Search Results (274)

The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, and highlighting methodological trends at this nexus. A dataset of 268 peer-reviewed publications (2014–June 2025) was retrieved from the Web of Science Core Collection, filtered by the Business Economics category. Analytical techniques employed include Bibliometrix in R, VOSviewer, and science mapping tools such as thematic mapping, trend topic analysis, co-citation networks, and co-occurrence clustering. Results indicate an annual growth rate of 53.31%, with China leading in both productivity and impact, followed by Vietnam and the United Kingdom. The most prolific affiliations and authors, primarily based in China, underscore a concentrated regional research output. The most relevant journals include Energy Economics and Finance Research Letters. Network visualizations identified 17 clusters, with focused analysis on the top three: (1) Emission, Health, and Environmental Risk, (2) Institutional and Technological Infrastructure, and (3) Green Innovation and Sustainable Urban Development. The methodological landscape is equally diverse, with top techniques including blockchain technology, large language models, convolutional neural networks, sentiment analysis, and structural equation modeling, demonstrating a blend of traditional econometrics and advanced AI. This study not only uncovers intellectual structures and thematic evolution but also identifies underdeveloped areas and proposes future research directions. These include dynamic topic modeling, regional case studies, and ethical frameworks for AI in sustainable finance. The findings provide a strategic foundation for advancing interdisciplinary collaboration and policy innovation in green AI–finance ecosystems. Full article

Cities are the growth engines responsible for shaping the global economy, major contributors to climate change, and are significantly affected by it. However, the United Nations adopted the Sustainable Development Goals (SDGs) to make these cities and human settlements inclusive, safe, resilient, and sustainable. Yet, the rapid and unplanned urban expansion exacerbates various environmental challenges and reduces green cover in urban areas. To address these issues and meet the SDGs, stakeholders need to emphasise and optimise urban spaces. This study investigates the borough-level analysis of green spaces and human exposure to green spaces across London using satellite-derived datasets on vegetation and socio-economic factors to examine the variations in urban vegetation cover and urban population exposure to vegetation cover between 2017 and 2024. This study highlights the spatial disparity in green space coverage and exposure to green space between the inner and outer boroughs of London. The methodology used here suggests an average loss of approximately 11 and 9 percent in green space coverage and green space exposure to population, respectively, between 2017 and 2024 across London boroughs. Full article

Smart cities leverage digital marketing to promote sustainability and build a distinctive global branding. Despite its growing significance, the role digital marketing in smart city development remains underexplored. This study aims to fill this gap by employing bibliometric analysis of 1908 articles indexed in the Scopus database (2000–2024), using the Bibliometrix R-Studio (version 1.4.1743) and VOSviewer (version 1.6.20). The analysis reveals two thematic clusters: (1) “Digital Innovation and Sustainability”, which emphasizes technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data for energy efficiency and green urban development; and (2) “Governance and Policy”, which highlights digital marketing’s role in enabling participatory governance, citizen engagement, and inclusive urban policies. Findings underscore that digital marketing is not only a strategic communication channel but also a driver of sustainable urban transformation. By synthesizing insights from urban planning, technology, and sustainability, this paper provides a novel perspective on the intersection of digital marketing and smart cities. The results provide valuable guidance for policymakers, city planners, and researchers to harness digital marketing in promoting sustainability and further develop the smart city concept. Full article

Water Supply and Distribution Networks (WSDNs) offer underexplored potential for energy recovery. While many studies confirm their technical feasibility, few assess the long-term operational compatibility and economic viability of such solutions. This study evaluates the energy recovery potential of the Brussels Capital Region’s WSDN using four years (2019–2022) of operational data. Rather than focusing on available technologies, the analysis examines whether the real behavior of the network supports sustainable energy extraction. The approach includes network topology identification, theoretical power modeling, and detailed flow and pressure analysis. The Brussels system, composed of a Water Supply Network (WSN) and a Water Distribution Network (WDN), reveals strong disparities: the WSN offers localized opportunities for energy recovery, while the WDN presents significant operational constraints that limit economic viability. Our findings suggest that day-ahead electricity markets provide more suitable valorization pathways than flexibility markets. Most importantly, the study highlights the necessity of long-term behavioral analysis to avoid misleading conclusions based on short-term data and to support informed investment decisions in the urban water–energy nexus. Full article

