Identifying the next non-stop flying market with a big data approach

Abstract

Destination Marketing Organizations (DMOs) strive to increase visitor volume through targeting potential markets and eliminating barriers to travel, such as opening non-stop flight routes. This study develops a comprehensive model to identify the next direct flight route for a destination by deploying buying funnel theory and gravity model. In addition to the geographical and economic characteristics of each market of origination, web traffic at the destination's Convention and Visitors Bureau (CVB) website—a proxy for the market's interest in the destination—is used to determine the markets that would exhibit the most potential to generate visitors if a non-stop flight route was opened. The model estimates each market's potential, using multiple gravity models, and compares it to the market's interest in the destination based on buying funnel theory. The present study then empirically tests the model using the actual data of Charleston, South Carolina, where five potential cities were identified.