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

Xiaoliang Xie · Xiaomin Jin · Guo Wei · Ching‐Ter Chang

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COVID-19 Pandemic Impacts Financial Distress and Bankruptcy Prediction Supply Chain Resilience and Risk Management

Abstract

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

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2020Startups in Times of Crisis – A Rapid Response to the COVID-19 Pandemic 2020The perceived impact of the Covid-19 epidemic: evidence from a sample of 4807 SMEs in Sichuan Province, China 2021COVID ‐19: Small and medium enterprises challenges and responses with creativity, innovation, and entrepreneurship 2022Did the paycheck protection program hit the target?2016Major Challenges Facing Small and Medium-Sized Enterprises in Asia and Solutions for Mitigating Them 2020How to Survive a Pandemic: The Corporate Resiliency of Travel and Leisure Companies to the COVID-19 Outbreak 2013Quantitative credit risk assessment using support vector machines: Broad versus Narrow default definitions 2022Determinants and consequences of SME insolvency risk during the pandemic

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