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Applying linear programming in evaluating employees in higher education: A case study.

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This study introduces a mathematical model to optimize human resources in higher education. It aids institutions in maximizing output by efficiently allocating research and teaching staff, improving overall productivity.

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Area of Science:

  • Management Science
  • Educational Administration

Background:

  • Organizations globally focus on increasing profit margins by maximizing output with minimal resources.
  • Optimal resource allocation, particularly human resources, is crucial for organizational success.
  • Higher education institutions face challenges in efficiently managing their research and teaching staff.

Purpose of the Study:

  • To present a mathematical model for optimizing human resource allocation in the higher education sector.
  • To provide a structured approach for institutions to improve staff utilization and efficiency.

Main Methods:

  • The study outlines a seven-stage process for developing and implementing the human resource optimization model.
  • Key stages include staff availability assessment, stakeholder evaluation, cost determination, motivation analysis, and staff ranking.
  • A mathematical model is developed based on these stages for practical application.

Main Results:

  • The proposed model offers a systematic framework for higher education institutions to optimize their human resources.
  • Implementation of the model can lead to more efficient use of research and teaching staff.
  • The model facilitates informed decision-making regarding staff deployment and resource management.

Conclusions:

  • The mathematical model serves as a valuable tool for enhancing human resource management in higher education.
  • Optimizing staff allocation is essential for institutions aiming to improve productivity and achieve strategic goals.
  • This research contributes to the field of management science by providing a practical model for resource optimization in academic settings.