The unprecedented worldwide growth of Airbnb over the last decade deserves to be analysed from a geographical perspective so as to understand the underlying logic behind the spatial distribution of the accommodation offered on the platform. Multiple territorial and economic variables may influence this distribution. In this context, the article aims to analyse the spatial distribution of Airbnb in Switzerland and identify its determinants. Geographical Information Systems are used to analyse the geographical distribution of Airbnb listings, and Negative Binomial Models are applied to identify its determining factors. Results are particularly interesting as they highlight that Airbnb listings are mainly clustered geographically in specific areas of the country. The success of Airbnb as an accommodation supply platform has led to a concentration of Airbnb listings in areas of Switzerland where hotel supply is significant, but also in areas where there is a high presence of second homes and the potential for generating profit from the housing market is greater.Zusammenfassung: Angesichts des beispiellosen weltweiten Wachstums von Airbnb in den zurückliegenden zehn Jahren, drängt sich aus geographischer Perspektive die Frage nach der zugrunde liegenden Logik hinter der räumlichen Verteilung der auf dieser Plattform angebotenen Unterkünfte auf. Mehrere territoriale und wirtschaftliche Variablen können diese Verteilung beeinflussen. In diesem Zusammenhang zielt der Artikel darauf ab, die räumliche Verteilung von Airbnb-Angeboten in der Schweiz zu analysieren und deren Determinanten zu identifizieren. Geographische Informationssysteme werden verwendet, um die geografische Verteilung der Airbnb-Angebote zu analysieren, und Negative Binomiale Modelle werden verwendet, um ihre bestimmenden Faktoren zu identifizieren. Die Ergebnisse sind besonders interessant, da sie zeigen, dass die Airbnb-Angebote hauptsächlich in bestimmten Gebieten des Landes gebündelt sind. Der Erfolg von Airbnb als Unterkunftsversorgungsplattform hat sowohl zu einer Konzentration der Airbnb-Angebote in Gebieten der Schweiz geführt, in denen die Hotelversorgung bedeutend ist, aber auch in Gebieten, in denen es eine hohe Präsenz von Zweitwohnungen gibt und das Gewinnpotenzial auf dem Wohnungsmarkt größer ist.
Aircraft crash simulation is a mandatory exercise for all international airports. The procedure of such a simulation is that a set of figurants play out a given plane crash scenario. Then, all professional bodies-such as police, fire brigades, medical care professionals, airport staff, and airline companies-react to the figurants' role play. The quality of the overall problem resolution is evaluated by the national civil aviation regulator. We postulate that the closer the figurants' staging corresponds to reality, the more relevant the simulation exercise will be in training professionals involved in resolving an actual accident. To our knowledge, very little literature focuses on improving the performance of figurants (research objective). In this research, we conducted a fieldwork study (methodology) during a recent official exercise at Sion Airport in Switzerland. Based on the fieldwork analysis (results), we propose a new staging model (findings) to improve similar simulation exercises (implication).
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