12 weeks of leisure travel survey - IVT

Transcription

12 weeks of leisure travel survey
R Schilch
Travel Survey Metadata Series
10
12 weeks of leisure travel survey____________________________________________________________May 2004
Travel Survey Metadata Series
R Schlich
IVT
ETH Zürich
Zürich
Phone: 01-633 33 40
Fax: 01-633 10 57
Abstract
This survey was conducted with the research project „73/00 Determinanten des Freizeitverkehr“ of
the Swiss Association of Transport Engineers (SVI) and the research project “Kontrasträume und
Raumpartnerschaften (BMBF)”. It produces descriptive analyses as well as models of the variability
of leisure travel (with hazard models), the impact of living conditions on leisure activities (with
linear regression and Poisson regression), determinants of destination and mode choice in leisure
travel (with multinominal and nested logit models). Additional travel group surveys looked at the
motives behind leisure activities. All analyses focused on differences between week- and weekend
leisure days. The discussions are based on our own surveys as well as on analyses of national
datasets. The following surveys were conducted within this research project are: A survey which
covered a period of 12 weeks of the leisure behaviour of 71 persons. They reported nearly 6000
leisure activities. This survey was the main source for the analysis of intrapersonal variability in
leisure; Four focus groups, which enabled an analysis of personal attitudes and motives. Besides, the
following datasets were used for modelling mode- and destination choice The National surveys of
the Federal Office of Spatial Development (ARE) (“Mikrozensus 1994 und 2000”), die
“Kontinuierlichen Erhebung Personenverkehr” of the Swiss Federal Railway (KEP 1999 und 2000)
and the “Zusatzmodul Reiseverhalten der Einkommens- und Verbrauchserhebung 1994” (EVE) of
the Federal Office of Statistic (BfS). A database covering all Swiss municipalities with information
about their leisure infrastructure was collected from various sources during the research project. The
results of the research can be summarised very briefly as follows: Attributes of leisure activities. The
research confirms that different leisure activities are very distinct from each other in their travel
characteristics. As most leisure activities are performed in groups, the spatial distribution of social
networks and their development over time becomes crucial for the growth of leisure traffic. Because
social networks are spatially distributed widely it is difficult to influence leisure traffic. Rhythms and
Variability: It is too simplifying to assume, that daily leisure activities are mostly performed
regularly or routinely - although aspects of leisure travel like the mode choice might be to a high
degree routine. The analysis show that the majority of activities - and especially those that are
performed most often, like visist of friends - do not take place within a rhythm. Impact of residential
situation: The residential situation has statistically significant impact on the frequency of leisure
activities out of home. Nonetheless this influence is weak compared to other influences like
sociodemographic differences. Motives: Motives behind leisure are different for activities performed
in everyday life compared to motives of holiday trips. For both categories of leisure activities social
contacts and the search for variability are dominant motives. Destination choice: Main result of the
destination choice modelling for short excursions (with less than two nights at the destination) is the
fact, that the choice of a destination depends on the accessibility of them. Traveller evaluate a
destination dependant on the distance and the travel time to the alternatives of a choice set. The
influence of leisure infrastructure for the destination choice of shorter excursions is weak, but still
i
detectable. Further research: All results show that the reasons of the growth of leisure activities are
still not completely known. Because of the low goodness of fit of the models and the fact that new
variables were found to have a significant influence (e.g. social networks) it is clear that the
modelling approaches used so far in Switzerland need improvement. Additionally, the joint
consideration of different leisure activities is not sufficient. Hence, further research is necessary.
Social contact is a major motive of leisure traffic. Because of the spatially disperse distribution of
acquaintances and friends - which is a problem to public transport - and indications, that the spatial
spread of those networks has increased over the last years, those contacts are a main contributor to
the growth of leisure traffic. It would be useful to get to know more about this spatial distribution
and the development of these networks so that first trends can be derived. A second focus of further
research should be the common separation of leisure into daily leisure, weekend leisure and
holidays. Due to the growing number of short trips and new living forms (e.g. weekly commuter
with second flats) they cannot be separated unambiguously. Besides, one can assume, that the
performance of one type of leisure depends on the others- for instance that changes in daily leisure
could possibly cause changes in holidays. The link between the times and activities need to be
explored in more detail.
Keywords
12 week leisure data, survey design, travel behaviour diary, list of variables, 6 weeks, ETH Zürich,
Institut für Verkehrsplanung und Transportsysteme.
Preferred citation style
Schilch, R., (2004) 12 weeks of leisure travel survey , Travel Survey Metadata Series, 10, Institute
for Transport Planning and Systems (IVT); ETH Zürich, Zürich.
ii
12 weeks of leisure travel survey________________________________________________________May 2004
1.0 Document Description
Citation
Title:
Identification
Number:
SVI7300
Authoring Entity:
Institut für Verkehrsplanung und Transportsysteme, ETH Zürich
Other
identifications and Robert SChlich
acknowledgements:
Producer:
Copyright:
Date of Production:
2003-10-03
Software used in
Production:
Nesstar Hierarchy Builder
1
2.0 Study Description
Citation
Title:
Identification
Number:
SVI7300
Authoring Entity:
Producer:
Date of Production:
2003-10-03
Software used in
Production:
Nesstar Hierarchy Builder
Funding
Agency/Sponsor:
Vereinigung Schweizerischer Verkehrsingenieure, SVI
Funding
Agency/Sponsor:
German Ministry of research
Distributor:
Robert Schlich
Version:
10/2003
2
Study Scope
Keywords:
12 week leisure data, survey design, travel behaviour diary, list of
variables, 6 weeks, ETH Zürich, Institut für Verkehrsplanung und
Transportsysteme.
Topic
Classification:
Travel behaviour. Activity analysis and Dairy survey.
Abstract:
This survey was conducted with the research project „73/00
Determinanten des Freizeitverkehr“ of the Swiss Association of
Transport Engineers (SVI) and the research project “Kontrasträume
und Raumpartnerschaften (BMBF)”. It produces descriptive
analyses as well as models of the variability of leisure travel (with
hazard models), the impact of living conditions on leisure activities
(with linear regression and Poisson regression), determinants of
destination and mode choice in leisure travel (with multinominal
and nested logit models). Additional travel group surveys looked at
the motives behind leisure activities. All analyses focused on
differences between week- and weekend leisure days. The
discussions are based on our own surveys as well as on analyses of
national datasets. The following surveys were conducted within this
research project are: A survey which covered a period of 12 weeks
of the leisure behaviour of 71 persons. They reported nearly 6000
leisure activities. This survey was the main source for the analysis
of intrapersonal variability in leisure; Four focus groups, which
enabled an analysis of personal attitudes and motives. Besides, the
following datasets were used for modelling mode- and destination
choice The National surveys of the Federal Office of Spatial
Development (ARE) (“Mikrozensus 1994 und 2000”), die
“Kontinuierlichen Erhebung Personenverkehr” of the Swiss Federal
Railway (KEP 1999 und 2000) and the “Zusatzmodul
Reiseverhalten der Einkommens- und Verbrauchserhebung
1994” (EVE) of the Federal Office of Statistic (BfS). A database
covering all Swiss municipalities with information about their
leisure infrastructure was collected from various sources during the
research project. The results of the research can be summarised very
briefly as follows: Attributes of leisure activities. The research
confirms that different leisure activities are very distinct from each
other in their travel characteristics. As most leisure activities are
performed in groups, the spatial distribution of social networks and
their development over time becomes crucial for the growth of
leisure traffic. Because social networks are spatially distributed
widely it is difficult to influence leisure traffic. Rhythms and
Variability: It is too simplifying to assume, that daily leisure
activities are mostly performed regularly or routinely - although
aspects of leisure travel like the mode choice might be to a high
degree routine. The analysis show that the majority of activities and especially those that are performed most often, like visist of
3
friends - do not take place within a rhythm. Impact of residential
situation: The residential situation has statistically significant
impact on the frequency of leisure activities out of home.
Nonetheless this influence is weak compared to other influences
like sociodemographic differences. Motives: Motives behind leisure
are different for activities performed in everyday life compared to
motives of holiday trips. For both categories of leisure activities
social contacts and the search for variability are dominant motives.
Destination choice: Main result of the destination choice modelling
for short excursions (with less than two nights at the destination) is
the fact, that the choice of a destination depends on the accessibility
of them. Traveller evaluate a destination dependant on the distance
and the travel time to the alternatives of a choice set. The influence
of leisure infrastructure for the destination choice of shorter
excursions is weak, but still detectable. Further research: All results
show that the reasons of the growth of leisure activities are still not
completely known. Because of the low goodness of fit of the
models and the fact that new variables were found to have a
significant influence (e.g. social networks) it is clear that the
modelling approaches used so far in Switzerland need
improvement. Additionally, the joint consideration of different
leisure activities is not sufficient. Hence, further research is
necessary. Social contact is a major motive of leisure traffic.
