Search Results (3,127)

Despite European and international regulatory frameworks promoting circular economy principles, sustainability in the furniture sector is still challenged by the limited access to reliable information about circular materials for designers, manufacturers, and waste managers in the Made-in-Italy furniture ecosystem. This research develops a digital infrastructure to address these information gaps through mixed methodology, combining desk research on regulatory frameworks and existing platforms; field research involving stakeholder mapping and interviews with designers, manufacturers, and waste managers; and the experimental development of AI-enhanced digital tools. The result integrates a web-based platform for circular materials with a CAD plugin supporting real-time sustainability assessment. As AI-assisted data entry showed a reduced form completion time while maintaining accuracy through human verification, testing also revealed how the system effectively bridges knowledge gaps between stakeholders operating in currently siloed value chains. The platform is a critical step in enabling designers to incorporate circular materials during the early design stages, while providing manufacturers access to verified punctual sustainability data compliant with mandatory Green Public Procurement criteria. Beyond the development of an innovative digital tool, the study outlines a corresponding operational model as a practical framework for strengthening the transition toward a circular economy in the Italian furniture industry. Full article

This study analyses the dynamics of the energy transition within the SPRING-F group (Spain, Poland, Romania, Italy, the Netherlands, Germany, France) through a hybrid approach that combines econometric panel ARDL models with machine learning algorithms. The analysis is based on energy, economic, and technological indicators, including renewable energy consumption, energy intensity, emissions, GDP per capita, urbanization, trade openness, and R&D expenditure. The results of the exploratory analysis highlight the existence of clear structural differences between Western European and emerging Central and Eastern European economies. Based on the estimates made with the ARDL panel model, the long-term equilibrium relationships were confirmed. They indicated positive and significant effects of urbanization and economic growth on renewable energy consumption, as well as a negative impact of emissions. Regarding the short-term effects, the error correction coefficient suggests a moderate convergence towards equilibrium. Machine learning models highlight the superiority of nonlinear approaches, and SHAP analysis confirms the dominant role of emissions and the heterogeneity of national energy transition trajectories. Full article

We introduce the Economic Productivity of Energy (EPE), GDP generated per unit of energy consumed, as a quantitative lens to assess the sustainability of the Artificial Intelligence (AI) revolution. Historical evidence shows that the first industrial revolution, pre-scientific in the sense that technological adoption preceded scientific understanding, initially disrupted this ratio: EPE collapsed as profits outpaced efficiency, with poorly integrated technologies, and recovered only with the rise in scientific knowledge and societal adaptation. Later industrial revolutions, such as electrification and microelectronics, grounded in established scientific theory, did not exhibit comparable declines. Today’s AI revolution, highly profitable yet energy-intensive, remains pre-scientific and may follow a similar trajectory in EPE. We combine this conceptual discussion with cross-country EPE data spanning the last three decades. We find that the advanced economies exhibit a consistent linear growth in EPE: these countries account for a large share of global GDP and energy use and are therefore expected to be most affected by the AI transition. Therefore, we advocate for regular monitoring of EPE: transparent reporting of AI-related energy use and productivity-linked incentives can expose hidden energy costs and prevent efficiency-blind economic expansion. Embedding EPE within sustainability frameworks would help align technological innovation with energy productivity, a critical condition for sustainable growth. Full article

Despite the immense potential of digital intelligence technologies to enhance corporate profitability, manufacturing enterprises often face the “digital–green paradox”, which indicates that while companies invest in digital and intelligent transformation, their energy consumption increases rather than promoting green transition. To provide reasonable transformation solutions for manufacturers still caught in this paradox, this paper adopts a single-case study approach from a product lifecycle perspective. Focusing on FAW-Volkswagen—a manufacturing enterprise demonstrating outstanding performance in digital-intelligent green transformation—this study conducts an in-depth investigation into the stage characteristics and underlying mechanisms. The results show that the following: (1) The digital-intelligent green transformation of manufacturing enterprises is an iterative process evolving from “green design, low-carbon production, intelligent service to enterprise spiral value-added”, with distinct digital-intelligent empowerment models at each stage. (2) By leveraging digital-intelligent technologies, manufacturing enterprises can build a multi-tiered “internal-external dual circulation” green development system encompassing the “enterprise—industrial chain—full ecosystem,” driving comprehensive green upgrades across the entire industry and ecosystem. This paper reveals the intrinsic mechanisms through which digital-intelligent technologies facilitate manufacturing enterprises’ green transformation. It expands and enriches the research context and theoretical implications of product lifecycle management, offering management insights and strategic references for other enterprises pursuing green transformation and upgrading pathways in the digital-intelligent economy era. Full article

