GOALI: A Choice Modeling Approach to Incorporating Heterogeneous Consumer Preferences into Enterprise-Driven Product Design

本次Goali奖的研究目标是开发一种基于信息的分层选择建模方法，用于管理和分析来自多个来源的消费者偏好数据。这种方法将允许将定性的营销偏好转换为定量的绩效度量，以便管理大规模构件的需求建模的复杂性。将使用先进的概率选择建模方法来捕捉客户偏好和市场异质性。将开发模型融合(数据丰富)技术，以有效地结合来自不同来源的揭示和陈述的偏好数据，以提高预测精度和模型有效性。最后，将选择模型整合到企业驱动的设计框架中，在考虑多学科权衡的情况下，在汽车内包装尺寸的设计中进行演示。如果成功，所提出的研究将提供一种通用的需求建模和企业驱动的设计方法，可以应用于大规模系统、工程消费品和移动/假肢设备。我们的研究将利用市场研究和交通工程中现有的离散选择分析技术的结果，并扩大它们在工程设计中的应用。大学和产业界之间的强有力的合作将确保所产生的技术成功转移和实施。这项拟议的研究对设计教育具有深远的影响，因为它通过分析建模，在产品使用的背景下灌输严谨的方式来捕捉客户的偏好。研究结果将纳入机械工程的本科生和研究生设计课程。行业合作伙伴将通过与研究团队的合作、学生论文委员会的服务、受邀的研究研讨会报告和客座讲师机会，在该项目中发挥重要作用。

The research objective of this GOALI award is to develop an information-based hierarchical choice modeling approach for managing and analyzing consumer preference data from multiple sources. This approach will enable the transformation of qualitative marketing preferences to quantitative performance measures in order to manage the complexity of demand modeling for large-scale artifacts. Advanced probabilistic choice modeling approaches will be used to capture customer preferences and market heterogeneity. Model fusion (data enrichment) techniques will be developed to effectively combine revealed and stated preference data from various sources to improve prediction accuracy and model validity. Finally, the integration of the choice model into an enterprise-driven design framework will be demonstrated in the design of vehicle interior package dimensions, considering multidisciplinary tradeoffs.If successful, the proposed research will offer a general demand modeling and enterprise-driven design approach that can be applied to large-scale systems, engineered consumer goods, and mobility/prosthetic devices. Our research will leverage the results from existing discrete choice analysis techniques in market research and transportation engineering, and extend their use in engineering design. The strong collaboration between the university and industry will ensure that the resulting technology is successfully transferred and implemented. The proposed research has far reaching consequences for design education by instilling rigor into capturing customers' preference in the context of product usage through analytical modeling. Results of the research will be incorporated into undergraduate and graduate design courses in mechanical engineering. Industry co-PIs will have significant involvement in the project through collaborations with the research team, service on student thesis committees, invited research seminar presentations, and guest lecturer opportunities.