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The determinants of willingness to continuously use financial technology among university students: Dataset from a private university in Indonesia.


ABSTRACT: The dataset examines the two perceived benefit and risk factors that continuously influence university students' willingness to use financial technology (Fintech). A non-probability sampling technique was employed to target the study participants. A total of 436 students from a private university in Jakarta, Indonesia, completed a self-administered online questionnaire. The collected quantitative data were screened and analyzed using Partial Least Square Structural Equation Modeling (PLS-SEM). The quantitative analysis result revealed that students' willingness to utilize Fintech continuously is associated with their perceived benefits from such Fintech use. Particularly, students perceived that the benefits of seamless transactions offered by the technology had been the most critical factors that promoted their strong willingness. The data provides new insight related to the university students' use of Fintech for their economic and financial activities. The dataset is also significant for financial technology companies to target and attract more users, particularly from those university students. More importantly, the dataset will be useful for university program development to prepare their students with financial literacy.

SUBMITTER: Sumardi 

PROVIDER: S-EPMC9404273 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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The determinants of willingness to continuously use financial technology among university students: Dataset from a private university in Indonesia.

Sumardi   Azizah Ummu Salma Al USA   Mulyono Herri H   Suryana Anisa Maulita AM  

Data in brief 20220807


The dataset examines the two perceived benefit and risk factors that continuously influence university students' willingness to use financial technology (Fintech). A non-probability sampling technique was employed to target the study participants. A total of 436 students from a private university in Jakarta, Indonesia, completed a self-administered online questionnaire. The collected quantitative data were screened and analyzed using Partial Least Square Structural Equation Modeling (PLS-SEM). T  ...[more]

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