1. A first approach to measuring the
impact of changes in online reviews
on hotel room prices
Igor Ibarguren, Ibai Roman, Jon Kepa Gerrikagoitia,
Aurkene Alzua-Sorzabal
CICtourGUNE, Spain
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Slide Number 1

2. Agenda
• Introduction
– Problem
– Previous research
• Method
• Expected results
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Slide Number 2

3. Introduction
Problem
•Customers choose a destination and then select
accommodation based on price and available rooms
(Wu, Zhang, & Fujiwara, 2011), hotel location,
category, services, facilities and third party
experiences (Dickinger & Manzanec, 2008)
•Travel agencies used to recommend a hotel
depending on previous experiences
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4. Introduction
• The user generated content (UGC) changed the
information flow to an electronic word-of-mouth
paradigm
• There are several studies analysing the influence
of online reviews on sales of products such as
books (Clevalier & Mayzlin, 2006), but it is more
pronounced on experience goods as they require
consumption before knowing their quality
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5. Introduction
• The Internet has changed the global business
scene. The development of IDS has brought
new opportunities (Van den Poel & Leunis,
1999)
• Most hotel room attributes such as locational
and non-locational attributes cannot change
in time. Since online, adjust prices rating can
be a deciding factor among similar hotels with
similar prices
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Slide Number 5

6. Related Work
Previous research
•Ye, Law, & Gu (2009) studied the effect
online reviews had on hotel room sales on
the biggest Chinese IDS
•Zhang, Ye, & Law (2011) used the hedonic
price model to quantify the effect the quality
of hotel attributes have on room price based
on online reviews
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7. Related Work
• Studies focused on locational attributes as price
determinants:
– Espinet, Saez, Coenders, & Fluvia (2003) and Alegre,
Cladera, & Sard (2013) focused on sun and beach
destinations in different parts of Spain and both
concluded that proximity to the beach is a
determining factor on room price.
– Distance to other places, such as the city centre, was
only found to affect prices on some destinations, while
the polarity of the effect varied between customer
nationalities.
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Slide Number 7

8. Related Work
• Studies focused on locational attributes as price
determinants:
– A view of the sea was also found to increase the value
of the room in Mediterranean locations (Fleischer,
2012).
– Other studies concentrated on room specific attributes
and identified hot-tub, private bath and a larger room
to be determinant for bed-and-breakfasts (Monty &
Skidmore, 2003), and hairdryer and mini-bar for hotels
in Oslo (Thrane, 2007).
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9. Related Work
• Pastor (1999) focused on the hotel sector,
measuring the relationship between star
categories and the services published on hotel
guides, and their effect on price.
• However as of yet, no study has analysed the
relationship of online ratings and room price over
time.
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Slide Number 9

10. Method
• In previous work, a methodology to measure the
hotel Average Daily Rate (ADR) was developed
(Roman, Ibarguren, Gerrikagoitia, & TorresManzanera, 2013).
• A information gathering system has been be
developed to obtain review information along
with, policies, services, star category, location
and types of rooms
• Several different hedonic price functions will be
used
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11. Method
•
Every 24 hours, data on accommodation prices are collected automatically
•
The system asks for the price and availability of an overnight for the 1-28, 30, 45,
60 and 90 days -> Future price variation
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Slide Number 11

12. Method
Data Volume
Hotels
Records
Daily recs.
Hist. Series
Spain
11.569
140M
195K
5/2011
France
13.784
135M
300K
10/2011
Ireland
742
5M
18K
11/2012
Mediterranean Coastal Destination Sample
Croacia
86
323K
2k
Egypt
33
123K
1K
Greece
431
138K
10K
1.105
2,5M
18K
Morocco
217
812K
6k
Portugal
163
141K
4k
Tunisia
28
89k
1k
Turkey
678
2,3M
16k
Italy
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6/2013
Slide Number 12

