Niming Wang
Questrom School of Business, Boston University, Boston, MA 78602, USA.
*Corresponding author: Niming Wang
Abstract
With the deep-level integration of data elements into enterprise operations and management, resource allocation efficiency has become a key factor in determining enterprise competitiveness and sustainable development. Based on the practical necessity to improve the efficiency of enterprise resource allocation, this study takes a data-driven perspective. Paying attention to resource allocation efficiency problems and the need for model construction, it systematically devises an integrated analytical framework combining evaluation and optimization. By modeling and quantifying multi-dimensional enterprise resource allocation data, an efficiency evaluation model for resource allocation is created. Then, a relevant optimization model is designed based on what the evaluation shows. The results indicate that data-driven techniques can describe the differences in enter-prise resource-allocation efficiency and effectively reveal structural problems in resource management. The evaluation results clearly justify optimization decisions, and the proposed models show good feasibility and effectiveness in real-life applications. The research gives theoretical support and decision-making directions for enterprises to improve resource allocation efficiency, perfect the management decision-making flow, and promote data-driven management.
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How to cite this paper
Research on Evaluation and Optimization Models of Enterprise Resource Allocation Efficiency from a Data-driven Perspective
How to cite this paper: Niming Wang. (2026) Research on Evaluation and Optimization Models of Enterprise Resource Allocation Efficiency from a Data-driven Perspective. Advances in Computer and Communication, 7(1), 43-46.
DOI: http://dx.doi.org/10.26855/acc.2026.03.006