Using time series data covering the years 1980 to 2020, this study examines the effects of government spending, population growth, and economic expansion on unemployment in the context of South Africa. The study’s variables include government spending, population growth, and economic growth as independent factors, and unemployment as the dependent variable. To ascertain the study’s outcomes, basic descriptive statistics, the Vector Error Correction Model (VECM), the Johansen Cointegration Procedures, the Augmented Dicky-Fuller Test (ADF), and diagnostic tests were used. Since all the variables are stationary at the first difference, the ADF results show that there isn’t a unit root issue. According to the Johansen cointegration estimation, there is a long-term relationship amongst the variables. Hence the choice of VECM to estimate the outcomes. Our results suggests that a rise in government spending will result in a rise in South Africa’s unemployment rate. The findings also suggest that there is a negative correlation between unemployment and population growth. This implies that as the overall population grows, unemployment will decline. Additionally, the findings suggest that unemployment and economic growth in South Africa are positively correlated. This contradicts a number of economic theories, including Keynesian and Okuns Law, which hold that unemployment and economic growth are inversely correlated.

This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

Purpose: The paper aims to study the methodology and functional of Internal Audit (IA) during the transition to remote working methods necessitated by the COVID-19 pandemic crisis period. Design/methodology/approach: Data are collected over a sample of 352 internal audit departments in retail SMEs distributed in the Gulf Cooperation Council (GCC) region. The six variables are measured using a reflective model. An exploratory factor analysis is applied to gauge the measurement model’s validity and reliability. Findings: The research findings revealed that internal auditing within the Kingdom of Saudi Arabia (KSA) and the Qatari retail sector is not sufficiently advanced. The focus of internal auditing primarily revolves around compliance audits rather than performance audits, thereby limiting their degree of agility and strategy which negatively affects the IA methodology. Conversely, for the United Arab Emirates (UAE) retail companies the research hypotheses were validated showing an IA functions evolution, an IA reassurance and IA agility that are conducted throughout a remote working and a strategic design that affect positively IA working methodology. Originality: The originality impregnates by the fact that reviews of traditional audit working methods were updated and shaped according to the deficiencies that couldn’t be identified during a pre COVID-19 period. A traditional audit plan may not work in this situation. The originality of the study consists of estimating IA methodological review through an agile approach that provides internal reassurance and risk attenuation.

Smart cities incorporate fundamental aspects such as sustainability and citizens’ well-being. Therefore, the objective of this study is to analyze the feasibility and effectiveness of the implementation of an evaluation model of the transformation processes towards smart cities as a strategy to improve the state of the transformation processes in Lima, Peru. The research is descriptive and basic. A questionnaire was administered to 80 municipal officials in Lima, focusing on the variable “smart cities evaluation model”, covering three key dimensions: open data, smart public transport and energy efficiency, with a total of 15 questions and the variable “state of the transformation processes”, analysed through the dimensions of educational level of the population and municipal budget, with 10 questions. The results revealed that 48% expressed a gap in terms of the availability and quality of accessible information. 53% argued that stronger energy conservation and sustainability strategies need to be implemented. In addition, 53% felt that the education level needs to focus on improving local education systems. In conclusion, transformation processes drive economic, social and environmental development, improving the quality of life and promoting equality among citizens. This study contributes to a broader understanding of how to address these challenges in order to build more sustainable and liveable cities in the future.

Based on 898 English documents and 363 Chinese documents citing the Rising of Network Society, it studied that the knowledge contribution of citation content analysis and citation context analysis methods, and the knowledge contribution of Chinese and foreign quotations to human geography. The study found that “mobile space” is the most quoted theoretical view in domestic and foreign literature, and the proportion of domestic research is significantly higher than foreign research; the focus of domestic and foreign research focuses on the external spatial form and its transformation, while foreign research pays more attention on the internal spatial dynamics of network society and three types of knowledge contributions, reflecting the influence of “network social theory” on human geography. Among them, critical references reveal the shortcomings of “network social theory” point out the abstraction of “spatial duality” the importance of local space, and the limitations of research data, methods, and time background, which provides new enlightenment for the future application and innovation of “network social theory” in the field of human geography.

This research aimed to assess the results of two vendors used by the company in the shipping process of export goods. Two leading suppliers for one similar activity had caused more difficulties in the monitoring and controlling activities of DHL Global Forwarding Indonesia. This research used qualitative and quantitative methods, with the Analytic Hierarchy Process decision-making method using 36 internal staff members as the sample. Through a qualitative calculation method by distributing questionnaires to the existing suppliers, namely Monang Sianipar Kargo and Andima Transportindo, it was found that the weighted score for Monang Sianipar Kargo was 22.84 and for Andima Transportindo was 10.66. Subcriteria and indicators should be prioritized in the criteria of Price and service, significantly to improve the performance of problematic suppliers. This research recommended using the Analytic Hierarchy Process for assessment since it facilitated the research development by the opinion of the company’s experts. Such a finding implied that a policy from the management was needed in the assessment of suppliers. As an implication, it was necessary to assess all suppliers cooperating with DHL Global Forwarding Indonesia by using actual data from the current month.