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Experimental analysis of choice

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Abstract

Experimental choice analysis continues to attract academic and applied attention. We review what is known about the design, conduct, analysis, and use of data from choice experiments, and indicate gaps in current knowledge that should be addressed in future research. Design strategies consistent with probabilistic models of choice process and the parallels between choice experiments and real markets are considered. Additionally, we address the issues of reliability and validity. Progress has been made in accounting for differences in reliability, but more research is needed to determine which experiments and response procedures will consistently produce more reliable data for various problems.

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References

  • Adamowicz, W., J. J. Louviere, and M. Williams. (1993). “Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities,” Working paper, University of Alberta.

  • Alberini, A., and R. T. Carson. (1993). “Choice of Thresholds for Efficient Binary Discrete Choice Estimation,” Discussion paper 90–34R, Department of Economics, University of California, San Diego, September.

    Google Scholar 

  • Anderson, D. A., A. Borgers, D. Ettema, and H. Timmermans. (1992). “Estimating Availability Effects in Travel Choice Modeling: A State Choice Approach,”Transportation Research Record 1357, 51–65.

    Google Scholar 

  • Anderson, D. A., J. J. Louviere, T. Daniel, and B. Orland. (1993). “Comparing Verbal and Visual Attribute Representations in Choice-Based Conjoint: Videotapes Versus Paper and Pencil,” Working paper, Department of Marketing, University of Utah.

  • Anderson, D. A., J. J. Louviere, and W. S. Jenkins (1992).Factors Affecting Users' Choices of National Forest Recreation Sites. Report to the U.S. Forest Service.

  • Anderson, D. A., and J. B. Wiley. (1992). “Efficient Choice Set Designs for Estimating Cross-Effects Models,”Marketing Letters 3, 357–370.

    Google Scholar 

  • Barnard, P. O., and D. A. Hensher. (1992). “The Spatial Distribution of Retail Expenditures,”Journal of Transport Economics and Policy 26, 299–312.

    Google Scholar 

  • Batsell, R. R., and J. J. Louviere. (1991). “Experimental Choice Analysis,”Marketing Letters 2, 199–214.

    Google Scholar 

  • Ben-Akiva, M., and S. R. Lerman. (1985).Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge, MA: MIT Press.

    Google Scholar 

  • Ben-Akiva, M., T. Morikawa, and F. Shiroishi. (1991). “Analysis of the Reliability of Preference Ranking Data,”Journal of Business Research 24, 149–164.

    Google Scholar 

  • Borjas, G., and G. Sueyoshi. (In press). “A Two-State Estimator for Probit Models with Structural Group Effects,”Journal of Econometrics.

  • Bradley, M. A., and A. J. Daly. (In press). “Use of the Logit Scaling Approach in Stated Preference Analysis,”Transportation.

  • Brossier, G. (1990). “Piecewise Hierarchial Clustering,”Journal of Classification 7, 197–216.

    Google Scholar 

  • Bunch, D., M. Bradley, T. Golob, R. Kitamura, and G. Occhiuzzo. (1993). “Demand for Cleanfuel Vehicles in California: A Discrete Choice Stated Preference Pilot Project,”Transporation Research A 27A, 237–253.

    Google Scholar 

  • Bunch, D., J. Louviere, and D. Anderson. (1993). “A Comparison of Experimental Design Strategies for Multinomial Logit Models: The Case of Generic Attributes,” Working paper, University of California, Davis.

    Google Scholar 

  • Cameron, A. C., and P. K. Trevedi. (1986). “Econometric Models Based on Count Data: Comparisons and Application of Some Estimators and Tests,”Journal of Applied Econometrics 1, 29–53.

    Google Scholar 

  • Cardell, S. (1989). “The Hedonic Demand Model and Some Other Extensions of Multinomial Logit.” Ph.D. dissertation, Harvard University.

  • Chapman, R. G., and R. Staelin (1982). “Exploiting Rank Ordered Choice Set Data Within the Stochastic Utility Model,”Journal of Marketing Research 19, 281–299.

