Abstract
We present a methodology to derive efficient designs for Stated Choice (SC) experiments based on Random Regret Minimisation (RRM) behavioural assumptions. This complements earlier work on the design of efficient SC experiments based on Random Utility Maximisation (RUM) models. Capitalizing on this methodology, and using both analytical derivations and empirical data, we investigate the importance of the analyst's assumption regarding the underlying decision rule used to generate the efficient experimental design. We find that conventional RUM-efficient designs can be statistically highly inefficient in cases where RRM is the better representation of the actual choice behaviour, and vice versa. Furthermore, we present a methodology to construct efficient designs that are robust towards the uncertainty on the side of the analyst regarding the underlying decision rule.
Original language | English |
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Pages (from-to) | 50-64 |
Number of pages | 15 |
Journal | Transportation Research Part A: Policy and Practice |
Volume | 109 |
DOIs | |
Publication status | Published - 2018 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Fingerprint
Dive into the research topics of 'On the robustness of efficient experimental designs towards the underlying decision rule'. Together they form a unique fingerprint.Datasets
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Small value-of-time experiment, Netherlands
van Cranenburgh, S. (Creator) & Chorus, C. G. (Creator), TU Delft - 4TU.ResearchData, 9 Oct 2018
DOI: 10.4121/UUID:1CCCA375-68CA-4CB6-8FC0-926712F50404
Dataset/Software: Dataset