Optimizing faculty resource allocation in higher education: A mathematical model for strategic planning

Abstract

This paper introduces a new mathematical model aimed at improving how faculty resources are allocated in higher education institutions. The model takes into account the complexities of student enrollment, teaching quality, and program offerings. It provides a structured method to estimate faculty needs, including both Ph.D. holders teaching core courses and teaching assistants or lecturers managing practical courses, labs, and related tasks. By considering factors such as class sizes, faculty workloads, and student enrollment patterns, the model offers useful insights for academic planning. Two case studies from Hafr Al Batin University illustrate the model's practical value and flexibility. These examples show how the model can support informed decision-making, helping to maintain a balance between student numbers and teaching quality. The paper concludes by highlighting the importance of data-driven planning in the changing field of higher education, suggesting future research directions, and positioning the model as a key tool for improving the management and administration of higher education. The main goal is to ensure a high-quality education for students while making efficient use of resources.