    Google Scholar 

  • Dillon, W., and A. Kumar. (In press). “Latent Structure and Other Mixture Models in Marketing: An Integrative Survey and Overview.” In R. Bagozzi (ed.),Handbook of Marketing Research. Oxford: Blackwell.

  • Finn, A., J. J. Louviere, H. Timmermans, and W. Hutchinson. (1992). “International Generalizability of Shopping Center Choice and Consideration Models,” Paper presented at Marketing Science Conference, London, July.

  • Gaul, W., and M. Schader. (1988). “Clusterwise Aggregation of Relations,”Applied Stochastic Models and Data Analysis 4, 273–282.

    Google Scholar 

  • Guadagni, P. M., and J. D. C. Little. (1983). “A Logit Model of Brand Choice Calibrated on Scanner Data,”Marketing Science 2, 203–238.

    Google Scholar 

  • Hanemann, W. M. (1984). “Discrete Continuous Models of Consumer Demand,”Econometrica 52, 541–561.

    Google Scholar 

  • Hausman, J. A., and P. Ruud. (1987). “Specifying and Testing Econometric Models for Rank-Ordered Data,”Journal of Econometrics 34, 83–104.

    Google Scholar 

  • Hensher, D. A. (In press). “Stated Preference Analysis of Travel Choices: The State of Practice,”Transportation.

  • Hensher, D. A., P. Barnard, F. Milthorpe, and N. Smith. (1989). “Urban Tollways and the Valuation of Travel Time Savings,”Economic Record 66, 146–156.

    Google Scholar 

  • Hensher, D. A., and H.C. Battellino. (1993). “The Use of Discrete Choice Models in the Determination of Community Preferences Toward Sub-arterial Traffic Management Devices,” Proceedings of the 7th World Conference on Transport Research, Lyon France.

  • Hensher, D. A., and M. A. Bradley. (1993). “Using Stated Response Data to Enrich Revealed Preference Discrete Choice Models,”Marketing Letters 4, 139–152.

    Google Scholar 

  • Horowitz, J. L., and J. J. Louviere. (1990). “The External Validity of Choice Models Based on Laboratory Experiments.” In M. Fischer, P. Nijkamp, and Y. Papageorgiou (eds.),Spatial Choices and Process. Amsterdam: North-Holland.

    Google Scholar 

  • Huber, J., and J. Pinnell. (1993). “Value and Process Thresholds Governing Acceptance of a Default Alternative in Multiple Choice Tasks,” Paper presented at Duke Invitational Symposium on Choice Modeling and Behavior.

  • Hubert, L. J., and P. Arabie. (1992). “Correspondence Analysis and Optimal Structural Representations,”Psychometrika 56, 119–140.

    Google Scholar 

  • Kaciak, E., and J. J. Louviere. (1990). “Multiple Correspondence Analysis of Multiple Choice Data,”Journal of Marketing Research 27, 455–465.

    Google Scholar 

  • Kanninen, B. (1993). “Design of Sequential Experiments for Contingent Valuation Studies,”Journal of Environmental Economics and Management 25, 1–11.

    Google Scholar 

  • Kocur, G., and J. J. Louviere. (1983). “The Magnitude of Individual Level Variations in Demand Coefficients: A Xenia, Ohio, Case Example,”Transportation Research 17, 363–374.

    Google Scholar 

  • Krieger, A. B., and P. E. Green. (1991). “Designing Pareto Optimal Stimuli for Multiattribute Choice Experiments,”Marketing Letters 2, 337–348.

    Google Scholar 

  • Kuhfeld, W. F., M. Garratt, and R. D. Tobias. (1993). “Nonorthogonal Experimental Design Theory with Marketing Research Applications.” Paper presented at AMA Forum, Monterey, CA, June.

  • Lazari, A. (1991). “Designs for Discrete Choice Experiments Including Availability and Cross Effects.” Ph.D. Dissertation, University of Wyoming.

