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    Investigating the impact of catchment areas of airports on estimating air travel demand: A case study of regional Western Australia

    Access Status
    Fulltext not available
    Authors
    Zhou, Heng
    Xia, Jianhong (Cecilia)
    Luo, Q.
    Nikolova, G.
    Sun, Jie
    Hughes, Brett
    Kelobonye, Keone
    Wang, H.
    Falkmer, Torbjorn
    Date
    2018
    Type
    Journal Article
    
    Metadata
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    Citation
    Zhou, H. and Xia, J. and Luo, Q. and Nikolova, G. and Sun, J. and Hughes, B. and Kelobonye, K. et al. 2018. Investigating the impact of catchment areas of airports on estimating air travel demand: A case study of regional Western Australia. Journal of Air Transport Management. 70: pp. 91-103.
    Source Title
    Journal of Air Transport Management
    DOI
    10.1016/j.jairtraman.2018.05.001
    ISSN
    0969-6997
    School
    School of Earth and Planetary Sciences (EPS)
    School of Occupational Therapy and Social Work
    School of Electrical Engineering, Computing and Mathematical Sciences
    URI
    http://hdl.handle.net/20.500.11937/68831
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 Elsevier Ltd The aviation industry in Western Australia (WA) plays a vital role in the economic and social development of the state. However, accurate forecasts for passenger movements are not available to policy makers due to lack of relevant air travel demand information. The objective of this study is to estimate the domestic air passenger seat numbers between airport-pairs based on online flight information in regional WA based on a gravity model using Poisson pseudo-maximum likelihood estimation (PPML). Particularly, we aim to investigate the impact of distance, airfare, catchment areas, population, tourism and mining sector on forecasting air passenger seat numbers in order to inform and guide policy making. This research collected appropriate data and produced valid models that represent air passenger seat numbers offered on regular public transport (RPT) air services in regional WA. The models consider both geographic and service-related variables, such as the catchment area of airports, population and number of tourists in the airport's catchment area. Two kinds of airport catchment areas are generated in this study, based on Thiessen polygon and two and half hours’ driving distance. The Thiessen polygon catchment areas cover the whole WA regions, while the 2.5 h's driving catchment area covers only 32 percent of the WA region. The size of the catchment area can affect the magnitude of factors, and therefore influence the modelling results. When deciding the catchment area for the study, it is important to take the spatial distribution of factors into considerations. For both Thiessen polygon and two and half hours’ driving distance catchment area, the model results illustrate that distance between airports, airfare of the flight, population of the origin airport's catchment area and the number of operating mine sites of the destination airport's catchment area are significantly correlated with domestic air travel seat capacity provided. Given the guidance from policy documents and policy makers, the results will improve the understanding of the key parameters of regional passenger aviation services and help to guide policy makers considering regional passenger aviation issues. The outcome of this study would be useful for and guide policy development.

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