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Latent class models of international air carrier choice


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  • Wen, Chieh-Hua
  • Lai, Shan-Ching
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    This paper uses a market segmentation approach to identify airline passengers' potential segments and preferences toward international air carriers. The modeling approaches consist of the stated preference method and the latent class model. The stated choice experiments were designed based on service attributes in the international airline choice context. Empirical data was collected from airline passengers who have flown from Taipei to Tokyo or from Taipei to Hong Kong. The latent class model accommodating preference heterogeneity outperforms the multinomial logit model as indication of a better approach to analyze airline choice behavior. The latent class model with individual socioeconomic and trip characteristics in segment membership functions also improved model fit relative to the corresponding latent class model without individual characteristics. The values of willingness to pay for service attribute improvements vary across international air routes and segments. Passengers are willing to pay more for better service quality. In order to develop effective marketing and operational strategies for the international air travel market, this study highlights the importance of exploring airline choice behaviors by routes and segments.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 46 (2010)
    Issue (Month): 2 (March)
    Pages: 211-221

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    Handle: RePEc:eee:transe:v:46:y:2010:i:2:p:211-221

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    Keywords: Airline Latent class Logit Stated preference Service quality;


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    Cited by:
    1. José Grisolía & Kenneth Willis, 2012. "A latent class model of theatre demand," Journal of Cultural Economics, Springer, vol. 36(2), pages 113-139, May.
    2. Chiou, Yu-Chiun & Jou, Rong-Chang & Kao, Chu-Yun & Fu, Chiang, 2013. "The adoption behaviours of freeway electronic toll collection: A latent class modelling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 266-280.
    3. Hetrakul, Pratt & Cirillo, Cinzia, 2013. "Accommodating taste heterogeneity in railway passenger choice models based on internet booking data," Journal of choice modelling, Elsevier, vol. 6(C), pages 1-16.
    4. Vij, Akshay & Walker, Joan L., 2014. "Preference endogeneity in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 90-105.
    5. Tsai, Ming-Chih & Yang, Chih-Wen & Lee, Hsiao-Ching & Lien, Ching-Wei, 2011. "Segmenting industrial competitive markets: An example from air freight," Journal of Air Transport Management, Elsevier, vol. 17(4), pages 211-214.
    6. Wen, Chieh-Hua & Wang, Wei-Chung & Fu, Chiang, 2012. "Latent class nested logit model for analyzing high-speed rail access mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 545-554.
    7. Hurtubia, Ricardo & Nguyen, My Hang & Glerum, Aurélie & Bierlaire, Michel, 2014. "Integrating psychometric indicators in latent class choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 135-146.
    8. Hetrakul, Pratt & Cirillo, Cinzia, 2014. "A latent class choice based model system for railway optimal pricing and seat allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 68-83.
    9. Escobari, Diego & Mellado, Cristhian, 2013. "The Choice of Airport, Airline, and Departure Date and Time: Estimating the Demand for Flights," MPRA Paper 47943, University Library of Munich, Germany.


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