FAKTOR-FAKTOR YANG MEMENGARUHI KUALITAS LABA PADA INDUSTRI BERISIKO LINGKUNGAN TINGGI: TINJAUAN LITERATUR - Adli Rikanda Saputra (CV. Denasya Smart Publisher, 2026)
This review aims to synthesize the existing literature on factors influencing earnings quality in environmentally high-risk industries. These industries, including energy, mining, chemicals, heavy manufacturing, and utilities, face increasing pressure from carbon risk, carbon emissions, environmental regulation, public scrutiny, and sustainability reporting demands. This review adopts a structured literature review approach by examining relevant empirical and theoretical studies obtained from academic databases such as Scopus, Web of Science, SSRN, and Google Scholar. The literature was analyzed thematically to identify major determinants, theoretical perspectives, methodological trends, and future research gaps. The findings indicate that carbon risk and emission exposure generally reduce earnings quality through higher earnings management; however, this relationship is not linear and depends on governance quality, regulatory uncertainty, environmental performance, and institutional context. Environmental regulation and political costs also influence managerial reporting incentives, while environmental performance and CSR initiatives tend to improve earnings quality, although substitution between accrual-based and real earnings management remains an important concern. Investor attention, external monitoring, environmental disclosure, board financial literacy, executive compensation, internal control quality, and audit quality further moderate the relationship between environmental risk and earnings quality. This review concludes that earnings quality in environmentally high-risk industries is shaped by the interaction between environmental pressure, managerial incentives, governance mechanisms, and institutional context. Future research should expand the geographical and sectoral scope, adopt multidimensional earnings quality measures, and employ stronger causal identification strategies