As prominent oil producers, Gulf Cooperation Council (GCC) countries have played a significant role in the global energy market. However, as the world’s attention increasingly shifts towards environmental sustainability, understanding the implications of the GCC’s economic activities on CO2 emissions becomes indispensable. This research paper investigates the relationship between specific economic indicators and their impact on CO2 emissions in the GCC from 2001 to 2021. This study employs quantile regression, a robust statistical method that estimates the conditional quantiles of a response variable given a set of predictor variables. The findings reveal several essential insights: Financial institution efficiency is significant and negative at a 1% level at the lower (10th, −83,537.3) and higher quantiles (90th, −549,002.3). The relationship between the GDP per capita and CO2 emissions varies across quantiles, highlighting the complexity of the growth–environment nexus. Total patents exhibit a positive and significant relationship with emissions, underscoring the importance of directing innovation towards environmentally sustainable solutions. Renewable energy consumption displays a nuanced relationship with CO2 emissions, with a more substantial negative impact observed at higher consumption levels. This underscores the potential of renewable energy to mitigate emissions when integrated at scale. This study’s outcomes hold crucial policy implications for GCC countries as they seek to align economic growth with environmental sustainability. The findings emphasize the importance of fostering financial institution efficiency, promoting green innovation, and expanding renewable energy sources to reduce emissions.

Adopting a circular economy (CE) can play a role in achieving economic sustainability for all countries. Material and production waste must be recycled to make better use of limited resources. Developments in the CE need to transition linear economies into circular ones. Although the CE has a role in reaching economic sustainability, few studies have investigated the effect of transitioning to a CE in emerging economies. Thus, it is critical to examine the effect of circular economic influences on economic growth. This paper analyses particular indicators of the CE in the Gulf Cooperation Council (GCC) countries. The analysis employs econometric techniques such as unit root tests, random-effect models, and the autoregressive distributed lag (ARDL) model to examine different components, including environmental, social, and economic. Panel data are used to determine the dependency of circular economic factors on economic growth in GCC countries. The data was collected from the World Bank database covering the years 2000 to 2020. The paper is based on the analysis of the CE filed in GCC countries and intends to contribute to the studies in the field. The results gained from the GCC situation are valuable for both emerging and developing countries looking to include sustainable development measures in their policies and regulations. The findings highlight the importance of the CE to sustainability within GCC countries. This investigation of CE indicators based on the results of the economic model contributes to the empirical literature on the transition to a CE in emerging and developing countries.

Purpose: The aim of this study is to evaluate how remote work affects workers’ productivity in the Saudi financial sector. It tries to analyze the interrelation of workers’ productivity when working remotely with job satisfaction and work management. Moreover, the paper tries to shed light and reflect widely on the cons and pros of remote work. Theoretical Framework: Remote work is one of the digital transformation consequences, it is a new form of work that allows workers to work away from the employer’s primary workplace. The framework of the study is adopted from the association of workers productivity with (1) working remotely, (2) job satisfaction and (3) remote work management. This framework aims to provide the magnitude of these three variables on the productivity of workers in the Saudi financial sector. Research Methodology: Primary data collected by conducting a survey, which covers a sample consisting of 1270 respondents from banks, financial, and insurance companies in Saudi Arabia. Secondary data is obtained from previous scientific studies, official reports issued by the Saudi Central Bank (SAMA), and other related international institutions. Findings: The Results of the descriptive and inferential analysis showed that there is a positive effect and association of workers’ productivity by job satisfaction, remote work, and work management during working remotely. As workers in the financial sector feel satisfied with their job due to remote work, their productivity increases. Analysis of remote work advantages revealed that remote work raises the sense of responsibility of staff, promoting self-censorship. Moreover, remote work contributes to balance in work and life, serenity, and enhances the psychological and physical comfort of the employee, consequently, it increases workers’ productivity. While physical isolation, lack of communication between co-workers, and low levels of learning due to limited direct contact between colleagues and clients can also challenge building social relationships at work and negatively affect the workers ‘productivity. Research, Practical & Social implications: This study can be generalized and undertaken to improve the application of remote work as a new pattern of work in the financial sector, benefiting from its advantages and tackling its drawbacks. Moreover, design work strategies and restructure the work policies to include the remote work beside the traditional presentism work. In addition to introduce new management system compatible for remote work and specialized training programs, ensuring efficient communication to enhance employee productivity. Originality/value: This study addresses an important contemporary issue in the field of work and productivity, remote work. It is a pioneer empirical study which focused on the linkage between remote work and workers productivity in the Saudi financial sector. It presents comprehensive conceptional framework and literature review and provides empirical results and policy implications for decision makers in the Saudi financial sector and related sectors.

