Researchers from the University of Granada (UGR) at the Andalusian Interuniversity Institute for Data Science and Computational Intelligence (Dasci), together with scientists from the University of Las Palmas de Gran Canaria, have developed a decision support system (DSS) based on social network analysis and data visualization to analyze the accommodations sector in the Canary Islands.
Applied to the vacation accommodations market in the Canary Islands, this model allows, as detailed by the UGR in a press release, «to identify differentiation and profitability patterns in the P2P sector, providing valuable information for investors and tourism managers, as well as for political and social authorities.»
The study, published in the scientific journal ‘Socio-Economic Planning Sciences’, has analyzed over 9,000 tourist accommodations in the Canary Islands with real data from the Airbnb platform. The methodology used allows for «building a visual map that positions each accommodation based on its similarity to others, thus facilitating the identification of key patterns.»
The researchers have identified nine differentiated accommodation typologies based on characteristics such as guest capacity, the number of properties managed by the host, and cancellation policies.
Among the most relevant results, it is highlighted that accommodations with higher income tend to be located in peripheral areas of the visual map, indicating distinctive features. In particular, they have greater accommodation capacity and require longer minimum stays.
However, accommodations managed by large operators show lower economic performance compared to individual properties. Beyond capacity, the results suggest that strategies such as modifying the cancellation policy and obtaining the ‘Superhost’ badge can improve profitability.
«Differentiation is key in the vacation rental market,» explained the study’s lead author, Víctor A. Vargas Pérez, from the Department of Computer Science and Artificial Intelligence (IA) at the UGR. «Our system allows for an intuitive visualization of which accommodations are most successful and how they are distributed in the market, facilitating strategic decision-making.»
This model not only provides valuable information for investors seeking to maximize their returns but can also be useful for tourism managers and urban planning authorities.
By offering a detailed view of the market, the system helps «identify investment opportunities and design strategies to enhance sector competitiveness, as well as housing policies compatible with the local population,» detailed the UGR in a press release on Monday.
The study emphasizes that the classification of accommodations is not tied to a specific location within the archipelago, but rather the different typologies are evenly distributed across all the islands. This finding reinforces the idea that investment strategies should focus on differentiation and management characteristics, rather than solely relying on location.
The research team hopes that the methodology can be applied to other tourist destinations and vacation rental platforms, contributing to the development of more sophisticated analysis tools for the tourism industry.
The Dasci is a collaborative entity between the universities of Granada, Jaén, and Córdoba. It is dedicated to advanced research and training in the field of AI, with a particular focus on data science and computational intelligence.
