Influence of Quantum-Inspired Multi-Objective Optimization on Healthcare Resource Allocation Effectiveness in Selected Hospitals in Nigeria
Abstract
Healthcare resource allocation in Nigeria faces persistent challenges due to limited funding, workforce shortages, infrastructure constraints, and rising patient demand. Traditional allocation methods, often single-objective or heuristic-based, fail to capture the complex trade-offs between efficiency, equity, cost, and service quality. This study examines the influence of Quantum-Inspired Multi-Objective Optimization (QIMOO) on healthcare resource allocation effectiveness in selected Nigerian hospitals, integrating organizational readiness and data quality as key contextual factors. Drawing on principles of Optimization Theory, the Resource-Based View (RBV), and Organizational Readiness for Change Theory, the study models healthcare resource allocation as a multi-objective problem, where staff, equipment, beds, and budgets must be deployed efficiently under uncertainty. A quantitative cross-sectional design was employed, collecting primary data from hospital administrators and operational managers, complemented by secondary operational data from hospital records. Structural Equation Modeling (SEM) was used to assess the direct effects of QIMOO adoption on healthcare resource allocation effectiveness and the mediating role of organizational readiness, while controlling for data quality. Findings indicate that QIMOO adoption significantly improves resource allocation effectiveness (β = 0.41, p < 0.001) and that organizational readiness partially mediates this relationship (β…
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