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.

Details

Title
Information Retrieval and Survey Design for Two-Stage Customer Preference Modeling
Author
Xiao, Y 1 ; Cui, Y 2 ; Raut, N 3 ; Januar, J H 4 ; Koskinen, J 4 ; Contractor, N 2 ; Chen, W 2 ; Sha, Z 1 

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 
Pages
811-820
Section
Article
Publication year
2022
Publication date
May 2022
Publisher
Cambridge University Press
e-ISSN
2732-527X
Source type
Conference Paper
Language of publication
English
DOI
https://doi.org/10.1017/pds.2022.83
ProQuest document ID
2886570250
Copyright
The Author(s), 2022. This work is licensed under the Creative Commons  Attribution – Non-Commercial – No Derivatives License This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.