The present article provides a thorough examination of innovationology, a groundbreaking transdisciplinary field of study that is revolutionizing the concepts and methods associated with innovation, economic growth, and worldwide sustainable transformation. This work provides unparalleled insights into the transformative potential of innovationology, drawing on a comprehensive review of literature across diverse fields such as development economics, sustainability science, social entrepreneurship, transition studies, complexity theory, decolonial thought, and design thinking. In presenting innovationology as a force for systemic, multidimensional economic change, the paper explores the strong theoretical underpinnings, creative approaches, and elite case studies that highlight the groundbreaking science's extraordinary influence. Through a rigorous, evidence-based examination, the author provides policymakers, researchers, and practitioners with a comprehensive understanding of innovationology's capacity to redefine the principles and practices of wealth creation, inclusive growth, sustainable finance, and community-centric entrepreneurship. Anchored in real-world case studies from the Global North and South, the article demonstrates innovationology's potential to drive progress towards a more equitable, resilient, and prosperous global economy. By challenging dominant neoclassical paradigms and offering a decolonial, transdisciplinary framework for economic transformation, this work presents a groundbreaking pathway to a just, sustainable, and inclusive economic future.

One of the factors leading to the slow decline in poverty in Indonesia is the lack of government at-tention to reduce income inequality. Fiscal policy and economic growth can effectively reduce poverty after lowering income inequality, so the inequality channel must be considered. Socioec-onomic and infrastructure differences between provinces can influence the effectiveness of eco-nomic growth and fiscal policy in reducing poverty. This study aims to assess the effects of eco-nomic growth and fiscal policy on spending and taxes on direct and indirect poverty reduction through lowering income inequality and how these variables influence poverty by province. This study employed secondary data, including panel data for 2010-2023 from 34 provinces in Indo-nesia, which were analyzed using an autoregressive cross-lagged SEM model. The study finds that economic growth and fiscal policy on spending on education and health are statistically sig-nificant in reducing poverty directly in non-Java but do not affect it through income inequality. Taxes increase income inequality, and the social safety net does not reduce poverty outside Java. Increased spending on education and health should continue, with improvements in targeting so-cial safety nets and tax reforms needed to make the system more progressive and reduce inequality

As a branch of regional innovation theories, social filter theory fundamentally reveals the reasons for the geography of innovation in different countries and regions. However, compared with some other regional innovation theories, social filter theory has been as silent as a sleeping beauty and hasn’t been fully developed. For enriching and developing social filter theory, this article systematically traces the source and comments on four aspects: the concept of social filter, the construction and measurement of indicators of social filter, the mechanism and empirical re-search of social filter affecting regional innovation and innovation transformation. Until recently regional innovation theories primarily focused on the superficial description of the phenomenon of innovation, but lack of attention to the local social filter condition of innovation generation and innovation transformation, which are the pre-condition of constructing mature innovation system. Therefore, additional efforts are still required to fill the current knowledge gap from the recom-mended directions in the article.

Economic interests, penchant, and goals or pursuits drive and stir the motivation and impetus or motives for and the reason behind most business activities and ventures, which is in line with classical economic theory and capitalism; however, this revolves around one of the 3-4 pillars outlined and identified as “economic, legal, ethical, and discretionary or philanthropic” by ‘Carroll in this article and from previous works or articles. It is essential and crucial to note the line and clear distinction or border drawn between competing and complementary frameworks as exemplified in the present article by Carroll and different motives for different organizations in pursuing ‘CSR. The central objective of this presentation and research activity is to examine the decision-making and choice architecture from the influences of nudge on the economic decisions and aspects of ‘CSR pursued by managers stressing on the ‘RBV: resource-based view and point to the potentials and use of ‘CSR as a strategic tool by corporations from a stakeholder’s perspective, paying attention to crucial decision-makings and the need for striking a balance from the competing interests perspective, even though an economic aspect of ‘CSR is pursued and prioritized while gaining a competitive advantage or leveraging from the ‘RBV point of view.

This study investigates the relationship between economic growth and energy con-sumption—both renewable and non-renewable—in European Union countries during the green transition. Using a panel dataset of 28 EU countries from 1995 to 2021, we employ econometric techniques, including the Westerlund cointegration test, to assess long-term equilibrium relation-ships, accounting for cross-sectional dependence and slope heterogeneity. The results indicate that, while both renewable and non-renewable energy consumption are associated with economic growth, their roles differ. Renewable energy consumption shows a positive but less robust rela-tionship with GDP, with limited evidence of a predictive impact on economic growth. In contrast, non-renewable energy consumption demonstrates a more robust bidirectional causality with GDP, indicating a more intertwined relationship with economic growth during the study period. Our results have significant policy recommendations, indicating that promoting renewable ener-gy sources does not hinder economic growth. Moreover, such promotion has the potential to con-tribute substantially to economic growth in the future. Therefore, in addition to other crucial ben-efits, such as increased energy security, the development of renewable energy sources does not pose a threat to the economy. This is particularly relevant as many EU countries, including Po-land, Romania, Hungary, Bulgaria, Slovakia, and Lithuania, still have underdeveloped renewa-ble energy sectors.

In this study, the asymmetric effect of oil and natural gas price shocks on the trade balance of 11 CESEE countries was estimated. These countries are net importers of oil and natural gas, and price shocks are often the cause of imbalances in trade. Quarterly data for the period 1994Q1 to 2023Q4 and nonlinear ARDL model were used. In the long run, a significant asymmetric effect due to the oil price shock on the trade balance of Bulgaria, Czechia, Latvia and Slovenia was found, as well as a significant asymmetric effect due to the natural gas price shock on the trade balance of Croatia. Also in the long run, a significant asymmetric effect due to wholesale prices on the trade balance of Romania, Bulgaria and Croatia was found as well as a significant asymmetric effect due to industrial production on the trade balance of Croatia, Czechia and Latvia was found, in addition to a significant asymmetric effect due to the exchange rate on the trade balance of Czechia, Poland and Romania.

This study investigates the rapid growth of the e-commerce industry in Nepal while examining the associated security challenges. By analyzing factors driving e-commerce development, identifying prevalent threats, and evaluating existing security measures, this research aims to provide a comprehensive understanding of Nepal's e-commerce landscape. This research uses a combination of quantitative and qualitative data to better understand the complex relationship between e-commerce and security threats.E-commerce security is paramount for protecting online transactions. It ensures data integrity, prevents unauthorized access, and maintains confidentiality. While e-commerce offers opportunities for the banking industry, it also introduces security risks like hacking. Effective e-commerce security requires a coordinated approach, combining technical solutions with robust management practices. Key findings from this research are expected to inform the development of robust strategies to mitigate security threats and cultivate a secure e-commerce ecosystem in Nepal. By addressing the challenges and opportunities presented by e-commerce, Nepal can harness its potential for economic growth and development while ensuring a safe and secure online environment for consumers and businesses.

This article affords the question of methane emissions in the context of the ESG framework at the global level. The World Bank ESG-Environmental, Social, and Governance database was used. The data refers to 193 countries for a period between 2011 and 2020. The econometric models used are Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, and Weighted Least Squares-WLS. The impact of methane on the ESG model was calculated through three equations capable of analyzing the impact of methane emissions, respectively, con-cerning the E-Environmental, S-Social, and G-Governance components of the ESG model. The re-sults show that methane emissions tend to increase even in the improvement of ESG conditions at world level.

We present a simple proof of the well-known axiomatic characterization of state-salient decision rules on the domain of all strict preference profiles, using Pareto property and Global Independence of Irrelevant Alternatives. Our proof appeals to Sen’s Impossibility Theorem and an extract from a proof of the same theorem, that is available in an earlier paper of this author.

The war in Ukraine and the related disruptions in supply chains shook global markets for agricultural and energy commodities, causing their prices to increase to unprecedented levels. At the same time, this situation highlighted the fact that Ukraine is an important global producer and exporter of certain agricultural products. The complete opening of the EU market to duty-free imports from Ukraine showed that Ukrainian products constitute competition for both EU and Polish food producers. This, in turn, caused further disruptions in food supply chains within the EU. The aim of the article is to assess the competitive position of Polish and Ukrainian food producers in the EU market and the prospects for the evolution of their competitive advantages. The analysis was carried out using selected quantitative indicators of competitive position, namely Balassa's Revealed Comparative Advantage Index (RCA) and the Trade Coverage Index (TC). The calculations were made using statistical data from the World Bank WITS-Comtrade database. The research covered the period from 2018 to 2023 inclusive. The research shows that between 2018 and 2023, the share of products in Polish exports to the EU, in which both countries compete, increased to 37.5%; that is, both countries had comparative advantages in these products on this market. The current competition includes, among others, poultry meat, bakery products, wafers and cookies, chocolate, corn, fruit juices, frozen fruit, water and other non-alcoholic drinks, and wheat. At the same time, more than half of Polish exports consisted of products that may become the subject of such competition in the future (currently, only Poland has comparative advantages in the export of these products). These may include, among others, cigarettes, animal feed, fresh or chilled beef, other food products, smoked fish, canned meat, fish fillets, pork, canned fish, and liquid milk and cream. Therefore, Polish food producers face big challenges; the process of post-war reconstruction of Ukraine and its potential integration with the single European market will strengthen the competitive position of Ukrainian food producers in the EU market. The current competitive strategy of Polish producers, based on cost and price advantages, may turn out to be ineffective under these conditions. Therefore, they must look for new sources of competitive advantage that will distinguish Polish products from cheaper Ukrainian ones. Therefore, a strategy of competing on quality may prove effective.

Material Flow Analysis (MFA) is a key tool in the circular bioeconomy, providing insight into the flow of materials within a system. Its use in the wood-based value chain is increasingly recognized and provides valuable information for policy making. Based on a comprehensive literature review, this article presents recent applications, challenges and research gaps related to MFA methodologies that are crucial for describing the expanding circular wood-based bioeconomy. Different MFA models and their methodologies are described and classified according to their scale and scope. The discourse on future research directions highlights the need to critically examine new material flows associated with bioeconomy development, including hidden by-product streams and end-use wood product recycling, as well as the role of regulators. The results of this study provide advice on data collection methods and the implementation of MFA models, offering valuable information for future research in the sector.

The increasing energy consumption and industrial activities that release carbon dioxide (CO2) emissions into the atmosphere have become one of the most serious environmental issues of today. This article discusses the current status in Azerbaijan regarding the development of effective approaches to reduce carbon emissions and ensure sustainable development, and it proposes relevant strategies for managing the carbon footprint. By exploring the interrelationship between the economy and the environment, it aims to contribute to the formation of more effective policies for managing CO2 emissions in Azerbaijan. According to the results of the econometric model established within the research for the period of 1990-2023, as the Azerbaijan economy grows, per capita CO2 emissions tend to increase, which can be linked to rising industrial activity, energy consumption, and other factors driving economic growth. The presence of a positive long-term relationship between population growth and per capita CO2 emissions can be attributed to higher overall energy consumption, increased demand for goods and services, and rising transportation needs. The strong correlation between economic growth and CO2 emissions suggests that it may be too early to assert the validity of the Kuznets curve for Azerbaijan economy as a developing country.

This study addresses the challenge of evaluating circularity within the procurement-to-waste sys-tem boundaries, exemplified by single-use in-flight drinking cups provided on SWISS International Air Lines Ltd. flights. A comprehensive review of academic literature, market-based tools, and po-litical regulations highlights the absence of adequate methodologies for assessing circularity within these specific system boundaries. Existing approaches, primarily designed at the product level, are often either excessively complex or focused solely on waste management. To address this gap, the research proposes an extension to the Circularity Mass Utilisation Index (CMU), currently imple-mented at the European Union level. The traditional CMU does not account for circular inflow, thereby neglecting procurement decisions. In response, this study introduces an extended version of the CMU, expressed as: CMU Extended = (Circular Inflow + Circular Outflow) / (2 * Total Material Use). This modification enables a more holistic evaluation of circularity by incorporating both in-flows and outflows of materials in relation to total material use. Empirical testing demonstrated the applicability of this extended CMU in the context of SWISS, allowing for an efficient assessment of circularity for single-use in-flight drinking cups. From these initial results, we hypothesize that this ratio is expected to be broadly applicable beyond the airline industry, providing a valuable tool for businesses seeking to measure circularity within similar system boundaries.

