S
Sadler, T.R. (2001). Environmental
Taxation in an Optimal Tax Framework. Atlantic Economic Journal, 29 (2),
215-231.
Safizadeh, M.H. (1989). The
internal validity of the trade-off method of conjoint analysis. Decision
Sciences, 20, 451-461.
Salling, S.W. & Deegan, J.
(1991). Using conjoint information: Organizational factors. In M. Metegrano
(Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 163-174). Ketchum,
ID: Sawtooth Software.
Saltzman, A. & MacElroy, W.H.
(1999). Disk-based mail surveys: A longitudinal study of practices and
results. Paper presented at the 7th Sawtooth Software Conference, San
Diego, CA.
San Miguel, F., Ryan, M. &
McIntosh, E. (1997). Methodological issues in the use
of conjoint analysis in health care: An application to women’s preferences for
the treatment of menorrhagia (HERU discussion paper No.
06/97). Aberdeen: University.
San Miguel, F., Ryan, M. &
McIntosh, E. (2000). Applying conjoint analysis in
economic evaluations: An application to menorrhagia. Applied Economics, 32
(7), 823-833.
Sanchez, M. & Gil, J.M. (1998). Consumer
Preferences for wine attributes in different retail stores: A conjoint
approach. International Journal of Wine Marketing, 10 (1), 25-38.
Sanchez, R. & Sudharshan, D.
(1993). Real-time market research. Marketing Intelligence
& Planning, 11 (7), 29-38.
Sandor, Z. & Wedel, M. (1999,
May). Optimal mixed logit designs for conjoint choice experiments. Paper
presented at the Marketing Science Conference on Reflection and Renewal,
Syracuse, University School of Management.
Sands, S. & Warwick, K.
(1981). What product benefits to offer to whom: An application of conjoint
segmentation. California Management Review, 24, 69-74.
Sandvik-Wiklund,
P. & Wiklund, H. (1999). Student focused design and
improvement of university courses. Managing Service Quality, 9 (6),
434-443.
SAS Institute, Inc. (1993). SAS
technical report R-109: Conjoint analysis examples. Cary, NC: SAS
Institute.
Sattler,
H. & Hensel-Börner, S. (1999). A comparison of conjoint
measurement with self-explicated approaches
(Diskussionspapier Reihe A, Nr. 99/07). Jena: Universität, Wirtschaftswissenschaftliche Fakultät.
zugleich: Sattler, H. & Hensel-Börner, S. (2000). A
comparison of conjoint measurement and self-explicated approaches. In A.
Gustafsson & A. Herrmann (Hrsg.), Conjoint measurement: Methods and
applications (pp. 121-134). Berlin: Springer.
Sattler,
H. (1991). Herkunfts- und Gütezeichen im Kaufentscheidungsprozeß.
Stuttgart: M&P.
Sattler,
H. (1994). Die Validität von Produkttests. Ein empirischer Vergleich zwischen
hypothetischer und realer Produktpräsentation. Marketing
ZFP, 16 (1), 31-41.
Sattler, H. (1999). Ein Indikatorenmodell zur
langfristigen monetären Markenwertbestimmung (Teil 1). Die
Betriebswirtschaft, 59 (5), 633-653.
Sattler,
H., Hensel-Börner, S. & Krüger, B. (2001). Die Abhängigkeit der Validität
von Conjoint-Studien von demographischen Probandencharakteristika: Neue
empirische Befunde. Zeitschrift für Betriebswirtschaft, 71 (7), 771-787.
Saunders,
J. & Guoqun, F. (1996). Dual branding: How corporate names
add value. Marketing Intelligence & Planning, 14 (7), 29-34.
Sawtooth Software (1985). Adaptive
conjoint analysis: User's manual. Ketchum, ID: Sawtooth Software.
Sawtooth Software (1991). CVA
system: Conjoint value analysis. Evanston, IL: Sawtooth Software.
Sawtooth Software (1993). ACA
system: Adaptive conjoint analysis, version 4.0. Evanston, IL: Sawtooth
Software.
