A novel approach for DDoS attacks detection in COVID-19 scenario for small entrepreneurs

Assessing the spatial-temporal environmental efficiency of global construction sector

The extensive waste emissions and energy consumption in the construction industry has spurred calls for sustainable development reform. Identifying valuable development paradigms through evaluating the spatial-temporal environmental efficiency (EE) of the construction sector offers an effective avenue for practice guidance. However, a comprehensive and detailed global analysis of the construction sector's EE remains lacking. This study applies the super-slack-based measure (Super-SBM) model to assess EE of the construction sector across 112 countries from 2006 to 2016. The results reveal relatively low overall EE performance of global construction sector, with notable disparities among countries and improvements were observed in certain years. Singapore, Malta, and Paraguay emerge as top performers, while Moldova, Swaziland, and Iceland rank at the bottom. The findings highlight significantly better EE in European and coastal Asian countries compared to inland Asian and African nations. Using the Tobit model, we identify that industrial structure, trade dependency, international cooperation, energy intensity, and geographic factors significantly influence EE, with varying impacts across countries of different income levels. These findings provide a comprehensive overview of the global construction sector's environmental efficiency, emphasizing the urgent need for increased awareness and the adoption of sustainable practices. The study offers practical policy implications, advocating for targeted strategies to balance economic development with environmental protection.

Analysing the impact of geopolitical risk and economic policy uncertainty on the environmental sustainability: evidence from BRICS countries

This key article seeks to empirically examine the impact of geopolitical risk, economic policy uncertainty (EPU), natural resources, and renewable energy on a country's ecological footprint, a proxy for environmental sustainability on a national scale. We conducted a quantitative study using the cross-sectional autoregressive distributive lag, augmented mean group, and common correlated effect mean group estimation models, as well as a few tests such as the CD test, Westerlund's co-integration, and CIPS and CADF unit root tests, beginning in January 2000 and ending in January 2021, to determine the data's reliability. The findings indicate that while GPR and renewable energy sources lessen the ecological footprint (EF), EPU and the use of non-renewable energy enhance the EF. The study's scope is narrowed to the BRICS nations, but its implications for expanding existing knowledge and shaping policy are enormous. The results can aid decision-makers in preparing for the possibility of unexpected events causing harm to the economy. The reliability of the evidence can be strengthened by employing more stringent research methods. This study's dimensions reflect the current research paradigm. The research has policy implications for achieving sustainable development goals in emerging economies.

Renewable energy electricity, environmental taxes, and sustainable development: empirical evidence from E7 economies

Since globalization has increased both production and population, it has also increased environmental damage. This is why the development of renewable energy sources is crucial to the survival of humanity and the planet itself. Business patterns across the various nations, however, have changed significantly over time. This study examines how environmental taxes and renewable energy electricity affect renewable energy consumption in emerging seven economies by using panel dataset over the period of 1990 to 2020. Control variables include economic growth, carbon emissions, and environmental innovation. The results confirmed the presence of the long-run co-integration association, the existence of slope coefficient heterogeneity, and the dependency of cross sections using several panel data methods. Since the data was not normally distributed, a new technique known as method of moments quantile regression (MMQR) was applied in this study. The projected results contend that the major factors of renewable energy consumption are renewable energy output, environmental taxation, economic growth, and carbon emissions. However, eco-friendly innovations drastically cut back on the need for renewable energy. Bootstrap quantile regression verifies the results' reliability, and the panel Granger causality test corroborates that the listed factors have a bidirectional causal relationship with renewable energy usage. Furthermore, this research recommends boosting spending on renewable electricity, the environmental tax sector, and ecological innovation in order to expand the use of renewable energy.

Assessing and prioritizing biogas barriers to alleviate energy poverty in Pakistan: an integrated AHP and G-TOPSIS model

Biogas is a promising renewable technology to alleviate energy poverty. Pakistan has a capacity of 5 million bio digesters that can be installed in different farming areas. However, this target has never been achieved because many barriers hamper the biogas industry development. In previous studies, some researchers have indicated these barriers in different geographical contexts: however, these barriers are rarely examined in Pakistan. To fulfill the research gap, this study prioritizes potential barriers. Using a literature review and a modified Delphi technique, we identify 25 sub-barriers and catalog them into 5 main categories. The analytical hierarchy process (AHP) prioritizes the main barriers and sub-barriers based on potential. Grey Technique for Order Preference by Similarity to Ideal Solution (G-TOPSIS) ranks the practical alternatives to combat these barriers. The study findings specify that the "financial barrier" is the top-ranked barrier among the main categories, followed by technical, socio-cultural, institutional and administrative, and environmental barriers. The overall ranking shows that the "high starting price tag" is ranked first among all sub-barriers in all categories. It has been proposed that "appropriate financial incentives" and "promotion of customized technology" would be feasible alternative solutions to combat the issues. Based on the research findings, some policy recommendations were suggested for biogas uptake in Pakistan. This study may assist policymakers, stakeholders, and government institutions in accelerating the potential of biogas energy to alleviate energy poverty in rural areas of Pakistan.

