Search Results (12,558)

Occupational Health and Safety (OHS) in educational settings is a vital responsibility that is often inconsistently implemented. There is a need for research to bridge the gap between policy and practice. This study employed a cross-sectional mixed-methods design in six schools in the capital city of Indonesia to identify key implementation barriers, strategies, and compliance levels in OHS. Data were collected from 217 teachers using a structured KPAP (Knowledge, Attitudes, Perceptions, Practices) survey and from an additional 38 teachers via Focus Group Discussions (FGDs). Quantitatively, teachers showed highly positive attitudes (99.4% viewing OHS as a professional duty) and generally positive perceptions but implementation practices were sub-optimal (e.g., low participation in drills and PPE usage), showing a gap between awareness and action. Qualitatively, the main barriers identified were a lack of specific OHS regulation or guidance for schools, limited resources/infrastructure, and the perception of OHS as a low priority. Management strategies focused on external collaboration and ongoing in-school initiatives. In conclusion, a significant gap exists between OHS awareness and its integration into school management, highlighting the urgent need for strengthened governance, comprehensive policies, and sustained capacity-building to ensure a proactive, safe, and sustainable school environment for staff and students. Full article

This study investigates the impact of city-level capital factor market integration on corporate ESG performance, using a sample of Chinese A-share listed companies from 2010 to 2024. We find that greater capital factor market integration significantly improves firms’ overall ESG performance. Mechanism analysis reveals that capital factor market integration operates through three channels: market competition, technological advancement, and attention reconstruction, enhancing both firms’ capabilities and incentives to engage in ESG activities. The positive effect is stronger for state-owned enterprises, firms in less polluting industries, and those in regions with high government environmental attention. Further analysis indicates that capital factor market integration suppresses corporate greenwashing behavior and reduces discrepancies across ESG rating agencies. Moreover, capital factor market integration exhibits asymmetric effects across ESG sub-dimensions, significantly improving environmental and governance performance while weakening social responsibility performance. This reflects firms’ preference, under competitive pressure, for environmental and governance domains characterized by shorter payback periods and more readily quantifiable outcomes, as well as their cautious stance toward the social responsibility domain where effects take considerably longer to materialize. This study contributes to understanding the micro-level mechanisms through which capital factor market integration influences corporate sustainable development, providing empirical evidence for China’s construction of a unified national market and the advancement of sustainable development strategies. Full article

In the field of the road transportation industry, quantitative research on the relationship between artificial intelligence (AI) technology and corporate sustainable development is relatively scarce. This disparity has led to discussions about whether artificial intelligence technology can truly promote the sustainable development level of the highway maintenance industry. Therefore, this study aims to quantify the relationship between artificial intelligence technology and the sustainable development of the highway maintenance industry, and to analyze the reasons behind the current controversies. The research results show: (1) Each exogenous variable has an impact on sustainable development, although the degree of influence varies, especially the economic development level (ED) has the strongest direct effect on sustainable development, followed by the level of market demand (MD), the level of policy support (PS), and the level of enterprise capital (EC); (2) Moderating variables can enhance this direct impact, among which the moderating effect of ED on the relationship between ED and sustainable development is the strongest; (3) Artificial intelligence technology has different impacts on enterprises at different positions in the industrial chain, thereby explaining the controversy over whether to adopt it or not. These conclusions highlight the value of artificial intelligence technology and provide a reasonable explanation for the existing controversies in the industry and research field. Full article

A reading of the American Revolution and the post-Civil War Reconstruction period through the lens of W.E.B. Du Bois’s early writings provides new insights into his theory of racial monopoly capitalism. Many Americans saw the 1776 revolution as an idealistic fight for liberty, for the slaveholding elite who held disproportionate power within the revolutionary coalition; however, consolidating power and defending their property and expansionist ambitions were primary objectives. For them, the Revolution was a strategic move to establish racial nationalism and preserve slaveholder control over economic growth and national power. A century later, Du Bois’s analysis of the “bargain of 1876” revealed a similar consolidation of power, influencing both his research on the revolutionary period and his writings on Reconstruction. The political deal in 1876 abandoned the promise of Reconstruction’s “abolition democracy,” restoring white supremacist rule. Du Bois saw this as the victory of monopoly capital, which used racism to weaken interracial labor solidarity and enforce a system of super-exploitation. By linking 1776 to 1876, Du Bois demonstrated that U.S. capitalist development had been shaped by racial oppression from its settler-colonial roots through the rise of monopoly capitalism, consistently blocking the achievement of a true, non-racial democracy. Full article