Food security constitutes a fundamental pillar of future sustainable development. A systematic evaluation of the impact of urban expansion on food security is critical to advancing the United Nations Sustainable Development Goals (SDGs), particularly “Zero Hunger” (SDG 2). Drawing on bibliographic data from the Web of Science Core Collection, this study employs the bibliometrix package in R to conduct a comprehensive bibliometric analysis of the literature on the “urban expansion–food security” nexus spanning from 1982 to 2024. The analysis focuses on knowledge production, collaborative structures, and thematic research trends. The results indicate the following: (1) The publication trajectory in this field exhibits a generally increasing trend with three distinct phases: an incubation period (1982–2000), a development phase (2001–2014), and a phase of rapid growth (2015–2024). Land Use Policy stands out as the most influential journal in the domain, with an average citation rate of 43.5 per article. (2) China and the United States are the leading contributors in terms of publication output, with 3491 and 1359 articles, respectively. However, their international collaboration rates remain relatively modest (0.19 and 0.35) and considerably lower than those observed for the United Kingdom (0.84) and Germany (0.76), suggesting significant potential for enhanced global research cooperation. (3) The major research hotspots cluster around four core areas: urban expansion and land use dynamics, agricultural systems and food security, environmental and climate change, and socio-economic and policy drivers. These focal areas reflect a high degree of interdisciplinary integration, particularly involving land system science, agroecology, and socio-economic studies. Collectively, the field has established a relatively robust academic network and coherent knowledge framework. Nonetheless, it still confronts several limitations, including geographical imbalances, fragmented research scales, and methodological heterogeneity. Future efforts should emphasize cross-regional, interdisciplinary, and multi-scalar integration to strengthen the systematic understanding of urban expansion–food security interactions, thereby informing global strategies for sustainable development. Full article

This study investigates the nonlinear effects of air pollution on urban entertainment consumption by analyzing daily PM₁₀ levels and movie box office data across 334 Chinese cities from 2012 to 2022, resulting in a total of 1,250,339 observations. Utilizing a two-way fixed effects model and threshold regression framework, we identify three key findings: (1) elevated PM₁₀ concentrations significantly reduce movie attendance, with a 1-unit increase decreasing consumption by 0.0797 units; (2) the inhibitory effect intensifies during weekends and holidays, reflecting heightened sensitivity to pollution during leisure periods; (3) threshold effects emerge, where PM₁₀ exceeding 0.0229 μg/m³ triggers a sharp decline in attendance, while temperature moderates this relationship, amplifying pollution’s negative impact. By integrating meteorological, environmental, and socioeconomic datasets, this research reveals substitution patterns between digital and offline entertainment under pollution stress. The results underscore the necessity for region-specific pollution mitigation strategies, cinema infrastructure upgrades, and dynamic pricing policies to counteract environmental disruptions. These insights advance the interdisciplinary nexus of environmental economics and cultural consumption, offering actionable pathways for sustainable urban development. Full article

Urban vitality, a critical emergent property of complex urban systems, is pivotal for sustainable, human-oriented urbanization. While land use mix (LUM) is recognized as a key strategy for shaping these systems, the systemic mechanisms through which its multifaceted dimensions influence urban vitality across spatio-temporal scales remain underexplored. This study examines the complex and spatially heterogeneous impacts of land use mix on 24 h urban vitality in Ningbo, China, conceptualizing the city as a dynamic socio-spatial system. By integrating multi-source data (Baidu Maps, POI, and OSM) and employing OLS and geographically weighted regression (GWR) models, we unravel these systemic relationships. Key findings include the following: (1) LUM significantly enhances urban vitality, acting as a crucial urban system configuration for both daytime and nighttime activity. (2) The efficacy of LUM stems more from systemic interconnections—convenient access to adjacent spaces (proximity) and functional coordination among diverse land uses—than mere compositional diversity, emphasizing the importance of interrelated elements within the urban fabric. (3) The system’s response to LUM exhibits significant spatial and temporal heterogeneity; proximity’s impact is most variable, while diversity and coordination effects are more stable, underscoring the dynamic and context-dependent nature of these interactions. (4) System-adaptive strategies are crucial: newly developed urban areas benefit from foundational infrastructure and land use diversity (system inputs), while revitalizing older towns requires optimizing spatial accessibility and functional coordination (enhancing existing system linkages). These findings advance the theoretical systems-based theoretical understanding of the LUM–vitality nexus while offering practical insights for urban planners and policymakers. Full article

Automated external defibrillator resources (AEDRs) are the crux of out-of-hospital cardiac arrest (OHCA) responses, enhancing safe and sustainable urban environments. However, existing studies failed to consider the nexus between built environment (BE) features and AEDRs. Can explainable machine-learning (ML) methods reveal the BE-AEDR nexus? This study applied an Optuna-based extreme gradient boosting (OP_XGBoost) decision tree model with SHapely Additive exPlanations (SHAP) and partial dependence plots (PDPs) aiming to scrutinize the spatial effects, relative importance, and non-linear impact of BE features on AEDR intensity across grid and block urban patterns in Tianjin Downtown, China. The results indicated, that (1) marginally, the AEDR intensity was most influenced by the service coverage (SC) at grid scale and nearby public service facility density (NPSF_D) at block scale, while synergistically, it was shaped by comprehensive accessibility and land-use interactions with the prioritized block pattern; (2) block-level granularity and (3) non-linear interdependencies between BE features and AEDR intensity existed as game-changers. The findings suggested an effective and generalizable approach to capture the complex interplay of the BE-AEDR and boost the AED deployment by setting health at the heart of the urban development framework. Full article

