Optimal product line designing: A comparison of different discrete choice-based approaches
(A2021-93303)

AUTHORS

Friederike Paetz, Clausthal University of Technology; Winfried Steiner, Clausthal University of Technology; Harald Hruschka, University of Regensburg

ABSTRACT

Nowadays, short product life cylcles force companies to frequently develop and offer new products. In order to gain revenues and stay competitive, companies have to carefully design their revenue-maximizing product lines. Often, individual consumer preferences derived from discrete choice experiments build the input for product line optimization. Basically, two different approaches, e.g., a simultaneous approach and a separate approach exist, that differ in their consideration of consumers’ preference heterogeneity. We compared these two types of product line design approaches w.r.t. to their performance to detect revenue-maximizing product lines. We use a Monte Carlo simulation study and found the simultaneous approach to outperform the separate approach and therefore being more robust to biases in the recovery of preference structures, e.g., part-worth utility estimation. Furthermore, we detect several experimental factors that determine the approaches’ performances.