Template-type: ReDIF-Paper 1.0
Author-Name: Leonidas Aristodemou
Author-Name: Silvia Appelt
Author-Name: Brigitte van Beuzekom
Author-Name: Fernando Galindo-Rueda
Title: Assessing the relevance of R&D funding towards societal goals: Insights from new data sources and AI-assisted methods
Abstract: This paper presents and demonstrates a novel approach for assessing the relevance of public R&D funding towards societal goals. The approach relies on the development of a new machine learning classification model for R&D activity descriptions, trained on researchers’ self-assessments about the relevance of their R&D activity towards Sustainable Development Goals (SDGs). Applied to R&D project descriptions in the OECD Fundstat database, the model shows how funding, including for basic research, contributes towards societal goals. The analysis allows to compare funding portfolios and provides evidence of the interdependencies between societal goals served by R&D funding and its potential to contribute to multiple goals.
Classification-JEL: C55; H59; O32; O38; Q01; C38; C45; Q55
Creation-Date: 2025-11-26
Number: 2025/25
Handle: RePEc:oec:stiaaa:2025/25-EN