On the robustness of efficient experimental designs towards the underlying decision rule

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
3 Downloads (Pure)

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 languageEnglish
Pages (from-to)50-64
Number of pages15
JournalTransportation Research Part A: Policy and Practice
Volume109
DOIs
Publication statusPublished - Mar 2018

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

    Cite this