I’ve just written an entry for the 2nd edition of the Encyclopaedia of Tourism, on tourism carrying capacity. This is a concept that has become quite unfashionable in recent years – it is certainly one that I hadn’t thought about making use of in a practical way in my work in tourism destinations. Writing this entry encouraged me to revisit this concept and I was struck by the fact that carrying capacity could be a concept with much more utility now that we are seeing the possibilities offered by big data, especially the sensor-based approach to this being taken in the Smart Cities movement.
Simply put, carrying capacity is a measure of the maximum number of tourists that can use a tourism resource (which could be a resort, beach, attraction, town or any other kind of tourism destination), before unacceptable changes in the destination take place. This maximum number of tourists can refer to multiple factors, including the environment, local support for the tourism industry, economic development and tourist perceptions of overcrowding. The concept originally came from the natural sciences where it had been used to measure stocking limits in livestock management or the capacity of a rural area to accommodate the introduction of new species. The scientific, practical roots of carrying capacity have meant that it has fallen out of favour in the tourism studies field, which has more recently developed a tendency to look for multiple, contrasting narratives on tourism development and where many academics have moved away from what they see as simplistic, positivist approaches to our understanding of tourism.
In addition to this, although the concept of carrying capacity helped to inform the emergence of sustainable tourism, it has been overtaken by this newer concept. Sustainable tourism tends to see destinations as made of up of a mix of local and global influences and has come to de dominated by environmental issues, especially the issues connected to carbon and global climate change. Carrying capacity, a very locally specific way of measuring the impacts of tourism, has fallen out of favour within sustainable tourism approaches to development.
While I was researching this encyclopaedia entry, I found a fascinating article: ‘Carrying capacity assessment for tourist destinations: Methodology for the creation of synthetic indicators applied in a coastal area’ by Jurado et al (2012). In this article, the authors develop a methodology that is based on the design of synthetic indicators that measure change in key variables related to tourism growth in the Eastern Costa Del Sol, in Spain.
These indicators included climactic data, measurements of water health, GDP, resident satisfaction with tourism, municipal budgets, beach crowding and a long list of others. Crucially, these indicators mixed environmental sensors, statistical data, surveys and a Delphi study. Collecting this huge range of data, and integrating with it Geographic Information Systems (GIS), meant that the authors were then able to produce real-time, dynamic maps to show where tourism carrying capacity thresholds were being reached or exceeded in the region. This information can be used to guide tourism destination management decisions and contribute to tourism planning.
This approach has enabled the authors to operationalise a much more sophisticated approach to measuring and communicating tourism carrying capacity than has been the norm in tourism studies. New technologies and the lowering costs of collecting big data sets now mean that possibilities for creating new approaches to tourism carrying capacity are opening up. Bringing together quantitative and qualitative data, and presenting it in accessible ways can re-invigorate carrying capacity and address the concerns of many of its critics.
Discussions about Smart Cities around the world have tended to be driven by the desires of property developers to sell units or planners to attract high-value, high-tech businesses. Now is the time for the tourism industry, where sustainable development is a huge concern, to engage with these debates, to get access to data and influence over what is measured.