Impact Assessment of the outburst public health event on Chinese Tourism Demand for Japan -- a Case study of COVID-19 pandemic

Abstract

The COVID-19 pandemic has had a huge impact on the tourism industry. This study uses the Baidu index for travel to Japan from 2011 to 2019 to create an ARIMA model and uses geographic spatial analysis methods—seasonal concentration index, geographic concentration index, and coefficient of variation—to explore changes in China's demand for travel to Japan under the impact of major public health events such as the COVID-19 pandemic. The findings indicate that (1) before the pandemic, China's demand for travel to Japan had remained at a relatively high level, with demand peaking in March and July compared to other months. After the pandemic, monthly differences narrowed, and seasonal demand became more balanced, with summer emerging as the relatively peak season for travel demand, while autumn remained the lowest throughout the year. (2) Before the pandemic, the distribution of attention on Japan tourism network varied significantly among provinces, exhibiting an uneven pattern with higher attention in eastern regions and lower attention in western regions. After the pandemic, the gap between regions has widened. (3) Compared to unaffected values, affected values exhibit significantly wider inter-regional disparities and heightened seasonal volatility in online attention to Japan tourism. This study utilizes Baidu index to study Japanese tourism demand through network attention. It can enrich the theoretical system of tourism demand research and provide theoretical guidance for tourism enterprises to adjust their operating models and adapt to the post-epidemic tourism market.