This study aims to investigate how national climate policy enforcement influences environmental, social and governance (ESG) performance in green building startups. While ESG has been widely studied in large corporations, its relationship with regulatory enforcement in innovation-driven green building startups remains underexplored.
The study constructs Climate Policy Enforcement Index (CPEI) using eight regulatory enforcement components sourced from the World Bank. Firm-level ESG scores are derived using ESG-BERT, a natural language processing (NLP) model. A cross-sectional dataset of 858 green building startups across 63 countries is analyzed using multivariate fixed-effects regression, with heterogeneity explored by ESG subdimensions, firm revenue group and enforcement component.
Stronger climate policy enforcement is positively associated with overall ESG performance, particularly in the environmental dimension. Mid-sized startups show the highest responsiveness, while high-revenue firms appear decoupled from enforcement signals. Not all regulatory mechanisms are equally effective; early-stage enforcement tools such as energy code compliance and permitting processes have the most robust impact. Conversely, disclosure mandates and retrofit obligations may generate unintended negative effects.
This study advances ESG and institutional theory by highlighting the differentiated impact of enforcement mechanisms on startup behavior. It introduces an enforcement index tailored to the built environment and applies a state-of-the-art NLP model to assess ESG performance on a scale. The results offer actionable insights for policymakers designing sustainability regulation and investors evaluating ESG risk in early-stage firms.
