The purpose of this study is to analyze how the entrepreneurial mindset, social context, and entrepreneurial ambitions of university students in the United Arab Emirates (UAE) have progressed over time in terms of starting their businesses. The research aims to investigate the evolution of the entrepreneurship mindset, considering the implementation of educational and governmental policies over the past decade to promote entrepreneurship among UAE university graduates. To collect primary data and evaluate the impact of the studied variables on the dependent variable “entrepreneurial ambitions,” a self-created questionnaire was used. The results reveal a positive correlation between personal context variables and entrepreneurial ambitions, as well as between personality traits and entrepreneurial ambitions. Furthermore, the study demonstrates the constructive effect of education, government policies, and capital availability on fostering entrepreneurial ambitions in the UAE.

The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.

The purpose of the study was to examine the role of personalization in motivating senior citizens to use AI driven fitness apps. Vroom’s expectancy theory of motivation was applied to examine the motivation of senior citizens. The responses from participants were collected through structured interviews. The participants belonged to South Asian origin belonging to India, Bangladesh, Nepal and Bhutan. The authors adopted a content analysis approach where the gathered interview responses were coded in the context of elements of Vroom’s theory. The findings of the study indicated that a highly personalized approach in the context of motivation, expectancy, instrumentality and valence will motivate senior citizens to use AI based fitness apps. The study contributes to the personalization of AI fitness apps for senior citizens.

Background: People who are financially literate are able to make sound decisions regarding their money since they have a firm grasp of the fundamentals of money and financial products. The significance of financial literacy has been acknowledged by numerous nations, prompting the formation of task teams to assess their populations and develop educational and outreach programs. The requirement to make educated decisions about ever-increasing financial goods necessitates a higher level of financial literacy. Aim: Being able to make sense of one’s personal financial situation is becoming an increasingly valuable skill in today’s world. One of the most essential components for making sure and successful decisions is having a good grip on one’s financial status. By contrast, financial literacy refers to an individual’s level of knowledge and awareness regarding financial matters, whereas investors’ decision-making is characterised by their understanding, prediction, investigation, and assessment of the various stages and transactions involved in making an investment decision. Risk, a decision-making framework and process, and investing itself are all components of investing. Method: Researchers will conduct a cross-sectional survey of Saudi Arabian investors. We used a structured questionnaire to gather data. Using “Cronbach’s a and confirmatory factors” analysis, we checked whether the data is reliable. The links between financial literacy and investment decisions was demonstrated using structural equation modeling (SEM) in IBM-SPSS and SmartPLS. Purpose: The purpose of this research is to look at how the investment choices of Saudi Arabians are correlated with their degree of financial literacy. Consequently, research on the connection between financial literacy, knowledge, behaviour, and investment choices is lacking. Researchers on this subject have already acknowledged the problem’s importance and intended to devote substantial time and energy to solving it. Findings: The study concluded that there was a significant relationship between financial literacy and financial knowledge with respect of investment decision of investors. Similarly, there was a significant relationship between financial behaviour and financial knowledge with respect of investment decision of investors. The discovery of the outcomes will enable regulatory authorities to aid investors in preventing financial losses by furnishing them with sufficient financial information.

The Indonesian government is currently carrying out massive infrastructure development, with a budget exceeding 10. Risk mapping based on good risk management is crucial for stakeholders in organizing construction projects. Projects financed by government, whether solicited or unsolicited schemes, should also include risk mapping to add value and foster partnerships. Therefore, this study aimed to develop a risk management model for solicited and unsolicited projects, focusing on the collaborative management system among stakeholders in government-financed projects. Risk review was conducted from various stakeholders’ perspectives, examining the impacts and potential losses to manage uncertainty and reduce losses for relevant parties. Furthermore, qualitative analysis was conducted using Focus Group Discussion (FGD) and in-depth interviews. The results showed that partnering-based risk management with risk sharing in solicited and unsolicited projects had similarities with Integrated Project Delivery (IPD). This approach provided benefits and value by developing various innovations in the project life cycle.