We know that small businesses are vulnerable to crisis, however little is still known about how they cope during long crisis as the COVID-19 pandemic. This paper provides a qualitative analysis of small businesses in Macau, China, in the months following the outbreak. We collected interview data from six local small firms. We found that the sudden decline in demand has the strongest impact on small firms. As compared with large firms, new startups and small firms show high flexibility in their reactions to the crisis, partly due to the low level of bureaucracy and limited social responsibility compliance. Among the various types of response strategies, all participant firms adopted flexible HR strategies. Other common survival strategies include the increase of product diversification, exploration of new markets, and increase of learning. We also found that some small businesses had a formal crisis plan and strategy before the outbreak, and these firms tend to have longer history, experience in dealing with crisis, and operate in more regulated sectors. Based on these results, we define five types of renewal and survival strategies for small businesses and propose a SME crisis resilience model.

This research develops a framework that combines crisis stages, stakeholder engagement, and crisis challenges. The framework is applied to small firms in Macao during the 2019 novel coronavirus disease (COVID-19) pandemic crisis. We conduct a qualitative study based on semi-structured interviews with the leaders of six small firms in Macao. The findings suggest that the COVID-19 pandemic has turned into a “normal” context, which blurs the traditional crisis termination stage. We also find that participating firms engage more with internal stakeholders than external ones. The strategies adopted by small firms include flexible human resource (HR) practices, cost reduction, enhancing customer relations, and using government support schemes. These strategies are effective in the short term; firms need to pay attention to diversity and learning for the long term.

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In the absence of effective drugs to control the COVID-19 epidemic, the main intervention of human factors, namely strict isolation, may be the best prevention and control method at present. The conclusion of data empirical study using Benford's Law is of great significance.Research purpose of this paper analyze COVID -19 data to predict the authenticity and reliability, and on this basis, the method is to use Benford's Law and the panel model for 51 countries or regions COVID -19 data statistical analysis, the results of the study found that "other areas" unreliable data, Australia, Pakistan and global data are greatly influenced by artificial factors, Africa, Oceania data with several other states Data according to have significant difference, compared the southern hemisphere and northern hemisphere, the first phase of the data and the second stage also has the obvious difference between the data, The COVID-19 data are also predicted to suggest that the outbreak may have multiple iterations.In conclusion, in most cases, when COVID-19 data deviates from Benford's Law, epidemic prevention and control is better; otherwise, it is worse.