企业数字化转型如何重塑劳动力雇佣的任务结构？

汪雯¹　黄诗怡¹　王霆²

（1.北京林业大学；2.中国政法大学）

摘要：数字化转型正深刻重塑企业的雇佣结构，其就业效应受到广泛关注。本文选取2010—2023年沪深A股上市公司面板数据，从任务视角考察企业数字化转型对劳动力雇佣任务结构的影响及其作用机制。研究发现，数字化转型能够提高企业非常规任务型劳动力占比，降低常规任务型劳动力占比。机制分析表明，数字化转型通过提升全要素生产率和研发投入强度，推动企业劳动力雇佣结构向非常规任务转移。交互效应分析结果显示，“宽带中国”试点政策进一步强化了上述效应。异质性分析结果显示，该效应在制造业、高市场化程度地区与大规模企业中更为明显。进一步研究发现，数字化转型具有认知偏向特征，即其对非常规认知型任务的创造效应强于非常规非认知型任务，而对常规非认知型任务的替代效应强于常规认知型任务。本文拓展了数字化转型就业效应的任务分析框架，为数字化时代企业人力资源配置优化、就业政策完善及劳动者技能提升提供了启示。

关键词：企业数字化转型；劳动力雇佣；任务结构；认知任务；技术变革

作者简介：汪雯，北京林业大学经济管理学院教授、博士生导师，北京，100083；黄诗怡，北京林业大学经济管理学院硕士研究生；王霆，中国政法大学商学院教授、博士生导师，通信作者，北京，100088。

基金项目：国家社会科学基金一般项目“数字经济发展对农民工就业质量的影响与作用机制研究”（21BJY089）

引用格式：汪雯，黄诗怡，王霆. 企业数字化转型如何重塑劳动力雇佣的任务结构？［J］. 经济与管理研究，2026，47（10）：132-147.

How Does Firm Digital Transformation Reshape Task Structure of Employment?

WANG Wen¹, HUANG Shiyi¹, WANG Ting²

(1. Beijing Forestry University, Beijing 100083;

2. China University of Political Science and Law, Beijing 100088)

Abstract: Firm digital transformation (FDT) is reshaping business activities and employment structures. However, existing studies focus on skill groups rather than work tasks, with insufficient consideration of how digitalization reshapes the internal task structure within enterprises. Based on task-biased technological change theory, this paper examines how FDT reshapes the task structure of employment and its underlying mechanisms, using panel data from A-share listed firms in China from 2010 to 2023.

The FDT level is measured by the share of digital terms in the management discussion and analysis part of annual reports. Using reported staff posts, this paper groups production, finance, and administrative staff as routine-task labor and technical and sales service staff as non-routine-task labor. The results show that FDT raises the share of non-routine-task labor and lowers the share of routine-task labor. This conclusion remains stable after endogeneity analysis and a series of robustness tests. Two main channels explain the conclusion. First, FDT raises total factor productivity (TFP) by improving data use, resource allocation, and firm coordination. This cuts demand for tasks that follow clear rules while raising demand for more complex work. Second, FDT raises research and development (R&D) intensity and expands innovation, which needs data analysis, technical work, problem solving, and other non-routine skills. The external digital setting also matters. Taking the “Broadband China” pilot policy as a case of digital infrastructure policy, the findings confirm that better digital infrastructure drives both the rise in non-routine tasks and the fall in routine tasks. The effects differ across firms and regions. They are stronger in manufacturing, more marketized areas, and larger firms. It then adds a cognitive dimension and splits tasks into four groups: non-routine cognitive, non-routine non-cognitive, routine cognitive, and routine non-cognitive. The results show that FDT has a more positive effect on non-routine cognitive tasks. Its negative effect is also larger for routine non-cognitive tasks. Thus, FDT shifts labor from routine to non-routine work and also raises the cognitive content of the task structure.

This paper contributes to the literature on the employment effects of FDT by extending the analytical framework from a skill-based perspective to a task-based perspective. It also shows how TFP, R&D, and digital infrastructure shape task change, providing valuable insights for optimizing firms’ human resource allocation, improving employment policies, and enhancing workers’ skills in the digital age. The findings imply that policy should emphasize task-based skill training, lifelong learning, and job-transition support for workers exposed to routine-task substitution. Policy should also support firm innovation and digital infrastructure development to ensure that digital transformation creates more high-value and cognitive tasks while easing the risk of structural job loss.

Keywords: firm digital transformation; employment; task structure; cognitive task; technological change

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