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Refining the Air Traffic Approach to City Networks

Author

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  • Zachary Neal

    (Department of Sociology, Michigan State University, 316 Berkey Hall, East Lansing, MI 48824, USA, zpneal@msu.edu)

Abstract

Despite embracing the concept of networks to help explain the organisation of modern urban systems, measurement has presented an overriding challenge to researchers: how can linkages between cities be operationalised? Airline traffic data have been proposed as a promising solution, but these data introduce their own complications. In this paper, the Airline Origin and Destination Survey is used to refine this approach, distinguishing first between hub/spoke and origin/destination networks and, secondly, between networks of business-oriented and leisure-oriented travel among 115 US metropolitan areas in 2006. After illustrating the importance of these distinctions with employment data from the American Community Survey, the resulting and more narrowly focused business network is used to test a model of urban economic flows. Results suggest that the volume of business exchanges between US cities is a function of the cities’ own attributes and as well as relational factors including economic similarity.

Suggested Citation

  • Zachary Neal, 2010. "Refining the Air Traffic Approach to City Networks," Urban Studies, Urban Studies Journal Limited, vol. 47(10), pages 2195-2215, September.
    • Handle: RePEc:sae:urbstu:v:47:y:2010:i:10:p:2195-2215
    DOI: 10.1177/0042098009357352
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    References listed on IDEAS

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    Cited by:

    1. Yang, Haoran & Dobruszkes, Frédéric & Wang, Jiaoe & Dijst, Martin & Witte, Patrick, 2018. "Comparing China's urban systems in high-speed railway and airline networks," Journal of Transport Geography, Elsevier, vol. 68(C), pages 233-244.
    2. Richard Florida & Charlotta Mellander & Thomas Holgersson, 2015. "Up in the air: the role of airports for regional economic development," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(1), pages 197-214, January.
    3. Marques Teixeira, Filipe & Derudder, Ben, 2020. "Revealing route bias in air transport data: The case of the Bureau of Transport Statistics (BTS), Origin-Destination Survey (DB1B)," Journal of Air Transport Management, Elsevier, vol. 82(C).
    4. Bowen, John T., 2016. "“Now everyone can fly†? Scheduled airline services to secondary cities in Southeast Asia," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 94-104.
    5. Stefan Hennemann, 2012. "Evaluating the performance of geographical locations within scientific networks using an aggregation—randomization—re-sampling approach (ARR)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2393-2404, December.
    6. Zachary Neal, 2014. "Validity in World City Network Measurements," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 105(4), pages 427-443, September.
    7. Neal, Zachary P. & Kassens-Noor, Eva, 2011. "The business passenger niche: Comparing legacy carriers and southwest during a national recession," Journal of Air Transport Management, Elsevier, vol. 17(4), pages 231-232.
    8. Guangqing Chi, 2012. "The Impacts of Transport Accessibility on Population Change across Rural, Suburban and Urban Areas: A Case Study of Wisconsin at Sub-county Levels," Urban Studies, Urban Studies Journal Limited, vol. 49(12), pages 2711-2731, September.
    9. Murakami, Jin & Matsui, Yurika & Kato, Hironori, 2016. "Airport rail links and economic productivity: Evidence from 82 cities with the world’s 100 busiest airports," Transport Policy, Elsevier, vol. 52(C), pages 89-99.

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