Because of the spatially disperse distribution of acquaintances and
friends - which is a problem to public transport - and indications,
that the spatial spread of those networks has increased over the last
years, those contacts are a main contributor to the growth of leisure
traffic. It would be useful to get to know more about this spatial
distribution and the development of these networks so that first
trends can be derived. A second focus of further research should be
the common separation of leisure into daily leisure, weekend leisure
and holidays. Due to the growing number of short trips and new
living forms (e.g. weekly commuter with second flats) they cannot
be separated unambiguously. Besides, one can assume, that the
performance of one type of leisure depends on the others- for
instance that changes in daily leisure could possibly cause changes
in holidays. The link between the times and activities need to be
explored in more detail.
Country:
Switzerland
Geographic
Coverage:
Zurich, Opfikon, Männedorf
Unit of Analysis:
Persons
4
Methodology and Processing
Time Method:
Reporting Period from January, 15th to May, 30th 2002; splitted in
3 waves, first started at January, the 15th, second 3 weeks later,
third 6 weeks later. Due to the need to arrange a personal meeting at
the beginning, somem persoons were interviewed a bit later, so that
they finished after May, 30th. Persons of each waves reported their
bahaviour for 12 weeks.
Sampling
Procedure:
Random Sample from telephone book; Given ratios for place (about
one third each in Zurich, Männedorf and Opfikon) and household
size (one third each in 1, 2, 2+ households)
Mode of Data
Collection:
Personal interview of sociodempgraphic questions at the start; Later
a diary was send out weekly and checked, when it returned (12
times). Each respondent had a personal contact person from the
interview team, who contacted a person, if he forgots to send his
diary.
5
Sources Statement
Weighting:
no weighting
6
Other Study Description Materials
Related Materials
Citation
Title:
Zielwahl im FreizeitverkehrZielwahl im Freizeitverkehr
Holdings
Information:
http://www.ivt.baug.ethz.ch/vrp/ab181.pdf
Notes:
Schlich, R., A. Simma und K. W. Axhausen (2003) Zielwahl im
Freizeitverkehr, Arbeitsberichte Verkehr- und Raumplanung, 181,
Institut für Verkehrsplanung und Transportsysteme (IVT), ETH,
Zürich.
Citation
Title:
Durchführung einer 12-wöchigen Langzeitbefragung
Holdings
Information:
http://www.ivt.baug.ethz.ch/vrp/ab_123.pdf
Notes:
Schlich, R., B. Kluge, S. Lehmann und K. W. Axhausen (2002)
Durchführung einer 12-wöchigen Langzeitbefragung, Stadt Region
Land 73, Tagungsband zum 3. Aachener Kolloqium "Mobilität und
Stadt", Institut für Stadtbauwesen und Stadtverkehr, RWTH
Aachen, Aachen, 141-154.
Citation
Title:
Entwicklung eines Tagebuchs zur Erhebung von Freizeitverhalten
Holdings
Information:
http://www.ivt.baug.ethz.ch/vrp/ab_121.pdf
Notes:
Schlich, R., A. Simma, P. Rüssli und K. W. Axhausen (2002)
Entwicklung eines Tagebuchs zur Erhebung von Freizeitverhalten,
Arbeitsbericht Verkehr- und Raumplanung, 121, Institut für
Verkehrsplanung, Transporttechnik, Stassen- und Eisenbahnbau
(IVT), ETH, Zürich.
7
3.0 File Description
File: p_sum_new.NSDstat
z
File Structure: hierarchical
z
Record Group
z
Number of cases: 71
z
No. of variables per record: 89
z
Type of File: NSDstat 200203
8
3.0 File Description
File: acts2.NSDstat
z
File Structure: hierarchical
z
Record Group
z
Number of cases: 5561
z
No. of variables per record: 30
z
Type of File: NSDstat 200203
9
4.0 Variable Description
Variable
Groups
z
z
z
z
z
z
z
z
z
z
z
Working
education
residence
residence history
fixed committments
mobility tools
parking
social network
household information
mobility informations
other personal information
Working
Variables within Working
z
z
z
z
z
z
z
z
z
z
z
z
z
z
Number of workhours
Place of work
Zipcode place of work
Contact person 1
Domicile contact person 1
Working time rules
Pupil
Student
Apprentice
Employed Person
Homemaker
Pensioner
Unemployed
Military Service
education
Variables within education
z
z
z
z
z
z
z
Primary School
Secondary School
Comprehensive Secondary School
Vocational School
University of Applied Sciences
University
10
residence
Variables within residence
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
Number of workhours
Place of work
Contact person 1
Owner or lodger
Type of accommodation
Amount of rent
Ability to reach school within 10 minutes
Ability to reach kindergarden within 10 minutes
Ability to reach a doctor within 10 minutes
Ability to reach a bank within 10 minutes
Ability to reach post office within 10 minutes
Ability to reach super market within 10 minutes
Ability to reach bus / tram stop within 10 minutes
Ability to reach train station for underground or regional
trains within 10 minutes
Owner of a second accommodation
Accommodation faetures
Accommodation size
Place of residence
x coordinate of residence
y coordinate of residence
residence history
Variables within residence history
z
z
z
z
z
z
z
z
Age of the person
Number of workhours
Environment where person grew up
Place where person grew up
Zipcode of place where person grew up
Since when the person lifes in the municipality
Since when the person lifes in the flat or house
Number of moves in the last 10 years
fixed committments
Variables within fixed committments
z
z
z
z
z
Zipcode contact person 1
Association, club
Honorary activities
Nursing
11
z
Selfimprovement
mobility tools
Variables within mobility tools
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
internal identity number
Age of the person
Place of work
Number of personal vehicles
Number of bikes
Owner of a semiprice discount card
Owner of a network card
Owner of a personal vehicle
Regional Ticket (origin-destiniation)
Regional Ticket (area)
Seasonal Ticket
Passenger car
Truck, bus
Motorbike
Motocycle
parking
Variables within parking
z
z
z
z
z
z
Age of the person
Contact person 1
Number of parking-lots
Distance to parking lot [time]
Distance to parking lot [meters]
Availability of free parking space at work
social network
Variables within social network
z
z
z
z
z
z
z
z
z
z
z
internal identity number
Age of the person
Contact person 1
Contact person 2
Contact person 3
12
z
z
z
z
z
z
Contact person 4
Contact person 5
household information
Variables within household information
z
z
z
z
z
z
z
Number of workhours
Place of work
Contact person 1
Income net
Number of children
Number of household members
Owner of a dog
mobility informations
Variables within mobility informations
z
z
z
z
Age of the person
Number of trips by bicycle last week
Number of trips by public transports last week
Number of kilometers per year by car
other personal information
Variables within other personal information
z
z
z
z
z
Age of the person
Contact person 1
Gender
Married or in a concubinage
13
Variables
14
Variable: internal identity number
Location:
Variable Text: Index Variable
Width: 11
Range of Valid Data Values: 1301 to 3603
Summary Statistics:
Variable Format: numeric
15
Variable: Age of the person
Location:
Value
Width: 11
16 .
1
20 .
2
23 .
2
25 .
2
26 .
2
27 .
3
28 .
2
29 .
1
30 .
1
31 .
1
32 .
2
33 .
1
34 .
3
35 .
2
36 .
3
37 .
4
38 .
2
39 .
2
40 .
1
41 .
1
42 .
3
45 .
1
48 .
1
49 .
1
51 .
1
52 .
2
56 .
2
58 .
2
59 .
1
Label
16
Frequency
60 .
3
61 .
1
62 .
1
64 .
1
65 .
1
66 .
1
67 .
1
68 .
2
69 .
1
70 .
3
72 .
2
79 .
1
84 .
1
Summary Statistics:
Minimum : 16
Maximum : 84
Mean : 44.901
Standard deviation : 16.934
17
Variable: Number of workhours
Location:
Value
Label
Frequency
Width: 11
0.
not working
18
3.
1
4.
1
8.
1
9.
1
10 .
1
12 .
3
15 .
1
16 .
3
20 .
2
21 .
1
25 .
1
30 .
3
32 .
4
33 .
1
35 .
1
36 .
1
38 .
1
39 .
2
40 .
11
41 .
1
42 .
8
45 .
1
50 .
2
55 .
1
Summary Statistics:
Minimum : 0
18
Maximum : 55
Mean : 23.577
19
Variable: Place of work
Location:
Value
Width: 50
Aarau .
1
Affoltern .
1
Altstetten .
1
Bubikon .
1
Dietikon .
1
Feldmeilen .
1
Flughafen Kloten .
2
Horgen .
1
Kandersteg Be .
1
Kloten .
2
Kloten Flughafen .
1
Museen in Zürich .
1
Männedorf .
2
Oetwil am See .
1
Opfikon .
3
Rümlang .
1
Stadt Zürich .
2
Stäfa .
1
Universitätsspital Zürich .
1
Wallisellen .
3
Zh Flughafen .
1
Zollikerberg .
1
Zürich .
13
Zürich Höngg .
1
Zürich Seefeld .
1
Zürich und Rapperswil .
1
Zürich, Seebac .
1
am Wohnort .
1
daheim .
1
Label
20
Frequency
zu Hause .
1
zu Hause /Männedorf .
1
zu Hause und auswärts .
1
zürich oerlikon .
