This research examines the contribution of an explanatory model of behaviour to understanding response to a new transport policy instrument. The travel demand management technique; individualised marketing campaigns (IMCs; a form of personalised journey planning) are considered. IMCs are voluntary and are used to reduce car use where there is excess demand, or current levels of demand make it difficult to meet environmental and social policy objectives. However, reducing car use, which has many benefits and can be habitual, without penalties, which can be politically unacceptable, is slow and sometimes results in small amounts of behaviour change. One reason may be that IMCs are poorly understood, and not used in an optimal way. The research reported aimed to explain response to IMCs using an expectancy-value model. The aims of the research were two fold. Firstly, to establish whether such a model explains response to IMCs sufficiently to predict response and inform decision making. Secondly, to ascertain whether the explanation provided can contribute to improving the performance of such projects through improved design, and by identifying the most receptive target audience for IMCs. The expectancy-value model used was the Theory of Planned Behaviour (TPB). Expectancy-value modelling is based on an assumption of utility maximisation and rational decision making, but unlike some analysis frameworks, the TPB also considers three core social constructs underlying personal decision making. Experimental IMCs were implemented in two English cities to gauge transferability. The design of the IMCs was based on previous case studies to enable comparison of behaviour change. Data on the core social constructs, intentions to respond to the IMCs by reducing car use, and actual responses were collected. The data was analysed to compare samples, and explain intended and actual responses to the IMCs. The results of the IMCs are presented, comparing them to other such projects, followed by the TPB model analysis, and the questions raised above are considered. The results suggest that it is possible to explain some intentions to reduce car use as a result of the IMCs, but that explanation of actual response is lower. However, for the intentions that were explained, significant explanatory constructs were identified. Further to this, individuals who may respond positively to IMCs has been identified. These individuals provide in important target audience of innovators who could establishing a precedent for reducing car use and achieving critical mass. Consequences for the design and targeting of IMCs are discussed.