  • Lazari, A., and D. A. Anderson. (1993). “Availability and Attribute Cross-Effects Model: Determinant Optimal Designs,” Technical report, University of Wyoming.

  • Louviere, J. (1994a). “Conjoint Analysis.” In R. Bagozzi (ed.),Handbook of Marketing Research. Oxford: Blackwell.

    Google Scholar 

  • ——. (1984b). “Hierarchical Information Integration: A New Method for the Design and Analysis of Complex Multiattribute Judgement Problems,”Advances in Consumer Research 11, 148–155.

    Google Scholar 

  • ——. (1988).Analyzing Decision Making: Metric Conjoint Analysis. Beverly Hills: Sage.

    Google Scholar 

  • Louviere, J. J., M. Fox, and W. Moore. (1993). “Cross-Task Validity Comparisons of Stated Preference Choice Models,”Marketing Letters 4, 205–213.

    Google Scholar 

  • Louviere, J. J., and G. Woodworth. (1983). “Design and Analysis of Simulated Consumer Choice of Allocation Experiments,”Journal of Marketing Research 20, 350–367.

    Google Scholar 

  • McFadden, D., W. Tye, and K. Train. (1977). “An Application of Diagnostic Test for the Irrelevant Alternatives, Property of the Multinomial Logit Model,Transportation Research Record 637, 39–46.

    Google Scholar 

  • Montopoli, G. (1992). “The Analysis of Discrete Choice Set Experiments with Correlated Error Structure and Related Logistic Topics.” Ph.D. Dissertation, University of Wyoming.

  • Mitchell, R. C., and R. T. Carson. (1989).Using Surveys to Value Public Goods: The Contingent Valuation Method. Baltimore: Johns Hopkins University Press.

    Google Scholar 

  • Nelson, W. (1982).Applied Life Data Analysis. New York: John Wiley.

    Google Scholar 

  • Olsen, G. D., and J. Swait. (1993). “The Importance of Nothing.” Working paper, University of Calgary.

  • Oppewal, H., J. J. Louviere, and H. Timmermans. (In press). “Modeling Hierarchical Information Integration Processes with Integrated Conjoint Choice Experiments,”Journal of Marketing Research.

  • Raghavarao, D., and J. B. Wiley. (1993). “Experimental Designs for Availability Effects and Cross Effects with One Attribute.” Working paper, Department of Marketing and Economic Analysis, University of Alberta.

  • Sawtooth Software. (1993).The CBC System for Choice-Based Conjoint Analysis. Sun Valley: Sawtooth Software.

    Google Scholar 

  • Sueyoshi, G. (1992). “Semi-parametric Proportional Hazards Estimation of Competing Risks Models with Time Varying Covariates,”Journal of Econometrics 51, 25–58.

    Google Scholar 

  • Swait, J. (1993). “A Structural Equation Model of Latent Segmentation and Product Choice for Cross-Sectional Revealed Preference Choice Data.” Paper presented at the AMA Forum, Monterey, CA, June.

  • Swait, J., T. Erdem, J. J. Louviere, and C. Dubelaar. (1993). “The Equalization Price: A Measure of Consumer-Perceived Brand Equity,”International Journal of Research in Marketing.

  • Swait, J., and J. J. Louviere. (1993). “The Role of the Scale Parameter in the Estimation and Use of Generalized Extreme Value Models,”Journal of Marketing Research 30, 305–314.

    Google Scholar 

  • --. (In press). “A Sequential Approach to Exploiting the Combined Strengths of SP and RP Data: Application to Freight Shipper Choice,”Transportation.

  • Wiley, J. B. (1978). “Selecting Pareto Optimal Subsets from Multi-Attribute Alternatives,”Advances in Consumer Research 5, 171–174.

    Google Scholar 

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Carson, R.T., Louviere, J.J., Anderson, D.A. et al. Experimental analysis of choice. Market Lett 5, 351–367 (1994). https://doi.org/10.1007/BF00999210

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