This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.

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.

This study examines the relationship between board diversity (in term of percentage of female board members, educational qualification, independent directors, interlocking directorship, and financial literacy) and earnings quality of listed insurance companies in Nigeria. The study used secondary data from the stock exchange fact books and audited financial statements of the selected companies. We adopted a quantitative research design in which data were analyzed using descriptive and inferential statistics. Three variants of regression model, namely pooled ordinary least square, fixed effects and random effects models were estimated. Results revealed that significant differences exist in board diversity and earnings quality across the listed insurance companies in Nigeria. Also, the impact of board diversity on earnings quality is positive and strong. That is, the higher the company’s board diversity the better the ability to generate quality earnings. The results suggest than insurance companies with large number of women on the board are more likely to generate higher quality earning than those dominated by men. The paper draws the attention of management of listed insurance companies to the need to comply with the code of corporate governance on board diversity to increase the number of women on the board and ensure that the board consists of educationally qualified members, and financial literate members. The study also draws the attention of Nigeria Stock Exchange Group (NSGG) and other regulatory authorities to the need for regulation that will make disclosure of directors’ personal information a regulatory disclosure.

Analysing external factors with a design-thinking approach is crucial for adaptation, identifying opportunities, and mitigating risks in native digital enterprises. This research introduces a framework rooted in design principles and future scenarios for external analysis, with the aim of meeting current market needs. The study employs a mixed qualitative-quantitative research approach, incorporating methods such as literature review, workshops, and surveys. These methods enable the collection and analysis of both qualitative and quantitative data, providing a comprehensive and accurate understanding of the research topic by using it in a DNVB case study. Developing a conceptual framework using a design-thinking approach which we call ASPECT contributes to a comprehensive interpretation of complexity, intertwining collective and individual factors. This reduces the risk of overlooking essential elements when making strategic decisions in ambiguous, uncertain, and volatile contexts. This method contrasts with traditional external analysis frameworks like CAME, Pestle, and SWOT. The document aims to contribute to the literature by exploring new models of external analysis based on the design process. This framework combines the conventional stages of a design thinking process with methodologies for future scenarios to identify relevant external factors for organizations. It provides an innovative conceptual framework for creating new business models and growth strategies for digital enterprises.

Artificial intelligence chatbots can be used to conduct research effectively and efficiently in the fifth industrial revolution. Artificial intelligence chatbots are software applications that utilize artificial intelligence technologies to assist researchers in various aspects of the research process. These chatbots are specifically designed to understand researchers’ inquiries, provide relevant information, and perform tasks related to data collection, analysis, literature review, collaboration, and more. The purpose of this study is to investigate the use of artificial intelligence chatbots for conducting research in the fifth industrial revolution. This qualitative study adopts content analysis as its research methodology, which is grounded in literature review incorporating insights from the researchers’ experiences with utilizing artificial intelligence. The findings reveal that researchers can use artificial intelligence chatbots to produce quality research. Researchers are exposed to various types of artificial intelligence chatbots that can be used to conduct research. Examples are information chatbots, question and answer chatbots, survey chatbots, conversational agents, peer review chatbots, personalised learning chatbots and language translation chatbots. Artificial intelligence chatbots can be used to perform functions such as literature review, data collection, writing assistance and peer review assistance. However, artificial intelligence chatbots can be biased, lack data privacy and security, limited in creativity and critical thinking. Researchers must be transparent and take in consideration issues of informed content and data privacy and security when using artificial intelligence chatbots. The study recommends a framework on artificial intelligence chatbots researchers can use to conduct research in the fifth industrial revolution.