Application of Multiple Linear Regression on Factors Affecting the Acceptance of Financial Technology Among UiTM Students

Abstract

Financial technology, also referred to as "FinTech," is a term used to describe emerging technology that aims to enhance and automate the provision of financial services. In this research, the focus was on cryptocurrencies, non-fungible tokens (NFT), and metaverses that are considered part of the fintech industry, as they all involve technology to facilitate financial transactions and interactions. The insufficiency of quantitative academic literature on the factor influencing students’ acceptance of financial technologies resulting to have uncertainty on the local degree student’s attitudes and perceptions towards these emerging technologies. The purpose of this study was to identify the factors influencing the acceptance of financial technologies. A stratified sampling technique was utilized and 329 respondents were selected. This study used primary data which is by distributing the questionnaire in Google Form and the link was sent out via WhatsApp to collect the data. The independent t- test, one way ANOVA and multiple linear regression were applied in this study. The result of T-test indicates that the male students had higher mean value than female students in accepting the financial technology. Meanwhile, based on ANOVA, there was a significant mean difference in fintech acceptance between programmes. Hence, by using multiple linear regression, the significant factors influencing the acceptance of financial technologies were knowledge, openness, and social influences. It is recommended that future researchers study other areas of Fintech, like blockchain, to gain a better understanding of Fintech as a whole.