Akademik Məlumat İdarəetmə Sistemi
Corporate Social Responsibility and Environmental Management, 2026 (SSCI, Scopus)
Amid increasing global emphasis on sustainability, firms are under mounting pressure to align governance mechanisms with environmental, social, and governance (ESG) priorities. This study examines the relationships among internal control quality (ICQ), corporate sustainability (CS), and financial performance (FP) in the Chinese manufacturing sector, emphasizing the moderating role of CS. Using panel data from 226 A-share listed manufacturing firms between 2017 and 2021, we employ both traditional econometric techniques (OLS and 2SLS) and advanced machine learning methods to enhance analytical depth. Specifically, we utilize causal forest estimation, a generalized random forest (GRF) algorithm, to uncover heterogeneous treatment effects (HTEs) across firms. Our empirical findings reveal three key insights: (1) ICQ significantly enhances CS performance; (2) CS is positively associated with FP; and (3) CS moderates and strengthens the ICQ–FP association. The causal forest results further indicate that these effects vary by firm characteristics such as size, leverage, and age, underscoring the context-specific nature of governance–sustainability interactions. Theoretically, this study extends stakeholder theory by demonstrating how internal controls act as strategic enablers of sustainable value creation. Practically, it offers guidance for managers and policymakers on how aligning internal controls with sustainability objectives can yield superior financial outcomes, particularly in emerging economies.