Information overload in conjoint experiments

International Journal of Market Research

Volumn 46, Issue 3, 2004, Pages

  Lines, Rune ^a   Denstadli, Jon M ^a  

^a NORWEGIAN SCHOOL OF ECONOMICS   (Norway)

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EID: 3342970381     PISSN: 14707853     EISSN: None     Source Type: Journal    
DOI: 10.1177/147078530404600305     Document Type: Article

References (42)

1. Akaah, I.P. (1991) Predictive performance of self-explicated, traditional conjoint, and hybrid conjoint models under alternative data collection modes. Journal of the Academy of Marketing Science, 19, pp. 309-314.
2. Aaker, D.A. & Day, G.S. (1990) Marketing Research, 4th edn. New York: John Wiley & Sons.
3. Acito, F. (1977) An investigation of some data collection issues in conjoint measurement. In B.A. Greenberg & D.N. Bellenger (eds) Contemporary Marketing Thought. American Marketing Association.
4. Bateson, J.E.G., Reibstein, D. & Boulding, W. (1987) Conjoint analysis reliability and validity: a framework for future research. In Review of Marketing. M.J. Houston (ed.) American Marketing Association.
5. Bettman, J.R., Johnson, E.J. & Payne, J.W. (1991) Consumer decision making. In I.T.S. Robertson & H. Kassarijan (eds) Handbook of Consumer Behavior. Englewood Cliffs, NJ: Prentice-Hall.
6. Brucks, M. (1985) The effects of product class knowledge on information search behavior. Journal of Consumer Research, 12, pp. 1-16.
7. Cattin, P. & Weinberger, M.G. (1980) Some validity and reliability issues in the measurement of attribute utilities. Advances in Consumer Research, 7, pp. 780-783.
8. Cattin, P. & Wittink, D.R. (1982) Commercial use of conjoint analysis: a survey. Journal of Marketing, 46, pp. 44-53.
9. Fiske, S.T., Kinder, D.R. & Larter, W.M. (1983) The novice and the expert: knowledge-based strategies in political cognition. Journal of Experimental Social Psychology, 19, pp. 381-400.
10. Green, P.E. & Krieger, A.M. (1996) Individualized hybrid models for conjoint analysis. Management Science, 42, pp. 850-867.
11. Green, P.E., Goldberg, S.M. & Montemayor, M. (1981) A hybrid utility estimation model for conjoint analysis. Journal of Marketing, 45, pp. 33-41.
12. Green, P.E., Krieger, A.M. & Wind, Y. (2002) Thirty years of conjoint analysis: reflections and prospects. Interfaces, 31, pp. S56-S73.
13. Huber, J. & McCann, J. (1982) The impact of inferential beliefs on product evaluations. Journal of Marketing Research, 19, pp. 324-333.
14. Huber, J., Wittink, D.R., Fiedler, J.A. & Miller, R. (1993) The effectiveness of alternative preference elicitation procedures in predicting choice. Journal of Marketing Research, 30, pp. 105-114.
15. Jacoby, J., Speller, D.E. & Kohn, C.A. (1974a) Brand choice behavior as a function of information load. Journal of Marketing Research, 11, pp. 63-69.
16. Jacoby, J., Speller, D.E. & Kohn-Bering, C.A. (1974b) Brand choice behavior as a function of information load: replication and extension. Journal of Consumer Research, 1, pp. 33-42.
17. Jain, A.K., Acito, F, Malhotra, N.K. & Mahajan, V. (1979) A comparison of the internal validity of alternative parameter estimation methods in decompositional multiattribute preference models. Journal of Marketing Research, 16, pp. 313-322.
18. Johnson, R.D. (1989) Making decisions with incomplete information: the first complete test of the inference model. Advances in Consumer Research, 16, pp. 522-528.
19. Johnson, R.D. & Levin, I.P. (1985) More than meets the eye: the effect of missing information in purchase decisions. Journal of Consumer Research, 12, pp. 169-177.
