Enhancing discrete choice demand modeling for Decision-Based Design

Our research is motivated by the need for developing a rigorous Decision-Based Design framework and the need for developing an approach to demand modeling that is critical for assessing the profit a product can bring. Even though demand modeling techniques exist in market research, little work exists on product demand modeling that addresses the specific needs of engineering design in particular that facilitates engineering decision-making. Building upon our earlier work on using the discrete choice analysis approach to demand modeling, in this work, we provide detailed guidelines for implementing the discrete choice demand modeling approach in product design. The modeling of a hierarchy of product attributes is introduced to cascade customer desires to specific key customer attributes that can be represented using engineering language. To improve the predictive capability of demand models, we propose to use the Kano method for providing the econometric justification when selecting the shape of the customer utility function. A real (passenger) vehicle engine case study, developed in collaboration with the market research firm J.D. Power & Associates and Ford Motor Company, demonstrates the proposed approaches. The example focuses on demand analysis and does not reach beyond the key customer attribute level. The obtained demand model is shown to be satisfactory through cross validation.