管理评论

管理评论 ›› 2026, Vol. 38 ›› Issue (8): 31-44.

• 经济与金融管理 • 上一篇    

从数字化到具身化：数字技术推动知识转移数智化发展的研究

崔新健1,2, 任静1, 崔志新3   

  1. 1. 中央财经大学商学院, 北京 100081;
    2. 北京市人民政府参事室, 北京 100031;
    3. 中国社会科学院工业经济研究所, 北京 100006
  • 收稿日期:2025-04-18 发布日期:2026-09-11
  • 作者简介:崔新健，中央财经大学商学院教授，博士生导师，博士；任静（通讯作者），中央财经大学商学院博士研究生；崔志新，中国社会科学院工业经济研究所副编审，博士。
  • 基金资助:
    国家自然科学基金面上项目（72374234）。

From Digitalization to Embodiment: Research on the Development of Digital Technologies Promoting the Digitalization of Knowledge Transfer

Cui Xinjian1,2, Ren Jing1, Cui Zhixin3   

  1. 1. Business School, Central University of Finance and Economics, Beijing 100081;
    2. Advisory Office of the People's Government of Beijing Municipality, Beijing 100031;
    3. Institute of Industrial Economics of CASS, Beijing 100006
  • Received:2025-04-18 Published:2026-09-11

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摘要： 伴随数字技术的快速发展，人类知识转移、扩散和创造发生了根本性的变化。本文基于知识创造理论经典的SECI知识转移模型，从知识转移数智化轨迹、功能和模型三个维度，探索数字技术推动知识转移数智化发展的内在规律。本文发现，一是知识转移数智化轨迹呈现由易到难依次拓展，从数字化到智能化，走向具身化，揭示了数字技术突破知识转移底层逻辑——知识转移尤其是隐性知识转移的时空界限。未来，具身智能是人工智能的更高层次，侧重于大脑控制身体与环境之间的相互作用来实现更加高效的智能行为。二是知识转移数智化功能随着轨迹发展渐进强化，打破经典的SECI知识转移模型制约瓶颈，这标志着认知模式从连接共享逐步演化为智能赋能，并最终迈向人机共融。三是知识转移数智化模型重塑经典的SECI知识转移模型，通过云计算、量子计算与大模型等数字技术，实现从四阶段向“人机共感”的一阶段跃升，这使得知识转移在异质时空的即时实现变为可能。本文揭示数字技术在知识转移领域的深远影响，为知识管理及数智化发展提供新的理论视角，也为知识密集型组织在数智化转型过程中如何有效促进知识转移、提升知识创新能力提供了有益的参考。

关键词: 知识转移, 数智化, 具身化, 数字技术

Abstract: The rapid advancement of digital technology has fundamentally reshaped the transfer, diffusion, and creation of human know-ledge. Grounded in the classic SECI model, this study examines the intellectualization of knowledge transfer through three dimensions—its trajectory, function, and model—to uncover the underlying mechanisms driven by digital technologies. The findings indicate that: First, the trajectory evolves progressively from digitalization to intelligentization and toward embodiment, transcending spatiotemporal constraints, particularly in tacit knowledge transfer. Embodied intelligence, as an advanced form of AI, leverages body-environment interactions to enable more efficient intelligent behaviors. Second, the functionality intensifies along this trajectory, overcoming limitations of the SECI model and reflecting a shift in cognitive modes from connectivity and sharing to intelligent empowerment and ultimately human-machine integration. Third, The model transforms the classical SECI framework, leveraging technologies such as cloud computing, quantum computing, and large models to converge four stages into a unified “human-machine shared sensing” phase, enabling instant knowledge transfer across heterogeneous spatiotemporal contexts. This study highlights the profound impact of digital technologies on knowledge transfer, offers theoretical insights for knowledge management and intellectualization, and provides practical guidance for knowledge-intensive organizations in fostering knowledge transfer and enhancing innovation capabilities during digital transformation.

Key words: knowledge transfer, digital intelligence, embodiment, digital technology