IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v134y2020icp130-151.html
   My bibliography  Save this article

Holiday travel behavior analysis and empirical study with Integrated Travel Reservation Information usage

Author

Listed:
  • Han, Yan
  • Zhang, Tiantian
  • Wang, Meng

Abstract

The efficient travel demand management is more important than traffic congestion control. Currently, tour reservation system (TRS) based on demand response has become a significant part of travel demand management. The Integrated Travel Reservation Information (ITRI) released by TRS plays an important role in the decision-making process of tourist’s holiday travel destination and departure time choice behaviors, which is seldom investigated. To fill this gap, this paper explored the feedback mechanism among the ITRI usage, tourism utility of various alternatives and tourist decision-making behavior based on the Engel-Kollat-Blackwell (EKB) consumer purchase decision-making model. To quantify the impact of ITRI on travel behavior, a revealed preference and stated preference survey were designed and carried out in China. The data show about 80% of tourists are concerned about the information of tickets sold ratio. Nested Logit (NL) model for the joint choice of destination and departure time was established, which accounted for the impact of TRS and ITRI on the utility of alternatives. The NL model results reveal that tourist’s age, education level, number of visits, ITRI content, ITRI query method and the tickets sold ratio have significant effects on destination and departure time choice. Especially, sensitivity analysis results reveal that when the tickets sold ratio reaches 65%, 75%, 85% and 95% respectively, every 1% growth of tickets sold ratio is accompanied by 2.858%, 2.877%, 3.015% and 3.362% increase in the probabilities of traveling during non-holiday periods. Therefore, tourists are encouraged to travel during non-holiday periods by tickets sold information release, which can achieve the rational allocation of tourism resources and enable to make maximum use of tourism resources. Further, the results can provide a basic data for development of the tourism demand management and equilibrium of the tourist’s spatial and temporal distribution.

