The consensus is that price stability promotes sustainable economic growth while excessive inflation harms growth. This study assesses the linkage between inflation and economic growth in South Africa to determine the optimal inflation rate threshold for the sustainable growth of the economy. Quarterly data from 1995 to 2022 was analysed through the ARDL and threshold regressions. The ARDL and threshold regressions estimate established a relationship between inflation and economic growth and computed the optimal inflation rate threshold for economic growth at 6 percent. The results also established that both the repo rate (repurchase rate) and real effective exchange rate have a negative relationship with economic growth. The Toda-Yamamoto causality test result indicated a unidirectional causality runs from inflation to economic growth. These results are crucial for the South African Reserve Bank to discharge its monetary policy functions to attain and maintain price stability. Therefore, this study offers the Bank a roadmap for targeting an inflation rate that aligns with the nation’s long-term objectives for sustainable economic growth.

With the development of college education and the increasing demand of students' comprehensive quality training, the second classroom in colleges and universities has attracted much attention as an important form of education. The purpose of this study is to investigate and analyze the development of the second classroom in colleges and universities, and put forward corresponding countermeasures and suggestions. Through mixed research methods, including questionnaire survey, interview and literature research, we have a comprehensive understanding of the type and quantity of college second classroom projects, student participation, project quality and effectiveness, and organization and management. On this basis, we put forward a series of targeted countermeasures and suggestions, including strategies and measures to improve student participation, suggestions to improve the quality and effect of the project, and optimize the program of organization and management. The results of this study have important theoretical and practical significance for universities to improve the level of the second classroom and promote the all-round development of students.

It is important for society to know the actions implemented by companies in the construction sector to reduce the environmental pollution generated by this industry and to contribute to the solution of economic and social problems in their environment; however, the variables that allow identifying their contributions and impacts are not known. Based on this problem, the study focuses on identifying the factors that influence sustainability management within the construction sector in Colombia. The research presents a predictive approach and uses a quantitative methodology, applying statistical modeling techniques. The sample corresponds to 84 Colombian companies. As a result, a system of equations of the form y=mx+b is presented to describe the deviation of the environmental, economic, social, compensation measures, management, indicators and sustainability reports. The analysis of the intersections constitutes a projective tool to evaluate the relationships and balance points between the dimensions analyzed, helping to identify strengths and opportunities for improvement.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

The article aims to evaluate the participation of below-poverty-line local community in tourism-related business activity in Himalayan state of Uttarakhand. Further, this article addressed for those who work in the tourism sector. The study employs a mix of methods, including survey data from 500 respondents with a random sampling approach, using Analysis of variance (ANOVA) statistical tools for analysis, other methods were interviews and observations at six tourism sites in Garhwal and four sites in Kumaun. Our findings showed that there has declined in community participation in tourism development, due to the lack of economic benefits obtained in the tourism sector, many believe that the tourism sector does not provide much income growth for them and does not make a significant contribution to the development of their region. Moreover, lack of understanding is considered the basis for community’s inability to play an active role, and lack of stakeholders’ involvement in encouraging them to improve their economy and culture through the tourism sector. Ultimately, this research also underlines the existence of some efforts by tourism travel to encourage public trust, which can help reduce poverty and increase community trust in tourism development in their region.