摘要
Abstract
The development of new quality productive forces aims to raise total element productivity through disruptive innovation and resource allocation to realize multi-stakeholder equilibrium in the labor market.Based on the"capability-value creation"framework,this paper integrates fuzzy-set Qualitative Comparative Analysis(fsQCA)and Necessary Condition Analysis(NCA)to explore the complex configurational effects of eight factors on employees' data value creation,namely employees' strategic cognition of digital intelligence,digital intelligence strategy implementation,digital intelligence job demands,reliance on data value,intelligent data collection,digital technology support,construction of digital talent training systems,and organizational digital learning and growth.The study identifies five labor resource allocation models:awareness-driven growth,skill-driven growth,production-dependent,talent introduction,and organizational learning.The awareness-driven growth,skill-driven growth and talent introduction models highlight the importance of fostering employees' recognition of digital transformation,emphasizing data-driven decision-making and feedback mechanisms.The organizational learning model underscores that digital talent training systems are pivotal to stimulating employees' high-level data application capabilities.Meanwhile,the skill-driven growth,production-dependent and talent introduction models collectively demonstrate that organizational digital learning and growth guarantee the emergence of high-level data productivity among employees.关键词
新质生产力/员工数据价值创造/价值创造/模糊集定性比较分析(fsQCA)Key words
New quality productive forces/Employees' data value creation/Value creation/Fuzzy-set Qualitative Comparative Analysis(fsQCA)分类
社会科学
