W

Wachter, B. & Haupt, K. (1995). Kundenzufriedenheit erhöhen. Die qualitative Symbiose der Marktforschung und der Conjoint Analyse. Planung und Analyse, 22 (2), 51-52 und 69.

Wagner, J. (1990). Conjoint analysis and research on consumer preferences. In Book of Papers, American Association of Textile Chemists and Colorists, 1990 International Conference & Exhibition (pp. 387-412). Research Triangle Park, NC: American Association of Textil.

Walker, M. (1993). Cost-effective product development. Long Range Planning, 26, 64-66.

Walley, K., Parsons, S. & Bland, M. (1999). Quality assurance and the consumer: A conjoint study. British Food Journal, 101 (2), 148-161.

Wallsten, T.S. (1972). Conjoint-measurement framework for the study of probabilistic information processing. Psychological Review, 79 (3), 245-260.

Wallsten, T.S. (1976). Using conjoint-measurement models to investigate a theory about probabilistic information processing. Journal of Mathematical Psychology, 14 (2), 144-185.

Wallsten, T.S. (1977). Measurement and interpretation of beliefs: A review. In H. Jungermann & G. de Zeeuw (Eds.), Decision making and change in human affairs (pp. 369-393). Dordrecht.

Walsh, J. & Schmittlein, D. (1997). Using choice-based conjoint analysis for individual level predictions: An empirical investigation of choice set, choice task, and model estimation factors. Paper presented at the 1997 INFORMS Marketing Science Conference, Berkeley, CA.

Wang, D., Oppewal, H. & Timmermans, H. (2000). Pairwise conjoint analysis of activity engagement choice. Environment and Planning A, 32 (5), 805-816.

Wang, M.H. (1999). Factors influencing preferences for persons with disabilities: A conjoint analysis and cross-cultural comparison. Dissertation Abstracts International (Section B: The Sciences and Engineering), Vol 60(1-B), 0414.

Wangen, K.R. & Biørn, E. (2001). Prevalence and substitution effects in tobacco consumption: A discrete choice analysis of panel data. Discussion papers (No. 312), Statistics Norway, Research Department.

Wardman, M. (1988). A comparison of revealed preference and stated preference models. Journal of Transport Economics and Policy, 22, 71-91.

Weber, M., Eisenführ, F. & Winterfeldt, D.V. (1988). The effects of splitting attributes on weights in multiattribute utility measurement. Management Science, 34 (4), 431-445.

Wedel, M. & DeSarbo, W.S. (1994). A review of recent developments in latent class regression models. In R.P. Bagozzi (Ed.), Advanced methods of marketing research (pp. 352-388). Cambridge, MA: Blackwell Publishers Inc.

Wedel, M. & Kamakura, W. (1997). Market segmentation: Conceptual and methodological foundations. Boston: Kluwer.

Wedel, M. & Kistemaker, C. (1989). Consumer benefit segmentation using clusterwise linear regression. International Journal of Research in Marketing, 6, 45-59.

Wedel, M. & Steenkamp, J.-B.E.M. (1989). A fuzzy clusterwise regression approach to benefit segmentation. International Journal of Research in Marketing, 6, 241-258.

Wedel, M. & Steenkamp, J.-B.E.M. (1991). A clusterwise regression method for simultaneous fuzzy market structuring and benefit segmentation. Journal of Marketing Research, 28, 385-396.

Wedel, M., Vriens, M., Bijmolt, T., Krijnen, W. & Leeflang, P.S.H. (1998). Assessing the effects of abstract attributes and brand familiarity in conjoint choice experiments. International Journal of Research in Marketing, 15, 71-78.

Wedel, M., Vriens, M., Bijmolt, T.H.A. & Krijnen, W. (1995). CONFOLD: Simultaneous product optimization and brand positioning using conjoint choice methods. In EMAC Proceedings, Paris, May 1995 (pp. 2109-2115).

Weiber, R. & Rosendahl, T. (1996). Einsatzmöglichkeiten alternativer Untersuchungsansätze der Conjoint-Analyse. In A. von Ahsen & T. Czenskowsky (Hrsg.), Marketing und Marktforschung: Entwicklungen, Erweiterungen und Schnittstellen im nationalen und internationalen Kontext (S. 557-584). Hamburg: Lit.

Weiber, R. & Rosendahl, T. (1997). Anwendungsprobleme der Conjoint-Analyse. Marketing ZFP, 19, 107-118.

