Clustering of Provinces Based on Regional Tourism Statistics under the Epidemic Situation of Covid-19

Abstract

The objectives of this study were to classify provinces and determine their characteristics based on regional tourism statistics under the epidemic situation of COVID-19 using secondary data from official sources. The grouping of provinces by region was done by using cluster analysis technique. The results of the study in each region gave the similar results of grouping into 3 groups as follows: 1) A group of provinces, which is the main cities in the region, is the main target of tourists. This group has the highest number of tourists and tourism spending form both Thai and foreign tourists. 2) A group of provinces, which is a popular choice among foreign tourists in the region, has the highest number of tourists and tourism spending inferior to the first group. This group consists of medium-sized provinces with natural or cultural attractions and was a top choice for foreign tourists who want to experience the beautiful nature of Thailand. 3) A nearby provinces that can travel back and forth from the main city or provinces that are far from the main city, is a group of provinces with low number of tourists and tourism spending and also low occupancy. There are many tourist attractions but may not be very popular among foreign tourists maybe due to the inconvenience of travel or lack of information to search online or publicize.