Floods have always been an unavoidable natural disaster globally. Due to that, many efforts have been taken in order to alleviate the effect, especially in protecting the victims from losing their lives as well as their belongings. This study focuses on ensuring a smooth allocation process for flood victims to the relief centres considering the nature of their location, near the river, inland, and coastal. The finding indicated that a few implications have been highlighted for disaster management, such as changes in flood victim allocation patterns, classification of prone areas based on three areas, identification of most disaster areas, and others. Thus, to enhance the efficiency of allocation and to avoid any bad incidents happening during the flood occurrence, the allocation of flood victims is proposed to be started at a more critical area like the river area and followed by other areas. The finding also indicated that the proposed allocation procedure yielded a slightly lower average travel distance than the existing practice. These findings could also provide valuable information for disaster management in implementing a more efficient allocation procedure during a disaster.
Objective: This research aims to investigate the legal dynamics of leasing agricultural land plots integrated with protective plantings, motivated by recent legislative changes that significantly influence both agricultural productivity and environmental conservation. Methods: The authors of the article used the methods of axiological, positivist, dogmatic, historical, and comparative-legal analysis. Results: The study considers the recent legislative amendments that grant agricultural producers the right to lease land with forest belts without the need for bidding. It traces the historical development of forest plantations, highlighting their major role in intensifying agricultural production. Our results reveal that the new legislative framework allows agricultural producers to lease lands with protective forest belts without bidding, a change that highlights the complexities of balancing economic efficiency with ecological sustainability. Conclusions: The research emphasizes the unique legal challenges and opportunities presented by forest belt leasing in the agricultural context. It stipulates the need for a balanced legal framework that preserves environmental integrity, protects property rights, and supports sustainable agricultural practices. This study dwells on the evolving legal landscape of forest belt leasing and its implications for agricultural land management in Russia and similar regions. The significance of this research in its comprehensive analysis of the legal, economic, and ecological dimensions of land leasing, offering a nuanced understanding of how legislative changes shape land use strategies.
Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.
Investors and company managements often rely on traditional performance evaluation indicators, such as return on equity, return on assets, and other financial ratios, to explain changes in a company’s market value added (MVA). However, the effectiveness of these traditional measures in explaining market value fluctuations remains uncertain. This research aims to investigate the impact of various profitability measures, namely return on equity, gross profit margin, operating profit margin, and return on assets, on explaining changes in the MVA of pharmaceutical and chemical companies listed on the Amman Stock Exchange. To achieve the study’s objectives, we analyzed the published financial statements of a sample consisting of 14 industrial companies out of a total of 53 companies listed on the Amman Stock Exchange during the period from 2008 to 2022. Relevant financial indicators were extracted from these statements to serve the purposes of the study. Correlation coefficients were employed to measure the extent to which the independent variables (profitability measures) could interpret changes in the dependent variable (MVA). One of the most significant findings of the study is that three dimensions of profitability measures have a statistically significant impact on explaining changes in the MVA of pharmaceutical and chemical companies listed on the Amman Stock Exchange, albeit to varying degrees. This suggests that traditional profitability measures still play a crucial role in influencing market perceptions of a company’s value, despite the potential limitations of these measures in capturing the full scope of a company’s performance and potential.
This study investigates the impact of human resource management (HRM) practices on employee retention and job satisfaction within Malaysia’s IT industry. The research centered on middle-management executives from the top 10 IT companies in the Greater Klang Valley and Penang. Using a self-administered questionnaire, the study gathered data on demographic characteristics, HRM practices, and employee retention, with the questionnaire design drawing from established literature and validated measuring scales. The study employed the PLS 4.0 method for analyzing structural relationships and tested various hypotheses regarding HRM practices and employee retention. Key findings revealed that work-life balance did not significantly impact employee retention. Conversely, job security positively influenced employee retention. Notably, rewards, recognition, and training and development were found to be insignificant in predicting employee retention. Additionally, the study explored the mediating role of job satisfaction but found it did not mediate the relationship between work-life balance and employee retention nor between job security and employee retention. The research highlighted that HRM practices have diverse effects on employee retention in Malaysia’s IT sector. Acknowledging limitations like sample size and research design, the study suggests the need for further research to deepen understanding in this area.
China’s graduate quality management system is designed to ensure that students possess the necessary skills, knowledge, and competencies for future success. This system is rooted in China’s ambitious educational reforms aimed at cultivating a highly skilled workforce to drive economic growth and innovation. Effective graduate quality management significantly impacts employment levels, training models, and national policy formulation. This study investigates the quality management approaches of 56 vocational institutions in Yunnan Province using a 5-level questionnaire and a quantitative research methodology. A sample of 556 individuals was selected through stratified random sampling. Exploratory factor analysis identified five primary components of the quality management model: College graduate quality (mean = 4.56, SD = 0.49), teaching quality (mean = 4.39, SD = 0.42), hardware environment (mean = 4.38, SD = 0.44), social support (mean = 4.37, SD = 0.42), and job satisfaction (mean = 4.38, SD = 0.42). College graduate quality and teaching quality were the most influential factors, while hardware environment, social support, and job satisfaction had lesser impacts.
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