Identification of central urban attractions based on GPS tracking data and network analysis

Abstract

This study introduces a useful methodology to identify central urban tourism attractions based on the combination of GPS tracking data and the Network Analysis of visited attractions derived from GPS data. Identifying central attractions becomes critical for city managers when it comes to planning urban facilities, managing municipal resources, locating new attractions or capturing all the potential returns. The first step of the proposed methodology is the detection of visited attractions based on GPS tracking data analysis. Then from this GPS data set a network of visited attractions is built in order to carry out a network analysis. The empirical study is performed for the city of Bilbao, a tourism destination made famous by the Guggenheim Museum. Surprisingly, our methodology leads to unexpected results: while social media content (e.g. TripAdvisor) and experts (tourism agents) point to the Guggenheim as the main tourism asset, in fact it turns out to be the Old Town the most visited place in Bilbao according to real spatial behavior detected by our method. This methodological approach can be valuable for performing decisions that are more accurate and better policies concerning urban planning and management.