C
Cairns,
J. & van der Pol, M. (2001). Discrete choice with
repeated follow-up: A web-based experiment. Skriftserie
i helseøkonomi (No. 30), Program for helseøkonomi i Bergen.
Cakelja,
J. (1999). Einsatz der Conjoint-Analyse zur Bewertung von Logistiksystemen.
Diplomarbeit, Wirtschaftsuniversität Wien.
Carmichael, B. (1992). Chapter 6:
Using conjoint modeling to measure tourist image and analyze ski resort choice.
In P. Johnson & B. Thomas (Eds.), Choice and demand in tourism (pp.
93-106).
Carmichael, B. (1996). Conjoint
analysis of downhill skiers used to improve data collection for market
segmentation. Journal of Travel and Tourism Marketing, 5 (3), 187-206.
Carmone, F. (1987). New books in
review: ACA system for adaptive conjoint analysis. Journal of Marketing
Research, 24, 325-327.
Carmone, F.J. & Green, P.E.
(1981). Model misspecification in multiattribute parameter estimation. Journal
of Marketing Research, 18, 87-93.
Carmone, F.J. & Shaffer, C.M.
(1995). Software Review: Conjoint Designer, Conjoint Analyzer, SIMGRAF,
Conjoint Linmap, Conjoint Segmenter, Bridger, CONSURV, ACA, CBC, CVA. Journal
of Marketing Research, 32 (1), 113-120.
Carmone, F.J. (1986). New books in
review: CONJOINT DESIGNER. Journal of Marketing Research, 23, 311-312.
Carmone, F.J., Green, P.E. &
Jain, A.K. (1978). Robustness of conjoint analysis: Some monté carlo results. Journal
of Marketing Research, 15, 300-303.
Carpenter,
G.S., Glazer, R. & Nakamoto, K. (1994). Meaningful
brands from meaningless differentiation: The dependence on irrelevant
attributes. Journal of Marketing Research, 31, 339-350.
Carroll, J.D. & Green, P.E.
(1995). Psychometric methods in marketing research: Part I, Conjoint analysis. Journal
of Marketing Research, 23 (November), 385-391.
Carroll, J.D. (1969). Categorial
conjoint measurement. Paper presented at the Meeting of Mathematical
Psychology, Ann Arbor.
Carroll, J.D. (1969). Categorical
conjoint measurement. Unpublished Manuscript, Bell Laboratories, Murray
Hill, NJOURNAL.
Carroll, J.D. (1973). Models and
algorithms for multidimensional scaling, conjoint measurement, and related
techniques. In P.E. Green & Y. Wind (Eds.), Multivariate decisions in
marketing: A measurement approach (pp. 199-273). Hinsdale: The Dryden
Press.
Carroll, N.V. & Gagnon, J.P.
(1984). Consumer demand for patient-oriented pharmacy
services. American Journal of Public Health, 74 (6), 609-611.
Carter,
R. & Dubelaar, C. & Wiley, J.B. (2000). Applying
choice based conjoint measurement to forecast demand for a new restaurant
category. Journal of Food Products Marketing, 6 (3), 63-78.
Cattin,
P. & Bliemel, F. (1978). Metric vs. nonmetric procedures
for multiattribute modeling: Some simulation results. Decision Sciences, 9,
474-480.
Cattin, P. & Weinberger, M.
(1980). Some validity and reliability issues in the measurement of attribute
utilities. In J. Olson (Ed.), Advances in consumer research: Proceedings of
the Association for Consumer Research Tenth Annual Conference (No. 7, pp.
780-783). San Francisco, CA: Association for Consumer Research.
Cattin, P. & Wittink, D.R.
(1981). Commercial use of conjoint analysis: A survey. In J.W. Keon (Ed.),
Marketing: Measurement and analysis 1981, Proceedings of the Third ORSA/
TIMS special interest conference on market measurement and analysis (pp.
21-31).
Cattin, P. & Wittink, D.R.
(1982). Commercial use of conjoint analysis: A survey. Journal of Marketing,
46 (Summer), 44-53.
