Structural model of patent quality applied to various countries
Purpose In the current knowledge-based economy era, national innovation ability is crucial. Abundant information can be obtained through patent analysis, and such information can help in the formulation of policies and the making of R&D decisions; numerous researchers thus continue to make paten...
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Published in | International journal of innovation science Vol. 10; no. 3; pp. 371 - 384 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Brentwood
Emerald Publishing Limited
30.07.2018
Emerald Group Publishing Limited |
Subjects | |
Online Access | Get full text |
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Summary: | Purpose
In the current knowledge-based economy era, national innovation ability is crucial. Abundant information can be obtained through patent analysis, and such information can help in the formulation of policies and the making of R&D decisions; numerous researchers thus continue to make patent analyses. The quality of patents possessed by a country indicates the level of innovation and technology in the country, and this study aims to assess the quality of patents possessed by various countries.
Design/methodology/approach
In this study, the authors determined patent quality in various countries from the perspective of the reflective measurement model and used a novel method to construct a structural model of patent quality.
Findings
This study discovered that patent family, number of claims, number of international patent classifications, forward citations, nonpatent references and maintenance time are the structural factors that affect patent quality. Forward citations and the number of claims are particularly highly explained by patent quality, which is a latent construct.
Originality/value
The results of this study provide valuable information to the government and help in the assessment of patent quality in various countries. In addition, the assessment model proposed in this study can be used in the investigation of patent quality in academic research and can predict patent quality, which will be of interest to the government and industry. |
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ISSN: | 1757-2223 1757-2231 |
DOI: | 10.1108/IJIS-05-2017-0036 |