Sawtooth Software (1993). CBC
system: The CBC system for choice-based conjoint analysis. Evanston, IL:
Sawtooth Software.
Sawtooth Software (Summer 1994). Consumer
pulse creates mixed-media conjoint interview. In S. Weiss (Ed.), Sawtooth
News (No. 10 (1), p. 6). Ketchum, ID: Sawtooth Software.
Sawtooth Software (Summer 1994). Different
conjoint methods can produce different price information. In S. Weiss (Ed.), Sawtooth
News (No. 10 (1), p. 6). Ketchum, ID: Sawtooth Software.
Sawtooth Software (Summer 1994). Practical
improvements in perceptual mapping and conjoint analysis reported at marketing
science conference. In S. Weiss (Ed.), Sawtooth News (No. 10 (1), p. 3).
Ketchum, ID: Sawtooth Software.
Sawtooth Software (Winter
1994/1995). Discrete choice modeling merits serious investigation. In S. Weiss
(Ed.), Sawtooth News (No. 10 (2), p. 4). Ketchum, ID: Sawtooth Software.
Schaffer,
C.M. & Green, P.E. (1998). Cluster-based market segmentation:
Some further comparisons of alternative approaches. Journal of the Market
Research Society, 40 (2), 155-163.
Schaffer,
C.M. (1990). Importance weight sensitivity in the hybrid conjoint
model. In B.J. Dunlap (Ed.), Developments in marketing science. Proceedings
of the thirteenth annual conference of the Academy of Marketing Science
(Vol. 13, pp. 390-394). Cullowhee, NC: Academy of Marketing Science.
Schaffer,
C.M. (1991). Comment on Hase. In M. Metegrano (Ed.), 1991
Sawtooth Software Conference Proceedings (pp. 249-250). Ketchum, ID:
Sawtooth Software.
Scharf, A., Schubert, B. & Volkmer, H.-P. (1996). Conjointanalyse und Multimedia. Überprüfung von Produktkonzepten für neue Nahrungs- und Genußmittel mittels multimedialer adaptiver Conjointanalyse. Planung und Analyse, 23 (6), 26-31.
Scheer,
H.R. van der, Hoekstra, J.C. & Vriens, M. (1996). Using
"opt out" reply cards in direct mail optimal design, target
selection, and profit implications. Journal of Direct Marketing, 10 (3),
18-27.
Scheer,
M., Orth, U. & Oppenheim, P. (1999). Anwendung der Conjoint-Analyse zur
Vorbereitung eines internationalen Markteintritts. Agrarwirtschaft, 48
(5), 194-201.
Schellhase,
R. & Franken, B. (1997). Die Conjoint-Analyse als Instrument des
Marketing-Controlling. Der Markt, 36 (2), 75-83.
Schewe, G. & Dreesen, A. (1994). Die externe Rekrutierung des kaufmännischen Führungskräfte-Nachwuchses. Ergebnisse einer empirischen Untersuchung. Zeitschrift für Führung + Organisation, 6, 381-387.
Schifferstein,
H.N.J., Verlegh, P.W.J. & Wittink, D.R. (1998). Range and
number-of-levels effects in derived and stated attribute importances.
Working paper, Yale School of Management.
Schleusener,
M. (2001). Ermittlung von Preisbereitschaften im
Verkehrsdienstleistungsbereich – dargestellt am Beispiel der Deutschen Bahn AG.
Arbeitspapier (Nr. 149), Wissenschaftliche Gesellschaft für Marketing und
Unternehmensführung.
Schlossberg, H. (1991). Conjoint
vs. SCA: Choose your model and come out testing. Marketing News, 25 (2),
6.
Schmidhofer, M. (1996). Verbraucherpräferenzen bei
Kindermilchprodukten - Ergebnisse einer Conjoint-Analyse. In Wissenschaftlicher
Jahresbericht über die Tätigkeit des Forschungszentrums für Milch und
Lebensmittel (Bd. 38, S. 58-61).
Schmidt, M. (1987). An empirical
evaluation of some aggregation techniques and estimation algorithms in conjoint
analysis. In ESOMAR Symposium on Mikro and Macro Market Modeling (pp.
