A typology of EU tourist regions facing social inclusion issues
By Antonio Paolo Russo, from Universitat Rovira i Virgili
As a first stage of the research approach of SMARTDEST, we have constructed a typology of European regions that illustrate different forms and degrees of attractiveness for tourists and related mobilities, and matched with a wide range of social indicators showcasing trends of social exclusion. The spatial patterns devised provide an interesting canvas to further examine how territorial structures, geographical specificities and policy regimes may play a role in explaining these variations, and inform postCOVID recovery towards policy reforms that bring forwards socially resilient tourist cities and regions.
As a first stage of the research approach of SMARTDEST, we have constructed a typology of European regions that illustrate different forms and degrees of attractiveness for tourists and related mobilities. This typology is then matched with a wide range of social indicators showcasing trends of social exclusion. The objective of this piece of research is to identify key inclusion challenges for groups of regions, having similar profiles in terms of their capacity and evolution to attract mobile populations. The spatial patterns devised provide an interesting canvas to further examine how territorial structures, geographical specificities and policy regimes may play a role in explaining these variations. This analysis refers to a context of steady intensification of tourism and international mobility that has characterised the last decades, to come to an abrupt halt with the sanitary emergency of COVID-19 in 2020, with an expected long tail of disruptions in global and local mobility systems. Looking into the near past goes in the way of understanding how tourism mobilities could have become enmeshed with social inequalities; the hindrances provoked by COVID-19 have been opening new relevant avenues of social exclusion, which the recent literature claims to be overlapping and heightening, and not substituting, pre-existing ones. Our analysis should therefore be informing the process of recovery, and underline the key policy challenges that are at stake in the debate as to whether tourism should bounce back to ‘business as usual’ and pre-COVID trends once the emergency is over, or whether this could be an important opportunity for reforms that bring forward social resilience in the face of the transformative and exclusionary power of tourism mobilities on places.
The indicators used to obtain this basic regional typology were selected from a wide range of measures of tourism and related mobilities considered in preliminary tasks of the SMARTDEST project. These include absolute and relative measures of tourism movement in space and in relation to the resident population (intensity and pressure indexes), for international and domestic markets. Whenever possible and relevant, these indicators have been stratified for areas that have different degrees of urbanisation. We also considered net migration rates for age groups, which the literature relates with different motivations for displacement; the mobility of Erasmus students; and a measure of the penetration of Airbnb supply in relation to the total population which is a proxy of the attractiveness of regions for visitors using this kind of platform-mediated accommodation structures (generally not accounted for in official tourism movement statistics). All these indicators are calculated in stocks, taking 2018 as the most recent year for which there is an almost complete data cover, as well as in change rates, taking 2008 (the period immediately preceding the effects of global financial crisis) and 2013 (marking the start of the post-crisis recovery) as reference years. The technique used for obtaining the final typology has been 4-means clustering on a selection of such indicators after having eliminated redundancies.
The resulting geographical configuration is illustrated in the figure below. The first type, FAST INTERNATIONALISATION, includes only four regions in the European space (Iceland, Northern Ireland, the North-West of England, and the north of Serbia). These are relative newcomers in international tourism that have made a scale jump in the last decade, presenting themselves with an attractive destination profile especially for their rural and small and medium-sized towns. They have been experiencing a strong growth of tourism over the last decade and specifically of the share of international tourists, and are therefore subject to a relatively high tourism pressure (with low growth in cities and towns, high in rural areas). They are relatively unattractive as a site of migration for more senior cohorts but boast high crude migration rates for the younger migration cohorts.
The second class, LOW INTENSITY, includes 92 regions that are characterised as poorly attractive regions for tourism and other migrations but are subject to a rising tourist pressure in cities and towns, have a low and decreasing share of international tourism, and a moderate offer of Airbnb. This is a large set of regions across the core of Europe and stretching to its periphery. These regions are characterised by general low levels of attractiveness for visitors although they have been experiencing recent growth of the tourist intensity in cities and towns. The domestic market is the driving force of tourism development and wherever they have been experiencing some growth this has been mostly accompanied by an expansion of non-traditional forms of hospitality like short-term rentals mediated by digital platforms (as Airbnb). It is noteworthy that in spite of their relatively low tourist dimension, these regions can be moderately attractive for working age adults and senior migrants, maybe precisely on account of the ‘low pressure’ to which they are subject. The context of these regions varies to a great extent, from regions in the European core (as in Germany, France, Belgium and Switzerland as well as Southern Holland) to inland and predominately rural regions of Spain, regions in the Eastern periphery (Poland, Slovakia, Romania), the south of Finland, north of Sweden, the Italian South and Albania.
