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Using Kansei Engineering to Analyze Consumers’ Product Attribute Preferences

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Advances in Ergonomics in Design (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 261))

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Abstract

In the online shopping environment, consumers cannot access real products. Graphical information becomes the actual carrier of multi-dimensional attributes such as product functions, appearance, brand, concept, after-sales, and publicity, and establishes a comprehensive product image in the user’s brain. Those information affect consumers’ decisions such as purchase, collection or abandonment. This article take smartphone as an example, collect a wide range of smartphone attributes samples and kansei words. Based on kansei engineering and quantitative theory type I, a mathematical model between smartphone attributes and consumers’ preferences is built. This model will give reference for designers and can improve the accuracy of the online shopping recommendation system from another dimension.

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Acknowledgments

This paper is supported by Science and Technology on Avionics Integration Laboratory and Aeronautical Science Fund (No. 201913069001).

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Authors and Affiliations

  1. School of Mechanical Engineering, Southeast University, Nanjing, 211189, China

    Tongzhou Jiang, Lei Zhou & Chengqi Xue

  2. Chinese Flight Test Establishment, Xi’an, 710089, China

    Chao Yang

Authors
  1. Tongzhou Jiang
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  2. Chao Yang
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  3. Lei Zhou
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  4. Chengqi Xue
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Corresponding author

Correspondence to Lei Zhou .

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Editors and Affiliations

  1. Faculdade de Arquitetura, Universidade de Lisboa, Lisboa, Portugal

    Francisco Rebelo

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Jiang, T., Yang, C., Zhou, L., Xue, C. (2021). Using Kansei Engineering to Analyze Consumers’ Product Attribute Preferences. In: Rebelo, F. (eds) Advances in Ergonomics in Design. AHFE 2021. Lecture Notes in Networks and Systems, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-030-79760-7_118

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  • DOI: https://doi.org/10.1007/978-3-030-79760-7_118

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-79759-1

  • Online ISBN: 978-3-030-79760-7

  • eBook Packages: EngineeringEngineering (R0)

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