How data assetization enhances corporate ESG performance: a knowledge management perspective

Purpose Data assetization, the process through which firms convert dispersed data into governable, reusable assets, differs from digital transformation, yet its implications for corporate sustainability remain poorly understood. The authors examine whether and how data assetization affects corporate environmental, social and governance (ESG) performance from a knowledge management perspective. Design/methodology/approach The authors construct a firm-level data assetization index from data-related laws and policy documents and firms’ annual reports using a neural-network-based word embedding method. Using data for Chinese A-share listed firms from 2011 to 2023, the authors estimate fixed-effects models and conduct two-stage mechanism tests. Findings Firms with greater data assetization exhibit better ESG performance. Knowledge acquisition, storage, sharing, and application are potential channels underlying this relationship. The positive effect is weaker for firms with higher Tobin’s Q or more government subsidies. Jointly pursuing data assetization and sustainable development may exert short-term pressure on financial performance. Practical implications Managers should build integrated data and knowledge management systems and embed data assets into ESG-related strategic decisions. Government departments should improve data asset standards, valuation rules, and disclosure mechanisms. Originality/value This study extends the knowledge-based view from the deployment of knowledge resources to their prior formation, theorizing data assetization as the process through which data become governable, reusable knowledge assets. It links this process to ESG performance through four knowledge management channels, distinguishes it from digital transformation, and extends research on data assetization beyond financial outcomes.