Search Results (168)

The depletion of global fish stocks poses a major challenge to sustainable development, particularly in economies where marine resources are critical to livelihoods and food security. In this study, the relationship between economic development and the sustainability of fish stocks is examined using the Environmental Kuznets Curve (EKC). We use panel data from 32 economies between 2002 and 2020 and analyze the fish stock status indicator (EPI_FSS) from the Environmental Performance Index, which captures the proportion of national catches from overfished or collapsed stocks. Using a dynamic panel approach and the generalized method of moments (GMM), we investigate how the human development index (HDI) and other socio-economic factors influence changes in the state of fish stocks. Our results show a statistically significant inverted-U-shaped (∩-shaped) relationship between the HDI and the state of fish stocks, suggesting that the deterioration of fish stocks increases at lower levels of development, but improves beyond a certain threshold. In addition, higher levels of foreign direct investment (FDI), education, and research and development (R&D) spending are associated with better outcomes for fish stocks. These results suggest that while early economic growth may put pressure on marine resources, sustained investment in human capital, innovation, and global integration is critical to promoting long-term marine sustainability. Full article

This paper aims to enhance operational efficiency in the labor-intensive production of composite wind turbine blades, which are critical components of renewable energy systems. The study was conducted at a wind energy facility in Türkiye, integrating the Single-Minute Exchange of Die (SMED) methodology with a Multi-Mode Resource-Constrained Project Scheduling Problem (MRCPSP) model to reduce production cycle time and optimize labor utilization. An operational time analysis was used to identify and classify non-value-adding activities. SMED principles were then adapted to the fixed-position manufacturing environment, enabling the conversion of internal setup activities into external ones and facilitating task parallelization. These improvements significantly increased productivity and labor efficiency. Subsequently, a scheduling model was developed to optimize the sequence of operations while accounting for activity precedence and resource constraints. As a result, the proposed approach reduced cycle time by 28.6% and increased average labor utilization from 68% to 87%. Scenario analyses confirmed the robustness of the model under varying levels of workforce availability. The findings demonstrate that integrating lean manufacturing techniques with optimization-based scheduling can yield substantial efficiency gains without requiring major capital investment. Moreover, the proposed approach offers practical insights into workforce planning and production scheduling in renewable energy manufacturing environments. Full article

With China’s emergence as a major global economy, its involvement in tackling climate change and fostering sustainable growth has garnered considerable focus. What impact does global direct investment have on carbon emissions within Belt and Road economies? This study innovatively utilizes a quantile regression model to analyze the varied impacts of international direct investment across distinct carbon emission quantiles, further delving into the conditional probability distribution of the dependent variable to provide a strong theoretical basis for precise policy-making by relevant departments and integrating time and space delays in examining the effects of carbon reduction strategies within the Belt and Road Initiative. Furthermore, this study aims to concentrate its research efforts on the host nations. Findings from this study indicate that global direct investments could escalate carbon emissions in economies with lower carbon emissions; yet, with the rise in the host nation’s carbon emissions, the ripple effect of international direct investments in green technology becomes increasingly evident. Empirical evidence indicates that global direct investment in Belt and Road economies demonstrates a significant mitigating effect on carbon emissions, thereby amplifying the decarbonization benefits associated with such cross-border capital flows. Full article

The cosmetic industry in the Ecuadorian Amazon region faces the challenge of competitively integrating locally sourced plant-based raw materials into efficient and sustainable production processes. This study proposes the design of a pilot plant for the production of a cosmetic emulsion (CE), using oils extracted from Morete (Mauritia flexuosa) and Ungurahua (Oenocarpus bataua), with a focus on process intensification to reduce both capital investment and resource consumption. Process design methodologies and computational simulation (SuperPro Designer V10) were applied, along with Systematic Layout Planning (SLP) principles to optimize spatial configuration. The intensified scheme enabled the integration of extraction lines, reducing the number of major equipment units from 12 to 9 and lowering the investment from USD 1,016,000 to USD 719,000. Energy and environmental indicators showed consumption levels of 5.86 kWh and 48.4 kg of water per kg of cream, which are lower than those reported for other natural cosmetics plants. The intensified design achieved a Net Present Value (NPV) of USD 577,000 and a payback period of 3.93 years. Furthermore, solid by-products were valorized through circular economy principles. This approach offers a feasible, viable, and sustainable solution for the utilization of these Amazonian oils in the cosmetic industry. Full article

