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Feasibility Study on the Use of Mobile
Positioning Data in Tourism Statistics
Big Data Seminar, 2nd June 2014
Ossi Nurmi
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)
13/06/2014 2Tietopalveluyksikkö/Viestintä
Eurostat Feasibility Study on the Use of
Mobile Positioning Data for Tourism Statistics
Project time: January 2013 – March 2014
The Aim of the Project
 Exploring the possibilities - and limits - of using mobile
positioning data stored by mobile network providers for
measuring tourism flows
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
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)
13/06/2014 6Tietopalveluyksikkö/Viestintä
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
13/06/2014 7Tietopalveluyksikkö/Viestintä
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
13/06/2014 8Tietopalveluyksikkö/Viestintä
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?
13/06/2014 9Tietopalveluyksikkö/Viestintä
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
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
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
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
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.
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.
Example: Domestic Trips Outside Usual
Environment
Using LAU-1 for defining usual environment
Using LAU-2 for defining usual environment
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
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
More Information
 More information and all reports of the Eurostat Feasibility
study can be found on the project website:
 http://mobfs.positium.ee/
13/06/2014 19Tietopalveluyksikkö/Viestintä

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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) 13/06/2014 2Tietopalveluyksikkö/Viestintä
  • 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) 13/06/2014 6Tietopalveluyksikkö/Viestintä
  • 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 13/06/2014 7Tietopalveluyksikkö/Viestintä
  • 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 13/06/2014 8Tietopalveluyksikkö/Viestintä
  • 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? 13/06/2014 9Tietopalveluyksikkö/Viestintä
  • 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/ 13/06/2014 19Tietopalveluyksikkö/Viestintä