The effectiveness of lifestyle interventions on ecological literacy: A contribution to the underlying mechanism in linguistic ecology

In today's society, citizens' ecological literacy (ecoliteracy) is critical for their understanding of sustainable development. This study used a questionnaire designed to quantitatively assess ecoliteracy from a linguistic ecology perspective. First, an underlying mechanism model for ecoliteracy was designed based on the results of previous studies. Then, the ecoliteracy level assessment scores of Guiyang inhabitants were combined with the respondents' corresponding lifestyle characteristics to explore the effectiveness of interventions in affecting the participants' ecoliteracy levels. The results showed that the formation and development of ecoliteracy is a dynamic and circular process that revolves around variables of independent, dependent, mediating, moderating and control. The various factors in the model interact and operate evenly along a particular path. As for the level of lifestyle characteristics, participants' ecoliteracy levels had a statistically significant relationship with their attitudes regarding the importance of nature, participating in outdoor activities, and improving their ecoliteracy levels; as well as the frequencies regarding daily outdoor activity, the main activities in ecological areas, participation in volunteer activities, and use of ecological knowledge. The respondents with the highest levels of ecoliteracy had the most positive attitudes and engaged in ecological actions with the highest frequency. The lifestyle intervention features here are of great significance to the harmonious coexistence between humans and the natural environment and are also helpful for improving human health.

A Novel Prairie Dog-Based Meta-Heuristic Optimization Algorithm for Improved Control, Better Transient Response, and Power Quality Enhancement of Hybrid Microgrids

The growing demand for electricity driven by population growth and industrialization is met by integrating hybrid renewable energy sources (HRESs) into the grid. HRES integration improves reliability, reduces losses, and addresses power quality issues for safe and effective microgrid (MG) operation, requiring efficient controllers. In this regard, this article proposes a prairie dog optimization (PDO) algorithm for the photovoltaic (PV)-, fuel cell (FC)-, and battery-based HRESs designed in MATLAB/Simulink architecture. The proposed PDO method optimally tunes the proportional integral (PI) controller gain parameters to achieve effective compensation of load demand and mitigation of PQ problems. The MG system has been applied to various intentional PQ issues such as swell, unbalanced load, oscillatory transient, and notch conditions to study the response of the proposed PDO controller. For evaluating the efficacy of the proposed PDO algorithm, the simulation results obtained are compared with those of earlier popular methodologies utilized in the current literature such as bee colony optimization (BCO), thermal exchange optimization, and PI techniques. A detailed analysis of the results found emphasizes the efficiency, robustness, and potential of the suggested PDO controller in significantly improving the overall system operation by minimizing the THD, improving the control of active and reactive power, enhancing the power factor, lowering the voltage deviation, and keeping the terminal voltage, DC-link voltage, grid voltage, and grid current almost constant in the event of PQ fault occurrence. As a result, the proposed PDO method paves the way for real-time employment in the MG system.

COP27 perspective of resources management: From conflict to COVID-19 of emerging countries

Resources management in the modern era is a crucial perspective of a sustainable environment linked with sustainable development. Therefore, it is crucial to re-estimate the resources-environment management nexus in a new setting. Concerning environmental management from the COP27 perspective, economies are taking various economic, financial, and environmental steps to reduce hazardous emissions in the region. Recently, BRICS economies have invested in renewables and enhanced capital formation to accelerate environmental recovery. In this respect, this study tends to examine the influence of electricity from renewable resources (ELREC), resources management (resources rents), research and development (RDEV) and gross fixed capital formation (GFCF) on carbon emissions of the BRICS economies throughout 1989-2021. Using various diagnostic tests, this study confirms the long-run equilibrium association between the variables. This study uses non-parametric estimation approaches and concludes that ELREC and RDEV significantly enhance environmental sustainability. Except for forest and oil resources, the rest of the forms of the resources increase emissions. On the other hand, economic growth and GFCF significantly lead to higher emissions, which degrades the environment. Resources rents also contribute to increasing carbon emissions.

