Verification Techniques in FinTech Compared from User Perspectives
| Autor: | Jen Sheng Wang |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Social Science Computer Review. :089443932110583 |
| ISSN: | 1552-8286 0894-4393 |
| DOI: | 10.1177/08944393211058310 |
| Popis: | FinTech, which primarily uses mobile devices and applications as promotional platforms, is on the rise, and verification techniques play an important role. This study aims to compare verification techniques for the development of FinTech. Based on the research goal, this study newly adds the three variables “perceived privacy,” “perceived trust,” and “perceived satisfaction” to extend the traditional technology acceptance model (TAM) as the analysis architecture. Second, this study applies the fuzzy analytic hierarchy process to integrate the nonfuzzy best performance as the novelty hybrid multiple-criteria decision-making (MCDM) approach. According to the above research framework, this study investigates over 400 users for a more complete comparison of verification techniques in FinTech. The outcomes first indicate that perceived usefulness is the most emphasized key objective in comparing verification techniques. It also indicates that personal information leaking should be considered and then strengthens user trust. Additionally, the biometrics verification technique would be more advantageous for evaluating and selecting target users in FinTech industries because of their high criteria scores. The objectives and criteria of this study could suggest strategies and measures to improve verification techniques in FinTech to meet user expectations. |
| Databáze: | OpenAIRE |
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