V

van Asseldonk, M.A.P.M., Huirne, R.B.M & Dijkhuizen, A.A. (1998). Quantifying characteristics of information-technology applications based on expert knowledge for detection of oestrus and mastitis in dairy cows. Preventive Veterinary Medicine, 36 (4), 273-286.

van der Haar, J.W., Kemp, R.G.M & Omta, O. (2001). Creating value that cannot be copied. Industrial Marketing Management, 30 (8), 627-636.

van der Lans, I.A. & Heiser, W.J. (1992). Constrained Part-worth estimation in conjoint analysis using the self-explicated utility model. International Journal of Research in Marketing, 9, 325-344.

van der Lans, I.A., Wittink, D.R., Huber, J. & Vriens, M. (1992). Within- and across-attribute constraints in ACA and full profile conjoint analysis. In M. Metegrano (Ed.), 1992 Sawtooth Software Conference Proceedings (pp. 365-379). Ketchum, ID: Sawtooth Software.

Van der Pol, M. & Cairns, J. (1998). Establishing patient’s preferences for blood transfusion support: An application of conjoint analysis. Journal of Health Services Research and Policy, 3, 70-77.

van der Pol, M. & Cairns, J. (2001). Estimating time preferences for health using discrete choice experiments. Social Science & Medicine, 52 (9), 1459-1470.

van der Pool, M. & Ryan, M. (1996). Using conjoint analysis to establish consumer preferences for fruit and vegetables. British Food Journal, 98 (8), 5-12.

van Limburg, B. (1998). City marketing: a multi-attribute approach. Tourism Management, 19 (5), 475-477.

van Schaik, G., Dijkhuizen, A.A., Huirne, R.B.M. & Benedictus, G. (1998). Adaptive conjoint analysis to determine perceived risk factors of farmers, veterinarians and AI technicians for introduction of BHVl to dairy farms. Preventive Veterinary Medicine, 37 (1-4), 101-112.

van Schijndel, C. (1992). How to communicate complex techniques in a multi-cultural environment. Marketing Opportunities with Advanced Research Techniques: Proceedings of the second SKIM Seminar (pp. 51-58). Rotterdam, The Netherlands: SKIM Market and Policy Research.

Vandenbosch, M.B. & Weinberg, C.B. (1997). A value analysis model for farm equipment manufacturers. Agribusiness, 13 (4), 409-421.

VanDeVyvere, Y., Oppewal, H. & Timmermans, H. (1998). The validity of hierarchical information integration choice experiments to model residential preference and choice. Geographical analysis: An international journal of theoretical geography, 30 (3), 254-272.

Vavra, T.G., Green, P.E. & Krieger, A.M. (1999). Evaluating EZPass. Using conjoint analysis to assess consumer response to a new tollway technology. Marketing Research, Summer, 4-13+16.

Verhallen, T. & DeNooij, G.J. (1982). Retail attributes and shopping patronage. Journal of Economic Psychology, 2, 439-455.

Verma, R. & Pullman, M.E. (1998). An analysis of the supplier selection process. Omega-International Journal of Management Science, 26 (6), 739-750.

Verma, V.K. & Zellner, A. (1991). A bayesian econometric methodology for estimation and prediction in conjoint analysis. In T.K. Kaul & J.K. Sengupta (Eds.), Economic models, estimation, and socioeconomic systems: Essays in honor of Karl A. Fox (pp. 369-397). Amsterdam, Holland: North-Holland.

Vick, S. & Scott, A. (1998). Agency in health care. Examining patients´ preferences for attributes of the doctor-patient relationship. Journal of Health Economics, 17 (5), 587-605.

Vickers, Z.M. (1993). Incorporating tasting into a conjoint analysis of taste, health claim, price and brand for purchasing strawberry yogurt. Journal of Sensory Studies, 8, 341-352.

Vidulich, M.A. & Tsang, P.S. (1986). Techniques of subjective workload assessment: A comparison of SWAT and the NASA-Bipolar methods. Special Issue: Aviation psychology. Ergonomics, 29, 1385-1398.

Viscusi, W.K., Magat, W.A. & Huber, J. (1991). Pricing environmental health risks: Survey assessment of risk-risk and risk-dollar trade-offs for chronic bronchitis. Journal of Environmental Economics and Management, 21, 32-51.

Viswanathan, M. & Narayanan, S. (1992). Processing numerical versus verbal attribute information: A Study using information acquisition patterns. Marketing Letters, 3 (2), 201-208.

Voeth, M. & Hahn, C. (1998). Limit Conjoint-Analyse. Marketing ZFP, 20, 119-132.

Voeth, M. (1999). 25 Jahre conjointanalytische Forschung in Deutschland. Zeitschrift für Betriebswirtschaft – Ergänzungsheft, 2, 153-176.

Voeth, M. (2000). Nutzenmessung in der Kaufverhaltensforschung: Die hierarchische individualisierte Limit-Conjoint-Analyse (HILCA). Wiesbaden: Gabler.

Vriens, M. & Maas, A. (1990). Conjoint analysis of trade-off preference matrices: Some possible extensions. In S.E.G. Lea, P. Webley, & B.M. Young (Eds.), Applied economic psychology in the 1990's (pp. 1075-1081). Springer, Berlin.

Vriens, M. (1992). Strengths and weaknesses of various conjoint analysis techniques and suggestions for improvement. In Marketing Opportunities with Advanced Research Techniques: Proceedings of the second SKIM Seminar (pp. 11-26). Rotterdam, The Netherlands: SKIM Market and Policy Research.

Vriens, M. (1994). Solving marketing problems with conjoint analysis. Journal of Marketing Management, 10 (1-3), 37-55.

Vriens, M. (1995). Conjoint analysis in marketing. Developments in stimulus representation and segmentation methods. Groningen: SOM.

Vriens, M., Loosschilder, G.H., Rosbergen, E. & Wittink, D.R. (1998). Verbal versus realistic pictorial representations in conjoint analysis with design attributes. Journal of Product Innovation and Management, 15 (5), 455-467.

Vriens, M., Oppewal, H. & Wedel, M. (1998). Ratings-based versus choice-based latent class conjoint models. Journal of Market Research Society, 40 (3), 237-248.

Vriens, M., Scheer, H.R. van, Hoekstra, J.C. & Bult, J.R. (1998). Conjoint experiments for direct mail response optimization. European Journal of Marketing, 32 (3/4), 323-339.

Vriens, M., Wedel, M. & Wilms, T. (1996). Metric conjoint segmentation methods: A monte carlo comparison. Journal of Marketing Research, 33 (1), 73-85.

vvan der Lans, I.A. & Heiser, W.J. (1991). Constrained part-worth estimation in conjoint analysis using the self-explicated utility model (Research Report RR 90-02). Department of Data Theory, University of Leiden, The Netherlands.