NDLI: 324,000 people can't be wrong: evaluating the world's largest individualised marketing project

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324,000 people can't be wrong: evaluating the world's largest individualised marketing project

Content Provider	Semantic Scholar
Author	Freer, David Henderson, Paul Cubie, Andy
Copyright Year	2010
Abstract	The aim of this travel behaviour change project in Queensland is to reduce vehicle kilometres travelled by 10 per cent, reduce CO2 emissions and increase sustainable transport use. The qualitative and quantitative impacts of the project are being assessed based on a methodology that goes beyond just measuring journeys and includes understanding how and why people have changed their behaviour and whether this change is a short term reaction to stimuli or a long term shift in attitude. The 3-year evaluation includes an analysis of attitudes, modal shift, external factors (such as policy / infrastructure changes) and public perception. Evaluation of what has changed in terms of reduced vehicle trips, increased walking / cycling, reduced travel distances and greater public transport use and why it has changed in terms of the behavioural motivators will be carried out. This paper will give an in depth look at the evaluation methodology used by the authors and how it differs from evaluations of previous TravelSmart Communities projects, supported by qualitative and quantitative data where available. At this stage the paper does not include a full comparison of implementation methodologies (to be completed at the end of the project). A comprehensive review of best practice (national and international) is included in the full benchmark report (focused on projects involving direct household contact as opposed to broader initiatives involving schools or workplaces) and is referenced in this paper. (a) For the covering record of this conference, please refer to ITRD abstract no E220725.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://atrf.info/papers/2010/2010_Freer_Henderson_Cubie.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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