企业数字化转型、城市数字基础设施与劳动力数字技能需求

张艺¹，司徒东博²，李秀敏¹

（1. 广东工业大学 经济学院，广东 广州 510520；

2. 中国社会科学院大学 应用经济学院，北京 102488）

摘要：基于《中华人民共和国职业分类大典（2022版）》中数字职业的工作任务，借助大语言模型构建数字技能特征词图谱，并利用自然语言处理技术分析海量招聘广告的岗位描述，系统测算岗位层面的劳动力数字技能需求水平。将招聘广告文本与上市公司年报及城市数据进行匹配，构建岗位-企业-地区层级的数据集，研究企业数字化转型对劳动力数字技能需求的影响。研究结果显示，数字化转型能够提升企业对劳动力的数字技能需求，经内生性分析和稳健性检验后，该结论仍然稳健。机制分析结果显示，城市数字基础设施对企业数字技能需求具有溢出效应。异质性分析结果显示，企业数字化转型对劳动力数字技能需求影响较大的是高学历和低工作经验要求的岗位，并集中在农林渔牧业和高技术行业；同时，数字化转型抑制了金融业企业对数字技能劳动力的需求。研究结论为数实融合背景下发展新质生产力、把握劳动力数字技能的升级趋势和实现高质量就业提供了理论指导。

关键词：新质生产力；数字化转型；数字技能；城市数字基础设施；招聘岗位任务内容

作者简介：张艺（1986—），男，广东工业大学经济学院讲师；司徒东博（2001—），男，中国社会科学院大学应用经济学院硕士研究生；李秀敏（1964—），女，广东工业大学经济学院教授。

基金项目：国家社会科学基金后期资助一般项目“数字经济时代零工工资影响因素研究”（22FJYB045）；国家自然科学基金面上项目“粤港澳大湾区创新网络演进与政策效应：创新要素流动的视角”（72173032）

引用格式：张艺,司徒东博,李秀敏.企业数字化转型、城市数字基础设施与劳动力数字技能需求[J].首都经济贸易大学学报,2025,27(6):53-66.

Digital Transformation of Enterprises, Urban Digital Infrastructure and the Demand for Labor Digital Skills

ZHANG Yi¹, SITU Dongbo², LI Xiumin¹

(1. Guangdong University of Technology, Guangzhou 510520;

2. University of Chinese Academy of Social Sciences, Beijing 102488)

Abstract: China has designated the development of new quality productive forces as a national priority. Against the backdrop of this strategic initiative and the deepening integration of digital and physical economies, artificial intelligence (AI) and digital technologies are reshaping the demand structure for skills in the labor market. In particular, jobs associated with digital transformation increasingly require workers to possess digital skills.

To examine this shift, this paper first constructs a dictionary of keywords for measuring the digital skills required for various jobs, based on the task descriptions of occupations classified as digital in the Chinese Standard Classification of Occupations (2022 edition). Using natural language processing techniques, it analyzes unstructured job descriptions from online job postings to quantify the specific digital skill requirements for different occupations. It further matches these digital skill measurements with firms' levels of digital transformation to assess the impact of digital adoption on the demand for digital skills. Additionally, this paper explores the heterogeneous effects of digital transformation on digital skill demand across different dimensions. It provides theoretical insights into the development of new quality productive forces in the digital economy, the evolving trajectory of digital skill upgrading in the labor market, and strategies for promoting high-quality employment.

The empirical analysis yields three primary findings. First, firms' digital transformation significantly increases recruitment demand for digital skills, and this effect remains robust after addressing endogeneity with an instrumental variable approach and robustness checks. Second, the development of urban digital infrastructure partially substitutes for firms' demand for digital skills. Third, heterogeneity analysis shows that the effect of digital transformation on digital skill demand is strongest in positions requiring doctoral degrees and in those with less than 1 year of experience; and the effect is positive in agriculture-related sectors, negative in finance, and most pronounced in high-tech industries.

This paper makes three key contributions. First, it constructs a comprehensive digital skills dictionary based on job descriptions of digital occupations and applies NLP techniques to analyze job descriptions in online recruitment advertisements. Second, it quantifies the impact of firms' digital transformation on labor market demand for digital skills by leveraging text data from corporate online job postings, thereby offering a more precise assessment of job-specific skill demands. This helps address gaps in the existing literature regarding the effects of digital transformation on labor skills. Third, it refines the methodology for measuring digital transformation by addressing the subjectivity in keyword selection. By systematically synthesizing existing digital economy terminology and previously used keywords for measuring corporate digital transformation, this paper develops a more comprehensive measure of digital transformation among listed firms, reducing potential measurement errors.

Keywords: new quality productive forces; digital transformation; digital skills; urban digital infrastructure; job posting task

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