Tracking Tourist Spatial-Temporal Behavior in Urban Places, A Methodological Overview and GPS Case Study

  • Lenka Kellner
  • Roman EggerEmail author
Conference paper


The tourism industry is inundated with tourists who have diverse profiles and choose to spend their time in different ways when visiting urban destinations. Understanding the so-called spatial-temporal behavior of tourists would include, a study of their movement within the space, the duration of time they spend at any given location and the services they utilize, all of which can provide valuable information not only to Destination Management Organizations, but also to all stakeholders involved in tourism businesses and the field of tourism research. While spatial-temporal behavior of tourists can be monitored and measured by several tracking methods, no general overview on the methodological approaches has been provided so far. Therefore, this research paper attempts to investigate and describe the possible tracking methods, while outlining the associated advantages and disadvantages of tracking tourist behavior in an urban place. Since using the Global Positioning System (GPS) has proven to be the most promising method in measuring tourist movement patterns in an urban destination, a case study undertaken in Salzburg City will highlight the benefits and limitations of using the GPS as a tracking technique. Understanding all the possible tracking methods and their advantages and disadvantages will serve as a theoretical basis for the future monitoring of tourist spatial-temporal behavior in urban destinations and allow researchers to select the appropriate approach for their project.


Urban Tourism Spatial-temporal Behavior Tracking Methods GPS Tracking 


  1. Asakura, Y., & Hato, E. (2004). Tracking survey for individual travel behaviour using mobile communication instruments. Transportation Research Part C: Emerging Technologies, 12(3-4), 273–291.CrossRefGoogle Scholar
  2. Baker-Shenk, C. L., & Cokely, D. (1991). American Sign Language: A teacher’s resource text on grammar and culture. Washington, DC: Gallaudet University Press.Google Scholar
  3. Becker, C. (2000). Freizeit und Tourismus in Deutschland. Nationalatlas der Bundesrepublik Deutschland, 10.Google Scholar
  4. Dejbakhsh, S. (2008). Determining the Spatial Needs of International Tourists. Victoria (MA): RMIT University Melbourne.Google Scholar
  5. Edwards, D., Giffin, T., & Hayllar, B. (2008). Urban tourism research: Developing and agenda. Annals of Tourism Research, 35(4), 1033–1052.CrossRefGoogle Scholar
  6. Geocommunity (2008). Quantum GIS software: Application user review. [WWW] Available from: [Accessed 27/06/2015].
  7. Glaeser, D. (2006). Crisis management in the tourism industry. London: Routledge.Google Scholar
  8. Karski, A. (1990). Urban tourism: A key to urban regeneration. The Planner, 76(13), 15–17.Google Scholar
  9. Klima, E., & Bellugi, U. (1979). The sign of language. Cambridge, MA: Harvard University Pres.Google Scholar
  10. Lankford et al. (2004). Cognitive mapping: An application for trail management. In: Proceedings of the 2004 Northeastern Recreation Research Symposium (pp. 378–384).Google Scholar
  11. Lew, A., Hall, C. M., & Williams, A. (2004). Companion to tourism. Oxford: Blackwell Publishers.CrossRefGoogle Scholar
  12. MCKercher, B., & Lew, A. (2006). Modeling tourist movements: A local destination analysis. Annals of Tourism Research, 33(2), 403–423.CrossRefGoogle Scholar
  13. Merriam-Webster (2015). [WWW]. Merriam-Webster Online Language Center. Available from: [Accessed 30/05/2015].
  14. Millonig, A., & Gartner, G. (2008). Exploring human spatio-temporal behavior patterns. Workshop on Behaviour Monitoring and Interpretation BMI ‘08 in Conjunction with 31st German Conference on Artificial Intelligence, Kaiserslautern.Google Scholar
  15. Nielsen, N. C., & Blichfeldt, B. S. (2009). Where do they go? Monitoring tourist mobility at the destination. In: 18th Nordic Symposium in Tourism and Hospitality Rsearch. University of Southern Denmark.Google Scholar
  16. O’Connor, A., Zerger, A., & Itami, R. (2005). Geo-Temporal tracking and analysis of tourist movement. Mathematics and Computers in Simulation, 69(1–2), 135–150.CrossRefGoogle Scholar
  17. Parrocco, A. M., & De Cantis, S. (2012). Multi-destination trips and tourism statistics: Empirical evidences in Sicily. Econoemics, 6(44), 1–28.Google Scholar
  18. Richards, G., & Musters, W. (2010). Cultural torusim research methods. Wallingford: CABI Publishing.CrossRefGoogle Scholar
  19. Schlegel, V. (2015). BigData Services: The mobile revolution in tourism: What are and will be the factors of success? [online video]. ENTER 2015 eTourism Conference-1st Keynote Session (2015). Available from: [Accessed 05/07/2015].
  20. Seepold, R. (2015). Follow the main routes of tourists. Ubiquitous Computing Laboratory. [WWW]. Available from: [Accessed 20/06/2015].
  21. Shaw, G., Agarwal, S., & Bull, P. (2000). Tourism consumption and tourism behaviour: A British perspective. Tourism Geographies, 2(3), 264–289.CrossRefGoogle Scholar
  22. Shoval, N., & Isaacson, M. (2007). Tracking tourists in the digital age. Annals of Tourism Research, 34(1), 141–159.CrossRefGoogle Scholar
  23. Thornton, P., Williams, A., & Shaw, W. G. (1997). Revisiting time-space diaries: An exploratory case study of tourist behavior in Cornwall, England. Environment and Planning A, 29, 1847–1867.CrossRefGoogle Scholar
  24. Visit-Salzburg (2015). Salzburg, where the hills are alive. [WWW]. Available from: [Accessed 21/06/2015].
  25. Zoltan, J. (2014). Understanding tourist behavior in terms of activeness and intra-destination movement patterns for managing tourism experience. Unpublished thesis (PhD), Università della Svizzera italiana.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Salzburg University of Applied SciencesUrstein Süd 1Austria

Personalised recommendations