Evolution of policy-driven ecosystem of original innovation talents

Abstract

In an era of unprecedented global challenges, the cultivation, attraction, and retention of original innovation talent have become critical determinants of national competitiveness and sustainable development. This study introduces a novel multi-agent original innovation talent ecosystem model (MOITEM) to systematically analyze the effects of different talent policies on the ecosystems of original innovation talent across various regions in China. The simulations reveal that while direct talent policies drive short-term talent growth, they often fall short of addressing the long-term needs for resource allocation and environmental optimization, thereby limiting sustained competitiveness. In contrast, indirect and combined talent policies prioritize the overall quality of the ecosystem, providing more enduring support for original innovation. Furthermore, this study explores the interactions among agents within the ecosystem and their synergistic relationships with the external environment, highlighting the necessity of targeted policy formulation and multi-agent collaboration. The findings not only elucidate the strengths and limitations of various talent policies but also offer tailored recommendations based on regional characteristics, emphasizing the importance of continuous evaluation and adaptive policy adjustment. These insights hold substantial theoretical and practical implications for the development and optimization of global policies aimed at fostering original innovation talent.