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Keywords: bootstrap
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Proceedings Papers

Proc. ASME. DETC97, Volume 3: 9th International Design Theory and Methodology Conference, V003T30A014, September 14–17, 1997
Paper No: DETC97/DTM-3878
..., the significance of uncertainty in relation to design improvement potential is discussed. The proposed method is then applied to an engine concept selection problem. product design evaluation preference uncertainty bootstrap Proceedings of DETC 97: 1997 ASME Design Engineering Technical Conference...
Proceedings Papers

Proc. ASME. IDETC-CIE2011, Volume 9: 23rd International Conference on Design Theory and Methodology; 16th Design for Manufacturing and the Life Cycle Conference, 769-780, August 28–31, 2011
Paper No: DETC2011-47493
... calculation of a fuel cell vehicle. KEYWORDS: Demand Modeling, Choice-Based Conjoint Analysis, Bootstrap. 1. INTRODUCTION U.S. firms are facing severe competition in the global marketplace. Differentiating designs of their own products from competing products is critical to winning the competition; however...
Proceedings Papers

Proc. ASME. IDETC-CIE2011, Volume 9: 23rd International Conference on Design Theory and Methodology; 16th Design for Manufacturing and the Life Cycle Conference, 781-787, August 28–31, 2011
Paper No: DETC2011-47496
... as a method to estimate a demand of a new product design, it has not been fully employed to model demand uncertainty. This paper demonstrates and compares two approaches that use conjoint analysis data to model demand uncertainty: bootstrap of respondent choice data and Monte Carlo simulation of utility...
Proceedings Papers

Proc. ASME. IDETC-CIE2010, Volume 6: 15th Design for Manufacturing and the Lifecycle Conference; 7th Symposium on International Design and Design Education, 205-212, August 15–18, 2010
Paper No: DETC2010-28231
... of customers. This paper proposes an alternative to traditional conjoint analysis methods that provide point estimates of market shares. It proposes two approaches to model market share uncertainty; bootstrap and binomial inference applied to choice-based conjoint analysis data. The proposed approaches...
Proceedings Papers

Proc. ASME. IDETC-CIE2009, Volume 8: 14th Design for Manufacturing and the Life Cycle Conference; 6th Symposium on International Design and Design Education; 21st International Conference on Design Theory and Methodology, Parts A and B, 157-166, August 30–September 2, 2009
Paper No: DETC2009-86771
... applying bootstrap to customers’ preference data obtained from conjoint analysis. The proposed approach is demonstrated in an illustrative example: a decision-analytic automobile concept selection. Concept Selection Decision Analysis Case-Based Reasoning Conjoint Analysis Clustering Bootstrap...
Proceedings Papers

Proc. ASME. IDETC-CIE2007, Volume 4: ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications and the 19th Reliability, Stress Analysis, and Failure Prevention Conference, 779-790, September 4–7, 2007
Paper No: DETC2007-35080
... clusters). Applying Bootstrap to SC (BS-SC) helps engineers to make inferences on the population primary clusters. In this paper, we randomly pulled out samples of different sizes from both the simulation approach using simulation-generated population data and the empirical approach using experimental...
Proceedings Papers

Proc. ASME. IDETC-CIE2005, Volume 4b: Design for Manufacturing and the Life Cycle Conference, 503-511, September 24–28, 2005
Paper No: DETC2005-85432
.... In grouping similar needs, engineers use affinity diagram, which is a popular consensus-based method, or subjective clustering, which is a statistical method. This paper applies bootstrap to subjective clustering in order to assist engineers make an inference about the population cluster of customer needs...
Proceedings Papers

Proc. ASME. IDETC-CIE2006, Volume 4b: 11th Design for Manufacturing and the Lifecycle Conference, 811-819, September 10–13, 2006
Paper No: DETC2006-99623
... number of representative needs. Subjective Clustering is a statistical method that uses Hierarchical Clustering algorithm to group similar customer needs into clusters. This paper compares Subjective Clustering (SC) and Bootstrap applied to Subjective Clustering (BS-SC) for determining how accurately...