Urban planning is critical to managing rapid urban growth, particularly in African regions experiencing high urbanization rates. This study focuses on Bol, Lake Chad Province, a city facing significant challenges due to inadequate planning frameworks compounded by recurrent humanitarian and climate crises. It fills an empirical gap by analyzing how local planning mechanisms respond to these socio-environmental complexities, with a focus on the interplay between institutional structures, legislative frameworks, and resource allocation. The study assesses urban planning practices in Bol to identify challenges and opportunities, with the aim of improving institutional effectiveness, aligning policies with realities, and integrating climate resilience strategies. Using a qualitative methodology, it combines field surveys, stakeholder interviews, and document analysis, using SWOT (Strengths, Weaknesses, Opportunities, Threats) and PESTEL (Political, Economic, Sociocultural, Technological, Environmental, Legal) frameworks for data analysis. The findings reveal that ineffective institutions, poor inter-sectoral coordination, outdated legislative frameworks and resource constraints hamper sustainable urban development in Bol. To address these issues, the study proposes to strengthen local institutional capacities, foster stakeholder collaboration, and modernize urban planning policies through participatory approaches. The study highlights the need to integrate resilience strategies into urban settings to mitigate climate change impacts and improve governance. These measures not only address immediate challenges, but also advance urban planning theory and provide a basis for future research on adaptation strategies in crisis-prone regions. This study offers practical insights for policy makers and contributes to developing more sustainable and resilient urban planning systems in similar contexts.

This research addresses environmental, ethical, and health concerns related to high meat consumption, and aims to identify key predictors that encourage a shift towards sustainable diets among young adults. A cross-sectional survey involving 340 students from ten Malaysian universities was conducted using a structured questionnaire. The findings indicate that attitudes, subjective norms, perceived behavioral control, and personal norms significantly predict the intention to adopt plant-based diets. These results have practical implications, suggesting that policymakers, educators, and health professionals should create supportive environments and educational programs that emphasize the benefits of plant-based diets and equip students with the necessary knowledge and skills. Theoretically, the study reinforces the TPB framework’s applicability in understanding dietary behaviors and underscores the importance of personal and social factors in shaping dietary intentions. Ultimately, promoting plant-based diets among university students necessitates a comprehensive approach and strategy addressing attitudes, social norms, perceived control, and personal values. By leveraging these insights, stakeholders can foster sustainable and healthy eating practices among young adults, contributing to broader environmental and public health objectives for sustainable development.

Electricity consumption in Europe has risen significantly in recent years, with households being the largest consumers of final electricity. Managing and reducing residential power consumption is critical for achieving efficient and sustainable energy management, conserving financial resources, and mitigating environmental effects. Many studies have used statistical models such as linear, multinomial, ridge, polynomial, and LASSO regression to examine and understand the determinants of residential energy consumption. However, these models are limited to capturing only direct effects among the determinants of household energy consumption. This study addresses these limitations by applying a path analysis model that captures the direct and indirect effects. Numerical and theoretical comparisons that demonstrate its advantages and efficiency are also given. The results show that Sub-metering components associated with specific uses, like cooking or water heating, have significant indirect impacts on global intensity through active power and that the voltage affects negatively the global power (active and reactive) due to the physical and behavioral mechanisms. Our findings provide an in-depth understanding of household electricity power consumption. This will improve forecasting and enable real-time energy management tools, extending to the design of precise energy efficiency policies to achieve SDG 7’s objectives.

The importance of tourism to nations’ socioeconomic development cannot be overemphasised as it has proven to be a significant source of revenue for many countries globally. However, sub-Saharan nations like Nigeria have not tapped into the unlimited potential of tourism in their development drive, hence the continuous grappling with underdevelopment challenges. This study examines how tourism impacts socioeconomic growth in Nigeria, focusing on well-known tourist destinations in Lagos State, Nigeria. The study adopts quantitative and qualitative mixed-method research using survey questionnaires and in-depth interviews to elicit responses from visitors at the tourist centres and the tourists’ operations. Data were analysed using simple percentages of frequency distribution tables and thematic analysis. The Neo-liberal theory was adopted as a theoretical framework for the study. The findings highlight the need for better infrastructure, security measures, destination awareness, better housing, financial help, the development of a competent workforce, solid governmental policies, the conservation of cultural and natural assets, and encouragement of collaboration. Future studies may focus primarily on three areas: the evaluation of tourism’s economic impacts, the effectiveness of specific tourist development programs, and the role of tourism in community empowerment.

Artificial intelligence (AI) has rapidly evolved, transforming industries and addressing societal challenges across sectors such as healthcare and education. This study provides a state-of-the-art overview of AI research up to 2023 through a bibliometric analysis of the 50 most influential papers, identified using Scopus citation metrics. The selected works, averaging 74 citations each, encompass original research, reviews, and editorials, demonstrating a diversity of impactful contributions. Over 300 contributing authors and significant international collaboration highlight AI’s global and multidisciplinary nature. Our analysis reveals that research is concentrated in core journals, as described by Bradford’s Law, with leading contributions from institutions in the United States, China, Canada, the United Kingdom, and Australia. Trends in authorship underscore the growing role of generative AI systems in advancing knowledge dissemination. The findings illustrate AI’s transformative potential in practical applications, such as enabling early disease detection and precision medicine in healthcare and fostering adaptive learning systems and accessibility in education. By examining the dynamics of collaboration, geographic productivity, and institutional influence, this study sheds light on the innovation drivers shaping the AI field. The results emphasize the need for responsible AI development to maximize societal benefits and mitigate risks. This research provides an evidence-based understanding of AI’s progress and sets the stage for future advancements. It aims to inform stakeholders and contribute to the ongoing scientific discourse, offering insights into AI’s impact at a time of unprecedented global interest and investment.

This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that South Africa’s Human Resource Management (HRM) landscape, marked by a combination of approaches, provides an opportunity to cultivate alternative methods attuned to contextual conditions in the global South. Consequently, adopting AI in recruiting, retaining, and managing a diverse workforce demands a critical examination of the colonial/apartheid past, integrating contemporary realities to explore the potential infusion of contextually relevant AI innovations in managing South Africa’s workforce.