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The present study attempts to examine the link between trade openness and sustainable human development (SHD) in 19 emerging economies. The study used the data for the period from 1996 to 2019. The study employed fixed-effect regression with Driscoll-Kraay standard error techniques robust to cross-section dependence. The study found the favorable impact of trade openness on sustainable development through sustainable human development. Trade openness affects sustainable human growth in many ways. It is a critical component that should not be ignored in sustainable development policies. Moreover, foreign direct investment, economic growth, and renewable energy consumption positively impact the sustainable human development. In contrast, innovations and institutional quality have an adverse impact on SHD. The study also provides policy suggestions for the emerging economies that will promote all the dimensions of sustainable development: economic, social, and environmental.

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Background: Achieving universal health coverage is one of the prominent targets of the United Nations' sustainable development goals. Reducing out-of-pocket expenditure (OOPE) is essential because high OOPE can deter the use of healthcare services, which can lead to poor health outcomes and medical impoverishment. Objectives: The study sought to determine the effects of various factors such as Domestic General Government Health Expenditure, Gross Domestic Product, Government schemes and compulsory contributory healthcare financing schemes, and Voluntary health insurance schemes on OOPE per Capita in emerging economies. Design: Econometric methods using panel data. Data Sources and Methods: The study analyzed the publicly available panel data from the World Health Organization using fixed, random, and dynamic models. Results: Domestic General Government Health Expenditure and Gross Domestic Product are associated with an increase in OOPE. Government schemes, compulsory contributory healthcare financing schemes, and voluntary health insurance programs are linked to a reduction in OOPE. Conclusion: In conclusion, this study, conducted through econometric methods on panel data, sheds light on the critical importance of reducing OOPE to achieve universal health coverage, aligning with the United Nations' sustainable development goals. Countries shall implement a holistic approach focusing on preventive healthcare and health promotion, providing comprehensive health insurance, strengthening public health systems, and regulating medicine prices.

Making healthcare affordable in emerging economies This study examines how to make healthcare more affordable in developing countries. People often skip needed care due to high out-of-pocket costs (money paid directly for medical services). The researchers analyzed data across multiple countries to see what affects these costs. They found that while government spending on healthcare and a strong economy are good things, they can ironically lead to people paying more out of pocket for medical care. However, government healthcare programs, mandatory health insurance, and even voluntary insurance plans can all help bring these costs down. The study suggests that keeping these out-of-pocket costs low is key to achieving the United Nations' goal of everyone having access to healthcare. Countries can achieve this by focusing on preventive care, ensuring everyone has health insurance, strengthening public health systems, and keeping the price of medicine under control.

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Background: Currently, China is steadily pursuing high-quality development and promoting common prosperity, for which residents' health is a precondition. However, high housing-price-to-income ratios and rent-to-income ratios have already triggered many social problems and have substantially affected people's work and life. It is of practical significance to examine the relationship between housing burden and residents' health. Methods: Combining city-level housing price-to-income ratio data and residents' health data from the China Family Panel Studies, this study employs a binary logit model to investigate the impact and mechanism of housing burden on residents' physical and psychological health. Results: Overall, a 1% increase in the housing-price-to-income ratio leads to a 1.2% decrease in physical health and a 1.9% decrease in psychological health. In terms of different psychological state indicators, a 1% increase in the housing price-to-income ratio leads to a 1.1% increase in depression, 1.1% increase in nervousness, 1.4% increase in relentlessness, 1.4% increase in hopelessness, 1.0% increase in a sense of incapability, and 1.4% increase in meaninglessness. According to mechanistic analyses, a 1% increase in the housing-price-to-income ratio leads to increases of 0.6 and 0.7% in the smoking rate and late sleep rate, respectively, while it leads to a 0.9% decrease in the noon nap rate. Conclusion: A growing housing burden significantly negatively impacts both the physical and psychological health of residents and increases the possibility of negative emotions. Further investigation revealed that the housing burden damages residents' health by increasing their likelihood of smoking and sleeping late and decreasing their likelihood of taking a nap at noon, while exercise alleviates the negative impacts of the housing burden on residents' physical and psychological health. Finally, we also find that housing burdens' impacts on physical and psychological health differ significantly in terms of gender, age, and educational attainment. From the perspective of improving livelihoods, governments should consider the relationship between housing burdens and residents' health when formulating livelihood policies. Location-specific and targeted policies should be followed. Additionally, efforts should be made to promote exercise among citizens.

