基于贝叶斯网络模型的服务要素幸福感识别研究

Yuho Suzuki, M. Tsubaki, Taro Isobe
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引用次数: 0

摘要

即使消费者得到同样的服务,他们也可能没有同样的幸福感或满足感。本文利用贝叶斯网络模型将消费者分为几种幸福类型,并确定每种类型的消费者最重视哪些点,从而研究消费者如何体验幸福。此外,本文提出了一种基于贝叶斯网络模型的概率推理方法,推导出哪些服务相关变量对每种类型的幸福感有更高的提高概率,以及根据每种类型影响幸福感体验的变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Identification of Service Elements by Well-being Type Using Bayesian Network Modelling
Even when consumers receive the same services, they may not have the same experiences of well-being or satisfaction. In this paper, we investigate how consumers experience well-being by classifying consumers into several well-being types using Bayesian network model and identifying what kind of points consumers of each type consider importantly. Furthermore, this paper proposes a method for deriving which service-related variables have higher probabilities of enhancing well-being of each type, as well as the variables that affect experiences of wellbeing according to each type using probabilistic reasoning based on a Bayesian network model.
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