Search Results (3,604)

This research examines the relationship between environmental, social safety and governance risks, and the mitigation strategies of the host country to enhance project performance in the China–Pakistan Economic Corridor (CPEC). The study concludes that the timely and effective completion of CPEC projects is challenged by environmental, social safety, and governance (ESG) risks, including environmental degradation, security threats, and governance issues. Based on the data of 618 respondents from Pakistan and using Structural Equation Modeling (SEM) through SMART PLS 4, the study investigates the impact of sustainable environmental practices, safety and security measures, governance risk mitigation actions, and project management systems on the project performance of CPEC projects. The results show that mitigation efforts implemented by the host country reduce the ESG investment risk and yield a positive effect on the project performance. Hence, this paper will show the importance of proactive measures such as sustainable development practices, security risk management systems, and transparent governance practices in matching challenges and enhancing project benefits. This research reinforces the potential for these risks to be mitigated through the adoption of innovative technologies. Innovation in environments, social protection, and governance frameworks can greatly mitigate the negative impacts of risks, directly improving the outcomes of project delivery. Infrastructure projects are extremely challenging to manage, and this study gives key hints for enhancing project safety and risk management in those types of infrastructure projects for practitioners, policymakers, project managers, and other stakeholders to establish innovative, sustainable strategies. Full article

This study aimed to analyze the influence of local politics, village facilitators, recruitment of administrators, training and education, and organizational culture on work motivation and management performance. The study was conducted in Wajo Regency, South Sulawesi Province, Indonesia, utilizing primary data collected from 250 participants, including administrators of village-owned enterprises (BUMDES), community leaders, and representatives from the private sector. The data were analyzed using structural equation modeling (SEM) with the LISREL program. The results indicated that the latent variables of local politics, village facilitator, recruitment of administrators, training and education, and organizational culture had a positive and significant impact on work motivation and management performance. These findings are valuable key indicators and provide essential insights for promoting and driving the BUMDES as a pillar of rural development strategies. Based on these findings, it is recommended that the local government revitalize the local political system, reorient the organizational culture of the BUMDES toward a modern business-oriented culture suited to rural conditions, and enhance the training and education of village facilitators to improve their motivation and performance. This recommendation will empower the BUMDES to promote rural economic improvement and sustainable rural development by enhancing work motivation and management performance. Full article

The COVID-19 pandemic has highlighted critical vulnerabilities in urban logistics systems, particularly in last-mile delivery. To enhance logistics resilience and efficiency, the Korean government has initiated an innovative project that repurposes idle spaces in subway vehicle bases within the Seoul Metropolitan Area into logistics centers. This study proposes a comprehensive multi-criteria evaluation framework combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the suitability of ten candidate sites. The evaluation criteria span four dimensions, facility, geographical, environmental, and social factors, derived from the literature and expert consultations. AHP results indicate that geographical factors, especially proximity to urban centers and major logistics facilities, hold the highest weight. Based on the integrated analysis using TOPSIS, the most suitable locations identified are Sinnae, Godeok, and Cheonwang. The findings suggest the strategic importance of aligning infrastructure development with spatial accessibility and stakeholder cooperation. Policy implications include the need for targeted investment, public–private collaboration, and sustainable logistics planning. Future research is encouraged to incorporate dynamic data and consider social equity and environmental impact for long-term urban logistics planning. Full article

This study employs k-means clustering to analyze local organizations responsible for land improvement in Greece, identifying four distinct groups with consistent geographic patterns but divergent financial and operational characteristics. By integrating unsupervised machine learning with spatial analysis, the research offers a novel perspective on irrigation water pricing and cost recovery. The findings reveal that organizations located on islands, despite high water costs due to limited rainfall and geographic isolation, tend to achieve relatively strong financial performance, indicating the presence of adaptive mechanisms that could inform broader policy strategies. In contrast, organizations managing extensive irrigable land or large volumes of water frequently show poor cost recovery, challenging assumptions about economies of scale and revealing inefficiencies in pricing or governance structures. The spatial coherence of the clusters underscores the importance of geography in shaping institutional outcomes, reaffirming that environmental and locational factors can offer greater explanatory power than algorithmic models alone. This highlights the need for water management policies that move beyond uniform national strategies and instead reflect regional climatic, infrastructural, and economic variability. The study suggests several policy directions, including targeted infrastructure investment, locally calibrated water pricing models, and performance benchmarking based on successful organizational practices. Although grounded in the Greek context, the methodology and insights are transferable to other European and Mediterranean regions facing similar water governance challenges. Recognizing the limitations of the current analysis—including gaps in data consistency and the exclusion of socio-environmental indicators—the study advocates for future research incorporating broader variables and international comparative approaches. Ultimately, it supports a hybrid policy framework that combines data-driven analysis with spatial intelligence to promote sustainability, equity, and financial viability in agricultural water management. Full article