135-156). ESOMAR.
Schmidt,
M. (1990). Conjoint analysis: How sensitive are parameter
estimates with regard to syntactical variations in the wording of attribute
levels? – Empirical evidence from an experimental design study. In American
Marketing Association Educators´ Proceedings (pp. 270-275). Chicago,
Ill: American Marketing Association.
Schmidt-Gallas, D. (1998). Nachfrageorientierte
Produktgestaltung auf Investitionsgütermärkten. Wiesbaden: Deutscher
Univ.-Verlag.
Schmitz,
P.M. & Wiegand, S. (1991). Die zukünftige Entwicklung der Landwirtschaft
in den fünf neuen Bundesländern. Kiel: Wissenschafts-Verlag Vauk.
Schmutte, A.M. (1997). Conjoint Analyse zur simultanen Ermittlung von Patientenpräferenzen im Krankenhaus. Diskussionspapier 7/97, Universität der Bundeswehr München. Verfügbar unter: http://www.unibw-muenchen.de/campus/WOW/v1072/Personen/Schmutte/Pub/Diskpap7_97/Diskpap7_97.htm, 12.10.98.
Schneider, C. (1997). Präferenzbildung bei Qualitätsunsicherheit: Das Beispiel Wein. Berlin: Duncker & Humblodt.
Schneider,
D. (1998). Produktoptimierung und zielorientierte Kostengestaltung mit Conjoint
Measurement. Zeitschrift für Unternehmensentwicklung und Industrial
Engineering, 47 (1), 24-27.
Schneider,
W. & Kornmeier, M. (1996). Die Entscheidungsbereitschaft von Studierenden
der Wirtschaftswissenschaften aus den Neuen Bundesländern. In K. Schweickart
(Hrsg.), Systemtransformation in Osteuropa: Herausforderungen an Unternehmen
beim Übergang von der Planwirtschaft in die Marktwirtschaft (S. 65-83).
Stuttgart: Schäffer-Poeschel.
Schnore, H.J. & Prosperi, D.C.
(1978). A conjoint measurement model of consumer spatial
behavior. Regional Science Perspectives, 8, 122-134.
Schopp,
M. (1995). Verbraucherpräferenz für verschiedene Trinkmilch-Verpackungssysteme.
In Wissenschaftlicher Jahresbericht über die Tätigkeit des
Forschungszentrums für Milch und Lebensmittel (Bd. 37, S. 55-58).
Schori, T.R. & Meadow, H.L. (1987). Conjoint analysis vs preference analysis: A comparison. Psychological Reports, 60 (3 (2)), 1063-1068.
Schrader,
S. (1990). Zwischenbetrieblicher Informationstransfer: eine empirische
Analyse kooperativen Verhaltens. Berlin: Duncker & Humblodt.
Schrieder,
G. & Heidhues, F. (1991). Conjoint analysis and its
predictive power for financial market development: A methodological framework. In
C. Cuevas & M. Benoit-Cattin (Eds.), Finance and rural development in
West Africa. Ouagadougou: OSU, CIRAD, CEDRES, INERA, CNCA.
Schubert, B. & Wenk, T.
(1992). Vom
Pauschalurteil zur Einzelanalyse. Touristik-Management, 71-74.
Schubert,
B. & Wolf, A. (1993). Erlebnisorientierte Produktgestaltung. In U. Arnold
& K. Eierhoff (Hrsg.), Marketingfocus: Produktmanagement (S.
121-151). Stuttgart: Schäffer-Poeschel.
Schubert, B. (1991). Entwicklung von Konzepten für Produktinnovationen mittels Conjointanalyse. Stuttgart: Poeschel.
Schuler,
H.J. (1981). Grocery shopping choices: Individual preferences based
on store attractiveness and distance. Environment and Behavior, 13 (3),
331-347.
Schwalba,
M. (2000). Die wettbewerbsbezogene Abgrenzung des relevanten Marktes.
Frankfurt am Main u.a.: Lang.
