Search Results (96)

This study examines the relationship between digitalisation and eco-innovation across countries, with a particular focus on the role of digital government and digital standardisation. Using cross-country data for 2022, eco-innovation is proxied by environment-related patenting activity, while digitalisation is measured using the United Nations E-Government Development Index (EGDI). Employing a combination of ordinary least squares, population-weighted regressions, spline specifications, and quantile regressions, we document three main findings. First, digitalisation is positively and robustly associated with eco-innovation across countries. Second, the relationship is non-linear, with marginal effects that strengthen at higher levels of digital development, suggesting important complementarities between digital capabilities and national innovation systems. Third, the association between digitalisation and eco-innovation is heterogeneous across the distribution of eco-innovation, with particularly strong associations observed among countries with intermediate levels of innovative activity. Taken together, these findings suggest that digitalisation is systematically associated with eco-innovation across countries and indicate the potential relevance of digital governance and digital standardisation to sustainable technological change. Full article

This study delves into how the literature conceptualizes banking efficiency as a capability shaping sustainability-oriented pathways under conditions of systemic uncertainty, including recurrent economic–financial disruptions and geopolitical shocks. Using records indexed in the Web of Science Core Collection, the study combines bibliometric mapping with conceptual structuring to examine publication dynamics, collaboration networks, and the thematic evolution of research linking bank efficiency, green finance intermediation, sustainable digital innovation, and risk governance. The study reveals a multidimensional knowledge base organized around two converging streams: (i) research on efficiency, stability, and crisis transmission emphasizing intermediation quality, performance under stress, and prudential responses; and (ii) sustainability and innovation scholarship focusing on how financial systems enable eco-innovation diffusion and low-carbon transition through capital allocation, governance mechanisms, and digitally enabled transformation. Across these streams, banking efficiency is increasingly discussed not merely as a performance ratio, but as a strategic capability that becomes particularly salient in crisis environments: it can reduce intermediation frictions when funding conditions tighten, strengthen screening and monitoring of green projects amid elevated uncertainty, and support the continuity and scaling of eco-innovations by improving decision speed and resource allocation through digital tools. Collaboration patterns indicate growing interdisciplinary engagement—especially among European and Asian institutions—where crisis, sustainability, and innovation perspectives are integrated into systems-based approaches to green finance. Building on these insights, the article outlines a research agenda oriented toward innovation outcomes in turbulent contexts, emphasizing (a) measurement strategies that connect efficiency to eco-innovation diffusion and adoption rates during stress periods; (b) comparative analyses of how policy incentives and green market signals interact with bank efficiency across crisis episodes; and (c) hybrid methodological designs combining econometric identification, network analytics, scenario-based stress framing, and AI-enabled analytical tools to capture nonlinear dynamics in efficiency–innovation linkages. Overall, the study clarifies how banking efficiency may condition the capacity of financial institutions to sustain green investment intermediation and advance eco-innovation pathways when uncertainty is systemic rather than episodic. Full article