This study systematically reviews and re-evaluates the international competitiveness and economic sustainability of China’s solar photovoltaic (PV) industry. Based on the PRISMA protocol, it integrates both qualitative and quantitative evidence from 70 core English-language publications published between 2000 and 2025. An analytical framework is developed that combines keyword co-occurrence analysis, thematic clustering, and mechanism pathway mapping. The study identifies three key thematic domains: policy governance mechanisms, economic feasibility and cost structures, and the coupling between technological innovation and environmental performance. The findings reveal a transition in China’s PV development pathway—from early policy-driven expansion to the co-evolution of institutional adaptation and market mechanisms—highlighting the dynamic tension among multi-level variables. Four institutional dimensions and associated variable chains are proposed, uncovering long-term contradictions such as the reliance on subsidies versus structural efficiency and the strategic mismatch between national industrial strategies and global decarbonization goals. The study suggests that future research should prioritize system modeling, feedback mechanism identification, and the theoretical expansion of multi-level governance frameworks. In doing so, this review provides a reusable variable classification framework for analyzing green industrial transformation and offers policy insights for emerging economies engaged in global climate governance. Full article

It is undeniable that rapid population increase coupled with growing resource constraints are making the demand for smart and sustainable solutions more urgent than ever to secure future resources for the transition to sustainable energy production. To address these issues, it is necessary to define innovative approaches that can exploit more efficiently and extensively the resources we have at our disposal. Consequently, this paper provides an overview of the potential benefits of processing waste-printed circuit boards (WPCBs) that are generated in large quantities and, due to their high metal content, can emerge as an adequate and profitable supply of critical metals, such as copper, aluminum, and nickel, which are essential for green energy transition. The review promotes the idea of industrial symbiosis as a concept that goes beyond circular economy and can integrate WPCB treatment and manufacturing processes related to sustainable energy transition, although they are different industrial sectors that can be even regionally separated. Major metal recovery processes from WPCBs are examined and discussed, with the primary focus on the performances of copper, aluminum, and nickel production, while additional metals relevant to the energy transition are also highlighted. Finally, the review paper argues and exemplifies that the recovered metals from WPCBs have the required properties to be supplied into the manufacturing processes of wind turbines, solar panels, and lithium-ion batteries. Full article

Licorice (Glycyrrhiza glabra) is a perennial herb traditionally valued for its aromatic and therapeutic properties. In recent years, however, growing attention has shifted toward the technical and environmental potential of the plant’s industrial by-products, particularly the fibrous material left after extraction. This review integrates botanical knowledge with engineering and industrial perspectives, highlighting the role of licorice fiber in advancing sustainable innovation. The natural fiber obtained from licorice roots exhibits notable physical and mechanical qualities, including lightness, biodegradability, and compatibility with bio-based polymer matrices. These attributes make it a promising candidate for biocomposites used in green building and other sectors of the circular economy. Developing efficient recovery processes requires collaboration across disciplines, combining expertise in plant science, materials engineering, and industrial technology. The article also examines the economic and regulatory context driving the transition toward more circular and traceable production models. Increasing interest from companies, research institutions, and public bodies in valorizing licorice fiber and its derivatives is opening new market opportunities. Potential applications extend to agroindustry, eco-friendly cosmetics, bioeconomy, and sustainable construction. By linking botanical insights with innovative waste management strategies, licorice emerges as a resource capable of supporting integrated, competitive, and environmentally responsible industrial practices. Full article

