A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index
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 nu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/3/262 |
| _version_ | 1827597029468012544 |
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| author | Mingyuan Li Kuen-Suan Chen Chun-Min Yu Chun-Ming Yang |
| author_facet | Mingyuan Li Kuen-Suan Chen Chun-Min Yu Chun-Ming Yang |
| author_sort | Mingyuan Li |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T03:22:30Z |
| format | Article |
| id | doaj.art-71ec07a05dad4139906dfc8e07d026ea |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T03:22:30Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-71ec07a05dad4139906dfc8e07d026ea2023-12-03T15:07:14ZengMDPI AGMathematics2227-73902021-01-019326210.3390/math9030262A Fuzzy Evaluation Decision Model for the Ratio Operating Performance IndexMingyuan Li0Kuen-Suan Chen1Chun-Min Yu2Chun-Ming Yang3School of Business Administration, Guangxi University of Finance and Economics, No. 189, Daxuexi Road, Xixiangtang District, Nanning 530003, ChinaDepartment of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 41170, TaiwanDepartment of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 41170, TaiwanSchool of Economics and Management, Dongguan University of Technology, No. 1, Daxue Road, Songshan Lake, Dongguan 523808, ChinaIn 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.https://www.mdpi.com/2227-7390/9/3/262ratio operating performance indexconfidence intervalfuzzy numberexponential distributionfuzzy evaluation decision model |
| spellingShingle | Mingyuan Li Kuen-Suan Chen Chun-Min Yu Chun-Ming Yang A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index Mathematics ratio operating performance index confidence interval fuzzy number exponential distribution fuzzy evaluation decision model |
| title | A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index |
| title_full | A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index |
| title_fullStr | A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index |
| title_full_unstemmed | A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index |
| title_short | A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index |
| title_sort | fuzzy evaluation decision model for the ratio operating performance index |
| topic | ratio operating performance index confidence interval fuzzy number exponential distribution fuzzy evaluation decision model |
| url | https://www.mdpi.com/2227-7390/9/3/262 |
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