Global urbanization and climate change are intensifying challenges in the sustainable management of the Food–Energy–Water (FEW) system. This study introduces a multi-objective optimization framework that redefines urban spaces through a dual rooftop-ground hierarchy, interlinkage nodes for mapping material and energy flows, and the application of NSGA-II optimization to balance food production, energy output, and costs. The framework was applied to a case study area, generating non-dominated solutions with diverse resource-cost configurations. The findings revealed that optimal scenarios could meet 40.6% of local energy demands and exceed 102.9% of local grain demands, while maintaining economic viability. This approach bridges resource systems theory and spatial planning practice, providing economically viable pathways for high-density cities to transform into hybrid production-consumption spaces, effectively addressing the dual pressures of urbanization and climate change. Full article

Transportation infrastructure systems sit at the nexus of urban economic development and emission mitigation. The primary objective is to identify and quantify the key factors influencing CI, with a focus on both the conventional and emerging indicators through an innovative MLP neural network developed using the data of 20 Chinese transportation enterprises that have a business focus on the construction and operation sector from 2018 to 2022. The hypothesis is that integrating unconventional indicators—such as business model entropy and green revenue share—alongside traditional metrics can significantly enhance the predictive accuracy for CI. The results show that business model entropy explains 42.6% of carbon intensity (Cl) variability through green revenue diversification pathways, while emissions trading system (ETS) exposure accounts for 51.83% of decarbonization outcomes via price-signaling effects. The analysis reveals that a critical operational threshold–renewable energy capacity below 75% fails to significantly reduce Cl, and capex/revenue ratios exceeding 73.58% indicate carbon lock-in risks. These findings enable policymakers to prioritize industries with sub-75% renewable adoption while targeting capex-intensive sectors for circular economy interventions. The novelty of this work lies in the application of advanced machine-learning techniques to a comprehensive, multi-source dataset, enabling a nuanced analysis of CI drivers and offering actionable insights for policymakers and industry stakeholders aiming to decarbonize transport infrastructure. Full article

Urban green spaces (UGSs) play a pivotal role in sustaining the livelihoods of urban dwellers. This study sought to explore the impact of UGSs on livelihoods in Bulawayo and Johannesburg cities. A mixed-methods approach was used to develop a nuanced understanding of the nexus between UGSs and the livelihoods of the residents. A questionnaire survey (n = 658) with 329 participants from each city and 20 interviews were used to gather and generate data. Twelve types of UGSs were identified, with a relatively large proportion of the participants recognizing informal recreational areas as the common type of urban green space (UGS) in both cities. Domestic gardens, cemeteries, parks, woodlands, institutional green spaces, street trees, wastelands, commonages, and green roofs were other green spaces in both cities. Economically, job opportunities emerged in areas such as selling wares, photography, and the collection of firewood and wild fruits for sale. Likewise, farming activities and property values increased. Socially, they were valuable recreation and leisure spots for picnicking, dog walking, dating escapades, mental and spiritual wellness as well as education. Environmentally, UGSs were special in terms of medicinal provisions and aesthetics. However, urbanization and encroachment are undermining the extent of livelihood benefits. Therefore, it is imperative to revitalize UGSs by instituting robust partnerships and collaboration between government agencies, mobilize resources and expertise, value addition to existing UGSs, rigorous education to promote better appreciation, inclusion of the locals in the design process so that green spaces meet their needs and priorities, and establishing effective maintenance and management systems that ensure sustainability of UGSs. Full article