This study investigates policy-relevant pathways for achieving a green transition by examining the impact of energy diversification (ED) and economic complexity (EC) on load capacity factors (LCFs) across the Organization for Economic Co-operation and Development (OECD) countries from 1999 to 2021. To capture structural heterogeneity in environmental performance, this study develops a novel Energy Mix Concentration Index (EMCI), based on the Herfindahl–Hirschman Index, and employs Method of Moments Quantile Regression (MMQR), allowing for distribution-specific analysis beyond conventional mean-based estimators. The empirical framework integrates three distinct dimensions of ECI trade-based (ECI-Trade), technology-based (ECI-Technology), and research-based (ECI-Research) alongside GDP per capita and its squared term to test the validity of the load capacity curve (LCC) hypothesis. The findings of MMQR confirm the validity of the LCC hypothesis in OECD countries. ED is found to exert a statistically significant downward pressure on LCFs across all quantiles, with particularly strong adverse effects in environmentally constrained economies, highlighting the relevance of Jevons’ paradox when diversification is not explicitly oriented toward low-carbon energy sources. Regarding EC, research-driven complexity positively affects LCFs, especially in lower LCF quantiles, by facilitating structural shifts toward cleaner, knowledge-intensive activities. In contrast, trade- and technology-based ECI reduce LCFs due to scale effects, supply-chain emissions, and rising energy demand, except in high-performing economies where strong institutions, stringent environmental regulations, and advanced renewable systems enable complexity-induced eco-innovation. These results underscore that innovation and diversification are not environmentally neutral and must be strategically directed. Overall, this study demonstrates that a successful green transition requires more than ED and economic upgrading alone. Effective policy pathways must combine targeted low-carbon energy strategies, mission-oriented research and development, and demand-side regulatory frameworks to ensure that EC reinforces, rather than undermines, environmental sustainability. The findings offer nuanced guidance for OECD policymakers seeking to align post-pandemic recovery strategies with long-term ecological resilience. Full article

Addressing the growing need for sustainable innovation in PVC materials, this study presents an illustrative framework that develops and demonstrates an ontological system that integrates lifecycle simulation using Granta EduPack, systematic literature analysis (including bibliometric, thematic, and content analytics) of peer-reviewed publications, and Protégé-based semantic reasoning, and their combination, in a holistic manner. Material and use-phase data for PVC, HDPE, PP, PET, and FRP cooling-tower components were sourced from ANSYS Granta EduPack Level-3 Polymer Sustainability 2023 R2 Version; 23.2.1, and a systematic analysis of the literature was then encoded as ontology classes, properties, and individuals following the Seven-Step ontology development method. Eco-audit simulations, standardised to a functional unit of 1 kg cooling tower fill material, reveal that the use phase dominates environmental impact (67 MJ primary energy, ~80% of total lifecycle), while material production and end-of-life recycling contribute ~15% and credits of ~900 MJ and 28 kg CO₂ via recycling offsets. Ontology reasoning with corrected SWRL rules and SPARQL queries classifies VirginPVCRef and PVC10ES as strong structural materials (tensile strength ≥ 40 MPa), identifies PVCRH40 as high-moisture-risk (water absorption > 0.10 g/g), and ranks hydro-thermal dechlorination (recyclability 0.90) over mechanical recycling (0.55). A systematic analysis of 40 Scopus-indexed publications (2015–2025) highlighted key themes in recycling technologies, LCA emissions, additive toxicity, ontology frameworks, machine learning integration, circular economy policy, and cooling-tower applications. Demonstrated via a simulation-based cooling-tower case study, hybrid PVC-FRP designs yield the highest justified Material Sustainability Performance Index (MSPI), outperforming PVC-only and FRP-only alternatives. This framework provides a conceptual decision-support tool for exploring PVC material optimisation, illustrating pathways to enhancing circularity and environmental responsibility in industrial applications. The proposed framework is, therefore, not intended as a validated decision-support tool, nor does it claim analytical optimisation or predictive performance but rather serves as a method of illustration that shows how domain knowledge can be formally structured using ontology principles linked to simulation representations, and that was examined for internal logical consistency. Full article

