A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site
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 attentio...
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ndltd-TW-104NCKU54570242019-05-15T22:53:51Z http://ndltd.ncl.edu.tw/handle/qm2qd5 A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site 數位口碑與感性知識萃取法於精準行銷應用之研究─以烘培業電子商務網站為例 Chih-AnChan 詹智安 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. Sheng-Tun Li 李昇暾 2016 學位論文 ; thesis 63 zh-TW |
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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.
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Sheng-Tun Li |
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Sheng-Tun Li Chih-AnChan 詹智安 |
author |
Chih-AnChan 詹智安 |
spellingShingle |
Chih-AnChan 詹智安 A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site |
author_sort |
Chih-AnChan |
title |
A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site |
title_short |
A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site |
title_full |
A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site |
title_fullStr |
A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site |
title_full_unstemmed |
A Hybrid Model of e-WOM and Kansei Engineering in Precision Marketing - A Case of Bakery E-commerce Web Site |
title_sort |
hybrid model of e-wom and kansei engineering in precision marketing - a case of bakery e-commerce web site |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/qm2qd5 |
work_keys_str_mv |
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