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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

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
Issue Date: 2018-12-17T07:10:35Z
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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