Information Retrieval and Survey Design for Two-Stage Customer Preference Modeling. (May 2022)

• Record Type: Journal Article
• Authors: Xiao, Y.; Cui, Y.; Raut, N.; Januar, J. H.; Koskinen, J.; Contractor, N.; Chen, W.; Sha, Z.
• Is Part Of: Proceedings of the Design Society. Volume 2(2022)
• Page Start: 811
• Page End: 820
• Publication Date: 2022-05
• Subjects: data-driven design -- customer integration methods -- information retrieval -- customer preference analysis; Industrial design -- Congresses; Engineering design -- Congresses; 620.0042
• DOI: 10.1017/pds.2022.83
• Languages: English
• ISSNs: 2633-7762

Abstract

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.