Mobility Services Kagerbauer

KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association

INSTITUTE FOR TRANSPORT STUDIES KARLSRUHE SERVICE RESEARCH INSTITUTE

www.kit.edu

KSRI Summer School Dr.-Ing. Martin Kagerbauer Dr. Wibke Michalk Karlsruher Institute for Technology (KIT) Karlsruher Institute for Technology (KIT) Senior Researcher at the KIT Institute for Transport Studies Managing Director at the Head of Topic Infrastructure Traffic and Mobility Behavior Karlsruhe Service Research Institute at the KIT Mobility Systems Center

Institute for Transport Studies Karlsruhe Service Research Institute

Karlsruhe Institute of Technology (KIT)

2 26. September 2013

Dr. Wibke Michalk and Dr. Martin Kagerbauer

Agenda

10:30 – 11:15 Travel Demand (Surveys), Trends in Mobility Research 11:15 – 12:00 Business Models in the Mobility Sector 13:30 – 15:00 Hands On Session: The Future of Mobility 15:30 – 17:00 Present your Solutions!





Outline

Travel Behavior in a Glance

Travel Survey Methods International

Germany

Results Future Trends in Mobility Behavior





Quelle: Korea Automobile Manufacturers Association: Motor Vehicles Worldwide, 2012

International View

Changing Markets?

Industrialized countries vs. Emerging markets Saturation of travel demand Increasing travel demand and car ownership and car ownership

Reg

istr

atio

n of

new

car

s

Year

China Brasil India Russia Germany Mexico Japan US





International View

Times Series of travel demand in different countries

Source: T. Kuhnimhof : Are Young Men Responsible for Peak Car? Vortrag beim Peak Travel Round Table, IFSTTAR, Paris, 19.6.2012





Data

Countries with National Travel Behavior Surveys (NTS)

Source: COST Action SHANTI





Data

Countries with National Travel Behavior Surveys (NTS)






Data

Are the survey data comparable?


Δ 3%

persons 15+

persons 0+

persons 10+

persons 0+





Data



88% trip makers

90% trip makers

92% trip makers

78% trip makers





Data







Data

Are the survey data comparable? – Yes!






Two complementary surveys in Germany

MiD (= German NTS) MOP Design Repeated cross-sectional survey Longitudinal panel survey

Daily travel behavior: 7 consecutive days (autumn) in 3 consecutive years

Odometer reading: all refuel processes of all car in the MOP sample (spring) in 8 weeks in three consecutive years

Net sample Large (~ 25.000 HH) Small (~ 1.000 HH)

Frequency Irregular (every 6 to 8 years) Every year

Contractor Field work: infas (2002, 2008) Scientific supervisors:

DIW (2002), DLR (2008)

Field work: infratest (since 1994) infas (cohort 2003)

Scientific supervisor: KIT

Funding BMVBS (Federal Ministry of Transport, Building and Urban Development)





German Surveys in comparison: Net Sample Size

KONTIV 1976

KONTIV 1982

KONTIV 1989

MiD 2002 MiD 2008

MOP since 1994

0

1000

2000

3000

4000

5000

0

5000

10000

15000

20000

25000

1976

1982

1989

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Sample size MOP [HH]

Sample size KONTIV / MiD [HH]

Year





MiD / MOP in comparison: Coverage

MiD MOP Sampling frame Official population registry Market research bus

Sampling unit Individual person (aged ≧ 14) Household

Sampling stratification

16 federal states (Bundesländer) 17 regional / community types

Germany 5 regional types 4 household types car ownership

Weighting (post stratification)

5 HH sizes 7 regional types 7 weekdays / 12 months Age / sex

4 HH sizes 3 groups car ownership 3 groups population of home location Age / sex

Respondents Up to 8 HH members aged ≧ 0 Up to 5 HH members aged ≧ 10

Individual / HH reporting period

1 day (trip diary) up to 3 journeys with overnight stay

(3 months retrospectively)

1 week (trip diary) 8 weeks (odometer reading)

Overall reporting period

Every day of an entire year Several weeks in autumn (HH questionnaire, trip diary)

8 weeks in spring (odometer reading)





