0
Research Papers

Understanding Consumer Tradeoffs Between Form and Function Through Metaconjoint and Cognitive Neuroscience Analyses

[+] Author and Article Information
Brian Sylcott

e-mail: sylcott@alumni.cmu.edu

Jonathan Cagan

e-mail: cagan@cmu.edu
Department of Mechanical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15213

Golnaz Tabibnia

Department of Social & Decision Sciences,
Carnegie Mellon University,
Pittsburgh, PA 15213
e-mail: tabibnia@uci.edu

Contributed by the Design Theory and Methodology Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received April 5, 2012; final manuscript received June 28, 2013; published online August 7, 2013. Assoc. Editor: Wei Chen.

J. Mech. Des 135(10), 101002 (Aug 07, 2013) (13 pages) Paper No: MD-12-1194; doi: 10.1115/1.4024975 History: Received April 05, 2012; Revised June 28, 2013

This work investigates how consumers make preference judgments when taking into account both product form and function. In prior work, where aesthetic preference is quantified using visual conjoint methods, aesthetic preference and functional preference were handled separately. Here, we introduce a new methodology, metaconjoint analysis, for testing the hypothesis that when consumers make decisions taking into account both a product's form and its function they employ a more complex decision-making strategy than when basing their decisions on form or function alone. We anticipate that this strategy will involve both analytical and emotional processes. When compared with participant ratings of form and function combinations across 28 subjects, the metaconjoint model is shown to have a correlation that was not statistically different from an additive model of form and function. However, unlike the additive model, the metaconjoint model gave additional information about how participants make tradeoffs between form and function. Next, we developed a novel paradigm using functional magnetic resonance imaging (fMRI) to determine what parts of the brain are primarily involved with a given tradeoff between form and function. While in the scanner, study participants were asked to make decisions in trials where only form varied, where only function varied, and where both form and function varied. Results from 14 participants suggest that choices based on products that vary in both form and function involve some unique and some common brain networks as compared to choices based on form or function alone; notably, emotion-related regions are activated during these complex decisions where form and function are in conflict. These results are consistent with the inclusion of emotion in decision-making with regards to product choice and demonstrate the feasibility of using fMRI to address questions about the mental processes underlying consumer decisions. Studying preference decisions together with their accompanying neurological activity will give engineers and designers greater insight into the consumer decision-making process.

Copyright © 2013 by ASME
Your Session has timed out. Please sign back in to continue.

