Price determinants of Airbnb rentals the case of Denmark

Transcription

1 Price determinants of Airbnb rentals the case of Denmark Carl Marcussen, senior researcher, PhD Center for Regional and Tourism Research, Bornholm, Denmark, ENTER 2018, Jönköping, Sweden,

2 Overview Web scraping: An option for harvesting data in this case about Airbnb The current status of Airbnb in major cities Airbnb in Denmark Copenhagen / major cities and coastal areas Price determinants of Airbnb rentals the case of Denmark Discussion: Web scraping is it useful? --- Price determinants.

3 Web scraping of Airbnb.com Two passionate web scrapers in the context of Airbnb Murray Cox: 45 cities - Many variables - Europe: 20 North America: 21 Rest of World: 4 Tom Slee: 118 cities Fewer variables - Europe: 56 North America: 45 Rest of World: 17 Tom Slee Europe 56 destinations

4 Listings in selected major cities, Sept E. E. E. E. E. E. Rank City Listings Mill. inhab. Per 1000 inhab. 1 London ,8 7,1 2 Paris ,4 5,5 3 New York ,5 4,5 4 Rio de Janeiro ,5 5,2 5 Rome ,9 8,9 6 Barcelona ,6 14,4 7 Tokyo ,5 1,5 8 Sydney ,8 3,9 9 Berlin ,6 5,2 10 Los Angeles ,0 4,4 x1 Copenhagen Greater ,3 13,2 x2 Copenhagen Province ,8 20,0 x3 Copenhagen Municip ,6 21,9 Top ,6 4,9 Sources: visited Jan Wikipedia

5 20 European cities Airbnb web scrapes by Murray Cox Amsterdam (TS) Antwerp Athens Barcelona (TS) Berlin (TS) Brussels Copenhagen (TS) Dublin (TS) Edinburgh (TS) Geneva (TS) London (TS) Madrid (TS) Malaga Mallorca * ((TS)) Manchester Paris (TS) Rome (TS) Trentino ** Venice (TS) Vienna (TS) Notes: * Island ** Region TS= 13 of 20 Tom Slee too

6 56 European destinations Airbnb web scrapes by Tom Slee Alpes Maritime Amsterdam (MC) Asturias Barcelona (MC) * Belgium Berlin (MC) Bologna Bordeaux Brighton Bristol Brno Clichy sous Bois Copenhagen (MC) * Denmark Dublin (MC) Edinburgh (MC) * Estonia Florence Frankfurt Geneva (MC) Girona Granada Groningen Helsinki * Hungary * Iceland Linköping Lisbon London (MC) Lyon Madrid (MC) Mallorca (MC) Melun Menorca Nantes Nice Palermo Paris (MC) Porto Reykjavik Rome (MC) Saint Denis Saint Malo * Switzerland Tallinn Turin Tuscany Veneto Venice (MC) Versailles Vienna (MC) Warsaw York Zagreb Zurich Aarhus Reference: Notes: * 6 countries MC= Murray Cox too (14 of 56) Unfortunately, Tom Slee will discontinue his philanthropic scraping activities. None after July 2017.

7 Airbnb listings per 1000 inhabitants - European cities (and areas) only 1 Versailles 84,0 2 Nice 33,8 3 Alpes Maritime 29,9 4 Reykjavik 29,6 5 Florence 24,5 6 Venice 24,2 7 Lyon 20,6 8 Granada 15,1 9 Copenhagen Greater 13,2 10 Tuscany 13,1 11 Barcelona 11,8 12 Aarhus 11,7 13 Rome 9,2 14 Amsterdam 7,7 15 London 7,3 16 Edinburgh 7,0 17 Paris 6,8 18 Bordeaux 6,3 19 Berlin 6,1 20 Dublin 5,9 Note: Airbnb listings (min. 3000) according to Tom Slee, ~July Population (metropols) according to Wikipedia. - Selected cities

8 Airbnb listings per capita, municipalities DK, July 2017 Rank Municipality Listings Inhabitants Per 1000 inhab. 1 Copenhagen ,8 2 Fanø (island) ,5 3 Frederiksberg ,7 4 Samsø (island) ,2 5 Gribskov ,3 6 Bornholm (island) ,5 7 Ærø (island) ,3 8 Odsherred ,2 9 Læsø ,6 10 Århus ,2 Top 10 by listings/population ,3 Source: Airbnb listings July 2017, Tom Slee. Population , Stat.DK

9 Airbnb listings per province in Denmark, 2017 Province i Denmark Listings pop 1/12017 Per 1000 inhab. 01 Copenhagen City ,0 02 Copenhagen Sub ,7 03 North Sealand ,4 04 Bornholm ,5 05 East Sealand ,0 06 W & S Sealand ,3 07 Funen ,1 08 South Jutland ,0 09 East Jutland ,3 10 West Jutland ,7 11 North Jutland ,4 Total, Denmark ,6 Greater CPH (1+2) ,2 Source: Airbnb listings July 2017, Tom Slee. Population , Stat.DK

10 Previous studies on Airbnb re. price determinants

11 Variables included in Airbnb web scrapes (by Tom Slee) 1. room_id 2. host_id 3. room_type 4. borough 5. neighbourhood * 6. reviews 7. overall_satisfaction 8. accommodates 9. bedrooms 10. price (in $US) 11. minstay * 12. latitude and longitude 13. last_modified 14. name: catch phrase Note: * Not included in the scrapes available for Denmark Possible to add, e.g.: Population density in the municipality of each listing. Reference:

12 Some factors affecting the price per night Location Population density No. of reviews Satisfaction score Superhost badge

13 Some factors affecting the price per night Location Price per m 2 of housing No. of reviews Satisfaction score Superhost badge

14 Included variables: With 12% fee. 1 EUR~7.46 DKK. Per renting unit, not per B&B Lowest=0. Highest=1. Not dummy variable. Dummy variable, 0 or 1. Max # persons/bedroom. Lowest (~3)=0. Highest(5)=1. Not dummy variable. Percentage here 2% Percentage here 19% In English or.. 3/4

15 Results model 1 Note: Dependent variable: Listprice_DKK_incl_12_pct. 1 EUR ~ 7.46 DKK Model 2 (weighted by reviews): R2 = Model 3 (w., log of Y): R3 =

16 Thank you for your attention Questions - Comments - Discussion Is web scraping useful? Is it easy to make web scrapes? How to explain (or set) list prices of accommodations? Which variables to explain by which determinants? Acknowledgement: This work is part of CRT s own contribution to the project Innovation in Danish coastal tourism areas WP about sharing economy. - Supported by the Danish Innovation Fund.