A Theoretical Framework for Multi-Attribute Decision-Making Methods in the Intelligent Leading and Allocation of Human Resources in Research and Development Projects

Effective human resource allocation is crucial for research and development project success. While multi-attribute decision-making methods are valuable, their application to human resource allocation in research and development remains underexplored; success factors are lacking, hindering robust decision frameworks. This paper identifies key human resource management attributes for research and development project success, integrating them into a theoretical framework for optimal allocation using multi-attribute decision-making methods. Our systematic literature review and content analysis of project performance research identified 49 distinct human resource-centric factors. These are organized into a functional model with four categories: strategic orientation, operational execution, organizational competence, and innovative–adaptive potential; their frequency indicates managerial focus. This highlights the critical need for a structured human resource allocation approach in research and development. Factors and the framework enhance project success. This study represents a foundational framework for MADM, offering a comprehensive and up-to-date list of relevant factors to ensure empirical and quantitative studies are grounded in a complete analysis rather than a random selection of a few factors. This work addresses a significant gap in the application of multi-attribute decision-making methods for human resource allocation in research and development, providing a comprehensive and robust tool for academia and practice.