TECHNOLOGY FORECASTING VIA PUBLISHED PATENT APPLICATIONS AND PATENT GRANTS

doi:6119/JMST-011-0111-1

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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