The Jiangsu Yangtze River city cluster is a key growth pole of the Yangtze River Economic Belt, yet substantial disparities in development levels persist across cities, and the role of rail transit investment in fostering regional economic coordination remains insufficiently understood. This study aims to reveal the dynamic mechanisms through which railway transportation investment influences regional economic growth via population migration and service industry agglomeration, and to quantify the economic multiplier effects under different investment scenarios. Considering the close economic linkages among cities, spatial autocorrelation analysis is applied to assess intercity economic dependence, which provides the basis for developing a system dynamics model that links the rail transit system with the regional economy. Using data from eight core cities over the period 2014–2023, the model is employed to simulate long-term economic responses under different investment scenarios. The results indicate that increasing the rail transit investment ratio from 0.0077 to 0.02 is associated with an estimated 13.2% increase in regional GDP by 2030, with a corresponding economic multiplier of approximately 1.8, while simulation errors remain within 4.1–16.2% compared with historical data. The findings suggest that rail transit investment promotes regional growth through improved accessibility, factor agglomeration, and industrial upgrading, and that coordinated planning at the urban agglomeration scale is more effective than isolated city-level strategies. By integrating spatial dependence analysis with system dynamics modeling, this study offers a dynamic perspective on the regional economic impacts of rail transit investment. Full article

The development of renewable energy has emerged as a cornerstone of sustainable economic transformation, offering a pathway to reduce carbon dependence and enhance long-term energy security. As a result, this study examines the influence of supply chain digitalization, economic growth, and environmental stringency policies on renewable energy consumption (REC) across 33 OECD countries from 2000 to 2021. Using the Method of Moments Quantile Regression (MMQR) approach, the research provides robust, distribution-sensitive insights into how these factors shape renewable energy dynamics. In addition to the main variables, financial development and economic globalization were included as control variables to capture broader macroeconomic effects. The empirical results reveal that supply chain digitalization exerts a negative and consistent influence on REC across all quantiles, suggesting that technological advancement within supply chains may still be heavily dependent on non-renewable energy inputs. Conversely, environmental stringency policies demonstrate a positive and significant impact on REC at all quantiles, indicating that stricter environmental regulations effectively drive the transition toward cleaner energy sources. However, the effect of economic growth varies across quantiles, reflecting a nonlinear relationship—fostering renewable energy use in some instances while increasing conventional energy demand in others. Among the control variables, economic globalization enhances REC, implying that greater international integration facilitates technology transfer and access to green innovations. In contrast, financial development negatively affects REC, suggesting that current financial systems may still prioritize fossil fuel investments. Overall, the study emphasizes the need to align digital transformation strategies, financial reforms, and policy frameworks to strengthen renewable energy development and ensure a sustainable, low-carbon future across OECD nations. Full article

Recent studies in the Romanian Western Carpathians have revealed increasing socio-demographic fragility in rural areas and small towns, driven by depopulation, population aging, and declining living standards. These trends stem from the legacy of forced collectivization and industrialization (1950–1990) and the post-1990 transition, which triggered extensive out-migration and the erosion of local socio-economic structures. This study examines the fragility of human communities in the Trascău Mountains in order to evaluate spatial, demographic, and economic recovery dynamics and to assess settlement vulnerability as a major obstacle to sustainable regional development. Fragility was measured using indicators of population density and change, age structure, accessibility, and socio-demographic dynamics, based on comparative data for the interval of 1977–2021. These variables were integrated into a composite development index (Id), derived from twelve indicators covering demography, economy, infrastructure, and living standards, enabling the hierarchical classification of settlements by degree of vulnerability. The methodological framework combines empirical and analytical methods, statistical, cartographic, bibliographic, and field-based analyses within evolutionary, structural–functional, and typological perspectives. The results identify the main drivers of decline, quantify their impacts, and outline development prospects and policy directions for reducing territorial disparities. Overall, fragile settlements emerge as critical pressure points that undermine sustainability, intensify regional instability, and increase risks related to migration and social cohesion. Full article

