Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13824
Title: Optimizing the implementation of policy measures through social acceptance segmentation
Authors: COOLS, Mario 
BRIJS, Kris 
TORMANS, Hans 
De Laender, Jessie
WETS, Geert 
Issue Date: 2012
Source: Transport Policy, 22 (July 2012), p. 80-87
Abstract: This paper proposes Q-methodology as a technique for the identification of more homogenous subgroups or 'segments' within a rather heterogeneous overall population whenit comes to social acceptance of demand-restricting policy measures. Identification of such segments would allow policy makers to better tailor their future actions and thereby increase the chance for a succesful implementation of the measures they propose. A set of 33 persons, selected in function of age, gender and car ownership evaluated the acceptability of a number of 42 demand-restricting policy measures. Special care was taken care that the final set of statements covered the four classically distinguished demand-restricting strategies, i.e., improved transport options, incentives for the use of alternative transport modes, parking and land-use management, and institutional policy revision. In addition, a balance between both 'hard' and 'soft' and 'push' and 'pull' measures was strived for. The results indicate that four different segments in terms of social acceptance of demand-restricting policy measures can be distinguished, i.e., travelers in favor of traffic calming, travelers against hard push measures, travelers in favor of demand restriction, and travelers against policy innovations. Besides the differences and similarities between these segments, the practical implications for policy makers are discussed, together with a series of specific recommendations and suggestions for future research.
Keywords: sustainable transport; demand-restricting policy measures; social acceptance; Q-methodology
Document URI: http://hdl.handle.net/1942/13824
ISSN: 0967-070X
e-ISSN: 1879-310X
DOI: 10.1016/j.tranpol.2012.05.013
ISI #: 000307126500009
Category: A1
Type: Journal Contribution
Validations: ecoom 2013
Appears in Collections:Research publications

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