The Public-Private Partnerships management model (PPP) in Portugal was initially applied to the highways sector. Recently, this model began to spread to the health sector for hospital management. The recent growth of patient’s knowledge and expectations regarding the quality of healthcare services is compelling service providers to pursue new ways of delivering this care to meet users’ expectations. One wonders if the increase in patient access to knowledge may indicate a growth in health literacy, particularly regarding PPP Hospitals. This study assesses the Portuguese population’s literacy level regarding the PPP Hospital model, using a quantitative research approach based on a survey of the Portuguese population served by PPP hospitals and a Public Hospital Management (PHM) model. It was found that the Portuguese population has a low literacy concerning the PPP model, which can cause feelings of injustice. It was found that PPP users tend to have a favourable opinion regarding private involvement since they are also more satisfied compared to PMH users. These results may impact political decision-making concerning the renewal of new contracts for private management of public services.

This study provides empirical data on the impact of generative AI in education, with special emphasis on sustainable development goals (SDGs). By conducting a thorough analysis of the relationship between generative AI technologies and educational outcomes, this research fills a critical gap in the literature. The insights offered are valuable for policymakers seeking to leverage new educational technologies to support sustainable development. Using Smart-PLS4, five hypotheses derived from the research questions were tested based on data collected from an E-Questionnaire distributed to academic faculty members and education managers. Of the 311 valid responses, the measurement model assessment confirmed the validity and reliability of the data, while the structural model assessment validated the hypotheses. The study’s findings reveal that New Approaches to Learning Outcome Assessment (NALOA) significantly contribute to achieving SDGs, with a path coefficient of 0.477 (p < 0.001). Similarly, the Use of Generative AI Technologies (UGAIT) has a notable positive impact on SDGs, with a value of 0.221 (p < 0.001). A Paradigm Shift in Education and Educational Process Organization (PSEPQ) also demonstrates a significant, though smaller, effect on SDGs with a coefficient of 0.142 (p = 0.008). However, the Opportunities and Risks of Generative AI in Education (ORGIE) study did not find statistically significant evidence of an impact on SDGs (p = 0.390). These findings highlight the potential opportunities and challenges of using generative AI technologies in education and underscore their key role in advancing sustainable development goals. The study also offers a strategic roadmap for educational institutions, particularly in Oman to harness AI technology in support of sustainable development objectives.

This study examined the factors influencing online purchases among consumers in Bangladesh, employing a modified version of the Technology Acceptance Model (TAM). Data from 353 individuals in Bangladesh revealed that perceived ease of use, social influence, security, convenience, trust, emotional experience, and functional experience significantly positively affect the intention to purchase online. Additionally, results show that the intention to purchase online significantly positively affects actual online purchases. Findings further highlighted that intention to make online purchases mediated the influence of perceived ease of use, social influence, security, convenience, trust, emotional experience, and functional experience over online purchases. The study provides significant practical recommendations to help businesses and consumers support online purchasing with diverse advantages.

This study aims to identify factors related to the impact of social capital on happiness among multicultural families using the 2019 Community Health Survey, which represents the South Korean population. The study utilized data from the 2019 Korea Community Health Survey, and the study participants, aged 20 years or older, included 3524 members of multicultural families from a total of 229,099 adult households. The study found a significant difference in happiness scores across different age groups (t = 57.00, p < 0.01). Based on the median value of happiness, significant relationships were found with the independent variables: Physical Environment of Trust (t = −5.13, p < 0.001), Social Networks (t = −5.51, p < 0.001), and Social Participation (t = −5.47, p < 0.001). Happiness was found to have a positive correlation with the Physical Environment of Trust (r = 0.12, p < .001), Social Participation (r = 0.11, p < 0.001), and Social Network (r = 0.13, p ≤ 0.001). In contrast, Age (r = −0.13, p ≤ 0.001) and Stress (r = −0.14, p ≤ 0.001) showed negative correlations with happiness (r = 0.57, p < 0.001). The analysis identified a positive community physical environment (t = 3.85, p < 0.01), increased social networks (t = 4.27, p < 0.01), and higher social participation (t = 6.88, p < 0.01) as significant predictors of happiness. This model suggests that the explanation power is 15%, which is statistically significant (R² = 0.15, F = 57.72, p < 0.001). This study highlights the influence of social capital on the happiness of multicultural families living in Korea. Given the increasing number of multicultural families in the country, strategic interventions aimed at enhancing social networks and participation are necessary to promote their happiness.

This study assesses Vietnam’s state-level implementation of artificial intelligence (AI) technology and analyses the government’s efforts to encourage AI implementation by focusing on the National Strategy on AI Development Program. This study emphasizes the possibility of implementing AI at the state level in Vietnam and the importance of conducting continuous reviews and enhancements to achieve sustainable and inclusive AI growth. Impact evaluations were conducted in public organizations alone, and implication evaluations were considered optional. AI impact assessments were constrained by societal norms that necessitated establishing relationships among findings. There is a lack of official information regarding the positive impact of Vietnam’s AI policy on the development of AI infrastructure, research, and talent pools. The study’s findings highlight the necessity of facilitating extensive AI legislation, and strengthening international cooperation. The study concludes with the following recommendations for improving Vietnam’s AI policy: implementing a strong AI governance structure and supporting AI education and awareness.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.