International Journal of Management

Greenwashing occurs when organizations exaggerate or falsely claim environmental responsibility to influence public perception. As sustainability becomes central to global branding, regulatory regimes, consumer activism, and ESG-driven investment, cross-border detection models are increasingly necessary. This paper examines conceptual, regulatory, and computational frameworks designed to detect greenwashing across diverse national environments. The study introduces the Global Greenwashing Detection Framework (GGDF), integrating linguistic analysis, supply-chain traceability, ESG compliance scoring, cultural sentiment interpretation, and third-party audit verification. Findings emphasize that greenwashing varies by region due to political motives, legal systems, cultural environmental narratives, and digital activism. Effective detection requires international data alignment, machine learning classification, and culturally adaptive inference models.