The Airbnb phenomenon as part of the broader growth of the socalled collaborative economy has grabbed the attention of a growing number of tourism researchers. Among the topics explored have been investigations as to the spatial tendencies of Airbnb in cities and discussions concerning its effects, inter alia, on gentrification, over-touristification and eventual resident displacement. Recognizing that the majority of extant studies have been conducted either in major cities, which in their own right attract large numbers of visitors or in tourism-intensive smaller communities we chose to investigate what Airbnb growth means for a mid-sized city with a highly diversified economy, which is not yet over-touristified. Our focus was on the Dutch city of Utrecht. Through a geospatial and statistical analysis of AirDNA data, we explored the growth of Airbnbs in the city overall, focusing specifically on the phenomenon's effects on the Lombok neighbourhood, a nascent 'neo-bohemia' neighbouring the citycentre tourist bubble. Our analysis reveals that although Airbnb activity in this neighbourhood is relatively recent there are signs suggesting that further touristification of parts of Lombok has ignited increased Airbnb activity. Moreover, there is a distance decay of Airbnb activity as one moves away from the city centre and from established tourism services including restaurants. These findings suggest that in an emerging neo-bohemian space such as Lombok, Airbnb takes on a role as instigator of urban tourism bubble expansion. The study ends with a call for further investigations to better understand the implications expanded Airbnb activity has, among others, on social justice within cities. For example, future investigations could examine the manner in which Airbnbs influence the everyday life of the residents of urban spaces and investigate the conflicts that might arise in Airbnb ghettoes between visitors and locals.

This paper presents an overview of the current state of research into tourism networks, by providing a systematic literature review and relational citation analysis of 98 scientific papers focusing on network collaboration in tourism destinations. The aim of this study is to get a better understanding why the promising theoretical claims of potential benefits of networked collaboration in tourist destinations are so little supported by empirical evidence.This paper shows there are two explanations for this lack of empirically proven benefits.First, progress is hampered by the lack of integration within the field of tourism network studies. The citation analysis identified the existence of different sub-fields of research. These sub-fields apply different approaches towards tourism networks, both from a theoretical and from a methodological perspective. There is little cross-fertilization between the sub-fields and integrative studies are still scarce. Second, while many studies show interesting and promising findings, the field would make more progress, if researchers would reflect more systematically on the relationship between network goals and projected outcomes, and on the most suitable methodology to test the effects of the desired network development in a comprehensive way. Since networks thrive on the perspectives of future benefits that accrue from network participation, there is a need for empirical proof of these network outcomes.Examples of best practices should be provided which visualize and explain the benefits of networks. Tangible, quantitative benefits have to be found in order to stimulate tourism entrepreneurs investing time and money in local tourism networks.Postprint version of article Tourism networks unravelled; a review of the literature on networks in tourism management studies by Egbert van der Zee & Dominique Vanneste published in Tourism Management

(1) Background: This study aimed to explore and define socio-economic (SES) differences in urban school food environments in The Netherlands. (2) Methods: Retail food outlets, ready-to-eat products, in-store food promotions and food advertisements in public space were determined within 400 m walking distance of all secondary schools in the 4th largest city of The Netherlands. Fisher’s exact tests were conducted. (3) Results: In total, 115 retail outlets sold ready-to-eat food and drink products during school hours. Fast food outlets were more often in the vicinity of schools in lower SES (28.6%) than in higher SES areas (11.5%). In general, unhealthy options (e.g., fried snacks, sugar-sweetened beverages (SSB)) were more often for sale, in-store promoted or advertised in comparison with healthy options (e.g., fruit, vegetables, bottled water). Sport/energy drinks were more often for sale, and fried snacks/fries, hamburgers/kebab and SSB were more often promoted or advertised in lower SES areas than in higher SES-areas. (4) Conclusion: In general, unhealthy food options were more often presented than the healthy options, but only a few SES differences were observed. The results, however, imply that efforts in all school areas are needed to make the healthy option the default option during school time.

The emergence of social media and Web 2.0 has a notable impact upon the tasks of destination managers as these platforms have developed into influential mechanisms affecting tourist behaviour. This paper shows how Destination Management Organizations (DMOs) can reap the benefits of the Web 2.0 revolution as it serves as an important source of user-generated information, bringing novel opportunities for data-driven destination management. To test the applicability of user-generated content for destination management, this paper analyses restaurant reviews from five Flemish art cities which were retrieved from the Web 2.0 platform TripAdvisor. Getis-Ord hot spot analysis revealed spatial clusters of frequently ('hot spots') and rarely ('cold spots') reviewed restaurants in four out of the five art cities. By comparing these spatial patterns, the digital footprints of tourists were uncovered and discussed with DMO directors. Found patterns appeared to reflect local policies aimed either at concentrating tourism, as in Bruges, the city with the most prominent hot spot, or spreading tourism over time and space as seen in Antwerp and Ghent where less prominent hot spots were present. The visualization proved to be a valuable input when discussing tourism management and fuelled the sharing of knowledge between the destinations.

No abstract