1
Summary Statistics:
Variable Format: character
21
Variable: Zipcode place of work
Location:
Width: 11
Variable Text: Zipcode of working place, if available
Value
Label
Frequency
0.
18
3718 .
1
5000 .
1
8000 .
19
8005 .
1
8006 .
1
8046 .
1
8048 .
1
8049 .
1
8052 .
1
8125 .
1
8152 .
5
8153 .
1
8302 .
6
8304 .
3
8608 .
1
8618 .
1
8640 .
1
8706 .
1
8708 .
3
8712 .
1
8810 .
1
8953 .
1
Summary Statistics:
22
Variable: Contact person 1
Location:
Variable Text: Relationship to a person, which was named as an
important contanct person
Width: 50
Value
Label
Frequency
Bruder .
2
Cousin .
1
Eltern .
13
Familie .
12
Familie des Mannes .
1
Feund .
1
Freund .
4
Freunde .
7
Freundin .
4
Kolleg .
1
Mutter .
3
Nichte .
1
Partner .
3
Partnerin .
2
Schwiegereltern .
1
Schwiegermutter .
2
Sohn .
3
Tochter .
3
Tochter I .
1
Vater .
3
Verwandte .
2
schwester .
1
Summary Statistics:
23
Variable: Domicile contact person 1
Location:
Value
Width: 50
Aarau .
1
Arosa /GR .
1
Basel .
1
Bassersdorf .
1
Bern .
1
Boppelsen .
1
Bruchsal (D) .
1
Bülach .
1
Chur .
1
Dürnten/ZH .
1
Erlenbach .
2
Flums .
1
Genf .
1
Glattbrugg .
3
Grafstal .
1
Hausen am Albis .
1
Höngg .
1
Kreis 11 .
1
Muhen .
1
Männedorf .
6
Münchenbuchse (BE) .
1
Oberhasli .
1
Opfikon .
3
Ottenbach .
1
Regensdorf .
1
Region Basel .
1
Rietheim .
1
Schaffhausen .
1
Schwammendingen .
1
Label
24
Frequency
Schwyz .
1
Seebach zh .
1
Sion .
1
St. Gallen .
1
Stauffen (Deutschl.) .
1
Stäfa .
1
Stäfa / ZH .
1
Sulgen .
1
Tann-Rüti .
1
Uster .
1
Wallisellen .
1
Wetzikon .
1
Winterthur .
2
Wollishofen (ZH) .
1
Wädenswil .
1
Zürich .
10
Zürich Seebach .
1
Zürich, Kreis 6 .
1
Zürich, Triemli .
1
opfikon .
1
rheineck .
1
zürich .
1
Summary Statistics:
25
Variable: Zipcode contact person 1
Location:
Value
Width: 11
0.
2
1200 .
1
1950 .
1
3000 .
1
3052 .
1
4001 .
1
4102 .
1
5000 .
1
5037 .
1
5323 .
1
6430 .
1
7000 .
1
7050 .
1
8000 .
11
8006 .
1
8011 .
1
8038 .
1
8051 .
1
8052 .
1
8093 .
1
8105 .
1
8113 .
1
8152 .
7
8156 .
1
8180 .
1
8200 .
1
8303 .
1
8304 .
1
8310 .
1
Label
26
Frequency
8400 .
2
8583 .
1
8610 .
1
8620 .
1
8632 .
1
8635 .
1
8703 .
2
8708 .
6
8712 .
2
8820 .
1
8890 .
1
8913 .
1
8915 .
1
9000 .
1
9424 .
1
9999 .
abroad
2
Summary Statistics:
27
Location:
Width: 50
Value
Label
Frequency
Arbeitskollege .
1
Bruder .
1
Cousin .
1
Eltern .
3
Ex-Mann .
1
Familie .
9
Freund .
6
Freunde .
12
Freundin .
8
Freundinnen (Arbeit) .
1
Kollege .
3
Mutter .
1
Nachbarn, 4 Haushalte .
1
Neffe .
1
Schwager .
1
Schwager & Schwägerin .
1
Schwester .
2
Schwiegereltern .
3
Sohn .
2
Sohn I .
1
Tochter .
1
Tochter II .
1
Vater .
2
Verwandte .
2
schwägerin .
1
Summary Statistics:
28
29
Location:
Value
Width: 50
Adliswil .
1
Allschwil .
1
Basel .
1
Bern .
2
Buochs, LU .
1
Dielsdorf / ZH .
1
Dietikon .
1
Egg (ZH) .
1
Eglisau .
1
Embrach .
1
Erlenbach .
1
Ermattingen (TG) .
1
Gossau .
1
Herisau .
1
Herrliberg .
1
Hombrechtikon .
1
Kilchberg .
1
Kloten .
2
Kreis 11 .
1
Kreis 5 .
1
Küsnacht .
1
Locarno .
1
Muri BE .
1
Männedorf .
3
Männedorf / ZH .
1
Opfikon .
3
Rapperswil .
1
Samstagern .
2
Schlieren .
1
Label
30
Frequency
Schwyz .
1
St.Gallen .
1
Trier (Deutschl.) .
1
Uznach /St.Gallen .
1
Wallisellen .
3
Wangen .
1
Weinfelden .
1
Weisslingen .
1
Winterthur .
3
Zollikerberg .
1
Zollikon .
2
Zürich .
9
Zürich Höngg .
1
Zürich, Kreis 6 .
1
Zürich, Oerlikon .
1
oberglatt .
1
st.margrethen .
1
Summary Statistics:
31
Location:
Value
Label
Frequency
Width: 11
0.
no second person
5
3000 .
2
3074 .
1
3380 .
1
4000 .
1
4123 .
1
6374 .
1
6430 .
1
6600 .
1
8000 .
7
8001 .
1
8005 .
3
8006 .
1
8049 .
1
8050 .
1
8125 .
1
8132 .
1
8134 .
1
8152 .
3
8154 .
1
8157 .
1
8193 .
1
8272 .
1
8302 .
2
8304 .
3
8400 .
3
8424 .
1
8484 .
1
8570 .
1
32
8625 .
1
8634 .
1
8640 .
1
8700 .
1
8702 .
2
8703 .
1
8704 .
1
8708 .
4
8730 .
1
8735 .
1
8802 .
1
8833 .
2
8952 .
1
8953 .
1
9100 .
1
9430 .
1
9999 .
abroad
1
Summary Statistics:
Minimum : 0
Maximum : 9999
Mean : 7331.38
33
Location:
Width: 50
Value
Label
Frequency
Bandkollegen .
1
Bruder .
1
Bruder I .
1
Bruder undPatenkind .
1
Famiie .
1
Familie .
3
Freund .
7
Freunde .
18
Freundin .
3
Grossmutter .
1
Kolleg .
2
Kollege .
3
Mutter .
4
Nachbarn .
2
Patin .
1
Schwager und Schwägerin .
1
Schwester .
1
Sohn II .
1
Tochter .
1
Vater .
1
ehemaliger Arbeitskollege .
1
freundin .
1
kolleg .
1
Summary Statistics:
34
Location:
Value
Width: 50
Adliswil .
1
Bachenbülach .
1
Basel .
3
Beinwil a. See .
1
Brütten .
1
Dübendorf .
3
Eg (ZH) .
1
Egg / ZH .
1
Erlenbach .
1
Eschlikon/TG .
1
Gossau (ZH) .
1
Grüningen .
1
Hombrechtikon .
2
Isikon zh .
1
Kilchberg .
2
Kreis 3 .
1
Kreis 4 .
1
Kreis 5 .
1
Küsnacht .
1
Meilen .
1
Männedorf .
5
Männedorf /ZH .
1
Neuseeland .
1
Oberengstringen .
1
Opfikon .
4
Ottikon zh .
1
Rheintal .
1
Schaffhausen .
1
Spreitenbach .
1
Label
35
Frequency
Stadt Zürich .
2
Trier (Deutschl.) .
1
Uetikon .
1
Winkel zh .
1
Wittikon (ZH) .
1
ZH Seebach .
1
Zürich .
5
Zürich, Kreis 3 .
1
steinach .
1
zürich .
1
Summary Statistics:
36
Location:
Value
Label
Frequency
Width: 11
0.
no third person
14
4000 .
2
4001 .
1
5712 .
1
7310 .
1
8000 .
4
8001 .
2
8003 .
3
8004 .
1
8005 .
2
8046 .
1
8052 .
1
8102 .
1
8132 .
2
8134 .
1
8152 .
4
8184 .
1
8185 .
1
8200 .
1
8311 .
1
8335 .
1
8360 .
1
8600 .
3
8625 .
1
8626 .
1
8627 .
1
8634 .
2
8700 .
1
8703 .
1
37
8706 .
1
8707 .
1
8708 .
6
8802 .
2
8957 .
1
9323 .
1
9999 .
abroad
2
Summary Statistics:
38
Location:
Width: 50
Value
Label
Frequency
Arbeitskollege .
1
Bruder .
1
Bruder II .
1
Eltern .
1
Familie .
4
Freund .
5
Freunde .
15
Freunde (TV) .
1
Freunde II .
1
Freundin .