This study conducts a systematic literature review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) process. The Scopus database is our main source of data, and our data analyses comprised bibliometric, systematic, and advanced analyses conducted with the help of VOSviewer. The analysis pinpoints the various roles played by AI in SCF: the strengthening of supply chain resilience and management, especially in times of crises like the COVID-19 pandemic; the convergence of sustainability performances via better relationships with suppliers; the effective management of risks by anticipating distress and fraud; improvements in working capital and supply chain efficiency; and tracking supply chain activities while on the go with IoT (Internet of Things). However, the following major setbacks are also observed: implementation challenges, large initial investments, resistance to change, a dearth of expertise in AI, security and privacy concerns, challenges in the integration of systems, the reliability of the data’s quality, etc. Full article

Background: The global space economy has grown remarkably, witnessing a 10-fold increase in active satellites during the last 15 years. This growth was accompanied by both the increase in geopolitical tensions feeding huge investments (the New Space Race), on the one hand, and the transformation, shifting from a domain historically dominated by government-led programs to one partially energized by commercial players and innovative business models (“New Space”), on the other hand. Objective: To assess the space economy’s current state and future prospects by considering its economic and social dimensions. Methods: Over 120 scholarly articles and “grey” literature positions (e.g., industry reports) were reviewed. The review was structured by a modified Structure–Conduct–Performance framework originally developed by industrial organization (IO) scholars. Findings: Outer space creates extremely harsh conditions for placing and operating objects in orbits, which results in high launching costs, steep reliability standards, capital intensity, and risks that are unmatched in most terrestrial industries. One of the main motivations to venture into this harsh domain was, and still is, the desire to dominate or the fear of being subjugated by others. This “original sin”, born of geopolitical rivalries, continues to cast a shadow over the space economy, channeling the majority of public space budgets into military-related programs. Moreover, many space technologies have a dual-use feature. Not surprisingly, governments are still the major source of demand, dominating midstream in the space value chain. This triad—harsh physics, great power rivalry, and a state-centric midstream—produces a specificity of the sector. In the recent two decades, new entrants (called “New Space”) have begun altering market structure, resulting in new conduct patterns focused on pursuits towards serial production, reusability, and lowering costs. Performance outcomes are mixed. While some efficiency gains are unprecedented, some doubts about market power and negative externalities arise. The assessment of the space economy’s performance is a challenge, as such, due to the blurred boundary between political objectives (supplying public goods, mitigating negative externalities) and economic optimization. Such trade-offs are becoming even more complicated considering the potential conflict between national and global perspectives. The paper offers a preliminary, descriptive study of the space economy through the lens of the modified S-C-P framework, laying basic foundations for the future, possibly more rigorous research of the increasingly important space economy. Full article

The advancement of sustainable economic development has become a strategic imperative for enterprises aiming to combine financial development with environmental and social responsibility. In this regard, strategic enterprise management (SEM) has a critical role in incorporating the aspects of sustainability into decision making. The present paper suggests a multicriteria decision-making framework that utilizes fuzzy TOPSIS in assessing and ranking sustainability integration aspects in organizations. By considering the intrinsic vagueness of sustainability analysis, the fuzzy TOPSIS model enables the systematic analysis of environmental, social, and governance (ESG) factors by companies for ensuring their alignment to corporate strategic goals. A case study of a major international airport in Greece demonstrates how the proposed methodology assists strategic choice making, balancing economic viability and sustainable value creation. The results show primary trade-offs among human capital investment, environmental footprint reduction, and stakeholder communication, demonstrating how companies can enhance long-term resilience and competitiveness. This research adds to the existing literature by giving an integrated strategic enterprise management framework with the use of decision support instruments to foster sustainability-oriented corporate governance and strategic efficacy. The suggested model is flexible and can be applied in any industry, hence being a benchmark for sustainable business practice. This paper contributes to the literature by integrating fuzzy TOPSIS with balanced scorecard in the context of airport strategic sustainability management, offering both methodological advancement and empirical insights for transport and supply chain enterprises. Full article

The evolving macroeconomic landscape, shaped by the global financial crisis and the COVID-19 pandemic, poses significant challenges for economies worldwide. However, Central, Eastern, and Southeastern European (CESEE) countries have demonstrated resilience and rapid recovery during crises, driven by a surge in consumption fueled by domestic credit and robust export growth supported by flexible exchange rates and adaptive monetary policies. Prior to EU accession, substantial foreign direct investment (FDI) during privatization and restructuring facilitated knowledge and technology transfers in CESEE economies. This study examines the interplay of exports, real exchange rates, GDP growth, FDI, inflation, domestic credit, and the human development index (HDI) in the CESEE region from 1995 to 2022, covering the transition period, EU accession, and major crises. Employing a panel ARDL model, we account for asymmetric effects of these variables on exports. The results reveal that GDP, FDI, inflation, domestic credit, and HDI significantly and positively influence exports, with HDI and GDP exerting the strongest effects, underscoring the pivotal roles of human capital and economic growth in enhancing export competitiveness. Conversely, real exchange rate depreciation negatively impacts exports, though non-price factors, such as product quality, mitigate this effect. These findings provide a robust basis for targeted policy measures to strengthen economic resilience and export performance in the CESEE region. Full article

