کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5036903 | 1472384 | 2017 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
مدیریت، کسب و کار و حسابداری
کسب و کار و مدیریت بین المللی
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![عکس صفحه اول مقاله: Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology](/preview/png/5036903.png)
چکیده انگلیسی
Disruptive technology introduces new competitive platforms, possesses the ability of initiating new markets, and changes firms' technological competition status. Early identification of candidate application areas will allow for timely adjustment of technology innovation strategies and minimization of risks at firm level. This paper proposes a framework of application areas forecasting process for disruptive technology based on patent data. SIRS epidemic model is analogically introduced by measuring transition velocity of all the entities in the technology diffusion system respectively. We implement the model deterministically to forecast the potential of industrial and technological disruption in the short run, and stochastically to forecast the disruptive technology's major outbreak in candidate application areas in the long run. Radio-frequency identification technology is selected as case study. We conclude by discussing the major outbreak probabilities and potential disruptions of RFID in three different application areas. The results will provide practical suggestion to firms and other stakeholders to facilitate their strategy making when faced with disruptive technologies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Technological Forecasting and Social Change - Volume 117, April 2017, Pages 170-183
Journal: Technological Forecasting and Social Change - Volume 117, April 2017, Pages 170-183
نویسندگان
Yu Cheng, Lucheng Huang, Ronnie Ramlogan, Xin Li,