Green data center policy and labor outsourcing in heavy-polluting firms: a knowledge-management perspective

Purpose This paper aims to investigate the reshaping effect of urban-level green data center (GDC) approval policies on labor outsourcing decisions by heavy-polluting enterprises, along with its core influencing pathways. Design/methodology/approach Using A-share listed firms in China’s heavy-polluting industries from 2013 to 2023, this study treats city-level GDC approval as a policy shock and uses a difference-in-differences framework with firm fixed effects and industry-by-year fixed effects to estimate its effects on corporate labor outsourcing. Findings The GDC approval has increased both outsourced labor hours and outsourced expenditure. The baseline semielasticities are about 0.20–0.21, corresponding to roughly 22%–24% relative to the implied counterfactual path absent approval. The mechanism findings show that there is a relationship between policy exposure and higher knowledge diversification and increased recombinant creation and reuse, in line with how firms have reorganized and recombined their knowledge as they have been reconfiguring organization boundaries. Heterogeneity patterns also imply that the outsourcing response is more pronounced among firms that appear less embedded in platform ecosystems, although these subgroup results should be interpreted with caution. Originality/value This study adopts a knowledge-management perspective to challenge the conventional understanding that the scale of digital assets determines corporate outsourcing behavior. It highlights how external digital infrastructure can alter knowledge codification, coordination and boundary-spanning conditions, thereby affecting organizational boundary choices. This study provides new perspectives on the interdisciplinary approach to digital infrastructure, corporate boundary choices and knowledge management.