Abstract

The primary purpose of this study is to classify domestic tourists visiting community-based tourism destinations in Thailand according to their travel motivation. This study employed quantitative research as a main research method to achieve the purpose. An online self-administered survey was conducted on 384 tourists and the primary data was analyzed using the cluster analysis method. The study found three tourists’ clusters include ‘learning tourists,’ ‘leisure tourists,’ and ‘want-it-all tourists.’ These clusters were distinct from each other regarding travel motivation, socio-demographic profile, and online behavior. This knowledge contributed notable implications for academics and practitioners, allowing them to understand the differences among the tourists and to develop more appropriate marketing strategies for community-based tourism destinations and each segment. In addition, there are significant differences among the three clusters in terms of age and gender; hence, segmenting CBT tourists using age and gender should be researched in the future.

Keywords: Motivation-based segmentation, Community-based tourism, Online behavior, Tourism marketing