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Improving the Predictive Validity of Quality Function Deployment by Conjoint Analysis: A Monte Carlo Comparison

  • Daniel Baier
  • Michael Brusch
Part of the Operations Research Proceedings book series (ORP, volume 2005)

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.

Keywords

Conjoint Analysis Quality Function Deployment Product Innovation Management Adaptive Conjoint Analysis High Predictive Validity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Daniel Baier
    • 1
  • Michael Brusch
    • 1
  1. 1.Chair of Marketing and Innovation ManagementBrandenburg University of TechnologyCottbusGermany

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