On the empirical relevance of optimal designs for the measurement of preferences

Applied Optimal Designs

Volumn , Issue , 2005, Pages 45-65

  GroΒmann, Heiko ^a   Holling, Heinz ^a   Brocke, Michaela ^a   GraΒhoff, Ulrike ^a,b   Schwabe, Rainer ^a,b  

^a UNIVERSITY OF MÜNSTER   (Germany)

^b OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

Conjoint analysis; Conjoint analysis software ACA; D optimal paired comparison designs; Distance optimality criterion; DS optimality; Linear model approach; Measurement of preferences; Optimal design theory

Indexed keywords

EID: 47249135815     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/0470857005.ch3     Document Type: Chapter

References (45)

1. ACA system (Version 4.0) [Computer software] (1994). Sawtooth Software, Evanston, Ill.
2. Bradley, R. A. and Terry, M. E. (1952). Rank analysis of incomplete block designs. I. The method of paired comparisons. Biometrika, 39, 324-345.
3. Carroll, J. D. and Green, P. E. (1995). Psychometric methods in marketing research: Part I, conjoint analysis. Journal of Marketing Research, 32, 385-391.
4. Cattin, P. and Wittink, D. R. (1982). Commercial use of conjoint analysis. A survey. Journal of Marketing, 46, 44-53.
5. David, H. A. (1988). The Method of Paired Comparisons, 2nd edn. Charles Griffin, London.
6. Fishburn, P. C. and Roberts, F. S. (1988). Unique finite conjoint measurement. Mathematical Social Sciences, 16, 107-143.
7. Gifi, A. (1990). Nonlinear Multivariate Analysis. John Wiley & Sons, Ltd, New York.
8. Graßhoff, U., Großmann, H., Holling, H. and Schwabe, R. (2004). Optimal designs for main effects in linear paired comparison models. Journal of Statistical Planning and Inference, 126, 361-376.
9. Green, P. E. (1974). On the design of choice experiments involving multifactor alternatives. Journal of Consumer Research, 1, 61-68.
10. Green, P. E., Carroll, J. D. and Carmone, F. J. (1978). Some new types of fractional factorial designs for marketing experiments. In: J. N. Sheth (ed.), Research in Marketing Vol. 1, pp. 99-122. JAI Press, Greenwich, Conn.
11. Green, P. E., Helsen, K. and Shandler, B. (1988). Conjoint internal validity under alternative profile presentations. Journal of Consumer Research, 15, 392-397.
12. Green, P. E., Krieger, A. M. and Wind, Y. (2001). Thirty years of conjoint analysis: reflections and prospects. Interfaces, 31(3), 56-73.
13. Green, P. E. and Rao, V. R. (1971). Conjoint measurement for quantifying judgmental data. Journal of Marketing Research, 8, 355-363.
14. Green, P. E. and Srinivasan, V. (1978). Conjoint analysis in consumer research: issues and outlook. Journal of Consumer Research, 5, 103-123.
15. Green, P. E. and Srinivasan, V. (1990). Conjoint analysis in marketing: new developments with implications for research and practice. Journal of Marketing, 54, 3-19.
16. Großmann, H., Holling, H., Graßhoff, U. and Schwabe, R. (2001). Efficient designs for paired comparisons with a polynomial factor. In: A. Atkinson, B. Bogacka and A. Zhigljavsky (eds), Optimum Design 2000, pp. 45-56. Kluwer, Dordrecht.
17. Großmann, H., Holling, H. and Schwabe, R. (2002). Advances in optimum experimental design for conjoint analysis and discrete choice models. In: P. H. Franses and A. L. Montgomery (eds), Econometric Models in Marketing, Advances in Econometrics, Vol. 16, pp. 93-117. JAI Press, Amsterdam.
18. Gustafsson, A., Herrmann, A. and Huber, F. (eds). (2000). Conjoint Measurement: Methods and Applications. Springer, Berlin.
19. Holling, H., Jütting, A. and Großmann, H. (2000). ALASCA: Computergestützte Entscheidungs- und Nutzenanalyse [ALASCA: Computerized decision and utility analysis]. Hogrefe, Göttingen.
20. Huber, J., Ariely, D. and Fischer, G. (2002). Expressing preferences in a principal-agent task: a comparison of choice, rating, and matching. Organizational Behavior and Human Decision Processes, 87, 66-90.
