The study explores the relationship between authentic leadership, psychological capital, and work engagement among educators in the Makhado Municipality. The primary aim was to assess how authentic leadership influences educators’ psychological capital and examine how psychological capital impacts work engagement. A quantitative research design was employed, utilizing a survey-based approach to collect data from a sample of educators across 15 primary schools within the Makhado Municipality. Structural Equation Modeling was used to analyze the data and test the relationships between authentic leadership, psychological capital, and work engagement. Results indicate that authentic leadership has a significant positive influence on the psychological capital of educators. In turn, psychological Capital was found to have a strong positive impact on work engagement, suggesting that educators who perceive their leaders as authentic are more likely to experience higher levels of psychological well-being and engagement in their work. This study contributes to the literature on leadership and educator well-being by demonstrating the value of authentic leadership in promoting a supportive work environment that enhances educators’ psychological capital and engagement. The educational management and policy implications emphasize the need for leadership development programs that foster authentic leadership behaviors to improve educator performance and overall school effectiveness.
The recent development of characteristic towns has encountered a multitude of challenges and chaos. Nevertheless, there have been many instances of information asymmetry due to the absence of an effective management model and an intuitive digital management system. Consequently, this has caused the erosion of public interests and inadequate supervision by public agencies. As society is progressing at a rapid pace, there is a growing apprehension regarding poor management synergy, outdated management practices, and limited use of technology in traditional construction projects. In today's technologically sophisticated society characterized by the “Internet+” and intelligent management, there is an urgent requirement to identify a more efficient collaborative management model, thereby reducing errors caused by information asymmetry. This paper focuses on the integration of building information modeling (BIM) and integrated project delivery (IPD) for collaborative management within characteristic towns in the PPP mode. By analyzing the available literature on the application status, this study investigates the implementation methods and framework construction of collaborative management while exploring the advantages and disadvantages. On this basis, this study highlights the problems that arise and provides recommendations for improvement. Considering this, the application of the BIM-based IPD model to characteristic towns in PPP mode will enhance the effectiveness of collaborative management among all parties involved, thereby fostering an environment that facilitates decision-making and operational management in the promotion of characteristic industries.
The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.
Institutions of higher learning are crucial to sustainability. They play a crucial role in preparing the next generation of leaders who will successfully execute the Sustainable Development Goals of the United Nation. This research therefore intends to present a preliminary conceptual approach in examining how industrial revolution 4.0 (I.R. 4.0) technologies, and lean practices affect sustainability in South Africa’s Higher Education Institutions (HEIs). The study shall employ survey questionnaire to collect data from the employees of the institutions. This preliminary study reveals that hybrid IR 4.0 technologies and lean practices as enablers of sustainability has not gained enough attention in the HEIs. Existing literature show the important role plays by performance variance of lean practices to improve sustainable performance when deployed from industry to education sector. The report validates the HEI’s future course, which has been incorporating new technology into its services processes recently. Using the created items, researchers may utilize empirical analysis to look into the combined effects of lean practices and IR 4.0 technologies on sustainability in HEIs. The following conclusions may be drawn: HEIs are essential for the application of sustainability principles; curriculum focused on sustainability and culture change are critical for attitude development; and the political climate and stakeholder interests impact the implementation of sustainability.
North Korea has been isolated from the international community because of high-intensity sanctions. Nonetheless, research on North Korea should continue so that we are prepared not for contingencies that may occur because of sudden political changes in that country, as occurred after the unification of Germany and dissolution of the Soviet Union, and also to cope with future risks and threats wisely. This study conducted a quantitative survey regarding “inter-Korean cooperation in science and technology,” targeting experts at the Korean government-funded research institutes. As a qualitative survey, focus group interviews (FGI) were conducted to gain insights into the possibilities, considerations, and procedures for inter-Korean cooperation in science and technology. This study is the first to conduct quantitative research on inter-Korean exchange and cooperation in science and technology and shows significant statistical results.
Objective: This research analyzed the psychometric properties of the Ambivalent Classism Inventory (ICA) in Peru. Methodology: A critical review of literature related to poverty, inequality, and structural gaps was conducted, involving 882 participants aged 14 to 89 years (M = 24.61, SD = 9.07). Results: Exploratory-confirmatory factor analyses were satisfactory, finding a similar factorial structure to the original scale and the adaptation (hostile classism, protective paternalism, and complementary class differentiation). Regarding items, there was a reduction, leaving only 12; however, comparing alternative models, the three-factor structure with 12 reagents showed adequate fit (χ2 = 214.588, df = 51, p < 0.001; CFI = 0.996; RMSEA = 0.060; SRMR = 0.033), allowing for invariance testing. Practical Implications: The scale allows for investigating attitude profiles of individuals with privileged social class. Contribution: The instrument is a valuable contribution, considering that the nation has a high poverty rate, leading to economic, political, and social inequality among the population.
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