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New Perspectives in Tourism & Leisure

First results of the EPTUR Project

 

 

1. Conceptual Framework

As observed in previous projects, new tourism dynamics have been driven by factors such as digitalization, the growth of the collaborative economy, and urban transformations. Platforms like Airbnb have drastically changed the way housing is accessed in urban destinations, altering both the supply and demand for accommodation (González-Reverté et al., 2022; Morales-Pérez et al., 2024). On the other hand, one of the main challenges facing tourism today is the need to adapt to the so-called ‘twin transitions’ (digital and ecological transition). These transitions seek a balanced integration of digitalization with a sustainable approach, minimizing environmental impacts and maximizing economic and social benefits (Rossmannek et al., 2024; Díaz-Luque et al., 2022). Recent research has highlighted the importance of developing policies that promote sustainable practices in the tourism sector and mitigate the negative effects of mass tourism in urban and rural spaces.

 

In this regard, the phenomenon of overtourism has generated a significant social response in many tourist cities. In Barcelona, for instance, multiple protests against neighborhood touristification and rising housing prices have been documented (González-Reverté, 2023; Milano et al., 2023). These movements have led to stricter regulations in the management of tourist accommodation and a rethinking of the economic tourism model in certain regions. The growing tension between residents and tourism actors is a recurring theme in academic literature. Finally, the role of social networks in tourism perception and destination image construction has been a key element of analysis in recent studies (Garay-Tamajón & Roelofsen, 2024). Digital platforms not only serve as promotional tools for destinations but also shape tourists’ expectations and experiences. Content analysis on social networks allows for an evaluation of predominant narratives and an understanding of the evolution of public perception regarding tourism in different contexts.

 

Table 1: Bibliographic Meta-Analysis

Reference

Main Topic

Method

Alsina-Folch & Garay-Tamajón (2024)

Digitalization and Tourism

Social network analysis

Garay-Tamajón & Roelofsen (2024)

Social Networks and Tourism Crisis

Content analysis

Morales-Pérez et al. (2024)

Airbnb and Housing Market

Neural network modeling

González-Reverté & Díaz-Luque (2024)

Hosts’ Motivations in Airbnb

Motivational surveys

Fischer & Roelofsen (2022)

Hosts’ Adaptation to the Pandemic

Qualitative interviews

González-Reverté (2023)

Identity and Cultural Tourism

Cultural identity analysis

González-Reverté et al. (2023)

Airbnb’s Effects on the Hotel Market

Quantitative analysis

Garay-Tamajón & Morales-Pérez (2022)

Digital Narratives of Destinations

Discourse analysis

González-Reverté (2022)

Perception of Overtourism

Perception surveys

González-Reverté & Soliguer-Guix (2022)

Social Mobilization and Anti-Tourism

Social narrative analysis

Milano et al. (2023)

Touristification and Mobilities

Qualitative study

Díaz-Luque et al. (2022)

Tourism Transformation

Theoretical study

García & Garay-Tamajón (2022)

Image of Marine Destinations

Visual content analysis

 

2. Methodologies

To analyze the phenomena addressed in the EPTUR project studies, various methodologies have been employed, combining qualitative and quantitative approaches. One of the most commonly used methodologies is content analysis on social networks, which allows for an assessment of tourism narratives, user perceptions, and trend evolution on platforms such as Twitter and Airbnb (Garay-Tamajón & Roelofsen, 2024; Alsina-Folch & Garay-Tamajón, 2024). This type of analysis facilitates the identification of dominant discourses and their impact on decision-making in the tourism sector. Another key methodology is quantitative modeling, which has been used to study the platform economy and its impact on the housing market. Recent research has used artificial neural networks to predict supply and demand patterns in Airbnb, allowing for a more precise analysis of market dynamics (Morales-Pérez et al., 2024). The combination of statistical tools with qualitative approaches provides a comprehensive view of the tourism phenomenon in the context of digital and sustainable transformation.

 

3. Results

The reviewed studies show that digitalization has accelerated the transformation of tourism, with a particular focus on platforms like Airbnb and the use of artificial intelligence in sector management. These innovations have led to significant changes in how tourists plan their trips and in the competitiveness of traditional accommodations (Alsina-Folch & Garay-Tamajón, 2024). However, challenges have also arisen, such as reduced housing availability for residents and job precarization in the platform economy. From a social perspective, there has been an increase in citizen mobilization against the negative effects of mass tourism. Cities like Barcelona have implemented stricter regulatory policies to limit the impact of overtourism on local communities (González-Reverté & Soliguer-Guix, 2024; Milano et al., 2023). These measures have sparked a debate on balancing tourism economic sustainability with protecting residents’ well-being. Another key finding is the shift in consumer preferences towards more sustainable and responsible tourism models. Digitalization has also enabled the rise of tourism experiences based on sustainability, increasing interest in practices such as regenerative tourism and reducing the carbon footprint in travel (Rossmannek et al., 2024). These changes reflect an evolution in tourism perception and open new opportunities for the development of innovative policies in the sector.

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