This study aims to investigate the dynamic impact of socio-economic issues such as youth unemployment and income inequality on crime by comparing the findings from newly democratized African countries (South Africa and Namibia) to those of recently democratized European countries (Lithuania and the Ukraine) and newly democratized Asian countries (Kyrgyzstan) from 1994 to 2019. The study used the Bayesian vector autoregression approach with hierarchical priors. This model was chosen due to its ability to address the dynamics of several entities, such as the measurable defects where data quality is uncertain, or perhaps lacking as frequently happens. Prior selection in a Bayesian vector autoregression approach can help adjust for these flaws. According to the study's findings, an unexpected shock in unemployment and income inequality has a significant positive impact on crime; however, an unanticipated shock in government expenditure has a significant negative impact. The results are interesting, as we found that the impact of these socio-economic issues does not necessarily depend on the geographical area, as the results are similar for income inequality in both regions. This study serves as a wake-up call to the government that some policies (fiscal policy or income policy) are more appropriate for resolving concerns about inequality and unemployment than others. As a result, addressing these issues through policies that promote greater economic equality and ensure everyone has access to basic education, healthcare, and job training, could assist in reducing crime while promoting a more equal society.

This paper uses a Vector Autoregression (VAR) model and linear regression to analyze the effects of aggressive monetary policies (such as RRR cuts and interest rate reductions) and fiscal measures (like government bond issuance) on household wealth in China, with a focus on housing assets. A comparative analysis with Japan is conducted to explore the transmission mechanisms and the policies’ impacts on housing prices, wealth distribution, and economic growth. The findings highlight the significant role of monetary and fiscal interventions in shaping the housing market dynamics across different economic contexts.

Thanks to the Chinese government's strong monetary stimulus initiative, the Chinese stock market has seen a recent surge. A similar scenario in history reminds us that such a surge carries significant potential risks and undermines economic sustainability. This study examines the economic stimulus by the Chinese government during 2008 and 2015 utilizing monetary and real estate policy to stimulate stock market expansion, and identifies a pattern of path dependency in the government's approach to economic challenges. In the context of the fiscal pressures of 2024, the government has again employed an extraordinary level of intervention to catalyze a significant uptick in the stock market. While this has led to a temporary increase in stock market indices, it poses substantial risks. The potential for a stock market bubble, detached from fundamental values, could precipitate a subsequent market collapse. Additionally, the government's market stimulus may be aimed at providing financial support to underperforming state-owned enterprises, which in the long-run will damage China's economic sustainability. There is also a concern that the measures to stimulate the stock market could interlink the bond market and banking sector with the equity, potentially inciting broader systemic risks. Furthermore, the housing market crisis and investors' skepticism towards the extent of China's marketization reforms will also intensify. Overall, we believe that the current round of stock market stimulus is not sustainable and leaves the door open for future risks.

This paper analyses the evolution of the prices of intercity high-speed rail (HSR) services operated by the Spanish public company Renfe on the Madrid-Barcelona route between April 2019 and June 2022. This period marks one of the most important events in the recent history of railways in Spain: the end of Renfe's monopoly and the opening of this and other corridors to private competitors. Our main objective is to study the impact of the entry of the first competitor, Ouigo, on the incumbent's pricing strategy. Our analysis confirms that Renfe perfectly anticipated Ouigo's entry and adjusted its prices about four months before the market opened. Interestingly, the incumbent also modified its tariff structure in advance according to the willingness to pay of the target customer. These results may be of interest for the forthcoming liberalization of other inter-city corridors.

The analysis focuses on the intensity of energy consumption in the transportation sector, of the oil-rich country, Iran. The study emphasizes the importance of reducing energy consumption in transportation and identifies factors that affect energy efficiency. The research explores the impact of population growth, clean fuels, energy prices, and investment in energy efficiency in the transport sector. Using data from 1979 to 2011, the study estimates a model with the Autoregressive Distributed Lag model and emphasizes the significance of clean and renewable energies in reducing energy intensity. It also discusses the theoretical background, energy intensity factors, production technology, and the role of clean energy sources. The model framework includes variables like energy intensity index, relative energy price, number of cars, investment ratio, and clean energy production. The findings suggest an increasing trend in energy consumption in the transportation sector, highlighting the importance of identifying drivers that affect energy consumption in the sector.

The study focuses of analysis the impact of corporate social responsibility (CSR) on economic growth and reducing inequality, highlighting the importance of CSR in achieving sustainable development and social justice. The main aim is to analyze how different CSR initiatives contribute to economic development, social prosperity and the reduction of inequality, reviewing the methods used to assess their impact. The research methodology includes a detailed literature review, bibliometric analysis and scientific mapping, surveys of various business organizations and a Gap Analysis regarding the identification of gaps between the current state of CSR activities and the expected outcomes. The research shows that companies perceive CSR as a key tool for improving corporate image, responding to stakeholder expectations and investing in social justice. Despite positive intentions, challenges include the lack of clearly defined methodologies for measuring impact on economic inequality, as well as difficulties in assessing the long-term effects of CSR initiatives. Key conclusions highlight the need for more structured approaches to assessing the social and economic effects of CSR, recommending that companies improve their transparency and accountability, and implement clear indicators of success to achieve sustainable economic and social outcomes.

As the global economy pays increasing attention to sustainable development and environmental protection, the role of green finance in promoting regional technological innovation is becoming more and more prominent. This study aims to analyse the impact of green finance on regional technological innovation and its mechanism of action, with special attention to the mediating effect of R&D inputs and the moderating role of regional characteristics. By analysing the panel data of 30 provinces in China from 2008 to 2021 with fixed and mediated effect models, the results show that green finance significantly promotes regional technological innovation. R&D investment intensity partially mediates this effect, while regional innovation and entrepreneurship capacity plays a significant moderating role in this relationship. Specifically, regional innovation and entrepreneurship capacity reinforces the positive impact of green finance on R&D investment, but the marginal effect of R&D investment is reduced in regions with stronger innovation and entrepreneurship capacity. The findings provide a theoretical basis for formulating relevant policies to promote green finance development and sustainable innovation in regional economies.

The purpose of this article is to present a proposal to call a tourist destination a magical town using a multi-criteria approach. To this end, its application is approached as a real multi-criteria classification problem with the use of the ELECTRE III method and is built from the components, considered from the importance they represent for the agents involved in the tourism sector, which contemplates the tourism supply, demand and management, infrastructure, services, natural and cultural resources, economic benefits and social impact. The results obtained with the use of this approach allowed us to evaluate and compare the tourist destinations that wish to be recognized under this nomination. In conclusion, the ELECTRE method turned out to be a success, since it allows us to explain and understand the competitive order of the tourist destinations under study. For future work, this procedure could be used to identify which factors are most important or attractive to decision makers.

This study examines the impact of foreign direct investment (FDI) on economic growth using panel data from 84 countries between 2010 and 2019. We utilized a two-step system generalized method of moments (GMM) to analyze how FDI affects economic growth through productivity gains and the role of economic freedom in attracting FDI. The findings suggest that FDI has a positive impact on productivity and benefits both OECD and non-OECD countries. Economic freedom plays a significant role in attracting FDI, particularly in OECD countries, and contributes to economic growth in non-OECD countries. However, economic freedom alone does not guarantee strong economic growth in OECD countries, but it significantly enhances growth in non-OECD countries. The results also highlight that only economies with robust economic infrastructure and development levels benefit more from FDI.

Natural disasters are currently a matter of great concern worldwide. Droughts are among the most recurrent episodes, causing significant private losses and thus worsening the economic situation of regions that depend on agriculture and livestock. This article presents a study of the duration of droughts in the southernmost state of Brazil, which has a large agriculture production and has shown recurrent events over the last two decades. The approach focuses on the time of economic recovery and whether economic impacts occurred, in the years of 2020, 2022, and 2023, and for this purpose it uses the total value of invoices issued in the municipality by companies to consumers and between them. To this end, the Kaplan-Meier estimator and the Cox regression model were used to analyze the economic recovery rates of the municipalities, also using factors such as their size, geographic location and main sector of economic activity. The results show that the longest recovery time is concentrated in small cities and cities that have agricultural or livestock activities as their main activity, and also show greater resilience in cities in the metropolitan region, which has a tributary of many rivers and is more concentrated in services and industry, with larger cities. The study identify that in each year at least 75% of the municipalities have their economic recovery within 3 months. The findings allow a better planning for both prevention and mitigation of the effects of droughts. They are also relevant for the design of economic and social policies.

The advent of Web3 technologies, leveraging blockchain and smart contracts, promises a paradigm shift toward decentralized and autonomous economic interactions. However, the lack of robust trust and reputation mechanisms among pseudonymous participants hinders its evolution into a fully functional economic system. This paper introduces the Dmany Nexus Protocol, a decentralized reputation system that quantifies user trustworthiness through verified on-chain and off-chain actions, addressing critical issues of information asymmetry, moral hazard, and adverse selection inherent in decentralized networks. Building upon the live data and insights from the Dmany Quest Engine, the Nexus Protocol integrates advanced principles from information economics, game theory, and mechanism design to develop a quantifiable reputation metric—the Social Capital Score ((SCS)). This metric aggregates multiple facets of user behavior, employing sophisticated anti-collusion algorithms and zero-knowledge proofs for privacy preservation. Unlike existing solutions, the Nexus Protocol offers a standardized, interoperable, and tamperresistant reputation system that enhances economic efficiency and fosters mass adoption by enabling secure, privacy-preserving interactions among pseudonymous actors. Empirical analyses demonstrate that the protocol effectively mitigates security risks such as Sybil attacks and reduces information asymmetry, leading to improved task quality and reduced fraudulent activities in decentralized platforms. By establishing a foundation for trust and cooperation in the Web3 ecosystem, the Dmany Nexus Protocol significantly advances the potential for scalable and efficient decentralized economies.

This study examines the transformative potential of Artificial Intelligence (AI) in international trade, highlighting its significant roles in optimizing trade operations, enhancing trade finance, and improving market access. In trade optimization, through advanced machine learning and predictive analytics, AI helps in demand forecasting, route optimization, and customs processes, ensuring efficient logistics and inventory management. In trade finance, AI automates document processing and risk assessment, democratizing access to finance and enhancing transactional transparency through integration with blockchain technology. In improving market access, AI-driven analytics identify consumer trends and competitive dynamics, enabling personalized marketing and overcoming linguistic and cultural barriers. The study includes case studies of leading companies such as Alibaba, DHL, and Maersk, showcasing how they leverage AI to enhance their trade operations, improve customer service, and achieve greater efficiency. These real-world examples demonstrate AI's practical applications and significant benefits in the global trade landscape. However, the adoption of AI in international trade is not without challenges. These include data quality, ethical considerations, technological complexity, and public perception. Ensuring high-quality, accessible data, fostering ethical AI usage, and overcoming technological and regulatory barriers are crucial for successful AI integration. Policy recommendations emphasize the need for robust data infrastructure, ethical AI guidelines, and international cooperation to harmonize data protection regulations. These measures aim to create an environment conducive to AI-driven sustainable economic growth and innovation in global trade.

Cultural differences between nations lessens the degree of commerce and interactions that are performed. This could cause degredation in economic shifts, which could alter and devestate the lives of many people.

