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Advance purchase behaviors of air passengers: A continuous logit model

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  • Chiou, Yu-Chiun
  • Liu, Chia-Hsin

Abstract

Modeling the advance purchase behaviors of air passengers is essential when airlines develop revenue management strategies. Therefore, this study empirically investigates advance purchase behaviors based on the air ticket transaction data by using a continuous logit model. The estimation results show that advance purchase behaviors are significantly affected by price, price uncertainty, time of day (morning, afternoon and evening flight), days of week (flight on Friday), months of year (peak or off-peak seasons), and consecutive holiday. Accordingly, different pricing strategies should be used for different flights to maximize revenue.

Suggested Citation

  • Chiou, Yu-Chiun & Liu, Chia-Hsin, 2016. "Advance purchase behaviors of air passengers: A continuous logit model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 474-484.
    • Handle: RePEc:eee:transe:v:93:y:2016:i:c:p:474-484
    DOI: 10.1016/j.tre.2016.07.001
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    Cited by:

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    2. Tangjian Wei & Feng Shi & Guangming Xu, 2019. "Estimation of Time-Varying Passenger Demand for High Speed Rail System," Complexity, Hindawi, vol. 2019, pages 1-24, March.
    3. Ma, Shanshan & Li, Guo & Sethi, Suresh P. & Zhao, Xuan, 2022. "Advance booking discount strategies: Competition, information transparency and spot market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    4. Xiao-qiang Wu & Lei Zhang & Song-ling Tian & Lan Wu, 2021. "Scenario based e-commerce recommendation algorithm based on customer interest in Internet of things environment," Electronic Commerce Research, Springer, vol. 21(3), pages 689-705, September.
    5. Wen, Chieh-Hua & Chen, Po-Hung, 2017. "Passenger booking timing for low-cost airlines: A continuous logit approach," Journal of Air Transport Management, Elsevier, vol. 64(PA), pages 91-99.

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