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The purpose of this paper is to explore a new grey relational analysis model to measure the coupling relationship between the indicators for the water environment status assessment. Meanwhile, the model deals with the problem that the changing of indicator order may result in the changing of the degree of grey relation.

The binary index submatrix of the sample matrix is given first. Then the product of the matrix and its own transpose is used to measure the characteristics of the index and the coupling relationship between the indicators. Thirdly, the grey relational coefficient is defined based on the matrix norm, and a grey coupling relational analysis model is proposed.

The paper provides a novel grey relational analysis model based on the norm of matrix. The properties, normalization, symmetry, relational order invariance to the multiplicative, are studied. The paper also shows that the model performs very well on the water environment status assessment in the eight cities along the Yangtze River.

The model in this paper has supplemented and improved the grey relational analysis theory for panel data.

This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic conditions and varying levels of ICT specialists.

The research employs a dynamic panel data model using the System Generalized Method of Moments (GMM) to analyze the relationship between brain drain and government AI readiness from 2018 to 2022. The study incorporates various control variables such as GDP per capita growth, government expenditure growth, employed ICT specialists and several governance indicators.

The results indicate that brain drain negatively affects government AI readiness. Additionally, the presence of ICT specialists, robust governance structures and positive macroeconomic indicators such as GDP per capita growth and government expenditure growth positively influence AI readiness.

Major limitations include the focus on a specific region of countries and the relatively short period analyzed. Future research could extend the analysis with more comprehensive datasets and consider additional variables that might influence AI readiness, such as the integration of AI with emerging quantum computing technologies and the impact of governance reforms and international collaborations on AI readiness.

The theoretical value of this study lies in providing a nuanced understanding of how brain drain impacts government AI readiness, emphasizing the critical roles of skilled human capital, effective governance and macroeconomic factors in enhancing AI capabilities, thereby filling a significant gap in the existing literature.

This research fills a significant gap in the existing literature by providing a comprehensive analysis of the interaction between brain drain and government AI readiness. It uses control variables such as ICT specialists, governance structures and macroeconomic factors within the context of the European Union. It offers novel insights for policymakers to enhance AI readiness through targeted interventions addressing brain drain and fostering a supportive environment for AI innovation.

Energy affects all areas of daily life. Especially with the industrial revolution, the fact that manufacturing has become the engine of economic growth has led to a rise in energy consumption. In this process, the countries of the world have increased their economic growth with traditional energy consumption, and this has increased carbon emissions. However, to fulfill the sustainable development goals, both the continuation of economic growth and the reduction of carbon emissions are required. In this context, the substitution of renewable energy consumption in place of traditional energy sources has started to be discussed. The aim of this study is to research the relationships among CO₂ emissions, manufacturing growth, and renewable energy consumption. For this aim, the relationship among carbon emissions, manufacturing growth, and renewable energy consumption is analyzed for the period 1997–2019 in 38 Organisation for Economic Co-operation and Development (OECD) countries. With respect to the findings of autoregressive distributed lag (ARDL) test results, manufacturing growth enhances CO₂ emissions both in the short and long terms. As the proportion of renewable energy consumption in total energy consumption rises, CO₂ emissions decrease both in the short and long terms. On the other hand, according to the Dumitrescu–Hurlin causality test results, there is a one-way causality relationship from carbon emissions to manufacturing growth and from renewable energy consumption to carbon emissions. When the findings are evaluated together, it is understood that renewable energy consumption is a substantial factor in tackling the deadlock of lessening the carbon emissions without adversely impacting manufacturing growth. Therefore, policymakers need to encourage renewable energy consumption.

This paper examines the extent to which exchange rate volatility (ERV) is crucial for small island economies. These economies by their very nature and size tend to be net importers and highly dependent on trade for their economic survival. The island of Mauritius is used as a case study.

A GARCH model has been utilized using yearly data for the period 1993–2022. The ARDL bounds cointegration approach has been used to determine the long run relationship between exchange rate volatility and the performance of exports. The ECM-ARDL model has been used to estimate the short-run relationships, that is the speed of adjustments between the variables under consideration.

The findings reveal that exchange rate volatility has a positive and significant effect on exports in the short run as well as in the long run. The study also finds out that export has a long-term relationship with world GDP per capita. Both the presence and degree of exchange rate volatility are important aspects for consideration in policy making.

The literature gap that this study attempts to close is one related to global impacts within the recent time horizon. Recently, numerous important events shaped the financial and economic landscape globally, including but not limited to the financial crisis of 2008 and the COVID-19 pandemic in 2019. Both these events stressed the global volume of trade and the exchange rate markets, and these events affects small islands comparatively more given their heavy dependence on international trade for economic development, albeit economic survival.

We test the pertinence of the unemployment invariance hypothesis (UIH) for a set of Organisation for Economic Co-operation and Development countries.

We empirically investigate the nexus between unemployment and labour force participation employing structural vector autoregressive methods for panel data.

We find that shocks in unemployment produce long-lasting, negative effects on participation, testifying to a discouraged worker effect.

Our results do not support the validity of the UIH in high-income economies. This has relevant implications for policy making and macroeconomic models.

The study aims to find out the impact of financial inclusion and financial development on financial stability using panel data from eight countries in the Middle East and North Africa (MENA).

To achieve the aim of the study, the researcher prepared two indicators of financial inclusion and governance to find out the impact of financial development on the relationship between financial inclusion and financial stability. Data on financial inclusion was obtained from the International Monetary Fund, data on financial development and financial stability were obtained from the World Bank.

The results of the fixed and random effect methods show that financial inclusion has a significant positive effect on financial stability. Additionally, financial development represents a moderating variable in the significant positive effect on the relationship between financial inclusion and stability in the MENA countries.