Weinberg, B.D. (1990). Role for research and models in improving new product development. Report of the Marketing Science Institute Conference (No. 90-120). Cambridge, Massachusetts.

Weiner, J. (1994). Consumer electronics marketer uses a conjoint approach to configure ist new product and set the right price. Marketing Research, 6 (3), 7-11.

Weiner, J.L. (1993). Alternative conjoint analysis techniques: Implications for marketing research (Doctoral dissertation, The University of Texas at Arlington). Dissertation Abstracts International, 54-08A, 3122.

Weiner, J.L. (1999). Using scanner data to validate choice model estimates. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 201-206). Sequim, WA: Sawtooth Software.

Weisenfeld, U. (1987). Signifikanztest für die Anpassungsgüte in Conjoint-Analysen. Marketing ZFP, 4, 267-270.

Weisenfeld, U. (1989). Die Einflüsse von Verfahrensvariationen und der Art des Kaufentscheidungsprozesses auf die Reliabilität der Ergebnisse bei der Conjoint Analyse. Berlin: Duncker & Humblot.

Weiss, P.A. (1992). Die Kompetenz von Systemanbietern: Ein neuer Ansatz im Marketing für Systemtechnologien. Berlin: Schmidt.

Weitz, B. & Wright, P. (1979). Retrospective self-insight on factors considered in product evaluation. Journal of Consumer research, 6, 280-294.

Westwood, D., Lunn, T. & Beazley, D. (1974). The trade-off model and its extensions. Journal of the Market Research Society, 16 (3), 227-241.

Wetzels, M., de Ruyter, K., Lemmink, J. & Koelemeijer, K. (1995). Measuring customer service quality in international marketing channels: A multimethod approach. Journal of Business & Industrial Marketing, 10 (5), 50-59.

Wheatley, K.L. & Flexner, W.A. (1987). Research tool changes the way marketers view data. Marketing News, 21 (5), 23-24.

Whiting, R. (2001). Virtual focus group. Informationweek, 848, 53-58.

Wie, S., Ruys, H. & Muller, T.E. (1999). A gap analysis of perceptions of hotel attributes by marketing managers and older people in Australia. Journal of Marketing Practice: Applied Marketing Science, 5 (6-8), 200-212.

Wiegand, S. (1993). Die Conjoint-Analyse als Instrument zur Nutzenmessung – Ergebnisse einer Befragung in den neuen Bundesländern. In Gesellschaft für Wirtschafts- und Sozialwissenschaften e.V. (Hrsg.), Strukturanpassung der Land- und Ernährungswirtschaft in Mittel- und Osteuropa (Bd. 29, S. 459-470). Münster:???.

Wigton, R.S., Hoellerich, V.L. & Patil, K.D. (1988). How physicians use clinical information in diagnostic pulmonary embolism: An application of conjoint analysis. In J. Dowie & A. Elstein (Eds.), Professional judgment. A reader in clinical decision making (pp. 130-149). Cambridge: University Press.

Wilcox, R.T. (1999). Efficient fee structures for mutual funds. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 71-98). Sequim, WA: Sawtooth Software.

Wilensky, L. & Buttle, F. (1988). A multivariate analysis of hotel benefit bundles and choice trade-offs. International Journal of Hospitality Management, 7 (1), 29-41.

Wiley, J.B. & Low, J.T. (1983). A monté carlo simulation study of two approaches for aggregating conjoint data. Journal of Marketing Research, 20, 405-416.

Wiley, J.B. & Wyner, J.L. (1979). A generalized logit model to aggregate conjoint data. In N. Beckwith, M. Houston, R. Mittelstaedt, K.B. Monroe & S. Ward (Eds.), 1979 AMA Educators’ Proceedings (Series No. 44, pp. 78-82). Chicago, IL: American Marketing Association.

Wiley, J.B. (1978). Selecting pareto optimal subsets from multi-attribute alternatives. In K. Hunt (ed.), Advances in Consumer Research (No. 5, pp. 171-174). Chicago, IL: Association for Consumer Research.

Wiley, J.B. (1993). A strategy for a priori segmentation in conjoint analysis. In L. McAlister & M.L. Rothschild (Eds.), Advances in consumer research (No. 20, pp. 142-148). Provo, UT: Association for Consumer Research.

Wiley, J.B. (2001). Experimental designs in choice experiments. In Recent advances in design of experiments and related areas. Nova Science Publishers.