References

Boatwright, P., and Cagan, J., 2010, Built to Love: Creating Products that Captivate Customers, Berrett-Koehler Publishers, San Francisco, CA.
Payne, J. W., Bettman, J. R., and Johnson, E. J., 1988, “Adaptive Strategy Selection in Decision Making,” J. Exp. Psychol. Learn. Mem. Cogn., 14(3), pp. 534–552. [CrossRef]
Payne, J. W., Bettman, J. R., and Johnson, E. J., 1993, The Adaptive Decision Maker, Cambridge University Press, Cambridge.
Damasio, A. R., 1994, Descartes' Error: Emotion, Reason, and the Human Brain, Putnam, New York.
Loewenstein, G. F., Weber, E. U., Hsee, C. K., and Welch, N., 2001, “Risk as Feelings,” Psycholog. Bull., 127(2), pp. 267–286. [CrossRef]
Bettman, J., Luce, M., and Payne, J., 1998, “Constructive Consumer Choice Processes,” J. Consum. Res., 25(3), pp. 187–217. [CrossRef]
Shiv, B., and Fedorikhin, A., 1999, “Heart and Mind in Conflict: The Interplay of Affect and Cognition in Consumer Decision Making,” J. Consum. Res., 26(3), pp. 278–292. [CrossRef]
Isen, A. M., 2001, “An Influence of Positive Affect on Decision Making in Complex Situations: Theoretical Issues With Practical Implications,” J. Consum. Psychol., 11(2), pp. 75–85. [CrossRef]
Coricelli, G., Dolan, R. J., and Sirigu, A., 2007, “Brain, Emotion and Decision Making: The Paradigmatic Example of Regret,” Trends Cogn. Sci., 11(6), pp. 258–265. [CrossRef]
Slovic, P., Finucane, M., PetersE., and Macgregor, D., 2007, “The Affect Heuristic,” Eur. J. Oper. Res., 177(3), pp. 1333–1352. [CrossRef]
Luce, D. R., and Tukey, J. W., 1964, “Simultaneous Conjoint Measurement: A New Type of Fundamental Measurement,” J. Math. Psychol., 1(1), pp. 1–27. [CrossRef]
Orsborn, S., Cagan, J., and Boatwright, P., 2009, “Quantifying Aesthetic Form Preference in a Utility Function,” J. Mech. Des., 131(6), p. 061001. [CrossRef]
Phan, K. L., Wager, T., Taylor, S. F., and Liberzon, I., 2002, “Functional Neuroanatomy of Emotion: A Meta-Analysis of Emotion Activation Studies in PET and fMRI,” NeuroImage, 16(2), pp. 331–348. [CrossRef]
Nguyen, T. A., and Zeng, Y., 2010, “Analysis of Design Activities Using EEG Signals,” Proceedings of the ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE), Montreal, Quebec, Canada.
Alexiou, K., Zamenopoulos, T., Johnson, J. H., and Gilbert, S. J., 2009, “Exploring the Neurological Basis of Design Cognition Using Brain Imaging: Some Preliminary Results,” Des. Stud., 30(6), pp. 623–647. [CrossRef]
Knutson, B., Rick, S., Wimmer, G. E., Prelec, D., and Loewenstein, G., 2007, “Neural Predictors of Purchases,” Neuron, 53(1), pp. 147–156. [CrossRef]
Stoll, M., Baecke, S., and Kenning, P., 2008, “What They See is What They Get? An fMRI-Study on Neural Correlates of Attractive Packaging,” J. Consum. Behav., 7(4-5), pp. 342–359. [CrossRef]
Green, P. E., and Srinivasan, V., 1978, “Conjoint Analysis in Consumer Research: Issues and Outlook,” J. Consum. Res., 5(2), pp. 103–123. [CrossRef]
Zwerina, K., Huber, J., and Kuhfeld, W., 1996, A General Method for Constructing Efficient Choice Designs, Fuqua School of Business, Duke University, Durham, NC.
Turner, H., Orsborn, S., and Lough, K. G., 2009, “Quantifying Product Color Preference in a Utility Function,” Proceedings of 2009 American Society of Engineering Management, Springfield, MO.
Kelly, J., and Papalambros, P. Y., 2007, “Use Of Shape Preference Information in Product Design,” International Conference on Engineering Design, ICED’07, Paris, France.
Reid, T. N., Gonzalez, R. D., and Papalambros, P. Y., 2010, “Quantification of Perceived Environmental Friendliness for Vehicle Silhouette Design,” ASME J. Mech. Des., 132(10), p. 101010. [CrossRef]
Tseng, I., Cagan, J., and Kotovsky, K., 2011, “Learning Stylistic Desires and Generating Preferred Designs of Consumers Using Neural Networks and Genetic Algorithms,” Proceedings of the ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE), Washington, DC.
Huettel, S. A., Song, A. W., and McCarthy, G., 2004, Functional Magnetic Resonance Imaging, Sinauer Associates, Sunderland, MA.
Vartanian, O., and Goel, V., 2004, “Neuroanatomical Correlates of Aesthetic Preference for Paintings,” Neuroreport, 15(5), pp. 893–897. [CrossRef]
Knutson, B., Adams, C. M., Fong, G. W., and Hommer, D., 2001, “Anticipation of Increasing Monetary Reward Selectively Recruits Nucleus Accumbens,” J. Neurosci., 21(16), p. RC159.
Bush, G., Luu, P., and Posner, M., 2000, “Cognitive and Emotional Influences in Anterior Cingulate Cortex,” Trends Cogn. Sci., 4(6), pp. 215–222. [CrossRef]
Jacobsen, T., Schubotz, R. I., Höfel, L., and Von Cramon, D. Y., 2006, “Brain Correlates of Aesthetic Judgment of Beauty,” NeuroImage, 29(1), pp. 276–285. [CrossRef]