How institutional quality and renewable energy interact with ecological footprints: do the human capital and economic complexity matter in the Next Eleven nations?

Changes in the economy and human conduct have contributed to one of today's most urgent challenges: environmental pollution. This study's overarching objective is to evaluate the following Next Eleven nations (N-11) ecological footprints (EF) with their natural resources (NR), economic complexity (EC), renewable energy (RE), and foreign direct investment (FDI). The data from 1995 to 2018 are used with the panel data estimations. The complexity of an economy is found to influence the EF. For this purpose, the cross-sectional autoregressive distributed lag method is appropriate. The analysis shows that a higher degree of economic complexity was associated with a larger ecological impact. Moreover, this correlation was the highest among all the variables considered. However, the consumption of natural resources and the economies' complexity enhance environmental conditions. The key recommendation from the study's conclusions is to improve R&D activities to build environmentally friendly technology and clean energy infrastructures and to change to a clean industry pattern. Meanwhile, strategic initiatives are offered to legislators depending on the stability of institutional quality.

Return connectedness and multiscale spillovers across clean energy indices and grain commodity markets around COVID-19 crisis

The aim of this paper is to examine the return connectedness and multiscale spillovers between the Clean Energy Index and the grain commodity market around COVID-19. Using daily data from January 4, 2017 to July 1, 2022, a time-varying parametric vector autoregressive (TVP-VAR) connectedness approach is first used to reveal connectedness patterns before and during COVID-19. We further used Baruník and Křehlík (2018)'s frequency domain spillover method to assess connectedness in different domain horizons. Our results show spillover effects over time and frequency, with COVID-19 significantly affecting the connectedness of the whole system. Dynamic connectedness peaks significantly after sudden bursts of COVID-19, validating the reported uncertainty. We also documented higher spillover levels in the short term than in the medium and long term. In addition, We find that (i) most clean energy indices are positively affected by the COVID-19 outbreak; (ii) the NASDAQ OMX Bio/Clean Fuels Index and NASDAQ OMX Geothermal Index send spillovers to all grain commodities throughout the sample period, while the WilderHill Clean Energy Index and NASDAQ OMX Wind Energy Index indices are the largest recipients of spillovers from other markets regardless of time horizon; (iii) the OMX Bio/Clean Fuels and OMX Geothermal Energy indices dominate spillover shocks to grain commodity markets. This is the first study to analyse the connectedness and time-frequency dynamics of returns in the green energy index and the grain commodity market. These results provide valuable insights to investors and key policymakers, especially at a time of more significant uncertainty.

Research on design elements of household medical products for rhinitis based on AHP

To improve the scientificity of household medical product design for rhinitis patients, this study used the analytic hierarchy process (AHP) to provide guidance for household medical product design strategy. In the process of design decision-making, the identification of user needs and the evaluation of the scheme depend heavily on the designer's experience and knowledge. The main contribution of this paper is to evaluate the design elements through the AHP method and apply it to the actual design work. This work can greatly reduce the risk in design decisions. First, the AHP model and evaluation matrix of design elements were established and sorted out by semantic analysis of users' research results. Second, an expert group was invited to score using the 1-9 scale method. Then, the geometric mean method was used to calculate the weight shares of different indicators so as to rank them. Finally, the strategy was proposed based on ranking indicator weights, and product design was carried out. The application of AHP can make the product design process more objective and rigorous. The design scheme of this study can provide references and ideas to promote the vigorous development of household medical products for rhinitis patients.

Addressing the effect of meteorological factors and agricultural subsidy on agricultural productivity in India: a roadmap toward environmental sustainability

In the last two decades, the extensive literature that has measured agricultural productivity and growth rate remains controversial and provides few strategies about its main determinants. The present study aims to find out the key determinants of food grain yield (FGY) and examine the role of climate change and agricultural subsidy (SUB) in the context of India using annually data spanning from 1991 to 2018. The current study applied the ARDL modelling to investigate the impacts of climatic factors (average rainfall (RF), mean temperature (AT), and carbon emission (CO₂) and agricultural subsidy (SUB) on food grain yield (FGY) in the short-and long-term in India. The estimated outcomes indicate that climatic factors such as RF have a positive impact while AT and CO₂ have a negative effect on FGY. Similarly, non-climate variables such as gross capital formation (GCF) and fertilizer usage (FERT) positively contributed to FGY, while the area under crop (LUC), SUB, and employment (AL) negatively affected FGY in India. The results from Granger causality divulge that climatic and non-climatic elements are the main determinants of food grain yield, which have been playing play a significant role in enhancing food grain production and ensuring food security in India. Based on empirical outcomes and findings, some key policy implications emerged. Precisely, government and policy developers should focus on technological innovation and precision agriculture to increase agriculture production and productivity. Government should create funds to curb the climate change problem and promote eco-friendly renewable energy.