As global discourse increasingly centers on environmental, social, and governance considerations, ESG investment has become a major trend in financial markets. Artificial intelligence (AI), through its rapid evolution, has exerted a transformative influence that continues to reshape the fundamental structures of this domain. This study investigates the dynamic relationship between AI and ESG investment indices in China, aiming to reveal the bidirectional causal linkages and time-dependent interactions between these two critical areas. In methods, we used four different parameter stability tests to indicate that the Granger causality test based on the full-sample VAR model may produce biased results. Therefore, we employed a bootstrap rolling-window subsample Granger causality test using data from January 2013 to September 2024 in China. The results reveal a significant dynamic relationship between ESG investment and AI. In key findings, we find that AI exerts a negative impact on ESG investment. AI development attracts substantial capital inflows that favor technological advancement and commercialization over long-term ESG investments. Meanwhile, ESG investment shows both positive and negative effects on AI. The positive effect indicates that ESG investment promotes AI research and applications emphasizing energy efficiency, data privacy, and fairness, thereby supporting the sustainable development of AI technologies. However, driven by short-term economic returns, strict ESG standards and compliance requirements may, in the short term, constrain the development of certain energy-intensive or emerging AI technologies. In economic and political implications, our study provides policymakers with scientific evidence to improve the ESG investment environment and to design balanced policies that support both AI development and sustainable investment practices. It underscores the necessity of promoting coordinated development between AI and ESG investment to achieve global sustainability goals and recommends measures to align short-term economic interests with long-term ESG objectives. This study is expected to serve as a scientific basis for ESG goal-setting and contribute to the realization of China’s dual-carbon goals. In particular, it facilitates the convergence of artificial intelligence technologies with sustainable development initiatives and tells the importance of responsible technological progress for global sustainable development. Full article

Digital transformation is considered a high-risk investment due to the fact that as much as 80% of its initiatives fail. To effectively manage and execute digital transformation, organizations must establish capabilities tailored to this process. Thus, this study aims to identify capabilities essential for digital transformation in the business context. A systematic literature review (SLR) was conducted following the PRISMA. An initial search across major academic databases yielded 542 articles. After applying inclusion and exclusion criteria, 43 relevant articles were selected for in-depth analysis. Descriptive, co-occurrence, and qualitative analyses were then applied. The findings reveal five core dimensions of digital transformation capability: digital dynamic capability, digital leadership capability, employee digital capability, digital technology and operational capability, and digital investment capability. These capabilities demonstrate that successful digital transformation depends not only on technology, but also on leadership, human capital, strategy, and investment that ensure resource readiness. This study contributes to digital transformation theory by identifying essential organizational capabilities and provides insights into how organizations can develop these capabilities to achieve successful digital transformation. Full article

The strategic goal of high-quality national development depends on intelligent manufacturing, where introducing and cultivating high-end technical talent is crucial. Although prior research has linked talent policies to technological innovation, few studies have examined how targeted talent policies promote intelligent transformation in enterprises. Methods: Focusing on industry fit, this study uses new-energy-vehicle companies to represent advanced manufacturing. Drawing on targeted talent policies issued by major Chinese cities from 2016 to 2022, we employ a multi-period difference-in-differences model to assess how these policies attract high-skilled talent related to the new-energy automotive sector and drive intelligent investment and technological upgrading. Results: Our findings indicate that targeted talent policies significantly boost intelligent investment, which holds for robustness tests. Mechanism analyses reveal that these policies optimize firms’ human capital by increasing the share of highly educated and technical employees, thereby enhancing technological innovation, patent output, production quality, and efficiency. Conclusions: This research extends the capital–skill complementarity theory by highlighting the importance of specialized talent for intelligent transformation. The results offer data-driven insights for refining talent policies to support the intelligent development of the new-energy-automobile industry. Full article

In countries and regions where Asian elephants are distributed, human–elephant conflict has become an important ecological and socio-economic issue. As one of the major habitats of Asian elephants, China faces severe challenges. Based on the theory of planned behavior and the risk perception theory, this study takes the survey data of 449 smallholder farmers in the Asian elephant distribution areas of Pu’er City, Yunnan Province as samples and uses the Tobit model and the mediating effect model to empirically analyze the impact of human–elephant conflict on farmers’ land use efficiency and its mechanism. The results show the following: (1) The human–elephant conflict risk perception has a significant negative impact on farmers’ land use efficiency. A one-unit increase in risk perception decreases land use efficiency by 250.34 CNY/mu. (2) Social networks positively moderate the negative impact of the human–elephant conflict risk perception on farmers’ land use efficiency, further strengthening the negative impact of risk perception. (3) From the perspective of the mechanism, the human–elephant conflict risk perception increases the likelihood of farmers changing their land use behavior. Farmers with high risk perception tend to reduce agricultural capital investment, which in turn leads to a decline in land use efficiency. In view of this, this paper puts forward suggestions in terms of strengthening ecological monitoring and control, increasing support for agricultural production, and guiding rational social network communication, providing theoretical support and practical guidance for alleviating human–elephant conflict and improving farmers’ land resource use efficiency. Full article

