Abstract
Paul Green inspired many of us who work in conjoint analysis and related areas, such as stated preference discrete choice experiments, and all of us who undertake research in understanding and modeling preferences have benefited from his work. Knowing Paul Green, his impact and contributions will continue during his “retirement.” Our thanks to him for so many of the advances that we now often take for granted, but without which we would not be where we are today.
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References
Anderson, D. A., and Wiley, J. B. (1992),“Efficient choice set designs for estimating availability cross-effects models,”Marketing Letters, 3, 4, 357–370.
Batsell, R. R., and Lodish, L. M. (1981), “A model and measurement methodology for predicting individual consumer choice,” Journal of Marketing Research, 18, 1–12.
Batsell, R. R., and Polking, J. C. (1985), “A generalized model of market share,” Marketing Science, 4, 177–198.
Ben-Akiva, M., and Morikawa, T. (1990a), “Estimation of travel demand models from multiple data sources,”in M. Koshi (ed.), Transportation and Traffic Theory, North Holland: Elsevier, 461–476.
Ben-Akiva, M., and Morikawa, T. (1990b), “Estimation of switching models from revealed preferences and stated intentions,” Transportation Research A, 24A, 6, 485–495.
Ben-Akiva, M., McFadden, D., Train, K., Walker, J., Bhat, C., Bierlaire, M., Bolduc, D., Boersch-Supan, A., Brownstone, D., Bunch, D. S., Daly, A., de Valme, A., Gopinath, D., Karlstrom, A., and M. A. Munizaga (2002) “Hybrid choice models: Progress and challenges,” Marketing Letters, 13, 3, 163–176.
Berkum, E. E. M. van (1987a), “Optimal paired comparison designs for factorial and quadratic models,” Journal of Statistical Planning and Inference, 15, 265–278.
Berkum, E. E. M. van (1987b), “Optimal paired comparison designs for factorial experiments,” CW1 Tract, 31, Amsterdam.
Berkum, E. E. M. van (1989), “Reduction of the number of pairs in paired comparison designs and exact designs for quadratic models,” Computational Statistics and Data Analysis, 8, 93–107.
Bunch., D. S., Louviere, J. J., and Anderson, D. A. (1996), “A comparison of experimental design strategies for choice-based conjoint analysis with generic-attribute multinomial logit models,” Working Paper, Graduate School of Management, University of California, Davis, ( May).
Burgess, L., and Street, D. J. (2002), “Optimal designs for 2k choice experiments,” Research Report, Department of Mathematical Sciences, University of Technology, Sydney.
Cameron, T. A., Poe, G. L., Etheir, R. G., and Schulze, W. D. (2002), “Alternative nonmarket value-elicitation methods: Are the underlying preferences the same?” Journal of Environmental Economics and Management, 44, 391–425.
Carson, R. T., and Jeon, Y. (2002), “On overcoming informational deficiencies in estimating willingness to pay distributions,” Working Paper, Department of Economics, University of California, San Diego, ( September).
Dey, A. (1985), Orthogonal Fractional Factorial Designs, New York: John Wiley & Sons, Inc.
El-Helbawy, A. T., and Ahmed, E. A. (1984), “Optimal design results for 2” factorial paired comparison experiments,” Communications in Statistics–Theory and Methods, 13, 2827–2845.
El-Helbawy, A. T., Ahmed, E. A., and Alharbey, A.H. (1994), “Optimal designs for asymmetrical factorial paired comparison experiments,” Communications in Statistics –Simulation, 23, 663–681.
El Helbawy, A. T., and Bradley, R. A. (1978), “Treatment contrasts in paired comparisons: large-sample results, applications and some optimal designs,” Journal of the American Statistical Association, 73, 831–839.
Grasshoff, U., Grossmann, H., Holling, H., and Schwabe, R. (2002), “Optimal comparison designs for first order interactions,” available at http://www.math.unimagdeburg.de/ x2013;schwabe/Preprints/2002.
Green, P. E. (1974), “On the design of choice experiments involving multifactor alternatives,” Journal of Consumer Research, 1, 61–68.
Grossmann, H., Grasshoff, U., Holling, H., and Schwabe, R. (2001), “Efficient designs for paired comparisons with a polynomial factor,” in A. C. Atkinson, B. Bogacka,and A. Zhigljaysky (eds.), Optimum Design 2000, Dordrecht: Kluwer, 45–56.
Grossmann, H., Holling, H., Grasshoff, U., and Schwabe, R. (2002), “On the empirical relevance of optimal designs for the measurement of preferences,” available at http://www.math.uni-magdeburg.de/–schwabe/Preprints/2002.
Grossmann, H., Holling, H., and Schwabe, R. (2002), “Advances in optimum experimental
design for conjoint analysis and discrete choice models,” Econometric Models in Marketing,16, 91–115.
Hensher, D., and Bradley, M. (1993), “Using stated response choice data to enrich revealed preference discrete choice models,” Marketing Letters, 4, 2, 139–151.
