Can neuromarketing add value to the traditional marketing research? An exemplary experiment with functional near-infrared spectroscopy (fNIRS)

Abstract Whether neuromarketing methods can add value to marketing research depends on their cost-utility ratio and their ability to offer hidden information that cannot be obtained using other marketing research methods. Due to the limitations of functional magnetic resonance imaging (fMRI) for real-world situations and its high costs, the aim of this study was to examine the feasibility of a mobile functional near-infrared spectroscopy (fNIRS) system. Two experiments dealing with brands and labels are used to discuss how and if neuromarketing can enrich marketing research and to what extent existing limitations and challenges can be overcome. In both experiments, differences in prefrontal cortex activity were measured. Thus, it is possible to measure brand- and label-related prefrontal cortex activation using fNIRS. As fNIRS is mobile and allows for experiments outside the laboratory, this considerably expands the field of usage of neuroimaging processes and can therefore decrease the costs of neuroimaging.

[1]  Gary H. Glover,et al.  A quantitative comparison of NIRS and fMRI across multiple cognitive tasks , 2011, NeuroImage.

[2]  João Ricardo Sato,et al.  fNIRS Optodes’ Location Decider (fOLD): a toolbox for probe arrangement guided by brain regions-of-interest , 2018, Scientific Reports.

[3]  Ariel Telpaz,et al.  Using EEG to Predict Consumers’ Future Choices , 2015 .

[4]  A. Lawrence,et al.  Individual Differences in Reward Drive Predict Neural Responses to Images of Food , 2006, The Journal of Neuroscience.

[5]  M. Tamura,et al.  Interpretation of near-infrared spectroscopy signals: a study with a newly developed perfused rat brain model. , 2001, Journal of applied physiology.

[6]  E. Rolls,et al.  Value, Pleasure and Choice in the Ventral Prefrontal Cortex , 2022 .

[7]  Toshinori Kato,et al.  Functional brain imaging using near-infrared spectroscopy during actual driving on an expressway , 2013, Front. Hum. Neurosci..

[8]  Martin Wolf,et al.  Different Time Evolution of Oxyhemoglobin and Deoxyhemoglobin Concentration Changes in the Visual and Motor Cortices during Functional Stimulation: A Near-Infrared Spectroscopy Study , 2002, NeuroImage.

[9]  Judith Lynne Zaichkowsky,et al.  Novel versus familiar brands: An analysis of neurophysiology, response latency, and choice , 2012, Marketing Letters.

[10]  Leslie G. Ungerleider,et al.  Involvement of human left dorsolateral prefrontal cortex in perceptual decision making is independent of response modality , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[11]  C. Julien The enigma of Mayer waves: Facts and models. , 2006, Cardiovascular research.

[12]  Christopher L. Newman,et al.  Twenty Years of Country-of-Origin Food Labeling Research , 2014 .

[13]  Jennifer A. Silvers,et al.  The neural bases of uninstructed negative emotion modulation. , 2015, Social cognitive and affective neuroscience.

[14]  Nick Lee,et al.  Welcome to the jungle! The neuromarketing literature through the eyes of a newcomer , 2018 .

[15]  Nicolas Merz,et al.  Consumer preferences for organic labels in Germany using the example of apples – Combining choice-based conjoint analysis and eye-tracking measurements , 2018 .

[16]  Arcangelo Merla,et al.  Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks , 2015, Journal of visualized experiments : JoVE.

[17]  Lia Maria Hocke,et al.  Automated Processing of fNIRS Data—A Visual Guide to the Pitfalls and Consequences , 2018, Algorithms.

[18]  Marco Ferrari,et al.  A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application , 2012, NeuroImage.

[19]  Frédéric Dehais,et al.  Detecting Pilot's Engagement Using fNIRS Connectivity Features in an Automated vs. Manual Landing Scenario , 2018, Front. Hum. Neurosci..

[20]  Leif D. Nelson,et al.  From “Where” to “What”: Distributed Representations of Brand Associations in the Human Brain , 2015, JMR, Journal of marketing research.

[21]  Fabian Simmank,et al.  Organic or popular brands—food perception engages distinct functional pathways. An fMRI study , 2017 .

[22]  Matthias J. Wieser,et al.  Auditory cortex activation is modulated by emotion: A functional near-infrared spectroscopy (fNIRS) study , 2011, NeuroImage.

[23]  Theodore J Huppert,et al.  Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy. , 2016, Neurophotonics.

[24]  Peter Kenning,et al.  The application of mobile fNIRS to “shopper neuroscience” – first insights from a merchandising communication study , 2018 .

[25]  Ilias Tachtsidis,et al.  False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward , 2016, Neurophotonics.