The aim of this article is to identify and systematize the principal research directions in sustainable strategic management (SSM) at the intersection of eco-innovation and business performance. Despite the growing prominence of sustainability in management scholarship, systematic understanding of how SSM, eco-innovation, and business performance are connected in the academic literature remains limited. In particular, it is unclear whether this intersection constitutes a coherent research domain or instead reflects a set of loosely related and fragmented lines of inquiry. To address this gap, the study combines bibliometric analysis and science mapping of 181 Scopus-indexed publications (2006–2024) with a PRISMA-guided scoping review of five core papers that explicitly link SSM, eco-innovation, and business performance. VOSviewer was used to identify thematic clusters and structural gaps, including missing or weak linkages between eco-innovation and different dimensions of business performance. Building on these findings, the article proposes a dual-path conceptual model: (1) a mediated path in which eco-innovation functions as a transmission mechanism between SSM and multidimensional business performance, and (2) a direct path linking SSM to business performance without mediation. The model further distinguishes between internal organizational conditions, which predominantly support the direct path, and external business environment factors, which are critical in enabling the mediated path through eco-innovation. The main contributions are as follows: (a) a structured mapping of the SSM–eco-innovation research field and its emerging thematic architecture; and (b) a conceptual model specifying the dual role of eco-innovation in shaping business performance outcomes. The study also outlines implications for theory, managerial practice, and public policy, particularly in terms of how organizations and their environments influence the effectiveness of different strategic sustainability pathways. The proposed framework should be interpreted as an evidence-informed conceptual model derived from bibliometric patterns and focused qualitative synthesis, rather than as a statistically validated causal model. Full article

This study developed a biodegradable dissolvable face mask incorporating liposomal kojic acid (KA) and licochalcone A from licorice extract (LE) to enhance skin delivery and performance. Liposomes were prepared by thin-film hydration method. The film matrix, composed of PVA/PVP/PEG400/HA, was optimized using factorial design to achieve suitable mechanical strength and rapid dissolution. The optimized mask, containing liposomal KA (1% w/v) and licochalcone A (0.025% w/v), was evaluated for antioxidant activity, ex vivo skin deposition, and short-term efficacy (Approval from the Institutional Review Board of Silpakorn University, Thailand; Ethics Approval No. REC 67.1001-146-7726/COA 68.0320-013 Date of registration: 20 March 2025). The optimized liposomes exhibited a mean particle size of 66–72 nm, entrapment efficiency above 65%, and a zeta potential of −12.5 mV (licochalcone A) and −1.67 mV (KA). Liposomal licochalcone A and KA showed potent antioxidant activity compared to their native forms. The optimized film dissolved within approximately 15 min on moist skin and showed favorable handling properties. Ex vivo studies revealed significantly higher skin deposition of both KA and licochalcone A from the liposomal mask compared with free and liposomal dispersions (p < 0.05). In a 7-day clinical evaluation, the mask significantly improved skin hydration and reduced melanin index (p < 0.05). No irritation or adverse reactions were observed, and user satisfaction was high. This liposomal dissolvable mask offered an effective, well-tolerated, and eco-friendly approach to enhancing skin brightness and hydration, supporting its potential as a sustainable cosmeceutical innovation. Full article

China’s National Eco-Industrial Parks (NEIPs) represent a significant policy intervention designed to achieve the synergistic reduction in pollution and carbon emissions. While previous studies have examined the impacts of NEIPs on pollution and carbon emissions in isolation, research on their synergistic reduction is still limited. This study constructs a Carbon-Pollution Co-Reduction Index (CPCRI) with weights determined by the entropy weight method (EWM) to capture the joint performance of emission intensities. By applying a staggered difference-in-differences (SDID) model to city-level panel data from the Yangtze River Delta between 2003 and 2021, the study finds that NEIPs significantly improve the CPCRI of cities where NEIPs are located by 2.30 percentage points. This positive effect exhibits a time lag, becoming statistically significant three years after establishment and strengthening thereafter. Mechanism analyses indicate that the synergistic reductions are driven by technological innovation and reduced energy intensity, while heterogeneity analyses reveal that the policy effect is more pronounced in economically developed provinces and larger cities but has diminished in recent years. Then, a coupling coordination degree (CCD) is integrated to construct a new index to capture both joint performance and synergy between reductions. These findings provide robust empirical support for NEIPs as a practical policy tool to achieve sustainable industrial transformation in the Yangtze River Delta. Full article