Assessing the nexus between COVID-19 pandemic-driven economic crisis and economic policy: lesson learned and challenges

This study examines China's budgetary policy during the COVID-19 pandemic as a result of China's insufficient ability to deal with a new crisis when the epidemic struck in March 2020 and as a result of the economic crisis that began in China in March 2020. In order to better comprehend China's economic status during COVID-19, the study relies on secondary data. The fiscal response of emerging market economies like India is less than in advanced economies. However, it is generally considered to be in line with the average for emerging market economies. As a result of the Disaster Management authority imposing a rigorous lockdown, unemployment rose, the trade cycle was interrupted, and manufacturing and service activities were affected. According to the study's findings, China's economic policies, namely its fiscal policy, responded in the years leading up to 2019 by increasing health expenditure, income transfer, welfare payments, subsidies, and reducing short-term unemployment. As a result of the COVID-19 pandemic, China's government has adopted a number of measures to minimize the damage to the economy. This article also focuses on China's numerous budgetary actions with COVID-19.

Research on a Coordination Evaluation and Prediction Model of Water Use and Industrial Ecosystem Development

Coordinating the relationship between water use and industrial ecosystem development is the key to ensuring high-quality and sustainable development of the industrial economy. In this paper, a model was proposed for evaluating and predicting the coordination between water use and industrial ecosystem development. First, aiming at the coordination of water use and industrial ecosystem development, this paper determined 15 indicators from the aspects of water demand and supply, water conservation and environmental protection, industrial sustainable development, input and output, and industrial development status. The combination weighting method based on game theory was used to determine the weight of the evaluation index. Then, the coordination evaluation model called the back propagation neural network (BP)-coupling coordination degree model (CCDM) and the coordination prediction model called gray models (GM)-BP-CCDM were established. Finally, the model was applied to the coordination evaluation and prediction of water use and industrial ecosystem development in the Hebei Province, China. The results show that the coordination degree of cities in the Hebei Province is moderate. Therefore, based on the research results, some scientific and reasonable suggestions for water resources utilization and industrial ecosystem development were put forward.

Study on Water Resource Carrying Capacity of Zhengzhou City Based on DPSIR Model

Based on the driving force-pressure-state-impact-response (DPSIR) model, a comprehensive evaluation index system is constructed. The index weight is determined by the combination weighting method in combination with the data of 2010-2019. The TOPSIS model is used to comprehensively analyze the water resource carrying capacity of Zhengzhou as the central city in China with a developed economy and relatively short water resources. The study results are as follows. (1) During the sample period, the comprehensive evaluation value of water resources carrying capacity of Zhengzhou increases from 0.4183 in 2010 to 0.5560 in 2019, with an overall fluctuating rise. Simultaneously, the water resource carrying capacity grade improves from Grade III (normal carrying capacity) to Grade II (good carrying capacity). (2) The contribution of each subsystem to the comprehensive evaluation value increases year by year. Among them, S subsystem and I subsystem make the largest contribution to the comprehensive carrying capacity. R subsystem makes a relatively stable contribution to the overall carrying capacity. Affected by GDP growth rate and uneven temporal-spatial distribution of water resources in Zhengzhou, the D subsystem and P subsystem of water resource carrying capacities show the fluctuating change. Finally, based on the above conclusions, this paper puts forward the countermeasures and suggestions to improve the level of water resource carrying capacity of Zhengzhou.

