Cet article cherche à estimer la validité prédictive de l'analyse conjointe lorsque des niveaux d'attribut interpolés sont insérés à l'intérieur des concepts à évaluer. Comme alternative à la pratique actuelle, cet article suggère d'utiliser les données perceptuelles lors de l'estimation de l'utilité associée à des niveaux d'attribut interpolés. Les résultats ont démontré que d'importants biais apparaissaient dans l'estimation des utilités estimées à partir des distances objectives. Cependant, aucune amélioration significative de la validité prédictive n'a pu être observée à travers la procédure des distances perceptuelles. Les implications de ces résultats sont discutées.
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References
1.
IsmaelAkaah P. (1987), Predictive Performance of Hybrid Conjoint Models in a Small Scale Design: An empirical Assessment, in AMA Educators Proceedings, DouglasSusan P., éds., Chicago, IL: American Marketing Association, 102–6.
2.
IsmaelAkaah P. (1988), Cluster Analysis Versus Q-type Factor Analysis as a Disaggregation Method in hybrid Conjoint Modeling: An Empirical Investigation, Journal of the Academy of Marketing Science, 19, Summer, 11–18.
3.
IsmaelAkaah P.PradeepKorgaonkar K. (1983), An Empirical Comparison of the Predictive Validity of Self-explicated, Huber-hybrid Conjoint Modeling: An Empirical Investigation, Journal of Marketing Research, 20, May, 187–197.
4.
NeilBeckwith E.DonaldLehman R. (1975), The Importance of Halo Effects in Multi-attribute Attitude Models, Journal of Marketing research, 12, August, 265–275.
5.
JamesBettman R. (1979), An Information Processing Theory of Consumer Choice, Reading, MA: Addison-Wesley.
6.
PhilippeCattinFriedhelmBliemel (1978), Metric vs. Nonmetric Procedures for Multiattribute Modeling: Some Simulation Results, Decision Sciences, 9, July, 472–480.
7.
RandallChapman G.RuthBolton N. (1985), Attribute Presentation Order Bias and Nonstationarity in Full Profile Conjoint Analysis Tasks, in LuschRobert F., éds., AMA Educator's Proceeding, Chicago, IL: American Marketing Association, 373–379.
8.
DavidsonJ.D. (1973), Forecasting Traffic on STOL, Operational Research Quarterly, 24, 561–569.
9.
FredEmery (1969), Some Psychological Aspects of Price, in TaylorBernardWillsGordon, éds., Pricing Strategy, London, Stapels Press, 98–111.
10.
PaulGreen E.StephenGoldberg M.JamesWiley B. (1983), A Cross-validation Test of Hybrid Conjoint Models, in Richard Bagozzi et Alice Tybout, éds, Advances in Consumer Research, vol. 10, Ann Arbor: Association of Consumer Research, 147–50.
11.
PaulGreen E.KristiaanHelsen (1989), Cross-validation Assessment of Alternatives to Individual-level Conjoint Analysis: A Case Study, Journal of Marketing Research, 26, August, 346–350.
12.
PaulGreen E.VithalaRao R.WayneDeSarbo (1978), Incorporating Group-level Similarity Judgments in Conjoint Analysis, Journal of Consumer research, 5, December, 187–193.
13.
MichaelHagerty R. (1985), Improving the Predictive Power of Conjoint Analysis: The Use of Factor Analysis and Cluster Analysis, Journal of Marketing Research, 22, May, 168–184.
14.
MorrisHolbrook B. (1983), Using a Structural Model of Halo Effect to Assess Perceptual Distortion Due to Affective Overtones, Journal of Consumer Research, 10, September, 247–252.
15.
MorrisHolbrook B.JoelHuber (1979), Separating Perceptual Dimensions From Affective Overtones: An Application to Consumer Aesthetics, Journal of Consumer Research, 5, March, 272–283.
16.
JacobJacobyJerryOlson C. (1977), Consumer Response to Price: An Attitudinal Information Processing Perspective, in WindYoramGreenbergMarshall, éds., Moving ahead with attitude research, Chicago, IL: American Marketing Association, 73–86.
17.
ThomasLeigh W.MacKayDavid B.JohnSummers O. (1984), Reliability and Validity of Conjoint Analysis and Self-explicated Weights: A Comparison, Journal of Marketing Research, 21, November, 456–462.
18.
DonaldLichtenstein R.PeterBolch H.WilliamBlack C. (1988), Correlates of Price Acceptability, Journal of Consumer Research, 15, May, 243–252.
19.
NareshMalhotra K. (1988), Some Observations on the State of the Art in Marketing Research, Journal of the Academy of Marketing Science, 16, Spring, 4–24.
20.
WilliamMoore L. (1980), Levels of Aggregation in Conjoint analysis: An Empirical Comparison, Journal of Marketing Research, 17, November, 516–523.
21.
KentMonroe B. (1973), Buyers’ Subjective Perceptions of Price, Journal of Marketing Research, 10, février, 70–80.
22.
KentMonroe B. (1979), Pricing: Making Profitable Decisions, New York: McGraw-Hill.
23.
HansMuhlbacherGuntherBotschen (1988), The Use of Trade-Off Analysis for the Design of Holiday Travel Packages, Journal of Business Research, 17, 117–31.
24.
AllanNewellHerbertSimon A. (1972), Human Problem Solving, Englewood Cliffs, NJ: Prentice-Hall.
25.
RichardNisbettLeeRoss (1980), Human Inference: Strategies and Shortcomings of Social Judgment, Englewood Cliffs, NJ: Prentice-Hall.
26.
DovPekelmanSubrataSen K. (1979a), Measurement and Estimation of Conjoint Utility Functions, Journal of Consumer Research, 5, March, 263–271.
27.
DovPekelmanSubrataSen K. (1979b), Improving Prediction in Conjoint Measurement, Journal of Marketing Research, 16, May, 211–220.
28.
DavidReibstein J.ChristopherLovelock H.De RecardoDobson P. (1980), The Direction of Causality Between Perceptions, Affects and Behavior: An Application to Travel Behavior, Journal of Consumer Research, 6, March, 370–376.
29.
JoelUrbany E.WilliamBearden O.DanWeilbaker C. (1988), The Effect of Plausible and Exaggerated Reference Prices on Consumer Perceptions and Price Search, Journal of Consumer Research, 15, June, 95–110.
30.
DickWittink R.PhilippeCattin (1989), Commercial Use of Conjoint Analysis: An Update, Journal of Marketing, 53, 91–96.
31.
WoodsideA. G.CarrJ.A. (1988), Consumer Decision Making and Competitive Marketing Strategies: Applications for Tourism Planning, Journal of Travel Research, 26, 3, 2–10.
32.
PeterWrightAnnKriewal Mary (1980), State-of-Mind Effects on the Accuracy With Which Utility Functions Predict Marketplace Choice, Journal of Marketing Research, 27, August, 277–293.