Green public procurement (GPP) is a pivotal policy instrument for advancing urban low-carbon transitions. Using panel data from 285 Chinese cities (2015–2023), this study employs a panel fixed-effects model, mediation analysis, and spatial Durbin model to assess the impact, influencing mechanisms, and spatial spillover effects of GPP on urban carbon emissions intensity. The key findings reveal the following: (1) a 1% increase in GPP implementation is associated with a 1.360% reduction in local urban carbon emissions intensity. (2) GPP reduces urban carbon emissions intensity through urban green innovation, corporate sustainability performance, and public ecological awareness. (3) GPP exhibits significant cross-boundary spillovers, where a 1% reduction in local carbon emissions intensity induced by GPP leads to a 14.510% decline in that in neighboring cities. These results provide robust empirical evidence for integrating GPP into the urban climate governance framework. Furthermore, our findings offer practical insights for optimizing the implementation of GPP policies and strengthen regional cooperation in carbon reduction. Full article

Promoting social equity is a global issue, and common prosperity is an important goal for human society’s sustainable development. This study is the first to examine climate risks’ impacts on common prosperity from the perspective of corporate employees, providing micro-level evidence for the coordinated development of climate governance and social equity. Employing data from companies listed on the Shanghai and Shenzhen stock exchanges from 2016 to 2023, a fixed-effects model analysis was conducted, and the results showed the following: (1) Climate risks are positively associated with the common prosperity of corporate employees in a significant way, and this effect is mainly achieved through employee guarantees, rather than employee remuneration or employment. (2) Climate risk will increase corporate financing constraints, but it will also force companies to improve their ESG performance. (3) The mechanism tests show that climate risks indirectly promote improvements in employee rights and interests by forcing companies to improve the quality of internal controls and audits. (4) The results of the moderating effect analysis show that corporate size and performance have a positive moderating effect on the relationship between climate risk and the common prosperity of corporate employees. This finding may indicate the transmission path of “climate pressure—governance upgrade—social equity” and suggest that climate governance may be transformed into social value through institutional changes in enterprises. This study breaks through the limitations of traditional research on the financial perspective of the economic consequences of climate risks, incorporates employee welfare into the climate governance assessment framework for the first time, expands the micro research dimension of common prosperity, provides a new paradigm for cross-research on ESG and social equity, and offers recommendations and references for different stakeholders. Full article

As sustainability becomes a strategic priority across global financial services, its implementation in emerging insurance markets remains insufficiently understood. This study explores the integration of environmental, social, and governance (ESG) principles within Saudi Arabia’s insurance sector, combining content analysis of corporate disclosures with qualitative insights from industry stakeholders. The research investigates how insurers embed ESG principles into their operations, the development of sustainable insurance products, and their perceived financial and regulatory implications. The findings reveal gradual progress in ESG integration, primarily driven by governance reforms aligned with national development agendas, while social and environmental dimensions remain comparatively underdeveloped. Stakeholders identify regulatory ambiguity, data limitations, and technical capacity as persistent barriers, but also point to increasing investor and consumer interest in sustainability-aligned offerings. This study offers policy and managerial recommendations to advance ESG principle adoption, emphasizing standardized disclosures, capacity-building, and product innovation. It contributes to the limited empirical literature on ESG principles in Middle Eastern insurance markets and highlights the sector’s potential role in promoting inclusive and sustainable finance. Full article

