Drivers of cycling demand and cycling futures in the Danish context.

(1)

General rights

Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

•Users may download and print one copy of any publication from the public portal for the purpose of private study or research.

•You may not further distribute the material or use it for any profit-making activity or commercial gain

•You may freely distribute the URL identifying the publication in the public portal ?

If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Downloaded from orbit.dtu.dk on: Dec 17, 2015

Drivers of cycling demand and cycling futures in the Danish context.

Nielsen, Thomas Alexander Sick; Christiansen, Hjalmar; Jensen, Carsten; Skougaard, Britt Zoëga

Publication date: 2014

Document Version

Author final version (often known as postprint)

Link to publication

Citation (APA):

Nielsen, T. A. S., Christiansen, H., Jensen, C., & Skougaard, B. Z. (2014). Drivers of cycling demand and cycling futures in the Danish context. Technical University of Denmark, Transport. [Sound/Visual production (digital)]. Cosmobilities Conference, Copenhagen, Denmark, 05/11/2014, http://www.cosmobilities.net/

(2)

Drivers of cycling demand and cycling

futures in the Danish context

.

Thomas Sick Nielsen Hjalmar Christiansen Carsten Jensen

Britt Zoëga Skougaard E: thnie@transport.dtu.dk

Cosmobilities Conference, Networked Urban Mobilities; November 5-7 2014, Copenhagen

(3)

Approach

• Analysis of the time trend in cycling mode share based on longest possible time series

• Logistic regression model of cycling as mode choice as basis for studying ‘driver variables’ contribution to time trend.

(4)

3 DTU Transport, Danmarks Tekniske Universitet

Data

• Danish National Travel Survey (TU)

• Two survey periods: 1992-2003 & 2006-2014

• One day of travel for 10000 Danish resident individuals per survey year • Some breaks in dataseries and variables over time

• Analysis in this presentation is mainly based on 1995-2014 and respondents age 16-74 (N=654203 trips) for comparability and availability of explanatory variables.

• Variables available for 1995-2014 include: age, gender, occupation, accomodation, home ownership, family type, drivers license and car ownership.

• An indicator of spatial integration/regionalisation is developed based on survey average trip lenghts by municipality and year (endogenity issue!).

(5)

Trend: cycling mode share 1992-2014

*

0,0% 5,0% 10,0% 15,0% 20,0% 25,0% 1992M08 1993M02 1993M09 1994M03 1994M10 1995M04 1995M11 1996M05 1996M11 1997M05 1997M11 1998M05 1998M11 1999M05 1999M11 2000M05 2000M11 2001M05 2001M11 2002M05 2002M11 2003M05 2003M11 2004M05 2004M11 2005M05 2005M11 2006M05 2006M11 2007M05 2007M11 2008M05 2008M11 2009M05 2009M11 2010M05 2010M11 2011M05 2011M11 2012M05 2012M11 2013M05 2013M11

Bicycle share by month 12 months mean

(6)

Trend in bicycle share by municipality

1995-2013

Large decline (-0,4- -0,2) Decline (-0,2- -0,1) No significant changes Growth (0,1- 0,13) High growth (0,27- 0,5)

(7)

Correlation and driver changes 1995-2013

Correlation with cycling Change in driver 1995-2013

Winter Less likely to bicycle in winter (Dec, Jan, Feb) No

Gender Women are more likely to cycle no

Occupation Students and pupils more likely to cycle; self employed less More students and retirees; fewer housewives

Accomodation Multi story dwellings linked to cycling; farm houses link to less cycling New dwelling types (dormitories etc.)

Home ownership Renters and shared owners more likely to cycle Fewer renters

Family type Couples less likely to cycle than singles More singles, fewer couples with children

Age cohorts Older cohorts are more likely to cycle (exception is the oldest 1918-1930 cohort) General shift from older to younger cohorts (ageing)

City size (population) Residents of large cities are more likely to cycle Average city size is increasing (13%) (migration)

Population density Residents of dense municipalities are more likely to cycle Average density is increasing (6%) (migration)

Drivers license License holders are less likely to bicycle Growth in licenseholding (7%)

Car in household Car owners are less likely to bicycle Growth in carownership (8%)

Trip lenghts (municipality) Long average triplenghts makes it less likely to bicycle Strong growth in average triplenghts (31%)

+ + + -

(8)

+/-7 DTU Transport, Danmarks Tekniske Universitet

Main change processes

Demographic and socioeconomic change

Urbanisation

Motorisation

Regionalisation

Population size and density

Drivers license and car ownership

Average trip lenghts for residents of municpalities

(9)

Vectors of change in cycling share 1995-2013

-0,02 -0,015 -0,01 -0,005 0 0,005 1995 2013 General trend

Demographic and socioeconomic change Urbanisation

Motorisation Regionalisation

Changes to probability of cy

clin

g due to changes in driv

ers

Combined partial effects of variables and variable changes 1995-2013. Effects of demographics and urbanisation without control for motorisation

(10)

Summary

• Cycling mode share in Denmark has seen a negative time trend between 1995 and 2013.

• There are substantial trend differences between cities, their hinterlands og more remote areas. From large increases over large declines, to status-quo.

• The negative time trend may be partially explained by a combination of unfavorable demographic and socio-economic changes.

• Changes to car access (motorisation) and trip lenghts (regionalisation) can account for the rest – and more so.

• The ongoing urbanisation makes a positive contribution to cycling – but only partially counterbalances the negative influence of other changes. • Especially the increasing regionalisation where commuting, shopping etc.

increasingly involve ‘interurban’ travel stands out as a major challenge to cycling modeshare.

(11)

There is much more work to do...

• Inclusion of additional variables such as income. (comparability issues to be solved)

• Analysis of change in recent years (2006-2014) will allow better modelling - and fuller elaboration of change vectors.

• Narrowing of ‘time window’ for analysis pust requirements of explicit treatment of weather (e.g. long and cold winters) as well as specific events and incidences e.g. the role of the financial crisis for the trends after 2006/7.

• Elaboration of processes of regionalisation and increasing trip lenghts. Notably the interaction between urbanisation and regionalisation

processes.

• Elaboration of trend variation by geographical context – and exchange between cycling and walking modes.