Search Results (5,494)

The rapid growth of road freight has increased urban carbon emissions, but decarbonization in this sector remains slow compared to other areas. This study examines city-level road freight decarbonization, focusing on extreme values, with the goal of establishing a quantitative reference indicator for tailored policies. Using data from 342 Chinese cities, we applied K-means clustering and Extreme Value Theory (EVT) to estimate the extreme levels of freight vehicles decarbonization (FVDEL) under various economic scenarios. Results show notable differences among city types. High-Tech and Light Industry Cities (Type I) display a more substantial decarbonization potential, with a key threshold around 1.27%. Surpassing this level indicates higher readiness for zero-emission road freight, while Heavy Industry-Manufacturing Cities (Type II) tend to behave more predictably during economic ups and downs because of their close ties between industry and freight activities. The study also finds that purchase subsidies tend to have diminishing returns, whereas operational incentives like electricity price discounts and road access advantages are more effective in maintaining adoption. By proposing EVT-based thresholds as practical benchmarks, this research connects statistical modeling with policy implementation. The proposed reference indicator offers useful guidance for assessing urban decarbonization capacity and developing customized strategies to promote zero-emission freight systems. Full article

This study investigates the complex interplay between internal communication, psychological well-being, and job satisfaction, as well as their influence on employee retention and job performance in Romania’s post-pandemic hospitality sector. In this study, data were collected from 350 employees across hotels, restaurants, and resorts. A Covariance-Based Structural Equation Modeling (CB-SEM) approach was employed for the analysis. Findings suggest that both internal communication and psychological well-being are significant positive predictors of job satisfaction. In turn, job satisfaction is a powerful driver of both employee retention and job performance. A key finding is that job satisfaction fully mediates the relationship between psychological well-being and job performance, with no direct effect observed between the latter two constructs. These results underscore that fostering an employee-centric environment is crucial for achieving social sustainability, directly supporting global Sustainable Development Goals (SDG 8: Decent Work and Economic Growth and SDG 3: Good Health and Well-being). Theoretical and practical implications, as well as limitations and future research directions, are discussed. Full article

Against the backdrop of China’s “dual carbon” strategy (carbon peaking and carbon neutrality), provincial-level carbon emission research is crucial for the implementation of related policies. However, existing studies insufficiently cover the driving mechanisms and scenario prediction for energy-importing provinces. This study can provide theoretical references for similar provinces in China to conduct research on carbon dioxide emissions from energy consumption. The carbon dioxide emissions from energy consumption in Jiangsu Province between 2000 and 2023 were calculated using the carbon emission coefficient method. The Tapio decoupling index model was adopted to evaluate the decoupling relationship between economic growth and carbon dioxide emissions from energy consumption in Jiangsu. An extended STIRPAT model was established to predict carbon dioxide emissions from energy consumption in Jiangsu, and this model was applied to analyze the emissions under three scenarios (baseline scenario, low-carbon scenario, and enhanced low-carbon scenario) during 2024–2030. The results show the following: (1) During 2000–2023, the carbon dioxide emissions from energy consumption in Jiangsu Province ranged from 215.22428 million tons to 783.94270 million tons, with an average of 549.96280 million tons. (2) The decoupling status between carbon dioxide emissions from energy consumption and economic development in Jiangsu was dominated by weak decoupling, accounting for 91.304%, while a small proportion (8.696%) of expansive coupling was also observed. (3) Under the baseline scenario, the carbon dioxide emissions from energy consumption in Jiangsu in 2030 will reach 796.828 million tons; under the low-carbon scenario, the emissions will be 786.355 million tons; and under the enhanced low-carbon scenario, the emissions will be 772.293 million tons. Furthermore, countermeasures and suggestions for reducing carbon dioxide emissions from energy consumption in Jiangsu are proposed, mainly including strengthening the guidance of policies and institutional systems, optimizing the energy consumption structure, intensifying technological innovation efforts, and enhancing government promotion and publicity. Full article

