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Ranking Hotels Based on Online Hotel Attribute Ratings Using Neutrosophic AHP and Stochastic Dominance

机译:使用中智AHP和随机优势基于在线酒店属性评级对酒店进行排名

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Electronic word-of-mouth (EWOM) is playing an important part in the consumer's purchasing decision making across various shopping platforms. This is especially true in service sector, where the feedbacks covering the guest experience influence the adoption intention of potential consumers. The online ratings of various service aspects of the hotels posted by earlier users provide a comprehensive evaluation of their opinions and assessments on a standardized scale. In order to maximize utility, customers look for various candidate alternatives as well as the online ratings corresponding to it. This requires making a mathematical justification for precise decision making. Moreover, purchasing decisions incorporate hesitation among customers. To take care of these problems, this paper proposes a model applying multi criteria decision making (MCDM) techniques with online ratings of hotel. The objective of the paper is to rank hotels on the basis of online ratings of their attributes available on Tri-padvisor. Firstly, the priorities of the service attributes, in the form of weights, are obtained using Neutrosophic Analytic Hierarchy Process (NAHP). The Neutrosophic set are an extension of fuzzy concept and has the advantage of handling hesitation in decision making process. We apply stochastic dominance along with the preference weights on the available ratings to obtain a comparison matrix of alternative. Finally, we make use of PROMETHEE technique to get the overall ranking of hotels. Future studies may include the role of online review text in the present model.
机译:电子口碑(EWOM)在各种购物平台上的消费者购买决策中起着重要作用。在服务行业尤其如此,在该行业中,涉及来宾体验的反馈会影响潜在消费者的采用意图。较早的用户发布的酒店各个服务方面的在线评分以标准化的规模对他们的意见和评估进行了全面评估。为了最大程度地发挥效用,客户会寻找各种备选方案以及与其对应的在线评分。这就需要进行数学上的辩解,以便做出精确的决策。此外,购买决策会引起客户的犹豫。为了解决这些问题,本文提出了一种应用多准则决策(MCDM)技术和酒店在线评级的模型。本文的目的是根据Tri-padvisor上可用属性的在线评分对酒店进行排名。首先,使用中智分析层次过程(NAHP)获得权重形式的服务属性的优先级。中智集是模糊概念的扩展,具有在决策过程中处理犹豫的优点。我们将随机优势和偏好权重应用于可用评级,以获得替代方案的比较矩阵。最后,我们利用PROMETHEE技术获得酒店的整体排名。未来的研究可能包括在线评论文本在当前模型中的作用。

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