6
Gotte .
1
Gottenkind .
1
Kolleg .
1
Kollege .
1
Schwester .
2
Sohn .
1
Tante .
1
Vater .
1
Verwandte .
1
freundin /nachbarin .
1
Summary Statistics:
39
Location:
Value
Width: 50
Aarau .
1
Beinwil a. See .
1
Bern .
1
Biel .
1
Birchwil zh .
1
Dürnten .
1
Flurlingen .
1
Greifensee .
2
Kilchberg /ZH .
1
Kloten .
1
Kreis 5 .
1
Kreis 6 .
1
Küsnacht .
1
Meilen .
1
Männedorf .
5
Neuchatel .
1
Opfikon .
3
Ottenbach .
1
Rapperswil /SG .
1
Rotkreuz (ZUG) .
1
Spreitenbach .
1
Stadt Zürich .
1
Stäfa .
1
Stäfa /ZH .
1
Tirol .
1
Urdorf zh .
1
Uster .
1
Wald .
1
Wiedlisbach .
1
Label
40
Frequency
Zollikon .
1
Zürich .
8
opfikon .
1
winterthur .
1
Summary Statistics:
41
Location:
Value
Label
Frequency
Width: 11
0.
no fourth person
24
2000 .
1
2502 .
1
3000 .
1
4537 .
1
5000 .
1
5712 .
1
6343 .
1
8000 .
4
8001 .
2
8003 .
1
8004 .
1
8005 .
2
8006 .
1
8152 .
4
8247 .
1
8302 .
1
8309 .
1
8400 .
1
8606 .
2
8610 .
1
8635 .
1
8636 .
1
8640 .
1
8700 .
1
8702 .
1
8706 .
1
8708 .
5
8712 .
2
42
8802 .
1
8902 .
1
8913 .
1
8957 .
1
9999 .
abroad
1
Summary Statistics:
43
Location:
Width: 50
Value
Label
Frequency
Altersbetreuung .
1
Arbeitskollege .
1
Bruder .
3
Cousine .
2
Eltern .
1
Familie .
3
Freund .
3
Freunde .
11
Freundin .
2
Kolleg .
2
Kollege .
1
Schwester .
1
Schwiegermutter .
1
Tante .
2
Verwandte .
4
kollegin .
1
verwandte .
1
Summary Statistics:
44
Location:
Value
Width: 50
Baden/Bülach .
1
Berlin .
1
Blumberg (Deutschl.) .
1
Brüttisellen .
1
Fribourg .
1
Glattbrugg .
2
Hombrechtikon .
1
Kloten .
2
Konstanz .
1
Kreis 3 .
1
Lachen .
1
Lenzburg .
1
Lyss .
2
Meilen /ZH .
1
Männedorf .
1
Olten .
1
Reinach AG .
1
Schaffhausen .
1
Schwammendingen .
1
Schwammendingen (ZH) .
1
Spanien .
1
Stäfa .
1
Tann-Rüti .
1
Volketswil .
1
Wetzikon .
1
Winterthur .
1
Zwillikon .
1
Zürich .
6
Zürich, Albisrieden .
1
Label
45
Frequency
bülach .
1
kloten .
1
meilen .
1
Summary Statistics:
46
Location:
Value
Label
Frequency
Width: 11
0.
no fifth person
31
784 .
1
1700 .
1
3250 .
2
4600 .
1
5400 .
1
5600 .
1
5734 .
1
8000 .
5
8003 .
1
8004 .
2
8051 .
2
8152 .
2
8180 .
1
8200 .
1
8302 .
3
8306 .
1
8400 .
1
8604 .
1
8620 .
1
8632 .
1
8634 .
1
8706 .
2
8708 .
1
8712 .
1
8853 .
1
8909 .
1
9999 .
abroad
3
47
Summary Statistics:
48
Variable: Number of personal vehicles
Location:
Value
Width: 11
0.
19
1.
39
2.
10
3.
3
Label
Frequency
Summary Statistics:
Minimum : 0
Maximum : 3
Mean : 0.958
49
Variable: Number of parking-lots
Location:
Value
Width: 11
0.
10
1.
22
2.
12
3.
5
4.
1
5.
1
30 .
1
9999 .
Label
no pv
Frequency
19
Summary Statistics:
Minimum : 0
Maximum : 9999
Mean : 2677.197
50
Variable: Distance to parking lot [time]
Location:
Width: 11
Variable Text: in minutes
Value
Label
Frequency
0.
3
1.
29
2.
6
3.
4
9999 .
no pv or parking lot
Summary Statistics:
51
29
Variable: Distance to parking lot [meters]
Location:
Width: 11
Variable Text: in meters
Value
Label
Frequency
0.
3
2.
1
10 .
1
15 .
1
20 .
11
25 .
4
30 .
10
50 .
2
100 .
4
200 .
4
250 .
1
9999 .
no pv or parking lot
Summary Statistics:
52
29
Variable: Number of bikes
Location:
Value
Width: 11
0.
12
1.
12
2.
17
3.
11
4.
13
5.
5
8.
1
Label
Frequency
Summary Statistics:
Minimum : 0
Maximum : 8
Mean : 2.31
53
Variable: Number of trips by bicycle last week
Location:
Value
Width: 11
0.
51
1.
1
2.
6
4.
1
6.
2
7.
1
8.
1
10 .
1
12 .
2
15 .
1
16 .
1
20 .
2
28 .
1
Label
Frequency
Summary Statistics:
Minimum : 0
Maximum : 28
Mean : 2.493
54
Variable: Number of trips by public transports last week
Location:
Value
Width: 11
0.
16
1.
3
2.
10
4.
10
5.
4
6.
5
8.
4
10 .
4
12 .
5
14 .
1
15 .
4
17 .
1
20 .
2
30 .
2
Label
Frequency
Summary Statistics:
Minimum : 0
Maximum : 30
Mean : 6.141
55
Variable: Number of kilometers per year by car
Location:
Value
Width: 11
0.
11
7.
1
100 .
3
200 .
1
208 .
1
300 .
1
500 .
1
600 .
1
700 .
2
800 .
1
1000 .
3
1200 .
1
1500 .
1
2000 .
4
2500 .
1
2600 .
1
3000 .
3
5000 .
3
6000 .
2
7000 .
1
7500 .
1
8000 .
4
8500 .
1
9000 .
1
10000 .
7
11000 .
1
12000 .
3
13000 .
1
15000 .
4
Label
56
Frequency
20000 .
2
25000 .
2
35000 .
1
Summary Statistics:
Minimum : 0
Maximum : 35000
Mean : 6170.634
57
Variable: Environment where person grew up
Location:
Value
Label
Frequency
Width: 11
1.
Bigger Town
27
2.
Smaller Town
17
3.
Rural area
25
Sysmiss .
2
Summary Statistics:
58
Variable: Place where person grew up
Location:
Value
Width: 50
Aarau .
1
Abidjan (Afrika,Elfenbeinküste) .
1
Arosa /GR .
1
Basel .
1
Bassersdorf (ZH) .
1
Beinwil a. See /AG .
1
Binningen/Baselland .
1
Bruchsal (D) .
1
Deutschland .
1
Dietikon .
1
Dürnten/ZH .
1
Ebnat Kappel (TG) .
1
Effretikon .
1
England .
1
Erlenbach (ZH) .
1
Flurlingen/ZH .
1
Frankfurt D .
1
Genf .
1
Glattbrugg Zh .
1
Hombrechtikon (ZH) .
1
Kilchberg .
1
Lima , Perü .
1
Meilen (ZH) .
1
Meilen/Lottstetten/Rümlang .
1
Meisterschwanden / Aargau .
1
Neukirch-Egnach .
1
Niederlenz (AG) .
1
Northcarolina, USA .
1
Oberhasli ZH .
1
Label Frequency
59
Opfikon .
1
Rio Brasilien .
1
Rümlang (ZH) .
1
SH/ZH .
1
Schaffhausen .
1
Schmitten,FR .
1
St. Gallen .
1
St.Gallen,Volketswil .
1
Stäfa / ZH .
1
Tann-Rüti .
1
Trier (Deutschland) .
1
Uster .
1
Wallisellen .
2
Walzenhausen / AR .
1
Wangen bei Dübendorf .
1
Wetzikon .
1
Worms (BRD) .
1
Wädenswil .
1
Zolliker Berg .
1
Zollikon / Zürich .
1
Zürich .
17
Zürich, Weiningen .
1
schlieren .
1
Summary Statistics:
60
Variable: Zipcode of place where person grew up
Location:
Value
Width: 11
1200 .
1
3185 .
1
4000 .
1
4102 .
1
5000 .
1
5616 .
1
5702 .
1
5712 .
1
7050 .
1
8000 .
13
8004 .
1
8005 .
1
8006 .
1
8007 .
1
8104 .
1
8125 .
1
8152 .
2
8153 .
1
8156 .
1
8200 .
2
8247 .
1
8303 .
1
8304 .
2
8307 .
1
8602 .
1
8610 .
1
8620 .
1
8632 .
1
8634 .
1
Label
61
Frequency
8635 .
