KITE - A Knowledge Base for Intermodal Passenger Travel in Europe. Andreas Frei

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1 KITE - A Knowledge Base for Intermodal Passenger Travel in Europe Andreas Frei Travel Survey Metadata Series 31 January 2013

2 Travel Survey Metadata Series KITE - A Knowledge Base for Intermodal Passenger Travel in Europe Andreas Frei IVT, ETH Zürich ETH Hönggerberg, CH-8093 Zürich January 2013 Abstract Travel behaviour surveys have to win and then maintain the cooperation of respondents from the first to the last contact with them. While not excessively demanding, they do require respondents to engage in a task with a highly variable response burden. This is due to the varying number of journeys undertaken during the reporting period. For long distance travel this can range from zero to dozens of journeys in a typical eight week reporting period. The details about each journey are also substantial (duration, timing, mode, costs, (route) of each stage, i.e. vehicle used), so that respondents have to be conscientious. The specific challenge of longdistance travel surveys is therefore to find a balance between the need to capture the correct number of all such journeys, while obtaining detailed information for at least some of them. In the Framework of the KITE Project (A Knowledge Base for Intermodal Passenger Travel in Europe) a new survey methodology based on the MEST (Methods for European Surveys of Travel Behaviour) and INVERMO (Intermodale Vernetzung) approaches has been developed which contains a journey roster with basic descriptions of long distance journeys and a stage form for the detailed information about the last previous three long distance journeys. During the November 2008 and February persons were surveyed with two different protocols. The first protocol was used in Switzerland and Portugal and consists of a full CATI for the long-distance travel survey and a written part for the SP questionnaire. In Czech republic the same survey was carried out as face-to-face interviews. Keywords travel behaviour survey Preferred citation style A. Frei (2013) KITE - A Knowledge Base for Intermodal Passenger Travel in Europe, Travel Survey Metadata Series, 31, Institute for Transport Planning and Systems (IVT); ETH Zürich, Zürich.

3 1.0 Document Description Citation Title: Identification Number: Authoring Entity: Other identifications and acknowledgements: Producer: Copyright: KITE - A Knowledge Base for Intermodal Passenger Travel in Europe KITE Andreas Frei (IVT ETHZ) KW Axhausen Andreas Frei Institute for Transport Planning and Systems Date of Production: Software used in Production: Nesstar Publisher

4 2.0 Study Description Citation Title: Identification Number: Authoring Entity: Producer: KITE - A Knowledge Base for Intermodal Passenger Travel in Europe KITE Andreas Frei (IVT ETHZ) Andreas Frei KW Axhausen Date of Production: Software used in Production: Funding Agency/Sponsor: Grant Number: Distributor: Nesstar Publisher European Union TREN/06/FP6TR/S / KITE Andreas Frei

5 Study Scope Keywords: travel behaviour survey, long-distance travel Topic Classification: long-distance travel Abstract: Country: Geographic Coverage: Unit of Analysis: Universe: Travel behaviour surveys have to win and then maintain the cooperation of respondents from the first to the last contact with them. While not excessively demanding, they do require respondents to engage in a task with a highly variable response burden. This is due to the varying number of journeys undertaken during the reporting period. For long distance travel this can range from zero to dozens of journeys in a typical eight week reporting period. The details about each journey are also substantial (duration, timing, mode, costs, (route) of each stage, i.e. vehicle used), so that respondents have to be conscientious. The specific challenge of long-distance travel surveys is therefore to find a balance between the need to capture the correct number of all such journeys, while obtaining detailed information for at least some of them. In the Framework of the KITE Project (A Knowledge Base for Intermodal Passenger Travel in Europe) a new survey methodology based on the MEST (Methods for European Surveys of Travel Behaviour) and INVERMO (Intermodale Vernetzung) approaches has been developed which contains a journey roster with basic descriptions of long distance journeys and a stage form for the detailed information about the last previous three long distance journeys. During the November 2008 and February persons were surveyed with two different protocols. The first protocol was used in Switzerland and Portugal and consists of a full CATI for the long-distance travel survey and a written part for the SP questionnaire. In Czech republic the same survey was carried out as face-to-face interviews. Switzerland, Czech Republic, Portugal Random sample of the whole population in the three surveyed countries. In Switzerland only the French and German speaking part. Household and Person Persons 15 years and older

