信息资源管理学报 ›› 2026, Vol. 16 ›› Issue (4): 121-135.doi: 10.13365/j.jirm.2026.04.121

• 研究论文 • 上一篇    下一篇

数据要素协同驱动企业颠覆性技术创新研究——基于资源编排理论视角

陈晔婷 李映谌   

  1. 云南师范大学经济学院,昆明,650500
  • 出版日期:2026-07-26 发布日期:2026-09-21
  • 作者简介:陈晔婷,博士,副教授,研究方向为数据要素价值化与数字经济;李映谌(通讯作者),硕士生,研究方向为数据要素与数字经济,Email:15368017263@163.com。
  • 基金资助:
    本文系国家社会科学基金青年项目“ 中国-东盟跨境数据共享机制研究”(22CGJ036)、云南省哲学社会科学基金重点项目“ 云南-东盟跨境数据共享安全风险评估与应对策略研究”(ZD202519)的研究成果之一。

Data Factor Synergy Drives Disruptive Technological Innovation in Enterprises: A Resource Orchestration Perspective

Chen Yeting Li Yingchen   

  1. School of Economics, Yunnan Normal University,Kunming, 650500
  • Online:2026-07-26 Published:2026-09-21
  • About author:Chen Yeting, PhD, associate professor, research interests including the valorization of data elements and the digital economy; Li Yingchen (corresponding author), master candidate, research interests including data elements and the digital economy, Email: 15368017263@163.com.
  • Supported by:
    This paper is one of the outcomes of the National Social Science Fund Youth Project "Research on China-ASEAN Cross-Border Data Sharing Mechanism" (22CGJ036) and the Yunnan Province Philosophy and Social Science Fund Key Project "Research on Security Risk Assessment and Response Strategies for Yunnan-ASEAN Cross-Border Data Sharing" (ZD202519).

摘要: 在数据要素战略价值日益凸显而单一维度投入效能遭遇瓶颈的背景下,数据与传统生产要素的互补协同成为企业打破路径依赖、激发创新增效的关键。本研究基于2013—2024年A股上市公司样本,运用耦合协调度模型测度数据要素协同水平,实证检验其对企业颠覆性技术创新的影响。研究发现:①数据要素协同显著促进颠覆性技术创新,该效应在非常规高技能劳动力占比高、高管非数字化背景、政企连接度低及传统企业中更突出;②基于资源编排理论,其作用机制包括加速数据要素渗透、促进知识多元化与提升资源配置新颖程度;③数据要素协同通过促进颠覆性技术创新提升商业信用融资与企业价值,但亦加剧股价崩盘风险;④该协同效应虽能同时推动颠覆性技术创新与渐进性创新,却会降低颠覆性技术创新比重,产生结构性稀释效应。本研究对于指导企业优化要素资源配置、利用数据要素赋能颠覆性技术突破,以及平衡创新风险与收益具有重要参考价值。

关键词: 数据要素协同, 企业颠覆性技术创新, 数据要素渗透, 知识多元化, 资源配置新颖程度

Abstract: Against the backdrop of data elements' increasingly prominent strategic value and the diminishing returns of single-dimensional inputs, the complementary synergy between data and traditional production factors has become critical for firms to break path dependency and stimulate innovation. Based on a sample of A-share listed companies from 2013 to 2024, this study employs the Coupling Coordination Degree (CCD) model to measure the level of data factor synergy and empirically examines its impact on corporate disruptive technological innovation. The findings are as follows: ① Data factor synergy significantly promotes disruptive technological innovation, and this effect is more pronounced in firms with a higher share of non-routine high-skilled labor, non-digital executive backgrounds, lower government-enterprise connectivity, and traditional industries. ② Drawing on resource orchestration theory, the underlying mechanisms include accelerating data factor penetration, enhancing knowledge diversification, and improving the novelty of resource allocation. ③ Data factor synergy enhances trade credit financing and firm value by promoting disruptive technological innovation, yet simultaneously exacerbates stock price crash risk. ④ While the synergy drives both disruptive and incremental innovation, it reduces the share of disruptive innovation, generating a structural dilution effect. This study offers important implications for firms seeking to optimize factor allocation, leverage data elements to achieve disruptive technological breakthroughs, and balance innovation risks with returns.

Key words: Data factor synergy, Corporate disruptive technological innovation, Data factor penetration, Knowledge diversification, Novelty of resource allocation

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