As an important renewable building material, wood’s flammability significantly limits its application range. This study addresses the environmental pollution issues associated with traditional flame retardants by developing an eco-friendly flame retardant system based on natural biomaterials. Utilizing layer-by-layer self-assembly techniques, sodium phytate, chitosan, sodium alginate, and sodium methyl silicate were sequentially deposited onto the wood surface to construct a multifunctional composite coating. A multifunctional composite coating was constructed on wood surfaces through layer-by-layer self-assembly technology, involving successive deposition of phytic acid sodium, chitosan, sodium alginate, and methyl silicate sodium. Characterization results indicated that the optimized sample WPCSMH achieved a limiting oxygen index of 34.0%, representing a 12% increase compared to untreated wood. Cone calorimetry tests revealed that its peak heat release rate and total heat release were reduced by 57.1% and 25.3%, respectively. Additionally, contact angle measurements confirmed its excellent hydrophobic properties, with an initial contact angle of 111°. Mechanistic analysis reveals that this system significantly enhances flame retardant performance through a synergistic interaction of three mechanisms: gas phase flame retardancy, condensed phase flame retardancy, and free radical scavenging. This research provides a sustainable and innovative pathway for developing environmentally friendly, multifunctional wood-based composites. Full article

Establishing a mechanism for ecological product value realizing (EPVR) is a critical component of China’s ecological civilization strategy, aimed at translating the concept that “lucid waters and lush mountains are invaluable assets” into actionable economic policies. Although central government investments in the form of project for EPVR have increased significantly, surpassing CNY 700 billion by 2024, studies rarely focus on these projects and how to evaluate them. Evaluating the performance of EPVR projects is essential for optimizing resource allocation, enhancing project accountability, and ensuring the sustainable realization of ecological, economic, and social values. This study innovatively defines the conceptual connotation of EPVR projects and constructs a comprehensive performance evaluation system based on a “benefit-cost” analysis, comprising a multi-dimensional indicator system, quantifiable calculation methods, and explicit evaluation criteria. As water source protection projects are typical EPVR projects, the comprehensive water environment management project of Hongfeng Lake is selected for an in-depth empirical study. The results reveal that (1) the total annual benefits amount to CNY 923.66 million, dominated by ecological benefits (84.04%); (2) with an investment of CNY 1194.66 million, the project yields a net loss and a moderate performance index (PCPI = 0.77); (3) the project performance is primarily affected by weak economic value conversion stemming from restrictive zoning policies and underdeveloped market mechanisms for ecological services; and (4) integrated development pathways—such as ecotourism, eco-aquaculture, and ecological branding—are proposed to enhance the long-term sustainability of the project. The Hongfeng Lake case establishes a replicable framework for global assessment of analogous projects and delivers actionable insights for enhancing benefit–cost ratios in public ecological initiatives, with costs confined to data collection, modeling, and validation. Therefore, this study contributes a quantifiable and reproducible tool for the full lifecycle management of EPVR projects, thereby facilitating more informed government decision-making. Key findings reveal the following: (1) A comprehensive “Benefit-Cost” performance evaluation framework, pioneered in this study and tailored specifically for individual EPVR projects, surpasses regional-scale accounting methodologies like Gross Ecosystem Product (GEP). (2) A novel consolidated metric (PCPI) is introduced to integrate ecological, economic, and social dimensions with cost input, thus enabling direct cross-project comparison and classification. (3) The framework operationalizes evaluation by providing a detailed, adaptable indicator system with explicit monetization methods for 26 distinct benefits, thereby bridging the gap between theoretical value accounting and practical project assessment. (4) The empirical application to a drinking water source protection project addresses a critical yet understudied category of EPVR projects, offering insights into “protection-oriented” models. Full article