Unleashing the mechanism between small and medium enterprises, and green financing in China: a pathway toward environmental sustainability and green economic recovery

In this research, we analyzed green finance, small and medium-sized businesses, and financial literacy in China to boost the green economy. Green finance and financial literacy were examined holistically using a rigorous empirical approach and data envelopment analysis to provide the way to advance green economic recovery in this research. According to empirical evidence, green financing impacts SMEs at 0.31, 0.41, and 2.02 on green economic recovery. China's green finance and small businesses contribute significantly to the country's overall green economic revival. A more accurate forecast of green economic recovery was made possible by including other variables such as population expansion, development, and small business development. The analysis used the data envelopment analysis, and the results were solid. Additional hypothetical time-dependent instances demonstrated China's predicted green financing and small business's nexus for 2000 to 2020. The proportion of SMEs is decreasing, and as a result, green financing and financial literacy have increased by an average of 12.5% during this time. China's green financing would fall dramatically if the country's industrial structure is reduced. According to our findings, financial literacy is positively correlated with green economic recovery, while illiteracy is negatively correlated with growth. Finally, the report provides some ideas for China's future green economic recovery.

The impact of COVID-19 on small- and medium-sized enterprises (SMEs): empirical evidence for green economic implications

Small- and medium-sized enterprises (SMEs) in China have been hit hard by the coronavirus (COVID-19) outbreak, which has jeopardized their going out of business altogether. As a result, this research will shed light on the long-term impacts of COVID-19 lockdown on small businesses worldwide. The information was gathered through a survey questionnaire that 313 people completed. Analyzing the model was accomplished through the use of SEM in this investigation. Management and staff at SMEs worldwide provided the study's data sources. Research shows that COVID-19 has a significantly bad influence on profitability, operational, economic, and access to finance. In the study's findings, outside funding aids have played an important role in SMEs' skill to persist and succeed through technological novelty than in their real output. SME businesses, administrations, and policymakers need to understand the implications of this study's results.

Unbundling the dynamic impact of renewable energy and financial development on real per capita growth in African countries

Industrialization is considered imperative for growth but energy transitions are paramount for inclusive and green growth especially for a region with low financial sector development to spur investment in renewable energy. This study thus unbundles the interrelation among renewable energy production, financial development, and real per capita growth in 32 selected African countries from the period of 1996 to 2018. These countries are categorized on the basis of oil-rich and non-oil-rich as well as income levels. The study employs Pooled Mean Group, Augmented Mean Group, and Dynamic OLS, and key findings are established. The findings reveal a significantly positive renewable energy-economic growth relationship in all the different groups. Financial development is also found to improve economic performance in all categories except in non-oil-rich African countries. These findings empirically support the need for cleaner energy in the production process to spur inclusive and green growth amidst current global concern for climate change and global warning. This study thus recommends the restructuring of the energy pricing system, provision of long-term finance, adoption of risk mitigation instruments, and improved institutional framework for private participation in renewable energy infrastructural development for growth sustainability in Africa.

Sustainable impact of COVID-19 on education projects: aspects of naturalism

History records show that pandemics and threats have always given new directions to the thinking, working, and learning styles. This article attempts to thoroughly document the positive core of coronavirus 2019 (COVID-19) and its impact on global social psychology, ecological stability, and development. Structural equation modeling (SEM) is used to test the hypotheses and comprehend the objectives of the study. The findings of the study reveals that the path coefficients for the variables health consciousness, naturalism, financial impact and self-development, sustainability, compassion, gregariousness, sympathy, and cooperation demonstrate that the factors have a positive and significant effect on COVID-19 prevention. Moreover, the content analysis was conducted on recently published reports, blog content, newspapers, and social media. The pieces of evidence from history have been cited to justify the perspective. Furthermore, to appraise the opinions of professionals of different walks of life, an online survey was conducted, and results were discussed with expert medical professionals. Outcomes establish that the pandemics give birth to creativity, instigate innovations, prompt inventions, establish human ties, and foster altruistic elements of compassion and emotionalism.

Exploring renewable energy, financial development, environmental quality, and economic growth nexus: new evidence from composite indices for environmental quality and financial development

The association between trade, financial development, consumption of renewable energy, environmental quality, foreign direct investment, and economic growth is important for sustainable growth and environmental strategies. Hence, this research unveils this association in selected low- and high-income economies from 1996 to 2020. Unlike most of the previous literature, this study uses a composite environmental quality index, a composite financial development index, and a composite trade share measure to better represent environmental quality, financial development, and trade openness, respectively. The Continuously Updated Fully Modified and Continuously Updated Bias Corrected estimators along with the Dumitrescu Hurlin causality method are utilized to scrutinize the nature of the linkage between the modeled variables. The long-run estimation provided that consumption of renewable energy and environmental quality augment economic growth in high-income nations, while both these variables do not contribute to the economic growth in low-income countries. Financial development upsurges economic growth in high- as well as low-income nations. Interestingly, trade openness boosts economic growth in high-income countries, while in low-income countries, it obstructs economic growth. In causal linkage, the conservation hypothesis for low-income countries and the feedback hypothesis for high-income countries are confirmed in the context of consumption of renewable energy and economic growth association. The supply-leading hypothesis for low-income countries and the feedback hypothesis for high-income countries are supported regarding the financial development-economic growth nexus. Moreover, one-way causality from growth to environmental quality and bidirectional causality between environmental quality and economic growth for low- and high-income countries are established, respectively. Lastly, exhaustive environmental and economic policies are directed.