This paper explores the dynamics of political competition, resource availability, and conflict through a simulation-based approach. Utilizing agent-based models (ABMs) within an evolutionary game theoretical framework, we investigate how individual behaviors and motivations influence collective outcomes in civil conflicts. Our study builds on the theoretical model developed by Basuchoudhary et al. (2023), which integrates factors such as resource availability, state capacity, and political entrepreneurship to explain the evolution of civil conflict. By simulating boundedly rational agents, we demonstrate how changes in resource availability and state capacity can alter the nature of civil conflict, leading to different equilibrium outcomes. The findings highlight the importance of understanding individual motivations and adaptive behaviors in predicting the stability and resolution of conflicts. This research contributes to the growing body of literature on the use of agent-based models in evolutionary game theory and provides valuable insights into the complex interactions that drive civil violence.

As the whisky industry applies circular economy principles to maximize resource utilization and minimize environmental impact, companies become exposed to several risks, which require complex assessments to ensure reliable outcomes. This study provides an organized framework to identify, prioritize and rank various risk factors commonly observed in whisky industry through the development of an Analytical Hierarchy Process (AHP) multi-criteria analysis model. Experts from 18 small European distilleries identified five main risk criteria and nineteen sub-criteria from brainstorming workplace observations, and categorized them as: environmental (5), operational (4), technological innovation (3), food safety (3) and economical (4) risks. The Analytical Hierarchy Process (AHP) approach was used to determine the weights and ranks of the main criteria and sub-criteria based on the survey responses received from experts from each distillery. The final judgements are consistent, as indicated by consistency values (CR) of less than 0.1 for all risk criteria. Unlike traditional risk assessment methods, the AHP model effectively integrates qualitative and quantitative data, aiding strategic decision-making in the whisky industry by breaking down complex problems into manageable sub-problems. Future research directions may expand the criteria and explore additional sustainable practices.

The scale of China's floating population is very large, and it is a key group that needs attention in promoting the equalization of basic public services. This study explores the impact and mechanism of adjusting the urban household registration threshold on the acquisition of citizenship status by the "rural-urban" floating population, with the household registration threshold as the link. It was found that the threshold for household registration has an impact on the willingness of rural urban migrant population to settle down from two aspects. On the one hand, a high threshold for household registration implies the unaffordability of obtaining citizenship status for the "rural-urban" migrant population, which has a significant crowding out effect on their willingness to settle down. Moreover, the high skilled "rural-urban" migrant population without housing is more sensitive to the high threshold for household registration. On the other hand, from the perspective of urban scale, the increase in the threshold for household registration has had a crowding out effect on the floating population for Type I large cities, mega cities, and super large cities. The increase in the threshold for settling in mega cities has the strongest crowding out effect on the floating population, which means that as the urban population expands, the welfare benefits enjoyed by the floating population in these cities will decrease, leading them to be more inclined to leave these cities and seek development opportunities in other cities. This study effectively answers how the threshold for household registration affects the willingness of rural urban migrant population to settle, providing mathematical support for urban development.

The study used the data from emerging markets to examine the impact of restrictive macroprudential policies on income inequality from 2000–2019 using Bayesian panel vector autoregression and Bayesian panel dynamics generalized method of moments models. The chosen models are suitable for addressing multiple entity dynamics, accommodating a wide range of variables, handling dense parameterization, and optimizing formativeness and heterogeneous individualspecific factors. The empirical analysis utilized various macroprudential policy proxies and income inequality measures. The results show that when the central banks tighten systems using macroprudential policy instruments to sticker debt-to-income and financial instruments for lower-income borrowers (the bottom 40% of the income distribution) promote income inequality in these countries while reducing income inequality for high-income borrowers (the high 1 per-cent of the income distribution). The impact loan-to-value ratios were found to be insignificant in these countries. Fiscal policy through government expenditure and economic development reduces income inequality, while money supply and oil price shocks exacerbate it. The study suggests implementing a progressive debt-to-income (DTI) ratio system in emerging markets to ad-dress income inequality among lower-income borrowers. This would adjust DTI thresholds based on income brackets, allowing lenient credit access for lower-income borrowers while stricter limits for higher-income borrowers. This would improve financial stability and reduce income disparities. Additionally, targeted financial literacy programs and a petroleum-linked basic income program could be implemented to distribute oil revenue to lower-income households. Monetary Supply Stabilization Fund could also be established to maintain financial stability and prevent excessive inflation.

This paper examines the impact of renewable energy heating on air quality in northern China, using the Qinling Mountains-Huaihe River line as a quasi-natural experiment to distinguish between regions with central heating and those without. Employing a difference-in-differences approach and analyzing panel data from 299 cities between 2014 and 2022, our findings indicate that the renewable energy heating policy has significantly improved air quality. Specifically, the policy led to substantial reductions in the Air Quality Index (AQI) and concentrations of key pollutants: SO2 by 28.31%, CO by 7.57%, NO2 by 5.72%, and PM2.5 by 7.15%. The policy's effects are most pronounced in regions with lower temperatures and in the eastern parts of the country. Further analysis emphasizes the critical role of energy transition, environmental regulations, and government investment in technology as key drivers of these air quality improvements.

This study examines the relationship between Gross Domestic Product (GDP) and income inequality in Greece across three key periods: the pre-crisis period (2003-2008), the crisis and memoranda period (2009-2014), and the post-crisis period (2015-2020). Using data from the World Bank Open Data database, the study employs correlation analysis, and linear regression models to analyze how economic changes influence income distribution. The findings reveal that during the pre-crisis period, economic growth was moderately correlated with increasing inequality, although this relationship was not statistically significant, indicating uneven distribution of growth benefits. In the crisis period, a strong and statistically significant negative relationship between GDP and the Gini coefficient was identified, highlighting the sharp rise in inequality as the economy contracted due to austerity measures. In the post-crisis period, the relationship between GDP and inequality weakened, showing a statistically insignificant correlation, suggesting that economic recovery alone did not significantly reduce inequality. The study concludes that economic growth is insufficient to address income inequality without targeted policy interventions, particularly during periods of crisis. These findings underscore the importance of comprehensive social policies to mitigate inequality and suggest areas for future research on the impact of specific interventions on income distribution.

The capability of large food retail chains to respond quickly to changes in consumer behaviour and their dominant market position affects all food market players and often conflicts with the interests of national food producers, which can reduce the presence of locally sourced products in the food product mix in the country. In Latvia, there have been several proposals to limit retailers' opening hours on weekends and public holidays to increase the viability of small local food producers, retailers, and catering enterprises; however, limiting retailers' opening hours without research-based arguments is unacceptable. The research studies conducted in Europe also do not give a unified conclusion. Household consumer behaviour in the food market is viewed as an essential argument for increasing domestic demand and economic stability. Accordingly, the present research aims to identify the impacts of diversification of opening hours of food supermarkets on consumer shopping habits and the implications for creating an advantage for small and medium agri-food producers in selling their products. The research applied a quantitative approach to identify the main trends in society (n=2738), with a survey including 31 variables to quantify consumer behaviour, values, and opinions and seven socio-demographic variables. If a decision were made in Latvia to close grocery shops on Sundays or reduce their opening hours on weekends, 85% of consumers indicated that they would be unlikely to change their usual shopping location and would plan to shop at a supermarket on other days. The choice between farmers' markets and local food shops on Sundays would be made by 45% of consumers, with more than half (53%) of them shopping at local food shops at least a few times a month. It could, therefore, be argued that reducing the opening hours of supermarkets and closing them on Sundays and public holidays do not provide a competitive advantage and do not divert consumers to small and medium agri-food producers.

The investigation of the correlation between Foreign Direct Investments (FDIs) and wage dynamics, particularly in the context of gender-related aspects, is of paramount importance in understanding the broader implications of economic globalization. This study aims to provide a comprehensive analysis of the intricate relationship between FDIs and wage trends, with a specific focus on the Dutch context. Using data from the United Nations Conference on Trade and Development (UNCTAD) and the World Bank, the research applies statistical techniques, including regression analysis, to explore the relationship between FDIs and wage trends over time, with a focus on gender differences. The analysis reveals that while FDIs contribute to overall wage growth, their impact varies significantly between male and female employees in the Netherlands. This highlights the need for policies addressing these gender-based disparities, providing a unique gender-focused perspective on the influence of FDIs on wage trends and expanding the existing literature on economic globalization and wage dynamics.

This paper examines the determinants of CO2 emissions in Oman from 1990 to 2022, focusing on the impacts of energy consumption, economic growth, urbanization, financial development, and foreign direct investment. Utilizing stepwise regression, robust least squares, Fully Modified Least Squares (FMOLS), Canonical Cointegrating Regression (CCR), and various cointegration tests including the Johansen cointegration test, Engle-Granger cointegration test, and Vector Error Correction (VEC) model, the study reveals several key findings. Energy use per capita (ENGY) and real GDP per capita (RGDPC) are consistently significant positive predictors of CO2 emissions. Urbanization (URB) also significantly contributes to higher emissions. Conversely, Financial Development Index (FDX) and foreign direct investment (FDI) do not show significant effects on CO2 levels. The high R-squared values across models indicate that these variables explain a substantial portion of the variation in emissions. Cointegration tests confirm long-term equilibrium relationships among the variables, with the Johansen test identifying two cointegrating equations and the Engle-Granger test showing significant tau-statistics for FDX, ENGY, and URB. The VEC model further highlights the short-term dynamics and adjustment mechanisms. These findings underscore the importance of energy policy, economic development, and urban planning in Oman's efforts towards sustainable development and decarbonization.

The small business sector in Kazakhstan demonstrates dynamic growth, but its sustainable development in modern conditions requires activation from government agencies, society and entrepreneurs themselves The purpose of the article is to study the development of small entrepreneurship in Kazakhstan and develop a mechanism for sustainable development based on network interaction "business entities - society-state" with the identification of priority areas of development based on a rating approach. The methods of bibliographic analysis of scientific literature, statistical, correlation analysis, survey, comparative analysis, ranking based on data normalization were used. The results revealed the need to formalize indicators of sustainable development of the small business sector in strategic development programs; create conditions, support, explain the importance and prospects of investing in sustainable innovations by small businesses; form a balanced strategy for achieving carbon neutrality based on network interaction "business entities - society-state" with the identification of priority areas of development based on a rating approach to ensure transparency and publicity of decisions made. Conclusions are made about the need to popularize sustainable development among business entities, stimulate investment activity through government participation, legislative regulation of public presentation of non-financial reporting, and assist society in the formation of an ESG culture.

The COVID-19 pandemic has significantly reshaped global power dynamics, impacting economies, political landscapes, international relations, and technological advancements. Historically, pandemics have acted as catalysts for social and economic transformations, and COVID-19 has followed this pattern by intensifying existing trends and creating new opportunities for power shifts. Economically, the pandemic led to unprecedented disruptions, with East Asian countries demonstrating greater resilience and adaptability compared to Western economies. This has resulted in notable economic power shifts, particularly benefiting China, which experienced a swift recovery. Politically, the pandemic exacerbated geopolitical tensions, notably between the United States and China, while also fostering new forms of international cooperation, such as vaccine diplomacy and multilateral health initiatives. Technologically, the pandemic accelerated digital transformation and innovation in biotechnology, with significant advancements in healthcare systems. Socially, it exposed and exacerbated inequalities, prompting discussions on social justice and healthcare reforms. Environmentally, short-term improvements were observed, but the need for sustainable development and green recovery strategies became evident. This article examines these shifts, highlighting the interconnectedness of global challenges and the necessity for coordinated, multilateral responses to build a more equitable and sustainable future.

Under the new pattern of "Double-Cycle" economy, how to restructure the domestic economic structure to cope with the continuous softening of the global economic structure is an urgent issue. This paper empirically examines the impact of digitalization level on the division of labor in National Value Chain (NVC) within cities using panel data from 263 cities between 2001 and 2016, employing a spatial Durbin model.The study demonstrates that the digitization level can enhance division of labor in NVC in neighboring regions through spatial spillovers. An increase in digitization not only positively deepens the construction of NVC but also contributes to the development of NVC in adjacent areas.The digitization level can deepen the division of labor in NVC through the impact of cost reduction, consumption upgrading, and market integration. This effect exhibits regional variations, with consumption upgrading playing a crucial role in expanding the division of labor in NVC in the eastern region through improving digitization levels, while cost reduction is a key factor in the central region. The research results of this paper provide some empirical evidence for further progress and transition of China's NVC developing mode from the perspective of digital level.

