客户满意度的预期不确认模型、理想点模型和卡诺模型:比较

Hui-Hsin Huang
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摘要

本文比较了三种顾客满意度模型:期望不确认模型、理想点模型和卡诺模型。文章描述了三种满意度随机模型的细节。本文使用一家美容店的电子商务数据库作为经验数据,用于参数估计和模型比较。模型校准使用了均方根偏差(RMSD)和卡方检验(Chi-square test)。结果表明,期望不确认模型在 RMSD 指数上的拟合度最高,但在卡方检验中的拟合度最低。相比之下,理想点模型在 RMSD 指数和卡方检验中的结果正好相反。期望模型的参数数量多于其他两个模型,可用于解释愉悦的各种情景要素的弹性变化,但它也需要更多的数据才能保持稳定。然而,理想点模型的结构比其他两个模型简单。只需估计一个参数,因此易于应用。不过,在测量动态满意度时,它的准确性不如其他两个模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expectation Disconfirmation, Ideal Point and Kano Models of Customer Satisfaction: A Comparison
This article compares three customer satisfaction models: expectation disconfirmation, ideal point, and Kano. It depicts the details of the three types of satisfaction stochastic models. A beauty shop's e-commerce database is used as empirical data for parameter estimates and model comparisons. The model calibration uses both root-mean-square deviation (RMSD) and the Chi-square test. The results demonstrate that the expectation disconfirmation model has the maximum fitness in the RMSD index, but the lowest goodness of fit in the Chi-square test. In contrast, the ideal point model produces opposite findings on the RMSD index and the Chi-square test. The expectation model, which has a larger number of parameters than the other two models, can be used for elastic changes to explain varied situational elements of pleasure, but it also requires more data to be stable. However, the ideal point model has a simpler structure than the other two models. There is only one parameter to estimate, which makes it easy to apply. However, it is less accurate than the other two models when measuring dynamic satisfaction.
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