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The advancement of artificial intelligence (AI), algorithm optimization and high-throughput experiments has enabled scientists to accelerate the discovery of new chemicals and materials with unprecedented efficiency, resilience and precision. Over the recent years, the so-called autonomous experimentation (AE) systems are featured as key AI innovation to enhance and accelerate research and development (R&D). Also known as self-driving laboratories or materials acceleration platforms, AE systems are digital platforms capable of running a large number of experiments autonomously. Those systems are rapidly impacting biomedical research and clinical innovation, in areas such as drug discovery, nanomedicine, precision oncology, and others. As it is expected that AE will impact healthcare innovation from local to global levels, its implications for science and technology in emerging economies should be examined. By examining the increasing relevance of AE in contemporary R&D activities, this article aims to explore the advancement of artificial intelligence in biomedical research and health innovation, highlighting its implications, challenges and opportunities in emerging economies. AE presents an opportunity for stakeholders from emerging economies to co-produce the global knowledge landscape of AI in health. However, asymmetries in R&D capabilities should be acknowledged since emerging economies suffers from inadequacies and discontinuities in resources and funding. The establishment of decentralized AE infrastructures could support stakeholders to overcome local restrictions and opens venues for more culturally diverse, equitable, and trustworthy development of AI in health-related R&D through meaningful partnerships and engagement. Collaborations with innovators from emerging economies could facilitate anticipation of fiscal pressures in science and technology policies, obsolescence of knowledge infrastructures, ethical and regulatory policy lag, and other issues present in the Global South. Also, improving cultural and geographical representativeness of AE contributes to foster the diffusion and acceptance of AI in health-related R&D worldwide. Institutional preparedness is critical and could enable stakeholders to navigate opportunities of AI in biomedical research and health innovation in the coming years.

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Objective: This study aims to disclose and compare meat consumer segments in Switzerland and Vietnam, which differ in terms of their socioeconomic and cultural settings (the former is a developed country, and the latter is an emerging one) to develop a set of segment-specific recommendations that might be applied to consumption in comparable contexts, that is, in other developed countries and other emerging economies. Methods: Data were collected through two online surveys: one for Swiss residents from randomly selected households and one for Vietnamese urban residents recruited via snowball sampling. The final sample size was N = 643 for Switzerland and N = 616 for Vietnam. Hierarchical cluster analyses followed by K-means cluster analyses revealed five distinct clusters in both countries. Results: Three clusters were common to both countries: meat lovers (21% in Switzerland and 19% in Vietnam), proactive consumers (22% in Switzerland and 14% in Vietnam) and suggestible consumers (19% in Switzerland and 25% in Vietnam). Two were specific to each country, namely traditional (19%) and basic (21%) consumers in Switzerland and confident (16%) and anxious (26%) consumers in Vietnam. Conclusion: Relying on voluntary actions, nudging techniques, private initiatives and consumers' sense of responsibility will certainly be useful but will nevertheless be insufficient to achieve a planetary health diet within the given timeframe (the 2030 Agenda for Sustainable Development). Governments will have no choice but to activate all levers within their sphere of influence - including regulatory measures - and oblige private sector actors to commit to the measures imposed on them. A binding international agenda with common objectives and measures is a judicious approach. Unlike most previous studies, which focused on meat consumption intensity and frequency or diet type to segment consumers, our approach, based on psychographic profiles, allows the identification of segments that share common drivers and barriers and thus the development of better-targeted measures to reduce meat consumption.