Schwan, I. (1996). Conjoint-Analyse im Bankensektor. Die Bank, 36 (4), 236-239.
Schweiger,
G., Friederes, G. & Strebinger, A. (1995). Produktionsverlagerung bei
Markenartikeln aus Sicht des Konsumenten. In D. Baier & R. Decker (Hrsg.), Marketingprobleme:
innovative Lösungsansätze aus Forschung und Praxis (S. 187-196).
Regensburg: Roderer.
Schweikl, H. (1985). Computergestützte Präferenzanalyse mit individuell wichtigen Produktmerkmalen. Berlin: Duncker & Humblot.
Scott, J.E. & Wright, P.
(1976). Modeling an organizational buyer`s product evaluation strategy:
Validity and procedural considerations. Journal of Marketing Research, 13,
211-224.
Sebastian, K.-H. & Hilleke, K.
(1991). Welche
Qualität kann sich Ihr Unternehmen leisten? Absatzwirtschaft, 34 (Okt.),
180-186.
Segal,
M.N. (1982). Reliability of conjoint analysis: Contrasting data
collection procedures. Journal of Marketing Research, 19, 139-143.
Segal, R. (1995). Forecasting the
market for electric vehicles in California using conjoint analysis. Energy
Journal, 16 (3), 89-111.
Sentis, K. & Li, L. (2000). HB
plugging and chugging: How much is enough? In Proceedings of the Sawtooth
Software Conference (No. 8, pp. 207-219). Sequim, WA: Sawtooth Software.
Shamir, M. & Shamir, J.
(1995). Competing values in public opinion: A conjoint analysis. Political
Behavior, 17 (1), 107-133.
Sheldon, R.J. & Steer, J.K.
(1982). The use of conjoint analysis in transport research. Planning and
Transport Research and Computation, 145-158.
Shepherd, D.A. (1999). Venture
capitalists´ introspection: A comparison of ‚in use‘ and ‚espoused‘ decision
policies. Journal of Small Business Management, 37 (2), 76-87.
Shepherd, D.A. (1999). Venture
capitalists‘ assessment of new venture survival. Management Science, 45
(5), 621-632.
Sheth, J.N., Newman, B.I. &
Gross, B.L. (1991). Chapter 2: Consumption values and market choices. Chapter
3: Functional and social values. In Consumption values and market choices:
Theory and applications (pp. 16-49). Cincinnati, OH: South-Western Publishing
Co.
Sheth, J.N., Newman, B.I. &
Gross, B.L. (1991). Why we buy what we buy: A theory of consumption values. Journal
of Business Research, 22, 159-170.
Shi, L. & Olafsson, S. &
Chen, Q. (1999). A new hybrid optimization algorithm. Computers and
Industrial Engineering, 36 (2), 409-426.
Shi, L., Olafsson, S. & Chen,
Q. (2001). An optimization framework for product design. Management Science,
47 (12), 1681-1692.
Shiell, A., Seymour, J., Hawe, P.
& Cameron, S. (2000). Are preferences over health states complete? Health
Economics, 9 (1), 47-55.
Shocker, A.D. & Srinivasan, V.
(1979). Multiattribute approaches for product concept evaluation and
generation: A critical review. Journal of Marketing Research, 16,
159-180.
Silk, A.J. (1973). Preference and
perception measures in new product development. In H.H. Kassarjian & T.S.
Robertson (Eds.), Perspectives in consumer behavior, revised (pp.
42-55). Glenview, IL: Scott, Foreman and Company.
Simmons, S. & Esser, M. (2000). Developing
business solutions from conjoint analysis. In A. Gustafsson, A. Herrmann &
F. Huber (Eds.), Conjoint measurement - methods and applications (pp.
67-96). Berlin:
Springer.
Simon,
H. (1992). Pricing the ‘tiger’ with conjoint measurement. Pricing
opportunities – and how to exploit them. Sloan Management Review, 33,
55-65.
Simon, H. (1993). High-Tech und Kundennutzen. In T.
Reichmann (Ed.), Tagungsband Controlling `93 (S. 543-557). München:
Techno-Verlag.
