Search Results (29)

This study presents a comprehensive analysis of carbon emission trends and their driving factors at Shanghai Port, with a particular focus on the decoupling relationship between port economic development and carbon emissions, as well as forecasting the timeline for achieving the port’s carbon peak. The findings reveal distinct temporal patterns in emission growth: from 2009 to 2012, Shanghai Port experienced steady increases in carbon emissions, while from 2020 to 2023, it witnessed accelerated growth, primarily driven by fuel oil consumption. Using the Logarithmic Mean Divisia Index (LMDI) decomposition model, the study identifies operational revenue as the most significant contributor to carbon emission growth, while economic intensity emerges as the strongest inhibiting factor. Notably, the carbon-promoting effects of energy structure and efficiency improvements substantially outweigh the emission reductions achieved through enhanced economic intensity. The Tapio decoupling analysis indicates that during 2010–2023, neither operational revenue nor port cargo throughput capacity achieved stable decoupling from carbon emissions at Shanghai Port. Operational revenue exhibited alternating patterns of strong and weak decoupling, while cargo throughput showed more pronounced fluctuations, cycling through phases of decoupling and negative decoupling. Scenario-based predictions using the GRU-LSTM hybrid model provide critical insights: under the baseline scenario, Shanghai Port is projected to fail to achieve a carbon peak by 2035. However, both the low-carbon and enhanced mitigation scenarios project a carbon peak around 2026, with the enhanced scenario enabling earlier attainment of the target. These findings offer valuable theoretical foundations for formulating Shanghai Port’s carbon peak strategy and provide practical guidance for emission management and policy development at ports. The methodological framework and empirical results presented in this study may serve as a reference for other major ports pursuing similar decarbonization goals. Full article

Global tourism activities have become increasingly digitalized, yet the economic and environmental impacts of digitalization on tourism remain underexplored. This study develops a supply-side analytical framework to examine whether and how digitalization decouples tourism economy from carbon emissions by integrating Ghosh input-output analysis, subsystem analysis, and structural decomposition analysis. Our findings reveal that digitalization has largely decoupled China’s tourism economy from carbon emissions, with the increases in economic gains notably outpacing those in emission losses. Specifically, the digital-enabled tourism value-added (DTV) increased by approximately 18 times from 2002 to 2017, while digital-enabled tourism emissions (DTE) only grew by about 11 times. Between 2017 and 2020, due to the impact of the COVID-19 pandemic, the DTV decreased by about 61%, and DTE dropped by approximately 63.5%. The expansion in DTV can be primarily attributed to advancements in software and IT services and electronic components, while the increase in DTE is significantly driven by software and IT services and communication services. The growth in digital supply emerged as the predominant driver for the surging DTV and DTE, with the emission intensity of tourism subsectors acting as a notable constraint. This study offers both a methodological framework and empirical evidence aimed at guiding policy initiatives that target the digitalization and low-carbon transition of the tourism sector. Full article

This paper explores the impact of trade openness and exchange rate volatility on South Africa’s industrial growth from 1980 to 2024 through a hybrid econometric framework combining Autoregressive Distributed Lag (ARDL) and Structural Vector Autoregression (SVAR) models. It captures both long-term relationships and short-term economic patterns; the analysis reveals that gross domestic product (GDP) is the most significant and consistent driver of industrial value added (IVAD), while trade openness and currency volatility exert limited standalone effects. Structural shocks, notably the 2008 global financial crisis and the COVID-19 pandemic, had significant negative short-term impacts on industrial performance, highlighting systemic vulnerabilities. Robustness tests, including rolling window ARDL and first-difference GDP estimation, confirm the persistence of these relationships. Impulse response functions and forecast error variance decomposition underscore the transient and moderate influence of external shocks compared with the dominant role of internal macroeconomic fundamentals. These findings indicate that liberalisation and exchange rate flexibility must be embedded within a broader developmental strategy underpinned by institutional strength, resilience building, and sustainability principles. This study provides fresh insights supporting policy frameworks that prioritise domestic industrial capacity, macroeconomic stability, and alignment with Sustainable Development Goal 9—inclusive and sustainable industrialisation. Full article