Highway accessibility plays a vital role in supporting local economic development, particularly in regions lacking access to sea or river ports. Recognizing the functional transformation of road infrastructure, the Chinese government has made substantial investments in its expansion. Nevertheless, a theoretical gap remains in justifying whether such investments yield significant economic returns. Drawing on the theory of economic externalities, this study investigates the causal relationship between highway development and regional economic growth, and assesses whether highway construction leads to an acceleration in growth rates. Utilizing panel data from 14 Chinese cities spanning 2000 to 2014, the synthetic control method (SCM) is employed to evaluate the economic externalities of highway investment. The results indicate a positive impact on surrounding industries. Furthermore, a growth rate forecasting analysis based on Back-Propagation Neural Networks (BPNNs) is conducted using industrial enterprise data from 2005 to 2014. The growth rate in the treated city is 1.144%, which is close to the real number 1.117%, higher than the number for the weighted control group, which is 1.000%. The findings suggest that the growth rate of total industrial output improved significantly, confirming the existence of positive spillover effects. This not only enriches the empirical literature on transport infrastructure but also provides targeted enlightenment for the sustainable development of urban economy in terms of policy guidance. Full article

Demands for companies to comply with environmental, social, and governance (ESG) requirements are growing, and companies are also expected to play a role in promoting sustainable development. For companies to achieve sustainable growth while addressing ESG, it must be understood whether ESG activities promote improved corporate financial performance. We conducted a five-year panel data analysis of 635 Japanese firms from FY 2019 to FY 2023, using the PBR, PER, and ROE financial indicators as the dependent variables and CSR ratings in the human resource utilization (HR), environment (E), governance (G), and social (S) categories as the independent variables. The results revealed that, depending on the combination of ESG field and financial indicators, companies with advanced ESG initiatives had greater financial performance, with some cases showing a nonlinear relationship; differences in the results between manufacturing and nonmanufacturing industries were also observed. For companies to effectively advance ESG activities, it is important to clarify the objectives and results for each ESG category. For policymakers to consider measures to encourage companies’ ESG activities, it is also important to design finely tuned regulations and incentives according to the ESG category and industry characteristics. Full article

Promoting municipal solid waste (MSW) sorting is critical to advancing sustainable and low-carbon urban development. While existing research often focuses separately on external policy tools or internal behavioral drivers, limited attention has been given to their joint effects within an integrated framework. This study addresses this gap by analyzing micro-survey data from 1983 residents across 34 prefecture-level and above cities in China, using a bivariate probit model to examine how policy tools and policy perception—both independently and interactively—shape residents’ active and passive compliance with MSW sorting policies. The findings reveal five key insights. First, the adoption and spatial distribution of policy tools are uneven: environment-type tools dominate, supply-type tools are moderately deployed, and demand-type tools are underutilized. Second, both policy tools and policy perception significantly promote compliance behaviors, with policy cognition exerting the strongest effect. Third, differential effects are observed—policy cognition primarily drives active compliance, whereas policy acceptance more strongly predicts passive compliance. Fourth, synergistic effects emerge when supply-type tools are combined with environment-type or demand-type tools. Finally, policy perception not only directly enhances compliance but also moderates the effectiveness of policy tools, with notable heterogeneity among residents with higher cognitive or emotional alignment. These findings contribute to a deeper understanding of compliance mechanisms and offer practical implications for designing perception-sensitive and regionally adaptive MSW governance strategies. Full article

The construction and development of digital infrastructure have emerged as a crucial indicator of national competitiveness, which holds significant importance in driving the sustained growth of the national economy and the comprehensive advancement of society. This paper explores the impact of digital infrastructure on farm households’ scale management, aiming to reveal the role and potential of digital technology in agricultural modernization. Additionally, it seeks to offer a scientific foundation for the government to formulate agricultural policies and advance agricultural modernization. Using the OLS (Ordinary Least Squares) model, moderating effect model, and other methods, this study investigates how digital infrastructure affects farm households’ scale management based on micro-level research data of 2510 farm households from the CRRS (China Rural Revitalization Survey). The following conclusions are drawn: Firstly, the enhancement of digital infrastructure can motivate farm households to expand the land management area and increase the unit output of land. Secondly, farm households’ digital literacy positively moderates the effect of digital infrastructure on their land unit output; moreover, digital skills training for farm households exhibits a positive moderating effect on the influence of digital infrastructure on their management area. Finally, there is a heterogeneity in the impact of digital infrastructure on farm households’ scale management. Specifically, the promotion of farm households’ scale management is stronger in plain areas and weaker in hilly and mountainous areas; stronger for middle-aged and older and small-scale farm households; and weaker for youth groups and large-scale farm households. Based on this, this paper suggests increasing the investment in digital infrastructure construction, improving farm households’ digital literacy, carrying out digital skills training, and formulating differentiated regional policies for reference. Full article

