This study investigates the complex interrelationship between democracy, corruption, and economic growth in Greece over the period 2012–2022. Using data from Transparency International, the Economist Intelligence Unit, and Eurostat, appropriate methods such as Ordinary Least Squares (OLS) regression, Generalized Method of Moments(GMM) estimation, and Granger causality tests were applied. The findings reveal that increased democracy correlates positively with reported corruption, likely reflecting heightened transparency and exposure. Conversely, economic growth shows a negative association with corruption, underlining the role of structural reforms and institutional improvements. These insights emphasize the need for strengthening democratic institutions, promoting digital governance, and implementing targeted economic reforms to reduce corruption and foster sustainable development.

Urbanization plays a crucial role in facilitating the integration of population growth, industrial development, economic expansion, and energy consumption. In this paper, we aim to examine the relationships between CO2 emissions and various factors including economic growth, urbanization, financial development, and energy consumption within Pakistan’s building sector. The study utilizes annual data spanning from 1990 to 2020. To analyze the cointegration relationship between these variables, we employ the quantile autoregressive distributed lag error correction model (QARDL-ECM). The findings of this research provide evidence supporting the presence of an asymmetric and nonlinear long-term relationship between the variables under investigation. Based on these results, we suggest the implementation of tariffs on nonrenewable energy sources and the formulation of policies that promote sustainable energy practices. By doing so, policymakers and architects can effectively contribute to minimising environmental damage. Overall, this study offers valuable insights that can assist policymakers and architects in making informed decisions to mitigate environmental harm while fostering sustainable development.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.

This study provides an empirical examination of the design and modification of China’s urban social security programme. In doing so, this study complements the popular assumption regarding the correlation between economic growth and social security development. Focusing on the economic and political motivations behind the ruling party’s decision to implement social security, this study first discusses the modification of urban social security and welfare in China. It then empirically demonstrates the mechanisms behind the system’s operation. This study proposes the following hypothesis: in a country like China, a change in the doctrine of the ruling party will affect government alliances, negating the positive impact of economic growth on the development of social security. In demonstrating this hypothesis, this study identifies a political precondition impacting the explanatory power of popular conceptions of social security development.

Working Capital Management (hereafter WCM) is the strategic tool that helps a company navigate through challenging economic growth, and influence its competitive performance. Thus, this study examines the impact of WCM on the competitiveness of firms operating in the non-financial sectors in Pakistan. We use the Generalized Method of Moments (GMM) technique to ensure the robustness of our results. The study findings reveal that both a large net trade cycle and surplus working capital have a substantial negative impact on firms’ competitiveness within their respective industries. These results suggest that companies should streamline their investments in working capital accounts and concentrate more resources on long-term projects that maximize value to improve their competitiveness compared to other companies. Therefore, firms that are effectively managing their short-term financial affairs are experiencing much better performance in all aspects of firm performance. The research findings highlight the urgent need for governmental initiatives designed to improve WCM practices in these industries. It is imperative for the management of  companies with excess net working capital to maximize their working capital efficiency, aligning it with industry standards to enhance competitiveness. Moreover, policymakers should prioritize easing access to financial alternatives that allow enterprises to maintain an efficient working capital structure without relying on excessive measures. Furthermore, policymakers should be cautious when determining minimum cash balance requirements in a cash-strapped economy where external financing is relatively more expensive than in other regional economies.

This study aims to compare investment in human capital, equality of gender education in Kuwait before and after adopting SDG 4 and SDG 5 in 2015. It also aims to assess the effect of women’s empowerment on economic growth. To achieve this objective, published data on the State of Kuwait were collected from the World Bank DataBank between 1992 and 2022 and from the Central Bank of Kuwait. The study employed autoregressive distributed lag (ARDL) to determine the impact of women’s empowerment on economic development. The analysis results revealed that the State of Kuwait provided high-quality education for both genders. The results also showed that women are more educated than men. However, this was not reflected in the role of women in the country’s politics, as their participation in parliament and government is still limited. Similarly, women’s participation in business and economic activities is still limited. Finally, the results of the ARDL test showed that women’s education and their political, business, and economic empowerment affect economic development in the short and long run.