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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/113058
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/113058

    Title: Innovative chance discovery for finding innovative useful idea in travelling
    Authors: 林木花
    Lin, Mu Hua
    Hong, Chao Fu
    Lin, Woo Tsong
    Contributors: 資管系
    Keywords: Commerce;Decision making;Students;Blue Ocean Strategy;Boston consulting groups;Classification models;Cluster frequencies;Innovative value;Lead users;Multiobjective decision;Transformation functions;Decision theory
    Date: 2017-01
    Issue Date: 2017-09-15 16:10:20 (UTC+8)
    Abstract: If the following enterprises want to enter the blue ocean strategy market with high profits, they need to find the value for new products earlier and take up a position in the new markets. In order to survive for a longer time, enterprises have to find the rare and valuable information at the early stage. To achieve this purpose, the researchers proposed a BCG-based novel innovation classification model. We use KeyGraph algorithms to find the rare keyvalue and the inverse cluster frequency algorithm proposed by this study to conduct two-objective decision analysis. Then, we use the Boston consulting group model to classify keyvalue and inverse cluster frequency's value in which we get the early innovative value. Finally, we used the innovative value to test college freshmen to see the difference between before and after the college freshmen accepted the innovative value. The results show that 59% of the college freshmen perceive the usefulness of the new product, which demonstrates a significant progress. This is to justify that the model proposed by this study can be of help to mine the rare and valuable information early and effectively.
    Relation: International Journal of Intelligent Information and Database Systems, 9(3/4), 269-288
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1504/IJIIDS.2016.081601
    DOI: 10.1504/IJIIDS.2016.081601
    Appears in Collections:[資訊管理學系] 期刊論文

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