Against the backdrop of global carbon neutrality goals, the textile industry, a labor-intensive and high-emission sector, faces urgent challenges in its green transition. However, empirical research examining how digital transformation (DT) drives carbon emission performance (CEP) in labor-intensive, low-innovation sectors such as textiles remains limited. Addressing this gap, this study applies the resource-based view (RBV) to explore whether green technological innovation (GTI) mediates the DT-CEP relationship in textile enterprises. The study utilizes panel data from 187 Chinese A-share listed firms (2013-2022) and employs fixed-effects regression with bootstrapping for mediation analysis. The results reveal three main findings. First, DT, measured by heterogeneous resources (digital technology assets and digital talent), has a positive effect on GTI. Among these resources, digital talent plays a stronger role in driving innovation than technology assets. Second, GTI, particularly process innovation (e.g., energy-efficient dyeing), significantly improves CEP. Third, GTI mediates 7.9%-16.5% of the DT-CEP relationship, providing new evidence on the importance of innovation for DT-driven carbon reduction in labor-intensive sectors, particularly among leading textile firms. This study extends RBV beyond capital-intensive manufacturing by demonstrating that heterogeneous digital resources can build green capabilities even in low-innovation firms. For global practice, the findings highlight digital talent development as key to green transitions in the textile industry, offering actionable insights for firms, policymakers, and international organizations aligned with the UN Sustainable Development Goals. This research advances cross-sectoral RBV application and provides a benchmark for DT-innovation-CEP studies in emerging economies.

textile enterprises, digital transformation, green technological innovation, carbon emission performance, resourcebased view