An analysis of visitors' behavior in the Louvre Museum: A study using Bluetooth data

TL;DR

This study uses Bluetooth data to analyze visitor movement patterns in the Louvre Museum, revealing insights into visitor behavior and spatial distribution that can inform congestion management strategies.

Contribution

It provides a detailed analysis of visitor movement and spatial impact using anonymized Bluetooth data, highlighting behavioral similarities and differences among visitor types.

Findings

Short and long stay visitors visit similar key locations.

Long stay visitors explore more extensively.

Visitor distribution is uneven across the museum.

Abstract

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