La proliferación de plataformas peer to peer (P2P) de alojamiento turístico extrahotelero (Airbnb, Vrbo, HouseTrip, etc.) ha promovido la turistificación de muchos barrios en gran un número de ciudades, que se han visto afectados por un considerable incremento de la oferta de estos alojamientos. En este artículo se analizan los alojamientos turísticos extrahoteleros de Airbnb en el territorio de Madrid. Para medir el impacto de Airbnb en Madrid se realizan diversas agrupaciones de los distritos de la ciudad mediante análisis clúster en base a tres indicadores cuantitativos referidos a los alojamientos de la plataforma (nº de alojamientos, nº de alojamientos/𝑘𝑚2 y precio medio de los alojamientos). Se complementa el análisis de los alquileres turísticos, agrupando los distritos en función del precio medio de los alquileres destinados a uso permanente (Fotocasa), a fin de tener una imagen más fidedigna de la vivienda de alquiler en la capital española. Por último, se sugieren distintas soluciones para la descongestión de determinados distritos, resaltando la posibilidad del uso de inteligencia artificial mediante algoritmos para una gestión eficaz de los destinos; así como se acentúa la importancia de guiar las actuaciones gubernamentales hacia la sostenibilidad del destino.

This study develops and validates the Smart Destination Perception Scale (SDPS), a tool designed to assess perceptions of smart destinations among tourists and residents. Grounded in a comprehensive literature review and refined through expert evaluation and pretesting, the SDPS identifies four main dimensions: Innovation, Connectivity, Market Intelligence, and Social and Environmental Responsibility. Market Intelligence integrates Intelligence Systems and Information and Promotion Systems, while Social and Environmental Responsibility integrates Accessibility and Sustainability. Data were collected from 1200 participants (600 tourists and 600 residents), and exploratory and confirmatory factor analyses confirmed the scale's reliability, validity, and dimensional structure. Madrid was selected as the empirical context due to its consolidated status as a leading smart destination in Spain and its relevance as a major European urban tourism hub, underscoring the real-world applicability of the SDPS within a mature smart destination. Findings identify Market Intelligence as the most influential dimension, highlighting the importance of intelligence systems and information and promotion mechanisms in shaping effective smart destination strategies. The Social and Environmental Responsibility dimension also emerges as pivotal by integrating accessibility and sustainability, emphasizing the need for inclusive and environmentally conscious practices. This study contributes to smart destination research by introducing a robust, multidimensional 29-item scale aligned with stakeholder theory and supportive of both strategic planning and practical application. By providing standardized measurements, the SDPS enables authorities to compare destinations and evaluate perceptions from both tourists and residents, fostering a comprehensive approach to smart destination management.