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

Daniel Baier () and Michael Brusch ()
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Daniel Baier: Brandenburg University of Technology
Michael Brusch: Brandenburg University of Technology

A chapter in Operations Research Proceedings 2005, 2006, pp 619-624 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1007/3-540-32539-5_97

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