Singh,
J., Cuttler, L., Shin, M., Silvers, J.B. & Neuhauser, D. (1998). Medical
decision-making and the patient: Understanding preference patterns for growth
hormone therapy using conjoint analysis. Medical Care, 36 (8),
AS31-AS45.
Singh, M.J. & Kingsley, S.
(1999). Matching candidates with job openings using web-based adaptive
conjoint. In Proceedings of the Sawtooth Software Conference (No. 7, pp.
123-130). Sequim, WA: Sawtooth Software.
Siqueira, J. (1995). Mensuração
da estrutura de preferência do consumidor: uma aplicação de Conjoint Analysis
em Marketing. Dissertação (Mestrado) apresentada à Faculdade de Economia,
Administração e Contabilidade da Universidade de São Paulo.
Smallwood, D.R. (1991a). Using
conjoint analysis for price optimization. In M. Metegrano (Ed.), 1991
Sawtooth Software Conference Proceedings (pp. 157-162). Ketchum, ID:
Sawtooth Software.
Smallwood, D.R. (1991b). Comment
on Huber and Fiedler. In M. Metegrano (Ed.), 1991 Sawtooth Software
Conference Proceedings (pp. 203-204). Ketchum, ID: Sawtooth Software.
Smith, S.L. (1989). Conjoint
measurement. In Tourism analysis: A handbook (pp. 82-94). New York: John
Wiley & Sons, Inc.
Smith, S.M. (1988). Statistical
software for conjoint analysis. In R.M. Johnson (Ed.), Proceedings of the
Sawtooth Software Conference of Perceptual Mapping, Conjoint Analysis, and
Computer Interviewing (No. 2, pp. 109-115). Ketchum, ID: Sawtooth Software.
Smith, S.M. (1991). Simulating
market choice in conjoint analysis. In W.D. Neal (Ed.), First Annual
Advanced Research Techniques Forum, June 24-27, 1990, Beaver Creek, Colorado
(pp. 22-31). Chicago, IL: American Marketing Association.
Smith,
V.K. & Desvousges, W.H. (1986). Measuring
water quality benefits. Norwell, MA: Kluwer-Nijhoff.
Spoth, R. & Redmond, C.
(1993). Identifying program preferences through conjoint analysis: Illustrative
results from a parent sample. American Journal of Health Promotion, 8
(2), 124-133.
Spoth, R. (1989). Applying conjoint
analysis of consumer preferences to the development of utility-responsive
health promotion programs. Special Issue: Cancer control. Health Education
Research, 4, 439-449.
Spoth, R. (1990). Multi-attribute
analysis of benefit managers' preferences for smoking cessation programs. Health
Values, Health Behavior, Education and Promotion, 14 (5), 3-15.
SPSS (1998). SPSS conjoint 8.0.
Chicago, IL: SPSS Inc.
Srinivasan, V. & deMaCarty, P.
(1998). An alternative approach to the predictive validation of conjoint
models. Working paper, Stanford University, CA.
Srinivasan, V. & Park, C.S.
(1997). Surprising robustness of the self explicated approach to customer
preference structure measurement. Journal of Marketing Research, 34
(May), 286-291.
Srinivasan, V. & Shocker, A.D. (1973). Estimating the weights for multiple attributes in a composite criterion using pairwise judgments. Psychometrika, 38, 473-493.
Srinivasan, V. & Shocker, A.D. (1973). Linear programming techniques for multi-dimensional analysis of preferences. Psychometrika, 38, 337-369.
Srinivasan, V. & Shocker, A.D. (1981). LINMAP version-IV - Users manual. Nashville, TN: Vanderbilt University.
Srinivasan,
V. & Weir, H. (1992). A conjoint analysis-based approach
for determining benefit segments. June 1992 Advanced
Research Techniques Forum, Lake Tahoe, NV.
Srinivasan, V. (1980). Comments on
conjoint analysis and quantal choice models. Journal of Business, 53
(July), 547-550.
Srinivasan, V. (1988). A
conjunctive-compensatory approach to the self-explication of multiattributed
preferences. Decision Sciences, 19, 295-305.