Ernst, M., and Paulus, M. P., 2005, “Neurobiology of Decision Making: A Selective Review From A Neurocognitive and Clinical Perspective,” Biol. Psychiatry, 58(8), pp. 597–604. [CrossRef]
Plassmann, H., O'Doherty, J., Shiv, B., and Rangel, A., 2008, “Marketing Actions Can Modulate Neural Representations of Experienced Pleasantness,” Proc. Ntnl. Acad. Sci., 105(3), pp. 1050–1054. [CrossRef]
Zysset, S., Wendt, C. S., Volz, K. G., Neumann, J., HuberO., and Von Cramon, D. Y., 2006, “The Neural Implementation of Multi-Attribute Decision Making: A Parametric fMRI Study With Human Subjects,” NeuroImage, 31(3), pp. 1380–1388. [CrossRef]
Goel, V., and Dolan, R. J., 2003, “Reciprocal Neural Response Within Lateral and Ventral Medial Prefrontal Cortex During Hot and Cold Reasoning.,” NeuroImage, 20(4), pp. 2314–2321. [CrossRef]
Luce, R. D., 1977, “The Choice Axiom After Twenty Years,” J. Math. Psychol., 15(3), pp. 215–233. [CrossRef]
Green, P. E., Carroll, J. D., and DeSarbo, W. S., 1981, “Estimating Choice Probabilities in Multiattribute Decision Making,” J. Consum. Res., 8(1), pp. 76–84. [CrossRef]
Johnson, R. M., 1987, “Adaptive Conjoint Analysis,” Sawtooth Software Conference Proceedings, pp. 253–265.
Kessels, R., Goos, P., and Vandebroek, M., 2010, “Optimal Two-Level Conjoint Designs With Constant Attributes in the Profile Sets,” J. Stat. Plann. Inference, 140(11), pp. 3035–3046. [CrossRef]
Netzer, O., Toubia, O., Bradlow, E. T., Dahan, E., Evgeniou, T., Feinberg, F. M., Feit, E. M., Hui, S. K., Johnson, J., Liechty, J. C., Orlin, J. B., and Rao, V. R., 2008, “Beyond Conjoint Analysis: Advances in Preference Measurement,” Mark. Lett., 19(3–4), pp. 337–354. [CrossRef]
Amaro, E., and Barker, G. J., 2006, “Study Design in fMRI: Basic Principles,” Brain Cogn., 60(3), pp. 220–232. [CrossRef]
Friston, K. J., Penny, W. D., Ashburner, J., Kiebel, S. J., and Nichols, T. E., 2006, Statistical Parametric Mapping: The Analysis of Functional Brain Images, Academic Press, New York.
Forman, S. D., Cohen, J. D., Fitzgerald, M., Eddy, W. F., Mintun, M. A., and Noll, D. C., 1995, “Improved Assessment of Significant Activation in Functional Magnetic Resonance Imaging (fMRI): Use of a Cluster-Size Threshold,” Magn. Reson. Med., 33(5), pp. 636–647. [CrossRef]
Lieberman, M. D., and Cunningham, W. A., 2009, “Type I and Type II Error Concerns in Fmri Research: Re-Balancing the Scale,” Soc. Cogn. Affect. Neurosci., 4(4), pp. 423–428. [CrossRef]
Nichols, T., Brett, M., Andersson, J., Wager, T., and Poline, J.-B., 2005, “Valid Conjunction Inference With the Minimum Statistic,” NeuroImage, 25(3), pp. 653–660. [CrossRef]
Eisenberger, N. I., and Lieberman, M. D., 2004, “Why Rejection Hurts: A Common Neural Alarm System For Physical and Social Pain,” Trends Cogn. Sci., 8(7), pp. 294–300. [CrossRef]
Craig, A. D., 2002, “How Do You Feel? Interoception: The Sense of the Physiological Condition of the Body,” Nat. Rev. Neurosci., 3(8), pp. 655–666.
Critchley, H. D., Wiens, S., Rotshtein, P., Ohman, A., and Dolan, R. J., 2004, “Neural Systems Supporting Interoceptive Awareness,” Nat. Neurosci., 7(2), pp. 189–195. [CrossRef]
Nachev, P., Kennard, C., and Husain, M., 2008, “Functional Role of the Supplementary and Pre-Supplementary Motor Areas.,” Nat. Rev. Neurosci., 9(11), pp. 856–869. [CrossRef]
Ritov, I., and Baron, J., 2011, “Joint Presentation Reduces the Effect of Emotion On Evaluation of Public Actions,” Cogn. Emotion, 25(4), pp. 657–675. [CrossRef]
Hsee, C. K., 1996, “The Evaluability Hypothesis: An Explanation for Preference Reversals Between Joint and Separate Evaluations of Alternatives,” Org. Behav. Human Decis. Process., 67(3), pp. 247–257. [CrossRef]
Bazerman, M. H., Tenbrunsel, A. E., and Wade-Benzoni, K., 1998, “Negotiating With Yourself and Losing: Making Decisions With Competing Internal Preferences,” Acad. Manage. Rev., 23(2), pp. 225–241.
Kahneman, D., and Ritov, I., 1994, “Determinants of Stated Willingness to Pay for Public Goods: A Study in the Headline Method,” J. Risk Uncertainty, 9(1), pp. 5–37. [CrossRef]
Pochon, J.-B., Riis, J., Sanfey, A. G., Nystrom, L. E., and Cohen, J. D., 2008, “Functional Imaging of Decision Conflict,” J. Neurosci., 28(13), pp. 3468–3473. [CrossRef]
Dux, P. E., Ivanoff, J., Asplund, C. L., and Marois, R., 2006, “Isolation of a Central Bottleneck of Information Processing With Time-Resolved FMRI,” Neuron, 52(6), pp. 1109–1120. [CrossRef]
Poldrack, R. A., 2006, “Can Cognitive Processes be Inferred From Neuroimaging Data?,” Trends Cogn. Sci., 10(2), pp. 59–63. [CrossRef]
Falk, E. B., Berkman, E. T., Mann, T., Harrison, B., and Lieberman, M. D., 2010, “Predicting Persuasion-Induced Behavior Change From the Brain,” J. Neurosci., 30(25), pp. 8421–8424. [CrossRef]