Green total factor productivity (GTFP), as an important indicator considering both economic development and environmental protection, has prompted countries around the world to actively explore ways to improve it in the context of the global transition to a green economy. The Low-Carbon City Policy (LCCP) implemented by the Chinese government, along with the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ), which serve as key carriers of green regulation and digital innovation, respectively, play an important role in improving green total factor productivity (GTFP) and achieving high-quality economic development. This study aims to deeply explore whether there is a collaborative enabling effect of the Low-Carbon City Policy (LCCP) and the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ) on green total factor productivity (GTFP) and to reveal the internal mechanism by which they improve GTFP through green technological innovation and industrial agglomeration. Specifically, based on the panel data of 269 prefecture-level cities in China from 2006 to 2022, a “dual-pilot” policy is constructed through LCCP and NBDCPZ, and a multi-period difference-in-differences model (DID) is used to evaluate the collaborative effect of the “dual-pilot” policy on GTFP. The results show that the “dual-pilot” policy has a significant collaborative effect on green total factor productivity (GTFP), and its enabling effect is more obvious than that of the “single-pilot” policy. These conclusions still hold after a series of endogeneity and robustness tests. Mechanism analysis shows that the “dual-pilot” policy can also improve green total factor productivity (GTFP) through green technological innovation and industrial agglomeration. Heterogeneity analysis reveals that the collaborative enabling effect of the “dual-pilot” policy is influenced by geographical location and population density. Specifically, the “dual-pilot” policy significantly promotes green total factor productivity (GTFP) in coastal cities and those with high population density. These research results provide a scientific basis for formulating green development policies in China and other countries, as well as a direction for subsequent research on the collaborative enabling effect of multiple policies. Full article

The accelerating low-carbon transition requires decision-support approaches capable of addressing complex, interdependent sustainability challenges across multiple sectors. While Multi-Criteria Decision-Making (MCDM) techniques are gaining popularity in assessing sustainability within energy and agricultural systems, their current application remains fragmented, sector-focused, and poorly aligned with the fundamental system characteristics of uncertainty, circularity, and social equity. This Perspective employs a systematized conceptual analysis to integrate different MCDM techniques, methodological trends, and integration challenges in energy and agricultural systems. Through a literature review, this work provides a critical view of the predominant structural deficiencies, which stem from methodological isolation, the use of disparate and heterogeneous datasets, ad hoc treatment of uncertainty, and the lack of incorporation of the circular economy (CE) and equity dimensions in the analysis. Given the presence of multifunctionality, circularity, climate sensitivity, and strong social characteristics, the analysis underscores that agriculture is a prime candidate to serve as a system-level testbed for the development of integrated MCDM frameworks. Based on this analysis, the paper articulates the fundamental characteristics of next-generation MCDM frameworks that are cross-sectoral, flexible, adaptive, uncertainty-resilient, and actionable. In doing so, it prioritizes integrated approaches that combine MCDM with life cycle assessment (LCA), data analytics, and nexus modelling. This paper stresses that structural deficiencies need to be addressed for MCDM to evolve from sectoral and fragmented analytical frameworks to cohesive decision-support systems that can guide energy and agricultural systems transitions towards equity, circularity, and climate change adaptation. As a perspective, this paper does not aim to provide empirical validation but instead articulates conceptual design principles for next-generation MCDM frameworks that integrate uncertainty, circularity, and social equity across energy and agricultural systems. Full article

The mobility of data factors and the adoption of a collaborative innovation framework are key drivers influencing the gaps in total factor productivity (TFP) among enterprises in the digital economy. Using panel data from Chinese A-share listed companies between 2006 and 2022, this study empirically demonstrates how data factor flow reduces TFP gaps. The findings reveal that data factor flow enhances TFP convergence by facilitating knowledge diffusion, improving information transmission, and boosting innovation efficiency. However, the heterogeneity in enterprise RD efforts limits this convergence effect, highlighting the importance of collaborative innovation. The study further shows that the impact of data factor flow is more significant in smaller, privately owned enterprises in the eastern regions and in industries with low to high technology intensity and high market concentration. Key insights include (1) a positive synergy between government data openness policies and enterprise data flow, which reinforces the narrowing of TFP gaps; (2) a nonlinear relationship between data flow and TFP gaps, suggesting an optimal range for its maximum impact. The study concludes that an integrated framework optimizing both data governance and collaborative innovation ecosystems can foster innovation diffusion and support productivity-based competition. These findings provide valuable insights for innovation policy formulation and strategic decision-making in the digital economy. Full article