Cattin,
P., Gelfand, A.E. & Danes, J. (1983). A simple
bayesian procedure for estimation in a conjoint model. Journal of Marketing
Research, 20, 29-35.
Cattin, P., Hermet, G. &
Pioche, A. (1982). Alternative hybrid models for conjoint analysis: Some
empirical results. In R.K. Srivastava & A.D. Shocker (Eds.), Analytic
Approaches to Product and Marketing Planning: The Second Conference (No.
82-109, pp. 142-151). Cambridge, MA: Marketing Science Institute.
Cerro, D. (1988). Conjoint
analysis by mail. In R.M. Johnson (Ed.), Proceedings of the Sawtooth
Software Conference on Perceptual Mapping, Conjoint Analysis, and Computer
Interviewing (No. 2, pp. 139-144). Ketchum, ID: Sawtooth Software.
Cestre, G. & Darmon, R.Y. (1998).
Assessing consumer preferences in the context of new product diffusion. International
Journal of Research in Marketing, 15, 123-135.
Chakraborty, G., Ball, D., Gaeth,
G.J. & Sunkyu, J. (2002). The ability of ratings and choice conjoint to
predict market shares. A Monte Carlo simulation. Journal of Business
Research, 55 (3), 237-249.
Chakraborty, G., Ettenson, R.
& Gaeth, G. (1994). How consumers choose health insurance. Analyzing
employees´ selection process in a multiplan environment identifies
the trade-offs consumers make and the benefits that affect their decision
making. Journal of Health Care Marketing, 14 (1), 21-33.
Chakraborty, G., Gaeth, G. &
Cunningham, M. (1993). Understanding consumers preferences for dental service. Journal
of Health Care Marketing, 13 (3), 48-58.
Chakraborty, G., Woodworth, G.G.,
Gaeth, G.J. & Ettenson, R. (1992). Screening for interactions between
design factors and demographics in choice-based conjoint. Journal of
Business Research, 24 (2), 115-133.
Chakraborty, G., Woodworth, G.G.,
Gaeth, G.J. & Ettenson, R. (1991). Screening for interactions between
design factors and demographics in choice-based conjoint. Journal of
Business Research, 23 (3), 219-237.
Chan, L.K., Kao, H.P., Ng, A.
& Wu, M.L. (1999). Rating the importance of customer needs in quality
function deployment by fuzzy and entropy methods. International Journal of
Production Research, 37 (11), 2499-2518.
Chapman, R.G. & Bolton, R.N.
(1985). Attribute presentation order bias and nonstationarity in full profile
conjoint analysis tasks. In R.F. Lusch, G.T. Ford, G.L. Frazier, R.D. Howell,
C.A. Ingene, M. Reilly & R.W. Stampfl (Eds.), 1985 AMA Educators’
Proceedings (No. 51, pp. 373-379). Chicago, IL: American Marketing
Association.
Chapman, R.G. & Staelin, R.
(1982). Exploiting rank ordered choice set data within the stochastic utility
model. Journal of Marketing Research, 19, 288-301.
Chapman, R.G. (1984). An approach
to estimating logit models of a single decision maker's choice behavior. In Advances
in consumer research (No. 11, pp. 656-661). Provo, UT: Association for
Consumer Research.
Chapman, R.G. (1993). BRANDSä
: A marketing game. Englewood Cliffs, NJ: Prentice Hall, Inc.
Chen,
K.D. & Hausman, W.H. (2000). Technical note: Mathematical
properties of the optimal product line selection problem using choice-based
conjoint analysis. Management Science, 46 (2), 327-332.
Chinburapa, V., Larson, L.N., Brucks,
M., Draugalis, J., et al. (1993). Physician prescribing
decisions: The effects of situational involvement and task complexity on
information acquisition and decision making. Social Science and Medicine, 36
(11), 1473-1482.
Choi, S.C. & DeSarbo, W.S.
(1993). Game theory derivations of competitive strategies in
conjoint analysis. Marketing Letters, 4 (4), 337-348.
Chrzan, K. & Boeger, L. (1999,
May). Improving choice predictions with the cutoff-constrained aggregate
choice model. Paper presented at the Marketing Science Conference on
Reflection and Renewal, Syracuse, University School of Management.
