This study analyzes the relationship between Environmental, Social and Governance (ESG) scores and bond returns using the corporate bond data in Korea during the period of 2010 to 2015. We find that ESG scores include valuable information about the downside risk of firms. This effect is particularly salient for the firms with high information asymmetry such as small firms. Interestingly, of the three ESG criteria, only environmental scores show a significant impact on bond returns when interacted with the firm size, suggesting that high environmental scores lower the cost of debt financing for small firms. Finally, ESG is complementary to credit ratings in assessing credit quality as credit ratings cannot explain away ESG effects in predicting future bond returns. This result suggests that credit rating agencies should either integrate ESG scores into their current rating process or produce separate ESG scores which bond investors integrate with the existing credit ratings by themselves.

This study investigates how to apply artificial intelligence for social innovations using two socio-political factors critical for a Behavioral Theory of the Firm (BTF) – uncertainty and conflict. The analysis leads to four approaches for applying artificial intelligence for social innovations such as the agent-based modeling, social entrepreneurship, stakeholder capital, and social contract approaches. The valuation of artificial intelligence in the projects is endogenously created while the social innovators evaluate their environments, goals, and technologies. The study offers step-by-step guidance to assess the performance of and to create implementation strategies for social innovation projects combined with artificial intelligence.