Wuyi Zhang

The COVID-19 outbreak has drastically altered the behavior of tourists, posing a significant challenge to countries that heavily rely on the tourism industry to develop sustainable policies. This study utilizes structural equation modeling (SEM) techniques to analyze the effects of four variable groups on travel decisions during the pandemic. These groups include tourism potential, tourism logistics efficiency, the impact of COVID-19 on tourism potential, and the impact of COVID-19 on logistics efficiency. We collected data from a sample group of 943 foreign tourists visiting Thailand through online and on-site questionnaires. Our findings reveal that accommodation and information flow were the most significant factors affecting travel decisions during the pandemic, while the mode of transport had minimal impact. Based on our results, we recommend that post-COVID-19 tourism policies focus on improving accommodation quality and hygiene standards and building networks that offer comprehensive and up-to-date information about the pandemic. Our proposed approach is more efficient and cost-effective than mobilizing resources across all tourism industry sectors. It promotes sustainable tourism recovery planning while minimizing adverse effects on the community. These results are particularly relevant to stakeholders and policymakers who have been heavily affected by the COVID-19 pandemic and need to develop effective tourism policies.