1
8702 .
1
8703 .
1
8706 .
2
8712 .
1
8802 .
1
8820 .
1
8952 .
1
8953 .
1
9000 .
2
9315 .
1
9428 .
1
9642 .
1
9999 .
abroad
9
76646 .
1
Sysmiss .
2
Summary Statistics:
62
Variable: Since when the person lifes in the municipality
Location:
Value
Width: 11
1918 .
1
1934 .
1
1951 .
1
1955 .
1
1957 .
1
1960 .
1
1961 .
1
1962 .
1
1964 .
1
1966 .
1
1967 .
1
1971 .
1
1974 .
1
1975 .
1
1976 .
3
1977 .
1
1979 .
1
1980 .
1
1982 .
3
1983 .
1
1985 .
3
1986 .
2
1987 .
4
1988 .
1
1989 .
2
1990 .
2
1992 .
4
1994 .
1
1995 .
2
Label
63
Frequency
1996 .
5
1997 .
2
1998 .
2
1999 .
2
2000 .
9
2001 .
4
2002 .
2
Summary Statistics:
64
Variable: Since when the person lifes in the flat or house
Location:
Value
Width: 11
1964 .
1
1967 .
1
1969 .
1
1971 .
1
1975 .
2
1976 .
2
1978 .
1
1980 .
2
1982 .
2
1983 .
1
1985 .
1
1986 .
2
1987 .
2
1988 .
1
1990 .
2
1992 .
4
1995 .
4
1996 .
4
1997 .
3
1998 .
4
1999 .
4
2000 .
15
2001 .
9
2002 .
2
Label
Frequency
Summary Statistics:
65
Variable: Number of moves in the last 10 years
Location:
Value
Width: 11
0.
26
1.
17
2.
9
3.
5
4.
4
5.
4
6.
3
7.
1
10 .
1
12 .
1
Label
Frequency
Summary Statistics:
Minimum : 0
Maximum : 12
Mean : 1.873
66
Variable: Owner or lodger
Location:
Value
Label
Frequency
Width: 11
0.
no information
1
1.
Flat
48
2.
House, Condominium
20
3.
Others
1
Sysmiss .
1
Summary Statistics:
67
Variable: Type of accommodation
Location:
Value Label
Frequency
Width: 11
0.
no information
2
1.
Apartement house with more than 6
units
33
2.
Apartement house with 6 or less
units
20
3.
Terrace house / semi-detached house 8
4.
Detached house
8
5.
Others
0
Summary Statistics:
68
Variable: Amount of rent
Location:
Width: 11
Variable Text: in Swiss Franken
Value
Label
Frequency
0.
6
500 .
1
780 .
1
800 .
1
850 .
1
900 .
1
1000 .
1
1050 .
1
1100 .
2
1130 .
1
1200 .
4
1250 .
1
1300 .
3
1350 .
2
1365 .
1
1380 .
1
1400 .
5
1428 .
1
1450 .
1
1500 .
2
1570 .
2
1600 .
3
1633 .
1
1650 .
1
1700 .
2
1800 .
2
1900 .
1
69
1950 .
2
1980 .
1
2000 .
5
2060 .
1
2100 .
1
2200 .
1
2300 .
1
2450 .
1
2500 .
4
3000 .
1
4500 .
1
Sysmiss .
3
Summary Statistics:
Minimum : 0
Maximum : 4500
Mean : 1501.412
70
Variable: Income net
Location:
Value
Width: 11
0.
Label
Frequency
7
1.
less than 2000 SFR
8
2.
2001 to 3000 SFR
9
3.
3001 to 4000 SFR
9
4.
4001 to 5000 SFR
8
5.
5001 to 7500 SFR
17
6.
7501 to 10000 SFR
5
7.
10001 SFR and more
6
Sysmiss .
2
Summary Statistics:
71
Variable: Date of Interview
Location:
Variable Text: Date when the first interview took place. Reporting
period started the following Monday
Width: 11
Summary Statistics:
72
Variable: Personal number of interviewer
Location:
Variable Text: Index variable of the person who did the interview neccesary to identify biases through the interviewer
Width: 12
Value
Label
Frequency
1.
15
2.
15
3.
12
4.
15
5.
14
Summary Statistics:
73
Variable: Number of children
Location:
Value
Width: 12
0.
54
1.
8
2.
8
3.
1
Label
Frequency
Summary Statistics:
Minimum : 0
Maximum : 3
Mean : 0.38
74
Variable: Number of household members
Location:
Value
Width: 12
1.
16
2.
27
3.
17
4.
10
5.
1
Label
Frequency
Summary Statistics:
Minimum : 1
Maximum : 5
Mean : 2.338
75
Variable: Working time rules
Location:
Value
Label
Frequency
Width: 12
1.
flexible work time
20
2.
fixed working hours
16
3.
shiftting times with fixed working
8
hours
4.
Others
0
9999 .
no work
18
Sysmiss .
9
Summary Statistics:
76
Variable: Owner of a semiprice discount card
Location:
Value
Label
Frequency
Width: 12
0.
No
28
1.
Yes
43
Summary Statistics:
77
Variable: Owner of a network card
Location:
Value
Label
Frequency
Width: 12
0.
No
61
1.
Yes
10
Summary Statistics:
78
Variable: Owner of a personal vehicle
Location:
Value
Width: 12
0.
Label
Frequency
38
1.
Yes
33
2.
No
0
Summary Statistics:
79
Variable: Ability to reach school within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
27
1.
yes
44
Summary Statistics:
80
Variable: Ability to reach kindergarden within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
23
1.
Yes
48
Summary Statistics:
81
Variable: Ability to reach a doctor within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
25
1.
Yes
46
Summary Statistics:
82
Variable: Ability to reach a bank within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
27
1.
yes
44
Summary Statistics:
83
Variable: Ability to reach post office within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
15
1.
Yes
56
Summary Statistics:
84
Variable: Ability to reach super market within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
18
1.
Yes
53
Summary Statistics:
85
Variable: Ability to reach bus / tram stop within 10 minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
4
1.
Yes
67
Summary Statistics:
86
Variable: Ability to reach train station for underground or regional trains within 10
minutes
Location:
Value
Label
Frequency
Width: 12
0.
No
28
1.
Yes
43
Summary Statistics:
87
Variable: Owner of a second accommodation
Location:
Value Label
Frequency
Width: 12
0.
no second accomodation
57
1.
Vacation apartement
9
2.
Weekend house
2
3.
Permanent place on a campground
0
4.
Allotment garden
3
Summary Statistics:
88
Variable: Accommodation faetures
Location:
Value
Width: 12
0.
Label
Frequency
9
1.
Garden
7
2.
Balcony
33
3.
Terrace
22
Summary Statistics:
89
Variable: Accommodation size
Location:
Value
Width: 12
25 .
1
50 .
2
55 .
2
60 .
3
70 .
8
72 .
1
74 .
1
75 .
2
80 .
8
85 .
3
90 .
4
95 .
2
100 .
9
114 .
1
120 .
6
130 .
1
150 .
1
160 .
2
170 .
1
180 .
4
184 .
1
200 .
2
270 .
1
300 .
1
Sysmiss .
4
Label
Frequency
Summary Statistics:
Minimum : 25
90
Maximum : 300
Mean : 105.881
91
Variable: Place of residence
Location:
Value
Label
Frequency
Width: 12
3.
Opfikon
20
4.
Männedorf
23
5.
Zürich
28
Summary Statistics:
92
Variable: Gender
Location:
Value
Label
Frequency
Width: 12
0.
female
37
1.
male
34
Summary Statistics:
93
Variable: Owner of a dog
Location:
Value
Label
Frequency
Width: 12
0.
No
63
1.
Yes
8
Summary Statistics:
94
Variable: Married or in a concubinage
Location:
Value
Label
Frequency
Width: 12
0.
No
14
1.
Yes
57
Summary Statistics:
95
Variable: Availability of free parking space at work
Location:
Value
Label
Frequency
Width: 12
0.
No
50
1.
Yes
21
Summary Statistics:
96
Variable: x coordinate of residence
Location:
Width: 12
Variable Text: x coordinate of residence
Value
Label
Frequency
681.777 .
16
683.534 .
12
685.286 .
23
695.009 .
20
Summary Statistics:
97
Variable: y coordinate of residence
Location:
Width: 12
Variable Text: y coordinate of residence
Value
Label
Frequency
235.724 .
20
248.551 .
12
249.056 .
16
254.09 .
23
Summary Statistics:
98
Variable: Pupil
Location:
Value
Label
Frequency
Width: 12
0.
No
68
1.
Yes
3
Summary Statistics:
99
Variable: Student
Location:
Value
Label
Frequency
Width: 12
0.
No
69
1.
Yes
2
Summary Statistics:
100
Variable: Apprentice
Location:
Value
Label
Frequency
Width: 12
0.
No
69
1.
Yes
2
Summary Statistics:
101
Variable: Employed Person
Location:
Value
Label
Frequency
Width: 12
0.
No
20
1.
Yes
51
Summary Statistics:
102
Variable: Homemaker
Location:
Value
Label
Frequency
Width: 12
0.