Srinivasan, V. (1998). A strict
paired comparison linear programming approach to nonmetric conjoint analysis. In
J.E. Aronson & S. Zionts (Eds.), Operations research: Methods, models
and applications (pp. 97-111). Westport, CT: Quorum Books.
Srinivasan, V., Flaschsbart, P.G.,
Dajani, J.S. & Hartley, R.G. (1981). Forecasting the effectiveness of
work-trip gasoline conservation policies through conjoint analysis. Journal
of Marketing, 45 (Summer), 157-172.
Srinivasan, V., Jain, A.K. &
Malhotra, N.K. (1983). Improving predictive power of conjoint analysis by
constrained parameter estimation. Journal of Marketing Research, 20,
433-438.
Srinivasan,
V., Wyner, G.A. (1989). CASEMAP: Computer-assisted
self-explication of multiattributed preferences. In W. Henry, M. Menasco &
H. Takada (Eds.), New product development and testing (pp. 91-111). Lexington,
Mass.: Lexington Books.
Stadie,
E. (1998). Medial gestützte Limit Conjoint-Analyse als Innovationstest für
technologische Basisinnovationen: eine explorative Analyse. Münster: Lit.
Stadtler,
K. (1990). Conjoint Measurement. Marktforschungsreport, 13 (2), 3-9.
Stahl, B. (1988). Conjoint
analysis by telephone. In R.M. Johnson (Ed.), Proceedings of the Sawtooth
Software Conference (No. 2, pp. 131-138). Ketchum, ID: Sawtooth Software.
Stallmeier, C.W. (1993). Die Bedeutung der Datenerhebungsmethode und des Untersuchungsdesigns für die Ergebnisstabilität der Conjoint-Analyse. Regensburg: Roderer.
Stanford,
K., Hobbs, J.E., Gilbert, M., Jones, S.D.M., Price, M.A., Klein, K.K. &
Kerr, W.A. (1999). Lamb-buying preferences of Canadian abattoirs
and producer marketing groups: Implications for the Canadian supply chain. Supply
Chain Management, 4 (2), 86-94.
Stanton, W.W. & Reese, R.M.
(1983). Three conjoint segmentation approaches to the evaluation of advertising
theme creation. Journal of Business Research, 11, 201-216.
Steckel,
J.H. & O'shaughnessy, J. (1989). Towards a new way to
measure power: Applying conjoint analysis to group decisions. Marketing
Letters, 1 (1), 37-46.
Steckel, J.H. & Vanhonacker,
W.R. (1993). Cross-validating regression models in marketing research. Marketing
Science, 12 (4), 415-427.
Steckel, J.H., DeSarbo, W.S. &
Mahajan, V. (1991). On the creation of acceptable conjoint analysis
experimental designs. Decision Sciences, 22, 435-442.
Steenkamp, J.E.M. & Wedel, M.
(1993). Fuzzy clusterwise regression in benefit segmentation: Application and
investigation into its validity. Journal of Business Research, 26,
237-249.
Steenkamp, J.E.M. & Wittink, D.R. (1994). The metric quality of full-profile judgments and the number-of-attribute-levels effect in conjoint analysis. International Journal of Research in Marketing, 11, 275-286.
Stegmüller,
B. & Hempel, P. (1996). Empirischer Vergleich unterschiedlicher
Marktsegmentierungsansätze über die Segmentpopulation. Marketing ZFP, 18,
25-31.
Stegmüller,
B. (1995). Internationale Marktsegmentierung als Grundlage für
internationale Marketing-Konzeptionen. Bergisch Gladbach: Eul.
Steinberg, D. (1992). Applications of logit models in market research. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 405-424). Ketchum, ID: Sawtooth Software.
Steiner,
W.J. & Hruschka, H. (2000). Conjointanalyse-basierte
Produkt(linien)gestaltung unter Berücksichtigung von Konkurrenzreaktionen. OR
Spektrum, 22 (1), 71-95.
Steiner, W.J. & Hruschka, H.