Wiley, J.B., MacLachlan, D.L. & Moinpour, R. (1977). Comparison of stated and inferred parameter values in additive models: An illustration of a paradigm. In W.D. Perreault Jr. (Ed.), Advances in consumer research (No. 4, pp. 98-105). Atlanta: Association for Consumer Research.

Wiley, J.B., Moinpour, R. & MacLachlan, D. (1984). A strategy for reducing and analysing ordered choice data. Journal of Multivariate Behavioral Research, 1984, 421-436.

Wilkie, W.L. & Pessemier, E.A. (1973). Issues in marketing`s use of multi-attribute attitude models. Journal of Marketing Research, 10, 428-441.

Williams, M. (1991). CONSURV: Conjoint analysis software. Edmonton, Canada: Intelligent Marketing Systems.

Williams, P. & Kilroy, D. (2000). Calibrating price in ACA: The ACA price effect and how to manage it. In Proceedings of the Sawtooth Software Conference (No. 8, pp. 81-95). Sequim, WA: Sawtooth Software.

Wilson, C. (1991). How market modelling can cut strategic decision risks. Business Marketing Digest, 16 (4), 71-80.

Wilson, T.C. & Harris, B.F. (1977). The application of additive conjoint analysis in marketing research: Assumptions, advantages, and limitations. In B.A. Greenberg & D.N. Bellenger (Eds.), 1977 AMA Educators’ Proceedings: Contemporary Marketing Thought (Series No. 41, pp. 86-89). Chicago, IL: American Marketing Association.

Wiltinger, K. (1997). Personalmarketing auf der Basis von Conjoint Analysen. Zeitschrift für Betriebswirtschaft, Ergänzungsheft (3), 55-78.

Wind, J. & Mahajan, V. (1990). In supporting and improving the new product development process: Some preliminary results. In B.D. Weinberg, Roles for research and models in improving new product development. Marketing Science Institute Conference, May 21 and 22, 1990 (Report No. 90-120, pp. 2-19). Cambridge, MA: Marketing Science Institute.

Wind, Y, Green, P.E., Shifflet, D. & Scarbrough, M. (1989). Courtyard by Marriott: Designing a hotel facility with consumer-based marketing models. Interface, 19 (1), 25-47.

Wind, Y. & Robinson, P.J. (1972). Product positioning: An application of multidimensional scaling. In R.I. Haley (Ed.), Attitude research in transition. Marketing research techniques (No. 15., pp. 155-175). American Marketing Association.

Wind, Y. (1976). Preference for relevant others and individual choice models. Journal of Consumer Research, 3, 50-57.

Wind, Y. (1977). Brand choice. In National Science Foundation (Ed.), Selected aspects of consumer behavior: A summary from the perspective of different disciplines (pp. 239-258). Washington DC: Directorate for Research Applications, RANN - Research Applied to National Needs.

Wind, Y., Green, P.E. & Robinson, P.J. (1968). The determinants of vendor selection: The evaluation function approach. Journal of Purchasing, 4, 29-41.

Wind, Y.J. (1990). Positioning analysis and strategy. In G. Day, B. Weitz & R. Wensley (Eds.), The interface of marketing and strategy (pp. 387-412). Greenwich, CT: JAI Press.

Winzar, H.F. & Duncan, K. (1992, November). Dichotomous responses in conjoint analysis. Paper presented at the Proceedings of the Sixth New Zealand Marketing Educators' Conference, University of Otago, Dunedin.

Winzar, H.F. & Johnson, L.W. (1991, December). Testing convergent validity of self-explicated and conjoint measures of multiattribute utility. Paper presented at the Australian New Zealand Association of Management Educators' (ANZAME) conference, Bond University.

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

Winzar, H.F. & Johnson, L.W. (1994, March). Evaluation of conjoint preference simulators. Paper presented at the TIMS Marketing Science Conference, Karl Eller Graduate School of Management, University of Arizona, Tucson, Arizona.

Winzar, H.F. & Johnson, L.W. (1995, July). Incorporating individual differences in a multinomial probit conjoint preferences simulator. Paper presented at the INFORMS Marketing Science Conference, Australian Graduate School of Management, Sydney.

Winzar, H.F. & Johnson, L.W. (1996). A variance based preference rule for conjoint analysis market share prediction. In C. Riquier & B. Sharp (Eds.), Proceedings of the 1996 Australian Marketing Educators' Conference: Southern Marketing: Theory and applications (No. 2, pp. 673-675). Adelaide: Marketing Science Centre, University of South Australia.