6 Methodology and Processing Time Method: Sampling Procedure: Mode of Data Collection: November 2008 and February 2009 Retrospective the last 8 weeks Random sample for Switzerland and Portugal Quota sample for the Czech Republic CATI and postal in Switzerland and Portugal Face-to-face interviews in the Czech Republic

7 Sources Statement

8 3.0 File Description File: KITE.NSDstat Number of cases: 3542 No. of variables per record: 33 Type of File: NSDstat

9 4.0 Variable Description Variable Groups Household Person Household Person Journey roster Vehicles Regular trips non-regular journeys SP-Dataset Variables within Household countrycode ID_Person Presence of a disability affecting travel Type of disability Highest education level CH Highest education level CZ Highest education level PT Employment status Number of paid working hours/week Job title Ownership of frequent flyer card of an airline Ownership of a railway discount card Ownership of a drivers license Car availability Languages able to speak Age Gender Variables within Person countrycode ID_Person What is the type of accommodation of this residence? Ownership of accommodation Internet access Number of cars and vans owned Number of motorcycles Number of further vehicles Existence and locations of second residence Number of visits to other residences in the last 6 months Household Income Household Income Household Income Age Gender

10 Number of household members Journey roster Variables within Journey roster countrycode ID_Person What is the type of accommodation of this residence? Number of journeys the last 8 weeks Number of non regular journeys the last 8 weeks of regular travelers Regular journeys the last 8 weeks Number of regular journeys the last 8 weeks

11 Variables

12 Variable: countrycode Value Label Frequency 1. Switzerland Czech Republic Portugal 1257 Range of Valid Data Values: 1 to 3

13 Variable: ID_Person Range of Valid Data Values: 1 to Minimum : 1 Maximum : Mean : Standard deviation :

14 Variable: What is the type of accommodation of this residence? Value Label Frequency 1. House High-rise flat Terrace Bedsit Flat Other don t want to say don t know 139 Range of Valid Data Values: 1 to 9999

15 Variable: Ownership of accommodation Value Label Frequency 1. Own Rented Sublet don t want to say don t know 276 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

16 Variable: Internet access Value Label Frequency 1. none Dial-Up / ISDN TV Cable ADSL (W)LAN don t want to say don t know 122 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

17 Variable: Number of cars and vans owned Range of Valid Data Values: 0 to 9999 Minimum : 0 Maximum : 9999 Mean : Standard deviation :

18 Variable: Number of motorcycles Range of Valid Data Values: 0 to 9999 Minimum : 0 Maximum : 9999 Mean : Standard deviation :

19 Variable: Number of further vehicles Range of Valid Data Values: 0 to 9999 Minimum : 0 Maximum : 9999 Mean : Standard deviation :

20 Variable: Existence and locations of second residence Value Label Frequency Variable Format: character

21 Variable: Number of visits to other residences in the last 6 months Value Label Frequency

22 don't know no answer Sysmiss Range of Valid Data Values: 0 to 9999

23 Variable: Household Income Value Label Frequency 1. Below 2000 CHF to 4000 CHF to 6000 CHF to 8000 CHF to CHF to CHF to CHF CHF and more don t want to say don t know 102 Sysmiss Range of Valid Data Values: 1 to 9999

24 Variable: Household Income Value Label Frequency 1. Below 500 Euros to 800 Euros to 1400 Euros to 2000 Euros to 3000 Euros Euros or more don t want to say don t know 170 Sysmiss Range of Valid Data Values: 1 to 9999