With the increasingly urgent demand for the localization of the United Nations’ sustainable development goals (SDGs), the construction of an evaluation system and the practice paths of counties, as important spatial units of China’s sustainable development, urgently need to be deepened. Based on the articulation of the SDGs and China’s national conditions, this study innovatively designed an indicator delivery framework covering the United Nations level to the county level; constructed a county-level sustainable development evaluation indicator system that includes three dimensions, including economic development, social culture, and ecological environment; adopted the entropy weight method to determine the weights of indicators; and introduced a dynamic evaluation and analysis model utilizing three analytical methods, namely coupling coordination analysis, obstacle analysis, and Dagum decomposition, to evaluate the level of sustainable development of 76 counties in the 2010–2021 period considering both time and space. The results show that (1) the national county sustainable development index (CSDI) was significantly improved, regional differences were narrowed, the central region has the best overall performance, and the western region has the fastest growth rate; (2) economic development has become the main driving force, and the economic gap between regions has gradually narrowed, but the spatial heterogeneity of the environmental and social dimensions is still prominent; (3) the eastern region has generated positive spillover effects on the central and western regions through industrial transfer and technology diffusion, while the northeastern region develops relatively slowly due to the lagging industrial transformation; and (4) the degree of coupling coordination rises as a whole, but the differences in synergistic ability between regions are obvious. This study provides a scientific basis for the formulation of differentiated sustainable development policies for counties and emphasizes the key role of regional synergy mechanisms in narrowing the development gap. Full article

This study investigated the spatiotemporal dynamics, regional disparities, and spatial spillover effects of carbon emissions in China’s livestock sector from 2003 to 2022. By integrating carbon accounting, decoupling elasticity analysis, kernel density estimation, Theil index decomposition, and the Spatial Durbin Model, the research revealed a 6.5% reduction in national livestock carbon emissions alongside intensified spatial polarization. The decoupling relationship evolved dynamically, with strong decoupling dominating but regional fluctuations persisting, particularly in resource-dependent areas. The distribution of emission intensity shifted from unimodal right-skewness to bimodal concentration, indicating technological diffusion barriers and structural divergence across regions. Spatial econometric analysis confirmed significant emission interdependence (ρ = 0.214, p < 0.01), where neighboring economic growth increased local emission intensity. These findings highlighted the limitations of uniform policy approaches and emphasized the need for region-specific governance, market-based incentives, and localized technological innovation. The study provided empirical evidence and a policy framework to address cross-regional coordination and sustainable low-carbon transitions in agriculture. Full article

As an economically active region, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) faces dual challenges of carbon and air pollution reduction. Existing studies predominantly focus on single pollutants or engineering pathways, lacking systematic analyses of multi-scale synergistic effects. This study investigates the spatiotemporal distributions, driving factors, and synergistic effects of CO₂ and volatile organic compounds (VOCs) at the multi-scale of urban agglomerations, cities, and industries, using global Moran’s index, standard deviational ellipse, logarithmic mean divisa index decomposition model, and Tapio decoupling model. The results show that the average annual growth rate of CO₂ (7.4%) was significantly higher than that of VOCs (4.5%) from 2000 to 2020, and the industrial sector contributed more than 70% of CO₂ and VOC emissions, with the center of gravity of emissions migrating to Dongguan. Industrial energy intensity improvement emerged as the primary mitigation driver, with Guangzhou and Shenzhen demonstrating the highest contribution rates. Additionally, CO₂ and VOC reduction show two-way positive synergy, and the path of “energy intensity enhancement–carbon and pollution reduction” in the industrial sector is effective. Notably, the number of strong decouplings of the economy from CO₂ (11 times) is much higher than the number of strong decouplings of VOCs (3 times), suggesting that the synergy between VOC management and economic transformation needs to be strengthened. This study provides scientific foundations for phased co-reduction targets and energy–industrial structure optimization, proposing regional joint prevention and control policy frameworks. Full article