Winzar, H.F. (1992a). Addressing some puzzles in conjoint analysis. Australian Marketing Researcher, 14 (1), 54-67.

Winzar, H.F. (1992b, August). Testing predictive validity of conjoint choice simulators: Building a model. Paper presented at the PhD Colloquium, Murdoch University.

Winzar, H.F. (1992c, November). Testing predictive validity of conjoint choice simulators: measurement issues. Paper presented at the ANZDOC 92: the Australian and New Zealand Marketing Doctoral Consortium, University of Otago, New Zealand.

Winzar, H.F. (1993a). Predictive validity of conjoint choice simulators: A research design (Commerce School Seminar Series). Murdoch University.

Winzar, H.F. (1993b). Validity issues in conjoint choice simulators (Marketing Seminar Series). Australian Graduate School of Management, University of New South Wales.

Winzar, H.F. (1994a). A monte carlo evaluation of conjoint preference simulators. Unpublished Ph.D. thesis, Graduate School of Business, The University of Sydney.

Winzar, H.F. (1994b). Testing assumptions and predictive validity of hybrid conjoint analysis. Unpublished Master's Thesis, Bond University.

Winzar, H.F., Pidcock, P. & Johnson, L. (1993). Modelling long distance preasure travel mode using perceived modal attributes. Journal Travel & Tourism Marketing, 2 (1), 53-67.

Winzar, H.F., Pidcock, P.J. & Karunaratna, A. (1991). Construct validity of conjoint analysis and self explicated measures of consumer utility. Paper presented at the Marketing Educators' Conference, Adelaide.

Wirth, U. (1996). Kundenorientierte Produktgestaltung mittels Conjoint-Measurement: Neuproduktplanung bei Mercedes-Benz. In H.H. Bauer, E. Dichtl & A. Herrmann (Hrsg.), Automobilmarktforschung. Nutzenorientierung von PKW-Herstellern (S. 53-66). München: Vahlen.

Witt, K.J. (1992). Comment on Gates and Foytik. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 189-190). Ketchum, ID: Sawtooth Software.

Wittink, D. (2000). Predictive validation of conjoint analysis. In Proceedings of the Sawtooth Software Conference (No. 8, pp. 221-237). Sequim, WA: Sawtooth Software.

Wittink, D.R. & Cattin, P. (1981). Alternative estimation methods for conjoint analysis: A Monte Carlo study. Journal of Marketing Research, 18, 101-106.

Wittink, D.R. & Cattin, P. (1989). Commercial use of conjoint analysis: An update. Journal of Marketing, 53, 91-96.

Wittink, D.R. & Keil, S.K. (2000). Continuous conjoint analysis. In A. Gustafsson, A. Herrmann & F. Huber (Eds.), Conjoint measurement - methods and applications (pp. 411-434). Berlin: Springer.

Wittink, D.R. & Montgomery, D.T. (1979). Predictive validity of trade-off analysis for alternative segmentation schemes. In N. Beckwith, M. Houston, R. Mittelstaedt, K.B. Monroe & S. Ward (Eds.), 1979 Educators' Conference Proceedings (series 44, pp. 69-73). Chicago, IL: American Marketing Association.

Wittink, D.R. & Seetharaman, P.B. (1999). A comparison of alternative solutions to the number-of-levels effect. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 269-282). Sequim, WA: Sawtooth Software.

Wittink, D.R. & Walsh, J.W. (1988). Conjoint analysis: Its reliability, validity, and usefulness. In R.M. Johnson (Ed.), Proceedings of the Sawtooth Software Conference of Perceptual Mapping, Conjoint Analysis, and Computer Interviewing (No. 2, pp. 1-23). Ketchum, ID: Sawtooth Software.

Wittink, D.R. (1989). New book in review: Analyzing decision making - metric conjoint analysis. Journal of Marketing Research, 26, 244-253.

Wittink, D.R. (1991a). Comment on Green, Schaffer, and Patterson. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 315-323). Ketchum, ID: Sawtooth Software.

Wittink, D.R. (1991b). Attribute level effects in conjoint results: The problem and possible solutions. In W.D. Neal (Ed.), First Annual Advanced Research Techniques Forum, June 24-27, 1990, Beaver Creek, Colorado (pp. 43-54). Chicago, IL: American Marketing Association.

