Ikels, M. (1995). Die Qualität von Conjoint-Analysen: Eine empirische Analyse zum Einfluß von Variationen des Untersuchungsdesigns. Frankfurt: St. Peter Port.

Irwin, J.R. & Spira, J.S. (1997). Anomalies in the values of consumer goods with environmental attributes. Journal of Consumer Psychology, 6 (4), 339-363.

Iten, R. (1990). Die mikroökonomische Bewertung von Veränderungen der Umweltqualität: dargestellt am Beispiel der Stadt Zürich. Winterthur: Schellenberg.


Jaccard, J., Brinberg, D. & Ackerman, L.J. (1986). Assessing attribute importance: A comparison of six methods. Journal of Consumer Research, 12 (March), 463-468.

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, 313-322.

Jain, A.K., Mahajan, V. & Malhotra, N.K. (1979). Multiattribute preference models for consumer research: A synthesis. In W.L. Wilkie (Ed.), Advances in consumer research (No. 6, pp. 248-252). Ann Arbor, MI: Association for Consumer Research.

Jain, A.K., Malhotra, N.K. & Mahajan, V. (1979). Aggregating conjoint data: Some methodological considerations and approaches. In N. Beckwith, M. Houston, R. Mittelstaedt, K.B. Monroe & S. Ward (Eds.), 1979 AMA Educators’ Proceedings (No. 44, pp. 74-77). Chicago, IL: American Marketing Association.

Jain, A.K., Malhotra, N.K. & Pinson, C. (1980). Stability and reliability of part-worth utility in conjoint analysis: A longitudinal investigation. Working Paper 80/05, European Institute of Business Administration.

Jain, D.C., Muller, E. & Vilcassim, N.J. (1999). Pricing patterns of cellular phones and phonecalls: A segment level analysis. Management Science, 45 (2), 131-141.

Jan, S., Mooney, G., Ryan, M., Bruggemann, K. & Alexander, K. (2000). The use of conjoint analysis to elicit community preferences in public health research: A case study of hospital services in South Australia. Australian and New Zealand Journal of Public Health, 24 (1), 64-70.

Janssen, V. (2000). Werbeerfolgskontrolle auf dem Prüfstand. Transfer Werbeforschung & Praxis, 45 (3), 33-35.

Jasny, R. (1994). Marktsimulationen mit Hilfe von Präferenzdaten zur kundenorientierten Planung von Vermögensanlageprodukten. München: VVF.

Jedidi, K., Kohli, R. & Desarbo, W.S. (1996). Consideration sets in conjoint analysis. Journal of Marketing Research, 28, 364-372.

Jenkins Jr., H.W. (1998, November). Business World: Rescuing the fat and happy. Wall Street Journal, 4, A23.

John, P.W.M. (1971). Chapter 9: Fractional factorials with more than two levels. In Statistical design and analysis of experiments (pp. 177-192). New York, NY: The Macmillan Company.

Johnson, E., Meyer, R.J. & Ghose, S. (1989). When choice models fail: Compensatory models in negatively correlated environments. Journal of Marketing Research, 26, 255-270.

Johnson, F., Desvousges, W., Wood, L. & Fries, E. (1995). Conjoint analysis of individual and aggregate environmental preferences. Technical Paper, No. T-9502, Triangle Economic Research.

Johnson, F.R., Desvousges, W.H., Ruby, M.C., Stieb, D. & De Civita, P. (1998). Eliciting stated health preferences: An application to willingness to pay for longevity. Medical Decision Making, 18 (2), S57-S67.

Johnson, J.S., Leone, T. & Fiedler, J. (1999). Conjoint analysis on the internet. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 145-148). Sequim, WA: Sawtooth Software.

Johnson, L.W. & Winzar H. (1992). Testing convergent and predictive validity of self-explicated and conjoint measures of consumer utility. Conference Paper, TIMS Marketing Science Conference, London Business School, London, UK.

Johnson, L.W., Ringham, L. & Jurd, K. (1991). Behavioral segmentation in the Australian wine market using conjoint choice analysis. International Marketing Review, 8 (2), 26-31.

Johnson, M.D. (1989a). The differential processing of product category and noncomparable choice alternatives. Journal Consumer Research, 16, 300-309.

