2020
DOI: 10.1016/j.tra.2020.04.020
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Analysing travel mode and airline choice using latent class modelling: A case study in Western Australia

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Cited by 25 publications
(11 citation statements)
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References 48 publications
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“…The chi-squared tests of independence do show that price is more likely to be a reason, important factor, and a reason for important factors for those who are travelling for leisure or visit friends and family. This is consistent with past literature highlighting that these are the most pricesensitive traveller types (Garrow et al, 2007;Morlotti et al, 2017;Zhou et al, 2020).…”
Section: Demographic Differencessupporting
confidence: 93%
“…The chi-squared tests of independence do show that price is more likely to be a reason, important factor, and a reason for important factors for those who are travelling for leisure or visit friends and family. This is consistent with past literature highlighting that these are the most pricesensitive traveller types (Garrow et al, 2007;Morlotti et al, 2017;Zhou et al, 2020).…”
Section: Demographic Differencessupporting
confidence: 93%
“…(2017) argue that high-income earners have high time value because they earn more money per hour, resulting in purchase behaviors, such as choice of high-quality service products, that helps minimize time waste. Similarly, leisure passengers are more sensitive to fare levels than business passengers because of the relative importance of travel purposes (Zhou et al. , 2020).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Travelers with checked-in bags, for example, experience greater exposure and may take more precautions to ensure quality service is delivered. Business purpose travelers are more sensitive to air service quality to protect their business interests that may be lost if the trip is not completed as scheduled, when compared to leisure travelers (Zhou et al. , 2020).…”
Section: Hypothesesmentioning
confidence: 99%
“…If the amount of data is large, it can effectively prevent the accuracy of the model from being too high. Generally, a smaller AIC or BIC demonstrates a better statistical performance (Kim et al, 2017 ; Zhou et al, 2020 ).…”
Section: Modelling Workmentioning
confidence: 99%