The 2007-2008 Global Financial Crisis profoundly impacted the housing markets, particularly of the so-called PIGS countries. Main cities in Portugal, Italy and Greece have seen a sharp decrease in house prices and rent value since 2010. At the same time, the rise of Airbnb has contributed to the reframing of housing market demand in cities, with an increase of temporary lettings in prime urban tourist areas. Understandably, this has direct implications for local residents, with renters' displacement, tourism gentrification and raising cases of tourismphobia. This article provides insights from three cities -Athens, Lisbon and Milan -to show how the dynamics in the housing market and the boost of Airbnb over the last decade are steadily changing the urban populations of the aforementioned cities. This research builds upon the Rent Gap Theory and the Lukes' Power Theory to illustrate how Airbnb is fostering a new form of urban displacement at a faster rate than traditional housing gentrification, with the renting of prime residential areas to tourists.

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Air transport liberalisation in Europe has produced some major changes to the networks operated by airlines and the services available at airports. Within this context the degree of airport dependency in terms of market, spatial and temporal concentration is important to know from an economic geography and risk management perspective. A composite index called the Airport Dependency Index (ADI) is developed to measure airport dependency based on the concept of the relative Gini coefficient. Liberalisation has had varying impacts depending on the size and type of airport and so a comparison is made of the degree of dependency at a large sample of European airports using the ADI. The ADI has the potential to provide insight on the sustainability and worthiness of financing airport projects, and on whether airports should diversify further their activities by investing in the growth and expansion of their network.Keywords: Air transport liberalisation; Airport Dependency Index (ADI); Gini coefficient; European airports. Highlights A composite Gini-based index is developed to measure airport dependency.  Dependency is measured according to market, spatial and temporal concentration.  Data is collected and analysed over a ten year period from 2005 to 2014.  735 European airports are compared.  Implications for impact/added value analysis are considered.2

This chapter covers three areas of institutional changes in the European aviation sector that may significantly affect the dynamics of the tourism industry. Further to the introduction, airlines are discussed in section two; airports are analysed in section three; and air navigation service provision are presented in section four. The dynamics of these three pillars and the interrelationship with the tourism industry is explored in section five. Among others, the chapter argues that when a proper systemic approach is followed any smart relaxation of regulatory and infrastructural constraints will have positive repercussions on tourism growth and development not only of central places but also of more peripheral regions. Finally, section six concludes and discusses the way forward.

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