sampling approaches and incorporate a wider range of factors.

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Generation Z’s Viewpoint: Key Determinants of Continuance Fintech Adoption

  • Hazlaili Hashim,
  • Neo Wen Xuan,
  • Md Shukor Masuod,
  • Khairol Nizat Lajis,
  • Anushia Chelvarayan

摘要

Fintech, or big data analytics, is made possible by developments in financial technology in this day of complex technology. Financial services are being impacted by the emergence of this new Fintech, which is also setting off a new trend in the industry. Generation Z is propelling the fintech revolution with its inclination towards digital financial solutions, adopting technologies such as mobile banking, bitcoin, and peer-to-peer payment applications. Hence, the objective of this study is to identify the factors influencing generation Z’s intention to continue using fintech and to study is there any influence between gender. The Theory of Planned Behaviour combines with Technology Acceptance Model models will be the two pillars on which this study is built. Based on the models this study examines the association between five independent variables which are perceived benefit, perceived risk, perceived ease of use, perceived usefulness and gender. A total of 200 responses were analysed in the survey, and the distribution of the survey instruments was conducted via an online platform. To clarify details and pinpoint trends for the results, this study employed quantitative research techniques. The findings suggest that generation Z’s continuance intention to continue using Fintech is significantly influenced by perceived benefit, perceived ease of use and perceived usefulness. Gender and perceived risk were shown to have no significant relationship. The study provides valuable insights for Fintech developers, policymakers, and academics, emphasizing the importance of focusing on the beneficial and accessible aspects of Fintech platforms to enhance user retention. The limitations of this study are also highlighted, such as the respondents’ regional concentration and the small number of factors examined. To obtain more thorough and generalizable results, further study is advised to employ random sampling approaches and incorporate a wider range of factors.