Measuring energy efficiency financing: a way forward for reducing energy poverty through financial inclusion in OECD

This paper seeks to examine the effect of financial inclusion on energy efficiency financing to limit energy poverty in OECD. The study uses 1998-2018 for the OECD economy to connect the nexus between financial inclusion, energy efficiency and poverty indices, country-wise GDP, and financial inclusion index. The findings show that a financial inclusion 1% increase improves 14% energy efficiency, and this energy efficiency lowers energy poverty by 28%. These results are deduced via the entropy technique and compatible with prior research on energy efficiency and poverty. This study illustrates the different policy changes that may be implemented based on the resultant deductions. The energy efficiency indices are affected by FI substantially, albeit in various ways. Unsustainable financial inclusion increases energy costs, but not to the level of energy use and environmental severe pollution. The increasing concern about environmental contamination should show in the energy industry of OECD.

Multicriteria decision making and goal programming for determination of electric automobile aimed at sustainable green environment: a case study

In this paper, we consider the problem of automobile selection for transportation in inner city using a hybrid multicriteria decision making approach. The electric automobiles that are a relatively new concept in the world of the automotive industry, are widely viewed as attractive among its alternatives day by day. Fuel-vehicles produce a lot of carbon emissions that are ejected into our natural atmosphere, leaving us vulnerable to things like pollution and greenhouse gases. So, electric vehicle and automobiles have emerged as a more efficient alternative and these vehicles have been a great step forward to help positively the environment with zero emissions and total energy consumption in their lifecycle. Many companies focus on electric vehicle production with the development of electric vehicle technology. Therefore, the selection process emerges among the various electric automobile technologies for the users. The selection process includes several conflicting factors which are such as economic, technical and technological factors. In the present study, we propose a hybrid approach for electric automobile selection that combines analytic hierarchy process (AHP), technique for order of preference by similarity to ideal solution (TOPSIS) and goal programming (GP) is used to determine the weights to assign to the factors that go into these selection decisions and TOPSIS method is used for preference ranking. These weights founded by AHP are inputted into a GP model to determine the best alternative among the electric automobiles. Finally, the study used three methods TOPSIS, AHP- TOPSIS and AHP-GP for better comparison and evaluation. The most suitable electric automobile is selected among their alternatives by using analytic methods and goal programming.

Assessing the nexus between fiscal policy, COVID-19, and economic growth

The COVID-19 issue deteriorated South Africa's already dire economic situation, exacerbated by years of considerable debt increase. The COVID-19 pandemic has disrupted trade to such an extent that some enterprises are barely working at a quarter of their potential. Furthermore, economic agents delay economic decisions while waiting to see how the crisis develops. According to some economists, increased government expenditure will raise GDP enough to keep the country's debt-to-GDP ratio steady and restore fiscal sustainability. We use a panel data model to estimate a fiscal reaction function, which we then apply to historical data to assess the government's prior efforts to maintain or restore budgetary sustainability. We calculate the impact fiscal balance, government expenditure, interest rate, and revenue changes that the government will have to make to restore the country's fiscal stability due to the financial impact of the COVID-19 issue.The findings show that fiscal balance and tax revinue have a significant impact on the economics growth, while government expenditure and corruption reduce the growth of the country.

Do technological innovations and trade openness reduce CO2 emissions? Evidence from selected middle-income countries

This paper examines the role of trade openness and innovation in reducing CO₂ emissions in middle-income countries with the goal of improving environmental quality. The generalised method of moments (GMM) method is used to estimate the long-run association between variables and Dumitrescu-Hurlin causality test is used to examine causality for a panel of 23 middle-income countries from 1994 to 2018. The findings refute the existence of an inverted u-shape relationship between innovation and CO₂ emissions. On the trade front, environmental deterioration is found to be relatively more severe in low middle-income countries than upper middle-income countries. Contrarily, the existence of the environment Kuznets curve (EKC) hypothesis for both country groups is also supported by the data; however, the fall in the EKC curve is insignificant for low middle-income countries. Implying that the quest to control carbon emissions has just begun in low middle-income countries and they must target a higher level of green innovation to reduce the ever-rising CO₂ emissions. It is also suggested to promote economic growth through knowledge spillovers and to establish a pollution level standard for trading and manufacturing sectors which generate the most contaminated waste.