The third class, STEADY GROWERS, includes 53 regions whose profile is of being attractive and growing regions for tourism, with highest and growing pressure in rural areas, have a high foreign student population in relation to their size, a high and growing share of international tourism. These regions are mostly situated in the Mediterranean coastal and island regions (including almost the whole of Portugal), the Atlantic archipelagos except the Canaries; and extend to regions in Great Britain, the inner part of the Netherlands, Luxembourg, most Scandinavian and Baltic regions, and almost the whole of Greece, plus some ‘capital city regions’ like London, Prague and Bucharest. These are mature destinations for tourism that have not stopped growing and becoming more internationalised in the last decade, registering the highest pressure in non-urban areas, and are poorly attractive for working age younger adults, but moderately attractive for other migrations including under 25 and over-50-year-old workers.
Finally, the fourth class, TOURISM STARS, includes 15 regions that stand out as very attractive for tourism, especially urban, and all migrations, experiencing a moderate growth concentrated in towns and cities; they are subject to a large penetration of Airbnb, and experience a high share of international tourism but seeing a relative growth of the domestic market. These are some of the most visited destinations in Europe and at the same time preferred destinations for migrants of all age groups. Tourist pressure over the last decade has been mostly growing in urban and intermediate areas, and this has been accompanied by a high level of penetration of platform-mediated supply; yet in general the attraction of tourism (the international market in particular) is decelerating, for having possibly met some capacity thresholds. These regions include Catalonia, Madrid, the Balearic and Canary archipelagos, the Algarve region of Portugal, Paris and the South of France, the northeast of Italy, the whole of Croatia and Ireland, and two other capital city regions, North Holland (the region of Amsterdam) and Berlin.
The subsequent step of this analysis has been to calculate the average means of the score of a selection of social indicators in the four classes of regions in this typology, and test that these differences are significant. We have included in this exercise:
- Health indicators (self-reported perception on health state by participants to the EU-SILC survey)
- Housing indicators (self-reported perception on quality of housing, financial access to housing and rent values by participants to the EU-SILC survey)
- Poverty and deprivation indicators (self-reported perception on conditions of dependency, lack of access to basic commodities and consumption, etc.)
- Labour indicators proceeding from the Labour Force Survey and especially pointing at the dimension of regional employment in the tourism sector and at the characteristics of workers in atypical conditions or earning low salaries
The full discussion of results is available in the SMARTDEST Delverable 2.3, which can be retrieved at https://smartdest.eu/results/#project-reports. Here we only wrap up the most important insights.
A key aspect explored by the literature – but not in a systematic way and using an established metrics – is how positive and negative externalities from tourism development balance out (geographically and socially) and whether population change processes which could be triggered by tourism development may be shadowing an underlying process of social exclusion. In this sense, we have singled out the small group of FAST INTERNATIONALISATION regions as the most problematic to this respect: they present a profile of being places where access to housing represents a burden for women and a heavy burden for non-European foreigners and where a sizable share of the over-65 population lives in overcrowded households, and these hindrances do not balance out through the share of population that derive rents from property, which tend to be the lowest among the four types considered. They present the worst profile in terms of conditions of poverty and deprivation, the female population being particularly affected. They also have the large shares of workers in the tourist with elementary occupations (or others) having atypical work profiles and while they offer good opportunities also in term of salary to foreigners and women, they seem to offer them worse condition in terms of protection. The LOW INTENSITY regions present quite an opposite profile – though they derive much lesser benefits from tourism and other inward flows of migration, they show very little of the hindrances through which tourism growth may sustain pathways of social inequality and exclusion.
The other two categories, STEADY GROWERS and TOURISM STARS, are a mixed bag. The former group of regions have not reached a stage of development in which tourism pressure could be considered excessive (also on account of the relative spread of tourism activity out of urban areas), especially in relation to housing affordability, and they have some the best profile in terms of salaries paid. Their trajectory of development has been more paced, having had the opportunity to become embedded in new structures of institutional and social capital, yet the trends indicate that they may resent from an increasing specialisation in tourism, which makes them particularly vulnerable to systemic crises like the one that we are currently living with COVID-19. Finally, TOURISM STARS are in their majority characterised as places where the intensification of tourism in areas otherwise economically buoyant, of their very strong degree of specialisation in tourism, could have tipped some threshold which challenge social inclusion, for instance nuancing a high level of polarisation (for instance between homeowners and tenants), deprivation, and work conditions. That the already high level of concentration in urban areas has not grown in the last decade in average as much as in other regional types is not preventing the tourism economy to increase its dimension and lead to a structural deflation of employment conditions.
These findings may thus inform on some of the key challenges that should be taken into account in the European urban and regional policy agenda when the ‘tourist dimension’ and pace of evolution of regions is considered as a driver of social change, such as housing affordability, socio-spatial polarization, the casualization and precarious nature of tourism work or the effects that the reconfiguration of space brought about my global mobilities in their anchoring to place has on the most vulnerable segments of resident communities. These areas of concern will be the object of in-deep scrutiny in further stages of the SMARTDEST project both at pan-European and at case study level.