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Factors Clustering Analysis of Influencing Thai Consumers to Buy China's Products Online

机译:影响泰国消费者在线购买中国产品的聚类分析

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Background: In the rapid development of cross-border e-commerce nowadays, it is of great significance to study and analyze the influencing factors of consumer online shopping. At present, China and Thailand have a strong trade momentum, governments and enterprises of both countries are eager to find the influence factors of consumers online shopping in Thailand, in order to promote the overseas market smoothly; Methods: Data was obtained by collecting survey questionnaires from a sample of 286 online consumers in Thailand, and was analyzed with SPSS and cluster these consumers with the K-means and SOM; Results: K-means clearly divides consumers into two categories that pay attention to product promotion price and product quality and aesthetics. The three people clusters obtained by SOM algorithm clustering pay more attention to shopping time cost, product evaluation and price; Conclusions: From the perspective of consumer diversity and market segmentation, the three clusters clustered by SOM algorithm may be closer to the real situation, and also enable enterprises to target consumers of each cluster from the perspective of consumer characteristics, so as to develop marketing strategies more effectively.
机译:背景:在现在跨境电子商务的快速发展中,研究和分析消费者网上购物的影响因素是具有重要意义。目前,中国和泰国有强劲的贸易势头,两国各国政府和企业都渴望找到泰国消费者网上购物的影响因素,以便顺利促进海外市场;方法:通过从泰国的286个在线消费者的样本中收集调查问卷来获得数据,并用SPSS分析并将这些消费者与K-means和Som进行分析;结果:K-mease明确地将消费者分为两类,注重产品促销价格和产品质量和美学。通过SOM算法获得的三个人群群集,更多地关注购物时间成本,产品评估和价格;结论:从消费者多样性和市场分割的角度来看,SOM算法集群聚集的三个集群可能更接近真实情况,并且还使企业从消费者特征的角度来实现每个集群的消费者,从而开发营销策略更有效地。

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