Exploring network-based dependencies between country-level sustainability and business risks

Abstract

The concept of sustainability has gained prominence in the global discourse, with increasing recognition of its impact on business risk. By integrating sustainability considerations into their strategies and operations, national policymakers and businesses can mitigate business risks and contribute to national sustainability goals. The objective of this study is to explore dependencies among the risks associated with the 17 Sustainable Development Goals (SDGs), introduced by the United Nations in 2015, and country-level business risk. In particular, this study aims to identify critical SDGs that can influence business risk based on the two extreme performance states (i.e., best and worst scenarios) of individual SDGs. A data-driven Bayesian Belief Network model is developed using two datasets on country-level sustainability performance and business risk assessment. On the one hand, ‘quality education’, ‘no poverty’, ‘affordable and clean energy’ and ‘sustainable cities and communities’ are identified as the most critical SDGs based on the negative impact of their associated risks on business risk. On the other hand, low risk (high performance) associated with the ‘peace, justice and strong institutions’, ‘life on land’ and ‘industry, innovation and infrastructure’ SDGs can reduce business risk. Strong dependencies are found between individual SDG risks and business risk, implying policymakers need to consider the implications of their sustainability initiatives on the risks and uncertainties surrounding their country's business environment.