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Please use this identifier to cite or link to this item:
http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51678
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Title: | TECHNOLOGY FORECASTING VIA PUBLISHED PATENT APPLICATIONS AND PATENT GRANTS |
Authors: | Chang-Pin Lin DarZen Chen Mu-Hsuan Huang Yi-Tung Chan |
Contributors: | 國立臺灣海洋大學:機械與機電工程學系 |
Keywords: | technology forecasting published patent application patent grants |
Date: | 2012-08
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Issue Date: | 2018-12-17T07:10:35Z
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Publisher: | Journal of Marine Science and Technology |
Abstract: | Abstract: The objective of this research is to study and establish the
relationships between published patent applications and patent
grants for exploring the technology development trend on a
specific technology since more and more patents have their
applications published before they are granted. Two modeling
algorithms based on the patent grant/publish ratio as well as
one long-term modeling algorithm based on the average publish-to-grant
lag, were developed accordingly. The relationships
between patent grants and published patent applications
were constructed through two case studies on Magnetic
Random Access Memory and Organic Light-Emitting Diode
technologies and corresponding forecasts were then conducted.
Comparing to the traditional time-series Autoregressive Integrated
Moving Average method, the predicting power of the
modeling algorithms based on the patent grant/publish ratio
was satisfactory. On the other hand, the modeling algorithm
based on the characteristic of average publish-to-grant lag has
shown superior predicting power. Results from these two
applications help us to validate the proposed methods and
appropriate tools for forecasting the patent grants. |
Relation: | 20(4) pp.345-356 |
URI: | http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51678 |
Appears in Collections: | [機械與機電工程學系] 期刊論文
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