Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge

Yi Ren, Panos Y. Papalambros

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Conjoint analysis from marketing has been successfully integrated with engineering analysis in design for market systems. The long questionnaires needed for conjoint analysis in relatively complex design decisions can become cumbersome to the human respondents. This paper presents an adaptive questionnaire generation strategy that uses active learning and allows incorporation of engineering knowledge in order to identify efficiently designs with high probability to be optimal. The strategy is based on viewing optimal design as a group identification problem. A running example demonstrates that a good estimation of consumer preference is not always necessary for finding the optimal design and that conjoint analysis could be configured more effectively for the specific purpose of design optimization. Extending the proposed method beyond a homogeneous preference model and noiseless user responses is also discussed.

Original languageEnglish (US)
Title of host publication40th Design Automation Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
Volume2A
ISBN (Print)9780791846315
DOIs
StatePublished - 2014
Externally publishedYes
EventASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014 - Buffalo, United States
Duration: Aug 17 2014Aug 20 2014

Other

OtherASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014
CountryUnited States
CityBuffalo
Period8/17/148/20/14

Fingerprint

Conjoint Analysis
Knowledge Engineering
Knowledge engineering
Questionnaire
Active Learning
Identification Problem
Marketing
Engineering
Necessary
Demonstrate
Design
Strategy
Optimal design
Model

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

Cite this

Ren, Y., & Papalambros, P. Y. (2014). Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge. In 40th Design Automation Conference (Vol. 2A). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2014-34790

Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge. / Ren, Yi; Papalambros, Panos Y.

40th Design Automation Conference. Vol. 2A American Society of Mechanical Engineers (ASME), 2014.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ren, Y & Papalambros, PY 2014, Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge. in 40th Design Automation Conference. vol. 2A, American Society of Mechanical Engineers (ASME), ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014, Buffalo, United States, 8/17/14. https://doi.org/10.1115/DETC2014-34790
Ren Y, Papalambros PY. Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge. In 40th Design Automation Conference. Vol. 2A. American Society of Mechanical Engineers (ASME). 2014 https://doi.org/10.1115/DETC2014-34790
Ren, Yi ; Papalambros, Panos Y. / Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge. 40th Design Automation Conference. Vol. 2A American Society of Mechanical Engineers (ASME), 2014.
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