ENTER2018 eTourism Conference presentation

1. ENTER 2018 Research Track Slide Number 1
Exploring the Booking Determinants
of the Airbnb Properties:
An Example of the Listings of
London
Richard T.R. Qiu1
Anyu Liu2
Daisy X.F. Fan3
The Hong Kong Polytechnic University, Hong Kong1
University of Surrey, UK2
Bournemouth University, UK3

2. ENTER 2018 Research Track Slide Number 2
Agenda
• Research Background
• Literature Review
• Data and Methodology
• Findings and Discussions
• Conclusions

3. ENTER 2018 Research Track Slide Number 3
Research Background

4. ENTER 2018 Research Track Slide Number 4
Research Background
US$142,000
US$3,300
Mean
Median
US$142,000
Data Source: Cave (2016)

5. ENTER 2018 Research Track Slide Number 5
Research Background
100%
98%
50%
Data Source: Cave (2016)

6. ENTER 2018 Research Track Slide Number 6
Research Background

7. ENTER 2018 Research Track Slide Number 7
Literature Review
• Booking determinants of Airbnb properties
Superhost (Liang, Schuckert, Law, & Chen,
2017)
Property images (Rahimi, Liu, & Andris, 2016)
Personal picture of the host (Ert, Fleischer, &
Magen, 2016)

8. ENTER 2018 Research Track Slide Number 8
Literature Review
• Determinants of Booking Intention and
Behaviours
Online review comments (Sparks & Browning,
2011; Yu, Guo, Zhang, & Zhao, 2016)
Terms and conditions (Chen, Schwartz, &
Vargas, 2011)
Location (Yang, Wong & Wang, 2012)

9. ENTER 2018 Research Track Slide Number 9
Literature Review
• Research Gap
A more general picture of the determinants
(Price, Spill-over effects, Attributes of the
property)
Sequential Bayesian estimation

10. ENTER 2018 Research Track Slide Number 10
Data and Methodology
• Data
Data source: Insideairbnb.com (365 days ahead
booking information for 44 cities)
Sample destination: London (49,348 listings)
35 days (5 Mar to 8 Apr) ahead (Chen
&Schwartz, 2008) with 41,124 valid listings
1.23 million observations

11. ENTER 2018 Research Track Slide Number 11
Data and Methodology
• Thirty one variables
Price per capita per night
Number of reviews
Location
Spill-over effects of the neighbouring
properties
Attributes of the property

12. ENTER 2018 Research Track Slide Number 12
Data and Methodology
• Methodology
– A binominal logistic model
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13. ENTER 2018 Research Track Slide Number 13
Data and Methodology
• Methodology
– The posterior distribution of the parameter
vector
– Sequential Bayesian updating
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14. ENTER 2018 Research Track Slide Number 14
Findings and Discussions
• The time effect on booking probability
Odds

15. ENTER 2018 Research Track Slide Number 15
Findings and Discussions
• The impact of price, neighbouring spill-over
and location on booking probability
Description Mean ΔOdds
Price per capita -0.0116 -1.16%
Number of neighboring listings 0.0001 0.01%
Available neighboring listings -0.0002 -0.02%
Distance to the nearest tube station -0.0792 -7.62%
Distance to city center -0.0694 -6.71%

16. ENTER 2018 Research Track Slide Number 16
Findings and Discussions
• The impact of available property and host
information on booking probability
Description Mean ΔOdds
Number of characters in rules -0.0871 -8.34%
Property Description 0.0530 5.45%
Description of space (Dummy) 0.1127 11.93%
Number of listing pictures 0.1830 20.08%
Super host (Dummy) 0.2511 28.54%
Host profile (Dummy) 0.3756 45.58%
Host verified ID (Dummy) 0.1793 19.64%

17. ENTER 2018 Research Track Slide Number 17
Findings and Discussions
• The impact of property attributes on
booking probability
Description Mean ΔOdds
Number of Bedrooms 0.0147 1.48%
Number of Amenities 0.0187 1.89%
Number of bed per bedroom -0.0984 -9.37%
Bathroom per capita 0.1940 21.40%
Internet (Dummy) 0.3023 35.29%
Kitchen (Dummy) 0.2371 26.76%
Number of Reviews 0.0069 0.69%

18. ENTER 2018 Research Track Slide Number 18
Findings and Discussions
• The impact of property attributes on
booking probability (II)
Description Mean ΔOdds
Property function (Group of dummies)
None Benchmark
Romantic 0.1214 12.89%
Family 0.1040 10.96%
Business -0.0659 -6.37%
Social -0.0361 -3.55%
Property type (Group of dummies)
Others Benchmark
Apartment 0.0175 1.77%
House & Townhouse 0.0943 9.89%
Bed & Breakfast -0.1905 -17.35%
Room Type (Group of dummies)

19. ENTER 2018 Research Track Slide Number 19
Findings and Discussions
• The impact of property attributes on
booking probability (III)
Description Mean ΔOdds
Room Type (Group of dummies)
Shared room Benchmark
Private room 0.4677 59.63%
Entire property 1.3632 290.84%
Bed Type (Group of dummies)
Others Benchmark
Couch -0.3284 -27.99%
Pull-out Sofa/Real bed 0.2512 28.55%

20. ENTER 2018 Research Track Slide Number 20
Findings and Discussions
• The impact of terms and conditions on
booking probability
Description Mean ΔOdds
Security deposit -0.0002 -0.02%
Cleaning fee -0.0003 -0.03%
Fee for extra person -0.0094 -0.93%
Weekly discount (Dummy) 0.0896 9.37%
Monthly discount (Dummy) 0.0846 8.82%
Instant reservation (Dummy) 0.2869 33.23%
Refund (Dummy) 0.0520 5.34%
Guest verification Required (Dummy) -0.1497 -13.91%

21. ENTER 2018 Research Track Slide Number 21
Conclusions
• How to be selected by guests among numerous
properties?
Price
More information of host and the property
Privacy (private bathroom/entire property)
Convenience (instant reservation/internet/kitchen)

22. ENTER 2018 Research Track Slide Number 22
Q & A
Thank You!