MiD / MOP in comparison: Instruments

MiD 2002 * MOP since 1994 HH level

PAPI (if no phone number is available) CATI

PAPI

Person level PAPI

Trip level PAPI

MiD 2008 * HH level ** PAPI (if no phone number is available)

(~ 7%) CATI (~ 85%) CAWI (~ 8%)

Person level CATI (100%)

Trip level CATI (100%)

* proxy interview for children: mandatory below age of 10, voluntary from age 10 to 13

** HH eligible only, if at least 50% of HH members completed both person and trip interview





MiD / MOP in comparison: Survey Process

MiD MOP Sampling method Random sampling with geographic

stratification Random sampling of the market

research bus with geographic and household specific stratification

Recruiting letter

Dissemination of survey material

1st phone call (HH interview) mailing of HH questionnaire

Phone call (ask for participation) Mailing of questionnaire and trip

diary

Mailing of memory jogger

Reminder for trip diary Reminder (if necessary)

2nd phone call (individual questionnaire / trip reporting)

Coding Plausibility check Basic analysis





MiD MOP HH size; type; vehicle ownership; income;

phone number size; type; area/ park condition of home location; vehicle ownership and use; accessability of public transport/ of usual destinations, income

Person socio-demographics; school/ occupation; long-distance trips; accessibility of public transport/ of usual destinations; general mode choice; individual availablity of car/ bike/ public transport ticket; handicaps; weather conditions

socio-demographics; school/ occupation; area of working place; parking conditions at work, individual availablity of car/ bike/ public transport ticket; handicaps

Trip purpose; type of O/ D; distance; duration; mode(s); regular business trips

weekday, start and end time of trip, purpose; mode(s); distance;

HH car manufacturer/ model; engine type/ power; type of registration; year of manufacture/ purchase; usual parking place; annual mileage; current odometer reading; main driver

Journey purpose; destination area; mode

Odometer reading

type of car (see MiD), milage, refuel process (date, odometer reading, amount, costs)

MiD / MOP in comparison: Content






























MiD / MOP in comparison: Available material

General data availability for third parties Academia, political decision makers, public authorities, planning engineers, transport providers, etc. Access is subject to prior registration

MiD MOP Data sets HH, person, trip, car, journeys

various file formats HH, person, person per day, trip Car (mileage/ fuel consumption) various file formats

Codebook User guide / manual Methodological report (part of the analytic report)

Tabular report (part of the analytic report)

Analytical report Analysis tool ---

Website





Options for analysis: MOP

517 297 161

447 203 173

1123 837 632

513 364 296

504 402 294

1189 761 623

563 417 309

975 766 617

699 524 491

856 599 481

748 575 401

671 448 352

706 573 433. . .720 589 442

761 575 480

613 491 404

797 611 …

785

total sample size (517) (744) 1487 1523 1500 1887 1618 2015 1774 1997 1838 1727 1555 1645 1783 1630 1768 1800

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 continu

Num

ber o

f per

sons

in d

iffer

ent c

ohor

ts o

f a y

ear

Selectivity study 2002

pilot study 1991 to 1993

crosssectional resultsdata of one year from all three cohorts

longitudinal results

data of personsin three

consecutive years from one cohort





MiD / MOP: Selected results

0

5

10

15

20

25

30

35

40

45

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Km

per

per

son

and

day

Year

MOP annual since1994

KONTIV 1976

KONTIV 1982

MID 2002

German Mobility Panel (MOP) Mobility in Germany (MiD) and KONTIV

MID 2008





MiD / MOP: Selected results

82 85

89 91 92

31

39 41 39 40 37

45 46 42 44

10,0 11,7 11,8 11,0 11,8

3

3,3 3,5 3,5 3,4

3,7 3,9 3,9 3,8 3,7

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

0

10

20

30

40

50

60

70

80

90

100

KONTIV 1982 MiD 2002 MiD 2008 MOP 2002 MOP 2008

Trips [n] Share [%] / Distance [km]

Share of mobilepersons [%]

Distance perperson per day[km]

Distance permobile personper day [km]

Average triplength [km]

Trips per personper day [n]

Trips per mobileperson per day[n]

