Integrated Crowd Tourism Analysis for Early Warning Systems: A Multidimensional Approach

Purpose: The increasing availability of digital trace data is transforming how crowd tourism can be observed and interpreted, although the phenomenon itself remains difficult to define and operationalise consistently. Existing studies tend to rely on partial indicators, often focusing on visitor flows, online visibility, or perceived experience in isolation, thereby limiting their ability to capture the complexity of crowding dynamics, particularly in culturally significant destinations. Methodology: This study proposes a multidimensional integrated approach to measuring crowd tourism by combining three complementary dimensions: physical pressure, digital attention, and perceived crowding, thereby extending existing approaches to overtourism measurement. The empirical analysis integrates near-real-time aggregated mobility data, digital discourse, and selected web sources collected for an Italian UNESCO World Heritage city. These heterogeneous data sources are spatially and temporally aligned to construct a set of indicators that capture the intensity, visibility, and evaluation of tourism activity. Findings: The proposed analysis process introduces a new Integrated Crowd Tourism Index (ICTI), providing a more nuanced representation of micro-crowding conditions by highlighting how different signals co-occur and evolve. The approach also contributes to the discussion of developing actionable insights for Early Warning Systems. Drawing on multiple dimensions of overcrowding, the analysis integrates behavioural and digital traces in a dynamic manner, revealing non-linear and context-dependent patterns. Research limitations/implications: The study introduces a data-driven and privacy-preserving analytical approach that could support more informed monitoring and management of tourism services, particularly in contexts where micro-crowding is a localised and dynamic phenomenon, subject to data availability limitations. Originality/Value: This study advances the debate on crowd tourism measurement and related early warning systems by integrating mobility, digital discourse, and online evaluations into a single framework, offering a multidimensional perspective on crowding in culturally significant destinations.