Investigating air travellers' travel motivation during a pandemic crisis

A New Trend of Tourism in the Post-COVID-19 Era: Big Data Analysis of Online Tours in Korea

In this study, big data analysis on Korea’s “online tour”, which emerged as an alternative to satisfy tourism needs after COVID-19, was conducted. After extracting keywords through text mining for 24,073 posts from the top three most frequently visited social media platforms, Naver, Daum, and Google, to gather tour information in Korea, frequency analysis and TF-IDF analysis were run. In addition, network analyses, such as centrality and convergence of iteration correlation (CONCOR) analyses, were performed. The results showed: First, the sense of presence via local live streaming is crucial. It is vital to prepare a suitable video environment where tourists can immerse themselves in the tour. Second, the interaction between travel agencies, local guides, and tourists is important because it can expand tourists’ travel experiences. Third, the importance of online tour program content was revealed. It is necessary to increase the demand by designing various programs tailored to the audience. Fourth, new possibilities for local travel that had been neglected were uncovered. Fifth, the importance of online tourism production support was highlighted. The role of the government must be expanded to reinforce the digital capabilities of small- and medium-sized enterprises (SMEs) and to create jobs. Although the scope of this study is limited to Korea, it can definitely be used as a regional strategy.

Travel Motivation during COVID-19: A Case from Nepal

The tourism industry is one of the most affected industries by the COVID-19 pandemic. Understanding travel motivation is necessary for the tourism movement, even in the COVID-19 pandemic. Thus, this quantitative study aimed to explore travel motivation and its determinants. We collected 181 samples through a web-based questionnaire survey of the Nepali people in January and February 2021. The data were analyzed using a probit regression model through two different travel companion perspectives, i.e., traveling with friends and traveling with family members. We found that travel motivation, attributes, travel purpose, and transport mode preferences differed in companion groups. Specifically, those who want to travel with friends are government employees, 20–29 years of age, set health and wellness purposes, choose the bike for transportation, are less willing to visit homestay and agritourism, and want to travel for around one week. Those who plan to travel with family members use the coach to travel, choose rural destinations, including villages, and spend around two weeks. Based on these findings, we suggest that the Nepalese tourism destination and public transport companies make tourism packages targeting the groups. Since both groups showed interest in visiting rural destinations, we can say that tourism in rural destinations may revive earlier than urban tourism after the pandemic. However, a low-risk travel environment should be ensured for traveling to attract more tourists during and the post-disaster.