Agriculture is the largest sector of Nepalese economy among the south-Asian developing countries that contributed 26.98 % share of Gross Domestic Product (GDP) in the year 2018/19. The capacity to derive maximum output by per unit of resource is resource use efficiency. Resource use efficiency of a producer explains the comparison between inputs and output value. Potato is staple vegetable in every parts of Nepal. Cobb-Douglas production function is used to predict the significance of inputs in income from cash crops. Due to lack of optimum utilization of available resources in cultivation of vegetable like lack of technical knowledge, low education level, and extensive service the productivity and production is low in Nepalese economy. It ensures vegetable security in Nepal. Though, there are extensive researches on the resource use efficiency and productivity issues on agriculture, very few papers explored in the case of Sudurpaschim province of Nepal OBJECTIVE: This study had the specific purposes: (1) To identify the factors affecting in resource use efficiency and productivity of potato production (2) to utilize the resource use efficiency and productivity in potato production and (3) to show the type of returns to scale in potato production. METHODS: Applying post-positivist paradigm and quantitative causal survey research design, it explored the resource use efficiency and productivity through the semi-structured questionnaire from 140 households by random sampling. Data analysis was carried out by multiple regression model using Cobb-Douglas production function. SPSS software was used to find quantitative results. From the analysis of data using mean, and SD, t-test, analysis of variance, Durbin-Waston test, Marginal Value Product and marginal Factor cost, findings of this research was emerged. RESULTS AND DISCUSSION: The major findings: education level, extension service, farm size and pesticide cost were significant variables in potato production; seed, hired labor, Family Yard Manure and pesticide cost were overused and needed to decrease their cost for optimum allocation and there was decreasing returns to scale in production. This study emphasized on increasing education level, extensive service and farm size for optimum utilization of resources and increasing returns to scale. SIGNIFICANCE: Barriers to Indian potatoes and increasing returns to scale are only possible through protection policy of government. For optimum use of resources and increasing returns to scale, government can introduce capital intensive technique. This study can be implied in policy making and improving existing situation of agriculture, and allocating budget.

While financial literacy is crucial in improving the population's financial well-being, its effectiveness can be enhanced by exposure to financial information. This paper investigates the nexus between financial literacy, financial information consumption, and financial well-being in rural Ghana. The study employed cross-sectional data from a survey of 663 rural households using simple random and cluster sampling with reflective-reflective constructs. The data was analyzed using Structural Equation Modelling-Partial Least Squares. The findings reveal that financial literacy and financial information consumption significantly enhance financial well-being among rural households in Ghana. Financial Literacy also promotes Financial Information Consumption. Notably, financial literacy's impact on financial well-being is stronger when mediated by the consumption of financial information. These findings underscore the importance of improving financial literacy and information access to uplift financial well-being in rural areas. Moreover, the study highlights that financial literacy education is crucial as it plays a mediating role; recipients of financial education experience a more substantial impact. Such findings emphasize the importance of acquiring financial knowledge and effectively processing financial information to achieve financial prosperity, particularly in rural areas. These findings should motivate individuals, especially those in rural areas, to process financial information successfully rather than merely acquiring financial knowledge to attain financial prosperity.

Over the coming decades, global freshwater withdrawals are expected to grow, especially in low and middle-income countries. Unless there are significant improvements in the efficiency of water use by economies, freshwater stress, crises and scarcity will worsen. This paper explores further the economic relationship between water use efficiency and scarcity. Because growing scarcity of freshwater in many regions and countries is not adequately reflected in markets, there is often insufficient incentives for investment and innovation to improve the efficiency of water use. To explore further changes in water use efficiency across countries, we conduct a panel analysis of water productivity changes for 130 countries over 1995 to 2020. Countries with lower initial levels of water use efficiency tended to have higher water productivity growth, whereas more agriculturally dependent economies displayed lower improvements in water use efficiency. Better institutional quality and capacity for innovation may also increase water use efficiency. We discuss the implications of these results for improving water use productivity in economies, and in particular, the opportunities and challenges for improving water markets and trades to alleviate water scarcity. We conclude by identifying further areas of research.

Introduction – Elections are a cornerstone of democratic societies, enabling citizens to express their preferences and shape the direction of their governments. Economic conditions, political dynamics, and social factors often play pivotal roles in influencing voter behavior and determining electoral outcomes, making elections a key area of study in understanding governance and policy change. Objectives – This study examines how key economic factors like inflation, unemployment, and poverty influence election results in Ghana. It also looks at how these economic elements shape voter choices and predicts the possible outcomes of the 2024 general elections using past data. Methodology – The study used historical economic and political data from 1992 to 2023, applying statistical models like ARIMA (Auto-Regressive Integrated Moving Average) to forecast future election outcomes. Economic indicators such as inflation and unemployment were included to study their relationship with voter behavior. Findings - The results show that economic factors significantly impact voter turnout and party vote share. High inflation and unemployment rates tend to reduce voter support for incumbent parties. The model also predicts possible outcomes for the 2024 election based on these economic trends. Conclusion and Recommendation – The study concludes that improving economic conditions, such as reducing unemployment, could positively influence electoral outcomes for incumbents. It is recommended that policymakers focus on stabilizing the economy to enhance electoral success.

This study addresses a gap in the literature by conducting a comparative analysis of statistical and artificial intelligence techniques for predicting bankruptcy in small and medium-sized enterprises (SMEs). Using a comprehensive database of 7,104 Belgian SMEs, our findings demonstrate that intelligent techniques offer superior predictive accuracy for bankruptcy. Notably, our results indicate that a firm's position in the global value chain significantly affects prediction accuracy, with lower performance for firms operating upstream in the production process. This suggests that bankruptcy risk may spread upward along the value chain. This insight is particularly valuable for practitioners, as it highlights the importance of focusing on specific performance factors based on the type of firms they manage, advise, or collaborate with.

An ambitious per capita GDP target has been envisioned by the Chinese government since 2020 to project its sustainable economic growth rate by 2035. Can China fully achieve its goal? This is a question worth investigating. By inserting relevant TABLO modules of the final goods trade, the intermediate goods trade, and factor-strengthening technology spillovers, along with technology absorption thresholds effects of the global value chain, this study builds a global dynamic recursive computational general equilibrium (CGE ) model on basis of GTAP-RD. This approach allows considering the 'dual circulation' system strongly advocated and pointed out as the sole way to realize China’s technological (total factor productivity (TFP)) progress by the Chinese government, which integrates both domestic internal and international external circulations (trade and foreign direct investment (FDI)). We simulate China's technological progress under eight scenarios, and use the latest GTAP Version 11 production and trade data (released in April 2023) for 141 countries and regions and results are aggregated into 10 countries groups with 9 activity sectors and 10 commodities. Main conclusions are as follows: (1) If China maintains its trade opening policy, the 2035 vision goal can be achieved, with external circulation being more important than internal circulation for technological spillovers. (2) The economic growth impacts of external and internal circulation operate relatively independently. However, FDI provides a relatively larger synergistic effect for all forms of external trade circulation than to the internal one. Regarding factor-strengthening effects, spillovers are more favorable to 'capital' than to labor factors. (3) We find that the Regional Comprehensive Economic Partnership Agreement is the most important strategic partner for China. (4) It appears that FDI is not an effective way to lift the productive services sector's total factor productivity (TFP), and more realistic for China is to open up the productive services market more widely, as its efficiency is a pivotal reflection of China's independent innovation capability. (5) China–US decoupling has an enormous global impact. In all the Scenarios we consider, the United States is always the country that loses the most, and Europe would be the group of countries that benefits when there is a large increase in TFP in the US.

The digital transformation of the global economy presents new challenges and opportunities for businesses and nations. With the growing role of digital technologies and the dynamic changes in the structure of the economy, there is a need for a better understanding of the processes shaping contemporary enterprises. This article analyzes the impact of digital transformation on businesses and the global economy, identifying key areas where these changes are most evident. As part of this discussion, a modification of the “9 Pillars of Industry 4.0” concept is proposed, incorporating solutions that have emerged since its inception. The resulting model, “11 Pillars of Industry 4.0,” enabled the analysis of the “born digital” and “born global” concepts, highlighting their numerous common features in the context of the digital transformation of economies. This became the basis for proposing a new concept: “born digibal” — enterprises that from the outset operate in multiple markets, with their main sphere of activity based on digital solutions.The conclusions of the article provide an assessment of the changes occurring in businesses and the global economy in the digital age. They suggest that the dynamics of globalization in the 21st century will be shaped by complex interactions between digital transformation and the actions of businesses and nations, requiring flexibility and innovation in adapting to new economic realities.

The paper analyzes the relationship between urban waste recycling and technological innovation systems in Europe. Data from the Global Innovation Index for 34 European countries in the period 2013-2022 was used. To analyze the characteristics of European countries in terms of waste recy-cling capacity, the k-Means algorithm optimized with the Elbow method and the Silhouette Coef-ficient was used. The results show that the optimal number of clusters is 3. Panel data results show that waste recycling increases with domestic market scale, gross capital formation, and the diffu-sion of Information and Communication Technologies (ICTs), while it decreases with the infra-structure index, business sophistication index, and the average expenditure in research and devel-opment of large companies.

This paper detects bidding behaviors in the auction with the random cutoff, where a winning bid needs to be above and the closest to the random cutoff. In this auction, each bidder is eager to predict the random cutoff in order to use the predicted random cutoff as bid. Furthermore, one of deep learning models, the transformer model is employed as one empirical method to anticipate the random cutoff. The result shows that the predicted random cutoff turns out to be a winner with probability of about 20 percent. This paper contributes to economic literature in terms of investigating the connection between a deep learning model and an auction based on the economic theory.

Sub-national governments (SNGs) in developing countries have increasingly explored green municipal bonds as a financing tool, driven by promises of lower borrowing costs, enhanced reputation, and support for sustainable economic development. This study aims to critically examine these claims by analysing the actual costs and complexities associated with green municipal bonds (GMBs). The research involves a comparative analysis of traditional municipal bonds and GMBs, focusing on the financial and operational challenges faced by SNGs. Detailed case studies from Mexico City and Cape Town are used to illustrate the practical implications of issuing GMBs. The findings reveal that, despite similar or slightly lower interest rates, GMBs often entail higher issuance costs due to the need for certification, monitoring, and reporting of green projects. These additional costs, coupled with the necessity of hiring external consultants, make GMBs more expensive and difficult to replicate after initial transactions. Furthermore, the study highlights that the demand from investors has not met initial expectations. While green-aligned investors show a higher appetite for GMBs, they constitute only a small portion of the finance market. Traditional investors, primarily focused on financial returns, are less inclined to invest in GMBs solely based on their green label. Consequently, many SNGs have reverted to issuing traditional “vanilla” municipal bonds while still using the proceeds to fund green initiatives. This shift underscores the need for a realistic assessment of GMBs’ viability in developing countries and calls for a re-evaluation of strategies for promoting sustainable economic development through green finance.

