Il finanziamento competitivo per Ricerca e Sviluppo in Italia: imparare dal passato, preparare il futuro

I dati e i risultati presentati in questo documento sono tratti dalla quarta edizione della Relazione sulla ricerca e l'innovazione in Italia promossa dal CNR-DSU e analizzano le criticità relative all’offerta degli strumenti nazionali di finanziamento per la Ricerca e Sviluppo (R&S) di tipo competitivo o “basato su progetto”. Fino agli anni della pandemia da COVID-19, il finanziamento italiano alla R&S “basato su progetto” ha sofferto di una modesta dotazione finanziaria e di una limitata varietà di strumenti competitivi. Le erogazioni dei fondi ai beneficiari hanno risentito di un andamento discontinuo, dovuto sia alla pubblicazione di bandi a cadenze irregolari che alla distanza tra l’avvio delle iniziative e l’effettiva approvazione dei progetti selezionati. Rispetto ad altri paesi europei, l'Italia si è inoltre distinta per una governance delle risorse centralizzata, dominata dai ministeri, e per una limitata focalizzazione dei programmi di ricerca su obiettivi legati alle grandi sfide sociali e tecnologiche. Il PNRR ha introdotto cambiamenti significativi, con l'attivazione di nuovi strumenti e uno stanziamento senza precedenti, puntando anche a un maggiore allineamento a priorità tematiche riconosciute a livello europeo. L’Italia dovrà dimostrare capacità, anche a PNRR concluso, nel mantenere questa crescita, non solo dal punto di vista delle risorse investite ma anche relativamente alla varietà degli strumenti che operano contemporaneamente. Il momento di cambiamento può inoltre stimolare una riflessione sulla gestione dei programmi competitivi, valutando la validità di una struttura di governo centralizzata rispetto a modelli alternativi e contemplando l’adozione di meccanismi di valutazione dei progetti che valorizzino maggiormente l’impatto delle attività di R&S sulla società

Using machine learning to map the European Cleantech sector

This paper is the introductory chapter of a series of analyses that will result from the CLEU1 project, a collaboration between the universities of Politecnico di Torino, Politecnico di Milano and Università degli Studi di Bologna. The project focuses on Cleantech, an industry sector that develops and deploys sustainable and environmentally friendly solutions for various target applications. It aims to: i) analyse the actions that are undertaken by European Cleantech firms to engage in transformative climate and innovation actions to align with the European Green Deal-inspired policies; ii) examine the association of environmental innovation and the number of new investments made by venture capital (VC) investors in Cleantech companies on environmental indicators; iii) analyse the enabling factors for the development of European Cleantech firms, with a focus on EU-level and country-level targeted policies and regulations and the different sources of financing; iv) analyse the extent to which the implementation of policies and regulations affect both the propensity of cleantech firms to seek external equity financing and the equity offering by VC funds

Link prediction and feature relevance in knowledge networks: A machine learning approach.

We propose a supervised machine learning approach to predict partnership formation between universities. We focus on successful joint R&D projects funded by the Horizon 2020 programme in three research domains: Social Sciences and Humanities, Physical and Engineering Sciences, and Life Sciences. We perform two related analyses: link formation prediction, and feature importance detection. In predicting link formation, we consider two settings: one including all features, both exogenous (pertaining to the node) and endogenous (pertaining to the network); and one including only exogenous features (thus removing the network attributes of the nodes). Using out-of-sample cross-validated accuracy, we obtain 91% prediction accuracy when both types of attributes are used, and around 67% when using only the exogenous ones. This proves that partnership predictive power is on average 24% larger for universities already incumbent in the programme than for newcomers (for which network attributes are clearly unknown). As for feature importance, by computing super-learner average partial effects and elasticities, we find that the endogenous attributes are the most relevant in affecting the probability to generate a link, and observe a largely negative elasticity of the link probability to feature changes, fairly uniform across attributes and domains

Organizational Factors Affecting Higher Education Collaboration Networks: Evidence from Europe

