Exploiting a Natural Hub: Turning a Stopover into a Destination
In the mature aviation system of today, it is difficult to establish new hubs that focus solely on transfer traffic. This paper identifies a new type of hub—a natural tourism hub—one at which an airline and the surrounding metropolitan area can simultaneously benefit from a transportation hub and ac...
Published in: | Transportation Research Record: Journal of the Transportation Research Board |
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Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
SAGE Publications
2018
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Subjects: | |
Online Access: | http://dx.doi.org/10.1177/0361198118758983 https://journals.sagepub.com/doi/pdf/10.1177/0361198118758983 https://journals.sagepub.com/doi/full-xml/10.1177/0361198118758983 |
Summary: | In the mature aviation system of today, it is difficult to establish new hubs that focus solely on transfer traffic. This paper identifies a new type of hub—a natural tourism hub—one at which an airline and the surrounding metropolitan area can simultaneously benefit from a transportation hub and accompanying tourist destination, respectively. The study aims to identify existing airports for these stopover locations that are located on highly trafficked international flight routes. Using Iceland as an example, this country’s success in optimizing its stopover location to promote tourism and gain airline passenger demand is examined. The analysis is carried out by implementing a k-means clustering algorithm on total distance added for stopover locations, as well as flight leg symmetry to identify existing airports that are geographically located in an optimal stopover path for international routes across the Atlantic and Pacific oceans, and between Europe and East Asia. Airports in the clusters that minimize total added distance are then observed, and the clusters are ordered based on how symmetric the two flight legs of a stopover journey at an airport in that cluster tend to be. In addition, three airports near the top of this list are analyzed as potential stopover locations. In using this algorithm, not only is it possible to forecast which hubs may become major tourist destinations, but also to identify how airlines can shape people’s perception of their location as a tourist destination. |
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