ArticlePloS one2018
An fNIRS-based investigation of visual merchandising displays for fashion stores.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Wearable Functional Near-Infrared Spectroscopy (fNIRS) Monitoring of Prefrontal Activation and Connectivity During Purpose-Driven Consumption.Sensors (Basel, Switzerland) · 2026Article
- The ethical, legal and social issues of neuroergonomics in the workplace.Frontiers in neuroergonomics · 2026Article
- Detection of Mild Cognitive Impairment Using Convolutional Neural Network: Temporal-Feature Maps of Functional Near-Infrared Spectroscopy.Frontiers in aging neuroscience · 2020Article
- Reduction of Onset Delay in Functional Near-Infrared Spectroscopy: Prediction of HbO/HbR Signals.Frontiers in neurorobotics · 2020Article
- Is consumer neural response to visual merchandising types different depending on their fashion involvement?PloS one · 2020Observational
- Measuring dlPFC Signals to Predict the Success of Merchandising Elements at the Point-of-Sale - A fNIRS Approach.Frontiers in neuroscience · 2020Article
- An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study.Frontiers in neuroscience · 2020Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper investigates a brain-based approach for visual merchandising display (VMD) in fashion stores. In marketing, VMD has become a research topic of interest. However, VMD research using brain activation information is rare. We examine the hemodynamic responses (HRs) in the prefrontal cortex (PFC) using functional near-infrared spectroscopy (fNIRS) while positive/negative displays of four stores (menswear, womenswear, underwear, and sportswear) are shown to 20 subjects. As features for classifying the HRs, the mean, variance, peak, skewness, kurtosis, t-value, and slope of the signals for a 20-sec time window for the activated channels are analyzed. Linear discriminant analysis is used for classifying two-class (positive and negative displays) and four-class (four fashion stores) models. PFC brain activation maps based on t-values depicting the data from the 16 channels are provided. In the two-class classification, the underwear store had the highest average classification result of 67.04%, whereas the menswear store had the lowest value of 64.15%. Men's classification accuracy for the underwear stores with positive and negative displays was 71.38%, whereas the highest classification accuracy obtained by women for womenswear stores was 73%. The average accuracy over the 20 subjects for positive displays was 50.68%, while that of negative displays was 51.07%. Therefore, these findings suggest that human brain activation is involved in the evaluation of the fashion store displays. It is concluded that fNIRS can be used as a brain-based tool in the evaluation of fashion stores in a daily life environment.
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