科研管理

科研管理 ›› 2025, Vol. 46 ›› Issue (1): 183-192.DOI: 10.19571/j.cnki.1000-2995.2025.01.019

• 论文 • 上一篇    

数字技能型劳动力集聚对企业创新的影响及传导机制研究

胡尊国1,郭雨如1,邓理婕1,毛军2   

  1. 1.长沙理工大学经济与管理学院，湖南 长沙410076；
    2.海南师范大学数学与统计学院，海南 海口571158

  • 收稿日期:2023-09-12 修回日期:2024-12-09 出版日期:2025-01-20 发布日期:2025-01-09
  • 通讯作者: 毛军
  • 基金资助:
    国家社会科学基金项目：“人工智能影响共同富裕的经济理论逻辑与政策优化研究”（24BJL008,2024.09—2026.12）。

Research on the impact and transmission mechanisms of digital-skilled labor agglomeration on innovation of enterprises

Hu Zunguo1, Guo Yuru1, Deng Lijie1, Mao Jun2   

  1. 1. School of Economics & Management, Changsha University of Science and Technology, Changsha 410076, Hunan, China;
    2. School of Mathematics and Statistics, Hainan Normal University, Haikou 571158, Hainan, China
  • Received:2023-09-12 Revised:2024-12-09 Online:2025-01-20 Published:2025-01-09

摘要：     当前数字化技能人才的空间集聚态势日益凸显，并形成了一定规模的数字“劳动力池”，为企业创新活动提供了重要条件。本文通过抓取大量网络招聘数据，构建了数字技能型劳动力集聚相关指标，并采用因果森林方法来克服传统计量的内生性难题，以分析数字技能型劳动力集聚对企业创新水平和结构的影响及其传导机制。研究发现，数字技能型劳动力空间集聚显著提升了当地企业绿色创新总水平，但其并未引起企业创新结构的显著变化。在数字化发展水平高于中位数的城市，数字技能型劳动力的集聚对区域内企业非绿色创新活动的推动效果更为显著，同时“挤出”了一些高风险、低收益的绿色创新项目。数字技能型劳动力的集聚通过推动企业数字化转型，进一步强化了企业的规模效应，从而促进了绿色创新的整体发展。这意味着政府应警惕数字技术深度发展对绿色创新项目产生潜在“挤出”效应，这对“双碳”目标的顺利实现具有重要理论启示。
关键词


关键词: 劳动力集聚, 绿色创新, 机器学习, 挤出效应, 数字化转型

Abstract:    The spatial agglomeration of digital-skilled talent is becoming increasingly evident, forming a substantial digital "labor pool" that provides critical support for enterprise innovation. This study utilized the extensive online recruitment data to construct indicators of digital-skilled talent agglomeration and applied the causal forest method to address traditional econometric endogeneity issues. It investigated the impact of digital-skilled talent agglomeration on enterprise innovation levels and structures, as well as its transmission mechanisms. The findings revealed that the spatial agglomeration of digital-skilled talent significantly enhances the overall level of green innovation among local enterprises but does not lead to substantial changes in innovation structures. In cities with digital development levels above the median, digital-skilled talent agglomeration has a more pronounced effect on promoting non-green innovation activities while "crowding out" some high-risk, low-return green innovation projects. This agglomeration drives enterprise digital transformation, amplifies scale effects, and consequently promotes the overall development of green innovation. These results have suggested that governments should be cautious of the potential "crowding-out" effect of advanced digital technology development on green innovation projects, thus providing important theoretical insights for achieving the goals of "carbon peaking and carbon neutrality".

Key words:  labor agglomeration, green innovation, machine learning, crowding-out effect, digital transformation