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The UN Sustainable Development Goals (SDGs) were developed in 2015 and serve as the main guide for achieving the 2030 Agenda. This paper analyses the impact of corporate governance (CG) and financial performance (FP) on SDG prioritisation, taking FP as a mediating variable and categorising the SDGs by the five pillars (5 Ps) commonly used for this purpose: People, Planet, Prosperity, Peace and Partnership. For this purpose, structural equations (PLS-SEM) were applied, using a sample of 312 Latin-American firms. The study results show there is a positive relationship between FP, CG and SDG prioritisation. Moreover, FP has a partial mediating role in the relationship between CG and SDG prioritisation. This study is innovative in the context of emerging Latin American economies and suggests paths for future research on this topic that would be of interest to academics, regulators and industry professionals. This paper highlights the important role of CG in helping achieve the objectives of the 2030 Agenda in Latin America. Furthermore, the study has implications for policymakers, showing that CG may enhance companies' FP and their commitment to the SDGs. Accordingly, regulators should establish minimum requirements for all companies regarding the structure and practices of CG. The study findings also have implications for stakeholders and responsible investors, suggesting that companies' level of sustainable development can be assessed via their CG policies.

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This study delves into the impact of formal institutions on stock market volatility within a selection of emerging economies. Specifically, it examines the role that formal institutions play in shaping this volatility. To accomplish our goal, we analyze panel data from 46 emerging nations spanning the years 2000-2019, utilizing system generalized method of moments (GMM), as well as random and fixed effect models for our estimations. The findings of this research validate the existence of a significant association between formal institutions and stock market volatility. Likewise, through dynamic panel estimation, we discover that formal institutions such as property rights, financial freedom, and government regulations have a notable negative effect on stock market volatility. Consequently, this study implies that formal institutions play a crucial role in reducing stock market volatility in emerging economies, fostering their development. The insights gained from this research encourage policymakers to view formal institutions as key influencers of stock market volatility. These results offer valuable guidance for emerging nations.

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This study collected data on waste generation and management in China between 1979 and 2020 from government statistics and literature and reviewed the development of municipal solid waste (MSW) management in China. The extended stochastic impact by regression on population, affluence and technology (STIRPAT) model was employed to identify the driving forces of MSW generation, and the cointegration analysis showed that economy (0.35, t = -3.47), industrial structure (3.34, t = -20.77) and urbanization (-1.5, t = 5.678) were the significant socioeconomic driving forces in the long run. By employing the framework of evolutionary economics, this study then investigated the internal rules of long-term interaction between socioeconomic factors and MSW management. The results indicate that, in the long run, MSW management development can be viewed as an evolutionary process that includes a continuous adaptation to external socioeconomic factors and the co-evolution of internal institutions and technologies. Adaptation and diversity of institutions and technologies play an important role in achieving sustainable waste management and circular economy (CE). This study offers a novel evolutionary perspective for explaining dynamic changes of MSW management in China, as well as recommendations for emerging economies to achieve sustainable waste management and CE goals.

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An overview of blockchain fundamentals and its potential benefits for sustainability is provided. The role of expertise as an intermediary on the blockchain to drive transparency and accountability is examined. This research examines the potential of blockchain technology in the field of economic management and to drive future sustainable development in emerging companies, which are referred to as hidden champions. This study addresses the need for transparent and responsive practices that promote social stability, economic growth, and environmental sustainability. The goals are to analyze economic functions, investigate the formation of appropriate economic patterns, facilitate equitable distribution, and support environmental protection efforts. The research method includes case studies and theoretical frameworks to collect relevant data. The results emphasize the importance of balancing competing interests, promoting security, and strengthening inclusive decision-making processes. This study emphasizes the intersection between economic development and environmental protection and highlights the role of sustainability criteria in guiding land use practices. The conclusion emphasizes that sustainable economic practices are critical for social, economic and environmental development, especially in emerging economies. Practical recommendations are provided to policymakers and stakeholders to improve economic governance frameworks and help achieve the Sustainable Development Goals.

