Consumers waste significant amounts of food. Food waste presents a substantial problem for the environment, society and economy. Addressing the food waste challenge is crucial for fostering sustainable behavior and achieving the Sustainability Development Goal 12.3 agenda. Norms are a significant determinant in motivating consumers to prevent food waste and could be activated by other factors. Religiosity has the potential to influence norms related to food waste behavior. This study investigated how religiosity affects the intentions of consumers to minimize food waste. The interplay of religiosity, personal norms, subjective norms, and intention to avoid food waste was examined by the extended norm activation model. Data were obtained from Muslim consumers in Indonesia. Structural equation modeling evaluation showed that religiosity positively affects the intention to prevent food waste. The intention to avoid food waste is more closely associated with personal norms compared to subjective norms. Personal norms mediate the religiosity and food waste reduction intention relationship. Consumer awareness activates personal norms by making them feel accountable for food waste’s negative impact. These findings provide insights to stakeholders in developing policies to mitigate the food waste issue.

The aim of this research is to determine the incidence of socioeconomic variables in migration flows from the main countries of origin that form part of the international South-North migration corridor, such as Mexico, China, India, and the Philippines, during the 1990–2022 period. The independent variables considered are GDP per capita, unemployment, poverty, higher education, and public health, while the dependent variable is migration flows. An econometric panel data model is implemented. The tests conducted indicate that all variables have an integration order of I (1) and exhibit long-term equilibrium. The econometric models used, Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS), reveal that unemployment and poverty had the strongest influence on migration flows. In both models, within this international migration corridor, GDP per capita, higher education, and health follow in order of importance.

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.

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.