Abstract
Using a corpus of 5,490 annual CSR and ESG disclosures from Chinese state-owned enterprises, this study adapts a text-based technological forecasting approach by proposing a novel artificial intelligence-driven fusion framework specifically designed to analyze complex, long-form textual data in the Chinese language. Our analysis provides empirical evidence that social value creation is multidimensional in nature and encompasses a wide variety of interconnected themes such as environmental, governance and technological innovation. In addition, our findings reveal an increasing blurring of boundaries between these themes as technological and environmental themes become progressively integrated with governance and social concerns, which indicates a shift from fragmented, responsibility-oriented strategies of social value creation towards interconnected strategies which integrates technological and environmental themes, especially as “bridges” connecting social responsibilities with economic goals. Our proposed novel framework also offers a scalable approach for forecasting emerging socio-technical trajectories using unstructured long form textual data.Using a corpus of 5,490 annual CSR and ESG disclosures from Chinese state-owned enterprises, this study adapts a text-based technological forecasting approach by proposing a novel artificial intelligence-driven fusion framework specifically designed to analyze complex, long-form textual data in the Chinese language. Our analysis provides empirical evidence that social value creation is multidimensional in nature and encompasses a wide variety of interconnected themes such as environmental, governance and technological innovation. In addition, our findings reveal an increasing blurring of boundaries between these themes as technological and environmental themes become progressively integrated with governance and social concerns, which indicates a shift from fragmented, responsibility-oriented strategies of social value creation towards interconnected strategies which integrates technological and environmental themes, especially as “bridges” connecting social responsibilities with economic goals. Our proposed novel framework also offers a scalable approach for forecasting emerging socio-technical trajectories using unstructured long form textual data.