Soft transport policy measures 1 : Results of implementations

To abate problems resulting from increased car use, hard transport policy measures have been introduced. Such measures often meet public disapproval, are politically infeasible, and may alone be insufficient. As a consequence, alternative soft transport policy measures have been proposed. These measures are designed to motivate individuals to voluntarily reduce car use. This paper reviews implementations of soft transport policy measures in Japan, Australia, UK, and several other countries. The review underscores the effectiveness of soft transport policy measures in general and points to a variety of positive outcomes. Yet, the variety in the results makes it hard to infer why the measures are effective. Several gaps of knowledge are also identified. A companion paper will discuss these and identify research needs.

[1]  T. Gärling,et al.  Travel Demand Management Targeting Reduced Private Car Use: Effectiveness, Public Acceptability and Political Feasibility , 2007 .

[2]  Elizabeth Ampt,et al.  THE EVALUATION OF TRAVEL BEHAVIOUR CHANGE METHODS: A SIGNIFICANT CHALLENGE , 2001 .

[3]  P. Marinelli,et al.  TRAVELSMART SUBURBS BRISBANE: A SUCCESSFUL PILOT OF A VOLUNTARY TRAVEL BEHAVIOUR CHANGE TECHNIQUE , 2002 .

[4]  T. Gärling,et al.  Behavioural Theory Based Evaluation 1 Evaluation of Soft Transport Policy Measures Based on Behavioural Theory , 2009 .

[5]  Michael A. P. Taylor,et al.  Travelling smarter down under: policies for voluntary travel behaviour change in Australia , 2003 .

[6]  Linda Steg,et al.  Sustainable Transport Policy: The Contribution from Behavioural Scientists , 1999 .

[7]  Chuang-Zhong Li,et al.  Sustainable Transport , 2021, Industry, Innovation and Infrastructure.

[8]  Michael A. P. Taylor,et al.  Voluntary Travel Behavior Change Programs in Australia: The Carrot Rather Than the Stick in Travel Demand Management , 2007 .

[9]  J. Anable,et al.  Smarter Choices: Assessing the Potential to Achieve Traffic Reduction Using ‘Soft Measures’ , 2008 .

[10]  Satoshi Fujii,et al.  TIME-USE DATA, ANALYSIS AND MODELING: TOWARD THE NEXT GENERATION OF TRANSPORTATION PLANNING METHODOLOGIES , 1997 .

[11]  S. Bamberg,et al.  The effectiveness of soft transport policy measures: A critical assessment and meta-analysis of empirical evidence , 2008 .

[12]  S. Bamberg,et al.  Why are work travel plans effective? Comparing conclusions from narrative and meta-analytical research synthesis , 2007 .

[13]  Elizabeth S. Ampt,et al.  Travel Behavior Change through Individual Engagement , 2003 .

[14]  Peter Loukopoulos,et al.  A Classification of Travel Demand Management Measures , 2007 .

[15]  Elizabeth Ampt,et al.  Understanding Voluntary Travel Behaviour Change , 2003 .

[16]  A Taniguchi,et al.  A meta-analysis to evaluate an effectiveness of mobility management in Japan and its comparison to the case of EU countries , 2006 .

[17]  Ayako Taniguchi,et al.  Mobility Management in Japan , 2007 .

[18]  G. Rose,et al.  Travel blending: an Australian travel awareness initiative , 1997 .

[19]  E. I. Pas.  THE URBAN TRANSPORTATION PLANNING PROCESS , 1986 .

[20]  T. Gärling,et al.  Soft transport policy measures 2: research needs , 2009 .

[21]  S. Fujii,et al.  Determinants of the effectiveness of travel feedback programs—a review of communicative mobility management measures for changing travel behaviour in Japan , 2006 .

[22]  W. Broeg,et al.  BEHAVIOUR CHANGE SUSTAINABILITY FROM INDIVIDUALISED MARKETING , 1999 .