| Summary: | 碩士 === 國立成功大學 === 製造資訊與系統研究所 === 104 === In today's competitive business environment, The core of the marketing strategy is to understand the consumer profile. In the past, companies have to use the time-consuming questionnaires and statistical analysis in order to understand the consumer profile；But with the development of internet and social media, more and more consumer will leave interaction record, text and other data (ie, Digital Footprint) at the social media website, This also means that companies have a different way to understand the consumer profile more objectively. Thus, how to extract nd analyze the valuable information from the large digital footprints at Internet community media groups for assisting enterprises to develop marketing strategies to enhance the competitive advantage, is an important research topic.
This study develops a method for predicting consumers’ decision‐making styles by mining digital footprints in Facebook to help enterprises quickly and accurately grasp the consumer's decision-making style, thereby reducing marketing costs and improve customer satisfaction. In accordance with the above purposes, the main research tasks include: (i) designing a process of predicting consumers’ decision‐making styles by mining digital footprints in Facebook, (ii) developing the techniques involved in the designed process, and (iii) implementing a mechanism for predicting consumers’ decision‐making styles by mining digital footprints in Facebook.
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