Energy system planning has evolved from a narrow focus on engineering and supply works towards addressing more complex, multifactorial challenges. Increasingly challenged by climate change, extreme events, economic shocks, and altered supply demand patterns, the analysis of energy systems requires holistic approaches based on data-driven models, taking into account key socio-economic factors. We draw insights from reviewing the literature, indicating the need to cover the following major gaps: the shift to transdisciplinary approaches, incorporating environmental system analysis; resilient and sustainable energy designs based on flexible portfolios of renewable mixes; the integration of socio-economic aspects, economic analyses and behavioural models to ensure energy systems are not only technically sound but socially acceptable and viable; the need for stakeholder engagement considering the human angle in energy security and behavioural shifts. Responding to these pressing challenges and emerging needs, the Global Climate Hub (GCH) initiative, operating under the UN Sustainable Development Solutions Network, offers a conceptual framework, leveraging transdisciplinary approaches. In this Concept Paper, we present for the first time the idea of the GCH as a framework that we believe has the potential to address the modern holistic needs for energy system analysis and policymaking. By setting the conceptual/theoretical ground of our suggested approach, we aim to provide guidance for innovative combinations of cutting-edge models, socio-economic narratives, and inclusive interaction with relevant stakeholders for the development and the long-term implementation of sustainable pathways.

Foreign direct investment (FDI) has grown dramatically as a major form of international capital transfer over the past decades. The unprecedented growth of cross‐country FDI flows has been attributed to a rich set of economic, geographical and institutional factors. In this paper, Ι examine the role of financial system heterogeneity as a potential detrimental factor to FDI flows across OECD economies. To do so, Ι use a panel dataset of the most recently updated bilateral FDI data at the country level according to OECD BMD4 definition and construct measures of financial distance using a broad set of financial indicators. The econometric approach consists of a gravity‐style model, estimated according to the latest advancements in econometric techniques in order to avoid omitted variable bias. The results indicate that financial system similarity is associated with increased bilateral FDI flows, a conclusion that is robust across different estimation strategies and financial distance measures. This insightful policy implication for advanced economies is that the restructuring of the financial system and harmonisation to best practices can contribute to economic recovery through the FDI channel as well. Finally, the results highlight the importance for the full implementation of the Banking Union and the Capital Markets Union in the EU.

This paper introduces a machine learning (ML) based approach for integrating Human Security (HS) and Sustainable Development Goals (SDGs). Originating in the 1990s, HS focuses on strategic, people-centric interventions for ensuring comprehensive welfare and resilience. It closely aligns with the SDGs, together forming the foundation for global sustainable development initiatives. Our methodology involves a structured analysis of the relationship between 44 HS reports and the SDGs using advanced text analytics and machine learning methods, each report was evaluated based on its thematic relevance to HS aspects and SDG goals and sub-targets using a keyword-based matching approach. The data retrieved from the HS-related reports was transformed into a numerical format using the Term Frequency-Inverse Document Frequency (TF-IDF) method and classified through the Random Forest Classifier. Advanced models were utilized for exploration, namely BERT (Devlin et al. in Polit Sci, 2018) DistilBERT (Sanh et al. in ArXiv preprint arXiv: 1910.01108, 2019), and ELECTRA (Clark et al. in Polit Sci, 2020). This process contributed to the development of a web-based SDG mapping tool, specifically tailored for elaborating on the HS-SDG nexus. enabling the analysis of 13 new reports and their connections to the SDGs. This web application provides a streamlined interface for analyzing documents in PDF form and determining their relevance to the SDGs, allowing users to upload PDF files via an HTML form. Following expert consultation, our results outperform currently available similar online tools and assist in establishing strong links between the reports and global objectives, offering a nuanced understanding of the interplay between HS and sustainable development. This research provides a scalable framework to explore the relationship between HS and the global sustainability agenda, offering a practical, efficient resource for scholars and policymakers.

This paper the effects of a technology-driven increase in crop and livestock productivity on key agricultural, land-use, and environmental indicators in Greece, using the FABLE (Food, Agriculture, Biodiversity, Land Use, and Energy) Calculator. Through empirical evidence and sophisticated modelling techniques, we analyze the intricate interplay between agricultural productivity and environmental sustainability. Our scenario-based projections show that higher agricultural productivity substantially reduces greenhouse gas emissions, primarily through lower livestock emissions, diminished pressure on pastureland, and increased emission withdrawals from land-use changes. Enhancing productivity in the livestock and crop sector reduces GHG emissions from agriculture by 29% until 2030 and 62% until 2050, compared to a business-as-usual scenario. The result is amplified when we embed the productivity surge in a holistic transformational strategy following Greece’s national commitment including a shift to healthy dietary consumption. Moreover, costs decline markedly, by almost 50% in the long run, driven mainly by the reduction in pesticide use. In addition to its empirical findings, this paper delineates policy recommendations to support cutting-edge technologies within the Greek agricultural sector, focusing on horizontal and vertical measures. We highlight key precision agriculture technologies that align with current trends in Greece, particularly in the areas of drone applications, advanced sensors, and variable rate technology, alongside innovations in precision livestock management. Overall, our findings demonstrate that boosting agricultural productivity can generate a double dividend—lower emissions and enhanced competitiveness—particularly when supported by holistic policy measures.

We explore the relation between sound institutions favouring innovation and technology investment and firms' emission reduction. Even though emission abatement is achieved at the firm or plant level, we postulate that structural and institutional factors underpinning green innovation, skills and technology adoption at the country level are of material importance. Advances in technology and infrastructure are the main drivers for the reduction of emission and are, in turn, intrinsically linked to overall country characteristics. Sound institutions can act as enablers and accelerators for firms and industries in the green transition process, hence we find an attenuating effect on emissions conditional on firm attributes.

We explore the relation between sound institutions favouring innovation and technology investment and firms’ emissions reduction. Even though emission abatement is achieved at the firm or plant level, we postulate that structural and institutional fac- tors underpinning green innovation, skills and technology adoption at the country level are of material importance. Advances in technology and infrastructure are the main drivers for the reduction of emissions and are, in turn, intrinsically linked to overall country characteristics. Sound institutions can act as enablers and accelerators for firms and industries in the green transition process, hence we find an attenuating effect on emissions conditional on firm attributes.