Social sustainability has become a central concern in development-induced resettlement, yet little is known about how social integration and community relations are sustained over long time horizons. Drawing on a retrospective longitudinal ethnographic reconstruction spanning 21 years (2004–2025) of Three Gorges Dam resettlers relocated to rural Anhui, China, this paper examines the co-evolution of group boundaries, interaction strategies, and social networks between migrants and local residents. Using group boundary theory, we identify three sequential phases of interaction: initial boundary demarcation and social distancing, subsequent bridge-building through economic cooperation and relational ingratiation, and a later stage of pragmatic, transactional engagement. We show that the gradual erosion of migrant–local boundaries is driven by economic interdependence, cultural adaptation, individualization, and rural out-migration. Rather than resulting in deep social fusion, long-term integration stabilizes in a form of “thin integration,” characterized by low-density but sustainable social ties, institutionalized conflict resolution, and routine coexistence. This study conceptualizes social integration as a dynamic process of social sustainability, demonstrating how resettled communities maintain social order and functional cohesion amid structural change. The findings contribute to debates on sustainable rural development, forced migration, and the long-term governance of resettlement communities. 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

This study aimed to analyze the impact of the digital economy and artificial intelligence (AI) on GDP growth in 10 developed and developing countries during the period 2010–2024. It was based on the hypothesis that increased digitalization and AI investments promote sustainable economic growth by improving national productivity and efficiency, in accordance with modern technological growth theory, which links digital innovation to economic development. The study used tablet data comprising 150 observations, which were analyzed using fixed- and random-effects models, controlling for traditional variables such as employment, human capital, and investment. The results showed that the Digitalization Indicators (DIGI) had a significant positive impact on growth (fixed: 0.003479, p < 0.01; random: 0.003325, p < 0.01), and that investment in AI also had a significant positive impact (fixed: 0.063695, p < 0.05; random: 0.066548, p < 0.05). In contrast, workforce size had a limited impact, while education and human capital emerged as key drivers of sustainable growth (Constant: 0.003257, p < 0.01; Random: 0.003264, p < 0.01). The inclusion of dummy variables further differentiated between developed and developing countries in the random-effects model, reinforcing the economic interpretation of the findings. The study suggests that integrating digitalization, education, and investment in artificial intelligence is an effective strategy for promoting sustainable economic growth, while emphasizing the importance of workforce skills development to maximize its impact. Full article

Grounded in the United Nations Sustainable Development Goal 4 (SDG4), specifically addressing the urgent need to increase relevant skills for decent work (Target 4.4) while ensuring inclusive access and quality (Targets 4.3, 4.5, 4.c), this study develops a province-level indicator system for the “talent chain” and “industry chain” and integrates entropy-weighted composite evaluation, a coupling coordination model, correlation tests, and mismatch typology classification to systematically assess the alignment between higher education talent formation and industrial demand across 31 Chinese provinces during 2000–2022. The analysis aims to characterize China’s phase-specific progress in SDG4-consistent development at the education–industry interface and to provide a theoretical and empirical basis for improving graduate job matching. The results show that (1) overall talent–industry matching improved steadily from 2000 to 2022, yet pronounced regional disparities persist, with eastern provinces generally outperforming central and western regions; (2) educational quality and structural inputs—such as faculty capacity, per-student expenditure, and the composition of human capital—are the primary drivers of talent-chain performance, whereas expansion-oriented indicators exhibit limited marginal contributions, implying that sustainable graduate job matching hinges more on quality upgrading and supply-structure optimization than on quantitative expansion alone; (3) industry-chain advancement is jointly driven by industrial scale, structural upgrading, and employment absorptive capacity, with the tertiary sector playing a particularly prominent role in shaping demand for higher-skilled labor; and (4) a divergence in driving mechanisms—quality- and structure-oriented on the education side versus scale- and structure-oriented on the industry side—combined with regional heterogeneity produces stage-specific mismatch typologies, suggesting remaining scope for structural alignment between higher education systems and industrial upgrading. Overall, strengthening regional coordination, integration, quality, and upgrading drives synergistic development, advancing SDG 4 targets by validating that quality-driven education reform is the key lever for sustainable employment in China. Full article

