Unlocking Tourism Diversity in Winter: Clusters of Tourists in Lisbon Based on Motivations, Profiles, and Behaviour

Abstract

Recent trends in Lisbon's winter tourism indicate a shift towards off-peak travel, attracting diverse visitors with its rich cultural heritage, sustainable initiatives, and extended stay options for digital nomads. The city's culinary scene, arts, wellness activities, and tech-driven tourism options enhance its appeal. Aligned with these recent trends, tourism in Lisbon's region during the winter season presents a unique and dynamic landscape influenced by a wide range of motivations, tourist profiles, and travel behaviours. This study aims to define distinctive clusters of winter tourists in Lisbon by analysing these key variables, providing valuable insights specific to the winter travel context. Based on a compiled dataset from the winter season in Lisbon, this study delves into examining the factors driving tourist visits, encompassing socio-economic backgrounds, travel frequency, and age demographics. We aim to reveal the distinctive subgroups that define Lisbon's winter tourist population, employing data analysis techniques such as cluster analysis. From an academic perspective, this study offers a novel tourist segmentation model based on motivations, profiles, and behaviour. This model enriches the existing body of knowledge in tourism studies, providing a valuable reference for future research. For tourism agents in Lisbon, this study provides actionable insights to enhance strategic decision-making. By segmenting winter tourists, they can tailor marketing strategies and product development to cater to diverse tourist segments. Moreover, this approach can lead to economic benefits, optimising resource allocation, and revenue generation.