Rare earth elements (REE) are vital for renewable energy, electronics, and advanced technologies; however, the process-related evolution of REE research has not been systematically quantified. This study conducts the first large-scale bibliometric analysis of 76,768 REE-related publications (1975–2024) from Web of Science, using the Cross-Disciplinary Publication Index (CDPI) and Technology–Economic Linkage Model (TELM). Results reveal three development phases: publication growth from <300 (1975–1990) to >5000 after 2008, driven by China’s export restrictions and the global clean energy transition; China leads with 24.1% of publications, followed by the U.S. (11.7%) and Germany (6.4%). Interdisciplinary mapping identifies materials science as the central field (CDPI = 0.81) linked to nanotechnology (0.75) and environmental science (0.66). Four thematic clusters dominate: (i) deposit geology, (ii) material applications, (iii) green extraction technologies, and (iv) circular economy strategies. Recent emphasis on sustainable practices and unconventional sources—such as phosphorites, bauxite, coal fly ash, and urban mining—reflects a shift toward green innovation. The findings guide policies to diversify REE supply through unconventional deposits (~50 Mt coal-hosted REE), eco-friendly extraction, and recycling. Future priorities include AI-driven exploration, lifecycle assessment of secondary sources, and stronger global collaboration to secure resilient, sustainable REE supply chains. Full article

In developing countries, technology-based startups (TBSs) play a vital role in driving innovation, and they significantly contribute to the generation of jobs and economic development. However, despite their importance, startups have a high failure rate worldwide, and a major contributing factor is a lack of funding. The objective of this study is to compare the existing financing mechanisms in Ethiopia, Uganda, and Kenya and determine the relative position of Ethiopia in the financing landscape. This study was based on resource-based theory and signaling theory. A desk research methodology was employed, and a total of 70 sources were reviewed. The data sources include academic literature, publications from the World Bank, local reports, government policies of the three nations, articles published in reputable journals, and global database indexes. Articles were also selected based on their relevance to the research question and the credibility of the publication. The comparison was carried out based on identifying similarities and differences in economic indicators, the innovation performance of the countries, the innovation eco-system, the types of existing financing mechanisms in each country, and various government policies and initiatives. We also validated our findings by cross-checking information from multiple sources to avoid bias. The results reveal that Ethiopia is lagging behind in most of the parameters set for comparison, while its neighbors, Uganda and Kenya, have a relatively better status in general. Finally, this study has theoretical and practical implications. Full article

The rapid growth of Waste Electrical and Electronic Equipment (WEEE) in the European Union highlights the need for a rigorous understanding of its long-term dynamics and the role of innovation in shaping its trajectory. This study investigates how innovation influences the dynamics of WEEE generation in the European Union. We develop an innovation-adjusted mathematical model of e-waste as a stock flow system and prove the existence and global stability of a unique positive equilibrium. The model analytically generates an environmental Kuznets-type turning point and shows that innovation reduces waste accumulation by accelerating effective depreciation. To link the theoretical results with empirical patterns, we embed the model in a STIRPAT panel specification using annual data for 27 EU member states from 2013 to 2023, where EU Eco-innovation Index (EEI) serves as a composite index which directly captures policy-driven green technology and circular economy activities, aligning precisely with our theoretical framework. We also extend the quasi-demeaning transformation to panels with correlated shocks and establish its consistency under a factor structured error process. The empirical estimates confirm a positive effect of income on WEEE at lower development levels and a negative coefficient on its squared term, consistent with an inverted U pattern, while innovation is associated with lower waste intensity. These findings demonstrate how mathematical modeling can strengthen the interpretation of macro panel evidence on circularity and provide a basis for future optimization of innovation driven sustainability transitions. Full article

