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B1640
Title: Optimal design and analysis of discrete choice experiments with partial profiles involving a no-choice option Authors:  Roselinde Kessels - University of Antwerp (Belgium) [presenting]
Daniel Palhazi Cuervo - University of Antwerp (Belgium)
Abstract: The aim is to show how to optimally design and analyse a discrete choice experiment (DCE) with a no-choice option for estimating a nested logit model when partial profiles are used to study a large number of attributes. As a motivating example, we describe a DCE to identify and quantify the determinants that influence the competitive position of the coach bus as transport mode for medium-distance travel by Belgians. We measured the attractiveness of different bus services for different destinations (Lille, Amsterdam, Cologne, Paris and Frankfurt) by having participants choose their preferred bus trip out of two bus trips, while still allowing them to also choose not to take the bus but any other transport mode comprised by the no-choice option. Each bus trip is a combination of levels of seven attributes: price, duration, and comfort attributes including wifi, leg space, catering, entertainment and individual power outlet. Varying the levels of all seven attributes of the bus trips in the choice sets would be cognitively too demanding for respondents. To ensure sensible and manageable choice tasks, we present and compare new and existing optimal design and analysis approaches for a no-choice partial profile setting in which the levels of only a subset of the attributes vary within every choice set.