The application of mobile fNIRS to “shopper neuroscience” – first insights from a merchandising communication study

Purpose This study is the first to examine consumer’s neural reaction to different merchandising communication strategies at the point-of-sale (PoS) by applying functional near-infrared spectroscopy (fNIRS). By doing so, the purpose of this study is to extend consumer neuroscience to retail and shopper research. Design/methodology/approach Two experiments were conducted in which 36 shoppers were exposed to a realistic grocery shopping scenario while their brain haemodynamics were measured using mobile fNIRS. Findings Results revealed that mobile fNIRS appears a valid method to study neural activation of the prefrontal cortex (PFC) in the field of “shopper neuroscience”. More precisely, results demonstrated that the orbitofrontal cortex (OFC) might be crucial for processing and predicting merchandising communication strategy effectiveness. Research limitations/implications This research gives evidence that certain regions of the PFC, in particular the OFC and the dorsolateral prefrontal cortex (dlPFC), are crucial to process and evaluate merchandising communication strategies. Practical implications The current work opens a promising new avenue for studying and understanding shopper’s behaviour. Mobile fNIRS enables marketing management to collect neural data from shoppers and analyse neural activity associated with real-life settings. Furthermore, based on a better understanding of shoppers’ perceptual processes of communication strategies, marketers can design more effective merchandising communication strategies. Originality/value The study is the first to implement the innovative, mobile neuroimaging method of fNIRS to a PoS setting. It, therefore, opens up the promising field of “shopper neuroscience”.

[1]  J. Kable The cognitive neuroscience toolkit for the neuroeconomist: A functional overview. , 2011, Journal of neuroscience, psychology, and economics.

[2]  Karl J. Friston Causal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging , 2009, PLoS biology.

[3]  P. Goldman-Rakic,et al.  Noise stress impairs prefrontal cortical cognitive function in monkeys: evidence for a hyperdopaminergic mechanism. , 1998, Archives of general psychiatry.

[4]  S. Arridge,et al.  Estimation of optical pathlength through tissue from direct time of flight measurement , 1988 .

[5]  Daniel Tranel,et al.  Prefrontal cortex damage abolishes brand-cued changes in cola preference. , 2008, Social cognitive and affective neuroscience.

[6]  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.

[7]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited—Again , 1995, NeuroImage.

[8]  G. Muruganantham,et al.  A Review of Impulse Buying Behavior , 2013 .

[9]  S. Kapur,et al.  The seats of reason? An imaging study of deductive and inductive reasoning , 1997, Neuroreport.

[10]  David F. Larcker,et al.  Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics: , 1981 .

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

[12]  G. Loewenstein,et al.  Neural Predictors of Purchases , 2007, Neuron.

[13]  K. Kubota,et al.  Cortical Mapping of Gait in Humans: A Near-Infrared Spectroscopic Topography Study , 2001, NeuroImage.

[14]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[15]  Atsushi Maki,et al.  Noninvasive imaging of prefrontal activation during attention-demanding tasks performed while walking using a wearable optical topography system. , 2010, Journal of biomedical optics.

[16]  T. Meyvis,et al.  Using Single-Neuron Recording in Marketing: Opportunities, Challenges, and an Application to Fear Enhancement in Communications , 2015 .

[17]  P. Kenning,et al.  NeuroEconomics: An overview from an economic perspective , 2005, Brain Research Bulletin.

[18]  Karl J. Friston Experimental Design and Statistical Parametric Mapping , 2003 .

[19]  Claudio Babiloni,et al.  Human cortical responses during one-bit delayed-response tasks: An fMRI study , 2005, Brain Research Bulletin.

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

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

[22]  W. Kaiser,et al.  Challenging the anterior attentional system with a continuous performance task: a functional magnetic resonance imaging approach , 1998, European Archives of Psychiatry and Clinical Neuroscience.

[23]  Steven Tompson,et al.  Functional brain imaging predicts public health campaign success. , 2016, Social cognitive and affective neuroscience.

[24]  P. Kenning,et al.  Utilitarian and Hedonic Motivators of Shoppers’ Decision to Consult with Salespeople , 2014 .

[25]  C. Spence,et al.  The Perfect Meal: The Multisensory Science of Food and Dining , 2014 .

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

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

[28]  Christopher P. Puto,et al.  The Framing of Buying Decisions , 1987 .

[29]  C. Curtis,et al.  Persistent activity in the prefrontal cortex during working memory , 2003, Trends in Cognitive Sciences.

[30]  Colin Camerer,et al.  Neuroeconomics: How Neuroscience Can Inform Economics , 2005 .

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

[32]  M. Just,et al.  The framing effect and risky decisions: Examining cognitive functions with fMRI , 2005 .