Figures

Grahic Jump Location
Fig. 1

Example vehicle design

Grahic Jump Location
Fig. 2

Screenshot of aesthetic preference trial

Grahic Jump Location
Fig. 3

Hood length preference example plot

Grahic Jump Location
Fig. 4

Screenshot of function preference trial

Grahic Jump Location
Fig. 5

Acceleration preference example plot

Grahic Jump Location
Fig. 6

Screenshot of combined preference trial

Grahic Jump Location
Fig. 7

Umform example plot

Grahic Jump Location
Fig. 8

Umfunc example plot

Grahic Jump Location
Fig. 9

Screenshot of combination rating task

Grahic Jump Location
Fig. 10

Screenshot of Form-Function Control trials

Grahic Jump Location
Fig. 11

Screenshot of follow-up question

Grahic Jump Location
Fig. 12

Experimental design of fMRI trials

Grahic Jump Location
Fig. 13

Additive, metaconjoint, and subject rating trend lines with respect to form

Grahic Jump Location
Fig. 14

Additive, metaconjoint, and subject rating trend lines with respect to function

Grahic Jump Location
Fig. 15

Neural activity during Form Only versus Control trials

Grahic Jump Location
Fig. 16

Neural activity during Function Only versus Control trials

Grahic Jump Location
Fig. 17

Neural activity during Form-Function Conflict versus Control trials

Grahic Jump Location
Fig. 18

Difference in neural activity between Form-Function Conflict trials and Form Only and Function Only trials

Grahic Jump Location
Fig. 19

Regions active in the conjunction of Form-Function Conflict and Form Only

Grahic Jump Location
Fig. 20

Regions active in the conjunction of Form-Function Conflict and Function Only

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In