Maturity assessment of green patent clusters: Methodological implications
Maryam Mazaheri,
Jaime Bonnin Roca,
Arjan Markus,
Elena M. Tur and
Bob Walrave
Technological Forecasting and Social Change, 2024, vol. 209, issue C
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.
Keywords: Green patents; Environmental innovation; Technology life cycle; Growth models; Technological maturity (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524006115
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524006115
DOI: 10.1016/j.techfore.2024.123813
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().