Such rapidly changing external conditions as the COVID-19 pandemic and the war in Ukraine, being pure crisis phenomena, not only determine the geopolitical and geoeconomic situation on the global markets, but also cause structural changes in individual countries. Under these conditions, the level of food self-sufficiency becomes particularly important, as it is one of the factors determining the food security of any country. The aim of the research is to assess Ukraine's food self-sufficiency compared to the European Union and Poland. The self-sufficiency ratio (SSR) index was used to assess food self-sufficiency. This is the ratio of the volume of production of the most important products of plant and animal origin to the volume of domestic consumption. Domestic consumption was defined as the volume of domestic production increased by the volume of imports, reduced by the volume of exports and also included changes in domestic stock levels. The surveyed time frame is 2019–2021. The analyzed data were taken from the State Statistics Service of Ukraine, FAOSTAT, USDA and Statistics Poland. A comparative analysis of self-sufficiency for the main agri-food sectors of Ukraine, the EU, and Poland showed significant differences. Taking into account the production potential and food self-sufficiency indicators of Ukraine, Ukraine's possible accession to the EU can be expected to have a major impact on the EU's supply and demand situation, as it may pose a threat to many EU agri-food sectors.

This article underscores the immense potential for substantial economic growth and development that can be harnessed through effective participation in global value chains (GVCs). It emphasises the role of policymakers in adeptly navigating GVCs, prioritising tasks, exploring different forms of GVC governance, and fostering a conducive environment for foreign investments. By effectively managing power dynamics and supply chain risks, countries can attract valuable foreign investors, enhance market connectivity, and improve infrastructure and services, leading to significant economic growth. The potential benefits of GVC participation are vast, and policymakers can shape the situation by understanding and addressing strategic inquiries, laying the foundation for a prosperous future. Furthermore, the article explores the potential for a country to enhance its involvement in GVCs and progress to more lucrative activities by strengthening existing connections between GVCs and the local economy. By enhancing the capacity of local stakeholders to acquire knowledge, policymakers can play a crucial role in maximising the benefits from GVC spillovers, positively impacting a country's economic development.

As a result of decades of austerity, the economies of the Eurozone are experiencing under-investment and crumbling infrastructures in an era of extremely severe emergencies as the cli-mate change and aggressive global competition. The private savings glut of the rich and the strict fiscal rules suggest a crowding-in approach in partnership with big finance in a new age of in-fra-structures. If governments mint public infrastructures into investable assets, they can gen-erate steady returns for investors and asset managers who look after pensions and insurances schemes and unlock trillions now devoted to welfare state. For the big finance to accept to be partner, however, governments must take the task of de-risking returns. Innovation technology and macro-financial literacy can synergically act to enhance this new de-risking role to address in a financially sustainable way the intense phenomena of Natural Hazards (NHs) that can severely compromise economic growth. This is precisely the aim of our Public-Private Partnership (PPP) among the Department of Economics, Management and Institutions of the University of Naples and a Knowledge Transfert Management, the Department of Engineering and the Aca-demic Spin-Off “STRAIN”, of the University of Campania. Our PPP has been contributing to the eval-uation and mitigation of NHs such as floods, landslides and earthquakes since 2012. The ex-tremely advanced results of this multi-stakeholder partnership ensure a better knowledge of NHs which, as evidenced in the paper, is the fundamental input for the desired Public-Private In-surance Programmes (PIPPs).

This study examines the aggregate consumption function of Saudi Arabia from 2000 to 2022, focusing on identifying key determinants of household consumption and evaluating the impacts of disposable income, household wealth, government expenditure, interest rates, and oil revenues. The research uses advanced econometric methods, including the Autoregressive Distributed Lag (ARDL) model and Johansen cointegration test, to analyze the relationships among these variables. The findings reveal that disposable income, household wealth, and government expenditure significantly and positively influence consumption, whereas interest rates show a negative correlation. Oil revenues also play a critical role, reflecting the country's economic reliance on oil. The study highlights the necessity for economic diversification to reduce the impact of oil price volatility on household income and consumption stability. The results offer crucial insights for policymakers, emphasizing the need for strategies that enhance household income and wealth, maintain robust public sector spending, and effectively manage interest rates. These findings also support the importance of consistent and predictable income sources for sustaining consumption. Additionally, this study suggests directions for future research, including developing sophisticated forecasting models to predict consumption trends and exploring other influencing factors such as demographic shifts and technological progress.

The environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus regarding the EKC hypothesis among countries and regions of different income groups. In this study, we analyze the EKC hypothesis for 158 countries and 44 regions from 1990 to 2020, categorizing them into different income groups based on the World Bank's income classification (low, lower-middle, upper-middle, and high-income countries). Our findings reveal mixed patterns in the EKC across different income levels, highlighting the heterogeneous relationship between economic growth and carbon emissions and showing differentiated patterns among different income levels. While a rise in income for high-income countries should be reflected in a shift toward fewer carbon emissions, for lower-income countries, growth is still associated with rising emissions. This underscores the urgent need for policy interventions that decouple economic development from environmental degradation. A balanced approach to economic growth, which prioritizes carbon neutrality across all stages of development, by tailoring environmental and economic strategies to address CO2 emissions effectively, should be adopted, recognizing the different developmental stages and income levels of countries and regions.

(1) Background: The rapid development of information technology has changed the traditional concept of space, gradually shifting the "container space" to the "relational space" . The constraints of geographical spatial elements are diminishing, and the theory of virtual agglomeration is gaining attention. (2) Methods: In this study, we constructed an evaluation system for virtual agglomeration, comprising four primary indicators: virtual infrastructure level, virtual output level, virtual input level, and virtual service level. The TOPSIS method was used to calculate the virtual agglomeration level for each province, and the DEA-Malmquist method was employed to measure provincial total factor productivity (TFP) in China. Using panel data from 30 provincial regions in China from 2013 to 2021, we examined the mechanism and impact path of virtual agglomeration on TFP. (3) Result: There is an inverted U-shaped relationship between virtual agglomeration and TFP in China. The overall development level of virtual agglomeration is relatively low, within the range where the marginal effect of virtual agglomeration on TFP is positive but diminishing, indicating significant potential for further development. The impact of virtual agglomeration on TFP is stronger in the Yangtze River Economic Belt compared to non-Yangtze River areas, and the highest stable point of TFP is higher in central provinces than in eastern and western provinces. (4) Conclusions: This study provides a theoretical basis and practical reference for improving the level of virtual agglomeration.

This work aims to initiate a reflection on the awareness of environmental, social, and corporate governance issues, summarized in the acronym ESG (Environmental, Social, Governance), among Italian SMEs. The integration of ESG issues into business models has led to an expansion of the risk taxonomy affecting corporate management. In addition to traditional financial risks, new risks have emerged, primarily climate risk, environmental, and energy risks, which can significantly impact companies' ability to create economic value. This includes planning and designing virtuous initiatives focused on sustainability and the ability to build public-private partnerships with various stakeholders. After this theoretical framework aimed at highlighting the evolution of the concept of corporate sustainability following the introduction of ESG factors, a clustering of non-performing loans of Italian companies is proposed using a k-Means algorithm, comparing the results obtained through two different methods, namely the Elbow method and the Silhouette coefficient. Finally, using data on Italian regions between 2004 and 2023, an empirical analysis is conducted to provide an estimate of the relationship between non-performing loans and some variables related to ESG components.

This study investigates the impact of Government Consumption (GC) on Saudi Arabia’s GDP during major economic crises from 1969 to 2022, with a focus on periods marked by fluctuations in oil and non-oil revenues. By integrating these revenue streams, the research provides a more comprehensive analysis of fiscal policy effectiveness during economic downturns. Using an Autoregressive Distributed Lag (ARDL) model, the study reveals the complex role of Government Consumption (GC) in stabilizing and stimulating the Saudi economy amidst revenue volatility.Key findings indicate that while GC does not significantly influence GDP in the short term, its long-term effectiveness varies across different crises. Specifically, GC has acted as a buffer against immediate economic shocks during certain crises while providing a stimulus for economic recovery in others. For instance, during the 2020 COVID-19 pandemic, timely fiscal measures significantly boosted GDP, underscoring the importance of adaptive and proactive fiscal policies. Conversely, the 2014-2016 oil price collapse demonstrated that GC alone was insufficient to counteract economic downturns, emphasizing the need for diversified revenue strategies.These findings underscore the dual role of GC in economic stabilization and recovery. During the COVID-19 pandemic, GC played a crucial role in both mitigating negative economic impacts and supporting recovery efforts, showcasing its effectiveness in times of global disruptions. This demonstrates GC's capability as an immediate buffer against economic shocks and a stimulus for economic recovery. In contrast, during the 2014-2016 oil price collapse, GC was less effective, indicating the limitations of relying solely on government spending without broader economic diversification. This highlights the necessity of diversified revenue strategies to complement fiscal measures for long-term economic resilience.The robustness of the findings was ensured through various diagnostic tests, including checks for autocorrelation, heteroskedasticity, and stationarity of residuals. The absence of significant autocorrelation and heteroskedasticity, along with the stationarity of differenced variables, confirms the validity of the econometric models used.The study contributes to the discourse on fiscal policy in oil-dependent economies by illustrating the critical role of diversified revenue strategies and adaptive fiscal measures in enhancing economic resilience. Recommendations are offered for policymakers to optimize fiscal strategies, ensuring robust economic recovery and long-term stability in volatile markets. This research highlights the necessity for Saudi Arabia to refine its fiscal policies towards greater economic diversification and stability.

We estimate general public’s willingness to pay (WTP) for agricultural soil quality protection and improvement in Spain (n=1000) and the UK (n=984) using data from a cross-sectional survey via Qualtrics panels in March-April 2021. We use a double bound dichotomous choice contingent valuation approach to elicit the individuals’ WTP. We investigate the effect of uncertainty on the success of policies aiming at achieving soil protection. In addition, to understand the heterogeneity in individuals’ WTP for agricultural soil quality protection and improvement we model individuals’ WTP through individual’s awareness and attitudes toward agricultural soil quality protection and the environment, trust in institutions; risk and time preferences; pro-social behavior and socio-demographics in Spain and the UK. We found that there is significant public support for agricultural soil quality protection and improvement in Spain and the UK. We also found that the support does not vary significantly under uncertainty of success of policies aiming at achieving soil protection. However the individual’s reasons for supporting agricultural soil quality protection and improvement are found to depend on the level of uncertainty and country. Hence, promoting public support for soil protection needs to be tailored according to the level of general public’s perceived uncertainty and geographic location.

Despite the known benefits of precision agriculture, the adoption is challenging due to the cost of investment and the farm sizes. Therefore, profitability is an important aspect to consider. This study aimed to evaluate the net returns, profitability, and investment efficiencies of PA by different economic farm sizes. The study was based on data retrieved from FADN and Eurostat. The study examined four countries (Poland, Germany, France, and Romania) under field crop farming using an investment cost of €35 941 - €71 883, and a 20% and 15% reduction in the cost of crop protection and fertilizer usage respectively without compromising productivity. There is a positive relationship between the adoption of PA and farm returns for larger-scale farms. The result of the profitability and analysis of investment efficiency using NPV showed a positive value for economic farm sizes of €100 000 and above. Hence, it is not economically advisable that all farmers use PA technologies with the hope that they will be profitable but with public support (subsidies) more farms will be able to use PA and be profitable. Also, an opportunity to meet the goal of the European Union Green Deal of minimizing emissions that cause climate change.

This study examines the relationship between entrepreneurship and sustainable devel-opment in Saudi Arabia from 2006 to 2022, focusing on the economic, social, and en-vironmental dimensions. Using the Autoregressive Distributed Lag (ARDL) model, the research investigates both short-run and long-run dynamics to understand how entre-preneurial activities influence sustainable development within the framework of Saudi Arabia's Vision 2030 initiative. The findings indicate that entrepreneurship significantly contributes to economic growth through job creation and innovation, thereby aiding in the diversification of the economy away from oil dependency. Socially, entrepreneurial ini-tiatives have a positive impact on gender equality and social inclusion by empowering women and integrating youth into the labour market. Environmentally, entrepreneurship helps reduce carbon emissions and promotes sustainable business practices. Despite these positive outcomes, challenges such as regulatory barriers, limited access to finance, and the need for a supportive entrepreneurial ecosystem remain. Recommendations include enhancing entrepreneurial education, providing financial incentives, and streamlining regulatory processes to better support start-ups and SMEs. The study highlights the ne-cessity of addressing these challenges to fully realize the potential of entrepreneurship for sustainable development in Saudi Arabia. By providing empirical evidence on the sig-nificant role of entrepreneurship in driving sustainable development, this research offers actionable insights for policymakers aiming to foster a more resilient and diversified economy in line with Vision 2030. .

