Designing lines of cars that optimize the degree of differentiation vs. commonality among models in the line: A natural intelligence approach

Abstract

The product life cycle of cars is becoming shorter and carmakers constantly introduce new or revised models in their lines, tailored to their customer needs. At the same time, new car model design decisions may have a substantial effect on the cost and revenue drivers. For example, although a new car model configuration with component commonality may lower manufacturing cost, it also hinders increased revenues that could have been achieved through product differentiation. This paper applies a state of the art, nature inspired approach to design car lines that optimize the degree of differentiation vs commonality among models in the line. Our swarm intelligence mechanism is applied to stated preference data derived from a large-scale conjoint experiment that measures consumer preferences for passenger cars in a sample of 1,164 individuals. Our approach provides interesting insights on how new and existing car models can be combined in a product line and suggests that differentiation among models within a product line elevates customer satisfaction. © 2012 Springer-Verlag.