Abstract

Policy makers and tourism developers must understand visitors’ mobility behavior and how they consume space and tourism resources in order to set up sustainable cultural tourism destinations. With this in mind, it should also be pointed out that the mobility patterns of tourists in urban destinations are mainly located in the city center (spatial centrality), the analysis of which enables us to define “how central” the resources (museums, monuments, etc.) are and what the interactions between them are. Comprehending which factors influence visitors’ urban mobility behavior is key to understanding tourists’ consumption of space and their connections with the tourism assets of the city. Furthermore, when tourists visit a destination, they make a mental representation of the destination, constructing a mental map of it. Thus, tourists consume not only spaces but also the image of a city/destination. Moreover, the latter influences the former. The quality of surrounding architecture and urbanism plays a crucial role in enhancing the experiential value of a destination and influencing space consumption preferences. Clearly, visitors are more likely to use/consume environments that are easily navigated and mentally legible. In order to explore these patterns, a real experiment was performed based on visitor behavior in the city of Bilbao. In addition, the central places of Bilbao were determined and an analysis of the spatial interaction between cultural sites was performed, making use of a new methodology based on GPS technologies, network analysis, and surveys. This methodology is the main contribution of this work. The results suggest that (1) easy mobility (walkability, accessibility, different transport modes) of the visited space facilitates the tourist experience; (2) simple and eligible mental maps of the city that are easily perceived by visitors facilitate the rapid consumption of the tourist destination; and (3) the centrality of the tourism resources affects the mobility of visitors and the consumption of the destination. Thus, by understanding how tourist mobility works in a destination and analyzing tourism resources’ centrality, policy makers may better tailor sustainable strategies for cultural tourism destinations.

Highlights

  • One of the main challenges in the field of urban tourism research is to understand what factors lead to more sustainable tourism, sustainability in terms of durability of the tourism activity and in terms of economic profitability

  • Policy makers and tourism developers must understand visitors’ mobility behavior and how they consume space and tourism resources in order to set up sustainable cultural tourism destinations

  • The results suggest that (1) easy mobility of the visited space facilitates the tourist experience; (2) simple and eligible mental maps of the city that are perceived by visitors facilitate the rapid consumption of the tourist destination; and (3) the centrality of the tourism resources affects the mobility of visitors and the consumption of the destination

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Summary

Introduction

One of the main challenges in the field of urban tourism research is to understand what factors lead to more sustainable tourism, sustainability in terms of durability of the tourism activity and in terms of economic profitability. Thereby, the purpose of this research is to meet this challenge by analyzing the following factors: the spatial centrality of tourism resources, urban mobility, and the spatial perception of tourists These factors were selected because they are key factors for the success and sustainability of a destination as they exert influence on the consumption of space by tourists and their mobility, and this in turn influences the economic activity in the city [1]. This methodology is based on the use of GPS technologies, network analysis, and surveys in order to determine the central places of Bilbao and analyze the spatial interaction between cultural sites. What follows now is the literature review of these concepts

Centrality
Urban Mobility
Tourism Sustainability
Case Study
Methods
GPS Data Analysis
POI Network Analysis
Findings
Mental Maps
Full Text
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