projects founded

WECARE: WEaving Complexity And the gReen Economy

WECARE: WEaving Complexity And the gReen Economy

  • Code: 20223W2JKJ
  • Project start and end date: 29/09/2023 – 28/09/2025
  • Extension date: 28/02/2026
  • Funding source: MUR Avviso 104/2022 – PNRR – Next Generation EU, Missione 4 Componente 2 Investimento 1.1 – “Fondo per il Programma Nazionale di Ricerca e Progetti di Rilevante Interesse Nazionale (PRIN)”
  • CUP: F53D23001010006
  • CREF Funding amount: 89.134,00 €
  • Total project cost: 117.995,00 €

CREF Unit Leader

Dario Mazzilli

Participating research units

  1. Principal Investigator (PI): Andrea Zaccaria – National Research Council – Institute for Complex Systems (CNR-ISC);
  2. Research Unit: CREF – Dario Mazzilli

Research team and staff recruited within the project

Personnel recruited with PRIN PNRR funds: three young researchers were recruited during the project (research fellowships/collaborations)

Results achieved

The WECARE project applied the Economic Complexity framework to the study of the green transition. We gathered and harmonised data on exports, patents, and scientific production, with a focus on green sectors, computing the export, technological, scientific, and green fitness of countries and regions and using it to improve GDP growth forecasts. We mapped the relatedness between industrial sectors and green technologies (validated against null models) and introduced a machine-learning-based “green readiness” index, validated against the Yale Environmental Performance Index. We investigated the role of critical raw materials in green innovation and the link between corporate diversification, patenting, and economic growth at the country, sector, and firm level. On the theoretical side, we proved the equivalence between the Fitness-Complexity algorithm and the Sinkhorn-Knopp algorithm, linking Economic Complexity to Optimal Transport theory, and developed a job- and skill-based measure of economic complexity. The results led to more than 15 publications in international journals, additional papers under review, and numerous presentations at international conferences. All input and output data are published open access on a dedicated repository.

Scientific publications

1. Albora et al. (2025), Challenges and opportunities for the EU labour market from AI development, JRC Policy Brief.
2. Albora, Straccamore & Zaccaria (2026), Machine learning-inspired similarity measure to forecast M&A from patent data, PLoS ONE, 21(2), e0341010.
3. Angelini et al. (2024), Forecasting the countries’ gross domestic product growth: the case of Technological Fitness, Chaos, Solitons & Fractals, 184, 115006.
4. Aufiero, De Marzo, Sbardella & Zaccaria (2024), Mapping job fitness and skill coherence into wages: an economic complexity analysis, Scientific Reports, 14(1), 11752.
5. Buffa et al. (2025), Maximum entropy modelling of sub-optimal transport, Communications Physics, 9(39).
6. Caldarola et al. (2024), Economic complexity and the sustainability transition: a review of data, methods, and literature, Journal of Physics: Complexity, 5(2), 022001.
7. Cresti et al. (2025), Vulnerabilities and capabilities in the EU Automotive industry, arXiv:2501.01781.
8. De Cunzo, Consoli, Perruchas & Sbardella (2025), Mapping critical raw materials in green technologies, Industry and Innovation, 1-34.
9. De Cunzo, Patelli, Sbardella & Tacchella (2025), The Functional Role of Critical Raw Materials in Technological Innovation, Utrecht University – Papers in Evolutionary Economic Geography, No. 2516.
10. De Stefano, Mula, Mariani & Zaccaria (2025), From macro to micro: economic complexity indicators for firm growth, arXiv:2507.21754.
11. Fenoaltea et al. (2024), Follow the money: a startup-based measure of AI exposure across occupations, industries, and regions, arXiv:2412.04924.
12. Fessina, Zaccaria, Cimini & Squartini (2024), Pattern-detection in the global automotive industry, Chaos, Solitons & Fractals, 181, 114630.
13. Fessina, Tacchella & Zaccaria (2025), Product-level value chains from firm data, arXiv:2505.01133.
14. Fessina, Albora, Tacchella & Zaccaria (2024), Identifying key products to trigger new exports, Journal of Physics: Complexity, 5(2), 025003.
15. Huang, Xu, Lü, Zaccaria & Mariani (2024), Uncovering key predictors of high-growth firms via explainable machine learning, arXiv:2408.09149.
16. Mariani, Mazzilli, Patelli, Sels & Morone (2024), Ranking species in complex ecosystems through nestedness maximization, Communications Physics, 7(1), 102.
17. Piombo, Mazzilli & Patelli (2026), Statistical Mechanics of the Sub-Optimal Transport, arXiv:2602.04308.
18. Russo, Scaramozzino & Zaccaria (2025), A job-based assessment of economic complexity: from hidden to revealed, arXiv:2507.05846.
In preparazione: Massell et al. (2026); Napoletano et al. (2026), Green Transition Readiness and Environmental Performance: A Machine-Learning Evaluation of Export Complexity in Renewable Energy Supply Chains.

Organised events or conference participation

Dario Mazzilli: NetSci-X 2026, Auckland (New Zealand); Eco2stat 2025, Vagliari (Italy); NetSci 2025, FinEcoNets satellite, Maastricht (The Netherlands); NetSci-X 2025, Indore (India); CCS-24, Exeter (UK); NetSci-X 2024, Venice (Italy); StatPhys 2023, Tokyo (Japan).
Angelica Sbardella: GEOINNO 2026, Budapest (Hungary); CONCORDi 2025, Seville (Spain); GERPISA International Colloquium 2025, Shanghai (China); RSA-SIE 2024, Urbino (Italy); CCS 2024, Exeter (UK); CONCORDi 2023, Seville (Spain); seminars at the University of Palermo (2025), Peking University (2025), Winter Workshop on Complex Systems 2025 (Bergamo, keynote), University of Oxford (2025), JRC Seminar Series (Seville, 2024), Bonn AI Climate Expert Meeting (2024), Autonomy Institute London (2024).
Andrea Zaccaria: StatPhys29 Satellite (2025); NetSci-X 2025, Indore (India); “Economic And Financial Networks. Reconstruction, Resilience And Recovery” workshop, Lucca (2024); Econophysics Colloquium 2024, Vienna (Austria); NetSci-X 2024 and “Economic Fitness and Complexity” workshop, Ca’ Foscari University of Venice.
Alberto Petri: Lipari School 2024, “Complex Systems from economics to biology and brain”.

Posters, dissemination materials, output

Project website, used as an open-access repository for the input and output datasets (exports, patents, science, green products) and for the results of the analyses (fitness, relatedness, green readiness).
Policy brief produced in collaboration with the European Commission’s Joint Research Centre: “Challenges and opportunities for the EU labour market from AI development”.

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