Researching the Consumer Behavior in Mobile Commerce Using Data Mining

• Main Authors: Yu-Chin Huang, 黃裕欽
• Other Authors: Kun-Huang Haurng
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/56801847943618452591

碩士 === 逢甲大學 === 經營管理碩士在職專班 === 93 === In the competitive operation business world, decision makers need to identify what are useful and valuable for an action. Data mining is a type of machine learning or modeling that formulates consumer characteristics. The results can be applied for forecasting and decision support. This study is devoted to use the data mining technology to analyze the database to discovery important information in mobile commerce consumer behavior. Data are collected from web database. Then, K-means is used method to mine the characteristics of mobile commerce customers. The empirical results reveal that (1) Pricing and Brand Name, (2) Services, (3) Portable Phone Number, and (4) Promotion are the important factors that consumers favor. Therefore, the telecommunication companies can use the empirical results to improve their consumer relationships.