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Understanding the tourist mobility using GPS: Where is the next place?

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  • Zheng, Weimin
  • Huang, Xiaoting
  • Li, Yuan

Abstract

Understanding the mobility of tourists plays a fundamental role in the administration and design of tourist destinations, planning of on-site movement and marketing of attractions. In this paper, we focus on how to accurately predict the tourist's next location within a given attraction. A heuristic method based on data mining is proposed, which considers the trajectory of a focal tourist and the movements of past visitors. To evaluate the performance of the proposed method, a case study was conducted at the Summer Palace in Beijing, China. We collected movement information from tourists using GPS tracking technology, and the results of an independent samples t-test indicate that the proposed method indeed performs significantly better than existing methods. We further explore the potential applications of the proposed method. Our results significantly contribute to enhancing the level of personalized location-based service, tourist attraction administration, and real-time crowd control.

Suggested Citation

  • Zheng, Weimin & Huang, Xiaoting & Li, Yuan, 2017. "Understanding the tourist mobility using GPS: Where is the next place?," Tourism Management, Elsevier, vol. 59(C), pages 267-280.
    • Handle: RePEc:eee:touman:v:59:y:2017:i:c:p:267-280
    DOI: 10.1016/j.tourman.2016.08.009
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    1. Lin, Ling-Zhong & Yeh, Huery-Ren, 2013. "Analysis of tour values to develop enablers using an interpretive hierarchy-based model in Taiwan," Tourism Management, Elsevier, vol. 34(C), pages 133-144.
    2. Xia, Jianhong (Cecilia) & Zeephongsekul, Panlop & Arrowsmith, Colin, 2009. "Modelling spatio-temporal movement of tourists using finite Markov chains," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1544-1553.
    3. Michael Batty, 1997. "Predicting where we walk," Nature, Nature, vol. 388(6637), pages 19-20, July.
    4. Dong, Ming & He, David, 2007. "Hidden semi-Markov model-based methodology for multi-sensor equipment health diagnosis and prognosis," European Journal of Operational Research, Elsevier, vol. 178(3), pages 858-878, May.
    5. Smallwood, Claire B. & Beckley, Lynnath E. & Moore, Susan A., 2012. "An analysis of visitor movement patterns using travel networks in a large marine park, north-western Australia," Tourism Management, Elsevier, vol. 33(3), pages 517-528.
    6. O’Connor, A. & Zerger, A. & Itami, B., 2005. "Geo-temporal tracking and analysis of tourist movement," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 69(1), pages 135-150.
    7. Xia, Jianhong (Cecilia) & Evans, Fiona H. & Spilsbury, Katrina & Ciesielski, Vic & Arrowsmith, Colin & Wright, Graeme, 2010. "Market segments based on the dominant movement patterns of tourists," Tourism Management, Elsevier, vol. 31(4), pages 464-469.
    8. Xia, Jianhong (Cecilia) & Zeephongsekul, Panlop & Packer, David, 2011. "Spatial and temporal modelling of tourist movements using Semi-Markov processes," Tourism Management, Elsevier, vol. 32(4), pages 844-851.
    9. Orellana, Daniel & Bregt, Arnold K. & Ligtenberg, Arend & Wachowicz, Monica, 2012. "Exploring visitor movement patterns in natural recreational areas," Tourism Management, Elsevier, vol. 33(3), pages 672-682.
    10. De Cantis, Stefano & Ferrante, Mauro & Kahani, Alon & Shoval, Noam, 2016. "Cruise passengers' behavior at the destination: Investigation using GPS technology," Tourism Management, Elsevier, vol. 52(C), pages 133-150.
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    Cited by:

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    3. Ana Muñoz-Mazón & Laura Fuentes-Moraleda & Angela Chantre-Astaiza & Marlon-Felipe Burbano-Fernandez, 2019. "The Study of Tourist Movements in Tourist Historic Cities: A Comparative Analysis of the Applicability of Four Different Tools," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    4. Yu, Ling & Zhao, Pengjun & Tang, Junqing & Pang, Liang, 2023. "Changes in tourist mobility after COVID-19 outbreaks," Annals of Tourism Research, Elsevier, vol. 98(C).
    5. Worapot Sirirak & Rapeepan Pitakaso, 2018. "Marketplace Location Decision Making and Tourism Route Planning," Administrative Sciences, MDPI, vol. 8(4), pages 1-25, November.
    6. José Ruiz-Meza & Julio Brito & Jairo R. Montoya-Torres, 2021. "Multi-Objective Fuzzy Tourist Trip Design Problem with Heterogeneous Preferences and Sustainable Itineraries," Sustainability, MDPI, vol. 13(17), pages 1-22, August.
    7. Linus W. Dietz & Avradip Sen & Rinita Roy & Wolfgang Wörndl, 2020. "Mining trips from location-based social networks for clustering travelers and destinations," Information Technology & Tourism, Springer, vol. 22(1), pages 131-166, March.
    8. Tiantian Zhang & Weicheng Hua & Yannan Xu, 2019. "“Seeing” or “Being Seen”: Research on the Sight Line Design in the Lion Grove Based on Visitor Temporal–Spatial Distribution and Space Syntax," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    9. Kang, Sanghoon, 2016. "Associations between space–time constraints and spatial patterns of travels," Annals of Tourism Research, Elsevier, vol. 61(C), pages 127-141.
    10. Sehrish Malik & DoHyeun Kim, 2019. "Optimal Travel Route Recommendation Mechanism Based on Neural Networks and Particle Swarm Optimization for Efficient Tourism Using Tourist Vehicular Data," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    11. Angela Chantre-Astaiza & Laura Fuentes-Moraleda & Ana Muñoz-Mazón & Gustavo Ramirez-Gonzalez, 2019. "Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability," Sustainability, MDPI, vol. 11(17), pages 1-32, August.
    12. José Ruiz-Meza & Jairo R. Montoya-Torres, 2021. "Tourist trip design with heterogeneous preferences, transport mode selection and environmental considerations," Annals of Operations Research, Springer, vol. 305(1), pages 227-249, October.
    13. Zheng, Weimin & Liao, Zhixue & Qin, Jing, 2017. "Using a four-step heuristic algorithm to design personalized day tour route within a tourist attraction," Tourism Management, Elsevier, vol. 62(C), pages 335-349.
    14. Liguo Lou & Zilu Tian & Joon Koh, 2017. "Tourist Satisfaction Enhancement Using Mobile QR Code Payment: An Empirical Investigation," Sustainability, MDPI, vol. 9(7), pages 1-14, July.
    15. Ruiz-Meza, José & Montoya-Torres, Jairo R., 2022. "A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines," Operations Research Perspectives, Elsevier, vol. 9(C).
    16. Pattama Krataithong & Chutiporn Anutariya & Marut Buranarach, 2022. "A Taxi Trajectory and Social Media Data Management Platform for Tourist Behavior Analysis," Sustainability, MDPI, vol. 14(8), pages 1-18, April.

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