25 Variable: Household Income Value Label Frequency 1. Below 9000 Euros to Euros to Euros to Euros to Euros to Euros to Euros to Euros to Euros Euros and More don t want to say don t know 88 Sysmiss Range of Valid Data Values: 1 to 12

26 Variable: Presence of a disability affecting travel Value Label Frequency 1. no yes don t want to say don t know 4 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

27 Variable: Type of disability Variable Format: character

28 Variable: Highest education level CH Value Label Frequency 1. No education Obligatory school Professional honor Vocational school University entrance level Higher education Technical college University don t know don t want to say don t know 0 Sysmiss Range of Valid Data Values: 1 to 9999

29 Variable: Highest education level CZ Value Label Frequency 1. No education 3 2. Obligatory school University entrance level professional honor higher education University Sysmiss Range of Valid Data Values: 1 to 9

30 Variable: Highest education level PT Value Label Frequency 1. No formal education/cannot read or write 2. Some of elementary school Completed elementary school Some of High/Secondary School Completed High/Secondary School [Qualification for College/U Some of college university Completed university or equivalent/ University Degree/Diplom Post Graduate Degree Professional honor don t want to say don t know 4 Sysmiss Range of Valid Data Values: 1 to 9999

31 Variable: Employment status Value Label Frequency 1. full time part time no don't know don't want to say 21 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

32 Variable: Number of paid working hours/week Range of Valid Data Values: 0 to 100 Minimum : 0 Maximum : 100 Mean : Standard deviation :

33 Variable: Job title Value Label Frequency 1. independent, one man independent independent, family apprentice own corporation employee, director position employee, avearage position employee other don't know no answer 4 Sysmiss. 839 Range of Valid Data Values: 1 to 9999

34 Variable: Ownership of frequent flyer card of an airline Value Label Frequency 1. No Yes don't want to say don't know 1 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

35 Variable: Ownership of a railway discount card Value Label Frequency 1. No Yes don't want to say don't know 3 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

36 Variable: Ownership of a drivers license Value Label Frequency 1. No Yes don't want to say don't know 0 Sysmiss. 1 Range of Valid Data Values: 1 to 9999

37 Variable: Car availability Value Label Frequency 1. always sometimes never don't know no answer 1 Sysmiss. 215 Range of Valid Data Values: 1 to 9999

38 Variable: Languages able to speak Value Label Frequency 01. German

40 French

41 Italian English

43 Spanish Portuguese Turkish Alabanian Serbo-Croatian Czech Russian Variable Format: character

44 Variable: Age Range of Valid Data Values: 15 to 90 Range of Invalid Data Values: Minimum : 15 Maximum : 91 Mean : Standard deviation : 15.83

45 Variable: Gender Value Label Frequency 1. male female 1840 Sysmiss. 1 Range of Valid Data Values: 1 to 2

46 Variable: Number of household members Value Label Frequency don't know don't want to say 13 Sysmiss. 1 Range of Valid Data Values: 0 to 9999 Minimum : 0 Maximum : 9999

47 Variable: Number of journeys the last 8 weeks Range of Valid Data Values: 0 to 60 Minimum : 0 Maximum : 60 Mean : Standard deviation : 4.829

48 Variable: Number of non regular journeys the last 8 weeks of regular travelers Range of Valid Data Values: 0 to 40 Minimum : 0 Maximum : 40 Mean : Standard deviation : 1.654

49 Variable: Regular journeys the last 8 weeks Value Label Frequency 1. no yes 872 Range of Valid Data Values: 1 to 2

50 Variable: Number of regular journeys the last 8 weeks Range of Valid Data Values: 0 to 90 Minimum : 0 Maximum : 90 Mean : Standard deviation : 4.938

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Tell us what you think. Provide feedback to help make American Community Survey data more useful for you. DP02 SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES 2016 American Community Survey 1-Year Estimates Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing