Feasibility Study on the Use of Mobile Positioning Data in Tourism Statistics, Ossi Nurmi
1. Feasibility Study on the Use of Mobile
Positioning Data in Tourism Statistics
Big Data Seminar, 2nd June 2014
Ossi Nurmi
2. Agenda
Eurostat Feasibility Study on the Use of
Mobile Positioning Data for Tourism Statistics
Data access in Finland
Feasibility of use: coherence (in tourism statistics)
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3. Eurostat Feasibility Study on the Use of
Mobile Positioning Data for Tourism Statistics
Project time: January 2013 – March 2014
4. The Aim of the Project
Exploring the possibilities - and limits - of using mobile
positioning data stored by mobile network providers for
measuring tourism flows
5. Main Project Objectives
Assess feasibility to access databases with mobile positioning
data in European countries
Assess the feasibility to use mobile positioning data for
tourism statistics in the European context
Identify, discuss and address the main challenges for
implementation
Assess the potential impact on cost-efficiency of data
production
Assess the possibility to expand the methodology to other
domains and define joint algorithms
6. Accessing Mobile Positioning Data in Finland
Main mobile network operators in Finland are Elisa, Sonera
and DNA
Two main related authorities are the Data Protection
Ombudsman (Tietosuojavaltuutettu) and the Finnish
Telecom Regulatory Authority (Viestintävirasto)
Statistics Finland had initial meetings with all operators and
the main authorities
Based on the request of Statistics Finland, the Office of the
Data Protection Ombudsman prepared a statement
concerning the use of CDRs (call detail records)
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7. Barriers of Access in Finland
Main barriers of access in Finland
1. Current Statistics Act doesn’t grant Statistics Finland the
authority to collect mobile positioning data from operators
2. According to the Act of Protection of Privacy in Electronic
Communications, the data containing identification may
only be processed by a person employed or acting on
behalf of the telecommunications operator
3. Raw mobile positioning data consitutes as personal data
even if subscriber ID is anonymized
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8. Possible Paths for Using Mobile Positioning Data in
Statistics
Voluntary basis: Operators process data into statistical
aggregates – either themselves or by a third party
Legal basis: The national legislation should be updated to
authorize national statistical institutes to obtain and process
the raw mobile positioning data
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9. Feasibility of Use: Coherence in Tourism Statistics
Task coordinator Statistics Finland
In-depth testing of tourism statistics compiled based on
mobile positioning data
Analysis of coherence compared to reference statistics
Key questions to be addressed:
Domain coverage: inbound, outbound and domestics
tourism?
Tourism breakdowns: same-day and overnight trips?
Coherence to existing statistical indicators? Reasons for
deviations?
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10. Reference Data – Tourism Statistics
Mobile positioning data Supply statistics
(=accommodation)
Demand statistics
Target population Outbound / domestic:
Population of the reference
country Inbound: non-
resident tourists
Accommodation
establishments (all or
above threshold)
Population over 15
years
Frame Data of mobile phone
subscribers
Business / tourism
register.
Population register or
area frame
Source data Administrative Enterprise survey Survey of individuals
Sampling design Census / sample Census / sample Sample
Time units
available
Day / week / month etc. Month Quarter / Year
Regional areas Any customized area NUTS 2 Country
Nationality
breakdown
Possible Possible Only residents
Timeliness 1-2 weeks 5-8 weeks 7-8 weeks
Legal basis None Regulation 692/2011 Regulation 692/2011
11. Reference Data – Related Statistics
Mobile positioning
data
Border interview Passenger
statistics
Border control
Target
population
Outbound / domestic:
Population of the
reference country
Inbound: non-resident
tourists
Inbound visitors to
the reference
country.
All passengers by
transport mode
(air / sea / train
etc.)
All passengers
passing through
border control.
Frame Data of mobile phone
subscribers
Main border crossing
locations
Register of
transport
authorities.
Register of border
authority.
