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Autori nimiPresentatsiooni teema 1 Mobile positioning as a data source for estimation of travel statistics Jaanus Kroon Head, Balance of payments and Economic Statistics Department 4.10.2010 Paris WPTGS; OECD Slide 2 Autori nimiPresentatsiooni teema 2 Outline Current data sources and main challenges The idea of mobile positioning and the project of Eesti Pank Estimation of inbound travellers Estimation of outbound travellers Conclusions Slide 3 Autori nimiPresentatsiooni teema 3 Simplified algorithm of travel account estimation in BoP Debits and credits Countries Number of travellers and lenght of stay Daily expenditures x Travel Prepaid travel agency and hotel services += Expenditures of short-term workers and students + Slide 4 Autori nimiPresentatsiooni teema 4 Data sources before 2009 DebitsCredits Number of travellers and lenght of stay Extra EU border statistics (MIS) Household survey (NSI) (Air)ports statistics (Ports) Travel Agencies Survey (NSI) Extra EU border statistics (MIA) Accomodation Survey (NSI) (Air)ports statistics (Ports) Travel Agencies Survey (NSI) Daily expenditures Household Survey (NSI)Border Survey (BoE + NSI) Pre paid travel agency and hotel services Household survey (NSI) Travel Agencies Survey (NSI) Expenditures of short-term workers and students Estimation Poor coverage (Shengen Treaty) Cancelling of NSI surveys Slide 5 Autori nimiPresentatsiooni teema 5 Data sources after 2009 DebitsCredits Number of travellers and lenght of stay Extra EU border statistics (MIS) Household survey (NSI) (Air)ports statistics (Ports) Extra EU border statistics (MIA) Accomodation Survey (NSI) (Air)ports statistics (Ports) Daily expenditures Household Survey (NSI) Credit card statistics (BoE) Border Survey (BoE + NSI) Credit card statistics (BoE) Pre paid travel agency and hotel services Household survey (NSI) BoP surveys (BoE) Expenditures of short-term workers and students Estimation Slide 6 Autori nimiPresentatsiooni teema 6 Challenge: how to estimate border crossing statistics? Regular Statistical Surveys of border crossing? Expensive Quality issues? (sufficient geography etc.) Installing car-counters on border-roads? Only indirect indicator Needs additional Surveying of the structure of cars/trucks/travellers Deriving border-crossing statistics from mobile- phone roaming/positioning? The best balance in between merits and costs Methodology needs regular re-estimations Slide 7 Autori nimiPresentatsiooni teema 7 ICT in Travel Studies ICT infulences travel Travel influences ICT Slide 8 Autori nimiPresentatsiooni teema 8 The idea of mobile positioning Mobile positioning - registering signals of cellphone usage and location by mobile phone network antennas When you travel to a foreign country, your mobile phone keeps working via foreign network: you are roaming. Registering roming activities could be the data source for estimating numbers of travellers and their lenght of stay Simplification: customer of a phone operator is a resident of the same country Slide 9 Autori nimiPresentatsiooni teema 9 Co-operation with Tartu University spin-off project LBS Positum (www.positium.ee) founded in 2001 in cooperation with geographers, city planners and architects services: using the idea of mobile positioning and methods for geographical studies and city planning to organize better and safer living, planning the city and sustainable environment Data source EMT (major of 3 mobile providers in Estonia) 2 procurement contracts for developing models for: Inbound travel 2008-2009 Outbound travel 2009-2010 Regular monthly cooperation (data license) Slide 10 Autori nimiPresentatsiooni teema 10 Estimation of inbound travellers (1) Slide 11 Autori nimiPresentatsiooni teema 11 Estimation of inbound travellers (2) # of travellers ~ # of abroad registered roamed cell phones Lenght of stay - Days between first and last phone operation -Border countries: 2 visits 2 and 3 days -Others: 1 visit 8 days Slide 12 Autori nimiPresentatsiooni teema 12 Estimation of inbound travellers (3) Nationality according to the country of origin of SIM- card Differentiation: Elimination of noise (sea transit, random border swiching) Transit travel (airport, transit-road corridors) Permanent (border) workers and students One day visitors Tourists Grossing up / calibration Penetration model Slide 13 Autori nimiPresentatsiooni teema 13 Estimation of inbound travellers (4) Noise on borders (Certain antennas should be excluded) Slide 14 Autori nimiPresentatsiooni teema 14 Estimation of inbound travellers (5) Foreign workers more than 7 visits more than 30 days