Spatial Patterns, Congestion and Modelling
Edited by Eliahu Stern, IIan Salomon and Piet H.L. Bovy
Chapter 10: Stated preference and conjoint analysis: A comparison using mode-choice behaviour
10. Stated preference and conjoint analysis: A comparison using mode-choice behaviour Kay W. Axhausen, H. Köll and M. Bader 1. INTRODUCTION In spite of their known limitations and problems, stated-preference-based survey techniques have become an accepted part of the transport planning tool kit. In general they are implemented as stated-choice experiments, in which respondents are asked to choose between two or more alternatives described to them. The analysis of stated-preference data is decompositional in the sense that one derives the part-worths of the different variables describing the alternatives from the one, joint judgement of all attributes (A chosen over B; A ranked 5th, B 10th; A received a scale value of 6 out of 10). In the case of choice data, logit or related utility-maximizing models are used to derive those part-worths. In marketing, surveys of hypothetical markets/goods are called conjoint analyses. The approaches used, for example the very popular ACA Software (Adaptive Conjoint Analysis) (Sawtooth, 1996), are hybrids of compositional and decompositional analysis methods. Compositional utility estimation is performed in two steps. In the ﬁrst step, variables are ranked one at a time for their importance and their attribute levels are ranked for their desirability. The total utility of an alternative (composite good) is calculated as the importance-weighted sum of the desirabilities. Conjoint analysis (CA) and stated preferences (SP) belong therefore to the same general class of techniques, where the respondents are offered hypothetical goods, mostly in the form of written descriptions, either individually or in sets, which...
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