情报科学 ›› 2025, Vol. 43 ›› Issue (7): 131-138.

• 业务研究 • 上一篇    下一篇

面向创新转化生态系统的知识管理模型构建与对策研究

  

  • 出版日期:2025-07-05 发布日期:2025-10-16

  • Online:2025-07-05 Published:2025-10-16

摘要:

【目的/意义】本文以知识管理理论为基础,分析创新转化生态系统不同参与主体的地位和作用,探究创新
转化生态系统知识管理过程。【方法/过程】通过对知识管理和创新转化等研究的回顾,以政府、高等学校、科研机
构、金融服务机构、科技中介机构、企业和最终用户在创新转化生态系统中的作用分析为起点,构建创新转化生态
系统知识管理模型,分析创新转化生态系统知识管理过程,并提出保障措施。【结果/结论】研究结果表明,面向创新
转化生态系统的知识管理是一项复杂的工程,该工程的顺利实施以不同参与主体为支撑,以知识极化、知识扩散、
知识回程为基础,目的是促进创新转化生态系统知识的充分利用,进而提升系统创新成果转化能力。【创新/局限】
本文创新点在于从不同创新主体视角分析创新转化生态系统整体的知识管理模式,局限性包括案例研究和模型验
证不足,后续将结合案例分析和系统动力学模型进行深入探讨。

Abstract:

【Purpose/significance】This paper draws on the theory of knowledge management to analyze the roles and contributions of
various stakeholders within the innovation transformation ecosystem, while exploring the knowledge management process specific to
this ecosystem. 【Method/process】By reviewing existing literature on knowledge management and innovation transformation, this study
examines the functions of key entities-government, universities, research institutions, financial service providers, technology interme⁃
diaries, enterprises, and end-users—within the innovation transformation ecosystem. Based on this analysis, a knowledge management
model for the innovation transformation ecosystem is constructed, the associated knowledge management process is systematically ana⁃
lyzed, and corresponding safeguard measures are proposed.【Result/conclusion】The findings indicate that knowledge management in
the context of the innovation transformation ecosystem is a multifaceted and intricate endeavor. Its successful implementation depends
on the coordinated efforts of all stakeholders, hinges on mechanisms such as knowledge polarization, diffusion, and feedback, and aims
to optimize the utilization of knowledge resources within the ecosystem, thereby enhancing the system's capacity for innovation trans⁃
formation and achievement.【Innovation/limitation】The primary contribution of this paper lies in its comprehensive analysis of the
knowledge management model for the innovation transformation ecosystem from the perspectives of diverse innovation participants.
However, limitations exist due to insufficient case studies and model validation. Future research will address these gaps through in
depth case analyses and the application of system dynamics models.