Autori
Quatraro, FrancescoManera, MariaTitolo
Mapping European Circular Economy Patents Using Advanced Natural Language Processing ModelsPeriodico
Università degli studi di Torino. Dip. Di Economia e Statistica Cognetti de Martiis. Working paper seriesAnno:
2025 - Volume:
5 - Fascicolo:
4 - Pagina iniziale:
1 - Pagina finale:
62The circular economy (CE) paradigm has recently gained increasing attention in both academic and policy circles. Existing literature has stressed that the
transition to the CE paradigm implies innovation aiming to change consumption
and production behaviors and technologies. Empirical studies have focused on
the drivers and effects of the adoption and generation of CE innovations, based
on survey and patent data, respectively. However, identifying and tracking CE
innovations through patents has been challenging due to the lack of a domainspecific classification system. Existing methods are often insufficient to capture
the diversity and complexity of CE technologies. This paper proposes a novel
methodology for the identification and classification of CE-related patents, combining large language models (LLMs), pre-trained language models (PLMs), and
topic modelling techniques. By applying these methodologies to patent data, we
uncover significant trends in the distribution of CE patents in sectors, technological fields, and geographical regions. Our exploratory findings highlight a growing
cross-sector engagement with CE principles, underscoring the transformative potential of circular economy innovations in driving sustainable industrial practices.
This paper contributes to advancing the classification and understanding of CE
innovations, offering valuable insights to policymakers, researchers, and industry
stakeholders.
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