A Decision-Analytic Concept Selection for a Commercial System Using Objective Data to Model Uncertainty

Abstract

This paper presents decision-analytic concept selection framework for a commercial system and an uncertainty modeling using objective data. The selection of a system concept for which a final system is designed and manufactured is a decision making process with incomplete information. Decision analysis is a prescriptive approach for decision making under uncertainty. While realizing that humans make decisions violating the expected utility axioms, decision analysis uses a set of tools to guide a decision maker toward an unbiased and rational decision making. The objective of this research is to propose a decision-analytic framework for commercial system concept selection, and an approach to utilize as much objective data as possible in the uncertainty modeling. Toward this objective, this paper construct cost distribution using case-based reasoning and market share distribution 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. Copyright © 2009 by ASME.

Meeting Name

2009 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2009

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Bootstrap; Case-Based Reasoning; Clustering; Concept Selection; Conjoint Analysis; Decision Analysis

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2010 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Jan 2010

Link to Full Text

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