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Estimation of Unconscious Preference Judgment with Near-Infrared Spectroscopy

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Advances in Affective and Pleasurable Design (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 585))

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Abstract

Conventionally, methods to investigate preference decisions, such as questionnaires and interviews, are used for estimating consumer preferences. However, there are many uncertainties in human decision-making, and the reasons for decision-making provided by respondents are not necessarily consistent with their original reasons. In recent years, neuro-marketing, which measures the brain’s reactions and explores the process of consumers’ preference judgment, has attracted attention. Through neuro-marketing, it is possible to estimate preference based on brain activity, which is not based on the consumers’ conscious processing. As a result, potential preferences of consumers are clarified; these are expected to be useful for marketing research on newly marketed products and for development of new products. In this study, we reveal that there are changes in blood flow in the prefrontal cortex while viewing things of interest.

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Acknowledgments

We are deeply grateful to the members of Human Media Engineering Laboratory of the Faculty of Science and Technology, Chuo University, and the Kansei Robotics Research Center, for their participation in research discussions and collaboration in experiments.

This work was partially supported by a JSPS KAKENHI grant, “Research on Sensitivity Symbiosis Mechanism within Groups in Real Space/Information Space” (No. 25240043) and a TISE Research Grant from Chuo University, “KANSEI Robotics Environment”.

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Correspondence to Haruka Tanida .

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Tanida, H., Kato, T. (2018). Estimation of Unconscious Preference Judgment with Near-Infrared Spectroscopy. In: Chung, W., Shin, C. (eds) Advances in Affective and Pleasurable Design. AHFE 2017. Advances in Intelligent Systems and Computing, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-60495-4_22

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  • DOI: https://doi.org/10.1007/978-3-319-60495-4_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60494-7

  • Online ISBN: 978-3-319-60495-4

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