13. Method
• Offered prices
• Extracted from Internet Distribution System
• Publicly available features of the hotel
•
•
•
•
•
Exact geographic location (coordinates)
Services
Policies
Room features (bed type, AC, etc.)
Customer rating
• Historic booking data
• From the hotel’s Property Management System
• Event Databases
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14. Method
Data Sets
•
•
•
•
•
•
1. Acommodation
2. Policy
3. Service
4. Product
5. Rating
6. Prices
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15. Method
2. Policy
accommodation_id
group
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
hotel_91748
Cancellation / Prepayment
Check-out
Pets
Accepted credit cards
Accepted credit cards
Accepted credit cards
Accepted credit cards
Accepted credit cards
Check-in
Groups
Groups
Children and extra beds
hotel_90599
hotel_90599
hotel_90599
hotel_90599
hotel_90599
hotel_90599
hotel_90599
hotel_90599
Cancellation / Prepayment
Check-out
Accepted credit cards
Accepted credit cards
Accepted credit cards
Accepted credit cards
Check-in
Pets
description
Cancellation and prepayment policies vary according to room
type.
Until 12:00 hours
Pets are not allowed.
American Express
Visa
Euro/Mastercard
Carte Bleue
Diners Club
From 15:00 hours
When booking more than 5 rooms
different policies and additional supplements may apply.
Cancellation and prepayment policies vary according to room
type.
Until 12:00 hours
American Express
Visa
Euro/Mastercard
Diners Club
From 14:00 hours
Pets are not allowed.
15
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16. Method
3. Service
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
hotel_90318
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Services
Internet
Parking
General
General
General
General
Meeting/banquet facilities
Business centre
Babysitting/child services
Laundry
Dry cleaning
VIP room facilities
Ironing service
Shoeshine
Car hire
Tour desk
Fax/photocopying
Concierge service
Special diet menus (on request)
Trouser press
Bicycle rental
Ticket service
Bikes available (free)
Vending machine (drinks)
Vending machine (snacks)
Public parking is possible at a location near
24-hour front desk
Newspapers
Non-smoking rooms
Facilities for disabled guests
16
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17. Method
4. Product
accommodation_id
name
adult_amount children_amount
hotel_91748
Superior Double or Twin Room
2
N
hotel_91748
Standard Double or Twin Room
2
N
hotel_91748
Standard Triple Room
3
N
hotel_91748
Junior Suite
2
N
hotel_91748
Standard Single Room
1
N
hotel_91748
Junior Suite with views
2
N
hotel_90599
Guggenheim Museum Package - Double or Twin Ro
2
N
hotel_90599
Double or Twin Room (1-2 Adults)
2
N
hotel_90599
Single Room
1
N
hotel_273500
Superior Double or Twin Room
2
N
hotel_273500
Standard Double or Twin Room
2
N
hotel_273500
Junior Suite (2 Adults + 2 Children)
2
2
hotel_273500
Double or Twin Room with Sofa Bed (3 Adults)
3
N
hotel_273500
Family Room (2 Adults + 1 Child)
2
1
hotel_273500
Junior Suite (2 Adults + 1 Child)
2
1
hotel_273500
Junior Suite
2
N
hotel_273500
Family Room (2 Adults + 2 Children)
2
2
hotel_273500
Double or Twin Room with Sofa Bed (2 Adults +
2
1
hotel_273500
Special Offer - Double or Twin Room
2
N
hotel_92284
Twin Room (interior)
2
N
hotel_92284
Twin Room Exterior
2
N
hotel_92284
Guggenheim Offer
2
N
17
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18. Method
5. Rating
accommodation_i
d
booking_date name
comfort value location clean services staff
hotel_94558
04/06/13solo
6.6
7.2
6.5
7.7
6.6
8.0
hotel_94558
04/06/13youngCouples
6.6
7.6
7.3
7.4
6.8
8.0
hotel_94558
04/06/13average
6.6
7.5
7.0
7.5
6.6
8.0
hotel_94558
04/06/13friendGroups
6.1
7.7
6.7
7.3
6.8
8.3
hotel_94558
04/06/13familiesYoungChildren
6.7
6.3
7.5
7.2
5..6
7.5
hotel_94558
04/06/13familiesOlderChildren
6.1
7.7
6.7
7..3
6.8
8.3
hotel_94558
04/06/13matureCouples
6.7
7.5
6.7
7.6
6.7
8.0
18
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Slide Number 18

19. Expected results
• The study will be to validate the effects
found in the literature within the scope
proposed in this work
• A data gathering process will be launched
periodically and changes in online rating
and hotel room prices will be analysed,
looking for causal relationships
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Slide Number 19