Food security is the cornerstone of national security, and exploring the resilience of the grain industry chain is particularly important under the current complex and changing external environment. The study is to evaluate the grain industry chain resilience and identify its influencing factors. Based on the panel data of 30 provinces (cities) in China from 2011 to 2022, this paper adopted Partial Least Squares structural equation modeling method to carry out comprehensive evaluation, applied Dagum Gini coefficient to analyze spatial differences, and used geo-detectors to identify the influencing factors. The results showed that (1) from an overall perspective, the resilience of China's grain industry chain showed an overall upward trend, and each region had been greatly improved; (2) from the perspective of spatial differences, the overall spatial variability of China's grain industry chain is relatively small, and the gap mainly originates from inter-regional differences; (3) from the perspective of influencing factors, the level of grain foreign trade, regional market size and agricultural innovation level were important factors. In order to enhance the resilience of China's grain industry chain, based on the heterogeneous characteristics, the coordinated development of each region should be integrated, and the endogenous power should be given full play to enhance the resilience of the industry chain.

Money demand is the amount of real money balance with people and they can decide at any time what part of their assets to keep in cash. In this study, money was assumed to be a durable good that leads to the flow of some kind of service. Therefore, money became a function of utility. Using AIDS elasticity demand function, income, price and cross elasticities were evaluated. The statistics of this study are related to the years 2003-2022. The results showed that, based on the assumption of three goods, the demand includes bills and negotiable instruments, demand deposits, and time deposits. Based on the limitation of symmetry, collectability and homogeneity, the tensions can be calculated. The results showed that the price elasticity of demand for banknotes and muskox with term deposits is not significant. On the other hand, the cross tension between sight deposits and term deposits is negative and significant.

Few studies have explored the gender wage gap among farmworkers, and there is a notable absence of research on how farm wages impact household welfare differently based on gender. This study aims to fill this gap by examining how farm wages affect gender disparities in household welfare among farmworkers in Nigeria. Using survey data from 720 farmworkers, we investigated gender-based differences in household welfare. Our approach combined parametric methods (Blinder-Oaxaca decomposition) to assess gender gaps in household welfare and non-parametric techniques (Propensity Score Matching, PSM) to estimate the effects of farm wages. The analysis reveals that female farmworkers experience significantly lower per capita food consumption expenditure (₦11,486.51 less) compared to their male counterparts. These disparities partly stem from differences in socioeconomic factors, job characteristics, and enterprise attributes between male and female farmworkers. The study underscores the role of farm wages in mitigating gender gaps in household welfare, demonstrating that farm wages have increased per capita food consumption expenditure for female farmworkers by ₦6,640.698. This finding highlights the potential of wage increases to enhance livelihoods, underscoring the importance of equitable wage policies in farming. Furthermore, our findings emphasize that the impact of farm wages on welfare varies with household characteristics, suggesting the need for targeted interventions tailored to enhance identified household attributes. Addressing these factors could effectively reduce gender inequalities in farm work and contribute to overall welfare improvements.

Abstract: The conundrum of Latin American countries in the green transition unveils new opportunities and old structural problems. There is a clear advantage in the energy grid for Argentina, Brazil, and Mexico, coming mainly from hydropower, solar, and wind energy. In 2022, Brazil had the largest solar photovoltaic energy generation capacity in Latin America and the Caribbean, with over 24 gigawatts. Mexico ranked second, with some 9 gigawatts, and Chile ranked third, with a capacity of around 6 gigawatts. The window of opportunity for the industrialized Latin American countries resides chiefly in greening the natural resources industries and agriculture and husbandry, mainly for Brazil and Argentina. Latin America faces the dual challenge of promoting renewable energy and upgrading its value chains while managing the socioeconomic dynamics inherent in its developmental stages. It poses an enormous challenge for Latin American countries because of the phenomenon of "time compression" (Whittaker et al., 2020). Developing country's innovation and technology-intensive segments coexist with informal labor and low-skilled workers. Far from disappearing with economic growth, such coexistence becomes reinforced through an increasingly wide array of temporary and insecure jobs. Time compression condenses different stages of industrial and economic development within the same space and time, directly affecting the indicators related to the reduction of environmental impacts. Instead of locking in one path for this transition, Latin American countries had better not cling to panaceas but consider the threats, the risks, and the need to experiment with multiple paths and solutions simultaneously. However, this change implies the formation of a genuine developmental and environmental coalition guided by rigorous strategic considerations not captured by immediate interests.

Greenflation or inflation for green energy transition in Europe, it becomes a structural problem of new scarcity and poverty, because the Green Deal and its fiscal and monetary policies. In this paper, it is paid attention to the Green financial bubble and the European greenflation paradox: in order to achieve greater future social wellbeing, due to a looming climate risk, present wellbeing and wealth is reduced, causing a real and ongoing risk of social impoverishment. According to the European Union data, it is going to show the relations between green transition (emissions, tax, debt, credit boom, etc.), GDP and inflation. As many emissions are reduced, there is a decrease of GDP (once deflated) and GDP per capita, evidencing social deflation, which in turn means more widespread poverty and a reduction of middle-class. Also, there is a risk of a green-bubble, like in the Great Recession of 2008 (but this time supported by the European Union) and possible stagflation. To analyze this problem, it is used here some econometric tools, but under the theoretical support of heterodox approaches, especially the Austrian Economics and the New-Institutional Schools.

Nuclear energy, along with renewable and alternative energy sources, is a crucial green energy source. However, the existing literature often overlooks the role of nuclear energy in achieving sustainable development goals. This study analyzes the impact of green technological innovation, nuclear energy consumption, and trade openness on environmental quality in the US, which consumed the most nuclear energy from 1990 to 2019. The ARDL bounds testing approach was applied for its effectiveness in smaller samples, suitable for the data set used in this study, to determine cointegration relationships. Additionally, the Toda-Yamamoto causality test was employed to explore causal links without requiring series stationarity or cointegration. The ARDL cointegration results indicate a significant long-term relationship between CO2 emissions, green technological innovation, nuclear energy consumption, and trade openness. The results suggest that promoting green technological innovation and nuclear energy (although this effect is less certain) can be effective strategies for reducing CO2 emissions, while the impact of trade openness requires careful consideration due to its potential to increase emissions. Green technological innovation has a significant unidirectional causal effect on CO2 emissions. These results will help policymakers design policies to achieve sustainable environmental goals in the US economy.

Based on the panel data of 114 Chinese resource-based cities from 2013 to 2022, this paper uses principal component analysis, Super-SBM and Malmquist index to measure the development level of digital economy and green total factor productivity of resource-based cities, and empirically studies the impact of digital economy on The impact effect and mechanism of green total factor productivity in resource-based cities. The research found that: (1)From 2013 to 2022, the overall green total factor productivity of resource-based cities in my country showed a trend of first decline and then an upward trend; (2) Digital economy can promote the improvement of green total factor productivity of resource-based cities, and digital economy has more long-term effects than short-term effects. (3)Mechanism analysis shows that energy efficiency and industrial struc-ture optimization are important paths for the digital economy to promote green total factor productivity in resource-based cities. (4)Heterogeneity research shows that digital economy has the largest effect on green total factor productivity in mature cities and the least effect on growth cities; From a regional perspective, the digital economy has the greatest effect on promoting re-source-based cities in the eastern region, followed by the central region, and the western region is weaker.

Remote work as a new working pattern is considered of high importance in determining the competitiveness of the institutions that adopt this form of work. This trend toward remote working has benefited workers greatly in terms of flexibility and work-life balance and has had unanticipatedly positive effects on sustainability. The issue has grown in importance considering recent development of digitalization and high concern of countries to achieve the sustainable goals. This study attempts to examine the effect of three explanatory variables: remote work, institutional efficiency, and work management on the competitiveness of finance institutions in Saudi Arabia. To collect the primary data, a survey was conducted on a stratified random sample that comprised 1270 respondents. The sample covers the three finance sector segments: banks, insurance, and finance companies. Correlation analyses, one-sample t-tests, and multi-regression analyses are applied to analyze the data. The results of the study showed that there is a positive significant relationship between the three explanatory variables of the study and institutional competitiveness. Besides, the regression model revealed that the two explanatory variables; remote work and institution efficiency are statistically significant at 95% confidence intervals, while work management is not statistically significant. The study recommends promoting remote work to increase the finance institution's competitiveness by restructuring the work policies, designing work strategies, and introducing a new management system compatible with remote work.

The savings behavior of individuals has been a topic of both macroeconomic and policy importance throughout history. Theoretical and empirical research offers strong evidence that savings are the result of a number of demographic and economic factors working together to produce long-term, sustainable economic growth. This study therefore looked at how domestic savings affected South Africa's economic growth between 1970 and 2022. The ARDL framework was used to analyze data that came from the World Bank and the South African Reserve Bank. The results of the study demonstrate that corporate savings have a major effect on economic growth, especially over the long term. When corporate savings rise by 1%, the economy expands by 3.12%. On the other hand, savings by the government and the general public, especially in the long run, have no appreciable impact on economic growth. Given that domestic savings mobilization is the most suitable channel for financing capital accumulation to support economic growth and development, the study suggests reviewing current policies to encourage domestic savings mobilization.

Sustainable development advocates for an environmentally friendly and resource-saving approach, fostering a new quality of productivity that is green and sustainable, and achieving a sustainable development where the economy and the environment are in harmony. The paper is based on clarifying the effects of coordinated development between the economy and the environment, and by establishing an indicator system, applying a remote sensing ecological index, entropy weight method, gray relational degree model, and a coupling coordination model, the relationship of coordinated development of Ordos in 2016-2022 is analyzed from a spatial-temporal perspective. The results are as follows: ① The years of coordinated development between the ecological environment and the economy are in the majority, while the uncoordinated years are fewer. ② The level of coordinated development between the ecological environment and the economy in the various regions of Ordos has been increasing year by year, but it still remains at the barely coordinated and primary coordinated levels. ③ The types of coordinated development between the ecological environment and the economy in Ordos exhibit significant spatial differentiation in terms of spatial distribution and clustering.Therefore, it is necessary to formulate coordinated development policies and measures according to the constraining factors of different regions.

This research aims to elucidate the organizational patterns of interregional economic interdependence to enhance our comprehension of the national economy's structure at a regional scale. Employing a multilayer network model, this study represents economic interdependence among Indonesian regions, utilizing the InterRegional Input-Output (IRIO) table. Through the application of various metrics, such as degree and strength distribution, assortativity coefficient, and global and local rich club coefficient, to the multilayer IRIO network, we uncover the organizational patterns of economic exchanges between provinces and economic sectors within Indonesia. Our findings demonstrate that a multilayer network approach reveals the heterogeneous and complex structure of the national economy at the regional level. By analyzing the assortativity pattern and global rich-club coefficient, we illustrate that the IRIO network exhibits a hierarchical organization, where significant provincial-sector nodes are interconnected and form dense rich clubs, extending from a few structural cores to peripheral regions. Additionally, we identify distinct connectivity patterns of non-rich nodes based on their incoming and outgoing relations. The insights gained from this study have implications for the macro-control of regional development.

In this article, we analyze the relationships that connect graduates from high school, the training system and employment rates and conditions in the Italian regions between 2004 and 2022. The data used refer to the Istat Bes database. The results show that the growth in the number of high school graduates is positively associated with higher university education and employment with the exception of job satisfaction. Subsequently we also present a clusterization with k-Means algorithm confronting the Silhouette Coefficient with the Elbow Method. Finally, we confront seven different machine-learning algorithms for the prediction of the level of graduated from high school. We also present economic policy suggestions to increase schooling in the Italian regions. The results are critically discussed.