Suggested Citation

  • Han, Yan & Zhang, Tiantian & Wang, Meng, 2020. "Holiday travel behavior analysis and empirical study with Integrated Travel Reservation Information usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 130-151.
    • Handle: RePEc:eee:transa:v:134:y:2020:i:c:p:130-151
    DOI: 10.1016/j.tra.2020.02.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096585641930494X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2020.02.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Bobin & Shao, Chunfu & Ji, Xun, 2017. "Dynamic analysis of holiday travel behaviour with integrated multimodal travel information usage: A life-oriented approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 255-280.
    2. Herriges, Joseph A. & Kling, Catherine L., 1996. "Testing the consistency of nested logit models with utility maximization," Economics Letters, Elsevier, vol. 50(1), pages 33-39, January.
    3. Koppelman, Frank S. & Wen, Chieh-Hua, 2000. "The paired combinatorial logit model: properties, estimation and application," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 75-89, February.
    4. Qin, Huanmei & Gao, Jianqiang & Zhang, Guohui & Chen, Yanyan & Wu, Songhua, 2017. "Nested logit model formation to analyze airport parking behavior based on stated preference survey studies," Journal of Air Transport Management, Elsevier, vol. 58(C), pages 164-175.
    5. Yang, Hai & Liu, Wei & Wang, Xiaolei & Zhang, Xiaoning, 2013. "On the morning commute problem with bottleneck congestion and parking space constraints," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 106-118.
    6. 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.
    7. Yunqiang Xue & Hongzhi Guan & Jonathan Corey & Heng Wei & Hai Yan, 2017. "Quantifying a Financially Sustainable Strategy of Public Transport: Private Capital Investment Considering Passenger Value," Sustainability, MDPI, vol. 9(2), pages 1-20, February.
    8. Jones, Stewart & Hensher, David A., 2007. "Modelling corporate failure: A multinomial nested logit analysis for unordered outcomes," The British Accounting Review, Elsevier, vol. 39(1), pages 89-107.
    9. 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.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    11. Wang, Yi-Shun & Li, Hsien-Ta & Li, Ci-Rong & Zhang, Ding-Zhong, 2016. "Factors affecting hotels' adoption of mobile reservation systems: A technology-organization-environment framework," Tourism Management, Elsevier, vol. 53(C), pages 163-172.
    12. van Cranenburgh, S. & Chorus, C.G. & van Wee, B., 2014. "Vacation behaviour under high travel cost conditions – A stated preference of revealed preference approach," Tourism Management, Elsevier, vol. 43(C), pages 105-118.
    13. Xiao, Yu & Lo, Hong K., 2016. "Day-to-day departure time modeling under social network influence," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 54-72.
    14. Juan Antonio Carrasco & Juan de Dios Ortúzar, 2002. "Review and assessment of the nested logit model," Transport Reviews, Taylor & Francis Journals, vol. 22(2), pages 197-218, January.
    15. Hensher, David A. & Greene, William H., 2002. "Specification and estimation of the nested logit model: alternative normalisations," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 1-17, January.
    16. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    17. Starr Roxanne Hiltz & Kenneth Johnson, 1990. "User Satisfaction with Computer-Mediated Communication Systems," Management Science, INFORMS, vol. 36(6), pages 739-764, June.
    18. Anciaes, Paulo & Metcalfe, Paul & Heywood, Chris & Sheldon, Rob, 2019. "The impact of fare complexity on rail demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 224-238.
    19. Horowitz, Joel L., 1991. "Reconsidering the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 433-438, December.
    20. Joseph C. Bonnice, 1985. "Application of the Engel, Kollat and Blackwell Model to Consumers of Automobile Insurance," Journal of Insurance Issues, Western Risk and Insurance Association, vol. 8(1), pages 23-41.
    21. Richard Zinbarg & William Revelle & Iftah Yovel & Wen Li, 2005. "Cronbach’s α, Revelle’s β, and Mcdonald’s ω H : their relations with each other and two alternative conceptualizations of reliability," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 123-133, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiaoe Wang & Fan Xiao & Frédéric Dobruszkes & Wei Wang, 2023. "Seasonality of flights in China: Spatial heterogeneity and its determinants," ULB Institutional Repository 2013/355192, ULB -- Universite Libre de Bruxelles.
    2. Aqeela Saleem & Javed Aslam & Yun Bae Kim & Shazia Nauman & Nokhaiz Tariq Khan, 2022. "Motives towards e-Shopping Adoption among Pakistani Consumers: An Application of the Technology Acceptance Model and Theory of Reasoned Action," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
    3. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2022. "Study on Peak Travel Avoidance Behavior of Car Travelers during Holidays," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    4. Wang, Jiaoe & Xiao, Fan & Dobruszkes, Frédéric & Wang, Wei, 2023. "Seasonality of flights in China: Spatial heterogeneity and its determinants," Journal of Air Transport Management, Elsevier, vol. 108(C).