Persons ≧ 10 years





Two survey approaches: (Dis-)Advantages

Current state Advantage / Opportunity Disadvantage / Risk

Long tradition of both surveys Consistent time series; continuous methodological development

Reluctancy to change anything (content, methods)

differing sampling frame Complementary coverage of different user groups

Sampling bias / selectivity; comparison of incomparable

Large (MiD) & small (MOP) sample

Combination of continouse survey (trends) and big sample Large sample is expensive

Differing reporting periods Complementary analysis Comparison of incomparable if inadequate post-harmonisiation

Differing instruments Complementary analysis Methodological bias; comparison of incomparable

Similar concepts (e.g. trip) Complementary / parallel analysis ---

Similar set of questions / variables

Parallel analysis; reciprocal validation

Limited comparability due to slight variations

Avoidance of pre-aggregated answering options easy post-harmonisation ---

Availability for third parties joint / comparative analyses Inaccurate data analysis in case of insufficient expertise





Travel activity

Respondents

In both surveys, „normal“ people are more likely to participate

Data quality: Selectivity of samples

Immobility due to handicaps?

Not interested in (travel) surveys?

Low income? Many business trips?

Busy people: lack of time?

Many recreational trips?

High income?

Many HH cars?





Traveled km in Germany

Use of public transport and cars in different age groups

Source: Kagerbauer and Vortisch.2013





Modes in Germany

Share of modes (trips) All persons

Modal split [%] all persons in Germany:

decreasing car use

Source: own calculations

PT

Bike

Walk

Car Pass.

Car Driver

Others

Year





Modes in Germany

Modal split [%] persons up to 30 years old in Germany:

decreasing car use and increasing use of PT

Share of modes (trips) All persons up to 30 years old


PT

Bike

Walk

Others

Year

Car Pass.

Car Driver





Verkehrsleistung in Deutschland

Modal split [%] persons 60 years old and more in Germany:

increasing car use

Share of modes (trips) All persons 60 years old and more


PT

Bike

Walk

Others

Year

Car Pass.

Car Driver





Car availability

0

20

40

60

80

100

18 bis unter 35 35 bis unter 60 60 und älter

Shar

e of

peo

ple

with

car [

%]

1996-1999 2005-2008

Deutsches Mobilitätspanel

Less car availability by younger persons – more car availability by elderly

Car availibility by age groups – End of 90s and today






Travel behavior changes

Increasing multimodal

travel behavior

Used modes in the last 15 years all persons

source: Kunert; Radke; Chlond; Kagerbauer: DIW Economic Bulletin, 2013





Demographic changes

Germany

Quelle: DESTATIS





Demographic changes

Germany

Quelle: DESTATIS





Demographic changes

Karlsruhe

Que

lle: B

erte

lsm

ann

Stif

tung

Quelle: Bertelsmann Stiftung





Demographic changes

Karlsruhe

Quelle: Bertelsmann Stiftung





Conclusions

Stagnation of traveled km per Person Decreasing car use of young adults Increasing car use of elderly people Differences between rural areas and conurbations

Demographic development Population is decreasing (in Europe and Germany) Population is getting older More population in conurbations – less in rural areas

Increasing inter- and multimodal travel behavior Use of all modes and and complementary mode us depending on the situation Mobility Services are getting more and more inportant Generation „iPhone“





Trends of development

Quelle: BITKOM, 2010

Question: „I can not imagine a life, without …“

Internet is getting more and more important instead of cars

Handy

Internet

car

my partner All 14 to 29 years





Reasons?

Season tickets for students

Quellen: Google Bilder: http://www.google.de

Mobility attitude Social Media and Apps

Other reasons





Outlook





Outlook

The futures mobility?

Quellen: www.bmw.de

Connected drive integrates Facebook, Twitter and

flinc (agency for arranging rides)





Outlook

Futures mobilty Car use instead of car ownership Multimodal instead of monomodal

Mobility services Car-Sharing Mobility apps New mobility ideas …

Source: Own figure

Complete solution Complementary modes





Agenda

10:30 – 11:15 Travel Demand (Surveys), Trends in Mobility Research 11:15 – 12:00 Business Models in the Mobility Sector 13:30 – 15:00 Hands On Session: The Future of Mobility 15:30 – 17:00 Present your Solutions!