Slide 15 Autori nimiPresentatsiooni teema 15 Estimation of inbound travellers (6) Transit Mobile positions in defined area only Sea ports Airports Certain road corridors: Ikla-Prnu- Tallinn Riga-Pskov Slide 16 Autori nimiPresentatsiooni teema 16 Estimation of inbound travellers (7) Visitors (up to 24 hr) Slide 17 Autori nimiPresentatsiooni teema 17 Estimation of inbound travellers (8) Tourists (over 24 h) Slide 18 Autori nimiPresentatsiooni teema 18 Grossing up sampling and calibration Bases on real statistical data series available up to 2008 Calibration according to currently available border- crossing indicators (Extra-EU statistics, Sea-ports and airport indirect statistics) Statistical models for each country or country groups, taking into account coverage (only 1 network) mobile phone usage pattern (surveys) Pre-paid cards & cheap roaming service cards Estimation of inbound travellers (9) Slide 19 Autori nimiPresentatsiooni teema 19 Estimation of inbound travellers (10) Accommodation statistics Slide 20 Autori nimiPresentatsiooni teema 20 Estimation of inbound travellers (11) Slide 21 Autori nimiPresentatsiooni teema 21 Estimation of outbound travellers (1) Lenght of stay and the geography Slide 22 Autori nimiPresentatsiooni teema 22 Estimation of outbound travellers (2) Determining the number of visits Slide 23 Autori nimiPresentatsiooni teema 23 Estimation of outbound travellers (3) Number of visits by countries visited Slide 24 Autori nimiPresentatsiooni teema 24 Destination and transit country Analyses of the travel pattern according to the lenght of stay and number of countries visited per day Cross border worker if # of trips during 6 month is over 6 Sum of the lenght of days exceeds 30 days Analyses of final destinations (over the world travellers) Estimation of outbound travellers (5) Slide 25 Autori nimiPresentatsiooni teema 25 Estimation of outbound travellers (4) Number of days by countries visited Slide 26 Autori nimiPresentatsiooni teema 26 Elimination of noise Estonian border masts Border masts abroad Seamen Estimation of outbound travellers (6) Slide 27 Autori nimiPresentatsiooni teema 27 Penetration model needs to take into account The market share of EMT Other operators (2, compensation cofficents) # of non-phone users abroad Workers EMT detailed user market research Data calibration Extra EU border crossing Ports and airport statistics Accommodation statistics by NSI Estimation of outbound travellers (7) Slide 28 Autori nimiPresentatsiooni teema 28 Estimation of outbound travellers (8) First results (red travel statistics, blue model) Slide 29 Autori nimiPresentatsiooni teema 29 Conclusions still too early to make So far we have covered the hole in statistics and become the only one institution in Estonia providing border-crossing statistics been cost effective (data licenses are cheaper than regular border-crossing surveying) taken advantage of partner scale-effect (one data source, wide range of usage possibilities) Major questions models need to be re-estimated according to changes in economic environment (no real data besides) developments (competition) on mobile market and ICT The future of mobile phones vrs Skype? Slide 30 Autori nimiPresentatsiooni teema 30 Thank you! CHALLENGE FOR STATISTICS! Mobile positioning would have much wider possibilities to serve statistics as a data source Slide 31 Autori nimiPresentatsiooni teema 31 Scientific Articles (not directly about current topic) Tiru, M., Saluveer E., Ahas, R., Aasa, A. 2009. Web-based monitoring tool for assessing space-time mobility of tourists using mobile positioning data: Positium Barometer. Journal of Urban Technology, 17(1): Ahas, R. Aasa, A., Roose, A., Mark, ., Silm, S. 2008. Evaluating passive mobile positioning data for tourism surveys: An Estonian case study. Tourism Management 29(3): 469486. Kuusik, A., Ahas, R., Tiru, M. 2009. Analysing Repeat Visitation on Country Level wirh Passive Mobile Positioning Method: An Estonian Case Study. XVII Scientific Conference on Economic Policy, Estonia 13.07.2009 in Tartu and Vrska. Ahas, R., Saluvee, E., Tiru,M. and Silm, S. 2008.Mobile Positioning Based Tourism Monitoring System: Positium Barometer. In: OConnor, P., Hpken, W. and Gretzel, U. (Eds.), Springer Computer Science: Information and Communication Technologies in Tourism, pp. 475-485. Ahas, R., Aasa, A., Silm, S., Tiru, M. 2007. Mobile positioning data in tourism studies and monitoring: case study in Tartu, Estonia. In: Sigala, M., Mich, L., Murphy, J. (Eds.), Springer Computer Science: Information and Communication Technologies in Tourism, ISBN: 978-3-211-69564-7, pp. 119-128.