No
52
1.
Yes
19
Summary Statistics:
103
Variable: Pensioner
Location:
Value
Label
Frequency
Width: 12
0.
No
57
1.
Yes
14
Summary Statistics:
104
Variable: Unemployed
Location:
Value
Label
Frequency
Width: 12
0.
No
71
1.
Yes
0
Summary Statistics:
105
Variable: Military Service
Location:
Value
Label
Frequency
Width: 12
0.
No
71
1.
Yes
0
Summary Statistics:
106
Variable: Primary School
Location:
Value
Label
Frequency
Width: 12
0.
No
2
1.
Yes
69
Summary Statistics:
107
Variable: Secondary School
Location:
Value
Label
Frequency
Width: 12
0.
No
15
1.
Yes
56
Summary Statistics:
108
Variable: Comprehensive Secondary School
Location:
Value
Label
Frequency
Width: 12
0.
No
45
1.
Yes
26
Summary Statistics:
109
Variable: Vocational School
Location:
Value
Label
Frequency
Width: 12
0.
No
31
1.
Yes
40
Summary Statistics:
110
Variable: University of Applied Sciences
Location:
Value
Label
Frequency
Width: 12
0.
No
63
1.
Yes
8
Summary Statistics:
111
Variable: University
Location:
Value
Label
Frequency
Width: 12
0.
No
59
1.
Yes
12
Summary Statistics:
112
Variable: Association, club
Location:
Value
Label
Frequency
Width: 12
0.
No
41
1.
Yes
30
Summary Statistics:
113
Variable: Honorary activities
Location:
Value
Label
Frequency
Width: 12
0.
No
69
1.
Yes
2
Summary Statistics:
114
Variable: Nursing
Location:
Value
Label
Frequency
Width: 12
0.
No
69
1.
Yes
2
Summary Statistics:
115
Variable: Selfimprovement
Location:
Value
Label
Frequency
Width: 12
0.
No
58
1.
Yes
13
Summary Statistics:
116
Variable: Regional Ticket (origin-destiniation)
Location:
Value
Label
Frequency
Width: 12
0.
No
66
1.
Yes
5
Summary Statistics:
117
Variable: Regional Ticket (area)
Location:
Value
Label
Frequency
Width: 12
0.
No
65
1.
Yes
6
Summary Statistics:
118
Variable: Seasonal Ticket
Location:
Value
Label
Frequency
Width: 12
0.
No
62
1.
Yes
9
Summary Statistics:
119
Variable: Passenger car
Location:
Value
Label
Frequency
Width: 12
0.
No
12
1.
Yes
59
Summary Statistics:
120
Variable: Truck, bus
Location:
Value
Label
Frequency
Width: 12
0.
No
70
1.
Yes
1
Summary Statistics:
121
Variable: Motorbike
Location:
Value
Label
Frequency
Width: 12
0.
No
60
1.
Yes
11
Summary Statistics:
122
Variable: Motocycle
Location:
Value
Label
Frequency
Width: 12
0.
No
56
1.
Yes
15
Summary Statistics:
123
Variable: Internal identification number: Person
Location:
Width: 11
Summary Statistics:
124
Variable: Date of first reporting day
Location:
Value
Width: 11
04-FEB-2002 .
202
04-MAR-2002 .
556
08-APR-2002 .
186
11-FEB-2002 .
486
11-MAR-2002 .
334
18-FEB-2002 .
493
18-MAR-2002 .
365
21-JAN-2002 .
1277
25-FEB-2002 .
228
25-MAR-2002 .
289
28-JAN-2002 .
1145
Label
Summary Statistics:
125
Frequency
Variable: Activity start time (hh:mm:ss)
Location:
Value
Width: 8
0:00:00 .
28
0:10:00 .
1
0:15:00 .
1
0:30:00 .
6
0:40:00 .
1
0:45:00 .
3
10:00:00 .
220
10:05:00 .
7
10:10:00 .
5
10:15:00 .
22
10:20:00 .
5
10:25:00 .
4
10:30:00 .
69
10:35:00 .
2
10:40:00 .
4
10:45:00 .
11
10:50:00 .
1
11:00:00 .
163
11:05:00 .
1
11:10:00 .
10
11:15:00 .
16
11:20:00 .
10
11:25:00 .
3
11:30:00 .
39
11:40:00 .
1
11:45:00 .
15
11:50:00 .
3
12:00:00 .
166
12:05:00 .
2
Label
126
Frequency
12:10:00 .
2
12:15:00 .
18
12:20:00 .
2
12:25:00 .
2
12:30:00 .
54
12:40:00 .
8
12:45:00 .
6
12:50:00 .
3
12:55:00 .
1
13:00:00 .
199
13:05:00 .
4
13:10:00 .
3
13:15:00 .
34
13:20:00 .
10
13:25:00 .
1
13:30:00 .
111
13:35:00 .
1
13:40:00 .
4
13:45:00 .
14
13:50:00 .
11
14:00:00 .
310
14:05:00 .
8
14:10:00 .
10
14:15:00 .
40
14:20:00 .
10
14:25:00 .
2
14:30:00 .
103
14:33:00 .
1
14:34:00 .
2
14:40:00 .
6
14:45:00 .
13
127
14:50:00 .
8
15:00:00 .
209
15:05:00 .
4
15:10:00 .
15
15:15:00 .
23
15:20:00 .
5
15:30:00 .
91
15:35:00 .
1
15:40:00 .
2
15:45:00 .
11
15:50:00 .
3
16:00:00 .
202
16:05:00 .
5
16:10:00 .
11
16:15:00 .
28
16:20:00 .
11
16:25:00 .
1
16:30:00 .
61
16:33:00 .
1
16:35:00 .
2
16:40:00 .
5
16:45:00 .
13
16:50:00 .
9
16:55:00 .
1
17:00:00 .
181
17:01:00 .
1
17:05:00 .
2
17:10:00 .
11
17:11:00 .
1
17:15:00 .
30
17:20:00 .
10
128
17:30:00 .
73
17:35:00 .
1
17:40:00 .
4
17:45:00 .
13
17:50:00 .
4
17:55:00 .
1
18:00:00 .
267
18:10:00 .
13
18:15:00 .
39
18:20:00 .
2
18:25:00 .
1
18:30:00 .
116
18:35:00 .
1
18:40:00 .
2
18:45:00 .
18
18:50:00 .
6
18:55:00 .
1
19:00:00 .
276
19:05:00 .
2
19:10:00 .
11
19:15:00 .
22
19:20:00 .
2
19:30:00 .
138
19:35:00 .
1
19:40:00 .
5
19:45:00 .
25
19:50:00 .
6
1:00:00 .
11
1:15:00 .
1
20:00:00 .
250
20:10:00 .
11
129
20:15:00 .
31
20:20:00 .
1
20:30:00 .
61
20:45:00 .
12
21:00:00 .
137
21:10:00 .
4
21:15:00 .
13
21:30:00 .
52
21:40:00 .
5
21:45:00 .
3
22:00:00 .
121
22:05:00 .
2
22:10:00 .
1
22:15:00 .
10
22:20:00 .
3
22:30:00 .
47
22:40:00 .
4
22:45:00 .
3
23:00:00 .
46
23:15:00 .
1
23:20:00 .
1
23:30:00 .
17
23:45:00 .
4
23:50:00 .
3
2:00:00 .
6
2:15:00 .
1
2:30:00 .
1
3:00:00 .
1
5:00:00 .
1
5:30:00 .
1
6:00:00 .
3
130
6:15:00 .
2
6:30:00 .
6
6:40:00 .
1
6:45:00 .
1
6:50:00 .
1
6:55:00 .
1
7:00:00 .
84
7:02:00 .
1
7:05:00 .
2
7:10:00 .
15
7:13:00 .
1
7:15:00 .
34
7:20:00 .
21
7:25:00 .
1
7:30:00 .
39
7:35:00 .
1
7:40:00 .
2
7:45:00 .
5
7:50:00 .
16
7:55:00 .
3
8:00:00 .
89
8:05:00 .
1
8:10:00 .
9
8:13:00 .
1
8:15:00 .
10
8:20:00 .
11
8:25:00 .
1
8:30:00 .
51
8:35:00 .
1
8:40:00 .
5
8:45:00 .
13
131
8:50:00 .
7
9:00:00 .
234
9:05:00 .
8
9:10:00 .
18
9:15:00 .
68
9:20:00 .
9
9:25:00 .
1
9:26:00 .
1
9:30:00 .
72
9:35:00 .
2
9:40:00 .
5
9:45:00 .
8
9:50:00 .
8
9:55:00 .
1
Summary Statistics:
132
Variable: Activity end time (hh:mm:ss)
Location:
Value
Width: 8
0:00:00 .
165
0:10:00 .
3
0:15:00 .
9
0:20:00 .
2
0:30:00 .
73
0:40:00 .
6
0:45:00 .
7
0:55:00 .
1
10:00:00 .
41
10:05:00 .
1
10:10:00 .
5
10:15:00 .
10
10:20:00 .
5
10:25:00 .
1
10:30:00 .