Macroeconomic lockdown effects of COVID-19 on small business in China: empirical insights from SEM technique

The coronavirus (COVID-19) outbreak in the China has exposed small- and medium-sized enterprises (SMEs) to a variety of challenges, some of which are potentially life-threatening to their sustainability. Therefore, this study aims to investigate the macroeconomic lockdown effects of COVID-19 on small business in China. A survey questionnaire with 313 participants was used to collect the data. In this study, the SEM technique was used to analyse model. The data have been gathered for the study from the managers and employees of Chinese SMEs. The findings of the study show that COVID-19 has a significant negative impact on financial performance, operational performance, profitability, access to finance, and customer satisfaction. According to the study's findings, external support aids have a greater impact on SMEs' ability to survive and thrive through innovation than on their actual performance. The findings of this study have a number of important practical consequences for small- and medium-sized business owners, governments, and policymakers.

The Spatial Spillover Effects of Environmental Regulation and Regional Energy Efficiency and Their Interactions under Local Government Competition in China

Under the pressure of serious environmental pollution and energy shortage, China needs to improve its energy efficiency to alleviate these problems. Environmental regulation is an important constraint on economic development, which has an impact on energy efficiency. Meanwhile, energy efficiency is a reference factor for adjusting environmental policies, which has an impact on environmental regulation. Therefore, the relationship between environmental regulation and energy efficiency needs to be further studied under a unified framework. Based on Chinese provincial panel data, we first use a stochastic frontier model to estimate the energy efficiency of China’s 30 provinces from 2004 to 2019, and then employ a spatial simultaneous equation model to study the spatial spillover effects of environmental regulation and energy efficiency and their interactions. The results show that: (1) Both energy efficiency and environmental regulation have significantly positive spatial spillover effects. Specifically, an overall increase of 1% in energy efficiency in the surrounding areas can promote an improvement in the local energy efficiency by about 1.0404%, and an overall increase of 1% in environmental regulation in the surrounding areas can lead to an increase of about 0.6075% in the local environmental regulation. (2) The impact of environmental regulation on energy efficiency is significantly positive; i.e., under the current situation in China, an increase of 1% in environmental regulation can promote local energy efficiency by about 0.2777%. (3) The impact of energy efficiency on environmental regulation is significantly positive; i.e., a 1% increase in energy efficiency may stimulate local governments to strengthen their environmental regulation by 1.5981%. Accordingly, some targeted policy suggestions are given.

Solar energy technology adoption and diffusion by micro, small, and medium enterprises: sustainable energy for climate change mitigation

This research intends to identify influential factors in adopting and diffusing solar energy technology (SET) by micro-, small-, and medium-sized enterprises (MSMEs) in two tehsils of Multan district in Pakistan's Punjab province. To this end, the influential factors are identified through studying literature surveys and conducting questionnaires. Following that, partial least squares-based path modeling is employed. The results showed that (1) enterprises' size, perceived SET's ease of use, and perceived SET's reliability are the top three driving factors. (2) The perceived SET's price, perceived level of competition's pressure, and MSME's energy cost intensity are the barriers to the adoption and diffusion of SET, while the lack of technical knowledge about SET is a neutral factor. (3) Perceived SET's price, MSMEs' energy cost intensity, and enterprises' size are among the most important factors based on the effect size and path coefficients, while the lack of technical knowledge about SET, preferences of MSMEs' customers, and eco-labels and green stickers have lower importance. Since the adoption of SET is a rational decision that is concretely dependent on economic incentives, it is recommended to lower the price of SET to scale up the adoption and diffusion of SET by Pakistani MSMEs.

