Transcript MOBILE POSITIONING AS A POSSIBLE DATA SOURCE FOR INTERNATIONAL TRAVEL SERVICE STATISTICS Jaanus Kroon Statistics Department, Bank of Estonia UN CONFERENCE OF EUROPEAN STATISTICIANS Seminar on.

MOBILE POSITIONING AS A POSSIBLE DATA
SOURCE FOR INTERNATIONAL TRAVEL
SERVICE STATISTICS
Jaanus Kroon
Statistics Department, Bank of Estonia
UN CONFERENCE OF EUROPEAN STATISTICIANS
Seminar on New Frontiers for Statistical Data Collection
31.10.2012, Geneva
Outline
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Background of the “story”
Exploring alternative data sources
The phenomena of mobile positioning
Methodological aspects
– Estimation of inbound travel
– Estimation of outbound travel
• Co-operation model
• Conclusions
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Background (1)
• Bank of Estonia - a provider of official statistics in Estonia,
– responsible for
• Monetary & Financial Statistics
• External Sector Statistics
• Balance of Payments, reflecting cross-border transactions, consists of many
sub-items, including
– Current Account
• International Trade in Services
• Simplified algorithm for “Travel Services”
– exports and imports by countries
Number of
travellers
x
Length of
stay
Border-crossing statistics
x
Daily
expenditures
+
Prepaid
travel agency
and hotel
services
+
Expenditures
of short-term
workers and
students
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Background (2)
• Data sources for Border-Crossing Statistics
Administrative Border
Control Statistics
Quarterly Border surveys
(NSI)
• Limitation: bases on citizenship/nationality not residency
• Inbound and outbound travellers and length of stay (Interviews)
• Replaced Administrative Border Control Data since 2008
Travel Agencies’ Survey
(NSI)
• Inbound and outbound travellers and length of stay
Household Survey (NSI)
• Outbound travel only
• Limitation: poor quality
• Changing environment
– 2004/2007 Entering into the Schengen: abolishment of border-controls
• Exploring alternatives (2007…)
– 2008… The economic crisis and remarkable budget cuts of NSI
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Exploring alternatives (1)
Alternatives
Pros
Cons
To finance the bordersurvey of NSI
• NSI experience
•Possibility to partly integrate
with visitor motivation surveys
•Time and labour intensive
•Unreasonably expensive
•Insufficient reliability
Implement an
accommodation statisticsbased assessment model
•Monthly frequency
•Easy to implement
•Reliable geographical allocation
•Low costs
•Additional costs regarding
regular calibration survey
•Does not cover outbound part
•Estimation errors
•High periodicity
Participate in the project
initiated by the Road Office •Supplement to harbour and
airport statistics
to install car-counters on
the road at border-crossings
Credit-card information,
based on Northern
European Transaction
Services (NETS)
•High periodicity
•Gives estimation on total
expenditures and indirect geo
allocations
•Only one service provider
•No administrative burden
•Low costs for compiler
•Investment costs
•Additional costs regarding
calibration survey
• Errors and quality issues
•Additional costs for calibration
survey
•Negative experience from
neighbouring countries
•“Noise” related to e-commerce
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Exploring alternatives (2)
Alternatives
Derive travelling statistics
from mobile-phone roaming
information
Pros
Cons
•High periodicity
•Representativeness (almost
everyone has a cell phone)
•Operational information in time
and space (incl. geographical
allocation)
•No administrative burden
•Lack of experience and practices
•Undefined co-operation model
with data providers
•Additional costs regarding the
calibration survey of mobile
usage pattern
•Remarkable IT resources for data
processing
• Mobile positioning as the final choice
– High quality, cost effective, low labour intensive
– Availability of potential partner experienced in using mobile positioning
data in urban and regional geography/planning
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Department of Geography, University of Tartu (Estonia) and spin-off
company, Positium LBS.
Scale effect: regular data exchange, calibration surveys
– Cooperation contract for data collection methodology and models
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2008-2010
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The phenomena of mobile
positioning
• Mobile positioning - locating (pinpointing) mobile telephones using radio
waves
– Active mobile positioning - tracking the location of mobile phones in real
time through a network of antennas
– Passive mobile positioning - uses location and activity information from
historical log files stored by mobile service providers (for charging
clients)
Activities in home network
or when roaming
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voice calls,
SMSes/MMSes,
mobile-net usage,
data transmission operations,
mobile supported GPS usage,
etc.
