Recently, most countries have entered the outbreak period of the novel coronavirus epidemic. This sudden outbreak has caused a huge impact on the global economy, which has intensified the division of globalization and the recession of the global economy. Although the epidemic situation in China has gradually stabilized, the severe situation in the world still inevitably impacts China's economy. Based on the uncertainty of future epidemic, this paper sets up three scenarios to analyze the impact of the epidemic on China's economy. The first is that in June, the epidemic both at home and abroad is under control without rebound; the second is that the domestic epidemic is basically controlled but the foreign situation is not effectively controlled; the third is that the epidemic situation in China has a serious rebound due to the influence of the imported cases from abroad, which destroy the economy again. At the same time, some corresponding guidelines are put forward for the recovery of economy, and to minimize the economic losses as well as accelerate the pace of national economic recovery. In addition, it is believed that these suggestions may have certain reference value to other countries.

With the rapid development of the global economy, crude oil is becoming more and more prominent in terms of national stability. However, oil prices dramatically fluctuate during emergencies. Meanwhile, network search data have been widely used for prediction during the era of big data. Herein, a suggestion is introduced for improving the traditional case analysis. An autoregressive distributed lag model is established, considering emergency and network search data. Moreover, a network attention index of specific emergencies is used to explain fluctuations of the oil price and the influence of this attention is analyzed. Results show: 1) major emergencies have a significant short‐term impact on the international oil market and a remarkable influence on the cumulative abnormal return of an event window, and 2) market attention can aggravate fluctuations of oil prices. It is found that the individual network attention paid to each of four emergencies has a significant impact on oil prices. The network attention related to Hurricane Katrina and the Libyan war has positive effects on oil prices. However, the effects of network attention paid to the subprime crisis and the Mexico oil spill of 2010 are negative. The attention paid to the subprime crisis has both the greatest and the longest lasting impact.

COVID-19 may not only pose threats but also provided opportunities for innovation and growth for many high-tech small- and medium-sized enterprises (SMEs). This study investigates the relationship between entrepreneurial passion (EP), dynamic capability (DC) for innovation and product innovation performance in SMEs during COVID-19. Hierarchical regression and bootstrapping methods were employed per the survey data of 195 Chinese SMEs. The results reveal that EP is an imperative antecedent of DC and product innovation. DC also positively mediates the relationship between SMEs’ product innovation performance and top managers’ EP. In addition, this mediation effect of DC becomes more pronounced when firms are facing more opportunities. These findings advance the existing literature by specifying the process top managers use to cultivate product innovation within SMEs in times of crisis.

Tourism destinations are now facing a dilemma choice of controlling the epidemic or developing the economy. This paper takes Macao, a typical international tourist city, as an example to study the strategy of tourist source control during the COVID-19 period. According to the published epidemic data of Macao, this study has established an improved SEIR (Susceptible-Exposed-Infected-Recovered) model, formulated six control strategies against the current epidemic, and used the model above to simulate the time required for all confirmed cases to recover and discharge under different strategies. By taking into consideration the gross revenue of Macao’s gambling industry from 2017 to 2019, the impact of different strategies on the economy is predicted and three control strategies are found to be feasible. This study shows that an effective way to break through the above dilemma is to design the tourist management strategy by screening the source of passengers and controlling the upper limit of capacity of destination. These findings provide a scientific basis for tourism destinations in formulating public policies. The improved SEIR model is more consistent with the actual conversion rule of patients in the current COVID-19 epidemic, and it can be applied to further public health related research.