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    政大機構典藏 > 商學院 > 資訊管理學系 > 會議論文 >  Item 140.119/75980
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/75980


    Title: Discover the used innovativeness of the early adopters
    Authors: Hong, C.-F.;Huang, C.-J.;Chiu, T.-F.;Yang, Hsiao-Fang;Lin, Mu-Hua
    楊筱芳
    Contributors: 資管系
    Keywords: Chance discovery;Chasm;Diffusion theory;Grounded systems;Grounded theory;Innovation diffusion;Innovativeness;New product;Rare Associative Analysis;Research models;Social Networks;Social values;Technical specifications;Artificial intelligence
    Date: 2011
    Issue Date: 2015-06-22 13:20:30 (UTC+8)
    Abstract: From the innovative diffusion theory, it is known that the early adopters have the characteristic of being liable to accept new products and generate new value from using new products. Through their social networks, they also transmit information about new products to the early majority. Moreover, from the use and gratification theory, if a new product provides users with usability of information, social value or entertainment, it is likely that this new product will be accepted because users' physical/mental need is fulfilled. Based on the above two principles, this study thereby develop a Human-Computing Grounded System. Expert first divides data as technical specification or value induced by early adopters, grounded theory analysis is then performed interactively. Results in this study indicate the new value induced by early adopters using new products which supported by new technology embedded in the new product. Meanwhile, inferred from the use and gratification theory, it is easier for the majority to accept a new product if this product offers more new values. By integrating multi-type of values conceived by the early adopters, our research model shows that indeed products with more and new values attract more majority. © 2011 Springer-Verlag.
    Relation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 6797 LNAI, 2011, Pages 292-301, 2nd JSAI International Symposia on Artificial Intelligence, JSAI-isAI 2010; Tokyo; Japan; 18 November 2010 到 19 November 2010; 代碼 87454
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1007/978-3-642-25655-4_28
    DOI: 10.1007/978-3-642-25655-4_28
    Appears in Collections:[資訊管理學系] 會議論文

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