This study aims to develop a robust prioritization model for municipal projects in the Holy Metropolitan Municipality (Makkah) to address the challenges of aligning short-term and long-term objectives. The research explores How multi-criteria decision-making (MCDM) techniques can prioritize municipal projects effectively while ensuring alignment with strategic goals and local needs. The methodology employs the analytic hierarchy process (AHP) and exploratory factor analysis (EFA) to ensure methodological rigor and data adequacy. Data were collected from key stakeholders, including municipal planners and community representatives, to enhance transparency and reliability. The model’s validity was assessed through latent factor analysis, confirming the relevance of identified criteria and factors. Results indicate that flood prevention projects are the highest priority (0.4246), followed by road projects (0.3532), park construction (0.1026), utility projects (0.0776), and digital transformation (0.0416). The study highlights that certain factors are critical for evaluating and prioritizing municipal projects. “Capacity and Demand” emerged as the most influential factor (0.5643), followed by “Strategic Alignment” (0.2013), “Project Interdependence” (0.1088), “Increasing Investment” (0.0950), and “Risk” (0.0306). These findings are significant as they offer a structured, data-driven approach to decision-making aligned with Saudi Vision 2030. The proposed model optimizes resource allocation and project selection, representing a pioneering effort to develop the first prioritization framework specifically tailored to Makkah’s unique municipal needs. Notably, this is the first study to establish a prioritization method specifically for Makkah’s municipal projects, providing valuable contributions to the field.

The study aims to examine the labor market challenges and motivational factors for employee retention through the example of a small machinery company in Hungary. In recent years, Hungary’s labor market has faced significant difficulties, particularly due to the COVID-19 pandemic, which resulted in temporary unemployment followed by labor shortages. The research aims to identify the motivational, welfare, and financial factors that contribute to employee retention. Due to the small sample size, we did not investigate the relationships concerning loyalty, commitment, and performance. The research methods included comprehensive data collection at a machinery company employing 24 people located near the Austrian-Hungarian border. During the data collection, we conducted a questionnaire survey that included questions related to benefits, performance, commitment, and loyalty. The collected data were processed by calculating weighted averages and differences. The results indicate that flexible working hours and easy accessibility to the workplace are of utmost importance to employees. There is also a significant demand for performance-based pay and diverse, flexible benefit packages. Employees require both formal and informal professional recognition, such as praise and awards. The research has practical significance for both organizational management and employee well-being. Understanding employee opinions and implementing measures based on these can have four primary effects: improvement in employee performance, reduction in turnover, increase in organizational commitment, and enhancement of the company’s positive perception.

Mapping land use and land cover (LULC) is essential for comprehending changes in the environment and promoting sustainable planning. To achieve accurate and effective LULC mapping, this work investigates the integration of Geographic Information Systems (GIS) with Machine Learning (ML) methodology. Different types of land covers in the Lucknow district were classified using the Random Forest (RF) algorithm and Landsat satellite images. Since the research area consists of a variety of landforms, there are issues with classification accuracy. These challenges are met by combining supplementary data into the GIS framework and adjusting algorithm parameters like selection of cloud free images and homogeneous training samples. The result demonstrates a net increase of 484.59 km² in built-up areas. A net decrement of 75.44 km² was observed in forest areas. A drastic net decrease of 674.52 km² was observed for wetlands. Most of the wastelands have been converted into urban areas and agricultural land based on their suitability with settlements or crops. The classifications achieved an overall accuracy near 90%. This strategy provides a reliable way to track changes in land cover, supporting resource management, urban planning, and environmental preservation. The results highlight how sophisticated computational methods can enhance the accuracy of LULC evaluations.

Regardless of the importance of accreditation and the role faculty play in a such process, not much attention was given to those in dental colleges This study aimed to explore faculty perceptions of accreditation in the College of Dental Medicine and its impact, the challenges that hinder their involvement in accreditation, and countermeasures to mitigate these barriers using a convergent mixed methods approach. The interviewees were faculty who hold administrative positions (purposeful sample). The remaining faculty were invited for the survey using convenience sampling. Quantitative data were analyzed by Mann-Whitney and Kruskal-Wallis tests at 0.05 significance. A consensus was achieved on the positive impact of accreditation with an emphasis on the collective responsibility of faculty for the entire process. Yet their involvement was not duly recognized in teaching load, promotion, and incentives. Quality Improvement and Sustainability Tools and Benchmarking were identified as common themes for the value of accreditation to institutions and faculty. Global ranking and credibility as well as seamless service were key themes for institutional accreditation, while education tools and guidance or unifying tools were central themes for faculty. Regarding the challenges, five themes were recognized: Lack of Resources, Rigorous Process, Communication Lapse, Overwhelming Workload, and Leadership Style and Working Environment. To mitigate these challenges, Providing Enough Resources and Leadership Style and Working Environment were the identified themes. This research endeavors to achieve a better understanding of faculty perceptions to ease a process that requires commitment, resources, and readiness to change.

The development of critical thinking (CT) enhances academic and professional opportunities. A review of literature reveals the use of fragmented analysis techniques, such as descriptive and correlational methods, among others, which hinder a deeper understanding of CT levels. This research aims to develop a methodology for analyzing Critical Thinking test scores, integrating five phases: exploratory, item analysis, scoring, gap analysis, and correlational. Using a quantitative approach, CT skills were analyzed with the Halpern Critical Thinking Assessment, which includes both open- and closed-ended questions to measure five skills: Verbal Reasoning (VR), Argument Analysis (AA), Hypothesis Testing (HT), Probability Use (PU), and Problem Solving (PS). The sample consisted of 214 students aged 18 and older. The item analysis phase categorized the items into quadrants: satisfactory, for review, or for elimination, based on difficulty and discrimination indices. The gap analysis revealed that Verbal Reasoning and open-ended formats were less satisfactory. The correlational phase, using heat maps, showed a stronger association between Verbal Reasoning and Probability Use. The methodological contributions include a variety of strategies that provide recommended procedures for analyzing tests or questionnaires in general. In today’s digital age, the development of critical thinking is not only a desirable skill but an essential necessity for the higher education system.

This study evaluates the health and sustainability of higher education systems in nine countries: the USA, UK, Australia, Germany, Canada, China, Brazil, India, and South Africa. Using a multi-level analysis model and principal component analysis (PCA), nine key factors—such as international student numbers, academic levels, and graduate employment rates—were identified, capturing over 90% of the cumulative impact on higher education systems. India, scoring 6.2036 initially, shows significant room for improvement. The study proposes policies to increase graduate employment, promote international faculty collaboration, and enhance India’s educational expenditure, which surpasses 9.8% of GDP. Post-policy simulations suggest India’s score could rise to 8.7432. The paper also addresses the impact of COVID-19 on global education, recommending a hybrid model and increased graduate enrollment in China to reduce unemployment by 5.4%. The research aims to guide sustainable development in higher education globally.