This paper aims to provide a comprehensive overview of research on patent valuation. Specifically, it identifies trends in publications and citations, research performance, collaboration, themes and gaps that will be useful for future research.
Two types of bibliometric analysis – performance analysis and science mapping analysis – were conducted on 273 relevant journal articles in the Scopus database published until March 2024. The R Bibliometrix application and VOSviewer were used for the analysis.
The analysis of scientific publications on patent valuation shows an increasing trend in the number of publications but a decreasing trend in the average number of citations per article per year. Lee Changyong is the most productive researcher, with China, the USA and South Korea leading in the number of publications. The most cited papers are by Kogan et al. (2017) and Harhoff et al. (2003). The science mapping analysis identified five major author collaboration networks, five main international collaboration clusters and four primary bibliographic coupling clusters. Prominent research themes include “decision making,” “biotechnology” and “neural network,” with machine learning/artificial intelligence-based patent valuation emerging as a trending topic. This study suggests that future research should focus on developing new methodologies and tools for patent valuation, conducting research in developing countries and promoting regional and global collaboration.
The article search was limited to journal articles on patent valuation indexed by Scopus and written in English. Consequently, research published in other forms and languages, or not indexed by Scopus, was not analyzed.
This research is believed to be the first comprehensive overview of research conducted on patent valuation and the first to conduct a bibliometric analysis of scientific articles published until March 2024.
