4 Conclusion and outlook
The “new” CA based approach for QFD shows a number of advantages in comparison to the traditional approach. PA importances as well as PC influences on PAs are measured “conjoint” resp. simultaneously. Furthermore, the calculated weights are more precise (real valued instead of 0-, 1-, 3-, or 9-values) which resulted in a higher predictive validity. The Monte Carlo comparison has shown a clear superiority in a huge variety of simulated empirical settings.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Akao Y (1990) QFD, Integrating customer requirements into product design. Productivity Press, Cambridge, MA
Askin RG, Dawson D (2000) Maximizing customer satisfaction by optimal specification of engineering Characteristics. IIE Transactions 32:9–20
Baier D, Brusch M (2005) Linking quality fuction deployment and conjoint analysis for new product design. In: Baier, D, Decker, R, Schmidt-Thieme, L (eds) Data analysis and decision support. Springer, Berlin, 189–198
Baier D, Gaul W (1999) Optimal product positioning based on paired comparison data. Journal of Econometrics 89:365–392
Baier D, Gaul W (2003) Market simulation using a probabilistic ideal vector model for conjoint data. In: Gustafsson A, Herrmann A, Huber F (eds) Conjoint measurement-methods and applications. 3rd ed., Springer, Berlin, 97–120
Brusch M, Baier D, Treppa A (2002) Conjoint analysis and stimulus presentation: a comparison of alternative methods. In: Jajuga K, Sokolowski A, Bock HH (eds) Classification, clustering, and analysis. Springer, Berlin, 203–210
Cristiano JJ, Liker JK, White CC (2000) Customer-driven product development through Quality Function Deployment in the U.S. and Japan. Journal of Product Innovation Management 17:286–308
Chan LK, Wu ML (2002) Quality Function Deployment: a literature review. European Journal of Operational Research 143:463–497
Gustafsson A (1996) Customer focused product development by conjoint analysis and Quality Function Deployment. Linköping University Press, Linköping
Hauser JR, Simmie P (1981) Profit maximizing perceptual positions: an integrated theory for the selection of product features and price. Management Science 27:33–56
Pullman ME, Moore WL, Wardell DG (2002) A comparison of Quality Function Deployment and conjoint analysis in new product design. Journal of Product Innovation Management 19:354–364
Urban GL, Hauser JR (1993) Design and marketing of new products. Prentice Hall, Englewood Cliffs, NJ
Yoder B, Mason D (1995) Evaluating QFD relationships through the use of regression analysis. In: Proceedings of the Seventh Symposium on Quality Function Deployment, ASI&GOAL/QPC. American Supplier Institute, Livonia, MI, 239–249
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Baier, D., Brusch, M. (2006). Improving the Predictive Validity of Quality Function Deployment by Conjoint Analysis: A Monte Carlo Comparison. In: Haasis, HD., Kopfer, H., Schönberger, J. (eds) Operations Research Proceedings 2005. Operations Research Proceedings, vol 2005. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-32539-5_97
Download citation
DOI: https://doi.org/10.1007/3-540-32539-5_97
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32537-6
Online ISBN: 978-3-540-32539-0
eBook Packages: Business and EconomicsBusiness and Management (R0)