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A Study of Tourists’ Holiday Rush-Hour Avoidance Travel Behavior Considering Psychographic Segmentation

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  • Haiyan Zhu

    (College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
    Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China
    School of Traffic, Qinghai Nationalities University, Xining 810007, China)

  • Hongzhi Guan

    (College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
    Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China)

  • Yan Han

    (Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China)

  • Wanying Li

    (Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China)

Abstract

Tourists are confronted with congestion caused by concentrated travel during public holidays. In order to guide tourists to make voluntary changes regarding their travel times during holidays, this paper focuses on exploring holiday rush-hour avoidance travel behavior (HRATB) considering psychological factors. First, based on the theory of planned behavior, the effects of psychological factors including attitude, subjective norm, and perceived behavior control on holiday avoidance travel intention and behavior were quantitatively analyzed by the structural equation model. Second, according to those three subjective psychological factors and the three objective factors of age, monthly income, and tourist group, the segmentation method of the latent class model was adopted to explore tourists’ preferences with regard to HRATB. Finally, an empirical analysis was carried out through questionnaire data. The results show that attitude, subjective norm, and perceived behavior control have significant impacts on intention and behavior with regard to holiday avoidance travel. There are significant differences in psychological observation variables such as rush-hour avoidance travel intention, attitude and subjective norm among the four segments of tourists, and cost sensitivity. In addition, this paper puts forward some countermeasures and suggestions for the four types of tourists. Conclusions provide a theoretical basis for formulating travel measures to attract different types of tourists.

Suggested Citation

  • Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2019. "A Study of Tourists’ Holiday Rush-Hour Avoidance Travel Behavior Considering Psychographic Segmentation," Sustainability, MDPI, vol. 11(13), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:13:p:3755-:d:246978
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    as
    1. Shiftan, Yoram & Outwater, Maren L. & Zhou, Yushuang, 2008. "Transit market research using structural equation modeling and attitudinal market segmentation," Transport Policy, Elsevier, vol. 15(3), pages 186-195, May.
    2. Yan Han & Hongzhi Guan & Jiaying Duan, 2014. "Tour Route Multiobjective Optimization Design Based on the Tourist Satisfaction," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-8, January.
    3. Ben-Elia, Eran & Ettema, Dick, 2009. "Carrots versus sticks: Rewarding commuters for avoiding the rush-hour--a study of willingness to participate," Transport Policy, Elsevier, vol. 16(2), pages 68-76, March.
    4. Stephane Hess & John Polak & Andrew Daly & Geoffrey Hyman, 2007. "Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands," Transportation, Springer, vol. 34(2), pages 213-238, March.
    5. Teichert, Thorsten & Shehu, Edlira & von Wartburg, Iwan, 2008. "Customer segmentation revisited: The case of the airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 227-242, January.
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Xiaomei Lin & Yusak O. Susilo & Chunfu Shao & Chengxi Liu, 2018. "The Implication of Road Toll Discount for Mode Choice: Intercity Travel during the Chinese Spring Festival Holiday," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    8. Zhang, Zheng & Fujii, Hidemichi & Managi, Shunsuke, 2014. "How does Commuting Behavior Change Due to Incentives? An Empirical Study of the Beijing Subway System," MPRA Paper 54691, University Library of Munich, Germany.
    9. Pronello, Cristina & Camusso, Cristian, 2011. "Travellers’ profiles definition using statistical multivariate analysis of attitudinal variables," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1294-1308.
    10. Wen, Chieh-Hua & Lai, Shan-Ching, 2010. "Latent class models of international air carrier choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(2), pages 211-221, March.
    11. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    12. Hess, Stephane & Daly, Andrew & Rohr, Charlene & Hyman, Geoff, 2007. "On the development of time period and mode choice models for use in large scale modelling forecasting systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 802-826, November.
    13. Molin, Eric & Mokhtarian, Patricia & Kroesen, Maarten, 2016. "Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 14-29.
    14. Wang, Bobin & Shao, Chunfu & Li, Juan & Weng, Jinxian & Ji, Xun, 2015. "Holiday travel behavior analysis and empirical study under integrated multimodal travel information service," Transport Policy, Elsevier, vol. 39(C), pages 21-36.
    15. Yan Han & Wanying Li & Shanshan Wei & Tiantian Zhang, 2018. "Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    16. Bao, Yue & Xiao, Feng & Gao, Zaihan & Gao, Ziyou, 2017. "Investigation of the traffic congestion during public holiday and the impact of the toll-exemption policy," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 58-81.
    17. Alegre, Joaquín & Mateo, Sara & Pou, Llorenç, 2011. "A latent class approach to tourists’ length of stay," Tourism Management, Elsevier, vol. 32(3), pages 555-563.
    18. Salomon, Ilan & Mokhtarian, Patricia L., 1997. "Coping with Congestion: Understanding the Gap Between Policy Assumptions and Behavior," University of California Transportation Center, Working Papers qt4bh3b670, University of California Transportation Center.
    19. Shelat, Sanmay & Huisman, Raymond & van Oort, Niels, 2018. "Analysing the trip and user characteristics of the combined bicycle and transit mode," Research in Transportation Economics, Elsevier, vol. 69(C), pages 68-76.
    20. Masiero, Lorenzo & Qiu, Richard T.R., 2018. "Modeling reference experience in destination choice," Annals of Tourism Research, Elsevier, vol. 72(C), pages 58-74.
    21. Cristina Pronello & Cristian Camusso, 2011. "Travellers’ profiles definition using statistical multivariate analysis of attitudinal variables," Post-Print halshs-01084027, HAL.
    22. Qian Jin & Hui Hu & Philip Kavan, 2016. "Factors Influencing Perceived Crowding of Tourists and Sustainable Tourism Destination Management," Sustainability, MDPI, vol. 8(10), pages 1-17, September.
    23. Wen, Chieh-Hua & Yeh, Yao, 2017. "Modeling air travelers’ choice of flight departure and return dates on long holiday weekends," Journal of Air Transport Management, Elsevier, vol. 65(C), pages 220-225.
    24. Thorhauge, Mikkel & Cherchi, Elisabetta & Rich, Jeppe, 2016. "How flexible is flexible? Accounting for the effect of rescheduling possibilities in choice of departure time for work trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 177-193.
    25. Yang, Liya & Shen, Qing & Li, Zhibin, 2016. "Comparing travel mode and trip chain choices between holidays and weekdays," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 273-285.
    26. Veronique Van Acker & Frank Witlox & Bert Van Wee, 2007. "The Effects of the Land Use System on Travel Behavior: A Structural Equation Modeling Approach," Transportation Planning and Technology, Taylor & Francis Journals, vol. 30(4), pages 331-353, May.
    27. Oppewal, Harmen & Huybers, Twan & Crouch, Geoffrey I., 2015. "Tourist destination and experience choice: A choice experimental analysis of decision sequence effects," Tourism Management, Elsevier, vol. 48(C), pages 467-476.
    28. Ben-Elia, Eran & Ettema, Dick, 2011. "Rewarding rush-hour avoidance: A study of commuters' travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(7), pages 567-582, August.
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