A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site

• Main Authors: Chih-AnChan, 詹智安
• Other Authors: Sheng-Tun Li
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/qm2qd5

碩士 === 國立成功大學 === 高階管理碩士在職專班(EMBA) === 104 === This study proposes a hybrid model in order to connect customers’ emotional factors and business goals, faciliate enterprises gain specialized knowledge and achivements. The advocate of electronic word-of-mouth (e-WOM) has received considerable attention in business communitiesand far-reaching consequences in emotional for consumers. In addition, more and more companies regconized that the payoff would be huge if they connect with customers’ emotions. Kansei words are the key to describe customers’ demands. This study uses use blog article as the source to extract customer’s emotional factors. Text mining technique, Kansei engineering and Google Analytics solutions are applied to extract Kansei words from blog articles and filter out those articles that could effectively bring network traffic to e-commerce websites. The results of this study are desired to build up a novel application that could help enterprises in their marketing activities.