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OBJECTIVES: Leukemia diagnosis in Vietnam is limited by a lack of hematopathology training and expert consultation as well as the cost of high-magnification digitization of hematology slides. Screen-sharing software allows international collaboration with experienced hematopathologists for improved diagnostic accuracy. METHODS: A hematopathology education and consultation program was proposed for Vietnam hospitals. By appointment, pathologists in Vietnam with access to a microscope camera, imaging software, and high-speed internet were invited to review slides and data with a volunteer board-certified hematopathologist in the United States using secure videoconferencing software. A single hospital in southern Vietnam assigned a pathologist proficient in English to access this service. All consultations from this site with clinicopathologic information were logged. After a 2-year period of online consultation, case slides for selected diagnoses were reviewed under the microscope in Vietnam to assess concordance. RESULTS: In total, 135 consultations were logged, 53 of which were for blood and bone marrow. T-cell large granular lymphocytic leukemia (T-LGLL) was 1 of the most frequent bone marrow consultation-related diagnoses; all diagnoses of this entity were confirmed by in-person microscopy (100% concordance). A records search and physician surveys found no prior documented diagnoses of T-LGLL made in Vietnam before this education and consultation program. CONCLUSIONS: Our virtual consultation model has improved patient care in Vietnam by providing correct diagnoses to inform best practices in treatment. As a result of our program, the first Vietnam diagnoses of T-LGLL were made and may help expand on the literature in this area. This model could provide cost-effective, real-time consultation and education services for pathologists in underserved communities.

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Emerging economies have prioritized the enhancement of carbon and energy productivity to uphold environmental integrity. Consequently, the policymakers introduced the environmental policy stringency measure to control emission activities. Accordingly, this study explores the environmental stringency policy's impact on carbon, energy, and non-energy productivity over the period of 1995-2020. This study addresses the impact of environmental policy stringency on quality of life (exposure to environmental risk). Regardless of variation, growing economies have higher carbon productivity. It is worth noting that energy productivity compared to carbon is higher. Based on the findings derived from the CS-ARDL model, it can be concluded that environmental stringency policies significantly positively impact carbon productivity in emerging countries. Economies that implement stringent environmental rules have the potential to enhance both energy and non-energy productivity to a greater extent. Meanwhile, the environmental policy effectively reduces environmental risk exposure and increases the quality of life. Environmental technology is inefficient in promoting emerging economies' environmental productivity. Similarly, trade promotes carbon activities and may involve comparative advantage race, pollution heaven hypothesis possible to exist. This study provides empirical evidence supporting the notion that investing in human capital is crucial in enhancing productivity. The findings suggest a more comprehensive and integrated approach to environmental policy in rising economies. This all-encompassing strategy is considered crucial for making significant gains in carbon productivity and simultaneously promoting sustainable green growth.