This paper introduces flourishing circularity as a transformative approach to resource assessment that transcends both traditional Resource-Based View (RBV) theory and conventional circular economy concepts. We demonstrate RBV’s fundamental limitations in addressing the polycrisis of breached planetary boundaries and social inequities. Similarly, while the circular economy focuses on resource reuse and recycling, it often merely delays environmental degradation rather than reversing it. Flourishing circularity addresses these shortcomings by reconceptualizing natural and social capital not as externalities but as foundational sources of all value creation. We develop a comprehensive framework for assessing resources within an open systems perspective, where competitive advantage increasingly derives from a firm’s ability to regenerate the systems upon which all business depends. The paper introduces novel assessment tools that capture the dynamic interplay between organizational activities and coevolving social and ecological systems. We outline the core competencies required for flourishing circularity: regenerative approaches to social and natural capital, and systems thinking with cross-boundary collaboration capabilities. These competencies translate into competitive advantage as stakeholders increasingly favor organizations that enhance system health. The framework provides practical guidance for transforming resource assessment from extraction to regeneration, enabling business models that create value through system enhancement rather than depletion. Full article

As a key strategic sector underpinning China’s future development, the artificial intelligence (AI) industry is essential to enhancing national competitiveness and advancing sustainable economic and social development. Based on Chinese provincial panel data from 2012 to 2022, we explore how industrial structure upgrading (ISU) affects the resilience of China’s AI industry chain (RAIIC) and empirically test the underlying transmission mechanism using a mediation effect model. The results indicate that (1) ISU significantly enhances the RAIIC, thereby providing a solid structural foundation for its long-term stability and sustainable evolution; (2) the impact of ISU on the RAIIC can be realized by enhancing regional financial agglomeration and human capital levels; (3) the positive impact of ISU on the RAIIC is significantly stronger in regions with larger population sizes, higher levels of economic development, higher technological sophistication, and more advanced digital inclusive finance. These findings imply that policy design should emphasize regional coordination and dynamic adaptability so as to support the balanced and sustainable nationwide development of the AI industry. According to these findings, we propose corresponding policy recommendations aimed at providing theoretical support and practical guidance for the sustainable and high-quality development of China’s AI industry. Full article

Industrial deployment of photocatalysis for recalcitrant wastewater treatment remains constrained by economic uncertainty and scale-up limitations. This study first reviews the current technological routes and application status of photocatalytic processes and then addresses the key obstacles through a quantitative techno-economic assessment (TEA) of a full-scale (10,000 m³/d) photocatalytic wastewater treatment plant. A process-level model integrating mass- and energy-balance calculations with equipment sizing was developed for a 280 kW UVA-LED reactor using Pt/TiO₂ as the benchmark catalyst. The framework quantifies capital (CAPEX) and operating (OPEX) expenditures and evaluates the overall economic performance of the photocatalytic treatment system. Sensitivity analysis reveals that the catalyst replacement interval and electricity tariffs are the principal economic bottlenecks, whereas improvements in catalyst performance alone provide limited cost leverage. Furthermore, the analysis indicates that supportive policy mechanisms such as carbon-credit incentives and electricity subsidies could substantially enhance economic feasibility. Overall, this work establishes a comprehensive integrated TEA framework for industrial-scale photocatalytic wastewater treatment, offering actionable design parameters and cost benchmarks to guide future commercialization. Full article

Under the combined influence of global climate change and intensified human activities, quantifying ecological compensation (EC) amounts between regions and formulating scientifically sound and rational policies have become critical strategies for addressing the imbalance between economic development and ecological conservation. This study focuses on the Yangtze River Economic Belt (YREB) as the research subject, assesses ecosystem service supply and demand (ESSD) in the years 2000, 2010, and 2020 from the perspective of the water-energy-food nexus (WEF-Nexus), identifies ecosystem service flows (ESF) between supply and demand areas, develops an integrated EC model incorporating ecological, economic, and social dimensions to estimate EC amounts, and ultimately employs the XGBoost-SHAP model to analyze the underlying driving mechanisms. The results indicate the following: (1) From 2000 to 2020, the spatio-temporal variations in the three ESSDs in the YREB were substantial. Additionally, imbalances in ESSDs were observed, predominantly in economically advanced regions. (2) A total of 183 ESFs were identified among cities within the YREB, reflecting relatively active exchanges of ecosystem services (ESs). (3) Over the past two decades, the average annual total EC of the YREB amounted to 46,866.35 million yuan, with EC capital flows occurring in 117 cities. The proportion of water area in each city constitutes the primary driver of the EC amount. The EC model based on the “water-energy-food” ecosystem service flow (WEF-ESF) proposed in this study provides a valuable reference and scientific basis for formulating EC policies among YREB cities. Full article

