Abstract
Taking the development of China's digital economy as a background, the article provides an in-depth analysis and summarises the influencing factors of labour force employment polarisation. The study employs provincial panel data from 2010 to 2020, applies fuzzy set qualitative comparative analysis methods, and constructs a fixed-effects model in order to explore the drivers, paths and their effects of employment polarisation. The results of the study show that economic, social and educational environments together have a significant impact on employment polarisation through interactions and synergistic effects; it also identifies four main paths of labour force employment polarisation, which are numerical-social-environment-driven, numerical-educational-environment-driven, numerical-economic-environment-driven, and types driven by other factors; this study also finds that compared to the summed impact of single elements, these grouping pathways have a more significant impact on employment polarisation. These findings not only provide a key perspective for understanding how the digital economy shapes employment polarisation, but also provide an empirical basis and insights for policies based on the findings.