Urban water usage spans diverse sectors, requiring effective management strategies to address increasing demand, limited supplies, and sector-specific needs. In this study, a multi-objective urban water resource allocation model is proposed to balance economic, ecological, and social benefits, focusing on social fairness. The model considers water availability, demand diversity, and environmental factors for optimized resource allocation. An improved zebra optimization algorithm-based multi-objective evolutionary algorithm (ZOA-MOEA/D) is developed, integrating zebra optimization with a decomposition-based approach to overcome the traditional methods’ limitations, improving solution diversity and convergence. ZOA-MOEA/D consistently outperforms the NSGA-II, MOPSO, and MOEA/D algorithms in solution distribution, convergence, quality, and diversity across multiple test scenarios. By applying the model to Ningbo, China, key trade-offs between economic growth, social fairness, living standards, and ecological protection are revealed. These findings provide useful insights into urban water resource management, offering a flexible framework for balancing multiple objectives and supporting sustainable development. Despite some limitations, the approach can contribute to the ongoing development of urban water resources. Full article

In recent years, with the formal implementation of the Regional Comprehensive Economic Partnership (RCEP) and the rise of the blue economy, the trade cooperation between China and ASEAN in aquatic products has been further deepened and expanded. This paper utilizes United Nations Commodity Trade (UN Comtrade) data from 2001 to 2023 and combines the perspective of the blue economy to systematically analyze the characteristics of bilateral trade volume, growth rate, market distribution, and trade types of aquatic products between China and ASEAN. By applying the modified Constant Market Share (CMS) model, the paper conducts a factor decomposition and effect analysis of the growth factors in China’s aquatic exports to ASEAN. The analysis indicates that the competitiveness effect has the highest contribution rate, and competitiveness has been the primary driver of growth in China’s aquatic product export trade to ASEAN, followed by the growth effect increasing year by year, which shows the impact of the scale of demand, while the product effect is relatively low. In particular, product structure urgently needs improvement to meet the requirements of the blue economy. In ASEAN’s aquatic product exports to China, demand scale serves as the main driving force, with the product variety adapting to the Chinese market as a secondary contributor. However, under the blue economy framework, product sustainability and environmental friendliness have emerged as new considerations, while the contribution of competitiveness remains relatively low, suggesting a need for further enhancement to align with green trade standards. Full article

Enhancing urban ecological welfare performance is essential for achieving sustainable urban development and fostering a comprehensive regional green transformation. This study develops a quantitative assessment framework for urban ecological welfare performance, grounded in both the welfare of urban residents and their consumption of ecological resources. Employing the spatio-temporal Logarithmic Mean Divisia Index model to dissect the ecological welfare performance across 108 key prefecture-level cities within China’s Yangtze River Economic Belt, considering both temporal and spatial dimensions, the analysis reveals a “W”-shaped trajectory in the ecological welfare performance from 2006 to 2022, characterized by pronounced spatial disparities. Particularly in the downstream coastal regions and notably the Yangtze River Delta, advantages in social and economic structures, along with public fiscal outlays, contribute to a superior ecological welfare performance, exhibiting a notable spatial spillover effect. The study introduces six key factors—social benefit, economic benefit, population dispersion, population density in urban areas, urbanization scale, and ecological sustainability—to examine their influence on ecological welfare performance, uncovering substantial differences in the outcomes of temporal and spatial decomposition. Temporal decomposition indicates that economic benefit and urbanization scale are the primary drivers enhancing ecological welfare performance, whereas population dispersion is identified as the primary inhibitor. Spatial decomposition reveals that the determinants of above-average urban ecological welfare vary regionally and undergo dynamic shifts over time. Overall, a holistic understanding of the interplay among economic growth, ecological preservation, and the enhancement of residents’ welfare can inform the development and execution of tailored policies by local governments. Full article

