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Representing tourists’ heterogeneous choices of destination and travel party with an integrated latent class and nested logit model

Author

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  • Wu, Lingling
  • Zhang, Junyi
  • Fujiwara, Akimasa

Abstract

Aiming at a better understanding of heterogeneous interdependencies between destination and travel party choices in tourism, this study attempts to simultaneously represent these two choices by integrating the nested logit model with the latent class modeling approach to accommodate both types of nested model structures together. Empirical analysis confirmed the effectiveness of the developed model, using a data collected from more than 2000 tourists in Japan. It was observed that on average the two types of nested model structures are almost equally shared by samples and the model structures could significantly vary with income level and gender. Influential factors related to choices of destination and travel party were also explored. Concretely speaking, travel time, attractiveness of destination and number of tourism spots were found to be important influential factors in destination choice, and gender, age, marital status have important effects on travel party choice.

Suggested Citation

  • Wu, Lingling & Zhang, Junyi & Fujiwara, Akimasa, 2011. "Representing tourists’ heterogeneous choices of destination and travel party with an integrated latent class and nested logit model," Tourism Management, Elsevier, vol. 32(6), pages 1407-1413.
    • Handle: RePEc:eee:touman:v:32:y:2011:i:6:p:1407-1413
    DOI: 10.1016/j.tourman.2011.01.017
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    Cited by:

    1. Bartosz Bursa & Markus Mailer & Kay W. Axhausen, 2022. "Intra-destination travel behavior of alpine tourists: a literature review on choice determinants and the survey work," Transportation, Springer, vol. 49(5), pages 1465-1516, October.
    2. Tomáš Gajdošík, 2020. "Smart tourists as a profiling market segment: Implications for DMOs," Tourism Economics, , vol. 26(6), pages 1042-1062, September.
    3. José Francisco Baños Pino & Beatriz Tovar, 2019. "Explaining cruisers’ shore expenditure through a latent class tobit model: Evidence from the Canary Islands," Tourism Economics, , vol. 25(7), pages 1105-1133, November.
    4. Christer Thrane, 2016. "Analysing related choices in tourism research," Tourism Economics, , vol. 22(3), pages 527-542, June.
    5. Renuka Mahadevan, 2018. "Examining domestic and international visits in Australia’s Aboriginal tourism," Tourism Economics, , vol. 24(1), pages 127-134, February.
    6. Zhang, Yixue & Zhao, Pengjun & Lin, Jen-Jia, 2021. "Exploring shopping travel behavior of millennials in Beijing: Impacts of built environment, life stages, and subjective preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 49-60.
    7. Wookhyun An & Silverio Alarcón, 2021. "Inferring customer heterogeneity for rural tourism: A latent class approach based on a best-worst choice modelling," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(7), pages 266-276.
    8. Crotti, Daniele & Maggi, Elena & Pantelaki, Evangelia, 2022. "Urban cycling tourism. How can bikes and public transport ride together for sustainability?," FEEM Working Papers 317840, Fondazione Eni Enrico Mattei (FEEM).
    9. Caspar G Chorus, 2018. "Paving the way towards superstar destinations: Models of convex demand for quality," Environment and Planning B, , vol. 45(1), pages 161-179, January.
    10. Masiero, Lorenzo & Qiu, Richard T.R., 2018. "Modeling reference experience in destination choice," Annals of Tourism Research, Elsevier, vol. 72(C), pages 58-74.
    11. Hunter-Jones, Philippa & Sudbury-Riley, Lynn & Chan, Jade & Al-Abdin, Ahmed, 2023. "Barriers to participation in tourism linked respite care," Annals of Tourism Research, Elsevier, vol. 98(C).

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