The current study suffers from some limitations that researchers must be aware of in future research. First, there is an inability to determine qualitative aspects such as time and cost when designing a composite indicator of financial inclusion. Second, due to limited data, we used only eight countries from the MENA. It is suggested to expand the sample to include other countries.

This paper contributes to the related literature between financial inclusion and financial stability by confirming or denying the results of previous studies. Also, to the best of the author’s knowledge, this paper is the only one that explains the role of financial development in the relationship between financial inclusion and stability in MENA countries, using a composite index to calculate financial inclusion. Finally, the study seeks to focus the attention of the government and policymakers to build a system of financial inclusion that leads to improving financial stability.

Corporate leadership and environmental, social and governance (ESG) performance are closely intertwined, as effective corporate leadership can facilitate the achievement of strong ESG performance. Thus, the purpose of the study is to investigate the impact of corporate board leadership on the ESG performance of listed firms.

The sample has been taken from the listed firms of the Nifty 500 index spanning the period of 10 years from 2012 to 2022. Dynamic panel data estimations are applied through a fixed effect model.

The findings of this study revealed that board size, board independence and board qualification have a significant positive influence on ESG performance. It is evident that good corporate governance practices can positively influence ESG performance by fostering accountability, transparency and ethical behavior, as well as better integrating ESG considerations into their decision-making processes and ensuring that ESG issues are prioritized at the highest levels of management. Further findings also revealed that chief executive officer (CEO) duality has a significant negative relationship with ESG performance, which goes against the belief of stakeholder theory.

It has practical implications for policymakers, as they can enact new regulations pertaining to the CEO’s position in the organizations to make corporate governance responsible for improved sustainability and ESG performance.

There are very few studies analyzing the impact of corporate board structure on ESG performance related to emerging markets. Thus, this study contributes to that literature by using the methodology GMM panel data for the first time as per our knowledge

This paper aims to examine the connection between digital payments, ownership structure, and bank performance in Jordan, as well as investigate the moderating role of the independent director in the said relationship.

The study uses data from 12 Amman stock exchange-listed commercial banks, covering the period from 2010 to 2023. This paper employs econometric analysis of panel data, including ordinary least squares (OLS) regression as the primary approach, as well as the generalised method of moments, the two-stage least square (2SLS), and the dynamic model to deal with causality and endogeneity issues in the proposed equations. This ensures that the results are valid.

The results indicate that digital payments and ownership structure have a significant positive connection with bank performance. Additionally, the independent director variable appears to play a substantial and positive moderating role in the link between ownership structure (e.g. institutional ownership) and bank performance. These results strengthen and support the claims of agency theory and the information systems success model.

Overall, this research helps stakeholders, bankers, managers, investors, customers, and policymakers, identify the influence of digital payment and ownership structure on bank performance in developing economies such as that of Jordan.

This investigation offers a unique understanding by illuminating how digital payment and ownership structure affect bank performance in a developing country such as Jordan. Additionally, it opens avenues for future research to delve into this literature domain in North African and Middle Eastern nations, with a particular focus on Jordan. This investigation is among the initial explorations in Jordan that aim to elucidate these relationships. On the theoretical level, it adds to the agency theory and IS model. It provides new insights into the dynamics of industry banking in developing nations (i.e. Jordan).

This study aims to investigate the institutional, macroeconomic and firm-specific determinants of financial leverage in Vietnam and provides new evidence from the dynamic panel fractional estimator.

This study uses a panel dataset of 859 Vietnamese firms from 2008 to 2022 and employs three estimators: Feasible Generalized Least Squares (FGLS), System Generalized Method of Moments (SysGMM) and Dynamic Panel Fractional (DPF), with DPF being particularly suitable for handling fractional dependent variables and the dynamic nature of financial leverage.

The results confirm the dynamic nature of the financial leverage model, with firm-specific factors, institutional factors and macroeconomic factors playing significant roles in shaping firms' financing decisions. The DPF estimator highlights the positive impact of stock market development on leverage. This study contributes to the literature by providing new evidence on the determinants of leverage in Vietnam, using the DPF estimator for more accurate estimation and revealing the significant impact of the size of the banking sector, the size of the stock market, the stock market development index, the financial development index and the corruption perception index on leverage.

This study contributes to the literature by providing new evidence on the dynamic nature of the financial leverage model and the impact of institutional, macroeconomic and firm-specific factors on financial leverage in the context of Vietnam. The use of the DPF estimator allows for a more accurate and reliable estimation of the determinants of leverage, considering the fractional nature of the dependent variable and the persistence of capital structure decisions over time.

This study investigates the impact of international remittances on the economic growth of remittance-receiving countries, using data from 113 developing countries between 1990 and 2015.

The authors used a novel approach to address the potential endogeneity of remittances. The authors estimated bilateral remittances and use them to create weighted indicators of remittance-sending countries, which the authors then use as instruments for remittance inflows to remittance-receiving countries.

The results indicate that while remittances have a positive impact on economic growth in developing countries with high human capital, they do not contribute to growth in developing countries with low human capital. The authors also examined the channels through which remittances affect growth. The findings suggested that remittances do not impact labor supply in developing countries with high human capital, but they reduce labor supply in countries with low human capital. Additionally, remittances increase investment in physical capital in developing countries with high human capital, but they do not have an effect on investment in developing countries with low human capital.

The authors investigated the impact of remittances on economic growth using a novel approach to address the endogeneity of remittances. Additionally, the authors examined the different indirect channels through which remittances can impact economic growth, such as their effect on labor supply and investment.