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BACKGROUND: Using the World Health Organization Classification 5th edition (beta version online; WHO-HAEM5bv) in emerging economies is key to global healthcare equity. Although there may be ongoing updates, hesitancy in accepting and reporting these diagnoses in publication conflicts with the WHO's commitment to global accessibility. Aggressive NK cell leukemia (ANKL) and systemic EBV-positive T-cell lymphoma of childhood (SEBVTCL) with CD4-positive immunophenotype are both rare entities, are most described in Asians and East Asians, are associated with prior systemic chronic active EBV disease (CAEBV), and presentation with Hemophagocytic Lymphohistiocytosis (HLH). Recognizing and diagnosing any one of these entities requires not only training and experience in hematopathology, but good cooperation between clinical physicians and all areas of the laboratory. We describe a 30-year-old woman who presented to a Vietnam hospital and was rapidly diagnosed with ANKL, SEBVTCL, and HLH using WHO-HAEM5bv essential criteria, aided by expert consultation from a United States (US) board certified hematopathologist in real-time using video conferencing software. METHODS: Zoom™ videoconferencing software; Immunohistochemistry; flow cytometric immunophenotyping; polymerase chain reaction (PCR), Next Generation Sequencing (NGS). RESULTS: At the time of hospital admission, automated complete blood count (CBC) with differential count showed slight anemia, slight lymphocytosis, and moderate thrombocytopenia. HIV serology was negative. Whole blood PCR for EBV was positive showing 98,000 copies/ml. A lymph node biopsy revealed histology and immunohistochemistry consistent with the online beta version WHO-HAEM5 classification of SEBVTCL arising in CAEBV. Blood and bone marrow studies performed for staging revealed no histologic or immunohistochemical evidence of T-cell lymphoma in the bone marrow core, however, atypical blood smear lymphocyte morphology and blood immunophenotyping by flow cytometry were consistent with WHO-HAEM5 classification of ANKL. NGS revealed no evidence of genetic variant(s) associated with HLH in Vietnam. All laboratory studies were performed at Blood Transfusion Hematology Hospital (BTHH) in Ho Chi Minh City Vietnam. CONCLUSION: Although Vietnam, an emerging economy, currently lacks the laboratory infrastructure to more rigorously confirm a rare synchronous presentation of two distinct EBV-driven T/NK cell neoplasms, these two concomitant diagnoses were made using only laboratory techniques available in Vietnam with the help of WHO-HAEM5bv and real-time video consultation by a US hematopathologist.

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This study assesses the relationship between financial inclusion and low-carbon development and its implications for regional development. Data envelopment analysis (DEA) is used to analyse data from a sample of E7 countries from 2001 to 2020. Results show that financial inclusion and low-carbon development are significantly related, indicating that financial inclusion is a significant driver of low-carbon development. Additionally, regional differences between E7 countries in financial inclusion and low-carbon development are identified, highlighting the need for region-specific policies to promote sustainable development. Moreover, findings show that deposits, bank accounts, and ATMs of all E7 economies contribute to environmental and economic growth inputs. The findings have important implications. Therefore, encouraging low-carbon growth via increased financial inclusion may be successful. Access to financial services, financial literacy, and financial innovation are all areas where policymakers might do more to advance the cause of financial inclusion. Accounting for variations in financial inclusion and low-carbon development between regions is important when crafting policies to encourage sustainable development. The economic climate, cultural norms, and institutional structures of a given area must all be considered by policymakers if they are to craft plans that will be successful.

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This study examines the role of environmental degradation in macroeconomic instability for a balanced panel sample of 22 emerging market economies from 1996 to 2019. Governance is included in the macroeconomic instability function as a moderating factor. Besides, bank credit and government spending are also included in the estimated function as control variables. The long-run results from using the PMG-ARDL method show that environmental degradation and bank credit induce macroeconomic instability, whereas governance and government spending reduce it. Interestingly, environmental degradation creates greater macroeconomic instability than the bank credit. We also find that governance being a moderating factor weakens the adverse impact of environmental degradation on macroeconomic instability. These findings are robust to the FGLS technique, suggesting that governments in emerging economies should prioritize environmental degradation and governance in mitigating climate change and ensuring macroeconomic stability in the long run.

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Studies have shown that energy consumption from economic development leads to an increase in carbon emissions. Emerging economies, as important sources of carbon emissions with high growth potential, play a crucial role in global decarbonisation efforts. However, the spatial pattern and evolution trend of carbon emissions in emerging economies have not been studied in depth. Therefore, this paper uses the improved gravitational model and carbon emission data from 2000 to 2018 to construct a spatial correlation network of carbon emissions in 30 emerging economies around the world, aiming to reveal the spatial characteristics and influencing factors of carbon emissions at the national level. The results show that the spatial network structure of carbon emissions in emerging economies is closely linked, forming a "big network" of interconnection. Amongst them, Argentina, Brazil, Russia, Estonia, etc. are at the centre of the network and play a leading role. Geographical distance, economic development level, population density, and scientific and technological level have a significant impact on the formation of spatial correlation between carbon emissions. Further use of GeoDetector shows that the explanatory power of two-factor interaction on centrality is greater than that of a single factor, indicating that a single economic development cannot well enhance the influence of countries in the carbon emission network, and needs to be combined with factors such as industrial structure and scientific and technological level. These results are helpful to understand the correlation between carbon emissions between countries from the perspective of the whole and part and provide a reference for optimizing the carbon emission network structure in the future.

