mobile telephones and mobile positioning data as source for statistics
TRANSCRIPT
Mobile telephones and mobile positioning data as source for
statistics: Estonian experiences
Prof. Rein Ahas, University of Tartu, EstoniaMargus Tiru & Erki Saluveer, Positium LBS
Christophe Demunter, EUROSTAT
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the world has changed abolishment of border controls (e.g. Schengen)
managerial / political decision to change the production methods for official statistics e.g. the so-called “Eurostat vision for the next decade” increasing user needs vs. burden & budget reduction
finding synergies in 3 interrelated fields of statistics passenger mobility balance of payments (travel item) tourism
promising research results
New methods for travel / tourism statistics …Why?
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capturing physical flows gps device to monitor mobility, travel, tourism during
a short period (e.g. one or two weeks) alternative to ‘bookkeeping system’ or ‘diary’
mobile positioning to monitor during a longer period alternative to ex-post questionnaires
follow up sample surveys qualitative information on the trip (transport,
accommodation, etc.), from a smaller sample
capturing monetary flows credit card information (primary or auxiliary data)
Tourism, travel and mobility statistics in the 21st century?A combination of interacting sources
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Wishful thinking?
only the flavour of the month?
experiments are happening in some countries!
or
Self-fulfill ing prophecy?
the belief can influence the behaviour…
It’s at least food for thought!!
Tourism, travel and mobility statistics in the 21st century?Will we arrive at our destination?
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improved timeliness less collecting and processing time
improved data quality less data entry error less recall bias (esp. for short or same-day trips) more consistency and harmonisation because of the
use of algorithms rather than the subjective feeling
reduction of burden on respondents and administrations
cost-efficient statistics
Tourism, travel and mobility statistics in the 21st century?The “dream” part
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access to databases privacy continuity of access cost
systematic and sampling bias e.g. mobile phone penetration, use of foreign sim-
cards when travelling, switching of to avoid roaming costs, bias linked to the digital divide in society
huge amount of information but no detail e.g. breakdown private vs. business trip e.g. means of transport used
Tourism, travel and mobility statistics in the 21st century?The “nightmare” part
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methodological challenges finding the relevant observations in huge databases translate the concept “usual environment” into a
algorithm using objective criteria need for longitudinal data (in order to define what is
the anonymised ID’s usual environment)
trust convincing users of the robustness of the data official statisticians will need a mental switch
Tourism, travel and mobility statistics in the 21st century?The “nightmare” part (2)
PartnersPositium LBSspin-off company of University of Tartu
Margus Tiru Development & testing
Bank of Estonia Andres KergeJaanus Kroon
End-user since 2008 Methodological development
EMTEstonian Mobile operator,Ericsson system
Argo KiviloData provider, system development
Mobile positioning
Mobile positioning is locating (pinpointing) mobile telephones using radio wave
Passive mobile positioning
Location information from memory files of mobile operator
Active mobile positioning:
- mobile tracking
- locating telephones with special queries
“find phone 3725035xxx” with 5 min intervals”
- Metapos system
Telephone use - based statistics
Billing LOG = easy and cheap source for statistics
Passive mobile positioning in tourism statistics
Incoming tourism
Nationality of tourist = Original registration country of phone
Identity of tourist = Randomly given ID. Not related to phone nr.
Phone use by ID 32xxxx in Estonia
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11 Calls Days
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10-11 2
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Software: Positium Data Mediator
Roamingdata
Data-base
Operator 1 Operator 2
Data managementDepersonalising&Privacy
Data Processing
Quality managementSamplingGeo-interpolationCustomising
Sampling IssuesDifferent phone use pattern for different tourists
Business/leisure/transitCountryAge group, Gender
Special casesNo phone usersMultiple phone users
Border noise:detected, evaluated, removed with special model
Statistics generated
Visitors = number of ID-s by nationalities
Visits = number of visits made by visitors
Visited days = number of days spent by visitors
Visited nights = overnight stays in destination
Quantitative tourism statistics Foreigners in Estonia
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Pär…
System developed with Bank of Estonia
Travel item for payment balanceUsed since 2008
Visitor segments (classification by Bank of Estonia)
Transit visitors:airportsharbours highways
<2 h; <3h ...
Visitor segments (classification by Bank of Estonia)
1- day visitors
1+x day visitors = tourists
Frequent visitors = foreign workers, students, real estate owners...
Incoming Tourism
Correlation with accommodation data
Outgoing tourism
Estonians abroad
Estonians using roaming services abroad
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5_6_ ..._22
22_23_..._29
Statistics for outgoing tourism
Persons
Days in Countries
Transit / tourism
Foreign workers & frequent visitors
Examples: outbound tourism toGermany and Egypt
Conclusions
Problems with mobile positioning data
Sampling: Penetration ? Phone use?
Privacy: Legislation, psychology
How to reach operators?
Too much data: need for new software...
Positium Data Mediator
- processes data from mobile operators’ databases
privacy protectioncommercial secrets protectiondata process and output
- is located in operator’s system, under its control and delivers datathat is approved by operator
Advantages of mobile positioning:
Way to get more complete tourism and travelstatistics in opening Europe.
Geographically-temporally good preciseness.
Cost-effective.
Fast data collection.
Thank You!Prof. Rein [email protected]
Chair of Human GeographyUniversity of Tartu