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An Analysis of Visitors' Behavior in the Louvre Museum: A Study Using Bluetooth Data

Author

Listed:
  • Yuji Yoshimura
  • Stanislav Sobolevsky
  • Carlo Ratti
  • Fabien Girardin

    (Near Future Laboratory, CP242, 3960 Sierre, Switzerland)

  • Juan Pablo Carrascal
  • Josep Blat
  • Roberta Sinatra

    (Center for Complex Network Research and Department of Physics, Northeastern University, 110 Forsyth Street, Boston, MA 02115, USA)

Abstract

Museums often suffer from so-called ‘hypercongestion’, wherein the number of visitors exceeds the capacity of the physical space of the museum. This can potentially be detrimental to the quality of visitors' experiences, through disturbance by the behavior and presence of other visitors. Although this situation can be mitigated by managing visitors' flow between spaces, a detailed analysis of visitor movement is required to realize fully and apply a proper solution to the problem. In this paper we analyze visitors' sequential movements, the spatial layout, and the relationship between them in a large- scale art museum—The Louvre Museum—using anonymized data collected through noninvasive Bluetooth sensors. This enables us to unveil some features of visitor behavior and spatial impact that shed some light on the mechanisms of museum overcrowding. The analysis reveals that the visiting styles of short-stay and long-stay visitors are not as significantly different as one might expect. Both types of visitors tend to visit a similar number of key locations in the museum while the longer-stay visitors just tend to do so more time extensively. In addition, we reveal that some ways of exploring the museum appear frequently for both types of visitors, although long-stay visitors might be expected to diversify much more, given the greater time spent in the museum. We suggest that these similarities and dissimilarities make for an uneven distribution of the number of visitors in the museum space. The findings increase the understanding of the unknown behaviors of visitors, which is key to improving the museum's environment and visitor experience.

Suggested Citation

  • Yuji Yoshimura & Stanislav Sobolevsky & Carlo Ratti & Fabien Girardin & Juan Pablo Carrascal & Josep Blat & Roberta Sinatra, 2014. "An Analysis of Visitors' Behavior in the Louvre Museum: A Study Using Bluetooth Data," Environment and Planning B, , vol. 41(6), pages 1113-1131, December.
  • Handle: RePEc:sae:envirb:v:41:y:2014:i:6:p:1113-1131
    DOI: 10.1068/b130047p
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    References listed on IDEAS

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    1. Carlo Ratti & Stanislav Sobolevsky & Francesco Calabrese & Clio Andris & Jonathan Reades & Mauro Martino & Rob Claxton & Steven H Strogatz, 2010. "Redrawing the Map of Great Britain from a Network of Human Interactions," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-6, December.
    2. Asakura, Yasuo & Iryo, Takamasa, 2007. "Analysis of tourist behaviour based on the tracking data collected using a mobile communication instrument," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(7), pages 684-690, August.
    3. Sam K. Hui & Eric T. Bradlow & Peter S. Fader, 2009. "Testing Behavioral Hypotheses Using an Integrated Model of Grocery Store Shopping Path and Purchase Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 36(3), pages 478-493.
    4. Stanislav Sobolevsky & Izabela Sitko & Sebastian Grauwin & Remi Tachet des Combes & Bartosz Hawelka & Juan Murillo Arias & Carlo Ratti, 2014. "Mining Urban Performance: Scale-Independent Classification of Cities Based on Individual Economic Transactions," Papers 1405.4301, arXiv.org.
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    Cited by:

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    2. Raun, Janika & Ahas, Rein & Tiru, Margus, 2016. "Measuring tourism destinations using mobile tracking data," Tourism Management, Elsevier, vol. 57(C), pages 202-212.

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