[Introduction]: In the contemporary international financial environment, marked by intricate complexities and increasing uncertainties, the impact of exchange rate fluctuations on national economies has become increasingly significant. In this context, this study uses the Chinese economy as a case study to delve deeply into the interaction effects between macroprudential and monetary policies, analyzing how these policies jointly address economic instability. The aim is to offer new perspectives and strategies for stabilizing the global economic and financial landscape. [Methods]: This paper constructs an open-economy Dynamic Stochastic General Equilibrium (DSGE) model specifically tailored for China, incorporating Bayesian estimation and numerical simulation techniques. The study meticulously examines how macroprudential and monetary policies can be coordinated to achieve economic stability in response to exchange rate shocks. [Results]: The research finds that (1) targeted coordination of macroprudential and monetary policies towards asset prices and price levels can maintain stability under exchange rate shocks; (2) the effective implementation of such coordinated policies not only mitigates the fluctuations in asset prices due to exchange rate shocks but also enhances the level of societal welfare; (3) in terms of choosing an exchange rate regime, a managed floating rate system can prevent policy overlaps and conflicts that might occur in a floating rate system during the coordination of macroprudential and monetary policies, thus offering comparative advantages. [Discussion]: The findings underscore the importance of policy integration in a dynamic and complex global economic environment. They provide policy recommendations for China and other emerging market countries on how to effectively maintain economic stability through the synergistic interplay of macroprudential and monetary policies amid fluctuations in exchange rates and asset prices.

In this paper, the ratio of gross agricultural production (GAP) and agricultural carbon emission is defined as agricultural carbon emission efficiency (ACEE). Considering rural labor transfer (RLT) increases the agricultural machinery intensity (AMI), the two are substitutes for each other and may interact with agricultural carbon emission efficiency (ACEE), we constructed a Simultaneous Equations Model (SEM) of ACEE, RLT and AMI, and analyzed the interaction mechanism of these three variables by using the Three-Stage Least Squares (3SLS) method to solve the endogeneity of the model. The following conclusions are drawn. First, RLT and AMI significantly promote the improvement of ACEE, while the improvement of ACEE and AMI further promotes RLT. Secondly, the causal relationship and influence mechanism of ACEE, RLT and AMI are interactive and multi-directional. An increase in AMI promotes ACEE, but an increase in ACEE inhibits an increase in AMI, suggesting that the marginal rate of substitution of machinery for labor is decreasing. Finally, China has significant regional heterogeneity. Labor transfer and machinery are only direct factors in increasing ACEE, while factors such as economic base, technology level and farmers' attitudes provide environmental support for the effective improvement of ACEE.

This study aims to broaden the current understanding of the antecedents and consequences of green purchase intention within the realm of perceived green value (PGV) A mixed-method approach is deployed, integrating PLS-SEM and Necessary Condition Analysis (NCA) to examine the role of influence and interaction as key precursors to perceived responsibility and perceived self-efficacy, and explores how perceived responsibility and perceived self-efficacy impacts green purchasing intention, mainly through the mediation of perceived responsibility (PER) and perceived self-efficacy (PSE) using survey data gathered from consumers participating. The results indicate that PGV positively influences green purchase intention (GPI). Moreover, PER and PSE exhibit significant chain mediation effects, with the mediation effect of perceived environmental responsibility being particularly strong. It is recommended that the government intensify green disseminate and education, promote the establishment of certification and evaluation systems for electric vehicle products, and that electric vehicle factories emphasize the environmental attributes and economic interest of their products to encourage green purchasing behavior.

Credit rationing, especially prevalent for smaller firms, impedes economic growth. A Central Bank aligned “not for profit” managed business to business “Stable-Coin” (“Synthetic Central Bank Digital Currency”) providing trade debt liquidity can lower small firm credit rationing. It raises growth by reducing monetary transmission imperfections consequent upon asymmetric information, commercial bank underwriting restrictions, market power dynamics and regulatory distortion. A simple framework is developed to contextualise small firm credit rationing and associated monetary transmission imperfections with broader credit flows into both the real and monetary sectors. Evidence is presented regarding US monetary transmission efficacy to firms, paving the way to proposing a trade debt business to business focused stable-coin to help close credit rationing gaps. Designed to minimise “moral hazard”, the proposed stable-coin provides an additional monetary transmission channel that supplies interest free trade debt funding to firms to support economic activity and raise growth. In addition to helping close the small firm financing gap, the stable-coin provides policy makers with an additional contra-cyclical monetary transmission instrument to minimise real economic disruption consequent upon financial system crises and liquidity events.

One of the factors in the mobility of a nation's economy is the stock exchange which plays a decisive role in sustainable economic development. Accordingly, and for the special place of the stock exchange in the economy, we decided to investigate the relationship between the interest and exchange rates and the Tehran stock exchange dividend and price index (TEDPIX). Using the autoregressive distributed lag method, the present study is conducted utilizing the annual data over the period of 1991 to 2020. The results indicate that the exchange rate has a positive long-run relationship with the TEDPIX, but no statistically significant relationship was found between the TEDPIX and the interest rate. Furthermore, the results of the estimation of the error correction model show that 30.786% of the disequilibrium in each period is adjusted to the long-run equilibrium.

The research investigates the factors affecting the financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia and their impact on the country’s economic growth. The research methods of the studies involve data collection through surveys or interviews, followed by statistical analysis. The study found that entrepreneurial qualities such as motivation, entrepreneurial orientation, and risk behavior positively influence the financial performance of MSMEs. MSMEs that manage working capital optimally tend to increase profitability and growth, despite operational difficulties like worker shortages. MSMEs engaged in foreign trade usually achieve higher profitability. Bank loans can enhance profitability and sales, but the collateral requirement may hinder growth. The owner’s involvement doesn’t affect growth but can enhance profitability. Factors like the Human Capital Index, interest rates, the Indonesian Rupiah exchange rate, and inflation do not significantly impact MSME investment. However, business units, labor, investment, and exports of MSMEs significantly influence Indonesia’s economic growth. MSMEs play a crucial role in job creation, rural development, economic diversification, and GDP contribution in Indonesia. Despite challenges, they have the potential for sustainable growth. The research also explores strategies for overcoming challenges faced by MSMEs and investigates the role of universities in supporting the MSME sector. The University of Indonesia (UI) supports the MSME sector through strategic initiatives, including education, training, mentoring, and internship programs. The research provides valuable insights into the operation of MSMEs in Indonesia and their contribution to the economy, highlighting areas for further exploration and potential strategies for supporting the growth and sustainability of these enterprises.

To meet the dual-carbon objective, China's economy needs to move from a carbon-intensive to a green economy. Green technology innovation and renewable energy development are key to promoting green economic growth. The study uses 2010–2022 provincial panel data from 30 Chinese provinces. The super-efficient SBM model measures the province's green economic growth index. A panel fixed-effects model is used to experimentally evaluate how green technology innovation and renewable energy development affect green economic growth. Green financing moderates and a panel threshold model tests the threshold effect of renewable energy development on green economic growth. The results demonstrate that (1) China's green economic growth is rising and has a "U" shape. (2) all selected variables significantly impact green economic growth. However, population density, government intervention, and industrial structure are inversely associated with GEG. Green economic growth is significantly boosted by the moderate role of green finance in the development of renewable energy and green technological innovation. (3) Renewable energy development has a single threshold non-linear effect on green economic growth, depending on its development level and green technological innovation. Considering China's current condition and research findings, this study examines the green energy transition to promote green economic growth and high-quality economic development. Meanwhile, puts forward some important policy recommendations.

This study assesses the impact of militarization, industrialization, technological innovation, and energy consumption on CO2 emissions in NATO countries, divided into "traditional" (Group 1) and "new member" states (Group 2), using data from 1985 to 2019. It identifies heterogeneity in effects and dependencies between the groups. Employing Pedroni and Kao panel cointegration tests, a long-term equilibrium relationship among the variables is confirmed. The analysis, using panel ARDL and GMM methods, reveals distinct outcomes for each group. In Group 1, military spending and energy consumption significantly increase CO2 emissions, while industrialization and technological innovation reduce them. Conversely, in Group 2, technological innovation and energy consumption raise emissions, whereas military spending and industrialization decrease them. The findings suggest Group 1 should strategize military expenditure and energy consumption to cut emissions, whereas Group 2 should focus on eco-friendly technology and efficient energy use to achieve environmental sustainability.

The study assessed the risk perception, attitude, and management tools of 260 randomly selected farmers and processors in the rice value chain using data elicited via a structured questionnaire. Descriptive statistics, Equally Likely Certainty Equivalent (ELCE) technique, Binary logistic regression, and a 5-point Likert scale were employed in the data analyses. Descriptive statistics show that the respondents are young, active, and in their productive age with an intermediate education level. Majority of the farmers and processors were risk averse. Risk aversion was common among farmers and processors. Farmers' risk attitudes and perceptions of risk are significantly influenced by a number of factors, including age, access to extension services, farm size, marital status, household size, education, income, training, and experience. Majority of rice farmers consider price risk as the most important risk while majority of processors perceive production risk as the most important risk. Pests and diseases, price fluctuation, drought, and lack of input were the most important source of risk to farmers, while processors perceived price fluctuation, technology adoption, and poor storage facilities as the most important source of risk. Off-farm investment, spraying for pests and diseases, cash contribution, market information, and cooperative were the important risk mitigating management strategies employed by the farmers/processors. The study suggests improvements in the identified risk sources, which could influence the attitude and perception of the farmers and processors.

The Southern European countries of Spain and Portugal both show a high degree of export spe-cialization in agri-food products compared to the EU-27 as a whole. This sector plays a funda-mental role in their economies, determining the management of natural resources, with the food and beverage industry being the most important manufacturing activity in both countries. Drawing on evidence obtained from Eurostat's database on foreign trade, this study analyzes whether the geographical concentration of agri-food exports from the Iberian Peninsula coun-tries to the EU-27 increases between 2008 and 2022, or, conversely, if there is a process of spatial diversification in favor of non-EU markets. Expansion towards new trading partners, as indicat-ed by estimated concentration indices, is significant in Spain but does not occur in Portugal. However, in both economies, the regional market with European partners, characterized by strong competition and low development expectations, remains decisive in the evolution of their exports in the short and medium term. Consequently, institutions and companies in this sector must adopt a more dynamic approach and implement measures that allow for increased sales orientation towards higher growth markets, thus enhancing the global competitiveness of the national agri-food sector.

Preserving and passing on folk traditions and gastronomic culture to the next generations was an important task of the older age group in every historical era. The most important objective of this study is to reveal people's attitudes regarding to the values of gastronomy and culture in a West Hungarian county. The combined presence of the Szigetköz Nature Park and the World Heritage sites (Fertő-Hanság National Park, Pannonhalma Abbey) in the offer requires re-sponsible, environmentally, socially and economically sustainable tourism planning. In the framework of a quantitative research (questionnaire survey), the tourists’ knowledge of gas-tronomy values and also their knowledge regarding to the architectural, cultural and natural attractions will be analysed. Four hypotheses were formulated in the study. The data collec-tion took place between September 1. 2023 and October 30. 2023 (N=666). The sample is not representative, the respondents were selected arbitrarily and randomly. The most important novelty of the study is that in contrast to previous studies, in this study, tourists' visits to different destinations were measured, while previous studies focused on tourists' interests.

