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A Fuzzy Improvement Testing Model of Bank APP Performance

Author

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  • Tian Chen

    (School of Economics and Management, Dongguan University of Technology, Dongguan 523808, China
    School of Management, University of Science and Technology of China, Hefei 230026, China)

  • Ting-Hsin Hsu

    (Department of Finance, National Taichung University of Science and Technology, Taichung 404336, Taiwan)

  • Kuen-Suan Chen

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
    Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan
    Institute of Innovation and Circular Economy, Asia University, Taichung 413305, Taiwan)

  • Chun-Ming Yang

    (School of Economics and Management, Dongguan University of Technology, Dongguan 523808, China)

Abstract

Numerous studies have pointed out that the issue of global warming is getting increasingly more serious. Therefore, the concepts of circular economy (CE) and sharing economy have been more and more valued by enterprises and governments. With the gradual popularization and maturity of the Internet of Things (IoT), various smart APP platforms have sprung up rapidly. For example, the fuzzy evaluation model of bank APP performance was proposed in such an environment, aiming to improve the APP service performance by means of evaluating, analyzing, improving, and enhancing customers’ satisfaction with their use of APPs, and increasing the number of users of APPs. Since the follow-up of the article did not mention the improved testing model used to verify the improvement effect, this paper then proposed a fuzzy two-tailed testing model with two indices before and after the improvement based on the confidence interval to verify whether the improvement has had a significant effect. This complete bank APP fuzzy performance evaluation, analysis, and improvement model measured the bank APP operation performance using customer time intervals, so the data collection time was short. Not only can it meet enterprises’ need for rapid response and grasp the opportunity for improvement to achieve the effect of energy-saving and carbon reduction, but it also can satisfy enterprises’ requirement to pursue fast and accurate decision-making. Furthermore, the fuzzy two-tailed test proposed by this paper was based on the confidence interval, which can reduce the risk of misjudgment caused by sampling error. Plenty of studies have indicated that the designs based on confidence intervals can integrate expert experience and past data so that the accuracy of testing can be maintained in the case of small-sized samples.

Suggested Citation

  • Tian Chen & Ting-Hsin Hsu & Kuen-Suan Chen & Chun-Ming Yang, 2022. "A Fuzzy Improvement Testing Model of Bank APP Performance," Mathematics, MDPI, vol. 10(9), pages 1-10, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:9:p:1409-:d:800095
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    References listed on IDEAS

    as
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