数据要素对企业就业规模的影响研究

Impact of Data Factors on Enterprise Employment Scale

中文关键词:  数据要素  就业规模  效率提升  成本降低  稳就业  就业质量

英文关键词:data factors  employment scale  efficiency improvement  cost reduction  stabilizing employment  employment quality

中文摘要:

      数据要素是数字经济深化发展的核心引擎,发挥数据要素乘数效应将为推动高质量发展提供有力支撑。基于2011—2022年中国上市公司数据,实证检验了数据要素对企业就业规模的影响及作用机制。研究发现,数据要素能够显著扩大企业就业规模,数据要素的就业增长效应主要通过提高企业效率、降低企业成本实现。异质性分析表明,数据要素扩大了企业非常规性任务岗位的就业规模,并呈现高技能劳动偏向的单极化趋势；数据要素的就业增长效应在高数据资本存量行业、服务业、位于胡焕庸线东南侧以及行业进入壁垒低的企业中更为显著。拓展性分析表明,数据要素能够有效改善企业员工福祉,实现稳就业和改进就业质量的双重效应。因此,政府应持续完善数据要素市场机制,助力企业有效利用数据要素,促进高质量充分就业。

英文摘要:

      Data factors serve as the core engine driving the deepening development of the digital economy. Leveraging the multiplier effect of data factors will provide robust support for promoting high-quality development. This paper, based on data from China's listed companies from 2011 to 2022, empirically examines the impact of data factors on enterprise employment scale and their underlying mechanisms. Findings reveal that data factors significantly expand enterprise employment scale. This employment growth effect of data factors is primarily achieved through two pathways:improving corporate efficiency and reducing corporate costs. Heterogeneity analysis indicates that data factors expand employment in non-routine task positions and exhibit a unipolar trend favoring high-skilled labor. The employment growth effect is more pronounced for enterprises in industries with high data capital stock, service industries, enterprises located southeast of the Hu Huanyong Line, and those facing lower industry entry barriers. Extended analysis shows that data factors can effectively improve employee well-being, achieving dual effects of stabilizing employment and improving employment quality. Therefore, the government should improve the market mechanism for data factors, assist enterprises in effectively utilizing data factors, and promote high-quality and full employment. 