學位論文

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    利用約略集合理論預測4G手機消費者偏好
    (2010) 楊雅嵐; YaLan Yang
    At the moment, when mobile phone users are demanding more mobile phone features as well as broader bandwidth, the 4G wireless telecommunication standard is emerging. However, how to define appropriate mobile phone features toward various market segmentations to fulfill customers’ needs and minimize the manufacturing cost has become one of the most important issues for 4G mobile phone manufacturers. Thus, a rule based consumer behavior forecast mechanism will be very helpful for marketers and designers of the mobile phone manufacturers to understand and realize. Moreover, precise prediction rules for consumer behavior being derived by the forecast mechanism can be very useful for marketers and designers to define the features of the next generation mobile phones. Therefore, in the pre-process, we utilized Rough Set Theory (RST) that found decision rules to construct the decision table, and approach to data mining and knowledge discovery based on information flow distribution in a flow graph. The post-process applied the formal concept analysis (FCA) from these suitable rules to explore the attribute relationship and the most important factors affecting the preference of customers for the 4G mobile phone features. An empirical study on Taiwanese mobile phone users will be leveraged for verifying the feasibility of the proposed forecast mechanism. Meanwhile, the proposed consumer behavior forecast mechanism can be leveraged on defining features of other high technology products/services.