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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Bibliographic Details
Published inInternational journal of innovation science Vol. 10; no. 3; pp. 371 - 384
Main Authors Chang, Shu-Hao, Chang, Hsin-Yuan, Fan, Chin-Yuan
Format Journal Article
LanguageEnglish
Published Brentwood Emerald Publishing Limited 30.07.2018
Emerald Group Publishing Limited
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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.
ISSN:1757-2223
1757-2231
DOI:10.1108/IJIS-05-2017-0036