Modeling spatiotemporal heterogeneity of customer preferences in engineering design

Youyi Bi, Mingxian Wang, Jian Xie, Yan Fu, Zhenghui Sha, Wei Chen*

*Corresponding author for this work

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

Abstract

Customer preferences are found to evolve over time and correlate with geographical locations. Studying spatiotemporal heterogeneity of customer preferences is crucial to engineering design as it provides a dynamic perspective for a thorough understanding of preference trend. However, existing analytical models for demand modeling do not take the spatiotemporal heterogeneity of customer preferences into consideration. To fill this research gap, a spatial panel modeling approach is developed in this study to investigate the spatiotemporal heterogeneity of customer preferences by introducing engineering attributes explicitly as model inputs in support of demand forecasting in engineering design. In addition, a step-by-step procedure is proposed to aid the implementation of the approach. To demonstrate this approach, a case study is conducted on small SUV in China’s automotive market. Our results show that small SUVs with lower prices, higher power, and lower fuel consumption tend to have a positive impact on their sales in each region. In understanding the spatial patterns of China’s small SUV market, we found that each province has a unique spatial specific effect influencing the small SUV demand, which suggests that even if changing the design attributes of a product to the same extent, the resulting effects on product demand might be different across different regions. In understanding the underlying social-economic factors that drive the regional differences, it is found that Gross Domestic Product (GDP) per capita, length of paved roads per capita and household consumption expenditure have significantly positive influence on small SUV sales. These results demonstrate the potential capability of our approach in handling spatial variations of customers for product design and marketing strategy development. The main contribution of this research is the development of an analytical approach integrating spatiotemporal heterogeneity into demand modeling to support engineering design.

Original languageEnglish (US)
Title of host publication44th Design Automation Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791851753
DOIs
StatePublished - Jan 1 2018
EventASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2018 - Quebec City, Canada
Duration: Aug 26 2018Aug 29 2018

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2A-2018

Other

OtherASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2018
CountryCanada
CityQuebec City
Period8/26/188/29/18

Fingerprint

Spatio-temporal Modeling
Engineering Design
Customers
Sales
China
Attribute
Modeling
Demand Forecasting
Product design
Fuel consumption
Spatial Pattern
Marketing
Product Design
Analytical models
Gross
High Power
Correlate
Analytical Model
Demonstrate
Economics

Keywords

  • Customer preference
  • Demand forecasting
  • Engineering design
  • Spatial panel model
  • Spatiotemporal heterogeneity

ASJC Scopus subject areas

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

Cite this

Bi, Y., Wang, M., Xie, J., Fu, Y., Sha, Z., & Chen, W. (2018). Modeling spatiotemporal heterogeneity of customer preferences in engineering design. In 44th Design Automation Conference (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2A-2018). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2018-86245
Bi, Youyi ; Wang, Mingxian ; Xie, Jian ; Fu, Yan ; Sha, Zhenghui ; Chen, Wei. / Modeling spatiotemporal heterogeneity of customer preferences in engineering design. 44th Design Automation Conference. American Society of Mechanical Engineers (ASME), 2018. (Proceedings of the ASME Design Engineering Technical Conference).
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Bi, Y, Wang, M, Xie, J, Fu, Y, Sha, Z & Chen, W 2018, Modeling spatiotemporal heterogeneity of customer preferences in engineering design. in 44th Design Automation Conference. Proceedings of the ASME Design Engineering Technical Conference, vol. 2A-2018, American Society of Mechanical Engineers (ASME), ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2018, Quebec City, Canada, 8/26/18. https://doi.org/10.1115/DETC2018-86245

Modeling spatiotemporal heterogeneity of customer preferences in engineering design. / Bi, Youyi; Wang, Mingxian; Xie, Jian; Fu, Yan; Sha, Zhenghui; Chen, Wei.

44th Design Automation Conference. American Society of Mechanical Engineers (ASME), 2018. (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2A-2018).

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

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AB - Customer preferences are found to evolve over time and correlate with geographical locations. Studying spatiotemporal heterogeneity of customer preferences is crucial to engineering design as it provides a dynamic perspective for a thorough understanding of preference trend. However, existing analytical models for demand modeling do not take the spatiotemporal heterogeneity of customer preferences into consideration. To fill this research gap, a spatial panel modeling approach is developed in this study to investigate the spatiotemporal heterogeneity of customer preferences by introducing engineering attributes explicitly as model inputs in support of demand forecasting in engineering design. In addition, a step-by-step procedure is proposed to aid the implementation of the approach. To demonstrate this approach, a case study is conducted on small SUV in China’s automotive market. Our results show that small SUVs with lower prices, higher power, and lower fuel consumption tend to have a positive impact on their sales in each region. In understanding the spatial patterns of China’s small SUV market, we found that each province has a unique spatial specific effect influencing the small SUV demand, which suggests that even if changing the design attributes of a product to the same extent, the resulting effects on product demand might be different across different regions. In understanding the underlying social-economic factors that drive the regional differences, it is found that Gross Domestic Product (GDP) per capita, length of paved roads per capita and household consumption expenditure have significantly positive influence on small SUV sales. These results demonstrate the potential capability of our approach in handling spatial variations of customers for product design and marketing strategy development. The main contribution of this research is the development of an analytical approach integrating spatiotemporal heterogeneity into demand modeling to support engineering design.

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Bi Y, Wang M, Xie J, Fu Y, Sha Z, Chen W. Modeling spatiotemporal heterogeneity of customer preferences in engineering design. In 44th Design Automation Conference. American Society of Mechanical Engineers (ASME). 2018. (Proceedings of the ASME Design Engineering Technical Conference). https://doi.org/10.1115/DETC2018-86245