Adaptive Questionnaires for Direct Identification of Optimal Product Design

TL;DR

This paper introduces an innovative adaptive questionnaire method that directly identifies the most profitable product design by integrating consumer preferences with engineering feasibility and costs, bypassing the need for preference estimation.

Contribution

The work presents a novel adaptive questionnaire approach that leverages engineering and manufacturing knowledge to directly find optimal product designs, improving efficiency over traditional preference estimation methods.

Findings

The proposed method outperforms standard preference estimation approaches.

It accelerates optimal product design identification by integrating multidisciplinary knowledge.

The approach provides insights into the complexity of design identification under noisy responses.

Abstract

We consider the problem of identifying the most profitable product design from a finite set of candidates under unknown consumer preference. A standard approach to this problem follows a two-step strategy: First, estimate the preference of the consumer population, represented as a point in part-worth space, using an adaptive discrete-choice questionnaire. Second, integrate the estimated part-worth vector with engineering feasibility and cost models to determine the optimal design. In this work, we (1) demonstrate that accurate preference estimation is neither necessary nor sufficient for identifying the optimal design, (2) introduce a novel adaptive questionnaire that leverages knowledge about engineering feasibility and manufacturing costs to directly determine the optimal design, and (3) interpret product design in terms of a nonlinear segmentation of part-worth space, and use this interpretation to illuminate the intrinsic difficulty of optimal design in the presence of noisy questionnaire responses. We establish the superiority of the proposed approach using a well-documented optimal product design task. This study demonstrates how the identification of optimal product design can be accelerated by integrating marketing and manufacturing knowledge into the adaptive questionnaire.