Abstract
This paper explores the use of neuroimaging data to inform results from a preference decision study involving product sustainability. Neurosynth, a meta-analytic database of functional magnetic resonance imaging (fMRI) studies, was used to extract regions of interest (ROIs) for cross comparison with an empirically collected fMRI dataset. The tasks for the empirically collected fMRI dataset were product preference decisions involving sustainability. In particular, participants were engaged in preference judgments separated into two conditions; one with and one without calculated environmental impact values displayed alongside each design alternative. Extracted meta-analytic ROIs were generated based upon keywords (moral, emotion, etc.) from hypotheses on the ways individuals formulate opinions regarding the environment. Furthermore, additional keywords were seeded based on the results of a whole-brain fMRI analysis. Results indicate the important role of moral reasoning and theory of mind processing in product evaluations within social choice domains, such as sustainability.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bartra O, McGuire JT, Kable JW (2013) The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. NeuroImage 76:412–427. doi:10.1016/j.neuroimage.2013.02.063
Bernstein W, Ramanujan D, Devanathan S, Fu Z, Sutherland J, Ramani K (2010) Function impact matrix for sustainable concept generation: a designer’s perspective (DETC2010-28340). In: Proceedings ASME 2010 international design engineering and technical conferences, pp 377–383
Blamey RK, Bennett JW, Louviere JJ, Morrison MD (1999) Validation of choice model involving green product choice. Choice modelling research reports no. 10. University of New South Wales, Canberra
Boatwright P, Cagan J (2010) Built to love, 1st edn. Berrett-Koehler Publishers Inc, San Francisco
Consultants P (2000) Eco-indicator 99 manual for designers. Ministry of housing, spatial planning and the environment (October). http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Eco-indicator+99+Manual+for+Designers#0
Cox RW (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res Int J 29(3):162–173. doi:10.1006/cbmr.1996.0014
Devanathan S, Ramanujan D, Bernstein WZ, Zhao F, Ramani K (2010) Integration of sustainability into early design through the function impact matrix. J Mech Des 132(8):081004. doi:10.1115/1.4001890
Fisher R (1925) Statistical methods for research workers. Biol Monogr Man. doi:10.1056/NEJMc061160
Fitzgerald DP, Herrmann JW, Schmidt LC (2010) A conceptual design tool for resolving conflicts between product functionality and environmental impact. J Mech Des 132(9):091006. doi:10.1115/1.4002144
Fleming SM, Thomas CL, Dolan RJ (2010) Overcoming status quo bias in the human brain. Proc Natl Acad Sci USA 107(13):6005–6009. doi:10.1073/pnas.0910380107
Goucher-Lambert K, Cagan J (2015) The impact of sustainability on consumer preference judgments of product attributes. J Mech Des 137(August):1–11. doi:10.1115/1.4030271
Goucher-Lambert K, Moss J, Cagan J (2016) The truth in the decision: using neuroimaging to understand multi-attribute product preference judgements involving sustainability. J Mech Des (Submitted) 1–11
Greene J, Haidt J (2002) How (and where) does moral judgment work? Trends Cognit Sci. doi:10.1016/S1364-6613(02)02011-9
Greene JD, Sommerville RB, Nystrom LE, Darley JM, Cohen JD (2001) An fMRI investigation of emotional engagement in moral judgment. Science 293(5537):2105–2108. doi:10.1126/science.1062872
Huettel SA, Song AW, McCarthy G (2004) Functional magnetic resonance imaging. ISBN: 0878932887
Macdonald E (2012) Seven cognitive concepts for successful sustainable design (DETC2012-70676). In: ASME 2012 international design engineering technical conferences 1–16
MacDonald E, Gonzalez R, Papalambros PY (2009) Preference inconsistency in multidisciplinary design decision making. J Mech Des 131(3):031009. doi:10.1115/1.3066526
Masui K, Sakao T, Kobayashi M, Inaba A (2003) Applying quality function deployment to environmentally conscious design. Int J Qual Reliab Manag 20(1):90–106
Moss J, Schunn CD (2015) Comprehension through explanation as the interaction of the brain’s coherence and cognitive control networks. Front Hum Neurosci 9(October):1–17. doi:10.3389/fnhum.2015.00562
Nederhof AJ (1985) Methods of coping with social desirability bias: a review. Eur J Soc Psychol 15(3):263–280
Orsborn S, Cagan J, Boatwright P (2009) Quantifying aesthetic form preference in a utility function. J Mech Des 131(6):061001. doi:10.1115/1.3116260
Peattie K, Belz F-M (2010) Sustainability marketing—an innovative conception of marketing. Mark Rev St. Gallen 27(5):8–15. doi:10.1007/s11621-010-0085-7
Peattie K, Charter M (2003) Green marketing. The Marketing Book 726–755. ISBN: 9780874216561
Poldrack RA (2007) Region of interest analysis for fMRI. Soc Cogn Affect Neurosci 2(1):67–70. doi:10.1093/scan/nsm006
Ramani K, Ramanujan D, Bernstein WZ, Zhao F, Sutherland J, Handwerker C, Thurston D (2010) Integrated sustainable life cycle design: a REVIEW. J Mech Des 132(9):091004. doi:10.1115/1.4002308
Reid TN, Gonzalez RD, Papalambros PY (2010) Quantification of perceived environmental friendliness for vehicle silhouette design. J Mech Des. doi:10.1115/1.4002290
Sawe N, Knutson B (2015) Neural valuation of environmental resources. NeuroImage. doi:10.1016/j.neuroimage.2015.08.010
She J, MacDonald E (2013) Priming designers to communicate sustainability. J Mech Des 136(1):011001
Spector P (2004) Social desirability bias. In: The SAGE encyclopedia of social science research methods, 1045–1046. doi:10.1002/9781444316568
Sylcott B, Cagan J, Tabibnia G (2013) Understanding consumer tradeoffs between Form and function through metaconjoint and cognitive neuroscience analyses. J Mech Des 135(10):101002
Yarkoni T, Poldrack RA, Nichols TE, Van Essen DC, Wager TD (2011) Large-scale automated synthesis of human functional neuroimaging data. Nat Methods 8(8):665–670. doi:10.1038/nmeth.1635
Zysset S, Wendt CS, Volz KG, Neumann J, Huber O, von Cramon DY (2006) The neural implementation of multi-attribute decision making: a parametric fMRI study with human subjects. NeuroImage 31(3):1380–1388
Acknowledgements
The authors would like to thank the staff at the Carnegie Mellon University Scientific Imaging and Brain Research Center for their support during fMRI data acquisition. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant DGE125252 and the National Science Foundation under Grant CMMI1233864.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing Switzerland
About this paper
Cite this paper
Goucher-Lambert, K., Moss, J., Cagan, J. (2017). A Meta-Analytic Approach for Uncovering Neural Activation Patterns of Sustainable Product Preference Decisions. In: Gero, J. (eds) Design Computing and Cognition '16. Springer, Cham. https://doi.org/10.1007/978-3-319-44989-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-44989-0_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44988-3
Online ISBN: 978-3-319-44989-0
eBook Packages: EngineeringEngineering (R0)