The reliability of the electrical grid is vital to economic prosperity and quality of life. Power transformers, key components of transmission and distribution systems, represent major capital investments. Traditionally, these machines have relied on petroleum-based mineral oil as an insulating liquid. However, with a global shift toward sustainability, renewable insulating materials like natural esters are gaining attention due to their environmental and fire safety benefits. These biodegradable liquids are poised to replace hydrocarbon-based oils in transformers, aligning with Sustainable Development Goals 7 and 13 by promoting clean energy and climate action. Despite their advantages, natural esters face challenges in high-voltage applications, particularly due to oxidation stability issues linked to their fatty acid composition. Various antioxidants have been explored to address this, with synthetic antioxidants proving more effective than natural ones, especially under high-temperature conditions. Their superior thermal stability ensures that natural esters retain their cooling and dielectric properties, essential for transformer performance. Furthermore, integrating machine learning and artificial intelligence in antioxidant development and monitoring presents a transformative opportunity. This review provides insights into the role of antioxidants in natural ester-filled power equipment, supporting their broader adoption and contributing to a more sustainable energy future. Full article

The transition to clean energy is crucial for mitigating the impacts of climate change and achieving sustainable development. Reliance on fossil fuels, which are integral to manufacturing and transportation, remains a major contributor to greenhouse gas (GHG) emissions. Biomass gasification presents a renewable energy alternative that can significantly reduce emissions. However, proper disposal of municipal solid waste (MSW) and agricultural residues, such as date palm waste (DPW), is an increasing global challenge, including in Qatar. This study evaluates the economic feasibility of implementing an MSW and DPW gasification plant for clean electricity generation in Qatar. The country’s growing population and economic development have led to substantial waste production, making it an ideal location for waste-to-energy (WTE) initiatives. Using discounted cash flow (DCF) analysis, the study estimates the capital cost of a 373 MW_th facility at approximately $12.07 million, with annual operating costs of about $4.09 million and revenue of $26.88 million in 2023. The results indicate a net present value (NPV) of $245.77 million, a return on investment (ROI) of 84.80%, a payback period of approximately 5 years over a 20-year project lifetime and a net reduction of 206,786 tonnes CO₂ annually. These findings demonstrate the economic viability of biomass gasification in Qatar while contributing to reduced GHG emissions and advancing the country’s sustainability goals under Qatar National Vision 2030. Full article

Investigating the spatio-temporal trends in agricultural green production level and proposing pathways to improve it can offer valuable insights for promoting the green, low-carbon, and sustainable development of China’s agriculture, as well as contributing to the achievement of the United Nations’ Sustainable Development Goals by 2030. Therefore, in order to investigate the spatio-temporal variations in agricultural green production level and its driving factors, and explore pathways to improve it in the major grain-producing areas of China, a new multi-dimensional framework for estimating the agricultural green production level was proposed, and based on the OLS regression and scenario prediction, the agricultural green production levels from 2012 to 2030 were estimated. The findings indicate that from 2012 to 2021, the agricultural green production level in the major grain-producing areas experienced a consistent annual increase. The average annual value for the agricultural green production level was recorded at 0.443. At a spatial scale, the agricultural green production level exhibited a pronounced regional pattern, showing higher levels in the central and eastern areas, while lower levels were noted in the northeastern and western regions. The actual utilization of foreign capital and the per capita disposable income of farmers positively influenced the agricultural green production level. In contrast, factors such as the proportion of the secondary industry, the proportion of the tertiary industry, and the urbanization rate negatively affected this level. From 2022 to 2030, the agricultural green production level is expected to demonstrate a gradual growth trend under the baseline scenario, although the rate of growth is expected to decrease over time. Conversely, under the green and sustainable development scenario, a notably significant growth trend in agricultural green production level is projected. However, under the rapid economic development scenario, it is estimated that the agricultural green production level will initially increase slowly before peaking in 2026 and then experiencing a decline. With the aim of ensuring the ongoing enhancement of agricultural green production level objectives, the major grain-producing areas should proactively encourage inter-provincial collaboration in agricultural green production, vigorously attract foreign investment to facilitate the advancement of green production technologies, promote the harmonious integration of primary, secondary, and tertiary industries in rural regions, and improve farmers’ income. Full article