A Multidimensional Composite Index for Measuring Overtourism: Methodological Development and Evidence from Spain

Imagine a place where the streets are so crowded with visitors that locals can no longer find a seat at a café, the noise drowns out daily life, and the very character of the neighborhood begins to fade. This is not just a feeling of being overwhelmed; it is a specific condition researchers call overtourism. It happens when a destination becomes so popular that the benefits of visitors are outweighed by the costs to the people who live there. For decades, the tourism industry operated on a simple belief: more visitors meant more success. But as destinations like Venice and Barcelona have shown, constant growth does not always lead to a healthy community. Instead, it can create a breaking point where the social, environmental, and political fabric of a place begins to tear. Understanding exactly where and when this happens is the first step toward fixing it, moving from a mindset of endless expansion to one of careful balance.

In a new study focused on Spain, a team of researchers has developed a practical tool to measure this pressure with precision. Spain is a perfect place to test such a tool because its tourism is not spread out evenly; it is heavily concentrated in specific islands and coastal cities. The researchers wanted to move beyond vague complaints or single numbers, like just counting how many people visit. Instead, they built a composite index, which is essentially a single score that combines several different signs of stress into one clear picture. They looked at four specific things across all fifty provinces of Spain: how many hotel beds exist relative to the size of the city, how many tourists visit compared to the number of residents, how full those hotels actually are, and how much extra trash is generated by visitors. By gathering official government data on these factors, they created a method that does not rely on guesswork or arbitrary opinions about what matters most.

To make sure their score was accurate and fair, the researchers used a statistical technique to let the data speak for itself. Rather than deciding that one factor, like hotel beds, was twice as important as another, like trash, they analyzed how these factors naturally moved together across the country. This process revealed that the most telling signs of overtourism in Spain were not just the number of beds available, but the environmental strain caused by visitors and the sheer intensity of tourists living alongside residents. The study confirmed that these different measurements were all pointing to the same underlying reality: a destination under pressure. This approach ensures that the final score is robust and can be trusted by policymakers who need to make difficult decisions about where to limit visitors and where to encourage them.

When the researchers applied this index to the map of Spain, a clear pattern emerged. The pressure was not felt equally everywhere. The highest levels of stress were found in the Balearic and Canary Islands, along with major coastal cities like Málaga and Barcelona, and the capital, Madrid. These areas showed a combination of crowded streets, high hotel occupancy, and significant environmental footprints. In contrast, most of the inland provinces, away from the coast and the major islands, remained far below the national average. The study identified three distinct groups of places: those in a critical state requiring immediate action to manage capacity, those with intense urban pressure needing better infrastructure and land-use rules, and those with low pressure that could potentially welcome more visitors without breaking their local systems.

The findings suggest that the old idea of treating all tourist destinations the same way is no longer viable. A one-size-fits-all policy cannot work when the reality on the ground varies so dramatically from one province to the next. For the most crowded areas, the study points toward the need for strict management, such as limiting the number of people allowed in at certain times or controlling the growth of new hotels. For the less crowded inland areas, the data offers an opportunity to gently redirect some of the flow, spreading the economic benefits more evenly without overloading the popular hotspots. The researchers emphasize that this tool is not just about counting numbers; it is about protecting the quality of life for residents while keeping the tourism industry sustainable. By using a transparent, data-driven method, local leaders can now see exactly where the balance has tipped and take steps to restore it before the situation becomes unmanageable.