The prospects of digital infrastructure in promoting rural economic growth and development are by and large immense. The paper found that rural development is considerably important for economic development and for achievement of sustainable livelihoods that increases people’s ability to achieve good health and wellbeing that enable the achievement of sustainable development. The paper found that digital imbalance and digital illiteracy in the rural areas hinder implementation of digital infrastructure to lead to rural economic growth. Digital infrastructure is the source of economic opportunities that enables local people in the rural areas to be more creative in achieving development success. It enables them to have a unique sense of place and fashioning of vibrant economic and financial opportunities that ensure the achievement of sustainable rural economic development. However, the paper found that the application of digital infrastructure to South Africa’s rural areas in the bid to promote rural economic growth has been hindered by factors like the digital divide, financial constraints, digital illiteracy and the failure to own a smart phone. These factors hinder digital infrastructure from leading to sustainable rural economic development and growth. The paper used secondary data gathered from existing literature. The use of qualitative research methodology and document and content analysis techniques became vital in the process of collecting and analyzing collected data.

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.

The study aims to investigate and analyse the social media, precisely the Instagram activity of several hotels in the city of Yogyakarta, Indonesia. Having been the second most popular destination besides Bali, it is mainly dominated by domestic tourism. Although several governmental institutions exist, the study focuses on the hotel’s activity only. The main purpose was to find, that after the classification of the posts, whether there is a more positive effect of one as opposed to the other type of posts. In addition, it was also important to see if with the time advancing positive effect of likes and comments appear and the relation of hashtags, likes and comments. Data was collected between 1st of January 2023. and 15th of July 2024. The first step was to collect posts done by the suppliers and then the posts were classified. Also, the number of hashtags used were collected. Second step was to collect the response from the demand side by gathering their likes and comments. Data then was analysed with SPSS 24 and JASP program. Results show that while there is no significance on increasing likes and comments with the months advancing, but in terms of the type of the posts there is. Promotional posts with other suppliers tend to bring a lot more comments and likes than self-promotional posts. This study’s main purpose to analyse through social media posts to enhance online networking by local suppliers promoting each other’s products.

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.

While the healthcare landscape continues to evolve, rural-based hospitals face unique challenges in providing quality patient care amidst resource constraints and geographical isolation. This study evaluates the impact of big data analytics in rural-based hospitals in relation to service delivery and shaping future policies. Evaluating the impact of big data analytics in rural-based hospitals will assist in discovering the benefits and challenges pertinent to this hospital. The study employs a positivist paradigm to quantitatively analyze collected data from rural-based hospital professionals from the Information Technology (IT) departments. Through a comprehensive evaluation of big data analytics, this study seeks to provide valuable insights into the feasibility, infrastructure, policies, development, benefits and challenges associated with incorporating big data analytics into rural-based hospitals for day-to-day operations. The findings are expected to contribute to the ongoing discourse on healthcare innovation, particularly in rural-based hospitals and inform strategies for optimizing the implementation and use of big data analytics to improve patient care, decision-making, operations and healthcare sustainability in rural-based hospitals.

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.

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.