The development of energy systems toward a decarbonized economy is increasingly constrained not only by technological challenges, but also by deficiencies in the organization, coordination, and governability of sustainable financing. This study aims to substantiate an integrated conceptual model and a multi-level governance framework for the sustainable financing mechanism of energy system development under decarbonization, ensuring the alignment of financial instruments with transition strategies, performance indicators, and feedback mechanisms. The methodology combines a bibliometric analysis of Scopus-indexed journal publications with an examination of international statistical and analytical data produced by leading global organizations, complemented by systemic, institutional, and comparative analytical approaches. The bibliometric analysis was conducted in 2025 and covered peer-reviewed articles published during 2017–2025, while empirical financial indicators were synthesized for the most recent available period of 2022–2024 using comparable time-series data reported by international institutions. The results indicate that despite global energy investments reaching approximately $3 trillion in 2024—nearly $2 trillion of which was allocated to clean energy technologies—a persistent annual financing gap for climate change mitigation in the energy sector remains. Moreover, to remain consistent with the Net Zero trajectory, investments in clean energy must increase by approximately 1.7 times by 2030. The synthesis of contemporary research and empirical evidence reveals a predominance of studies focused on individual green and transition finance instruments, accompanied by persistent fragmentation between financial flows, governance structures, and measurable decarbonization outcomes. To address this gap, the paper proposes a conceptual model that interprets sustainable finance as a governed system rather than a collection of isolated instruments, together with a multi-level governance framework integrating strategic (policy), sectoral, and project-level decision-making with systems of key performance indicators, monitoring, and feedback. The findings demonstrate that the effectiveness of sustainable financing critically depends on the coherence between financial instruments, governance architectures, and decarbonization objectives, which ultimately determines the capacity to translate mobilized capital into tangible energy infrastructure modernization and measurable emissions reductions. The proposed approach provides a practical foundation for improving energy transition policies and investment strategies at both national and supranational levels. Full article

The natural gas sector, as a pivotal transition fuel, is fundamentally constrained by the “Energy Trilemma”—the intertwined and often competing goals of energy security, affordability, and sustainability. Current research predominantly focuses on the demand side, leaving a significant gap in understanding the synergistic dynamics within production regions, which are critical to resolving this trilemma at its source. To address this gap, this study constructs a “Safety–Economy–Green” (S-E-G) evaluation framework aligned with the trilemma’s dimensions. Utilizing panel data (2011–2021) from four major Chinese natural gas production regions (Sichuan, Chongqing, Shaanxi, and Shanxi). By integrating the Entropy Weight Method, a Coupling Coordination Model, and Kernel Density Estimation, it delineates the system’s synergistic dynamics from both temporal and regional perspectives. The key findings are as follows: (1) Significant disparities and polarization are observed in the S and G dimensions, while the E dimension shows a narrowing gap, with its peak height increasing by 177.8% and bandwidth shrinking by 64.2%. G has emerged as a constraint on overall system coupling coordination. The persistently high coupling degree—rising from 0.87 in 2011 to 0.97 in 2021 while consistently exceeding the coordination degree, which increased from 0.45 to 0.62—underscores the continued need for improvement in synergistic development. (2) The coupling coordination degree of the S-E-G system underwent a three-stage evolution: rapid improvement (2011–2013, from 0.36 to 0.58 at 7.3% annually), fluctuating adjustment (2014–2017, between 0.58 and 0.66), and finally high-level stability (2018–2021, stabilizing at 0.76–0.80). (3) Obvious regional differentiation exists: Sichuan achieved a moderate level of 0.76 by 2021, Shaanxi maintained primary coupling coordination (0.6–0.7), while Chongqing and Shanxi remained marginal, fluctuating between 0.4 and 0.6. Enhancing subsystem coordination and implementing differentiated pathways are therefore essential for these regions’ sustainable development. The study suggests promoting the sustainable development of natural gas production regions by enhancing subsystem coordination and exploring differentiated pathways, thereby providing practical guidance for the energy transition of resource-based regions. Full article