Johnson, M.D. (1989b). On the nature of product attributes and attribute relationships. In T.K. Srull (Ed.), Advances in consumer research (No. 16, pp. 598-604). Provo, UT: Association for Consumer Research.

Johnson, R.D. (1987). Making judgments when information is missing: Inferences, biases, and framing effects. Acta Psychologica, 66, 69-82.

Johnson, R.D., Louviere, J.J. & Olsen, G.D. (1990). Are order and practice effects task dependent? Choice versus ratings. Paper presented at the 1990 Marketing Science Conference, Urbana-Champaign, IL.

Johnson, R.M. & Olberts, K.A. (1991). Using conjoint analysis in pricing studies: Is one price variable enough? American Marketing Association Advanced Research Technique Forum Conference Proceedings (pp. 164-173).

Johnson, R.M. & Pinnell, J. (1995). Comment on "Incorporating prior knowledge into the analysis of conjoint studies". Working Paper. Sequim, WA: Sawtooth Software.

Johnson, R.M. (1973). Pairwise nonmetric multidimensional scaling. Psychometrika, 38, 11-18.

Johnson, R.M. (1974). Trade-off analysis of consumer values. Journal of Marketing Research, 11, 121-127.

Johnson, R.M. (1975). A simple method for pairwise monotone regression. Psychometrika, 40, 163-168.

Johnson, R.M. (1976). Beyond conjoint measurement: A method of pairwise tradeoff analysis. In B.B. Anderson (Ed.), Advances in consumer research (Vol. 3, pp. 353-358). Provo, UT: Association for Consumer Research.

Johnson, R.M. (1981, October). Problems in applying conjoint analysis. In R.K. Srivastava & A.D. Shocker (Eds.), Analytic approaches to product and marketing planning: The second conference (No. 82-109, pp. 154-165). Cambridge, MA: Marketing Science Institute.

Johnson, R.M. (1987). Adaptive conjoint analysis. In Sawtooth Software (Ed.), Proceedings of the Sawtooth Software Conference on Perceptual Mapping, Conjoint Analysis, and Computer Interviewing (No. 1, pp. 253-265). Ketchum, ID: Sawtooth Software.

Johnson, R.M. (1988). Comment on Finkbeiner (1988). R.M. Johnson (Ed.), Proceedings of the Sawtooth Software Conference of Perceptual Mapping, Conjoint Analysis, and Computer Interviewing (No. 2, pp. 105-108). Ketchum, ID: Sawtooth Software.

Johnson, R.M. (1989). Assessing the validity of conjoint analysis. In Sawtooth Software (Ed.), Proceedings of the Sawtooth Software Conference. Gaining a competitive advantage through PC-based interviewing and analysis (Vol. 1, pp. 273-280). Ketchum, ID: Sawtooth Software.

Johnson, R.M. (1991). Comment on "Adaptive conjoint analysis: Some caveats and suggestions". Journal of Marketing Research, 28, 223-225.

Johnson, R.M. (1992). Ci3: Introduction and evolution. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 91-102). Ketchum, ID: Sawtooth Software.

Johnson, R.M. (2000). Monotonicity constraints in choice-based conjoint with hierarchical Bayes. Technical paper, Sawtooth Software, Inc.

Johnson, R.M. (2000). Understanding HB: An intuitive approach. In Proceedings of the Sawtooth Software Conference (No. 8, pp. 195-205). Sequim, WA: Sawtooth Software.

Johnson, R.M., Shocker, A.D. & Wittink, D.R. (1991). The effect of design and estimation program on conjoint utility limits: A comment. Marketing Research, March, 54-49.

Jonas, K. (1993). Expectancy-value models of health behaviour: An analysis by conjoint measurement. European Journal of Social Psychology, 23 (2), 167-183.

Jones, D.F. (1975). A survey technique to measure demand under various pricing strategies. Journal of Marketing, 39 (3), 75-77.

Joseph, A.E., Smit, B. & McIlravey, G.P. (1989). Consumer preferences for rural residences: A conjoint analysis in Ontario, Canada. Environment Planning A, 21, 47-63.

June, L.P. & Smith, S.L. (1987). Service attributes and situational effects on consumer preferences for restaurant dining. Journal of Travel Research, 20-27.