Presenter Bios

So Young Park is currently enrolled as a PhD candidate in the Department of Recreation, Park, and Tourism, College of Health and Human Development, Penn State University. Her research interests involve tourism economics, information technologies in tourism, and decision making behavior.

Bing Pan, PhD, is associate professor in the Department of Recreation, Park, and Tourism, College of Health and Human Development, Penn State University. His research interests include information technologies in tourism, destination marketing, and search engine marketing.

Abstract

Non-stop flights to a destination could reduce travel cost and increase visitor volumes. However, the airlines have to attract enough passengers to make those flights cost-effective. The identification of the next non-stop flying destination is one of the responsibilities of a Destination Marketing Organization (DMO). This paper develops a comprehensive model that encompasses the purchase funnel theory and the gravity model, which would help identify the potential markets for the next direct flight. Furthermore, the web traffic at the destination’s Convention and Visitors Bureau (CVB) is used as a proxy for each origin’s interest for the destination. This paper calculates the region’s potential to fly using multiple gravity models and compares actual visitors to the regions’ interest to the destination to find the most prospective markets. Theoretical background for the model and empirical evidence using the actual data of Charleston, South Carolina are provided for more thorough investigation.

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Tourism Market Segmentation using Big Data Approach: Where is the Next Non-Stop Destination?

Non-stop flights to a destination could reduce travel cost and increase visitor volumes. However, the airlines have to attract enough passengers to make those flights cost-effective. The identification of the next non-stop flying destination is one of the responsibilities of a Destination Marketing Organization (DMO). This paper develops a comprehensive model that encompasses the purchase funnel theory and the gravity model, which would help identify the potential markets for the next direct flight. Furthermore, the web traffic at the destination’s Convention and Visitors Bureau (CVB) is used as a proxy for each origin’s interest for the destination. This paper calculates the region’s potential to fly using multiple gravity models and compares actual visitors to the regions’ interest to the destination to find the most prospective markets. Theoretical background for the model and empirical evidence using the actual data of Charleston, South Carolina are provided for more thorough investigation.