The automotive industry is undergoing a transformative shift toward sustainability, driven by stringent environmental regulations, rising energy demands, and the pursuit of enhanced performance and efficiency. Lubricating materials play a pivotal role in reducing friction, wear, and energy losses in automotive systems, yet conventional lubricants, primarily petroleum-based, pose significant ecological and operational challenges. This review examines the development and performance of sustainable and advanced lubricant including bio-based oils, synthetic esters, nanolubricants, and ionic/solid lubricants for automotive applications. Drawing on tribological principles and recent advances in materials science, the article categorizes these lubricants based on source, chemical structure, and tribological behavior. A comparative framework is introduced to evaluate key performance indicators such as viscosity index, thermal stability, oxidation resistance, biodegradability, and compatibility with modern engine designs. The review also highlights emerging trends, including nanotechnology-based additives, green synthesis techniques, and novel antioxidant systems that enhance lubricant functionality and lifespan. Furthermore, a strategic research roadmap is proposed, outlining short-, medium-, and long-term priorities that integrate technical, environmental, and economic dimensions. By bridging foundational science with practical innovation, this article aims to guide researchers, manufacturers, and policymakers toward the adoption of high-performance, eco-compatible lubricants that support the transition to cleaner and more efficient mobility systems. Future directions and challenges in scaling, cost-effectiveness, and lifecycle assessment are discussed to guide innovation in this critical domain. Full article

Under the national “dual-carbon goal” and the pressing demand for sustainable development, eco-city construction and carbon reduction have become critical issues on China’s urban development agenda, closely aligned with the United Nations Sustainable Development Goals (SDGs). However, most studies focus on regional assessments, lacking national-scale evaluations and spatial heterogeneity analysis of obstacles. This study analyzes 280 Chinese cities using a multi-level evaluation system. Analytic hierarchy process (AHP) and entropy weight methods determine index weights, while the comprehensive evaluation method assesses ecological levels. The obstacle diagnosis model identifies key obstacle factors, and geographically weighted regression (GWR) analyzes spatial heterogeneity, computing carbon intensity to explore relationships with eco-cities development. The findings reveal that (1) the ecological level of Chinese cities exhibits a regional pattern of “high in the east, low in the west”; (2) the primary index-level obstacle factors include total per capita water resources, per capita green space area, college full-time faculty per 10,000 people, the proportion of tertiary industries in gross domestic product (GDP), and college students per 10,000 people; at the element level, the main obstacles are environmental bases, social services, economic potential, and innovative capacity; (3) the GWR model reveals that eastern regions should increase water resources, central regions expand green space, and western and northeastern regions enhance innovative capacity and social services to foster balanced development; and (4) carbon intensity follows a “low in the east, high in the west” pattern, with eco-cities scores significantly negatively correlated with carbon intensity (r = −0.235, p < 0.01). This study provides the first comprehensive national-scale evaluation of eco-cities development, providing reference for the construction of eco-cities. Full article

Retrieving and predicting summer average near-surface air temperature (SANSAT) across China remain challenging due to the country’s complex topography and heterogeneous vegetation cover. This study proposes an innovative deep learning framework that incorporates vegetation regionalization to achieve high-precision spatiotemporal temperature retrieval and prediction. Using MODIS land surface temperature, vegetation indices, weather station data (2000–2019) and other relevant datasets, we first apply GeoDetector to identify key influencing factors (e.g., nighttime surface temperature, elevation, vegetation index, and population density) within each vegetation region. Based on these findings, we develop a deep neural network (DNN) model, which achieves high accuracy in SANSAT retrieval (with validation R² ranging from 0.90 to 0.97 and RMSE from 0.46 to 0.64 °C). Results indicate that temperature variations in the eastern monsoon region are primarily influenced by human activity and topography, whereas natural factors dominate in the western regions. Subsequently, using a Long Short-Term Memory (LSTM) network with an optimal seven-year time step, we predict SANSAT for 2020–2023, achieving R² values of 0.71 in training and 0.69 in testing, which confirms the model’s high reliability in SANSAT prediction. The core innovation of this work lies in its vegetation-regionalized deep learning approach, which explicitly addresses landscape heterogeneity by customizing models to specific eco-climatic zones, thereby quantifying human-nature interactions more effectively than traditional, spatially uniform methods. This framework enhances the understanding of summer temperature dynamics and provides valuable spatial data to support applications in agricultural disaster prevention, ecological conservation, and carbon neutrality. Future research will incorporate multi-seasonal data and enhance the spatiotemporal resolution to further improve NSAT modeling. Full article