This article analyses the case of Dubai’s smart city from a public policy perspective and demonstrates how critical it is to rely on the use of the public-private partnership (PPP) model. Effective use of this model can guarantee the building of a smart city that could potentially fulfill the vision of the political leadership in Dubai and serve as a catalyst and blueprint for other Gulf states that wish to follow Dubai’s example. This article argues that Dubai’s smart city project enjoys significant political support and has ambitious plans for sustainable growth, and that the government has invested heavily in developing the necessary institutional, legal/regulatory, and supervisory frameworks that are essential foundations for the success of any PPP project. The article also points to some important insights that the Dubai government can learn from the international experience with the delivery of smart cities through PPPs.

This paper provides a concise historical analysis of the political economy of privatization in Algeria, Morocco, and Tunisia from the 1980s to 2007, a period that witnessed the emergence of privatization as a primary policy tool to reform the public sector. The paper examines the influence of political history, macroeconomic considerations, and International Development Agencies (IDAs) on the early privatization processes in these North African countries. Despite shared developmental trajectories, internal and external factors had a significant impact on the outcomes of economic liberalization. The paper aims to answer the following key questions: What were the underlying political-economic factors driving privatization, and how successful was it in achieving the promised economic growth? Through a focused analysis of each country’s contextual factors, privatization processes, and outcomes, the paper contributes valuable insights into the nuanced dynamics shaping privatization in developing countries.

Over the course of many years, the Mekong Delta region has experienced relatively low and inconsistent levels of business attraction and low quality of the enterprise environment compared to other regions in Vietnam. To delve into whether this discrepancy reflects a negative perception of the business environment in the area, this study employs a dataset comprising the aggregate Provincial Competitiveness Index (PCI) and nine of its component scores, alongside other significant control variables, to analyze business attraction trends spanning from 2010 to 2020. It based on the modeling analysis for the panel data that includes Pool-OLS, FEM and REM models. The findings indicate that PCI serves as an important indicator influencing the quality of the business environment and plays a role in determining the location preferences of businesses. It is observed that public investment has exerted an impact on enticing new businesses to the region throughout this period. These research outcomes carry several policy implications, suggesting that public policy interventions can positively shape the business environment, consequently bolstering the appeal of business investments in the region.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

Improving the practical skills of Science, Technology, Engineering and Mathematics (STEM) students at a historically black college and university (HBCU) was done by implementing a transformative teaching model. The model was implemented on undergraduate students of different educational levels in the Electrical Engineering (EE) Department at HBCU. The model was also extended to carefully chosen high and middle schools. These middle and high school students serve as a pipeline to the university, with a particular emphasis on fostering growth within the EE Department. The model aligns well with the core mission of the EE Department, aiming to enhance the theoretical knowledge and practical skills of students, ensuring that they are qualified to work in industry or to pursue graduate studies. The implemented model prepares students for outstanding STEM careers. It also increases enrolment, student retention, and the number of underrepresented minority graduates in a technology-based workforce.