Against the backdrop of climate change and the “dual carbon” goals, enhancing the ecological efficiency of cryospheric tourism is crucial not only for the high-quality development of the tourism industry itself but also for the protection of the ecological environment and the promotion of green sustainable development in the cryospheric region. In light of this, this study, taking climate change as its background and based on the perspective of carbon emission constraints, integrates multidimensional factors such as “climate change, carbon emission constraints, and cryospheric resources” into a unified measurement framework to construct a model for evaluating the ecological efficiency of tourism in the cryosphere. Specifically, the model considers inputs, expected outputs, and unexpected outputs. Subsequently, employing the super-efficiency slack-based measure (SBM) model, this study measures the tourism ecological efficiency (TEE) of three provinces (Xinjiang, Qinghai, Tibet) in the cryosphere from 2013 to 2021 and utilizes the Malmquist–Luenberger index and gray correlation model to reveal their dynamic changes, efficiency decomposition, and influencing factors. The results indicate that: (1) The overall mean of TEE in the cryosphere is between 0.2428 and 1.2142, Over the study period, the average annual growth rate and corresponding confidence interval were 14.74%, (−8.61%, 64.23%), showing a significant fluctuating growth trend. Among them, Xinjiang stands out, with its mean scores ranging from 0.2418 to 1.6229, surpassing the overall average level of the cryosphere. (2) During the study period, the overall dynamic efficiency of tourism ecology in the cryosphere increased by 21.54%, driven by the synergy of technological progress (TC), pure technical efficiency (PET), and scale efficiency (SE). For each province, the dynamic efficiency of tourism ecology has improved, but to varying degrees. (3) Regarding the driving factors of TEE in the cryosphere, each driving factor is closely related to TEE, ranked from large to small as follows: carbon emission structure, level of economic development, infrastructure, intensity of technological input, industrial structure, resource endowment, and environmental regulation. This article holds theoretical and practical significance for promoting the high-quality development of polar tourism and achieving synergistic progress between the economy and environment. Full article

The digital divide (DD) reflects the inequality of the digital economy, while existing research lacks a comprehensive framework for investigating the measurement of DD and its determinants. This study constructs a new framework with a five-dimensional comprehensive index system. City-level data are used to measure China’s DD index from 2010 to 2020 at the national, regional, and provincial levels. Furthermore, this study investigates the decomposition of DD at both regional and provincial levels and the determinants of DD from the perspectives of physical, human, and social capital. The key results are: (1) China’s DD has generally exhibited a fluctuating downward trend. While it remains high in the eastern and western regions, it has shown a decline year by year. However, the DD within most provinces is on the rise. (2) The intra-regional and inter-provincial are the primary drivers of changes in national DD, with both intra-regional and intra-provincial contribution rates on the rise. (3) Economic growth, infrastructure, foreign trade, education, and online interaction significantly impact DD, and these determinants may change at different periods. This study intends to provide empirical support for bridging the DD, fostering the balanced development of the digital economy, and reducing social inequality. Full article

With the increase in regional economic development disparities, a regional coordinated development strategy is put forward that prioritizes human welfare and holistic social progress over a purely materialistic growth model. To address the challenges of balanced regional development, this paper has developed a multidimensional assessment framework of social development encompassing education, healthcare, culture, and social security. Using the entropy weight TOPSIS method, this study measures the social development level across 296 Chinese prefecture-level cities from 1990 to 2020. It explores the spatio-temporal evolution characteristics of China’s social development level through the Dagum Gini coefficient decomposition method and exploratory spatial data analysis. The results indicate that (1) the level of social development in China exhibits a fluctuating upward trend over the time series, showing a phase-wise pattern of decline–rise–rise; (2) there is a clear heterogeneity in the level of social development, with a general hierarchy of Eastern, Northeastern, Western, and Central regions in terms of social development; (3) spatially, China’s social development level has evolved from a patchy distribution in 1990 to a clustered distribution around urban agglomerations by 2020, with pronounced characteristics of spatial imbalance; (4) the level of social development in China displays varying degrees of spatial clustering, with this trend intensifying over time; and (5) over the period 1990–2020, the overall disparity in China’s social development level presents a fluctuating trend, with a notable reduction after an initial increase, and regional disparities following the order of Central, Western, Eastern, and Northeastern regions. This research offers valuable insights for policymakers and scholars seeking to understand and enhance China’s social development landscape. Full article