Source data Administrative Survey of individuals Administrative Administrative
Sampling design Census / sample Sample Census Census
Time units
available
Day / week / month etc. Month / quarter Day / week /
month
Day / week /
month
Regional areas Any customized area Country Country Country
Nationality
breakdown
Possible Possible Not possible Possible
Timeliness 1-2 weeks 10-20 weeks 1-2 weeks 1-2 weeks
Legal basis None None EU Regulations National
12. Example: Very Good Coherence
Mobile positioning data provides very good consistency overall and broken down into countries. There is slight
over-coverage as more trips are registered.
Inbound Overnight Trips: Accommodation Statistics, EU27>EE
0
50 000
100 000
150 000
200 000
250 000
300 000
350 000
Jan-09
Mar-09
May-09
Jul-09
Sep-09
Nov-09
Jan-10
Mar-10
May-10
Jul-10
Sep-10
Nov-10
Jan-11
Mar-11
May-11
Jul-11
Sep-11
Nov-11
Jan-12
Mar-12
May-12
Jul-12
Sep-12
Nov-12
MOB_IN(EU-27)_OVERNIGHT SUPPLY_EE(EU-27)_ARR
13. Example: Very good coherence
Most passengers travel by ferry between Finland and Estonia. Consistency is excellent. Number trips is less in
mobile positioning other nationalities (than FI and EE) and transit passengers are on the ferry
Ferry passengers between Finland and Estonia
14. Example: Moderate Coherence
Outbound Overnight Trips: Demand Statistics, EE>EU27
0
50 000
100 000
150 000
200 000
250 000
300 000
350 000
400 000
450 000
500 000
Q1-09
Q2-09
Q3-09
Q4-09
Q1-10
Q2-10
Q3-10
Q4-10
Q1-11
Q2-11
Q3-11
Q4-11
Q1-12
Q2-12
Q3-12
Q4-12
MOB_OUT(EU-27)_OVERNIGHT DEMAND_EE(EU-27)_OVERNIGHT
Mobile positioning data contains many such outbound trips that do not qualify as tourism trips in the Demand
Survey either due to frequency, purpose or duration of the trip.
15. Example: Low Coherence
0
20 000
40 000
60 000
80 000
100 000
120 000
140 000
160 000
180 000
Jan-09
Mar-09
May-09
Jul-09
Sep-09
Nov-09
Jan-10
Mar-10
May-10
Jul-10
Sep-10
Nov-10
Jan-11
Mar-11
May-11
Jul-11
Sep-11
Nov-11
Jan-12
Mar-12
May-12
Jul-12
Sep-12
Nov-12
MOB_EE(RU) BORDCONT_EE(RU)
Inbound Overnight Trips: Border Control, RU>EE
Border control registers all trips, regardless of purpose. Very short trips close to the border may be seriously
underestimated in mobile positioning data because these tourists might not use the roaming services of MNOs in the
inbound country.
16. Example: Domestic Trips Outside Usual
Environment
Using LAU-1 for defining usual environment
Using LAU-2 for defining usual environment
17. Coherence: Strength/Weaknesses
Main strengths of mobile positioning data
1. Excellent consistency over time for the number of trips and nights spent
2. Superior coverage for overnight trips when compared to Supply Statistics: covers also trips in
non-rented or non-registered accommodation
3. Possibility to produce breakdowns based upon region and nationality
4. Possibility to apply rules for usual environment
5. Many short trips are excluded from mobile positioning data
Main weaknesses of mobile positioning data
1. No additional data about the trip
(purpose, expenditure, accommodation, means of transport)
2. Potential problems in the method for accurate breakdown of trips into same-day and overnight
trips
3. Over-coverage issues related to usual environment
(purpose, duration or frequency of trip)
4. Under-coverage issues based on mobile phone use:
some tourists don’t use their phone abroad
18. Main Conclusions
• Mobile positioning data alone cannot fulfill the requirements of
the regulation on tourism statistics (EU 692 / 2011)
• Mobile positioning data provides good estimates for the
number of trips, nights spent and destination
• Mobile positioning data doesn’t produce information on
purpose of trip, type of accommodation or expenditure
need for traditional surveys
19. More Information
More information and all reports of the Eurostat Feasibility
study can be found on the project website:
http://mobfs.positium.ee/
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