Research on the Impact Factors of Consumer' Purchasing Intention Based on Online Reviews: A Big Data Architecture

Jing Li, Yadong Li, Yanliang Zhang
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Abstract

Under the background of the volume of online stores with original brand increasing, the influencing factors of online consumers' purchase intention have been paid more and more attention. This paper collected online reviews for empirical analysis by constructing a big data mining framework based on chameleon clustering algorithm, and obtained hotspots about online reviews. Analytic hierarchy process is used to calculate the weights of factor. The results show that online reviews hotspots have several different degrees of impact on consumers' purchase intention. Among them, product style and material quality have the greatest impact on consumers' purchase intention, while logistics and customer service attitude, as health factors to stimulate consumers' purchase, although they can only maintain existing customers, they cannot increase the sales of product significantly.
基于在线评论的消费者购买意愿影响因素研究:大数据架构
在原创品牌网店数量不断增加的背景下,网络消费者购买意愿的影响因素越来越受到人们的关注。本文通过构建基于变色龙聚类算法的大数据挖掘框架,收集网络评论进行实证分析,获得网络评论热点。采用层次分析法计算各因素的权重。结果表明,网络评论热点对消费者的购买意愿有不同程度的影响。其中,产品款式和材质对消费者购买意愿的影响最大,而物流和客户服务态度作为刺激消费者购买的健康因素,虽然只能维持现有客户,但不能显著增加产品的销量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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