(2001). A probabilistic one-step approach to the optimal product line design
problem using conjoint and cost data. Regensburger Diskussionsbeiträge zur
Wirtschaftswissenschaft (Nr. 360), Universität Regensburg.
Steiner,
W.J. (1999). Optimale Neuproduktplanung. Entscheidungsmodelle und
wettbewerbsorientierter Ansatz. Wiesbaden: Deutscher Univ.-Verlag.
Stevens,
B. (2000, November 6). Save money with online analysis. Marketing News, 34
(23), 27-28.
Stevens,
K.T. & Cline, K. (1998). Firing up the front line (bank brands). Banking
Strategies, 74 (6), 34-38.
Stevens,
T.H., Belkner, R., Dennis, D., Kittredge, D. & Willis, C. (2000).
Comparison of contingent valuation and conjoint analysis in ecosystem
management. Ecological Economics, 32, 63-74.
Steward, D.W. (1982). Models of consumer choice or models of the choice tasks? In R.K. Srivastava & A. D. Shocker (Eds.), Analytic approaches to product and marketing planning: The second conference (Report No. 82-109, pp. 165-176). Cambridge, MA: Marketing Science Institute.
Stich, A. (1997). Herkunftszeichen als Qualitätssignal: Eine Erklärung der Nutzung eines extrinsischen Produktmerkmals als Qualitätssignal durch Konsumenten am Beispiel von Herkunftszeichen. Lohmar: Eul.
Stone, M. & Rasp, J. (1991). Tradeoffs in the choice between logit and OLS for accounting choice studies. The Accounting Review, 66 (1), 170-187.
Stotz,
M. (1998). Die Erhebung von Preis-Absatz-Funktionen mittels der
Conjoint-Analyse: Vergleich der Ergebnisse mit denen, die aus einfacher
Befragung und Paarvergleich resultieren. Unveröffentlichte Diplomarbeit, Westfälische
Wilhelms-Universität Münster.
Struhl, S. (1992). Comment on Chrzan and Grisaffe. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 243-244). Ketchum, ID: Sawtooth Software.
Struhl, S. (1994a). Discrete choice modeling comes to the PC. A review of CBC from Sawtooth Software and Ntelogit from Intelligent Marketing Systems. Quirk's Marketing Research Review, May, 12-41.
Struhl, S. (1994b). Discrete choice modeling: Understanding a "better conjoint than conjoint". Quirk's Marketing Research Review, June/July.
Struhl, S.M. (1991). Comment on Salling and Deegan. In M. Metegrano (Ed.), 1991 Sawtooth Software Conference Proceedings (pp. 175-176). Ketchum, ID: Sawtooth Software.
Swait,
J., Louviere, J. & Anderson, D. (1995). Best/worst conjoint: A new
preference elicitation method to simultaneously identify overall attribute
importance and attribute level partworths. Working paper, Intelliquest,
Inc.
Swallow, S., Opaluch, J. & Weaver, T. (1992). Siting noxious facilities: an approach that integrates technical, economic and political consideration. Land Economics, 68, 283-301.
Swenson,
M.J., Swinyard, W.R., Langrehr, F.W. & Smith, S.M. (1993). The appeal of
personal selling as a career: A decade later. Journal of Personal Selling
and Sales Management, 13 (1), 51-64.
Swinnen,
G. (1983). Decisions on product-mix changes in supermarket chains.
Unpublished doctoral dissertation, UFSIA, Antwerp University, Belgium.
Swoboda,
B. (2000). Messung von Einkaufsstaettenpraeferenzen auf der Basis der
Conjoint-Analyse. Die Betriebswirtschaft, 60 (2), 149-166.
Szeinbach,
S.L., Barnes, J.H. & Garner, D.D. (1997). Use of pharmaceutical
manufacturers´ value-added services to build customer loyalty. Journal of
Business Research, 40 (3), 229-236.
Szeinbach,
S.L., Barnes, J.H., McGhan, W.F., Murawski, M.M. & Corey, R. (1999). Using
conjoint analysis to evaluate health state preferences. Drug Information
Journal, 33 (3), 849-858.