In South Africa, the agricultural sector is a crucial pillar of the economy, with the livestock and grain industries playing significant roles in ensuring food security, fostering economic growth, and providing employment opportunities, particularly in rural areas. This research addresses the relatively unexplored relationship between the livestock and grain industries in South Africa. This study employs a comprehensive approach using a VAR/VECM framework alongside VECM Granger causality tests, Toda Yamamoto causality tests, impulse response functions, and variance decomposition analysis. The main findings of this study demonstrate a long-run relationship among the study variables, with consistently low error correction terms indicating slow short-term adjustments. Significant long-run relationships were observed between grain feed prices and livestock prices, where yellow maize and soybean prices affect live weaner prices, while beef carcass prices influence yellow maize prices. Overall, the results highlight the pivotal role that yellow maize plays as a link between the South African livestock and grain markets. The study concluded that policy formulation for the South African agricultural sector must consider the interconnected nature of the grain and livestock markets to achieve sustainable and effective outcomes. Full article

Higher education evaluation presents itself as a worldwide trend. It aims to improve performance due to its importance for economic and personal growth. Graduate activities are essential for Brazilian research and innovation systems. However, previous studies have disregarded the importance of this educational level and have evaluated efficiency by jointly considering teaching and research or only undergraduate courses. Therefore, this study contributes to Brazilian reality by proving a national graduate activities efficiency evaluation that considers them as a two-stage system (formative and scientific production stages). The study provides three main methodological contributions by presenting a new centralized two-stage dynamic network data envelopment analysis (DNDEA) model with shared resources. Besides measuring efficiency, an efficiency decomposition based on a leader–follower assumption shows managers how much efficiency can alter when one of the stages needs to be prioritized. Finally, a new framework based on modified virtual inputs and outputs provides a bi-dimensional representation of the efficiency frontier. Results indicate the usefulness of the approach for ranking universities, and the need to improve scientific production, highlighting the negative impacts of COVID-19 on the formative process efficiency and showing no significant regional discrepancies regarding performance. Full article

Ecosystems provide humanity with a wide variety and high economic value-added services, from biomass structuring to genetic information, pollutants’ decomposition, water purification and climate regulation. The foundation of ecosystem services is the Eltonian Pyramid, where via prey–predator relationships, energy metabolism and biomass building take place. In the context of existing ecosystem services classification and valuation methods (e.g., CICES, MEA, TEEB), financial investments in ecosystem services essentially address the conservation of trophic pyramids. Our work’s main target is to investigate how trophic pyramids’ dynamics (stability or instability) impact the long-run discounting of financial investments on ecosystem services’ value. Specifically, a trophic pyramid with highly fluctuating populations generates higher risks for the production of ecosystem services, hence for ecological finance instruments coupled to them, due to higher temporal uncertainty or information entropy that should be incorporated into their discount rates. As this uncertainty affects negatively the net present value (NPV) of financial capital on ecosystem services, we argue that the minimization of biomass fluctuations in trophic pyramids via population control should be among the priorities of ecosystem management practices. To substantiate our hypothesis, we construct a logistic predation model, which is consistent with the Eltonian Pyramid’s ecological energetics. As the logistic predator model’s parameters determine the tropic pyramid’s dynamics and uncertainty, we develop an adjusted Shannon entropy index (H(N)_ADJ) to measure this effect as part of the discount rate. Indicatively, we perform a Monte Carlo simulation of a pyramid with intrinsic growth parameter values that yield oscillating population sizes. Finally, we discuss, from an ecological energetics standpoint, issues of competition and diversity in trophic pyramids, as special dimensions and extensions of our analytical framework. Full article