Inside the Mind: Using Neuroimaging to Understand Moral Product Preference Judgments Involving Sustainability

Trying to decide whether to purchase a sustainable product often puts decision makers in a difficult situation, especially if the more sustainable option provides less desirable features or costs a premium. This paper theorizes that adding sustainability as a variable during product choice evaluations create decisions that are moral choice scenarios, where benefit to society is weighed against personal gain. From an engineering design perspective, modeling user preferences in this context can be extremely difficult. While several methods exist to assist researchers in eliciting consumer preferences, the vast majority relies upon conscious input from the potential consumers themselves. More critically, these methods do not afford researchers the ability to understand the cognitive mechanisms underlying what someone may be feeling or thinking while these preference judgments are being made. In this work, functional magnetic resonance imaging (fMRI) is used to investigate the neural processes behind multi-attribute product preference judgments. In particular, this work centers on uncovering unique features of sustainable preference judgments: preference judgments that involve products for which the environmental impact is a known quantity. This work builds upon earlier work that investigated how preference judgments are altered in the context of sustainability. A deeper look at participant decision making at the time of judgment is examined using neuroimaging with the goal of providing actionable insights for designers and product developers. [DOI: 10.1115/1.4035859]

[1]  L. Shah,et al.  Functional magnetic resonance imaging. , 2010, Seminars in roentgenology.

[2]  Panos Y. Papalambros,et al.  Quantification of perceived environmental friendliness for vehicle silhouette design , 2010 .

[3]  L Eric,et al.  It ` s not easy being green : the effects of attribute tradeoffs on green product preference and choice , 2013 .

[4]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[5]  J. D. E. Gabrieli,et al.  Integration of diverse information in working memory within the frontal lobe , 2000, Nature Neuroscience.

[6]  M. Tarr,et al.  Activation of the middle fusiform 'face area' increases with expertise in recognizing novel objects , 1999, Nature Neuroscience.

[7]  Gregory S. Berns,et al.  Neural mechanisms of the influence of popularity on adolescent ratings of music , 2010, NeuroImage.

[8]  J. Cagan,et al.  A Meta-Analytic Approach for Uncovering Neural Activation Patterns of Sustainable Product Preference Decisions , 2017 .

[9]  G. Berns,et al.  A Neural Predictor of Cultural Popularity , 2010 .

[10]  S. Gilbert,et al.  Exploring the neurological basis of design cognition using brain imaging: some preliminary results , 2009 .

[11]  Jordan J. Louviere,et al.  VALIDATION OF A CHOICE MODEL INVOLVING GREEN PRODUCT CHOICE , 1999 .

[12]  Brian Knutson,et al.  Neural valuation of environmental resources , 2015, NeuroImage.

[13]  P. Stern,et al.  Personal and contextual influences on househould energy adaptations. , 1985 .

[14]  Shalom H. Schwartz,et al.  Normative explanations of helping behavior: A critique, proposal, and empirical test , 1973 .

[15]  C. Frith,et al.  Functional imaging of ‘theory of mind’ , 2003, Trends in Cognitive Sciences.

[16]  Jordan Grafman,et al.  Functional Networks in Emotional Moral and Nonmoral Social Judgments , 2002, NeuroImage.

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

[18]  Jonathan Cagan,et al.  Understanding Consumer Tradeoffs Between Form and Function Through Metaconjoint and Cognitive Neuroscience Analyses , 2013 .

[19]  Jonathan Cagan,et al.  The Impact of Sustainability on Consumer Preference Judgments of Product Attributes , 2015 .

[20]  Jonathan Cagan,et al.  Concurrent Optimization of Computationally Learned Stylistic Form and Functional Goals , 2012 .

[21]  Jonathan Cagan,et al.  Quantifying Aesthetic Form Preference in a Utility Function , 2008 .

[22]  Jan Derrfuss,et al.  Cognitive control in the posterior frontolateral cortex: evidence from common activations in task coordination, interference control, and working memory , 2004, NeuroImage.

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

[24]  Evelyn C. Ferstl,et al.  What Does the Frontomedian Cortex Contribute to Language Processing: Coherence or Theory of Mind? , 2002, NeuroImage.

[25]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[26]  Joshua D. Greene,et al.  How (and where) does moral judgment work? , 2002, Trends in Cognitive Sciences.

[27]  Satrajit S. Ghosh,et al.  Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python , 2011, Front. Neuroinform..

[28]  Shinobu Kitayama,et al.  Advancing consumer neuroscience , 2014 .

[29]  J. O'Doherty,et al.  Automatic and intentional brain responses during evaluation of trustworthiness of faces , 2002, Nature Neuroscience.

[30]  K. Vogeley,et al.  Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy , 2012, Brain Structure and Function.

[31]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[32]  Panos Y. Papalambros,et al.  Incorporating user shape preference in engineering design optimisation , 2011 .