This paper investigates how renewable electricity production, energy consumption, and economic openness influence economic growth in the Gulf Cooperation Council (GCC) countries from 2008 to 2023. Using annual panel data for six countries—Saudi Arabia, UAE, Qatar, Bahrain, Kuwait, and Oman—we apply both the Pooled Mean Group (PMG) and Dynamic Fixed Effects (DFEs) estimators to explore short-run dynamics and long-run equilibrium relationships. These methods are preferred because they balance flexibility with efficiency where PMG allows country differences in short-run dynamics, while DFE provides robustness under small-sample conditions, making them more suitable than the Mean Group (MG) estimator or standard Fixed Effects (FE) models for our short panel of six countries. The results show that traditional electricity consumption significantly supports economic growth in the long run, while renewable energy, despite its potential, has yet to show a statistically significant growth-enhancing effect, likely due to its currently small share in the energy mix. Foreign direct investment and trade openness display mixed impacts, with their significance varying across models. Short-run dynamics highlight the importance of energy efficiency and infrastructure readiness in shaping how energy translates into growth. Overall, the findings suggest that while energy remains central to GCC economies, the transition to renewables must be better aligned with broader development and investment strategies. These insights are highly relevant for policymakers navigating the twin goals of energy diversification and sustainable economic growth under Vision 2030 agendas. Full article

This study examines community-based wellness tourism (CBWT) in Ubud, Bali, focusing on ownership structures, community participation, and the role of local traditions. Using a qualitative design, the data were collected through semi-structured interviews with wellness stakeholders and field observations of spas and yoga centers. The findings reveal that spas are predominantly locally owned and staffed, ensuring value retention and skill development, while flagship yoga and retreat centers are dominated by non-local actors, creating risks of economic leakage and weaker cultural stewardship. Community involvement is strong in operations but limited in planning and governance, highlighting a policy–practice gap. Integrating Balinese traditions, such as Usada Bali and Melukat, could enhance authenticity but requires careful protection against commodification. The findings reveal that locally owned spas contribute to SDG 1 (No Poverty) and SDG 8 (Decent Work and Economic Growth) through local value retention, employment creation, and skill development, while non-local dominance of yoga and retreat centers risks economic leakage and weakened cultural guardianship. The study also identifies gaps in governance and planning, underscoring the need for inclusive participation and capacity building to align with SDG 11 (Sustainable Cities and Communities). Integrating Balinese traditions, such as Usada Bali and Melukat, highlights the opportunities for safeguarding cultural heritage, provided that protocols against commodification are enforced. To address these challenges, the study proposes a strategic framework emphasizing governance reform through a quadruple-helix model, shared-equity ownership, standardized human capital development, and protocol-based cultural guardianship. Despite the limitations of this being a single-case, cross-sectional study, the findings contribute to wellness tourism research by shifting attention from visitor demands to governance and equity. The study offers practical strategies for institutionalizing CBWT in Ubud while providing a transferable model for destinations seeking to balance growth with tradition. Full article

The global need for tissue and organ transplantation paved the way for plant-based scaffolds as cheap, ethical, and valuable alternatives to synthetic and animal-derived matrices for tissue regeneration. Over the years, the field has outgrown its initial scope, including the development of tissue models, platforms for drug testing and delivery, biosensors, and laboratory-grown meat. In this scoping review, we aimed to shed light on the frequency of the use of different plant matrices, the main techniques for decellularization, the functionalization methods for stimulating mammalian cell attachment, and the main results. To that purpose, we searched the keywords “decellularized” AND “scaffold” AND (“plant” OR “vegetable”) in online-available databases (Science Direct, Scopus, PubMed, and Sage Journals). From the selection and study of 71 articles, we observed a multitude of plant sources and tissues, along with a large and inhomogeneous body of protocols used for decellularization, functionalization and recellularization of plant matrices, which all led to variable results, with different extents of success (mostly in vitro). Since the field of plant-based scaffolds shows high potential for growth in the next few years, driven by emerging biotechnological applications, we conclude that future research should focus on plant sources with low economic and environmental impacts while also pursuing the standardization of the methods involved and a much deeper characterization of the scaffold performance in vivo. Full article

