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

该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。这种方法将使定性的营销偏好转化为定量的绩效指标，以管理大规模工件需求建模的复杂性。 先进的概率选择建模方法将用于捕捉客户的偏好和市场的异质性。 将开发模型融合（数据浓缩）技术，以便有效地将来自各种来源的显示和陈述偏好数据联合收割机结合起来，提高预测准确性和模型有效性。 最后，集成的选择模型到企业驱动的设计框架将被证明在汽车内饰包装尺寸的设计，考虑多学科tradeoffs.If成功的，拟议的研究将提供一个通用的需求建模和企业驱动的设计方法，可应用于大型系统，工程消费品，和移动/假肢设备。 我们的研究将利用现有的离散选择分析技术在市场研究和运输工程的结果，并扩大其在工程设计中的使用。大学和工业界之间的密切合作将确保所产生的技术成功转移和实施。拟议的研究具有深远的影响，设计教育灌输严谨捕捉客户的偏好，在产品使用的背景下，通过分析建模。研究结果将纳入本科和研究生设计课程的机械工程。行业co-PI将通过与研究团队的合作，学生论文委员会的服务，邀请研究研讨会演讲和客座讲师机会来参与该项目。

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.