针对目前缺乏对Kano模型质量要素的分类结果进行动态预测研究的问题,结合灰色系统理论在处理不规则数据方面的优势,提出基于GM(1,1)模型的Kano质量要素分类动态预测方法。针对传统Kano模型分类结果过于主观的缺点,设计模糊Kano模型实现质量要素的客观化分类;结合GM(1,1)模型能处理少数据、贫信息,具有高预测精度的优点,利用GM(1,1)模型研究Kano质量要素分类动态预测问题;最后通过在快递业的实证验证模型的可行性和有效性。
According to the lack of study on the dynamic of quality elements classification results of Kano model, a dynamic prediction method based on GM(1,1) model is proposed in this paper, combining with grey system theory's advantage in coping with irregular data. A fuzzy Kano model is designed to realize its objective classification, due to the deficiency of traditional Kano model's subjective classification. GM(1,1) is used to study the dynamic of quality elements classification of Kano model, combining with its advantage in coping with less data, poor information, high prediction accuracy. Its feasibility and validity will be tested by an empirical research in an express industry.
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