The Human Development Index, which accounts for both net foreign income and the total value of goods and services generated domestically, illustrates how income becomes less significant as Gross National Income (GNI) rises by using the logarithm of income. South Africa ranks 109th out of 189 countries in the Human Development Index (HDI) within the Brazil, Russia, India, China and South Africa (BRICS) economic bloc, raising long-term sustainability concerns. The study explores the relationship between economic, demography, policy indicators and human development in South Africa. South Africa’s unique status as a developing country within the BRICS economic group, alongside its lengthy history of racial discrimination, calls for a sophisticated approach to understanding Human Development. Existing research considered economic, demography, policy indicators independently; the gap of understanding their interconnection and long-term effects in the South African contexts exists. The study addresses the gap by using Autoregressive-Distributed Lag (ARDL) approach to investigate the short-term and the long-term relationship between economic, demography, policy indicators and human development in South Africa. By discovering these links, the study hopes to provide useful insights for policymakers seeking to promote sustainable human development in South Africa. The findings indicate that growth in GDP is a key factor in the HDI since it shows that there are more financial resources available for human development. By discovering these links, the study hopes to provide useful insights for policymakers seeking to promote sustainable human development in South Africa.

Despite the efforts of public institutions and government spending, progress on the SDGs is mixed at the midpoint of the 2030 timeframe-some targets are off track and some have even regressed. ICT-related indicators, on the other hand, stand out for their strong progress. The author notes this progress, but questions its relationship to the implementation of the 2030 Agenda. He argues that the growth in internet and mobile network penetration is due to the economic characteristics of communications development. The objectives of the article are to review the impact of the ICT sector on economic growth, to consider the role of government spending in the development of this sector in the context of fostering the achievement of the Sustainable Development Goals, and to identify the prerequisites for significant progress towards SDG targets in communications. Achievement of these objectives will make it possible to determine whether this progress is a consequence of targeted efforts to achieve the SDGs, or whether, in accordance with the author’s hypothesis, it is based on the specifics of the ICT sector’s development, allowing for the accelerated spread of mobile communications and the Internet, which is reflected in the SDG indicators.

Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.

This study aims to scrutinize specific long-term sustainability industrial indicators in Thailand as a representative of an emerging economy. The study uses a Bloomberg database comprising all Thai listed companies on the Stock Exchange of Thailand from 2013 to 2023. The research employs a two-step Generalized Method of Moments (GMM) statistics to assess the enduring impact on industrial sustainability. These results provide consistent, significant and positive relationships between asset turnover and sales with all industrial sustainability. The results additionally reveal that some other factors may moderate industrial sustainability but reveal the GDP growth rate and institutional shareholders are less likely to be corporate sustainability to all indicators. The results provide insight into valuable guidance to management teams, financial statements’ users, investors and other stakeholders on designing effective operations and investment strategies to improve sustainability.

Social Services are vital for addressing adversity and safeguarding vulnerable individuals, presenting professionals with complex challenges that demand resilience, recovery, and continual learning. This study investigates Organizational Resilience within Community Social Services, focusing on strategic planning, adaptive capacity, and user perspectives. A cross-sectional study involved 534 professionals and service users from Community Social Services Centers in Spain. Centers were selected based on the characteristics of their population and the representativeness of their geographic location. The study utilized the Benchmark Resilience Tool (BRT) to evaluate Organizational Resilience and the SERVPERF questionnaire to gauge user-perceived service quality. The results demonstrate satisfactory levels of Organizational Resilience and user satisfaction, while also highlighting key areas for enhancing resilient strategies: reinforcement of personnel for thinking outside the box or in the resources available to the organization to face unexpected changes. These findings suggest the need to develop and optimize measures that improve the organization’s ability to adapt to and recover from adverse situations, ensuring a positive user experience. Emphasizing the importance of resilience in Social Services as a quality predictor, future research should explore innovative strategies to bolster Organizational Resilience. The findings emphasize the need to strengthen resilience in Social Services, enhancing practice, policy, and adaptability to support vulnerable populations.

This research explores the intricate relationship between digitalization, economic development, and non-cash payments in the ASEAN-7 countries over a ten-year period from 2011 to 2020. Focusing on factors such as commercial bank branches, broad money, and inflation, the study employs panel data regression analysis to investigate their impact on automated teller machine (ATM) usage. The findings reveal that commercial bank branches significantly influence ATM usage, emphasizing the role of accessibility, services, and technological preferences. Broad money also shows a significant impact on ATM transactions, reflecting the interplay between fund availability and non-cash transactions. However, inflation does not exhibit a direct influence on ATM usage. The research underscores the importance of maintaining service quality and security in the banking sector to enhance digital financial inclusion. Future research opportunities include exploring diverse non-cash payment methods and extending studies to countries with significant global economic impacts. This research contributes valuable insights to policymakers aiming to enhance digital financial inclusion policies, ultimately fostering economic growth through the digital economy in the ASEAN-7 region.