An Approach Toward Making a Design Decision Based on Future Demand Prediction
This paper presents an approach for modeling uncertainty of future demand according to a forecast of an influential exogenous variable, which serves as the first step toward making a product design decisions based on future demand prediction. Optimum product design that maximizes expected profit or expected utility of profit depends on future demand influenced by future exogenous variables (i.e., economic, societal, and political variables beyond designers' control). For example, an optimum design among gasoline, hybrid, electric, and fuel cell vehicles may depend on economic variables such as future gasoline prices, societal variables such as future climate change, and political variables such as future government standards for fuel-efficient vehicles. However, in particular for large-scaled and complex products, designers quite often make design decisions many years before the product is introduced to the marketplace without knowing future exogenous variables. To enable designers to make design decisions according to predicted demands, this study proposes to link demand distributions with exogenous variables and update demand distributions based on exogenous variable forecasts and their degrees of accuracies. An illustrative example is used to demonstrate impacts of exogenous variable forecasts and their accuracies on future demand prediction and expected profit calculation of a fuel cell vehicle. Copyright © 2011 by ASME and General Motors Company.
S. Takai et al., "An Approach Toward Making a Design Decision Based on Future Demand Prediction," Proceedings of the ASME Design Engineering Technical Conference, American Society of Mechanical Engineers (ASME), Jan 2011.
The definitive version is available at http://dx.doi.org/10.1115/DETC2011-47493
ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011
Mechanical and Aerospace Engineering
Keywords and Phrases
Bootstrap; Choice-Based Conjoint Analysis; Demand Modeling
Article - Conference proceedings
© 2011 American Society of Mechanical Engineers (ASME), All rights reserved.