90
10:35:00 .
2
10:40:00 .
6
10:45:00 .
19
10:50:00 .
5
10:55:00 .
2
11:00:00 .
154
11:05:00 .
1
11:10:00 .
8
11:15:00 .
19
11:20:00 .
8
11:25:00 .
1
11:30:00 .
99
11:35:00 .
2
11:40:00 .
11
Label
133
Frequency
11:45:00 .
17
11:50:00 .
6
11:55:00 .
8
12:00:00 .
104
12:05:00 .
2
12:10:00 .
2
12:15:00 .
14
12:20:00 .
1
12:25:00 .
12
12:30:00 .
44
12:40:00 .
3
12:45:00 .
5
12:50:00 .
2
12:55:00 .
1
13:00:00 .
119
13:10:00 .
2
13:15:00 .
16
13:20:00 .
5
13:25:00 .
1
13:30:00 .
56
13:35:00 .
1
13:40:00 .
2
13:45:00 .
8
13:50:00 .
4
14:00:00 .
106
14:05:00 .
2
14:10:00 .
2
14:15:00 .
18
14:20:00 .
3
14:25:00 .
2
14:30:00 .
48
134
14:40:00 .
1
14:45:00 .
19
14:50:00 .
8
14:55:00 .
2
15:00:00 .
110
15:05:00 .
2
15:15:00 .
11
15:20:00 .
7
15:25:00 .
2
15:30:00 .
87
15:35:00 .
1
15:40:00 .
7
15:45:00 .
17
15:50:00 .
16
15:55:00 .
2
16:00:00 .
206
16:05:00 .
3
16:10:00 .
4
16:12:00 .
1
16:15:00 .
25
16:20:00 .
6
16:30:00 .
129
16:35:00 .
1
16:40:00 .
15
16:45:00 .
45
16:50:00 .
33
16:55:00 .
4
17:00:00 .
344
17:05:00 .
2
17:10:00 .
11
17:15:00 .
39
135
17:20:00 .
7
17:30:00 .
169
17:35:00 .
2
17:40:00 .
10
17:45:00 .
40
17:50:00 .
26
17:55:00 .
6
18:00:00 .
256
18:10:00 .
9
18:15:00 .
32
18:20:00 .
3
18:25:00 .
1
18:30:00 .
92
18:35:00 .
2
18:40:00 .
9
18:45:00 .
17
18:50:00 .
16
18:55:00 .
5
19:00:00 .
146
19:10:00 .
2
19:15:00 .
22
19:20:00 .
7
19:25:00 .
4
19:30:00 .
83
19:31:00 .
1
19:35:00 .
2
19:40:00 .
5
19:45:00 .
17
19:50:00 .
9
19:55:00 .
1
1:00:00 .
62
136
1:15:00 .
2
1:30:00 .
26
1:45:00 .
2
20:00:00 .
193
20:05:00 .
1
20:10:00 .
4
20:15:00 .
23
20:20:00 .
6
20:27:00 .
1
20:30:00 .
61
20:35:00 .
1
20:40:00 .
1
20:45:00 .
8
20:50:00 .
2
21:00:00 .
155
21:01:00 .
1
21:10:00 .
4
21:15:00 .
26
21:20:00 .
11
21:30:00 .
116
21:40:00 .
7
21:45:00 .
19
21:50:00 .
10
22:00:00 .
203
22:05:00 .
3
22:10:00 .
12
22:15:00 .
32
22:20:00 .
6
22:30:00 .
178
22:35:00 .
1
22:40:00 .
10
137
22:45:00 .
10
22:50:00 .
8
22:55:00 .
1
23:00:00 .
155
23:05:00 .
1
23:10:00 .
5
23:15:00 .
11
23:20:00 .
2
23:30:00 .
120
23:35:00 .
1
23:40:00 .
6
23:45:00 .
12
23:50:00 .
7
23:59:00 .
1
24:00:00 .
8
2:00:00 .
47
2:15:00 .
1
2:20:00 .
1
2:30:00 .
20
2:45:00 .
1
2:50:00 .
1
3:00:00 .
28
3:15:00 .
3
3:30:00 .
12
3:45:00 .
1
4:00:00 .
15
4:15:00 .
2
4:30:00 .
10
4:40:00 .
1
5:00:00 .
18
5:30:00 .
2
138
6:00:00 .
5
6:30:00 .
1
7:00:00 .
7
7:10:00 .
1
7:15:00 .
3
7:20:00 .
2
7:25:00 .
2
7:30:00 .
68
7:35:00 .
8
7:40:00 .
11
7:45:00 .
23
7:50:00 .
5
8:00:00 .
14
8:10:00 .
2
8:15:00 .
3
8:20:00 .
7
8:25:00 .
2
8:30:00 .
15
8:35:00 .
2
8:40:00 .
5
8:45:00 .
7
8:50:00 .
6
8:55:00 .
1
9:00:00 .
36
9:10:00 .
6
9:15:00 .
16
9:20:00 .
5
9:30:00 .
28
9:35:00 .
2
9:39:00 .
1
9:40:00 .
13
139
9:45:00 .
11
9:50:00 .
9
9:55:00 .
1
Summary Statistics:
140
Variable: Number of reporting week
Location:
Value
Label
Frequency
Width: 11
1.
One
560
2.
Two
521
3.
Three
486
4.
Four
468
5.
Five
409
6.
Six
377
7.
Seven
426
8.
Eight
469
9.
Nine
415
10 .
Ten
502
11 .
Eleven
463
12 .
Twelve
465
Summary Statistics:
141
Variable: Weekday
Location:
Value
Label
Frequency
Width: 11
1.
Monday
691
2.
Tuesday
735
3.
Wednesday
793
4.
Thursday
789
5.
Friday
812
6.
Saturday
891
7.
Sunday
850
Summary Statistics:
142
Variable: Description of activity
Location:
Summary Statistics:
Width: 254
143
Variable: Internal identification number: Activity
Location:
Value
Width: 4
0.
19
1.
3435
2.
1434
3.
465
4.
145
5.
43
6.
14
7.
4
8.
2
Label
Frequency
Summary Statistics:
144
Variable: Place of activity
Location:
Summary Statistics:
Width: 50
145
Variable: Post code of activity place
Location:
Width: 11
Summary Statistics:
146
Variable: Number of visits at activity place before
Location:
Value
Label
Frequency
Width: 11
1.
Never
400
2.
One or two times
330
3.
Three to ten times
708
4.
More than 10 times
3962
5.
Not known
85
Sysmiss .
76
Summary Statistics:
147
Variable: Number of interviewer
Location:
Value
Label
Frequency
Width: 12
1.
One
1116
2.
Two
942
3.
Three
1095
4.
Four
1102
5.
Five
1306
Summary Statistics:
148
Variable: Mode of transport (to destination)
Location:
Value
Label
Frequency
Width: 12
1.
Walk
1907
2.
Bicycle
496
3.
Motorbike
2
4.
Car as driver
1355
5.
Car as passenger
493
6.
Bus / Light rail
826
8.
Train
386
9.
Others
43
Sysmiss .
53
Summary Statistics:
149
Variable: Mode of transport (in return)
Location:
Value
Label
Frequency
Width: 12
1.
Walk
1977
2.
Bicycle
498
3.
Motorbike
2
4.
Car as driver
1345
5.
Car as passenger
543
6.
Bus / Light rail
0
8.
Train
426
9.
Others
70
Sysmiss .
700
Summary Statistics:
150
Variable: Activity purpose (categories)
Location:
Value Label
Frequency
Width: 12
1.
Meeting relatives/family
190
2.
Meeting friends
623
3.
Pick up/Drop off
89
4.
child care
80
5.
club meeting
195
6.
honorary/ unpaid help
65
7.
cultural
330
8.
church
53
9.
restaurant, pub, etc
961
10 .
sport as spectator
45
11 .
active sport
734
12 .
Garden/Cottage
45
13 .
graveyard
21
14 .
going for a walk
1014
15 .
Excursion: nature
193
16 .
Excursion: city
78
17 .
Excursion: Ski
23
18 .
Short trip (whole day)
12
19 .
Car care and refueling
13
20 .
Shopping: Daily
170
21 .
Shopping: Non-Daily demand
90
22 .
window shopping
166
23 .
Private business: Administrative
28
24 .
'Private business: Health
70
25 .
further education
60
26 .
educatio/School
2
27 .
Work related business
14
28 .
work
22
29 .
others
41
151
30 .
Festivals, partys
72
31 .
making music
62
Summary Statistics:
152
Variable: X coordinate
Location:
Summary Statistics:
Width: 12
153
Variable: Y coordinate
Location:
Summary Statistics:
Width: 12
Minimum : 95.667
Maximum : 283.783
Mean : 244.855
154
Variable: Day of year
Location:
Value
Width: 11
01-APR-2002 .
67
01-FEB-2002 .
36
01-JUN-2002 .
18
01-MAR-2002 .
51
01-MAY-2002 .
28
02-APR-2002 .
60
02-FEB-2002 .
42
02-JUN-2002 .
18
02-MAR-2002 .
45
02-MAY-2002 .
