Mobile telephones and mobile positioning data as source for statistics

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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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 Ahasrein.ahas@ut.ee

Chair of Human GeographyUniversity of Tartu