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Analyzing the Impact of High-Speed Rail on Tourism with Parametric and Non-Parametric Methods: The Case Study of China

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Listed:
  • Francesca Pagliara

    (Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, 80125 Napoli, Italy)

  • Filomena Mauriello

    (Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, 80125 Napoli, Italy)

  • Yin Ping

    (Department of Tourism Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

Abstract

High-speed rail (HSR) and tourism are closely related activities since improved mobility is perceived to facilitate tourist behavioral changes. The interest in research is very high and this contribution tries to provide an insight into this topic by making a comparison between the estimation of the parametric Generalized Estimating Equation (GEE) approaches with the non-parametric Classification and Regression Tree (CART). A dataset containing information both on tourism and transport for thirty Chinese provinces, during the 2001–2017 period, has been collected. The finding of this paper shows that the presence of HSR has value in the explanation of tourist arrivals.

Suggested Citation

  • Francesca Pagliara & Filomena Mauriello & Yin Ping, 2021. "Analyzing the Impact of High-Speed Rail on Tourism with Parametric and Non-Parametric Methods: The Case Study of China," Sustainability, MDPI, vol. 13(6), pages 1-10, March.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3416-:d:520428
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    References listed on IDEAS

    as
    1. Shaw, Shih-Lung & Fang, Zhixiang & Lu, Shiwei & Tao, Ran, 2014. "Impacts of high speed rail on railroad network accessibility in China," Journal of Transport Geography, Elsevier, vol. 40(C), pages 112-122.
    2. Pagliara, Francesca & Mauriello, Filomena & Garofalo, Antonio, 2017. "Exploring the interdependences between High Speed Rail systems and tourism: Some evidence from Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 300-308.
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    4. Pagliara, Francesca & Mauriello, Filomena, 2020. "Modelling the impact of High Speed Rail on tourists with Geographically Weighted Poisson Regression," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 780-790.
    5. Jiao, Jingjuan & Wang, Jiaoe & Jin, Fengjun, 2017. "Impacts of high-speed rail lines on the city network in China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 257-266.
    6. Sophie Masson & Romain Petiot, 2009. "Can the high speed rail reinforce tourism attractiveness ? The case of the hagh speed rail between Perpignan (france) and Barcelona (Spain)," Post-Print hal-03062650, HAL.
    7. Sophie Masson & Romain Petiot, 2009. "Can the High Speed Rail reinforce tourism attractiveness? The case of the High Speed Railway section between Perpignan (France) and Barcelona (Spain)," Post-Print hal-02422659, HAL.
    8. Ping Yin & Francesca Pagliara & Alan Wilson, 2019. "How Does High-Speed Rail Affect Tourism? A Case Study of the Capital Region of China," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
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    Cited by:

    1. Li, Guangqin & Pu, Kangyun & Long, Minghui, 2023. "High-speed rail connectivity, space-time distance compression, and trans-regional tourism flows: Evidence from China's inbound tourism," Journal of Transport Geography, Elsevier, vol. 109(C).

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