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

Y. Xiao; Y. Cui; N. Raut; J. H. Januar; J. Koskinen; N. Contractor; W. Chen; Z. Sha

doi:10.1017/pds.2022.83

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

Y. Xiao, Y. Cui, N. Raut, J. H. Januar, J. Koskinen, N. Contractor, W. Chen, Z. Sha^*

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

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.

Original language	English (US)
Pages (from-to)	811-820
Number of pages	10
Journal	Proceedings of the Design Society
Volume	2
DOIs	https://doi.org/10.1017/pds.2022.83
State	Published - May 2022
Event	17th International Design Conference, DESIGN 2022 - Virtual, Online, Croatia Duration: May 23 2022 → May 26 2022

Funding

The authors acknowledge Lada Nuzhna, Fiona, Olga Lew-Kiedrowska, Laith Kassisieh, Neelam Modi for their assistance in data management on Cint and/or the inputs during research meetings. We also greatly acknowledge the funding support from NSF CMMI #2005661 and #2203080.

Keywords

customer integration methods
customer preference analysis
data-driven design
information retrieval

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Science Applications
Software
Modeling and Simulation

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10.1017/pds.2022.83

Cite this

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title = "Information Retrieval and Survey Design for Two-Stage Customer Preference Modeling",

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.",

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AU - Xiao, Y.

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AU - Raut, N.

AU - Januar, J. H.

AU - Koskinen, J.

AU - Contractor, N.

AU - Chen, W.

AU - Sha, Z.

N1 - Publisher Copyright: © The Author(s), 2022.

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AB - 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.

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KW - data-driven design

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

Abstract

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Keywords

ASJC Scopus subject areas

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