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A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index

Author

Listed:
  • Mingyuan Li

    (School of Business Administration, Guangxi University of Finance and Economics, No. 189, Daxuexi Road, Xixiangtang District, Nanning 530003, China)

  • Kuen-Suan Chen

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 41170, Taiwan
    Department of Business Administration, Chaoyang University of Technology, Taichung 41349, Taiwan
    Institute of Innovation and Circular Economy, Asia University, Taichung 41354, Taiwan)

  • Chun-Min Yu

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 41170, Taiwan)

  • Chun-Ming Yang

    (School of Economics and Management, Dongguan University of Technology, No. 1, Daxue Road, Songshan Lake, Dongguan 523808, China)

Abstract

In order to take into account cost and timeliness and enhance accuracy testing, this study developed the fuzzy number and membership function, using the confidence interval of ratio operating performance index. Subsequently, according to the statistical test rules and the application of the fuzzy number and membership function, a fuzzy evaluation decision model for the operating performance index is proposed, to evaluate if the business performance reaches the needed level. Based on the abovementioned, the evaluation model in this study took into account not only timeliness but also accuracy, so that it could grasp the opportunity of improvement for operating organizations with poor operating performance after being evaluated. This fuzzy evaluation decision model for the operating performance index constructs a fuzzy membership function retrieved from an index’s confidence interval, reducing the chance of miscalculation due to sampling mistakes and improving the efficiency of evaluation. Finally, in order to facilitate the application of readers and the industry, this paper uses cases to explain the proposed fuzzy verification method. On the whole, the model proposed in this paper is a data-based auxiliary tool for the service operating performance improvement strategy.

Suggested Citation

  • Mingyuan Li & Kuen-Suan Chen & Chun-Min Yu & Chun-Ming Yang, 2021. "A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index," Mathematics, MDPI, vol. 9(3), pages 1-12, January.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:3:p:262-:d:488915
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Chun-Ming Yang & Tsun-Hung Huang & Kuen-Suan Chen & Chi-Han Chen & Shiyao Li, 2022. "Fuzzy Quality Evaluation and Analysis Model for Improving the Quality of Unleaded Gasoline to Reduce Air Pollution," Mathematics, MDPI, vol. 10(15), pages 1-13, August.

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