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The purpose of this research is to synthesize the fragmented extant knowledge on flexible and green supply chain management (FGSCM) in the context of emerging economies and to unearth research gaps to motivate future research. We adopted a novel structured systematic literature review by triangulating a systematic literature review, text mining, and network analysis. Institutional theory and contingency theory were employed to analyze the results of the review. The results show that, firstly, research on FGSCM in emerging economies, despite its importance, is immature compared to general FGSCM literature. Second, the specificities of strategies and practices that distinguish this topic in emerging economies are discussed and the drivers and barriers are identified with respect to sources of institutional pressure. Third, a research framework for FGSCM in emerging economies is developed and 12 gaps for future research are identified. This study has exclusively developed a research framework for FGSCM in an emerging economy which has received the least consideration in the literature and practice. The framework was developed to synthesize the existing literature and to identify the research gaps to inspire future research.

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Emerging economies are predicted to be future emission hotspots due to expected levels of urbanization and industrialization, and their CO2 emissions are receiving more scrutiny. However, the driving forces underlying dynamic change in emissions are poorly understood, despite their crucial role in developing targeted mitigating pathways. We firstly compile energy-related emissions of 30 selective emerging economies from 2010 to 2018. Then, three growth patterns of emissions in these economies have been identified through emission data, which imply different low-carbon pathways. Most emerging economies saw an increase of varying degrees in emissions, driven by economic growth and partly offset by better energy efficiency and improvements in energy mixes. Furthermore, the industrial structure was another factor that slowed emissions, especially in Latin America and the Caribbean. Our research contributes to the heterogeneous exploration of CO2 emissions produced by energy among sectors and the creation of low-carbon development pathways in emerging economies.

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The COVID-19 pandemic proved to be an unprecedented socio-economic crisis in the last decades. More than three years after its outbreak, there is still uncertainty regarding its future evolution. National and international authorities adopted a prompt and synchronized response to limit the adverse effects of the health crisis, in terms of socio-economic damage. Against this background, this paper assesses the efficiency of the measures implemented by fiscal authorities in selected Central and Eastern European countries to ameliorate the economic repercussions of the crisis. The analysis reveals that the impact of expenditure-side measures is stronger than that of revenue-side ones. Additionally, the results of a time-varying parameter model indicate that the fiscal multipliers are higher in times of crisis. In view of the ongoing war in Ukraine, the related geopolitical turmoil and energy crisis, the findings of this paper are especially pertinent, given the need for additional fiscal support.

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The paper investigates the co-movement of COVID-19 pandemic and performance of stock markets of four emerging economies. The Quantile-on-Quantile regression model was applied to daily share prices of stock markets from March 13, 2020 to November 30, 2021 in these economies. The results indicate varied relationships across various quantiles of COVID-19 cases and share prices. Whilst both positive and negative relationships are established at different quantiles of share prices for Brazil and Kenya, negative co-movements are recorded for India and South Africa for all quantiles of share prices. The varying dependence between COVID-19 and stock markets provide critical insights to policy makers.

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This study takes a new look at the stock price-exchange rate nexus and attempts contributions to the extant studies in a number of intuitive ways. First, we analyze the reverse relationships given the theory-backed two-way causality between the two variables. We reassess the nexus across the First, Second and Third Waves of the COVID-19 pandemic, as well as comparison between advanced and emerging economies. Third, we adopt a panel modeling approach that simultaneously takes nonstationarity, cross sectional dependence, and asymmetry into account. The data analyses show that the relationship is statistically negative for the two nexuses. The magnitudes were higher during the crisis (the COVID-19 pandemic) although the relationship broke down during the Second Wave as the Delta variant surged. We identify relevant investment and policy implications of the findings.