Trade liberalization is commonly pursued to improve welfare of households in a country. However, the effects of liberalization are not evenly distributed. Certain households and sectors may benefit more than others. This study focuses on the East African Community Common External Tariff (EAC-CET), to analyze the distributional effects of trade liberalization in Kenya. The study utilizes two household budget surveys capturing pre- and post-trade liberalization scenarios. The paper examines changes in consumer prices, labor incomes, and consumption patterns to assess the effects of liberalization. A pass-through equation for prices and a negative compensation variation equation are estimated. The findings indicate that the EAC-CET had a significant pass-through effect on prices of manufactured goods, but incomplete pass-through for agricultural goods. This suggests a lack of competitiveness in domestic value chains. The distributional effects differ across worker categories, favoring skilled and formal workers over unskilled and informal workers. The income effect outweighs the negative expenditure effect for households in the middle- and upper-income deciles. However, the study reveals negative welfare effects for the poorest households in the lowest income deciles. Furthermore, the study identifies the EAC-CET to be pro-poor, with households in rural areas benefiting more than those in urban areas.

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from ten major Saudi banks, the research examines how different components of intellectual capital—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—influence key financial performance indicators such as Return on Equity (ROE) and Net Profit Margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effects models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size, financial leverage, GDP growth, inflation, and the impact of the COVID-19 pandemic. The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia's Vision 2030. The study's insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development.

It has been empirically observed that the upper tail of the firm size distribution follows either the Pareto distribution or the Zipf distribution, with both patterns being explained by Gibrat’s law (Gabaix, 1999). This article analyzed firm revenue data from China, spanning from 2005 to 2013, to examine the whole range of the firm size distribution. Our empirical analysis revealed that firm revenue data over these years is well fitted by a three-parameter generalized Pareto distribution, with the fitted parameters indicating a dichotomy: The size distribution of large-sized firms, namely the upper tail, is asymptotically characterized by a Pareto distribution or a Zipf distribution, whereas the size distribution of smaller and medium-sized firms is approximated by an exponential distribution. This finding suggests that Gibrat’s law should be extended to account for the emergence of a generalized Pareto distribution.

For this research we are selected three indicators of wheat: yield (t/ha), producer price (USD/t) and share of the harvested area under wheat in relation to the total land area of country (%). The mentioned indicators were analyzed for the period 2006-2021 in thirty-two European countries. The purpose of the research is to determine which of the mentioned indicators achieve average annual growth/decrease rates, what is the correlation between them, how European countries are grouped with their similarities and differences. The research examines the impact of the COVID-19 pandemic on the mentioned indicators in a two time phases: Phase I, before the pandemic (2006-2019); Phase II, during the pandemic (2020-2021). The methodological approach to the research topic involved the application of descriptive statistics, as the method of principal components analysis (abbr. PCA) with graphics. A positive correlation exists only between the yield of wheat and the share of the harvested area under wheat in the total area of the land (0.291). PCA method showed that countries are grouped differently depending on the observed indicator and the analyzed time phase.

As a result of increased energy consumption, global trade has surged, and serious environmental problems have arisen. The problem is made more complicated by the fact that either environmental damage or economic advancement cannot be compromised. The elements contributing to environmental contamination must be identified and dealt with accordingly if we are to have a healthier future. In this study, what causes CO₂ emissions in Malaysia are examined using the Autoregressive distributed lag (ARDL) model using time series data from 1995 to 2020. The paper also examines the impact of energy use and economic complexity on CO2 emissions. Firstly, it is noted that the Environmental Kuznets Curve (EKC) theory holds in Malaysia. Furthermore, energy consumption has a detrimental impact on reducing CO2 emissions. Furthermore, it has been noted that a greater degree of economic complexity leads to an elevated amount of CO2 emissions over an extended period. The findings suggest significant environmental policy implications for reducing CO2 emissions in Malaysia.

The sustainable development of resource-based cities has long been a focal point for both governmental policies and academic research. A wealth of academic literature identifies the 'resource curse' as a critical barrier to sustainable development in these urban areas. Despite extensive studies, a consensus on effective strategies to circumvent or resolve this challenge remains elusive. Recent empirical data reveals a noticeable pattern of economic growth differentiation in China's resource-based cities. Why do some resource-based cities experience economic decline while others achieve sustainable economic growth? Therefore, this paper analyzes the reasons for the divergence of economic growth in resource cities from the perspective of heterogeneity. The results of the study show that the phenomenon of the resource curse is conditional, and the heterogeneity of demo-graphic changes, geographic location and institutional environment has a significant impact on the economic growth of resource cities. These factors are investigated to elucidate the observed diversification and heterogeneity in the economic growth of resource-based cities. Building upon this analysis, the paper proposes a framework for differentiated sustainable development pathways tailored to the unique contexts of these cities. This approach not only contributes to the current understanding of the 'resource curse' but also offers novel insights for future research aiming to adopt a more nuanced and context-specific perspective in examining sustainable urban development.

The impact of the agriculture net carbon effect is crucial for climate change mitigation, yet research on this topic in China is currently insufficient. In this study, the carbon balance ratio (CBR) is used to characterise the net carbon effect of agriculture, and the spatial Durbin model and threshold regression model were used to empirically analyse the CBR with a sample of 30 provincial-level regions in China from 2004 to 2019. The aim was to investigate the mechanism of the influence of the land management scale (SCALE) of farming on the CBR. The results of the study indicate that national farming generally has a net sink effect, with large changes in interannual fluctuations; the expansion of SCALE has an obvious role in increasing sinks and reducing emissions, and has a positive spatial spillover effect on CBR, with significant spatial heterogeneity. Furthermore, as the SCALE expands, the direction of the influence of rural residents’ income and education level on CBR changes in the opposite direction, showing a significant non-linear relationship characteristic. However, in most areas, the SCALE threshold has not yet been reached, suggesting that the improvement in education levels can still offset the negative impact of economic income growth in the short term. The study recommends paying attention to the role of farmers’ human capital, changing production methods, and implementing carbon peaking and carbon neutrality goals to enhance the net sink effect of the farming industry, which would be achieved by increasing land management scale.

Local food has continued to become more popular in both the home and as featured ingredients in all segments of food service. Numerous studies have explored the motivating factors for consumer purchasing motivators. However, no known study has explored if there is a correlation between ego and intent to buy local foods. This study adopted a modified version of the Theory of Trying and surveyed a sample of 237 food service buying agents in South Carolina to examine their perceptions of buying local. Results suggest that ego is a predictor of trying to purchase local foods for restaurants. It was also found that the modified model is an acceptable model for predicting buyer intent. These findings support the majority of the studies looking at ego-centric behaviors with green purchases and could potentially help local food suppliers to better market their products to foodservice establishments. This study could also act as the foundation for future studies to explore the full extent of ego’s motivational effect on purchasing intentions in the food service industry.

The study is dedicated to analyzing the complex interaction between Artificial Intelligence (AI) and the Internet of Things (IoT) with institutional structures in the context of sustainable development. This work examines the impact of these technologies on economic and social development, identifying their potential advantages and risks. Methodologically, the research relies on information gathering and case study analysis, assessing the impact of technology in various domains, from smart cities to the manufacturing sector. The findings emphasize the necessity of integrating technological innovations into broader social and environmental initiatives, highlighting the importance of institutional transformations for achieving environmental sustainability.

Inclusive and sustainable development has become an important part of China's sustainable development agenda, the self-recovery and stability of China's economy cannot be achieved without the macro-governance of the government. Figuring out the internal logic of digital finance and economic resilience is an important part of effective government governance. Based on the panel data of 193 counties in five provinces in northwest China from 2014 to 2021, the paper tested digital finance and county-level economic resilience by using two-way fixed-effect model, intermediary-effect model and threshold-effect model, to test whether financial development promotes government governance in underdeveloped regions. The results prove that digital inclusive finance significantly enhances the resilience of county economies by improving capital allocation efficiency, stimulating entrepreneurship and employment, and reducing pollution emissions. In addition, there are dual threshold effects between capital allocation efficiency and employment vitality, in which capital allocation efficiency has a gradually increasing threshold effect, and entrepreneurship and employment vitality have a fluctuating increasing threshold effect. Therefore, "Digital inclusive finance" in underdeveloped regions is an indispensable part of financial globalization；promoting the healthy development of digital finance is the basis and premise for providing a good financial environment for government management; deepening the reform in the financial field and promoting the green and sustainable development of finance are the future trend and direction of efforts.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

In the following article I analyze the determinants of regular internet users in the Italian regions. The data is analyzed both in terms of static analysis and also through the application of the k-Means algorithm optimized with the Elbow method. Subsequently, an econometric model is presented for estimating regular internet users in the Italian regions based on variables that reflect the state of technological innovation and digital culture. The results are analyzed and discussed in light of the implications that digitalisation has for triggering economic growth.

in the following article I analyze the trend of cultural and creative employment in the Italian regions between 2004 and 2022 through the use of ISTAT-BES data. After presenting a static analysis, I also present the results of the clustering analysis aimed at identifying groupings between Italian regions. Subsequently, an econometric model is proposed for estimating the value of cultural and creative employment in the Italian regions. Finally, I compare various machine learning models for predicting the value of cultural and creative employment. The results are critically discussed through an economic policy analysis.

This study investigates the impacts of climate change policies on businesses across various sectors, aiming to understand how these regulations affect operational, financial, and strategic aspects of business management. Utilizing a mixed-methods approach, data was collected from 500 businesses through surveys and interviews, encompassing a wide range of industries, sizes, and geographic locations. The findings reveal a complex landscape where 30% of businesses report positive impacts, primarily in the renewable energy and technology sectors, citing increased demand for green products and improvements in energy efficiency. Conversely, 45% of businesses, especially from manufacturing and agriculture, experience negative impacts, including increased operational costs and regulatory compliance challenges. Notwithstanding, a significant majority of businesses are committed to enhancing their sustainability practices, viewing climate change policies as an opportunity for innovation and long-term growth. The study highlights the nuanced effects of climate change policies, emphasizing the need for sector-specific support measures to alleviate financial and operational burdens on negatively impacted businesses. Moreover, it points to a broader shift towards sustainability within the business community, suggesting that climate policies, despite their varied impacts, are driving significant changes in business strategies towards environmental stewardship.

Partially state-owned firms are common in both developed and developing countries and contribute around 10% of the world's GDP. This has led to a rich literature exploring various aspects of competition between such “mixed”-ownership firms. This paper contributes to the existing literature by studying the effects of mixed ownership on the intensity of competition in oligopoly markets. Our findings indicate that state ownership exerts an anti-competitive influence, with a higher state ownership share resulting in less aggressive behavior by firms in the product market. This result implies that industries with a higher proportion of state ownership yield lower total surplus. Further, when considering factors such as taxes, soft budget constraints, and weak property rights, the anti-competitive effects of state ownership are accentuated.

This study examines the complex relation among environmental taxes, productive capacities, urbanization, and their collective effects on environmental quality in Africa, drawing on two decades of data from twenty African countries. It situates the study within the broader discourse on sustainable development and economic growth, emphasizing the Environmental Kuznets Curve (EKC) framework to examine the relationship between economic development, characterized by urban expansion and increased productive capacities, and the adoption of environmental taxes amidst the continent’s diverse economic and environmental environments. Using advanced econometric techniques, including the Cross-Section Augmented Autoregressive Distributed Lag (CS-ARDL) model and the Dynamic Common Correlated Effects Mean Group (DCCEMG) estimator, the study addresses data challenges such as cross-sectional dependence and slope heterogeneity. The results provide important insights into the dynamics of environmental quality in relation to economic and urban growth and the role of environmental taxation. The study proposes tailored policy strategies aimed at strengthening sustainable development initiatives in line with international agreements such as the Paris Agreement and the Sustainable Development Goals. These strategies advocate for a nuanced application of environmental taxes and the promotion of productive capacities to enhance environmental sustainability across the African continent.

In the following article I take into consideration the role of knowledge workers in the Italian regions. The analysed data refers to the ISTAT-BES database. The metric analysis consists of an in-depth analysis of the trends of the regions and macro-regions, followed by clustering with the k-Means algorithm, the application of machine learning algorithms for prediction, and the presentation of an econometric model with panel methods date. The results are also critically discussed in light of the North-South divide and the economic policy implications.