Information Retrieval and Survey Design for Two-Stage Customer Preference Modeling

DS 116: Proceedings of the DESIGN2022 17th International Design Conference

Year: 2022
Editor: Mario Štorga, Stanko Škec, Tomislav Martinec, Dorian Marjanović
Author: Yinshuang Xiao (1), Yaxin Cui (2), Nikita Raut (3), Jonathan Haris Januar (4), Johan Koskinen (4), Noshir Contractor (2), Wei Chen (2), Zhenghui Sha (1)
Series: DESIGN
Institution: 1: The University of Texas at Austin, United States of America; 2: Northwestern University, United States of America; 3: Amazon, United States of America; 4: The University of Melbourne, Australia
Section: Design Information and Knowledge
Page(s): 811-820
DOI number: https://doi.org/10.1017/pds.2022.83
ISSN: 2732-527X (Online)

Abstract

Customer survey data is critical to supporting customer preference modeling in engineering design. We present a framework of information retrieval and survey design to ensure the collection of quality customer survey data for analyzing customers’ preferences in their consideration-then-choice decision-making and the related social impact. The utility of our approach is demonstrated through the survey design for customers in the vacuum cleaner market. Based on the data, we performed descriptive analysis and network-based modeling to understand customers’ preferences in consideration and choice.

Keywords: data-driven design, customer integration methods, information retrieval, customer preference analysis