[26]  Klaus-Robert Müller,et al.  Enhanced Performance by a Hybrid Nirs–eeg Brain Computer Interface , 2022 .

[27]  S. Meyerding Consumer preferences for food labels on tomatoes in Germany – A comparison of a quasi-experiment and two stated preference approaches , 2016, Appetite.

[28]  F. Jöbsis Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. , 1977, Science.

[29]  Simone Kühn,et al.  Multiple “buy buttons” in the brain: Forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI , 2016, NeuroImage.

[30]  Nicolas S. Linder,et al.  Organic labeling influences food valuation and choice , 2010, NeuroImage.

[31]  Achim Spiller,et al.  Characterising convinced sustainable food consumers , 2015 .

[32]  J. E. Korteling,et al.  Using neurophysiological signals that reflect cognitive or affective state: six recommendations to avoid common pitfalls , 2015, Front. Neurosci..

[33]  Murat Perit Çakir,et al.  An investigation of the neural correlates of purchase behavior through fNIRS , 2018 .

[34]  Kazuo Hiraki,et al.  Near-infrared spectroscopy (NIRS) in functional research of prefrontal cortex , 2015, Front. Hum. Neurosci..

[35]  Lucas R. Trambaiolli,et al.  Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments , 2017, Front. Hum. Neurosci..

[36]  J. O'Doherty,et al.  Neural Responses during Anticipation of a Primary Taste Reward , 2002, Neuron.

[37]  U. Shahani,et al.  Habituation-like Effects Cause a Significant Decrease in Response in MRI Neuroactivation During Visual Stimulation , 1997, Vision Research.

[38]  Andreas J Fallgatter,et al.  Affective perception and imagery: A NIRS study. , 2011, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[39]  D. Ariely,et al.  Neuromarketing: the hope and hype of neuroimaging in business , 2010, Nature Reviews Neuroscience.

[40]  D. Kennedy,et al.  The application of near infrared spectroscopy in nutritional intervention studies , 2013, Front. Hum. Neurosci..

[41]  C. Spence Neuroscience-Inspired Design: From Academic Neuromarketing to Commercially Relevant Research , 2019 .

[42]  J. O'Doherty,et al.  Marketing actions can modulate neural representations of experienced pleasantness , 2008, Proceedings of the National Academy of Sciences.

[43]  J. Hirsch,et al.  The present and future use of functional near‐infrared spectroscopy (fNIRS) for cognitive neuroscience , 2018, Annals of the New York Academy of Sciences.

[44]  S. Kühn,et al.  Does Taste Matter? How Anticipation of Cola Brands Influences Gustatory Processing in the Brain , 2013, PloS one.

[45]  David A. Boas,et al.  Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial , 2015, Neurophotonics.

[46]  Hilke Plassmann,et al.  Branding the brain: A critical review and outlook , 2012 .

[47]  R. Poldrack Inferring Mental States from Neuroimaging Data: From Reverse Inference to Large-Scale Decoding , 2011, Neuron.

[48]  Scott A. Huettel,et al.  Consumer Neuroscience: Applications, Challenges, and Possible Solutions , 2015 .

[49]  Samuel M. McClure,et al.  Neural Correlates of Behavioral Preference for Culturally Familiar Drinks , 2004, Neuron.

[50]  Hellmuth Obrig,et al.  A wearable multi-channel fNIRS system for brain imaging in freely moving subjects , 2014, NeuroImage.

[51]  Tom Chau,et al.  Decoding subjective preference from single-trial near-infrared spectroscopy signals , 2009, Journal of neural engineering.

[52]  M. Ferrari,et al.  Continuous non invasive monitoring of human brain by near infrared spectroscopy. , 1985, Advances in experimental medicine and biology.

[53]  Martin Wolf,et al.  A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology , 2014, NeuroImage.

[54]  Ann-Christine Ehlis,et al.  Enhancement of activity of the primary visual cortex during processing of emotional stimuli as measured with event‐related functional near‐infrared spectroscopy and event‐related potentials , 2008, Human brain mapping.

[55]  Siamac Fazli,et al.  Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI , 2015, Pattern Recognit..

[56]  Sungho Tak,et al.  Statistical analysis of fNIRS data: A comprehensive review , 2014, NeuroImage.

[57]  Hannah Jones,et al.  Organic food: What we know (and do not know) about consumers , 2010, Renewable Agriculture and Food Systems.

[58]  Peter Kenning,et al.  Near-infrared spectroscopy (NIRS) as a new tool for neuroeconomic research , 2014, Front. Hum. Neurosci..

[59]  Fabian Grabenhorst,et al.  How cognition modulates affective responses to taste and flavor: top-down influences on the orbitofrontal and pregenual cingulate cortices. , 2008, Cerebral cortex.