Configuration path identification of investment risk in China's overseas energy projects: An exploration based on LDA and fsQCA

Abstract

China's overseas energy investment is subject to various risks and uncertainties. This study uses the latent Dirichlet allocation (LDA) model for text mining to comprehensively identify risk factors for overseas energy project investment. Then, we utilize fuzzy set qualitative comparative analysis (fsQCA) to explore the configuration path of risk based on 25 overseas energy project investment cases. The results show that there are six categories of investment risks in overseas energy projects, namely: political risk, economic risk, resource risk, environmental risk, social risk, and national relations risk. The occurrence of a single risk is insufficient to cause an investment in an overseas energy project to fail. Rather, it is only when multiple risks occur together and act in concert that the project is disadvantaged. The configuration paths of risk can be categorized into four types, which are geopolitical dominance type, socio-economic dominance type, resource-environment dominance type, and comprehensive type. From a holistic perspective, this study examines the cumulative impact of multiple risk factors on the investment effect of energy projects, illustrating the inherent complexity of investment risks associated with overseas energy projects. This study provides direction for investors and policymakers to develop effective risk management programs and sound investment strategies.