As a pivotal ecological–economic nexus in China, the Yangtze River Basin (YRB)’s spatiotemporal evolution of habitat quality (HQ) profoundly influences regional sustainable development. This study establishes a tripartite analytical framework integrating remote sensing big data, socioeconomic datasets, and ecological modeling. By coupling the InVEST and PLUS models with Theil–Sen median trend analysis and Mann–Kendall tests, we systematically assessed HQ spatial heterogeneity across the basin during 2000–2020 and projected trends under 2030 scenarios (natural development (S1), cropland protection (S2), and ecological conservation (S3)). Key findings reveal that basin-wide HQ remained stable (0.599–0.606) but exhibited marked spatial disparities, demonstrating a “high-middle reach (0.636–0.649), low upper/lower reach” pattern. Urbanized downstream areas recorded the minimum HQ (0.478–0.515), primarily due to landscape fragmentation from peri-urban expansion and transportation infrastructure. Trend analysis showed that coefficient of variation (CV) values ranged from 0.350 to 2.72 (mean = 0.768), indicating relative stability but significant spatial variability. While 76.98% of areas showed no significant HQ changes, 15.83% experienced declines (3.56% with significant degradation, p < 0.05) concentrated in urban agglomerations (e.g., the Wuhan Metropolitan Area, the Yangtze River Delta). Only 7.18% exhibited an HQ improvement, predominantly in snowmelt-affected Qinghai–Tibet Plateau regions, with merely 0.95% showing a significant enhancement. Multi-scenario projections align with Theil–Sen trends, predicting HQ declines across all scenarios. S3 curbs decline to 0.33% (HQ = 0.597), outperforming S1 (1.07%) and S2 (1.15%). Nevertheless, downstream areas remain high-risk (S3 HQ = 0.476). This study elucidated compound drivers of urbanization, agricultural encroachment, and climate change, proposing a synergistic “zoning regulation–corridor restoration–cross-regional compensation” pathway. These findings provide scientific support for balancing ecological protection and high-quality development in the Yangtze Economic Belt, while offering systematic solutions for the sustainable governance of global mega-basins. Full article

Urban agriculture is key to sustainable city development, particularly through public engagement with the Water–Energy–Land–Food–People (WELFP) Nexus. This study examines the effectiveness of serious games in enhancing WELFP understanding and promoting pro-environmental and pro-social behaviors. A game-based learning model was developed using the Stimulus–Organism–Response (SOR) and Easy–Attractive–Social–Timely (EAST) frameworks, along with the Revised New Ecological Paradigm (NEP) Scale. The model simulates real-world urban agriculture challenges to foster participatory decision-making. A survey of 200 urban agriculture practitioners, analyzed via structural equation modeling (SmartPLS 4.0), found that perceived timeliness (PT) and perceived usefulness (PU) significantly influenced both the perceived sustainable livelihood value (PT: p = 0.000; PU: p = 0.006) and users’ attitudes toward the game (PT: p = 0.000; PU: p = 0.038). While enjoyment positively affected attitude (p = 0.002), it negatively impacted perceived value (p = 0.002), revealing a trade-off between fun and practical relevance. Perceived ease of use improved perceived value (p = 0.000) but did not affect attitude, suggesting emotional engagement matters more. Both attitude and perceived value strongly predicted users’ intention to engage with the game. Post-game reflections highlighted the need for cross-sector collaboration, strategic resource use, access to real-time data, and responsive crisis management. Participants also stressed the importance of public awareness, civic responsibility, and volunteerism in advancing community-driven sustainable agriculture. These findings highlight the need to balance engagement and educational depth in game-based learning for sustainability. Full article

To enhance sustainability in urban design, it is essential to consider urban planning and morphology. This study explores the relationship between key morphological layers and the degree of sustainability in urban forms. Understanding how morphological characteristics influence sustainable urban form parameters provides valuable insights into urban areas’ sustainability potential. Based on this premise, a theoretical model is proposed to assess the potential of urban design for sustainability. The study examines urban forms across multiple scales, from material level to city-wide analysis, employing typo-morphological analysis inspired by Italian and British urban morphology schools. The model has been evaluated by academics from various universities who assessed the relationship between sustainable urban form parameters and morphological elements by weighting their relevance. Analytical tools were applied, including SPSS 29.0 and Excel-based mathematical methods. The results confirm a strong correlation between morphological elements and sustainable urban form characteristics, influenced by scale and classification. Additionally, the study identifies the most impactful parameters for enhancing sustainability in urban design. This research contributes to a comprehensive framework for sustainable urban morphology, offering practical insights for planners and designers in shaping more sustainable cities. Full article

Traditional centralized network structures exhibit clear scalability and communication efficiency bottlenecks. This paper proposes a solution based on a bidirectional unweighted heterogeneous graph, Dynamic Nexus Mesh Communication, designed to improve communication efficiency and optimize user experience, particularly for high-density urban interaction spaces. DNMC reduces the reliance on central super nodes in traditional centralized networks by redistributing network centrality while increasing the betweenness centrality of a broader set of nodes. Additionally, DNMC introduces multiple node types, improving both the robustness and efficiency of the network. Through a series of simulation experiments, we compared the communication performance of DNMC networks with that of traditional centralized networks. The results show that DNMC achieves an average delay of 1.5824 s, representing a 13.69% improvement over centralized architectures. These findings demonstrate that DNMC significantly outperforms traditional networks in terms of communication efficiency, particularly at larger network scales, where DNMC exhibits enhanced stability and scalability. Full article