We explore the role of organizational factors in research collaboration networks among European universities. The study of organizational drivers in shaping collaboration patterns is crucial for policy design aimed at reducing research fragmentation and fostering knowledge creation and diffusion. By using Exponential Random Graph Models (ERGMs) and controlling for spatial factors, we investigate the role of two main mechanisms guiding the partners’ selection process: organizational attributes and homophily. We investigate two distinct scientific collaboration networks (i.e., projects and publications) and two research domains (Physical Sciences and Engineering, and Life Sciences) over the 2011–2016 time period. Our empirical evidence reveals that, among the main dimensions indicated by the literature, research capability (measured by the dimension of doctoral programmes) has the clearest and most stable impact either on the tendency to establish collaboration ties or as homophily effect. In terms of policy implications, it emerges that organizational similarity in research capability matters and policy makers should consider doctoral programmes as a strategic variable to promote successful collaborations in scientific research

The determinants of national funding in trans-national joint research: exploring the proximity dimensions

This paper investigates -using an explorative approach, why policy makers at national level engage in transnational joint research activities and mobilize dedicated financial resources. The research question is: why policy makers (either Governments or Research Funding Organisations-RFOs) in EU28 countries invest in transnational joint research activities beyond the European Framework Programmes, and what are the determinants of different levels of funding engagement? The question is relevant to understand the reasons that generate the existing imbalances within European countries as to the participation in transnational research, which are likely to create peripheries within the ERA, thus undermining the process of European integration. We assume that proximity linked to cognitive, institutional and organizational dimensions can affect the policy decisions about the level of funding (real engagement) joint European research programmes, because the closeness or distance in these dimensions generate similarities that are likely to influence the possibility of decision makers to collaborate in the implementation of research programmes. The paper also explores the existence of any effect of geographical proximity, although it is not supposed to play a role in policy decisions about investment in transnational research programmes

FOSSR First General Conference: project presentations

<p>The first yearly FOSSR General Conference intended to <strong>share with the diverse stakeholders and publics of the project the results and advancements of each package of research</strong>, as well as <strong>offer a discussion space for researchers to fine-tune the work plan</strong>, adapting to the development of the project.  The folder contains all presentations following the list below:</p><p> </p><p><strong>Data Collection</strong>  </p><p>"Automated data collection and Network Analysis: latest updates from FOSSR", Antonio Zinilli  </p><p>"Probabilistic panel for research", Mario Paolucci  </p><p> </p><p><strong>An open cloud for Social Studies  </strong></p><p>"Giving value to research data: data curation in the FOSSR project", Sonia Stefanizzi  </p><p>"Open cloud: Network of Data Center and Cloud Computing Infrastructure", Mario Ciampi, Mario Sicuranza  </p><p> </p><p><strong> Data Analysis  </strong></p><p>"Policy Learning Platform': state of the art and critical issues", Giovanni Cerulli  </p><p>"Ontologies, patterns and modelling solutions for enhancing data to knowledge graphs in FOSSR", Andrea Giovanni Nuzzolese  </p><p> </p><p><strong>Governance  </strong></p><p>"The first steps of the Strategic Management Committee and the role of the FOSSR Stakeholder Advisory Board", Marco Sprocati  </p><p> "Ethics@FOSSR, preliminary remarks", Cinzia Caporale  </p><p>"The first steps of the Governing Board and the role of the Scientific Advisory Board, Massimiliano Saccone  </p><p> </p><p><strong>Training and communication  </strong></p><p>"Enhancing Skills, Building Communities: The FOSSR Training Initiatives", Andrea Orazio Spinello  </p><p>"Communication, Dissemination & Outreach", Alessandra M. Stilo </p><p> </p><p> </p><p> </p><p>Link to the General Conference video recording (in italian): <a href="https://www.youtube.com/watch?v=HzlBHdkc_yc">https://www.youtube.com/watch?v=HzlBHdkc_yc</a></p&gt