As prominent oil producers, the Gulf Cooperation Council (GCC) countries have played a significant role in the global energy market. However, as the world's attention increasingly shifts towards environmental sustainability, understanding the implications of the GCC's economic activities on CO2 emissions becomes indispensable. This research paper investigates the relationship between specific economic indicators and their impact on CO2 emissions in the GCC from 2001 to 2021. The study employs quantile regression, a powerful statistical method that estimates the conditional quantiles of a response variable given a set of predictor variables. The findings reveal several important insights: Financial institution efficiency is significant and negative at a 1% level at the lower (10th) -83537.3 and the higher quantile (90th) -549002.3. The relationship between GDP per capita and CO2 emissions varies across quantiles, highlighting the complexity of the growth-environment nexus. Total patents exhibit a positive and significant relationship with emissions, underscoring the importance of directing innovation towards environmentally sustainable solutions. Renewable energy consumption displays a nuanced relationship with CO2 emissions, with a stronger negative impact observed at higher consumption levels. This underscores the potential of renewable energy to mitigate emissions when integrated at scale. The study's outcomes hold crucial policy implications for the GCC countries as they seek to align economic growth with environmental sustainability. The findings emphasize the importance of fostering financial institution efficiency, promoting green innovation, and expanding renewable energy sources to reduce emissions

This research analyses the heterogeneous effects of digital infrastructure on sustainable economic growth in five developing countries (Egypt, India, Kenya, Saudi Arabia and Sudan) using the period 2014-2025. We use panel fixed effects with Driscoll-Kraay standard errors to investigate the effect of internet penetration, mobile broadband and fixed broadband on the GDP per capita growth. Our results suggest that digital infrastructure has a statistically and economically significant impact on economic growth. Internet penetration yields the largest benefits, followed by mobile broadband, whereas fixed broadband is not statistically significant in the full model, which is reflective of limited access in these countries. An exploratory Random Forest analysis with the important caveat of limited sample size suggests that internet penetration is the most important predictor of growth, followed by mobile broadband and human capital. However, these machine learning results should be considered exploratory given the small sample (N=60, or N=48 when excluding Sudan) and should not be over-interpreted. Our heterogeneity analysis finds that internet penetration drives growth in middle-income countries (Egypt, India), while mobile broadband drives growth in low-income countries (Sudan, Kenya). The moderation by human capital is large: the marginal impact of internet penetration more than doubles once average education exceeds six years. However, we note that this threshold is illustrative, based on the distribution of the sample and not necessarily a policy cutoff. The results have implications for SDG 4 (quality education), SDG 9 (infrastructure and innovation) and SDG 10 (inequality reduction). However, with our purposively selected five-country sample, these results are better considered as case-based evidence rather than statistically representative of all developing economies. The stark digital divide is evident in the 87% internet penetration in MENA countries compared to 44% in Sub-Saharan Africa and underscores the need for context-specific policy approaches. We suggest that low-income countries focus on expanding mobile broadband and middle-income countries make complementary investments in internet infrastructure and human capital, but emphasize that these policy suggestions are indicative rather than conclusive.

This study examines whether annual changes in national innovation performance are associated, within the same year, with changes in or levels of five selected indicators aligned with the sustainable development pillars of People, Planet, Prosperity, Partnership, and Peace, and whether these indicator-level associations differ between developed and emerging economies. The analysis uses a balanced panel of 20 countries from 2014 to 2024 and applies two-way fixed-effects models with country and year fixed effects and country-clustered robust standard errors. Each pillar is operationalized using one observable indicator; consequently, the analysis provides an indicator-based assessment rather than a comprehensive measurement of the Five Ps. The baseline results provide no evidence of systematic contemporaneous associations, as the change in the Global Innovation Index is statistically insignificant across all five models. The one-year-lagged change in innovation is also statistically insignificant in all five specifications, indicating that the central finding remains unchanged after allowing for a short delay. The interaction analysis identifies a significant difference between developed and emerging economies for the indicator aligned with People, although the total association for emerging economies remains statistically insignificant. A weakly significant group difference is found for Partnership, while no significant differences are identified for Prosperity, Planet, or Peace. The demographic and macroeconomic control variables are associated with some of the selected outcomes. Overall, annual changes in aggregate national innovation performance are not systematically associated with contemporaneous or one-year-delayed movements in the selected outcomes. These findings represent conditional associations rather than causal effects.