Designing Conjoint Choice Experiments Using Managers' Prior Beliefs

@article{Sndor2001DesigningCC,
  title={Designing Conjoint Choice Experiments Using Managers' Prior Beliefs},
  author={Zsolt S{\'a}ndor and Michel Wedel},
  journal={Journal of Marketing Research},
  year={2001},
  volume={38},
  pages={430 - 444}
}
The authors provide more efficient designs for conjoint choice experiments based on prior information elicited from managers about the parameters and their associated uncertainty. The authors use a Bayesian design procedure that assumes a prior distribution of likely parameter values and optimizes the design over that distribution. The authors propose a way to elicit prior information from managers and show in Monte Carlo studies that the procedure provides more efficient designs than the… 

Figures and Tables from this paper

The usefulness of Bayesian optimal designs for discrete choice experiments

It is shown using an extensive case study that the resulting utility‐neutral optimal designs are not competitive with Bayesian optimal designs for estimation purposes.

Bayesian Conjoint Choice Designs for Measuring Willingness to Pay

In this paper, we propose a new criterion for selecting efficient conjoint choice designs when the interest is in quantifying willingness to pay (WTP). The new criterion, which we call the

Comparing Designs Constructed With and Without Priors for Choice Experiments: A Case Study

This article describes the second stage of an empirical comparison of the performance of designs for a discrete choice experiment. Six designs were chosen to represent the range of construction

Serial choice conjoint analysis for estimating discrete choice models

Serial choice conjoint is proposed in which each respondent faces a survey that has been optimized based on the choices of previous respondents, which keeps the advantage of efficient designs, i.e. requiring less respondents, while avoiding the need of priors.

Recommendations on the use of Bayesian optimal designs for choice experiments

In this paper, we argue that some of the prior parameter distributions used in the literature for the construction of Bayesian optimal designs are internally inconsistent. We provide practical advice

Heterogeneous Conjoint Choice Designs

Previous conjoint choice design construction procedures have produced a single homogeneous design that is administered to all study participants. In contrast, this article proposes to construct a
...

References

SHOWING 1-10 OF 22 REFERENCES

Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs

The drive to satisfy customers in narrowly defined market segments has led firms to offer wider arrays of products and services. Delivering products and services with the appropriate mix of features

Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data

The authors integrate concepts in conjoint analysis and discrete choice theory in econometrics to develop a new approach to the design and analysis of controlled consumer choice or resource

The Importance of Utility Balance in Efficient Choice Designs

Choice designs traditionally have been built under the assumption that all coefficients are zero. The authors show that if there are reasonable nonzero priors for expected coefficients, then these

A Comparison of Experimental Design Strategies for Multinomial Logit Models : The Case of Generic Attributes

The authors compare a variety of different designs for choice experiments that satisfy the properties of the MNL model, including both previously published and new design approaches based on “shifting” design codes that perform well in certain cases.

Graphical belief modeling

This innovative volume explores graphical models using belieffunctions as a representation of uncertainty, offering an alternative approach to problems where probability proves inadequate, and provides an invaluable illustration of the process of graphical belief modeling.

ELI: An Interactive Elicitation Technique for Subjective Probability Distributions

Abstract Uncertain knowledge about continuous quantities is usually formalized through subjective probability distributions (SPD′s). However, results from past experimental research have often

Optimal Design for Multinomial Choice Experiments

The author derives D-optimal designs for main-effects, multinomial choice experiments using attribute levels as design parameters. The design solutions are similar to standard main-effects designs

Designs of Discrete Choice Set Experiments for Estimating Both Attribute and Availability Cross Effects

The authors consider the construction of a class of discrete choice set experiment designs for estimating all availability and attribute cross effects where there are m brands and one attribute for each brand.

Bayesian estimation and experimental design in linear regression models

Estimation and Design as a Bayesian Decision Problem Choice of a Prior Distribution Conjugate Prior Distributions Bayes Estimation of the Regression Parameter Optimality and Robustness of the Bayes

Optimal Design: An Introduction to the Theory for Parameter Estimation

Prior to the 1970's a substantial literature had accumulated on the theory of optimal design, particularly of optimal linear regression design. To a certain extent the study of the subject had been