20. Kiretz, R. & Simonsen, I. (2000) The effects of incomplete information on consumer choice. Journal of Marketing Research, 37, pp. 427-48.
21. Koutsoyiannis, A. (1977) Theory of Econometrics, 2nd edn. London: Macmillan Press.
22. Leigh, T.W., MacKay, D.B. & Summers, J.O. (1981) On alternative experimental methods for conjoint analysis. Advances in Consumer Research, 8, pp. 317-322.
23. Leigh, T.W., MacKay, D.B. & Summers, J.O. (1984) Reliability and validity of conjoint analysis and self-explicated weight: a comparison. Journal of Marketing Research, 21, pp. 456-462.
24. Lines, R., Denstadli, J.M. & Grönhaug, K. (1993) Predictive and convergent validity of conjoint derived and self explicated attribute weights. Barcelona: Proceedings, EMAC.
25. Lussier, D.A. & Oshlavsky, R.W. (1979) Task complexity and contingent information processing in brand choice. Journal of Consumer Research, 6, pp. 154-165.
26. McCullough, J. & Best, R. (1979) Conjoint measurement: temporal stability and structural reliability. Journal of Marketing Research, 16, pp. 26-31.
27. Malhotra, N.K. (1982) Information load and consumer decision making. Journal of Consumer Research, 8, pp. 419-430.
28. Meyer, R.J. (1981) A model of multi attribute judgments under attribute uncertainty and informational constraint. Journal of Marketing Research, 18, pp. 428-441.
29. Milford, J.T. & Perry, R.P. (1977) A methodological study of overload. Journal of General Psychology, 97, pp. 131-137.
30. Montgomery, D.B. & Wittink, D.R. (1980) The predictive validity of conjoint analysis for alternative aggregation schemes. In Marketing Measurement and Analysis: Proceedings of the 1979 ORSA/TIMS Conference on Marketing. Marketing Science Institute, Cambridge, MA, pp. 298-309.
31. Neslin, S.A. (1981) Linking product features to perceptions: self-stated versus statistically revealed importance weights. Journal of Marketing Research, 18, pp. 80-86.
32. Olshavsky, R.W. (1979) Task complexity and contingent processing in decision making: replication and extension. Organizational Behavior and Human Performance, 24, pp. 300-316.
33. Parker, B.R. & Srinivasan, V. (1976) A consumer preference approach to the planning of rural primary health care facilities. Operations Research, 24, pp. 991-1025.
34. Payne, J.W. (1976) Task complexity and contingent information processing in decision making: an information search and protocol analysis. Organizational Behavior and Human Performance, 16, pp. 366-387.
35. Petty, R.E. & Cacioppo, J.T. (1979) Issue involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of Personality and Social Psychology, 37, pp. 1915-1926.
36. Reibstein, D., Bateson, J.E.G. & Boulding, W. (1988) Conjoint analysis reliability: empirical findings. Marketing Science, 7, pp. 271-286.
37. Scott, J.E. & Wright, P. (1976) Modeling organizational buyers' product evaluation strategy: validity and procedural considerations. Journal of Marketing Research, 13, pp. 211-224.
38. Segal, M.N. (1982) Reliability of conjoint analysis: contrasting data collection procedures. Journal of Marketing Research, 13, pp. 211-224.
39. Selnes, F. & Grönhaug, K. (1986) Subjective and objective measures of product knowledge contrasted. Advances in Consumer Research, 13, pp. 67-71.
40. Shugan, S.M. (1980) The cost of thinking. Journal of Consumer Research, 7, pp. 99-111.
41. Srinivasan, S. & Pardk, C.S. (1997) Surprising robustness of the self-explicated approach to customer preference structure measurement. Journal of Marketing Research, 34, pp. 286-291.
42. Wittink, D.R. & Cattin, P. (1990) Commercial use of conjoint analysis: an update. Journal of Marketing, 53, pp. 91-96.