Maturity assessment of green patent clusters: Methodological implications

Patents are one of the most widely used tools to analyze environmental technologies. Organizations such as the World Intellectual Property Organization and OECD have developed search strategies to retrieve green patents based on their patent classification. These classifications divide patents into clusters, which are aligned with different sustainability goals. In this paper, we take advantage of this to analyze the distribution of patents across 1.221 patent classes within six clusters defined by OECD's ENV-TECH classification. We also assess the maturity stage of each patent class by fitting two commonly used S-curve models, namely logistic and Gompertz. We find that (a) most patent classes are still in a relatively early stage of the technology life cycle and (b) considerable heterogeneity exists in the distribution of patents, both within and across clusters. We discuss the methodological implications of our results and provide recommendations for scholars, drawing on green patent analyses, to conduct future work on environmental technologies. • We analyze patenting activity across 1.221 green patent classes as defined by OECD. • The distribution of patents across six clusters of green patents is highly skewed. • A quarter of the patents in the dataset correspond to only 31 patent classes. • Most green patent classes are in the early stages of their technology lifecycle. • We find no connection between number of patents and technological maturity.

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Publication Details

Journal
Technological Forecasting and Social Change
Published
2024-10-19
DOI
https://doi.org/10.1016/j.techfore.2024.123813
Citations
4
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
4.52
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Maturity assessment of green patent clusters: Methodological implications

Arjan Markus, Elena M. Tur, Jaime Bonnín Roca, Maryam Mazaheri et al.
4 citations
Technological Forecasting and Social Change
Energy, Environment, Economic Growth
4.52
article

Maturity assessment of green patent clusters: Methodological implications

Arjan Markus, Elena M. Tur, Jaime Bonnín Roca, Maryam Mazaheri, Bob Walrave
article en
4 citations

Abstract

Patents are one of the most widely used tools to analyze environmental technologies. Organizations such as the World Intellectual Property Organization and OECD have developed search strategies to retrieve green patents based on their patent classification. These classifications divide patents into clusters, which are aligned with different sustainability goals. In this paper, we take advantage of this to analyze the distribution of patents across 1.221 patent classes within six clusters defined by OECD's ENV-TECH classification. We also assess the maturity stage of each patent class by fitting two commonly used S-curve models, namely logistic and Gompertz. We find that (a) most patent classes are still in a relatively early stage of the technology life cycle and (b) considerable heterogeneity exists in the distribution of patents, both within and across clusters. We discuss the methodological implications of our results and provide recommendations for scholars, drawing on green patent analyses, to conduct future work on environmental technologies. • We analyze patenting activity across 1.221 green patent classes as defined by OECD. • The distribution of patents across six clusters of green patents is highly skewed. • A quarter of the patents in the dataset correspond to only 31 patent classes. • Most green patent classes are in the early stages of their technology lifecycle. • We find no connection between number of patents and technological maturity.

Technological Forecasting and Social ChangeVol. 209
Eindhoven University of Technology (NL)
Openalex Percentile: Top 5%
Energy, Environment, Economic Growth
4.52
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Maturity assessment of green patent clusters: Methodological implications — Arjan Markus, Elena M. Tur, et al. · Technological Forecasting and Social Change (2024) | TGRS Research Map | TGRS