IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i8p3478-d349855.html
   My bibliography  Save this article

Spatial-Temporal Response Patterns of Tourist Flow under Real-Time Tourist Flow Diversion Scheme

Author

Listed:
  • Guang Yang

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    School of Transportation, Southeast University, Nanjing 211189, China)

  • Yan Han

    (Beijing Key Laboratory of Traffic Engineering (Beijing University of Technology), Beijing 100124, China)

  • Hao Gong

    (Beijing Key Laboratory of Traffic Engineering (Beijing University of Technology), Beijing 100124, China)

  • Tiantian Zhang

    (Beijing Key Laboratory of Traffic Engineering (Beijing University of Technology), Beijing 100124, China)

Abstract

This paper excavates tourist decision-making mechanism under the real-time tourist flow diversion scheme (RTFDS) and evaluates the tourist flow diversion effect of RTFDS. To meet the objectives, the stated preference survey and tourist flow survey of the Summer Palace were implemented. The tourist behavior adjustment model and tourist flow diversion simulation model were established. The results show that: (a) For core tourist spots, 66.5% and 16.5% of tourists will choose “behavior adjustment” and “no longer adjustment” under RTFDS, these behavior adjustments all shorten tourists’ residence time in tourist spots; (b) When the tourist congestion perception degree equals 4 or 5, tourists tend to adopt behavior adjustment or the individuals adopt no longer adjustment instead of cognitive adjustment when they face low tourist congestion perception degree, which equals 1 or 2; (c) When core tourist spots’ residence time is reduced by 10% and 20%, there are 60% and 73% time nodes where core tourist spots’ tourist flow density is less than or equal to the condition of null information, there are 73% and 60% time nodes where periphery tourist spots’ density is more than the condition of null information. The simulation results showed that some tourists could be guided from core tourist spots to periphery tourist spots through releasing RTFDS information. The research can provide theoretical support for the implementation of RTFDS, and alleviate the congestion inside the tourist attraction.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3478-:d:349855
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/8/3478/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/8/3478/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ko Koens & Albert Postma & Bernadett Papp, 2018. "Is Overtourism Overused? Understanding the Impact of Tourism in a City Context," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    2. 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.
    3. Patrick Bonnel & Michel Le Nir, 1998. "The quality of survey data: Telephone versus face-to-face interviews," Post-Print halshs-00140887, HAL.
    4. Vieira, José & Câmara, Gualter & Silva, Francisco & Santos, Carlos, 2019. "Airline choice and tourism growth in the Azores," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 1-6.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    6. 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.
    7. Zhixue Liao & Maozhu Jin & Peiyu Ren & Yuyan Luo, 2014. "Research on Scenic Spot’s Sustainable Development Based on a SD Model: A Case Study of the Jiuzhai Valley," Sustainability, MDPI, vol. 6(7), pages 1-13, July.
    8. 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.
    9. 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.
    10. Juan Li & Jing Ye & Qinglian He & Chunfu Shao, 2016. "A Novel Scheme to Relieve Parking Pressure at Tourist Attractions on Holidays," Sustainability, MDPI, vol. 8(2), pages 1-11, February.
    11. 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.
    12. Meleddu, Marta & Paci, Raffaele & Pulina, Manuela, 2015. "Repeated behaviour and destination loyalty," Tourism Management, Elsevier, vol. 50(C), pages 159-171.
    13. Alderighi, Marco & Gaggero, Alberto A., 2019. "Flight availability and international tourism flows," Annals of Tourism Research, Elsevier, vol. 79(C).
    14. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, November.
    15. 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.
    16. 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.
    17. 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.
    18. Horowitz, Joel L., 1991. "Reconsidering the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 433-438, December.
    19. 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.
    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. Wenbo Huang & Yanyan Chen & Shushan Chai, 2021. "Decision-Making Behavior Analysis and Empirical Study under Information Intervention in a Cold Environment," Sustainability, MDPI, vol. 13(20), pages 1-16, October.
    2. 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.
    3. Ruomu Miao & Yuxia Wang & Shuang Li, 2021. "Analyzing Urban Spatial Patterns and Functional Zones Using Sina Weibo POI Data: A Case Study of Beijing," Sustainability, MDPI, vol. 13(2), pages 1-15, January.

    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. 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.
    3. 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.
    4. 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.
    5. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    6. Andani, I Gusti Ayu & La Paix Puello, Lissy & Geurs, Karst, 2021. "Modelling effects of changes in travel time and costs of toll road usage on choices for residential location, route and travel mode across population segments in the Jakarta-Bandung region, Indonesia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 81-102.
    7. 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.
    8. Kemperman, Astrid, 2021. "A review of research into discrete choice experiments in tourism: Launching the Annals of Tourism Research Curated Collection on Discrete Choice Experiments in Tourism," Annals of Tourism Research, Elsevier, vol. 87(C).
    9. Zhifeng Gao & Ted C. Schroeder, 2009. "Consumer responses to new food quality information: are some consumers more sensitive than others?," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 339-346, May.
    10. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    11. 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.
    12. Potoglou, Dimitris & Palacios, Juan & Feijoo, Claudio & Gómez Barroso, Jose-Luis, 2015. "The supply of personal information: A study on the determinants of information provision in e-commerce scenarios," 26th European Regional ITS Conference, Madrid 2015 127174, International Telecommunications Society (ITS).
    13. Sant'Anna, Ana Claudia & Bergtold, Jason & Shanoyan, Aleksan & Caldas, Marcellus & Granco, Gabriel, 2021. "Deal or No Deal? Analysis of Bioenergy Feedstock Contract Choice with Multiple Opt-out Options and Contract Attribute Substitutability," 2021 Conference, August 17-31, 2021, Virtual 315289, International Association of Agricultural Economists.
    14. 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.
    15. 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.
    16. Kesternich, Iris & Heiss, Florian & McFadden, Daniel & Winter, Joachim, 2013. "Suit the action to the word, the word to the action: Hypothetical choices and real decisions in Medicare Part D," Journal of Health Economics, Elsevier, vol. 32(6), pages 1313-1324.
    17. David Hensher & John Rose & Zheng Li, 2012. "Does the choice model method and/or the data matter?," Transportation, Springer, vol. 39(2), pages 351-385, March.
    18. Qin, Pin & Carlsson, Fredrik & Xu, Jintao, 2009. "Forestland Reform in China: What do the Farmers Want? A Choice Experiment on Farmers’ Property Rights Preferences," Working Papers in Economics 370, University of Gothenburg, Department of Economics.
    19. Clark, Andrew E. & Senik, Claudia & Yamada, Katsunori, 2017. "When experienced and decision utility concur: The case of income comparisons," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 70(C), pages 1-9.
    20. Ping Qin & Fredrik Carlsson & Jintao Xu, 2011. "Forest Tenure Reform in China: A Choice Experiment on Farmers’ Property Rights Preferences," Land Economics, University of Wisconsin Press, vol. 87(3), pages 473-487.

    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:gam:jsusta:v:12:y:2020:i:8:p:3478-:d:349855. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.