Constructing Efficient Stated Choice Experimental Designs

By John M. Rose, Michiel C. J. Bliemer. 2009

804 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Transportation

View Paper: https://www.semanticscholar.org/paper/bd7e9ec492f60bdc7f388f2d0ab2e11d7bc5e19b

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Citations in the corpus

Modelling mode choice for freight transport using advanced choice experiments (2015, neutral): “…are aware that these designs are created to satisfy the econometric properties of linear regression models, not discrete choice models like the Multinomial Logit (see Rose and Bliemer, 2009 for an excellent discussion on the performance of efficient designs in comparison with other methods).”
Energy Efficiency Investments in the Home: Swiss Homeowners and Expectations about Future Energy Prices (2013, methodology): “Second, a fold-over design was used to generate a subsequent alternative B (Rose and Bliemer, 2009).”
Determining guests’ willingness to pay for hotel room attributes with a discrete choice model (2015, background): “Indeed, while efficient designs consistently increase the reliability of the model estimates (Rose & Bliemer, 2009), their formulation requires some prior knowledge about the model estimates.”
On the Treatment of Repeated Observations in Panel Data: Efficiency of Mixed Logit Parameter Estimates (2011, methodology): “…to measure the statistical efficiency of the expected outcomes of models estimated on a given dataset as in the experimental design literature (Rose and Bliemer, 2009); this can be done by computing the negative inverse of the Fisher information matrix (i.e. the asymptotic covariance matrix,…”
Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China (2018, methodology): “Although this is not as advanced as several later proposed designs, such as D-optimal design and D-efficient design (Bliemer et al., 2009; Rose and Bliemer, 2009; Bliemer and Rose, 2010), this project adopted the traditional orthogonal design due to time, cost and availability of advanced data…”
Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory (2017, methodology): “The combination of levels that appeared in each choice task was defined according to three different sub designs, namely near orthogonal, D-efficient [73], [74], [75], [76], and a serial design [77].”
Bayesian optimal designs for discrete choice experiments with partial profiles (2011, background): “As pointed out by Rose and Bliemer (2009), the Street and Burgess designs may promote lexicographic choice behavior.”