000 01886cam a2200229 4500500
005 20251012024439.0
041 _afre
042 _adc
100 1 0 _ad'Angelo, Viviana
_eauthor
700 1 0 _a Tuzi, Fabrizio
_eauthor
700 1 0 _a Filippetti, Andrea
_eauthor
245 0 0 _aReclassifying Innovation for Biodiversity: A Patent-Based Framework to Monitor Green and Pervasive Technologies
260 _c2025.
500 _a50
520 _aExisting patent classification systems often overlook the full spectrum of green and environmentally relevant technologies – especially pervasive technologies not originally designed for ecological purposes. This paper presents a novel methodological framework to identify, and classify both clean and pervasive technologies with relevance to biodiversity innovation. The approach combines the analysis of international patent data with machine learning techniques to enhance the accuracy and granularity of classification. In a two-step process, the study first identifies key biodiversity-related technologies and their corresponding IPC classes, and then maps innovation activity and geographic trends using patent-based indicators. By addressing limitations in existing international patent classification schemes, the framework enables more accurate ESG assessments and better-informed sustainability policies and investments. Ultimately, this work provides data-driven tools for tracking biodiversity-related technological progress, supporting robust ESG disclosure and strategic decision-making across sectors.
690 _aBiodiversity Innovation
690 _aESG
690 _aMachine Learning
690 _aPatent Classification
786 0 _nInnovations | hors-série | HS1 | 2025-10-10 | p. 38-38 | 1267-4982
856 4 1 _uhttps://shs.cairn.info/journal-innovations-2025-HS1-page-38?lang=en&redirect-ssocas=7080
999 _c1543943
_d1543943