We refine a bottom-up, quantity-clearing framework of Bitcoin price formation that couples its fixed 21-million-coin cap with plausible demand growth and execution behavior. This approach relies on first-principles economic supply-and-demand dynamics rather than assumptions about anticipated Bitcoin price appreciation, its price history, or its potential effectiveness in demonetizing other asset classes. We considered five key high-level factors that may affect price determination: level of market demand; intertemporal investment preferences; fiat-denominated withdrawal sensitivity; initial liquid supply; and daily withdrawal levels from liquid supply. With a goal of both increasing understanding of the impacts of price drivers and developing probabilistic forecasts, we show two models: (1) a baseline to assess the impacts of parameter changes, alone and in combination, on Bitcoin price trajectories and liquid supply over time and (2) a Monte Carlo simulation that incorporates uncertainty across a range of uncertain parameterizations and presents probabilistic price and liquid supply forecasts to 2036. Our baseline model highlighted the importance of liquid supply and withdrawal sensitivity in price impacts. The Monte Carlo simulation results suggest a 50% likelihood that Bitcoin price will exceed USD 5.17 M by April 2036. Generally, prices from the low single millions to the low tens of millions per Bitcoin by 2036 emerge under broad parameter sets; hyperbolic paths to higher price levels are relatively rare and concentrate when liquid supply falls near or below BTC 2 M and withdrawal sensitivity is low. Our results help locate where right-tail risk and disorderly market outcomes concentrate and suggest that policy tools are available to help guide trajectories. Full article

Urban flood management is pivotal to the construction of resilient cities. However, investigation into the spatiotemporal evolution of urban flood resilience (UFR) and its influencing factors is insufficient. Aiming to address the challenge, this study establishes a multidimensional UFR indicator system grounded in the disaster resilience of place (DROP) model. Following the calculation of UFR through the entropy weighted technique for order preference by similarity to ideal solution (EW-TOPSIS) method, spatiotemporal evolution evaluation and factor detection are conducted. With panel data from the Yangtze River Delta Urban Agglomeration (YRDUA) over the period of 2012–2021, the results demonstrate overall UFR growth from a dominance of lowest-level and low-level cities to a more balanced distribution. Moreover, significant spatiotemporal heterogeneity is observed, with UFRs in cities adjacent to the Yangtze River higher than peripheral ones. Spatial clustering is significant until 2019, primarily manifested as High-High clusters along the Yangtze River and Low-Low clusters in northern Jiangsu and Anhui. Finally, factor detection identifies economic status, population size, environmental regulation, and drainage infrastructure as key influencing factors. These findings not only advance the understanding of UFR in urban agglomerations but also provide targeted recommendations for policymakers to enhance UFR. Full article

International tourism has helped numerous economies and regions over the years in achieving the objective of long-term sustainable economic growth. The “Association of Southeast Asian Nations (ASEAN)” is the rising hub for international tourism due to its rich history, rich vibrant culture, pleasant weather conditions, and beautiful landscape. However, research evidence about the tourism-growth relationship in the context of ASEAN economies is indeed very scarce. Accordingly, this research paper focuses on the members of the ASEAN region to examine the true influence that international tourism has on economic growth. Relevant econometric technique such as the “Fixed Effects (FEF)” is chosen for analysis based on the Hausman test, “Feasible Generalized Least Squares (FGLS)” is used for robustness, and “Two Stages Least Squares (2SLS)” is employed for tackling the likely endogeneity issue. The results show that international tourism has contributed positively to the economic growth of the ASEAN economies. Similarly, openness to global trade and education have also helped the ASEAN economies in securing long run sustainable economic growth. Lastly, the inflation rate has decelerated the pace of economic growth, while government expenditures have accelerated the pace of economic growth among ASEAN members. Our empirical findings are robust to alternative model specifications and alternative econometric estimations. Therefore, we expect our empirical findings to help the policymakers of the ASEAN economies in developing suitable policy responses regarding the growth performance of their economies through the channel of international tourism. Full article