[33]  William H. Hampton,et al.  Predicting Advertising success beyond Traditional Measures: New Insights from Neurophysiological Methods and Market Response Modeling , 2015 .

[34]  C. Vaidya,et al.  Sensitivity of fNIRS to cognitive state and load , 2014, Front. Hum. Neurosci..

[35]  Hilke Plassmann,et al.  Anterior cingulate reflects susceptibility to framing during attractiveness evaluation , 2007, Neuroreport.

[36]  Colin Camerer,et al.  Self-control in decision-making involves modulation of the vmPFC valuation system , 2009, NeuroImage.

[37]  P. Kenning,et al.  A current overview of consumer neuroscience , 2008 .

[38]  Ale Smidts,et al.  Brain Responses to Movie Trailers Predict Individual Preferences for Movies and Their Population-Wide Commercial Success , 2015 .

[39]  Peter E. Rossi,et al.  Planning to Make Unplanned Purchases? The Role of In-Store Slack in Budget Deviation , 2010 .

[40]  Angelika Dimoka,et al.  What Does the Brain Tell Us About Trust and Distrust? Evidence from a Functional Neuroimaging Study , 2010, MIS Q..

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

[42]  J. O'Doherty,et al.  Orbitofrontal Cortex Encodes Willingness to Pay in Everyday Economic Transactions , 2007, The Journal of Neuroscience.

[43]  Hiroki Sato,et al.  A NIRS–fMRI investigation of prefrontal cortex activity during a working memory task , 2013, NeuroImage.

[44]  J. Duncan,et al.  Common regions of the human frontal lobe recruited by diverse cognitive demands , 2000, Trends in Neurosciences.

[45]  Karl J. Friston,et al.  Network discovery with DCM , 2011, NeuroImage.

[46]  T. Daugherty,et al.  Research in reverse: Ad testing using an inductive consumer neuroscience approach , 2016 .

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

[48]  Yong Zhang,et al.  Consumer product evaluation: the interactive effect of message framing, presentation order, and source credibility , 2000 .

[49]  Elliot T. Berkman,et al.  Neural activity during health messaging predicts reductions in smoking above and beyond self-report. , 2011, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[50]  P. W. Mccormick,et al.  Intracerebral penetration of infrared light. Technical note. , 1992, Journal of neurosurgery.

[51]  Nadine Gier,et al.  Beyond Traditional Neuroimaging: Can Mobile fNIRS Add to NeuroIS? , 2018 .

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

[53]  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.

[54]  E. Maguire,et al.  Decoding human brain activity during real-world experiences , 2007, Trends in Cognitive Sciences.

[55]  V. Schmithorst,et al.  Changes in neuronal activation with increasing attention demand in healthy volunteers: An fMRI study , 2001, Synapse.

[56]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[57]  Doug Walker,et al.  Spontaneous selection: The influence of product and retailing factors on consumer impulse purchases , 2012 .

[58]  Simone Kühn,et al.  The neural correlates of subjective pleasantness , 2012, NeuroImage.

[59]  M Petrides,et al.  Orbitofrontal cortex: A key prefrontal region for encoding information. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[60]  Daniel T. Knoepfle,et al.  Value Computations in Ventral Medial Prefrontal Cortex during Charitable Decision Making Incorporate Input from Regions Involved in Social Cognition , 2010, The Journal of Neuroscience.

[61]  Joseph W. Kable,et al.  The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value , 2013, NeuroImage.

[62]  Jonathan D. Cohen,et al.  An fMRI Investigation of Emotional Engagement in Moral Judgment , 2001, Science.

[63]  P. Hancock,et al.  Noise effects on human performance: a meta-analytic synthesis. , 2011, Psychological bulletin.

[64]  A. Eke,et al.  The modified Beer–Lambert law revisited , 2006, Physics in medicine and biology.

[65]  Benedetta Grandi,et al.  Does Shopping Preparation influence Consumer Buying Decisions , 2016 .

[66]  Hilke Plassmann,et al.  Nonlinear Responses Within the Medial Prefrontal Cortex Reveal When Specific Implicit Information Influences Economic Decision Making , 2005, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[67]  Daniel Corsten,et al.  From point-of-purchase to path-to-purchase: How pre-shopping factors drive unplanned buying , 2011 .

[68]  P. Halligan,et al.  The relevance of behavioural measures for functional-imaging studies of cognition , 2004, Nature Reviews Neuroscience.

[69]  J. Wallis Orbitofrontal cortex and its contribution to decision-making. , 2007, Annual review of neuroscience.

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

[71]  Rosellina Ferraro,et al.  The Interplay among Category Characteristics, Customer Characteristics, and Customer Activities on in-Store Decision Making , 2009 .

[72]  K. Kubota,et al.  Synchronous activity of two people's prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy. , 2011, Journal of biomedical optics.