Transcript Diapositiva 1

Building a
tourism
intelligence
system using
big data
Jon Kepa Gerrikagoitia, Ph.D.
OPTIMA / Optimization Modelling & Analytics
ICT - European Software Institute Division
[email protected]
Aurkene Alzua Sorzabal, Ph.D.
CICtourGUNE
[email protected]
The importance of tourism worldwide
Tourism is an economic phenomenon concerning the movement of people to places
outside their usual environment for either personal or professional purposes.
Great impact of tourism on the economy (employment, income): need for detailed and
updated information in “real time”
employment
GDP
UNWTO (2014)
Our challenge
Incorporate new measurement methods based on digital footprint (Big Data) as an
alternative and complementary source in the statistical production
Why:
Efficiency (cost, time)
How :
Tourism Observatory as
intelligence platform in tourism
to leverage innovative business
models
based
on
data
economy
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Tourism Observatories – conceptual framework
The
Relationship
between
statistics
and technology
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Tourism Observatories –sources and methods
Tourism Observatories – technology
Tourism Observatories – types of analytics
Dynamic Pricing monitor - Big data and its uses in the tourism statistics
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Official figures are published with a delay up to weeks. The system can publish the data at the end of
the collection period (for example the last day of the month)
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Good fit and strong correlation between pricing official statistics and the monitor’s data. Difference
aprox. 5%
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Modelling and prediction of hotel occupancy rates based on room prices offered online
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Dynamic pricing patterns and impact
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Hotel occupancy estimates at subnational level, Basque Country (Spain)
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Data: 1.984.149 observations for the Basque Country from 2013-01-01 to 2013-12-31
Method: The system collects double room price 1,..., 28, 45, 60, and 90 days in advance of the target date.
For each hotel, three percentiles (P
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30
, P , and P ) have been used as the bounds:
70
99
Seg1 low prices
Seg2 normal or middle prices
Seg3 high prices
Seg4 unusually high prices
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Results:
Fitted linear regression model
Model stimates and residuals
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Occupancy prediction model at subnational level, Basque Country (Spain)
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Model that allows to predict occupancy rates before the official figures are available
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Segmentation bounds obtained for the 2013 data (training set) and model are applied to
data for 2014 (test set)
Predictions for the Basque Country for 2014
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Price, seasonality and trend
Spain, Basque Contry, San Sebastian and Rioja
in 2014
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Destination performance analysis - Bilbao
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Benchmarking Regions in Spain
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Benchmarking Regions in Europe (France, Spain, Ireland)
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Dynamic Pricing monitor – Benchmarking Countries (France, Spain, Ireland)
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Dynamic Pricing monitor Benchmarking cities (Bilbao, San Sebastian, Vitoria)
June – September 2013
June – September 2014
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Dynamic Pricing monitor - Big data and its uses in the tourism statistics
Informal accommodation monitoring - Airbnb - July 2015
Apartment - w (N=622)
Mean price (€)
room
Araba
Bizkaia
Gipuzkoa
35
54,1
60,2
119
173,5
apartment 130
airbnb offer in july in the Basque Country
Private room - p (N=437)
Bizkaia
32%
Araba
2%
Gipuzk
oa
66%
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Social Media Monitor
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Monitoring platform and active listening in social media that allows
Learn and discover: what (concepts) - how (polarity) - where (sources
of opinion)
and management: early warning, real-time monitoring
online reputation using language processing technologies,
visualization and analytical modeling
It has been applied in the fields of Tourism, Culture, Territory, Transport
and Innovation models.
Destination Image Framework
Results
Results
Destination Web Monitor
Destination Web Monitor (DWM) is “a system to measure, analyse, and
model the behaviour of visitors in different virtual areas in which a
destination is promoted and with the objective of providing benchmarking
ratios that facilitate strategic surveillance and intelligent marketing
policies”
Destination Web Monitor
Descriptive analysis
Typologies
Navigation
patterns
Thank you !
Eskerrik asko!
Muchas gracias !
Jon Kepa Gerrikagoitia, Ph.D.
OPTIMA / Optimization Modelling & Analytics
ICT - European Software Institute Division
[email protected]
Aurkene Alzua Sorzabal, Ph.D.
CICtourGUNE
[email protected]