STRATEGIC RESOURCE ALLOCATION USING MANAGEMENT SCIENCE MODELS

Abstract

This study examines strategic resource allocation through the application of management science models to support effective organizational decision making under limited budget and capacity conditions. The analysis is based on a structured dataset containing projects across multiple business units, planning periods, and decision model categories. Key variables include available and required budget, staff hours, expected return on investment, risk score, strategic alignment, urgency, projected net present value, and allocation feasibility. The study uses a comparative analytical approach to evaluate how resource allocation outcomes vary across departments, project types, and management science techniques such as linear programming, goal programming, integer programming, simulation, decision trees, and multi-criteria scoring. The findings highlight that successful allocation decisions depend on balancing financial returns with strategic alignment, urgency, and operational constraints. The analysis also shows that integrated management science frameworks improve transparency, prioritization, and consistency in resource distribution. By combining quantitative evaluation with practical interpretation, the study provides a useful model for academic analysis and managerial application in strategic planning, project prioritization, and evidence-based resource management across complex organizational environments.