Predicting AIRBNB Sales with Google Searches in a Customer Journey Context

Mads Zacho Krarup, Niels Buus Lassen, Rene Madsen

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

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Abstrakt

This paper presents a predictive model of Airbnb sales in Copenhagen, build on a dataset with over a 33-months of Airbnb bookings in Copenhagen and related searches on Google. Moreover, geospatial patterns of the AIRBNB listings are detected by constructing a 100 m x 100 m grid cells in UTM 32 coordinates of the city of Copenhagen. The predictive models built are a stepwise regression model, which is compared with a neural network model, both performing well on training as well as on k fold cross validation data with an R2 value on 86%-96%.
OriginalsprogEngelsk
TitelSymposium i anvendt statistik : 22.-24. januar 2018
RedaktørerPeter Linde
Antal sider18
UdgivelsesstedKøbenhavn
ForlagInstitut for Fødevare- og Ressourceøkonomi, Københavns Universitet og Det Nationale Forskningscenter for Arbejdsmiljø
Publikationsdato2018
Sider32-49
ISBN (Trykt)9788779043336
StatusUdgivet - 2018
Begivenhed40. Symposium i Anvendt Statistik - Københavns Universitet, København, Danmark
Varighed: 22 jan. 201824 jan. 2018
Konferencens nummer: 40
http://www.statistiksymposium.dk/

Konference

Konference40. Symposium i Anvendt Statistik
Nummer40
LokationKøbenhavns Universitet
LandDanmark
ByKøbenhavn
Periode22/01/201824/01/2018
Internetadresse

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