Chrzan, K. & Fellermann, R.
(1997). A comparison of full- and partial-profile best/worst conjoint analsis. In
Sawtooth Software (Ed.), Proceedings of the Sawtooth Software Conference,
August 1997 (No. 6, pp. 59-67). Seattle, Washington: Sawtooth Software.
Chrzan,
K. & Grisaffe, D.B. (1992). A comparison of telephone conjoint
analysis with full profile conjoint analyses and adaptive conjoint analysis. In
M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp.
225-242). Sun Valley, ID: Sawtooth Software.
Chrzan, K. & Orme, B. (2000). An
overview and comparison of design strategies for choice-based conjoint analysis.
In Proceedings of the Sawtooth Software Conference (No. 8, pp. 161-177).
Sequim, WA: Sawtooth Software.
Chrzan,
K. & Skrapits, M. (1996). Best/worst conjoint analysis: An
empirical comparison with a full profile choice-based conjoint experiment.
Paper presented at the INFORMS Marketing Science Conference, Gainsville, FL.
Chrzan,
K. & Skrapits, M. (1997). Testing for IIA violations in
partial profile conjoint models. Paper presented at the
1997 INFORMS Marketing Science Conference, Berkeley, CA.
Chrzan, K. (1990, August). A
survey version of full-profile conjoint analysis. Paper presented at the
98th Annual Meeting of the American Psychological Association, Boston, MA.
Chrzan, K. (1991a). Unreliable
respondents in conjoint analysis: Their impact and identification. In M.
Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp.
205-228). Sun Valley, ID: Sawtooth Software.
Chrzan, K. (1991b). Comment on
Kopel and Kever. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference
Proceedings (pp. 155-156). Sun Valley, ID: Sawtooth Software.
Chrzan, K. (1992). Comment on
Huber, Wittink, Miller, and Johnson. In M. Metegrano (Ed.), 1992 Sawtooth
Software Conference Proceedings (pp. 283-284). Sun Valley, ID: Sawtooth
Software.
Chrzan, K. (1994). Three kinds of
order effects in choice-based conjoint analysis. Marketing Letters, 5
(2), 165-172.
Chrzan, K. (1998). Design
efficiency of partial profile choice experiments. Paper presented at the
1998 INFORMS Marketing Science Conference, Paris.
Chrzan, K. (1999). Full versus
partial profile choice experiments: Aggregate and disaggregate comparisons. In Proceedings
of the Sawtooth Software Conference (No. 7, pp. 235-248). Sequim, WA:
Sawtooth Software.
Chrzan, K. (2000, May). Testing
a psychological explanation of the number of levels problem in choice-based
conjoint analysis. Paper presented at the 2000 Advanced Research Techniques
Forum in Monterey, CA.
Chrzan, K., Bunch, D.S. &
Lockhart, D.C. (1996). Testing a multinomial extension to partial profile choice
experiments: Empirical comparisons to full profile experiments. Paper
presented at the INFORMS Marketing Science Conference, Gainsville, FL.
Churchill, G.A. (1995). Appendix
9B: Conjoint measurement. In Marketing research: Methodological foundations
(6th ed., pp. 505-523). Orlando, FL: The Dryden Press.
Churchill, G.A. Jr. (1987).
Appendix 8B: Conjoint measurement in chapter 8: Attitude measurement. In Marketing
research: Methodological foundations (4th ed., pp. 364-377). New York, NY:
The Dryden Press.
Churchill, G.A. Jr. (1988).
Conjoint measurement in part 4: Data-collection forms. In Basic marketing
research (pp. 358-361). Chicago, IL: The Dryden Press.
Churchill, G.A. Jr. (1991).
Appendix 9B: Conjoint measurement in chapter 8: Attitude measurement. In Marketing
research: Methodological foundations (5th ed., pp. 464-482). Chicago, IL:
The Dryden Press.
Clarke,
D.G. (1987). Marketing analysis and decision making.
Redwood City, CA: The Scientific Press.