This study examines the regional disparities in public perceptions of decarbonization and the acceptance of the bioeconomy within Western Macedonia, a Greek region undergoing structural economic change. While the environmental benefits of decarbonization, such as reduced carbon emissions and improved air quality, are widely acknowledged, perceptions of economic and social outcomes, including investments, new business development, and policy support, vary significantly across sub-regions. To this end, a structured survey was conducted among 765 residents, utilizing Likert-scale items to assess attitudes, with demographic data providing a contextual framework. Statistical analyses, incorporating techniques such as one-way analysis of variance (ANOVA), Kruskal–Wallis, and multiple regression, were employed to explore spatial variations and identify the primary drivers of bioeconomy acceptance. The results indicate that perceived government action, visible investment, new enterprises, and a positive view of public sentiment are all significant predictors of acceptance, with institutional support showing the strongest influence. The findings reveal that certain areas feel less engaged in the transition, expressing skepticism about its benefits, while others report more optimism. This disparity in perception underscores the necessity for targeted policy interventions to ensure inclusive and equitable participation. The study emphasizes the necessity for regionally responsive governance, enhanced communication strategies, and tangible local development initiatives to cultivate public trust and support. The study makes a significant contribution to the broader discourse on just transitions by emphasizing the role of place-based perceptions in shaping sustainable change. Full article

The escalating threat of climate change has intensified the global urgency to accurately predict carbon dioxide (CO₂) emissions for sustainable development, particularly in developing economies experiencing rapid industrialization and globalization. Traditional Extreme Learning Machines (ELMs) offer rapid learning but often yield unstable performance due to random parameter initialization. This study introduces a novel hybrid model, Red-Billed Blue Magpie Optimizer-tuned ELM (RBMO-ELM) which harnesses the intelligent foraging behavior of red-billed blue magpies to optimize input-to-hidden layer weights and biases. The RBMO algorithm is first benchmarked on 15 functions from the CEC2015 test suite to validate its optimization effectiveness. Subsequently, RBMO-ELM is applied to predict Indonesia’s CO₂ emissions using a multidimensional dataset that combines economic, technological, environmental, and globalization-driven indicators. Empirical results show that the RBMO-ELM significantly surpasses several state-of-the-art hybrid models in accuracy (higher R²) and convergence efficiency (lower error). A permutation-based feature importance analysis identifies social globalization, GDP, and ecological footprint as the strongest predictors underscoring the socio-economic influences on emission patterns. These findings offer both theoretical and practical implications that inform data-driven Artificial Intelligence (AI) and Machine Learning (ML) applications in environmental policy and support sustainable governance models. Full article

This review provides the recent advancements in nonlinear sea ice modeling for hydroelastic analysis of ice-covered channels and their interaction with floating structures. It surveys theoretical, experimental, and numerical methodologies used to analyze complex coupled sea ice–structure interactions. The paper discusses governing fluid domain solutions, fluid–ice interaction mechanisms, and ice–structure (ship) contact models, alongside experimental techniques and various numerical models. While significant progress has been made, particularly with coupled approaches validated by experimental data, challenges remain in full-scale validation and accurately representing ice properties and dynamic interactions. Findings highlight the increasing importance of understanding sea ice interactions, particularly in the context of climate change, Arctic transportation, and the development of very large floating structures. This review serves as a crucial resource for advancing safe and sustainable Arctic and offshore engineering. Full article

In an era marked by accelerating ecological degradation and widening global inequalities, prevailing patterns of resource extraction and consumption are proving increasingly unsustainable. Driven by hyper-consumption and entrenched linear production models, the global economy continues to exert immense pressure on planetary systems. This communication article calls for a fundamental paradigm shift from the long-standing assumption of resource abundance to a framework of responsible scarcity. Drawing from recent data on material throughput, on the transgression of planetary boundaries, and on the structural and geopolitical disparities underlying global resource use, this article highlights the urgent need to realign natural resource governance with ecological limits and social justice. A conceptual framework is proposed to support this transition, grounded in principles of ecological constraint, functional sufficiency, equity, and long-term resilience. The article concludes by outlining a forward-thinking research and policy agenda aimed at fostering sustainable and just modes of resource utilization in the face of growing environmental and socio-economic challenges. Full article