Hensher, D.A., Louviere, J. J., and Swait, J. (1999), “Combining sources of preference data,” Journal of Econometrics, 89, 197–221.
Huber, J., and Zwerina, K. (1996), “The importance of utility balance in efficient choice designs,” Journal of Marketing Research, 33, 307–317.
Kanninen, B. J. (2002), “Optimal design for multinomial choice experiments,” Journal of Marketing Research, 39, 214–227.
Kuhfeld, W. F., Tobias, R. D., and Garratt, M. (1994), “Efficient experimental design with marketing research applications,” Journal of Marketing Research, 545–557.
Lazari, A. G., and Anderson, D. A. (1994), “Design of discrete choice set experiments for estimating both attribute and availability cross effects,” Journal of Marketing Research, 31, 375–383.
Louviere, J. J. (2001), “Response variability as a behavioral phenomenon,” Journal of Consumer Research, 28, 506–511.
Louviere,J. J.,and Woodworth, G. (1983), “Design and analysis of simulated consumer choice or allocation experiments: An approach based on aggregated data,” Journal of Marketing Research,20, 350–367.
Louviere, J. J., Fox, M., and Moore, W. (1993), “Cross-task validity comparisons of stated preference models,” Marketing Letters, 4, 205–213.
Louviere, J. J., Hensher, D. A., and Swait, J. (1999), “Conjoint analysis methods in the broader context of preference elicitation methods,” in A. Gustafson, A. Hermann, and F. Huber (eds.), Conjoint Measurement: Methods and Applications, Berlin: Springer-Verlag, 279–318.
Louviere, J. J., Hensher, D. A., and Swait, J. D. (2000), Stated Choice Methods: Analysis and Application, Cambridge, U.K.: Cambridge University Press.
Louviere, J. J., Meyer, R. J., Bunch, D. S., Carson, R. T., et al. (1999), “Combining sources of preference data for modeling complex decision processes,” Marketing Letters, 10, 3, 187–204.
Louviere, J. J., Street, D., Carson, R., Ainslie, A., et al. (2002), “Dissecting the random component of utility,” Marketing Letters, 13, 3, 177–193.
Luce, R. D. (1959), Individual Choice Behavior: A Theoretical Analysis, New York: John Wiley & Sons, Inc.
McFadden, D. (2001), “Disaggregate behavioral travel demand’s RUM side: A 30-year retrospective,” in D. A. Hensher (ed.), Travel Behavioral Research: The Leading Edge, Amsterdam: Pergamon, 17–64.
McFadden, D., and Train, K. (2000), “Mixed MNL models for discrete response,” Journal of Applied Econometrics, 15, 447–470.
McFadden, D., Tye, W., and Train, K. (1978), “An application of diagnostic tests for the independence from irrelevant alternatives property of the multinomial logit model,” Transportation Research Record, 637, 39–46.
Morikawa, T. (1989), Incorporating Stated Preference Data in Travel Demand Analysis, Unpublished PhD Dissertation, Department of Civil Engineering, M.I.T.
Offen, W. W., and Littell, R. C. (1987), “Design of paired comparison experiments when treatments are levels of a single quantitative variable,” Journal of Statistical Planning and Inference, 15, 331–346.
Quenouille, M. H., and John, J. A. (1971), “Paired comparison design for the 2”-factorials,” Applied Statistics, 20, 16–24.
Revelt, D., and Train, K. (1998), “Mixed logit with repeated choices: Households’ choices of appliance efficiency level,” Review of Economics and Statistics, 80, 1–11.
Sandor, Z., and Wedel, M. (2001), “Designing conjoint choice experiments using managers’ prior beliefs,” Journal of Marketing Research, 38, 430–444.
Severin, V. C. (2000), Comparing Statistical Efficiency and Respondent Efficiency in Choice Experiments, Unpublished PE Thesis, Faculty of Economics and Business, University of Sydney, Australia.
Street, D. J., Bunch, D. S., and Moore, B. (2001), “Optimal designs for 2” paired comparison experiments,” Communications in Statistics — Theory and Methods, 30, 2149–2171.
Street, D. J., and Burgess, L. (2003), “Optimal and near-optimal pairs for the estimation of effects in 2-level choice experiments,” Journal of Statistical Planning and Inference, forthcoming.
Swait, J., and Louviere, J. J. (1993), “The role of the scale parameter in the estimation and use of generalized extreme utility models,” Journal of Marketing Research, 30, 305–314.
Thurstone, L. L. (1927) “A law of comparative judgment,” Psychological Review, 34, 273–286
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Louviere, J., Street, D.J., Burgess, L. (2004). A 20+ Years’ Retrospective on Choice Experiments. In: Wind, Y., Green, P.E. (eds) Marketing Research and Modeling: Progress and Prospects. International Series in Quantitative Marketing, vol 14. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-28692-1_9
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DOI: https://doi.org/10.1007/978-0-387-28692-1_9
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