The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

Electrical energy is known as an essential part of our day-to-day lives. Renewable energy resources can be regenerated through the natural method within a reasonably short time and can be used to bridge the gap in extended power outages. Achieving more renewable energy (RE) than the low levels typically found in today’s energy supply network will entail continuous additional integration efforts into the future. This study examined the impacts of integrating renewable energy on the power quality of transmission networks. This work considered majorly two prominent renewable technologies (solar photovoltaic and wind energy). To examine the effects, IEEE 9-bus (a transmission network) was used. The transmission network and renewable sources (solar photovoltaic and wind energy technologies) were modelled with MATLAB/SIMULINK^®. The Newton-Raphson iteration method of solution was employed for the solution of the load flow owing to its fast convergence and simplicity. The effects of its integration on the quality of the power supply, especially the voltage profile and harmonic content, were determined. It was discovered that the optimal location, where the voltage profile is improved and harmonic distortion is minimal, was at Bus 8 for the wind energy and then Bus 5 for the solar photovoltaic source.

As a key factor in the macroeconomic process, the interaction between public confidence and the commodity market, especially its impact on commodity facilitation returns and macroeconomic linkages, is worth exploring in depth. This study adopts the TVP-SV-VAR model to analyze the causal linkages, dynamic characteristics, and mechanisms of the interaction, and reveals the following core findings: (1) The economic background and information shocks contribute to the variations in the effects and orientations of the economic variables, which highlight the time-varying nature of the economic interactions. (2) Consumer and investor confidence exert heterogeneous influence on the macroeconomy, and their different responses to the negative effect of interest rates and convenience gains are particularly significant in the post-crisis recovery period. (3) In the short-term perspective, the influence of public confidence on monetary policy and inflation exceeds that in the medium and long term, highlighting the immediate sensitivity of individual economic behavior. (4) Since 2015, accommodative monetary policy has accelerated market capital flows, delaying the interaction between confidence indices and inflation, revealing policy time lag effects. (5) Convenience gains exhibit complex time-varying interactions with key economic parameters (interest rates, commodity prices, and inflation), with 2011 and 2014 displaying particular patterns, mapping differences between short- and long-term mechanisms, respectively. The study highlights the central role of consumer and investor confidence in the precise tailoring of macroeconomic policies, providing a scientific basis for policy forecasting and economic regulation, and contributing to economic stability. Meanwhile, the dynamic evolution of consumer confidence deepens market trend foresight, enhances the precision of market participants’ decision-making, and reinforces the resilience and predictability of economic operations.

The increasing use of social media has played a prominent role in shaping opinions and forming attitudes, especially among university students. They use them increasingly to transfer information, exchange data, and disseminate topics among students and all members of society. Therefore, this study aims to examine these networks and their role in public life, especially in shaping public opinion among university students. The study adopted a descriptive survey approach to achieve its objectives. The study was conducted on a sample of undergraduate students from four Jordanian universities, totaling 832 participants selected through purposive sampling and using the equal distribution method according to variables (gender, university, specialization). The study relied on a questionnaire as a method of data collection and filling out the data from the respondents in the questionnaire. The study found that social media plays a significant role in shaping opinions, beliefs, and ideas, and that its role is unparalleled. Also, the study showed that social media had a significant impact on shaping public opinion in Jordan among university students who use social media extensively and exchange opinions, ideas, and information, contributing to shaping a series of opinions among young people and contributing to their adoption of new ideas or changing their old ones through the dialogue facilitated by these networks, as users exchange and adopt ideas, contributing to shaping a public opinion on an issue. These findings underscore the importance of understanding and leveraging social media and online platforms to effectively communicate with and engage students.

The endogenous, human, and social factors influencing the economic development of the municipalities of San Juan Cotzocón and San Pedro y San Pablo Ayutla in the Istmo de Tehuantepec region of the state of Oaxaca are analyzed. The hypothesis posits that the dimensions of endogenous development, social capital, and human capital directly impact the economic development of the respective municipalities. The study involved administering 262 questionnaires to the residents of these municipalities during the month of May 2023. The collected data were examined using exploratory factor analysis to determine the underlying structure and structural equation modeling to estimate the effects and relationships between variables. Results indicate that endogenous development, social capital, and human capital are factors in the economic development of the studied communities, with endogenous development being the most influential factor due to its statistical significance. Notably, the existence of tourist and cultural attractions in the municipalities emerges as a catalyst for local economic development in response to the establishment and operation of the Isthmus of Tehuantepec Interoceanic Corridor.