Data file
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SIM card ID (statistical pseudonym)
Date and time
Antenna ID with location data
Country ID
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Methodological aspects (1)
• Presumable residence of phone owners is determined by the registration
country of the SIM-card
• The methodology is based on the anonymised patterns of roaming
activities of mobile phones
– by non-residents in resident reporting operator network (inbound
travel)
– by reporting operator domestic clients in networks abroad (outbound
travel)
• Country and region specific aspects should be taken into account when
determining calculation algorithms:
– Same-day visits
• Exclusion of transit travel
– Overnight visits and length of stay
• Exclusion of long-term stay
– Exclusion of “cross-border noise”
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Methodological aspects (2)
• From the statistical point of view, mobile owners are a representative large
sample within a statistical population whose spatial behavior and
characteristics in time can be extended to the entire population
• Extension coefficients (weights) take into account when grossing up
– Market share of reporting mobile operators
– Mobile phone usage traditions
• abroad by age and social groups
• in Estonia by visitor country
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Inbound travel (1)
• Number of travellers
– number of roamed cell phones in domestic net
• Length of stay
– days between first and last activity
• Border countries: 2 visits 2 and 3 days
• Other countries: 1 visit 8 days
Roaming activities per day
by single mobile phone
Inbound travel (2)
• Cross-border noise
– Certain antennas should be detected and excluded
• sea transit, random border switching
Inbound travel (3)
• Transit travel
– Antennas in 10 transit corridors are detected and excluded
• Sea ports
• Airports
• Road transit corridors
Inbound travel (4)
• Results
Inbound travel (5)
• Quality
Outbound travel (1)
• Number of visits
– number of domestic phones roamed in foreign networks
• Lenght of stay
– days between first and last activity
In Estonia
Abroad
Outbound travel (2)
• Elimination of cross-border noise
– registration of phone roaming by Estonian residents that
are incidentally in the coverage area of foreign mobile
operators
• Destination and transit country
– Analyses of the travel pattern according to the length of
stay and number of countries visited per day
• One of the criteria is the distance from Estonia
• Long-term visits (residents working or studying abroad)
– Stay for over 183 days during the past 12 months.
Outbound travel (3)
• Example: number of days by countries visited
Outbound travel (4)
• Example: the quality
– “Blue” – official statistics until 2009
– “Red” – mobile positioning results
Egypt
Turkey
Co-operation model
Positium LBS,
permanent
outsourcing
contractor
• Data collection and processing (monthly)
• Compilation
• Process is a part of location based services data
model provided to public
• Calibration and mobile usage surveys
• Data verification and validation
Bank of
Estonia
• indirect data sources (statistics of ports, EU administrative
border, accommodation statistics, the press, etc.)
• Input for monthly and quarterly external sector
statistics
• Publishing as official statistics on website on a
quarterly basis since 2012
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Conclusions (1)
• Advantages
– In time data
• information as co-product is already stored by mobile operators as the owner of
the data source
– Cost effective
• No direct costs associated with the network of interviewers
• No burden for travellers as potential respondents.
• Disadvantages
– Tailor made methodology (universal does not exists)
– Legal and privacy issues
– Sophisticated data processing and storage
– Co-operation with mobile operators as statistical reporters
– Sampling and calibration issues (total population is unknown)
• models need to be re-estimated according to changes in economic environment
– Unknown future / technical progress (ww wifi, internet phones etc.)
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Conclusions (2)
• Challenges
– Mobile positioning has wider possibilities to serve official statistics as a
data source in
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Regional visitor statistics
Domestic travel statistics
Detailed and specified research
Etc.
– In Estonia it would be legally possible to request data on mobile
positioning directly from the source to serve official statistics
• First priority to already collected, readily available data
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References
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International Recommendations for Tourism Statistics 2008. United Nations 2010.
Mobiilpositsioneerimisel põhinev väliskülastajate turismistatistikute uuring. OÜ
Positium LBS, Eesti Pank; Tartu 2009.
Mobiilpositsioneerimisel põhinev väliskülastajate turismistatistikute uuring:
penetratsioonimudeli kirjeldus. OÜ Positium LBS, Eesti Pank; Tartu 2009.
Mobiilpositsioneerimisel põhinev Eesti residentide välisturismistatistikute uuring.
OÜ Positium LBS, Eesti Pank; Tartu 2010.
Tiru, M. & Ahas, R., “Using mobile positioning data for tourism statistics:
methodological and legal issues”. 10th International Forum on Tourism Statistics,
Portugal 2010.
Ahas, R., Tiru, M., Saluveer, E. & Demunter, C., “Mobile telephones and mobile
positioning data as source for statistics: Estonian experiences” Conference on New
Techniques and Technologies for Statistics, 2011.
Ahas, R. Aasa, A., Roose, A., Mark, Ü., Silm, S. 2008. Evaluating passive mobile
positioning data for tourism surveys: An Estonian case study. Tourism
Management 29(3): 469–486.
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THANK YOU!
[email protected]
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