Profile Construction in Experimental Choice Designs for Mixed Logit Models

By Zsolt Sándor, M. Wedel. 2002

252 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing

View Paper: https://www.semanticscholar.org/paper/10e05001fc09eda2754b52c3e67c8c33f6fc0c3c

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Citations in the corpus

Attribute Processing, Heuristics, and Preference Construction in Choice Analysis (2009, methodology): “The focus is on the uncertainty that arises because of the lack of knowledge of the true state of nature, where we not only lack the knowledge of a stable frequency (how can we be sure that the heuristic adopted is stable over time? (see also Yoon and Simonson 2008), as implied by the process heuris”
Non-attendance and dual processing of common-metric attributes in choice analysis: a latent class specification (2010, methodology): “A stated choice (SC) experiment was designed using principles of statistically efficient designs (Kanninen (2002), Sandor and Wedel (2002) , Rose and Bliemer (2007), and Kessel et al. (2006) provide overviews of such design methods).”
Constructing Efficient Stated Choice Experimental Designs (2009, methodology): “Other researchers however set up the design matrix such that each row of the matrix represents an individual alternative and each column a different attribute (see, e.g. Huber and Zwerina, 1996; Sándor and Wedel, 2001, 2002; Carlsson and Martinsson, 2002; Kanninen, 2002; Kessels et al., 2006).”
An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs (2009, methodology): “We expect that such an approach would allow an efficient estimation of mixed logit (Sándor and Wedel 2002) and latent class models (Andrews, Ainslie, and Currim 2002; Train 2003) that aim at modeling consumer heterogeneity.”
Sample size requirements for stated choice experiments (2013, result): “Nevertheless, recent research has shown (e.g., McFadden 1974; Sándor and Wedel 2001; Yu et al. 2009; Bliemer and Rose 2010) that D-optimal designs can provide (much) better parameter estimates than orthogonal designs, assuming that prior knowledge is available, at much smaller sample sizes.”
Estimating the willingness-to-pay and value of risk reduction for car occupants in the road environment (2009, methodology): “Recent new and innovative methods have been developed to allocate the attribute levels to the design matrix that do not rely on orthogonality as a design principle (see e.g., Bliemer and Rose 2006; Carlsson and Martinsson 2002; Ferrini and Scarpa 2007; Huber and Zwerina 1996; Kanninen 2002; Kessels ”
Experimental design influences on stated choice outputs: An empirical study in air travel choice (2009, background): “…but not limited to work undertaken by Bliemer et al. (2009), Burgess and Street (2003), Ferrini and Scarpa (2006), Kanninen (2002), Kessels et al. (2006), Sándor and Wedel (2001, 2002, 2005), Rose and Bliemer (2008), Scarpa and Rose (2008), Street and Burgess (2004) and Toner et al. (1999).”
Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force. (2013, methodology): “Analogously to Sándor and Wedel’s incorporation of Bayesian uncertainty about parameter distributions, Bliemer et al. [30] introduced a method to account for uncertainty as to what kind of model will be estimated once data have been collected.”
Nudging Energy Efficiency Behavior: The Role of Information Labels (2014, unknown): “…but also depends on the underlying choice probabilities, the choice sets fielded for each treatment were constructed using Bayesian methods for statistically efficient experimental design (Sándor and Wedel 2002; Kessels, Goos, and Vandebroek 2006; Ferrini and Scarpa 2007; Kessels et al. 2009).”
Construction of experimental designs for mixed logit models allowing for correlation across choice observations (2010, methodology): “Furthermore, efficient designs for the cross-sectional mixed logit model are discussed in Sándor and Wedel (2002), for the nested logit model in Bliemer et al. (2007), and for the error components model in Ferrini and Scarpa (2007).”
Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why* (2008, unknown): “In terms of assumptions our research is therefore more akin to research efforts by Sándor and Wedel (2001, 2002, 2005), Bliemer and Rose (2005), Bliemer et al .”