The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Designing Conjoint Choice Experiments Using Managers' Prior Beliefs
Open accessAbstract
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 current procedures. The authors provide an empirical application, in which they elicit prior information on the parameter values and the associated uncertainty from managers. Here, the Bayesian design provides 30%-50% lower standard errors of the estimates and an expected predictive validity that is approximately 20% higher.
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Cites
Statistical Decision Theory and Bayesian Analysis
Berger, J. O. (1985) · Springer Series in Statistics · doi:10.1007/978-1-4757-4286-2 · Cited by 7,722
Stastical Decision Theory and Bayesian Analysis.
Ghosh, M., & Berger, J. (1988) · Journal of the American Statistical Association · doi:10.2307/2288950 · Cited by 2,905
Calibration of probabilities: the state of the art to 1980
Lichtenstein, S., Fischhoff, B., & Phillips, L. D. (1982) · Judgment under Uncertainty · doi:10.1017/cbo9780511809477.023 · Cited by 1,967
Bayesian Experimental Design: A Review
Chaloner, K., & Verdinelli, I. (1995) · Statistical Science · doi:10.1214/ss/1177009939 · Cited by 1,839
Wheeler, R. E., Atkinson, A. C., & Donev, A. N. (1993) · Technometrics · doi:10.2307/1270278 · Cited by 1,447
Louviere, J. J., & Woodworth, G. (1983) · Journal of Marketing Research · doi:10.1177/002224378302000403 · Cited by 1,394
The Importance of Utility Balance in Efficient Choice Designs
Huber, J., & Zwerina, K. (1996) · Journal of Marketing Research · doi:10.1177/002224379603300305 · Cited by 1,100
Efficient Experimental Design with Marketing Research Applications
Kuhfeld, W. F., Tobias, R. D., & Garratt, M. (1994) · Journal of Marketing Research · doi:10.1177/002224379403100408 · Cited by 764
Atkinson, A. C., & Donev, A. N. (1992) · doi:10.1093/oso/9780198522546.001.0001 · Cited by 752
Silvey, S. D. (1980) · Springer eBooks · doi:10.1007/978-94-009-5912-5 · Cited by 572
Cited by
Reed Johnson, F., Lancsar, E., Marshall, D., Kilambi, V., Mühlbacher, A., Regier, D. A., Bresnahan, B. W., Kanninen, B., & Bridges, J. F. P. (2013) · Value in Health · doi:10.1016/j.jval.2012.08.2223 · Cited by 1,799
Discrete choice experiments in health economics: a review of the literature
de Bekker‐Grob, E. W., Ryan, M., & Gerard, K. (2012) · Health Economics · doi:10.1002/hec.1697 · Cited by 1,329
Constructing Efficient Stated Choice Experimental Designs
Rose, J. M., & Bliemer, M. C. J. (2009) · Transport Reviews · doi:10.1080/01441640902827623 · Cited by 797
Designing efficient stated choice experiments in the presence of reference alternatives
Rose, J. M., Bliemer, M. C. J., Hensher, D. A., & Collins, A. T. (2008) · Transportation Research Part B: Methodological · doi:10.1016/j.trb.2007.09.002 · Cited by 528
Pracejus, J. W., Olsen, G. D., & Brown, N. R. (2003) · Journal of Advertising · doi:10.1080/00913367.2003.10639146 · Cited by 196
Metadata
- Authors
- SÁndor, Z., & Wedel, M.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 2001-11
- Volume
- 38
- Issue
- 4
- Pages
- 430-444
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W2155825816
- Cited by
- 478
- References
- 23
- FWCI
- 19.69
- Type
- journal article
- Language
- en
- Open access
- green
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- SÁndor, Z., & Wedel, M. (2001). Designing Conjoint Choice Experiments Using Managers' Prior Beliefs. Journal of Marketing Research. https://doi.org/10.1509/jmkr.38.4.430.18904
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.