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Combining grey relation analysis and entropy model for evaluating the operational performance: an empirical study

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  • Chia Sun

Abstract

Decision-making on operational performance evaluation is a complex multi-objective problem. Through the combination of grey relation analysis and information entropy, the evaluation results are more objective and reasonable. This paper would introduce entropy into the weighting calculation of the grey relational analysis method for improving the precision. The improved decision model was applied in four notebook computer original design manufacturer companies. The result presented the proposed method is practical and useful. Significantly, the proposed method provides more flexible and objective information in determine the weights vector of the criteria. Also the study result represented that the combined method had certain scientific and rationality. The evaluation model indicates that this method be more reasonable and easier to grasp than other methods. As a result, it is easier to popularize this evaluation method in enterprises. Copyright Springer Science+Business Media Dordrecht 2014

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  • Chia Sun, 2014. "Combining grey relation analysis and entropy model for evaluating the operational performance: an empirical study," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1589-1600, May.
  • Handle: RePEc:spr:qualqt:v:48:y:2014:i:3:p:1589-1600
    DOI: 10.1007/s11135-013-9854-0
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    References listed on IDEAS

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    1. Kumar, Vikas & Taneja, H.C., 2011. "Some characterization results on generalized cumulative residual entropy measure," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1072-1077, August.
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    Cited by:

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    2. Peng Jiang & Yi-Chung Hu & Ghi-Feng Yen & Hang Jiang & Yu-Jing Chiu, 2018. "Using a Novel Grey DANP Model to Identify Interactions between Manufacturing and Logistics Industries in China," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
    3. Che-Wei Chang, 2022. "Supply chain movement risk in the sneaker industry: an empirical study," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1073-1092, June.
    4. Peng Jiang & Yi-Chung Hu & Ghi-Feng Yen, 2017. "Applying Grey Relational Analysis to Find Interactions between Manufacturing and Logistics Industries in Taiwan," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 7(3), pages 1-2.
    5. Pei Yin & Jing Cheng & Miaojuan Peng, 2022. "Analyzing the Passenger Flow of Urban Rail Transit Stations by Using Entropy Weight-Grey Correlation Model: A Case Study of Shanghai in China," Mathematics, MDPI, vol. 10(19), pages 1-23, September.
    6. Bruno Ricca & Massimiliano Ferrara & Salvatore Loprevite, 2023. "Searching for an effective accounting-based score of firm performance: a comparative study between different synthesis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3575-3602, August.
    7. Jinqiu Li & Yuyou Zou & Mingqiu Li, 2022. "Dynamic evaluation of the technological innovation capability of patent‐intensive industries in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 3198-3218, October.

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