Event visitors’ geo-dispersal at the host destination: A Sequential Pattern Mining approach
Tourist dispersal in a tourism destination has important economic and social implications for destination management. However, tracking and analyzing such movement can be a challenge both conceptually and methodologically. Using a novel Sequential Pattern Mining approach, this study investigates the tourist dispersal of international visitors during the Gold Coast Commonwealth Games (GC2018) at a destination level by analyzing 377,960 tweets.
Results of this study show that sequential pattern mining is powerful in revealing the complex travel patterns and providing insights into the potential associated destinations of the visitors beyond the current point-to-point analysis. It makes an important contribution to the methodological literature on tourist dispersal. This approach can also assist destination management organizations and event organizers in identifying the event’s contribution to tourists’ local visitation.
Dr Mingming Cheng is a senior lecturer in digital marketing in the School of Marketing at Curtin University. Mingming is an award-winning researcher and educator with an international reputation in digital economy and tourism. His core research interests and expertise deal with tourist behaviour with a strong focus on Chinese young generations, the sharing economy (e.g., Airbnb), data science (big data) and social media marketing.
Mingming has won two prestigious awards the International Academy of the Study of Tourism Emerging Scholar of Distinction Award and CAUTHE Fellows Award for his significant contribution to ground breaking and innovative research in tourism