    5. Marta Borowska-Stefańska & Michał Kowalski & Paulina Kurzyk & Alireza Sahebgharani & Szymon Wiśniewski, 2022. "Spatiotemporal Changeability of the Load of the Urban Road Transport System under Permanent and Short-Term Legal and Administrative Retail Restrictions," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    6. Yuzong Zhao & Hui Wang & Zhen Guo & Mingli Huang & Yongtao Pan & Yongrui Guo, 2022. "Online Reservation Intention of Tourist Attractions in the COVID-19 Context: An Extended Technology Acceptance Model," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
    7. Lin-Lin Xue & Ching-Cheng Shen & Alastair M. Morrison & Li-Wen Kuo, 2021. "Online Tourist Behavior of the Net Generation: An Empirical Analysis in Taiwan Based on the AISAS Model," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    8. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2020. "Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays," Sustainability, MDPI, vol. 12(24), pages 1-29, December.
    9. Guang Yang & Yan Han & Hao Gong & Tiantian Zhang, 2020. "Spatial-Temporal Response Patterns of Tourist Flow under Real-Time Tourist Flow Diversion Scheme," Sustainability, MDPI, vol. 12(8), pages 1-28, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2022. "Study on Peak Travel Avoidance Behavior of Car Travelers during Holidays," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    2. Guang Yang & Yan Han & Hao Gong & Tiantian Zhang, 2020. "Spatial-Temporal Response Patterns of Tourist Flow under Real-Time Tourist Flow Diversion Scheme," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    3. Batley, Richard & Hess, Stephane, 2016. "Testing for regularity and stochastic transitivity using the structural parameter of nested logit," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 355-376.
    4. Honora Smith & Christine Currie & Pornpimol Chaiwuttisak & Andreas Kyprianou, 2018. "Patient choice modelling: how do patients choose their hospitals?," Health Care Management Science, Springer, vol. 21(2), pages 259-268, June.
    5. Roberto Basile & Davide Castellani & Antonello Zanfei, 2009. "National boundaries and the location of multinational firms in Europe," Papers in Regional Science, Wiley Blackwell, vol. 88(4), pages 733-748, November.
    6. Rinaldo Brau & Matteo Lippi Bruni, 2008. "Eliciting the demand for long‐term care coverage: a discrete choice modelling analysis," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 411-433, March.
    7. Bliemer, Michiel C.J. & Rose, John M. & Hensher, David A., 2009. "Efficient stated choice experiments for estimating nested logit models," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 19-35, January.
    8. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    9. Stephane Hess & Andrew Daly & Richard Batley, 2018. "Revisiting consistency with random utility maximisation: theory and implications for practical work," Theory and Decision, Springer, vol. 84(2), pages 181-204, March.
    10. Bunch, David S. & Rocke, David M., 2016. "Variance-component-based nested logit specifications: Improved formulation, and practical microsimulation of random disturbance terms," Journal of choice modelling, Elsevier, vol. 21(C), pages 30-35.
    11. Bobin Wang & Chunfu Shao & Xun Ji, 2017. "Influencing Mechanism Analysis of Holiday Activity–Travel Patterns on Transportation Energy Consumption and Emissions in China," Energies, MDPI, vol. 10(7), pages 1-20, July.
    12. Birolini, Sebastian & Cattaneo, Mattia & Malighetti, Paolo & Morlotti, Chiara, 2020. "Integrated origin-based demand modeling for air transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    13. Ren, Yilong & Lan, Zhengxing & Yu, Haiyang & Jiao, Gangxin, 2022. "Analysis and prediction of charging behaviors for private battery electric vehicles with regular commuting: A case study in Beijing," Energy, Elsevier, vol. 253(C).
    14. Yamada, Katsunori & Sato, Masayuki, 2013. "Another avenue for anatomy of income comparisons: Evidence from hypothetical choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 89(C), pages 35-57.
    15. Mtimet, Nadhem & Ujiie, Kiyokazu & Kashiwagi, Kenichi & Zaibet, Lokman & Nagaki, Masakazu, 2011. "The effects of Information and Country of Origin on Japanese Olive Oil Consumer Selection," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114642, European Association of Agricultural Economists.
    16. Choi, Andy S., 2013. "Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay," Ecological Economics, Elsevier, vol. 88(C), pages 97-107.
    17. Doherty, Edel & Campbell, Danny, 2011. "Demand for improved food safety and quality: a cross-regional comparison," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108791, Agricultural Economics Society.
    18. Schleich, Joachim & Faure, Corinne & Guetlein, Marie-Charlotte & Tu, Gengyang, 2020. "Conveyance, envy, and homeowner choice of appliances," Energy Economics, Elsevier, vol. 89(C).
    19. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    20. Veneziani, Mario & Sckokai, Paolo & Moro, Daniele, 2012. "Consumers’ willingness to pay for a functional food," 2012 First Congress, June 4-5, 2012, Trento, Italy 124101, Italian Association of Agricultural and Applied Economics (AIEAA).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:134:y:2020:i:c:p:130-151. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.