Wittink, D.R. (1992). Comment on Lewin, Jeuland, and Struhl. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 271-274). Ketchum, ID: Sawtooth Software.

Wittink, D.R. (1999). Comment on McCullough. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 117-121). Sequim, WA: Sawtooth Software.

Wittink, D.R., Huber, J., Fiedler, J.A. & Miller, R. (1993a). Design effects in conjoint analysis. Working paper, Graduate School of Management, Cornell University at Ithaca, NY.

Wittink, D.R., Huber, J., Fiedler, J.A. & Miller, R. (1993b). The magnitude of and explanation / solution for the number of levels effect in conjoint analysis. International Journal of Research in Marketing, 30, ???.

Wittink, D.R., Huber, J., Zandan, P. & Johnson, R.M. (1992). The number of levels effect in conjoint: Where does it come from, and can it be eliminated? In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 355-364). Ketchum, ID: Sawtooth Software.

Wittink, D.R., Krishnamurthi, L. & Nutter, J.B. (1982). Comparing derived importance weights across attributes. Journal of Consumer Research, 8, 471-474.

Wittink, D.R., Krishnamurthi, L. & Reibstein, D.J. (1989). The effect of differences in the number of attribute levels on conjoint results. Marketing Letters, 1, 113-123.

Wittink, D.R., McLauchlan, B. & Seetharaman, P.B. (1997). Solving the number of attribute levels problem in conjoint. In Proceedings of the Sawtooth Software Conference (No. 6). Seattle, WA: Sawtooth Software.

Wittink, D.R., Vriens, M. & Burhenne, W. (1994). Commercial use of conjoint analysis in europe: Results and critical reflections. International Journal of Research in Marketing, 11, 41-52.

Wittink,D.R. & Walsh, J.W. (1988). Conjoint analysis: Its reliability, validity, and usefulness. In R.M. Johnson (Ed.), Proceedings of Sawtooth Software Conference on Perceptual Mapping, Conjoint Analysis, and Computer Interviewing (No. 2, pp. 1-25). Ketchum, ID: Sawtooth Software.

Woehler, K. (1996). Präferenzen und Prädiktoren für umweltschonendes Verhalten von Urlaubern. Gruppendynamik, 27 (1), 21-32.

Wollerman, P. (1999). Predicting product registration card response rates with conjoint analysis. In Proceedings of the Sawtooth Software Conference (No. 7, pp. 131-144). Sequim, WA: Sawtooth Software.

Woodside, A. & Pearce, W.G. (1989). Testing market segment acceptance of new designs of industrial services. Journal of Product Innovation Management, 6, 185-201.

Woodside, A.G. & Carr, J.A. (1988). Consumer decision making and competitive marketing strategies: Applications for tourism planning. Journal of Travel Research, 2-7.

Woodside, A.G., Luikko, T. & Vuori, R. (1999). Organizational buying of capital equipment involving persons across several authority levels. Journal of Business & Industrial Marketing, 14 (1), 30-49.

Woratschek, H. (2000). Conjoint Measurement - ein Verfahren zur nachfrageorientierten Preisbestimmung. In M.P. Büch (Hrsg.), Märkte und Organisationen im Sport: Institutionenökonomische Ansätze (S. 77-101). Schorndorf: Hofmann.

Wright, P. & Kriewall, M.A. (1980). State-of-mind effects on the accuracy with which utility functions predict marketplace choice. Journal of Marketing Research, 17, 277-293.

Wu, C. & Wu, S.I. (1999). A proposed method for the design of consumer products. Journal of International Marketing and Marketing Research, 24 (1), 23-33.

Wuebker, G. & Mahajan, V. (1999). A conjoint analysis-based procedure to measure reservation price and to optimally price product bundles. In R. Fuerderer, A. Herrmann & G. Wuebker (eds.), Optimal bundling - marketing strategies for improving economic performance (pp. 157-176). Berlin: Springer.

Wyner, G.A. (1992). Uses and limitations of conjoint analysis - Part I. Marketing Research, June, 42-44.

Wyner, G.A. (1992). Uses and limitations of conjoint analysis - Part II. Marketing Research, September, 64-47.

Wyner, G.A. (1995). Trade-off techniques and marketing issues. Marketing Research, 7 (4), 32-34.

Wyner, G.A., Benedetti, L.H. & Trapp, B.M. (1984). Measuring the quantity and mix of product demand. Journal of Marketing, 48, 101-109.

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