Search for a command to run...
The overall objective of the project is to provide a comprehensive description of the different tools used to quantify tourism activity at three scales: international, national, and local. This dissertation focuses more specifically on the last of these levels, the local scale. By examining the cases of three cities—Paris, Lyon, and Barcelona—this research pursues two main objectives.This work focuses on two objects: tourism and quantification. Since 2018, the tourism sector has been the target of growing criticism and contestation in many cities of developed countries that have long—or more recently—become tourist destinations (Novy and Colomb, 2017). This phenomenon has been labelled “overtourism” (or surtourisme, a term that entered the French dictionary Le Robert last year). Numbers play a crucial role here. How many tourists, or how much tourism, is “too much”? Everyday nuisances, the relationship between touristification and rising prices, the appropriation of water resources, the social acceptability of tourism—these and many other issues have prompted extensive efforts to produce quantitative knowledge capable of explaining their impacts, causes, and possible solutions (Séraphin et al., 2020).However, when it comes to tourism, cities lack tools provided by National Statistical Systems (NSS). They therefore develop their own measurement instruments according to their needs and available resources. These tools are intended to quantify recent and multifactorial phenomena such as overtourism. In this context, the tourism sector has become a spearhead for the implementation, within the public sector, of a new type of data: big data, or massive datasets. Online ticketing systems, mobile phone data, accommodation booking websites, short-term rental platforms, sensors, and electronic payment terminals—this wide and ever-expanding range of tools for counting, tracking, and understanding tourist behaviour at the local and micro-local scales is continuously growing.This dissertation aims to describe these instruments and to identify the most widely used among them, which are gradually becoming indispensable for the production of figures of public interest at the local (and even national) level. Overtourism and big data thus appear to be naturally linked: to count “too many tourists,” one would need “too much data.” Yet empirical evidence reveals a political and technical reality that is, of course, far more complex than this simple assumption. This part of the dissertation will therefore highlight the complexity of the relationships between these two recent phenomena.