The accelerating global transition to electric mobility demands data-driven infrastructure planning that balances technical, economic, and spatial considerations. This study develops a scenario-based demand and economic modeling framework to estimate electric vehicle (EV) charging infrastructure needs across Abu Dhabi’s urban and rural regions through 2050. Two adoption pathways, Progressive and Thriving, were constructed to capture contrasting policy and technological trajectories consistent with the UAE’s Net Zero 2050 targets. The model integrates regional travel behavior, energy consumption (0.23–0.26 kWh/km), and differentiated charging patterns to project EV penetration, charging demand, and economic feasibility. Results indicate that EV stocks may reach 750,000 (Progressive) and 1.1 million (Thriving) by 2050. The Thriving scenario, while demanding greater capital investment (≈108 million AED), yields higher utilization, improved spatial equity (Gini = 0.27), and stronger long-term returns compared to the Progressive case. Only 17.6% of communities currently meet infrastructure readiness thresholds, emphasizing the need for coordinated grid expansion and equitable deployment strategies. Findings provide a quantitative basis for balancing economic efficiency, spatial equity, and policy ambition in the design of sustainable EV charging networks for emerging low-carbon cities. Full article

This paper develops a new conceptual and operational understanding of cultural heritage transformation, interpreting it as a systemic and dynamic process rather than a static state. It explores the realities and opportunities for action when cultural heritage is understood and managed as a complex, adaptive system. The study builds on a critical review of contemporary literature to identify the multi-scalar challenges currently facing urban heritage systems, such as climate change, disaster risks, social fragmentation, and unsustainable urban development. To respond to these challenges, the paper introduces a metamodel for heritage-based urban transformation, designed to apply systems thinking to heritage management that was developed based on cases from the Western European context. This metamodel integrates key variables—actors, resources, tools, and processes—and is used to test the hypothesis that a systems-oriented approach to cultural heritage can enhance the capacity of stakeholders to connect, adapt, use, and safeguard heritage in the face of complex urban transitions. The hypothesis is operationalized through scenario-based applications in the fields of disaster risk management (DRM), circular economy, and broader sustainability transitions, demonstrating how the metamodel supports the design of cross-over resilience strategies. These strategies not only preserve heritage but activate it as a resource for innovation, cohesion, identity, and adaptive reuse. Thus, cultural heritage is reframed as a strategic investment—generating spillover benefits such as improved quality of life, economic opportunities, environmental mitigation, and enhanced social capital. In light of the transition toward a greener and more resilient society, this paper argues for embracing heritage as a driver of transformation—capable of engaging with well-being, behavior change, innovation, and education through cultural crossovers. Heritage is thus positioned not merely as something to be protected, but as a catalyst for systemic change and future-oriented urban regeneration. Full article

The essay delves into the impact of environmental uncertainty on asymmetric mispricing, utilizing the data from listed firms in China spanning from 2007 to 2023. Our analysis reveals that environmental uncertainty amplifies stock mispricing within capital markets, whether upward or downward. Diverging from prior research, we distinguish between upward and downward mispricing and reveal the black box of environmental uncertainty affecting stock mispricing from dual channels. Specifically, environmental uncertainty intensifies upward mispricing through heightened earnings management and exacerbates downward mispricing by boosting investor irrationality. Furthermore, we explore the heterogeneous impact of different media coverage. In the downward mispricing sample, negative media exacerbated the relationship between the two, while positive coverage played a mitigating role. In the upward mispricing sample, only negative reports have a significant impact and mitigate the impact of uncertainty on mispricing. Our research on media heterogeneity once again proves that it is a double-edged sword. Our research indicates that improving the capacity to recognize different mispricing mechanisms in various market directions can greatly boost decision-making efficiency. Meanwhile, it is vital to strengthen professional ethics in media organizations and encourage more objective reporting. These efforts can jointly contribute to improving the efficiency of emerging capital markets. Full article