26
03-APR-2002 .
73
03-FEB-2002 .
39
03-JUN-2002 .
9
03-MAR-2002 .
49
03-MAY-2002 .
39
04-APR-2002 .
81
04-FEB-2002 .
27
04-JUN-2002 .
8
04-MAR-2002 .
36
04-MAY-2002 .
38
05-APR-2002 .
74
05-FEB-2002 .
35
05-JUN-2002 .
4
05-MAR-2002 .
40
05-MAY-2002 .
37
06-APR-2002 .
73
06-FEB-2002 .
29
06-JUN-2002 .
8
06-MAR-2002 .
62
Label
155
Frequency
06-MAY-2002 .
21
07-APR-2002 .
71
07-FEB-2002 .
30
07-JUN-2002 .
6
07-MAR-2002 .
50
07-MAY-2002 .
36
08-APR-2002 .
70
08-FEB-2002 .
30
08-JUN-2002 .
11
08-MAR-2002 .
43
08-MAY-2002 .
33
09-APR-2002 .
60
09-FEB-2002 .
39
09-JUN-2002 .
11
09-MAR-2002 .
76
09-MAY-2002 .
29
10-APR-2002 .
68
10-FEB-2002 .
30
10-JUN-2002 .
3
10-MAR-2002 .
60
10-MAY-2002 .
32
11-APR-2002 .
62
11-FEB-2002 .
34
11-JUN-2002 .
6
11-MAR-2002 .
43
11-MAY-2002 .
35
12-APR-2002 .
67
12-FEB-2002 .
29
12-JUN-2002 .
6
12-MAR-2002 .
50
12-MAY-2002 .
41
156
13-APR-2002 .
64
13-FEB-2002 .
33
13-JUN-2002 .
4
13-MAR-2002 .
57
13-MAY-2002 .
14
14-APR-2002 .
57
14-FEB-2002 .
41
14-JUN-2002 .
4
14-MAR-2002 .
52
14-MAY-2002 .
22
15-APR-2002 .
41
15-FEB-2002 .
46
15-JUN-2002 .
5
15-MAR-2002 .
56
15-MAY-2002 .
31
16-APR-2002 .
47
16-FEB-2002 .
46
16-JUN-2002 .
7
16-MAR-2002 .
70
16-MAY-2002 .
31
17-APR-2002 .
53
17-FEB-2002 .
50
17-JUN-2002 .
2
17-MAR-2002 .
55
17-MAY-2002 .
24
18-APR-2002 .
46
18-FEB-2002 .
37
18-JUN-2002 .
2
18-MAR-2002 .
47
18-MAY-2002 .
23
19-APR-2002 .
45
157
19-FEB-2002 .
41
19-JUN-2002 .
3
19-MAR-2002 .
53
19-MAY-2002 .
25
20-APR-2002 .
50
20-FEB-2002 .
41
20-MAR-2002 .
61
20-MAY-2002 .
20
21-APR-2002 .
51
21-FEB-2002 .
38
21-JAN-2002 .
13
21-JUN-2002 .
1
21-MAR-2002 .
64
21-MAY-2002 .
14
22-APR-2002 .
30
22-FEB-2002 .
33
22-JAN-2002 .
16
22-MAR-2002 .
62
22-MAY-2002 .
19
23-APR-2002 .
34
23-FEB-2002 .
36
23-JAN-2002 .
20
23-MAR-2002 .
75
23-MAY-2002 .
19
24-APR-2002 .
21
24-FEB-2002 .
33
24-JAN-2002 .
23
24-MAR-2002 .
69
24-MAY-2002 .
22
25-APR-2002 .
37
25-FEB-2002 .
35
158
25-JAN-2002 .
23
25-JUN-2002 .
2
25-MAR-2002 .
69
25-MAY-2002 .
25
26-APR-2002 .
33
26-FEB-2002 .
30
26-JAN-2002 .
21
26-JUN-2002 .
2
26-MAR-2002 .
63
26-MAY-2002 .
23
27-APR-2002 .
38
27-FEB-2002 .
43
27-JAN-2002 .
21
27-MAR-2002 .
60
27-MAY-2002 .
13
28-APR-2002 .
39
28-FEB-2002 .
38
28-JAN-2002 .
30
28-JUN-2002 .
3
28-MAR-2002 .
59
28-MAY-2002 .
16
29-APR-2002 .
30
29-JAN-2002 .
35
29-JUN-2002 .
1
29-MAR-2002 .
67
29-MAY-2002 .
11
30-APR-2002 .
36
30-JAN-2002 .
35
30-JUN-2002 .
3
30-MAR-2002 .
60
30-MAY-2002 .
18
159
31-JAN-2002 .
33
31-MAR-2002 .
61
31-MAY-2002 .
15
Summary Statistics:
160
Variable: Day of reporting period
Location:
Value
Width: 12
1.
65
2.
77
3.
78
4.
78
5.
79
6.
100
7.
83
8.
71
9.
75
10 .
69
11 .
69
12 .
89
13 .
70
14 .
78
15 .
58
16 .
61
17 .
64
18 .
70
19 .
70
20 .
90
21 .
73
22 .
62
23 .
63
24 .
60
25 .
77
26 .
63
27 .
76
28 .
67
29 .
56
Label
161
Frequency
30 .
50
31 .
64
32 .
53
33 .
66
34 .
58
35 .
62
36 .
45
37 .
42
38 .
57
39 .
57
40 .
63
41 .
56
42 .
57
43 .
48
44 .
52
45 .
64
46 .
60
47 .
57
48 .
80
49 .
65
50 .
56
51 .
57
52 .
75
53 .
63
54 .
72
55 .
76
56 .
70
57 .
51
58 .
60
59 .
57
60 .
67
162
61 .
48
62 .
65
63 .
67
64 .
57
65 .
73
66 .
69
67 .
68
68 .
67
69 .
90
70 .
78
71 .
60
72 .
65
73 .
70
74 .
65
75 .
72
76 .
57
77 .
74
78 .
62
79 .
60
80 .
66
81 .
62
82 .
66
83 .
73
84 .
76
Summary Statistics:
163
Variable: Day of week
Location:
Value
Label
Frequency
Width: 12
1.
Monday
691
2.
Tuesday
735
3.
Wednesday
793
4.
Thursday
789
5.
Friday
812
6.
Saturday
891
7.
Sunday
850
Summary Statistics:
164
Variable: Number of month
Location:
Value
Label
Frequency
Width: 12
1.
January
270
2.
February
1021
3.
March
1765
4.
April
1578
5.
May
780
6.
June
147
7.
July
0
8.
August
0
Summary Statistics:
165
Variable: Week of year
Location:
Value
Width: 12
3.
13
4.
154
5.
247
6.
227
7.
282
8.
257
9.
292
10 .
374
11 .
387
12 .
453
13 .
437
14 .
502
15 .
419
16 .
322
17 .
232
18 .
225
19 .
220
20 .
176
21 .
135
22 .
105
23 .
51
24 .
34
25 .
6
26 .
11
Label
Frequency
Summary Statistics:
Minimum : 3
166
Maximum : 26
Mean : 12.723
167
Variable: In company of household members
Location:
Value
Label
Frequency
Width: 12
0.
No
3810
1.
Yes
1751
Summary Statistics:
Mean : 0.315
168
Variable: In company of other persons
Location:
Value
Label
Frequency
Width: 12
0.
No
3297
1.
Yes
2264
Summary Statistics:
Mean : 0.407
169
Variable: Unaccompanied
Location:
Value
Label
Frequency
Width: 12
0.
No
3661
1.
Yes
1900
Summary Statistics:
Mean : 0.342
170
Variable: In company of a dog
Location:
Value
Label
Frequency
Width: 12
0.
No
4924
1.
Yes
637
Summary Statistics:
Mean : 0.115
171
Variable: Expenditure on activity (Without travel costs)
Location:
Value
Label
Frequency
Width: 12
1.
Less than 5 CHF
2767
2.
5 - 25 CHF
815
3.
25 - 100 CHF
1309
4.
More than 100 CHF
460
5.
No answer
96
6.
Not known
93
Sysmiss .
21
Summary Statistics:
172
Variable: Public holiday
Location:
Value
Label
Frequency
Width: 12
0.
No
5201
1.
Yes
360
Summary Statistics:
173
Variable: Time of activity start (in hours)
Location:
Width: 5
Variable Text: This is a numeric variable essentially created for
secondary analysis. A string variable "act_s" is created to publish
the preliminary distribution.
Summary Statistics:
Minimum : 0
Maximum : 23.833
Mean : 14.772
174
Variable: Time of activity end (in hours)
Location:
Width: 5
Variable Text: This is a numeric variable essentially created for
secondary analysis. A string variable "act_e" is created to publish
the preliminary distribution.
Summary Statistics:
Minimum : 0
Maximum : 24
Mean : 15.402
175
5.0 Other Study-Related Materials
Label:
Questionnaire diary
Notes:
in German
176
5.0 Other Study-Related Materials
Label:
Questionnaire starting interview
Notes:
in German
177

12 weeks of leisure travel survey - IVT

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