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Caravanning in the Iberian Peninsula: Data-driven approach to identify campers' key factors for a perfect parking spot

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Resumo:Tourism is, nowadays, a major activity in both Portugal and Spain, as it plays a significant role in their cultures and economies, contributing to 15% and 12% of both 2022 countries’ GDPs, respectively. Within the tourism sector, caravanning keeps growing and so does the number of services, recreational vehicle areas, and different camping materials for this type of activity. Despite this growth, it is rarely the subject of scientific research. Furthermore, existent studies use small samples based on questionnaires to retrieve information. Our study is one of the few that follows a data-driven approach. By exploring the whole park ecosystem and users’ opinions shared online, we aim to discover the key factors that make a perfect area for recreational vehicles in the Iberian Peninsula. We applied machine learning and text-mining techniques to uncover the crucial factors and characteristics. We found that water drainage systems is the main factor for a highly rated recreational vehicle area for all types of areas studied. For free areas it is important to keep a quiet environment at night and try to build these facilities in places close to the centre of towns, near municipal swimming pools, or close to coast when possible. Public paid areas need to be provided with functional services, specially laundry, electricity, hot water showers and, fundamentally, have clean sanitary facilities. Private areas need to keep a friendly and helpful staff, do not overprice accommodation and services and, if applicable, try to create areas near beaches. This study discusses implications for the tourism industry, providing insights for decision-making about location characteristics, services, and infrastructure within the recreational vehicle areas to better match travellers’ needs and preferences in the Iberian Peninsula.
Autores principais:Ribeiro, João Francisco Bruno
Assunto:Recreational Vehicles Recreational Vehicles Areas Key positive factors Machine Learning Iberian Peninsula
Ano:2024
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso embargado
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL

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