Provincial Data-Factor Capability and Individual Employment in China: A Multilevel Socio-Technical Systems Perspective

Employment adjustment under digital transformation is a multilevel outcome that depends not only on regional technical capability but also on the structural configuration and worker response conditions in which that capability is embedded. This study examines the relationship between provincial data-factor capability and individual employment in China by matching China Family Panel Studies data for 2012–2022 with a provincial DataIndex. Binary Logit models with province and year fixed effects reveal an age gradient: the employment association of DataIndex is positive for younger workers, weakens around midlife, and becomes negative at older ages. Province-year regressions further show that stronger data-factor capability is associated with industrial structure upgrading and greater regional innovation activity, while interaction tests indicate less favorable employment associations among agricultural-hukou and rural residents. These findings show that improvements in regional digital capability do not translate uniformly into employment gains. Instead, their labor-market consequences depend on worker adaptability and institutional and spatial conditions. The study therefore highlights the need to evaluate digital transformation not only through technological and structural progress, but also through the inclusiveness of its employment outcomes.