Relating Sustainable Business Development Practices and Information Management in Promoting Digital Green Innovation: Evidence From China

Digital green innovations are being implemented in manufacturing to help organizations achieve sustainability by adopting sustainable development practices (SDPC). However, little is known about the impact of the information management process (IMP) on organizations' digital green innovation. To address this gap, we devised a multidimensional framework based on the resource-based view (RBV) theory that serves as a basis for sculpting how the IMP captured and sustained organizational digital green innovation via SDPCs. 533 respondents from big and medium-sized manufacturing businesses in China were surveyed, and data were analyzed using the structural equation modeling (SEM) approach. The study makes numerous significant findings. Firstly, the SDPC's dimensions (environment, economic, and social) are considerably improved by the IMP' dimensions (acquisition, dissemination, and application). Secondly, SDPC's dimensions are critical for attaining organizations' digital green innovation. Thirdly, SDPCs' implementation mediates the linkage between the IMP and organizations' digital green innovation. Our findings suggest that investing in and implementing cutting-edge technology and sustainable practices are critical for long-term success. Still, soft issues, such as organizational information management, are equally critical in today's information-based economy. Finally, in light of the study findings, we present theoretical and managerial implications.

Modeling COVID-19 Impact on Consumption and Mobility in Europe: A Legacy Toward Sustainable Business Performance

This article has explored the impact of coronavirus disease 2019 (COVID-19)-induced decline in consumer durables and mobility on nitrogen dioxide (NO2) emission in Europe by providing empirical and graphical justifications based on consumer price index (CPI) and gross domestic product (GDP) deflator indexes. The empirical estimations show that carbon dioxide (CO2) and NOx emission along with other greenhouse gases drastically decreased in the wake of COVID-19-induced lockdowns and decrease in the demand of consumer goods in Europe. This means that COVID-19 improved environment in the European region. However, high cost (e.g., unemployment, loss of life, and social segregation) makes COVID-19 an unstable solution to environmental woes where positive impact of COVID-19 on environment achieved in short run cannot be guaranteed in the long run. Besides environment, COVID-19 drastically curtailed economic activities and exposed them to the risk of economic crisis particularly in case of Europe.

How Do Green Finance and Energy Efficiency Mitigate Carbon Emissions Without Reducing Economic Growth in G7 Countries?

Climate change is one of the most serious threats facing the world today. Environmental pollution and depletion of natural resources have been highlighted by the United Nations Sustainable Development Goals (SDGs), paving the way for modern concepts such as sustainable growth to be introduced. Therefore, this research explores the relationship between green finance, energy efficiency, and CO2 emissions in the G7 countries. The study uses panel data model technique to examine the dependence structure of green finance, energy efficiency, and CO2 emissions. Moreover, we use DEA to construct an energy efficiency index of G7 countries. A specific interval exists between the values of the energy efficiency indexes. Japan, the United Kingdom, and the United States were named the most energy-efficient countries in the world, based on results obtained for five consecutive years in this category. However, according to the comparative rankings, France and Italy are the most successful of all the G7 members, followed by the United Kingdom and Germany. Our overall findings of the econometric model confirm the negative impact of green finance and energy efficiency on CO2 emissions; however, this relationship varies across the different quantiles of the two variables. The findings in the study confirm that green finance is the best financial strategy for reducing CO2 emissions.

Ecosystem Stability Assessment of Yancheng Coastal Wetlands, a World Natural Heritage Site

By evaluating the stability of coastal wetland ecosystems, health conditions of regional ecosystems can be revealed and the sustainable development of coastal wetlands can be promoted. Coastal wetlands have been scarcely involved in present ecosystem stability evaluation studies, these being performed with relatively simple evaluation data sources. Therefore, in this research, a comprehensive and representative ecosystem stability evaluation index system was constructed by using the pressure-state-response model and multi-source datasets from perspectives of internal and external environmental changes of the Yancheng coastal wetlands, Jiangsu, China. The analysis results indicated that: (1) The ecosystem stability of the Yancheng coastal wetlands was at an early warning stage, and all segments except the Binhai segment (relatively stable) were in an early warning state. (2) In the criterion layer, the Dafeng District and the whole Yancheng District were faced with the highest pressure, followed by the Dongtai, Xiangshui and Binhai segments, successively. The Sheyang segment reached the highest state level, followed by the Binhai, Xiangshui and Dafeng segments in succession. (3) In the factor layer, the whole Yancheng District was faced with high resource and socioeconomic double pressures, with a poor water quality state and relatively low environmental pressure; favorable soil, biological and landscape states; and positive response to wetland protection. Various factors varied from county to county. (4) In the index layer, the ecosystem stability of the Yancheng coastal wetlands was significantly influenced by the invasion of alien species, change rate of natural wetland area (D32), change rate of artificial wetland area, increment of aquafarm area, intensity of fertilizer application and coverage of dominant vegetations. The novel significance of this research lies in enriching global coastal wetlands ecosystem stability evaluation investigations by providing a typical case study.