The Community and Civil Research Group of Eötvös Loránd University (Budapest) investigated sustainable community activities in Hungary and abroad to identify local responses to global challenges. Using qualitative research methods, focus groups and interviews, this research defined the concepts of community service, community practice and working methods by analysing nearly 80 practical examples and 65 interviews in Hungary. The practical examples were used to create a “sustainable community model” and a methodological guide for community developers on how to implement community services. The steps of the process presented in the model are based on building community involvement and participation, mobilising local resources and capacities, creating community-based services, building sustainability and self-sufficiency and consolidating innovative training and community working practices. The research resulted in the creation of an online Community Repository, which provides community responses to the 17 UN Global Sustainability Challenges and Goals —economic growth, social inclusion and environmental protection—by organising the collected community services, small community practices and working methods around seven community development perspectives: governance, place, sustainable livelihoods, culture (and the arts), identity (belonging and connection), human rights and resilience and engagement and knowledge. This study provides a methodological foundation for developing resilient community-based services that contribute to sustainability, inclusivity and innovation. Full article

This study presents a bibliometric and thematic analysis of economic convergence analysis from 1982 to 2025, based on a corpus of 2924 Scopus-indexed articles. Using VOSviewer and the bibliometrix R package, this research maps the field’s intellectual structure, identifying five main thematic clusters: (1) formal statistical models, (2) institutional-contextual approaches, (3) theoretical–statistical foundations, (4) nonlinear historical dynamics, and (5) normative and policy assessments. These reflect a shift from descriptive to explanatory and prescriptive frameworks, with growing integration of sustainability, spatial analysis, and institutional factors. The most productive journals include Journal of Econometrics (121 articles), Applied Economics (117), and Journal of Cleaner Production (81), while seminal contributions by Quah, Im et al., and Levin et al. anchor the co-citation network. International collaboration is significant, with 25.99% of publications involving cross-country co-authorship, particularly in European and North American networks. The field has grown at a compound annual rate of 14.4%, accelerating after 2000 and peaking in 2022–2024, indicating sustained academic interest. These findings highlight the maturation of convergence analysis as a multidisciplinary domain. Practically, this study underscores the value of composite indicators and spatial econometric models for monitoring regional, environmental, and technological convergence—offering policymakers tools for inclusive growth, climate resilience, and innovation strategies. Moreover, the emergence of clusters around sustainability and digital transformation reveals fertile ground for future research at the intersection of transitions in energy, digital, and institutional domains and sustainable development (a broader sense of structural change). Full article

The advancement of green energy is a crucial mechanism for balancing economic growth with environmental sustainability, helping to mitigate conflicts between development and ecological preservation. This paper assesses the policy effects of the Belt and Road Initiative (BRI) on China’s overseas green energy projects (including gas) using the difference-in-difference (DID) model from 2009 to 2022. The findings show that, overall, the BRI has notably augmented China’s green energy projects in the BRI countries. This result remains robust after excluding potential interference from Nationally Determined Contributions (NDCs). Specifically, its promotional effect shows heterogeneity. Firstly, the BRI has shown significant regional differences in promoting the development of China’s overseas green energy projects. Secondly, the BRI is more effective in promoting green energy projects in developing and low-risk countries compared to developed and high-risk countries. Additionally, it indicates that the BRI boosts green energy projects in BRI countries by enhancing their infrastructure quality, encompassing transportation, energy, communication, and financial infrastructure. Finally, based on the above findings, this paper provides context-specific recommendations aimed at enhancing the effectiveness of the BRI in promoting sustainable green energy cooperation. Full article

Identifying suitable areas for ecosystem services (ES) development is essential for balancing economic growth with environmental sustainability in ecologically fragile regions. However, existing studies often neglect integrating future climate and socioeconomic drivers into ES optimization, hindering the design of robust strategies for sustainable resource management. In this study, we propose a novel framework integrating the System Dynamics (SD) model, the Patch-based Land Use Simulation (PLUS) model, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and the Dynamic Bayesian Network (DBN) to optimize ES patterns in the Sanjiangyuan region under three climate scenarios (SSP126, SSP245, and SSP585) from 2030 to 2060. Our results show the following: (1) Ecological land (forest) expanded by 0.86% under SSP126, but declined by 11.54% under SSP585 due to unsustainable land use intensification. (2) SSP126 emerged as the optimal scenario for ES sustainability, increasing carbon storage and sequestration, habitat quality, and water conservation by 3.2%, 1%, and 1.4%, respectively, compared to SSP585. (3) The central part of the Sanjiangyuan region, characterized by gentle topography and adequate rainfall, was identified as a priority zone for ES development. This study provides a transferable framework for aligning ecological conservation with low-carbon transitions in global biodiversity hotspots. Full article

