Abstract This study proposes a model-based market segmentation approach to identify and investigate existing and potential aviation markets. This is based on a stated preference survey administered in Western Australia, and including both choice data and a range of socio-demographics and information about trip purpose. This stated preference survey balanced behavioural plausibility and statistical efficiency, through an extension of the widely-used Modified Federov Algorithm. Respondents recruited at airports and elsewhere were interviewed, which improves much of the existing literature base which has focused on recruitment through airports. Three distinct segments were identified in both airport and non-airport respondent samples. For the airport respondent sample, one segment was relatively less likely to choose flying over other modalities, and consisted of older males with middle level incomes. Conversely, in the non-airport respondent sample, two of the three segments were less likely to choose aviation, and typically were comprised of relatively younger, lower income and non-business purpose travellers. These findings, showing heterogeneous groups in both populations provides a nuanced view of the broader air travel market than has been developed to date, and allows key players in the aviation sector (including airlines and government) to better predict the consequences of the various policy levers at their disposal.

    Highlights A mixture model-based market segmentation approach is developed to identify existing and potential aviation markets. An extension of the Modified Federov Algorithm is proposed to generate a realistic and d-efficient stated preference survey. Potential aviation market segments are discovered in both airport and non-airport respondent samples. Characteristics of existing and potential aviation market segments are investigated and compared.


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    Title :

    Market segmentation approach to investigate existing and potential aviation markets


    Contributors:

    Published in:

    Transport Policy ; 99 ; 120-135


    Publication date :

    2020-08-21


    Size :

    16 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English