Towards an era of multi-source uncertainty: A systematic and bibliometric analysis

Abstract

The frequent occurrence and diverse nature of black swan events in recent years, has stimulated explosive growth in studies on different types of uncertainties. We propose the concept of multi-source uncertainty (MU) and systematically synthesize 2230 high-quality articles (2000−2023) extracted from Web of Science via bibliometric analysis. With the help of performance analysis and science mapping analysis, we find that: (1) MU research has gone through three stages, preparation stage (2000–2007), rising stage (2008–2015) and take-off stage (2016–2023). (2) MU research is undertaken across a wide range of disciplines from Economics to Environmental Science, from Meteorology to Business Finance and from Computer Science to Political Science. (3) The intellectual structure of MU research consists of a methodological basis for the measurement of uncertainty and its effects and a theoretical basis for the impact of uncertainty on corporate finance, economic activity, and asset pricing. (4) Four major themes have been investigated by current literature, namely, "Environmental uncertainty and adaptation", "Uncertainty nexus and commodity volatility forecasting", "The impact of uncertainty on corporate finance", and "The effects of uncertainty shocks on financial markets". (5) The keywords at the three stages show a rapid growth trend, with more diversified sources of uncertainty and increasingly rich research topics. Among them, "geopolitical risk", "volatility forecasting", "climate policy uncertainty", "economic policy uncertainty", "economic uncertainty", and "COVID-19", are currently the hottest keywords. Overall, we present recent research trends, gaps, and future research agendas in this domain, which will help policy-makers, regulators and academic researchers know the nuts and bolts of the MU research, and identify the relevant areas that need investigation.