The evolution of the generation mix towards deep decarbonization poses pressing questions about the role of hydropower and its possible share in the future mix. Most technical–economic analyses of deeply decarbonized systems either rule out hydropower growth due to lack of additional hydro resources or take it into account in terms of additional reservoir capacity. This paper analyzes a generation mix made of photovoltaic, wind, open-cycle gas turbines, electrochemical storage and hydroelectricity, focusing on the optimal generation mix’s reaction to different methane gas prices, hydroelectricity availabilities, pumped hydro reservoir capacities, and mean filling durations for hydro reservoirs. The key feature of the developed model is the sizing of both optimal peak power and reservoir energy content for hydropower. The results of the study point out two main insights. The first one, rather widely accepted, is that cost-effective decarbonization requires the greatest possible amount of hydro reservoirs. The second one is that, even in the case of totally exploited reservoirs, there is a strong case for increasing hydro peak power. Application of the model to the Italian generation mix (with 9500 MWp and 7250 MWp of non-pumped and pumped hydro fleets, respectively) suggests that it is possible to achieve methane shares of less than 10% if the operating costs of open-cycle gas turbines exceed 160 EUR/MWh and with non-pumped and pumped hydro fleets of at least 9200 MWp and 28,400 MWp, respectively. Full article

All over the world, the problem of ensuring the safety of pedestrians, who are the most vulnerable road users, is becoming more acute due to urbanization and the growth of micromobility. In 2013, according to WHO data, more than 270 thousand pedestrians were dying each year worldwide (accounting for 22% of all traffic accidents). Currently, experts report that around 1.3 million people die every year globally from road crashes. The roads in developing countries are particularly hazardous, according to experts, because the increase in the number of vehicles far exceeds the development of road infrastructure and safety systems. Since the risk of hitting a pedestrian depends on many factors that can have different natures, and the severity of the consequences can be determined by a set of other factors, the risk of an accident can only be reduced by influencing all these factors in a comprehensive manner. The novelty of our approach is to create an intelligent system that will gradually accumulate all the best practices into a single complex aimed at reducing the risk of an accident with pedestrians and the severity of the consequences if an accident does occur. The distinction lies in offering an integrated system where each module addresses a particular task, so by mitigating risks at every stage, one achieves a synergistic outcome. From the analysis of existing and applied developments, it is known that many specialists mainly solve a narrowly focused problem aimed at ensuring the one subsystems sustainability in the “vehicle-infrastructure-driver-pedestrian” system. Some of these ideas are given as practical examples. The relevance of the designated problem increases with the emergence of autonomous vehicles and smart cities, the sustainability of which depends on the sustainable interaction between all road users. As experience shows, only the implementation of comprehensive solutions allows us to solve strategic problems, including improving road safety. Here, by complex solutions we mean solutions that combine technical issues, as well as environmental, social, and managerial aspects. To account for different kinds of effects, indicator systems are developed and composite indices are computed to choose the most rational solution. The novelty of our approach consists in combining within a unified DSS algorithms for assessing the efficiency of the proposed solution with respect to technological soundness, environmental sustainability, economic viability, social acceptability, as well as administrative rationality and computation of interrelated effects resulting from implementing any given project. In our opinion, the proposed system will lead to a synergistic effect due to the integrated application of various developments, which will ensure increased sustainability and safety of the transport system of smart cities. Our paper proposes a conceptual approach to addressing pedestrian safety, and the examples provided illustrate how the same model or algorithm can lead to positive changes from different perspectives. Full article