Monitoring and Early Warning of SMEs’ Shutdown Risk under the Impact of Global Pandemic Shock

The COVID-19 outbreak devastated business operations and the world economy, especially for small medium-sized enterprises (SMEs). With limited capital, poorer risk tolerance, difficulty in withstanding prolonged crises, SMEs are more vulnerable to pandemics face a higher of shutdown. This research sought establish model response shutdown by investigating two questions: How do you measure SMEs’ due pandemics? reduce risk? To best our knowledge, existing studies only analyzed impact pandemic on through statistical surveys trivial recommendations. Particularly, there is no case study focusing an elaboration risk. We developed cognitive uncertainty differences opinion among experts COVID-19. was built integrating improved Dempster’s rule combination Bayesian network, where former based method weight assignment matrix analysis. first applied representative SME with basic characteristics survival analysis during pandemic. results show that this has probability 79% lower shutdown, 15% medium 6% high solving capital chain problem changing external conditions such as market demand difficult Based counterfactual inferred results, occurrence each factor obtained simulating interventions. most likely causal revealed it simpler solve employee health problems. For study, approach can being at 16%. consistent those identified respondents, which validates model.