21. Kohli, R. and Mahajan, V. (1991). A reservation-price model for optimal pricing of multiattribute products in conjoint analysis. Journal of Marketing Research, 28, 347-354.
22. Krantz, D. H., Luce, R. D., Suppes, P. and Tversky, A. (1971). Foundations of Measurement. Vol. I: Additive and Polynomial Representations. Academic Press, New York.
23. Kruskal, J. B. (1965). Analysis of factorial experiments by estimating monotone transformations of the data. Journal of the Royal Statistical Society, Ser. B, 27, 251-263.
24. Kuhfeld, W. F., Tobias, R. D. and Garratt, M. (1994). Efficient experimental design with marketing research applications. Journal of Marketing Research, 31, 545-557.
25. Liski, E. P., Luoma, A. and Zaigraev, A. (1999). Distance optimality design criterion in linear models. Metrika, 49, 193-211.
26. Liski, E. P., Mandal, N. K., Shah, K. R. and Sinha, B. K. (2002). Topics in Optimal Design. Lecture Notes in Statistics, 163. Springer, New York.
27. Louviere, J. J. (1988a). Analyzing Decision Making. Metric Conjoint Analysis. Sage, Beverly Hills.
28. Louviere, J. J. (1988b). Conjoint analysis modelling of stated preferences: a review of theory, methods, recent developments and external validity. Journal of Transport Economics and Policy, 10, 93-119.
29. Louviere, J. J., Hensher, D. A. and Swait, J. D. (2000). Stated Choice Methods. Analysis and Application. Cambridge University Press, Cambridge, UK.
30. Luce, R. D. and Tukey, J. W. (1964). Simultaneous conjoint measurement: a new type of fundamental measurement. Journal of Mathematical Psychology, 1, 1-27.
31. Mukerjee, R., Dey, A. and Chatterjee, K. (2002). Optimal main effect plans with nonorthogonal blocking. Biometrika, 89, 225-229.
32. Reiners, W. (1996). Multiattributive Präferenzstrukturmodellierung durch die Conjoint Analyse [Multiattribute preference structure modelling by conjoint analysis]. LIT, Münster.
33. SahaRay, R. and Bhandari, S. K. (2003). DS-optimal designs in one way ANOVA. Metrika, 57, 115-125.
34. Scheffé, H. (1952). An analysis of variance for paired comparisons. Journal of the American Statistical Association, 47, 381-400.
35. Schwabe, R. (1996). Optimum Designs for Multi-factor Models. Lecture Notes in Statistics 113. Springer, New York.
36. Sinha, B. K. (1970). On the optimality of some designs. Calcutta Statistical Association Bulletin, 20, 1-20.
37. Srinivasan, V. and Shocker, A. D. (1973). Linear programming techniques for multidimensional analysis of preferences. Psychometrika, 38, 337-369.
38. k paired comparison experiments. Communications in Statistics - Theory and Methods, 30, 2149-2171.
39. Street, D. J. and Burgess, L. (2004). Optimal and near-optimal pairs for the estimation of effects in 2-level choice experiments. Journal of Statistical Planning and Inference, 118, 185-199.
40. Teichert, T. (2000). Auswirkungen von Verfahrensalternativen bei der Erhebung von Präferenzurteilen [Effects of alternative methods on the elicitation of preference judgments]. Marketing ZFP, 22(2), 145-159.
41. Thurstone, L. L. (1928). Attitudes can be measured. American Journal of Sociology, 33, 529-554.
42. van Berkum, E. E. M. (1987). Optimal Paired Comparison Designs for Factorial Experiments. CWI Tract 31. Amsterdam, Centrum voor Wiskunde en Informatica.
43. West, P. M. (1996). Predicting preferences: an examination of agent learning. Journal of Consumer Research, 23, 68-80.
44. Wittink, D. R. and Cattin, P. (1989). Commercial use of conjoint analysis: an update. Journal of Marketing, 53, 91-96.
45. Wittink, D. R., Vriens, M. and Burhenne, W. (1994). Commercial use of conjoint analysis in Europe: results and critical reflections. International Journal of Research in Marketing, 11, 41-52.