This study examines how economic freedom and competition affect bank stability. We use data from 70 ASEAN-4 banks from 2007 to 2019 using the system generalized technique of moments. Results corroborate competition-fragility hypothesis. Market strength (or less competition) can boost bank stability. However, in the ASEAN-4 area, competition and bank stability have a non-linear relationship, suggesting that bank stability may decline after market strength exceeds a threshold. Financial and economic freedom also boosts bank stability. This implies banks in free financial and economic contexts are more stable. Banks with more market dominance in nations with more economic or financial autonomy may also be more unstable. The findings suggest that authorities should allow some competition and economic flexibility to keep banks stable. The study examined ASEAN-4 economic freedom’s effects empirically for the first time. It illuminates competitiveness and bank stability.

Environmental, social and governance (ESG) goes beyond its function as a business to maximize profits for the shareholders to work for societal purposes. Meanwhile, the green credit policy in China is still in its infancy, and the impact of green loans on the efficiency of commercial banks is significantly different. In this context, this paper details the company’s performance in crucial aspects such as low-carbon operations, eco-friendly financial innovation, a sustainable economic system, data security and the development of organizational capabilities to provide a sustainable development paradigm for supply chain finance technology peers. Based on ESG portfolio, we found that adding ESG holdings to a company affects its compliance with delivery or environmental rules, and anode and cathode of ESG combined Dual Carbon (DC) are presented in terms of emission levels. Our further research indicates the implementation of Green Credit Guideline has a positive impact on ESG performance of both green and polluting firms in comparison with others. The result was fully supported by different methods and models including PSM-DID (Propensity Score Matching-Differences-in-Differences), QDID (Quantiles Differences-in-Differences), and Kernel approaches, which can provide more implications and references for policy makers. Investors, politicians, and other essential stakeholders perceive ESG as a strategy to protect enterprises from future risks.

In recent years, environmental, social and governance (ESG) issues have emerged as a significant area of focus for companies. Furthermore, the international trend is reinforced by the emergence of relevant regulations and the obligation to prepare sustainability reports in leading economies and in the European Union. The impact of ESG and its constituent elements (environmental, social, and governance) on financial performance has been the subject of extensive investigation, with the majority of studies documenting a positive correlation. This evidence substantiates the assertion that sustainability initiatives can yield financial benefits. Concurrently, research has accorded much less attention to the impact of ESG performance on brand value, which can be identified as an indicator of consumer perception. This study, based on data from 26 global corporations between 2012 and 2021, demonstrates that efforts in the areas of environmental and social responsibility have a positive impact on consumer perception, which translates into increased brand value. Nevertheless, such a relationship was not found in case of the governance component.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

The present study attempted to assess the impact of fundamental ratios on the share prices of selected telecommunication companies in India. India has dramatically expanded over the past ten years to become the second-biggest telecoms market worldwide, with 1.17 billion users. The Indian telecom industry has proliferated thanks in part to the government of India’s liberal and reformist policies and strong customer demand. It has become a lucrative investment sector for investors due to its recent and prospective growth. Data on 13 telecom firms indexed in the S&P BSE telecommunication index from 2013 to 2022 were taken from companies’ annual reports, the BSE website (Bombay Stock Exchange), and other secondary sources. Six firm-specific fundamental factors viz. Debt to Equity ratio (D/E), Current ratio (CR), Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to earnings ratio (P/E), Return on equity (ROE), and three country-specific fundamental factors viz. Gross Domestic Product, Inflation rate, and S&P BSE Sensex return were considered. Fixed effect panel regression through Generalized Least Square (GLS) model was performed to find inferences. Debt Equity ratio and Inflation rate were found to impact share price negatively. Conversely, the Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to Earnings ratio (P/E), and Return on Equity (ROE) positively impacted selected companies’ share prices. The study results will benefit individual & institutional investors in formulating their investment and portfolio diversification strategies for gaining a high effective rate of return on their investments.

This study aims to evaluate the influence of population dependency ratio on the economic growth of Bangladesh, India, and Pakistan, the three members of the South Asian Association for Regional Cooperation (SAARC). The study covers the time from 1960 to 2021. It also analyses in detail how population aging and the youth dependency ratio affects the development of certain sectors, including industry, services and agriculture. This study uses panel data to determine the influence of population dependency ratios on economic growth. To estimate this effect, we use the Pooled Mean Group/Autoregressive Distributed Lag (PMG/ARDL) technique. Based on the results obtained from the ARDL analysis indicate the presence of a long-term relationship among these variables. These discoveries align with prior empirical research conducted by Lee and Shin, Mamun et al., and Rostiana and Rodesbi. Furthermore, the findings suggest that an increase in the old age population dependency ratio positively influences economic growth within these nations. The long-term relationship findings pertaining to the old and young dependency ratio and economic growth corroborate the conclusions of Bawazir et al., who proposed that the old population dependency ratio exerts a favorable impact, while the young population has an adverse effect on economic growth. Originality: This research focused on the population dependency ratio, a pivotal demographic metric that gauges the proportion of individuals relying on support (including children and the elderly) compared to those of working age. This investigation particularly explores the interconnection between the population dependency ratio and sectoral development, an essential aspect given that various sectors make distinct contributions to economic advancement. Examining how population dynamics affect sectoral development yields valuable insights into the overall economic performance of Pakistan, India, and Bangladesh.