[33]  Stephen M Fleming,et al.  Overcoming status quo bias in the human brain , 2010, Proceedings of the National Academy of Sciences.

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

[35]  R. Saxe,et al.  The neural basis of the interaction between theory of mind and moral judgment , 2007, Proceedings of the National Academy of Sciences.

[36]  Christophe Morin,et al.  Neuromarketing: The New Science of Consumer Behavior , 2011 .

[37]  Israel Liberzon,et al.  Decision neuroscience and consumer decision making , 2012 .

[38]  Brian Knutson,et al.  Interpretable Classifiers for fMRI Improve Prediction of Purchases , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  Jonathan Cagan,et al.  Experiential Conjoint Analysis: An Experience-Based Method for Eliciting, Capturing, and Modeling Consumer Preference , 2014 .

[40]  T. Heberlein The Land Ethic Realized: Some Social Psychological Explanations for Changing Environmental Attitudes1 , 1972 .

[41]  Thanh An Nguyen,et al.  ANALYSIS OF DESIGN ACTIVITIES USING EEG SIGNALS , 2010 .

[42]  Philip L. Smith,et al.  Psychology and neurobiology of simple decisions , 2004, Trends in Neurosciences.

[43]  A. Nederhof Methods of coping with social desirability bias: A review. , 1985 .

[44]  Mark W Woolrich,et al.  Associative learning of social value , 2008, Nature.

[45]  Ivanei E. Bramati,et al.  The Neural Correlates of Moral Sensitivity: A Functional Magnetic Resonance Imaging Investigation of Basic and Moral Emotions , 2002, The Journal of Neuroscience.

[46]  D. Yves von Cramon,et al.  The neural implementation of multi-attribute decision making: A parametric fMRI study with human subjects , 2006, NeuroImage.

[47]  Craig E. L. Stark,et al.  When zero is not zero: The problem of ambiguous baseline conditions in fMRI , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[48]  Henrik Walter,et al.  Cultural objects modulate reward circuitry , 2002, Neuroreport.

[49]  Jinjuan She,et al.  Priming Designers to Communicate Sustainability , 2012 .

[50]  R. Poldrack Can cognitive processes be inferred from neuroimaging data? , 2006, Trends in Cognitive Sciences.

[51]  A. Sanfey Social Decision-Making : Insights from Game Theory and Neuroscience , 2022 .

[52]  Corianne Rogalsky,et al.  Increased activation in the right insula during risk-taking decision making is related to harm avoidance and neuroticism , 2003, NeuroImage.

[53]  Yul-Wan Sung,et al.  Functional magnetic resonance imaging , 2004, Scholarpedia.

[54]  Troy D. Abel,et al.  A Value-Belief-Norm Theory of Support for Social Movements: The Case of Environmentalism , 1999 .

[55]  J. Cagan,et al.  Built to Love: Creating Products That Captivate Customers , 2010 .

[56]  S. Schwartz Normative Influences on Altruism , 1977 .

[57]  J. Mumford A power calculation guide for fMRI studies. , 2012, Social cognitive and affective neuroscience.

[58]  J. Zaichkowsky,et al.  Aesthetic package design: A behavioral, neural, and psychological investigation , 2010 .

[59]  Oshin Vartanian,et al.  Neuroanatomical correlates of aesthetic preference for paintings , 2004, Neuroreport.

[60]  西澤 由隆,et al.  面接調査におけるSocial Desirability Bias--その軽減へのfull-scale CASIの試み (特集 変化する政治,進化する政治学) , 2010 .

[61]  William A. Cunningham,et al.  Type I and Type II error concerns in fMRI research: re-balancing the scale. , 2009, Social cognitive and affective neuroscience.

[62]  Panos Y. Papalambros,et al.  Preference Inconsistency in Multidisciplinary Design Decision Making , 2007, DAC 2007.

[63]  S. Huettel,et al.  A nexus model of the temporal–parietal junction , 2013, Trends in Cognitive Sciences.

[64]  A. Gutchess,et al.  A Functional Magnetic Resonance Imaging Study of Neural Dissociations between Brand and Person Judgments , 2006 .

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

[66]  Bruce D. McCandliss,et al.  The visual word form area: expertise for reading in the fusiform gyrus , 2003, Trends in Cognitive Sciences.

[67]  Jinjuan She,et al.  Trigger Features on Prototypes Increase Preference for Sustainability , 2013 .

[68]  Jonathan Cagan,et al.  Using Neuroimaging to Understand Moral Product Preference Judgments Involving Sustainability , 2016 .

[69]  P. Stern New Environmental Theories: Toward a Coherent Theory of Environmentally Significant Behavior , 2000 .

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

[71]  M. Guha The Sage Encyclopedia of Social Science Research Methods , 2005 .