Claxton, J.D. (1994). Conjoint
analysis in travel research: A manager’s guide. In Ritchie & Goeldner
(Eds.), Travel tourism, hospitality research: Handbook for managers and
researchers (2nd ed., pp. 513-522).
Cohen,
S.H. (1997). Perfect union: CBCA marries the best of conjoint and
discrete choice models. Marketing Research, 9 (1), 12-17.
Cohen, S.L., Dove, D.W. &
Bachelder, E.L. (2001). Time to Treat Learners as Consumers. Training &
Development, 55 (1), 54-57.
Colberg, R.T. (1977). Validation
of conjoint measurement methods: A simulation and empirical investigation. Unpublished
dissertation, University of Washington.
Colberg, R.T. (1978). A Monte
Carlo evaluation of metric recovery of conjoint measurement algorithms. In S.C.
Jain (Ed.), Research frontiers in marketing: Dialogues and directions
(No. 43, pp. 22-26). Chicago: American Marketing Association.
Collins-Dodd, C. & Huber, J.
(1998). Using uncorrelated conjoint designs in a world of correlated beliefs. Developments
in Marketing Science, 21, 486-487.
Conrad, T. (1997). Preisbildung mittels Conjoint-Analyse und eines Simulationsmodells am Beispiel eines Premiumanbieters der Automobilindustrie. Dissertation, Universität Tübingen.
Coombs,
C.H. & Lehner, P.E. (1980). The conjoint analysis of the
bilinear model, illustrated with a theory of risk. In I. Borg (Ed.), Multidimensional
data representations: When & why (pp. 565-589). Ann Arbor, MI: Mathesis
Press.
Cooper, L.G. (1989). A review of
multidimensional scaling in marketing research. In P.E. Green, F.J. Carmone
& S.M. Smith (Eds.), Part III: Literature review of multidimensional
scaling: Concepts and applications (pp. 140-168). Boston, MA:
Allyn and Bacon.
Corstjens, M.L. & Gautschi, D.A.
(1983). Conjoint analysis: A comparative analysis of
specification tests for the utility function. Management Science, 29
(12), 1393-1413.
Cosper, R. & Kinsley, B.L.
(1984). An application of conjoint analysis to leisure research: Cultural
preferences in Canada. Journal of Leisure Research, 16 (3), 224-233.
Cramer, J.S. (1991). The logit
model for economicists. New York, NY: Edward Arnold.
Crane, M. (1991). Conjoint
analysis: A guide for designing & interpreting conjoint studies. Austin,
Texas: IntelliQuest, Inc.
Crawford, G.A. (1994). A conjoint
analysis of reference services in academic libraries. College & Research
Libraries, 55 (3), 257-267.
Creyer, E. & Ross, W.T.
(1988). The effects of range-frequency manipulations on conjoint importance
weight stability. In Advances in consumer research (No. 15, pp.
505-509). Provo, UT: Association for Consumer Research.
Crown, E.M. & Brown, S.A.
(1984). Consumer trade-offs among flame retardance and other product
attributes: A conjoint analysis of consumer preferences. Journal of Consumer
Affairs, 18 (2), 305-316.
Currim, I. (1982). Predictive
testing of consumer choice models not subject to independence of irrelevant
alternatives. Journal of Marketing Research, 19, 208-222.
Currim, I.S., Weinberg, C.B. &
Wittink, D.R. (1981). The design of subscription programs for a performing arts
series. Journal of Consumer Research, 8, 67-75.
Curry, D. & Rodgers, W.
(1977). Aggregating responses in additive conjoint measurement. In W.D.
Perreault (Ed.), Advances in consumer research (Vol. 5, pp. 35-40). Provo,
UT: American Marketing Association.
Curry, J. (1992). Technology - a
blueprint for success. Marketing opportunities with advanced research
techniques. In Proceedings of the second SKIM Seminar (pp. 109-116). Rotterdam,
The Netherlands: SKIM Market and Policy Research.
Curry, J. (1997). After the
basics: Keeping key issues in mind makes conjoint analysis easier to apply. Marketing Research, 9 (1), 6-11.