Skip to main content

Neuroscience Experiment for Graphical Visualization in the FITradeoff Decision Support System

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 315))

Abstract

The neuroscience approach is considered to be a study of the neural system and its implications for processes in the human body. Behavioral studies in Multicriteria Decision Making (MCDM) still have a gap and in this context, Neuroscience can be used as a decision support tool. Therefore, the aim of this research study is to explore the potential of using graphical visualization in the FITradeoff Decision Support System (DSS) by undertaking an eye-tracking experiment and applying it to a decision problem. In the end, based on the results, suggestions are made to the analyst and improvements are made to the design of the DSS so that solutions could be found that accurately express a decision maker’s preferences.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Ares, G., et al.: Influence of rational and intuitive thinking styles on food choice: preliminary evidence from an eye-tracking study with yogurt labels. Food Qual. Prefer. 31, 28–37 (2014)

    Article  Google Scholar 

  2. de Almeida, A.T., De Almeida, J.A., Costa, A.P.C.S., De Almeida-Filho, A.T.: A new method for elicitation of criteria weights in additive models: flexible and interactive tradeoff. Eur. J. Oper. Res. 250, 179–191 (2016)

    Article  Google Scholar 

  3. Fehr, E., Camerer, C.: Social neuroeconomics: the neural circuitry of social preferences. Trends Cogn. Sci. 11, 419–427 (2007)

    Article  Google Scholar 

  4. Glimcher, P.W., Rustichini, A.: Neuroeconomics: the consilience of brain and decision. Science 5695, 447–452 (2004)

    Article  Google Scholar 

  5. Goucher-Lambert, K., Moss, J., Cagan, J.: Inside the mind: using neuroimaging to understand moral product preference judgments involving sustainability. J. Mech. Des. 139, 41–103 (2017)

    Article  Google Scholar 

  6. Guixeres, J., et al.: Consumer Neuroscience-based metrics predict recall, liking and viewing rates in online advertising. Front. Psychol. 8 (2017). https://doi.org/10.3389/fpsyg.2017.01808

  7. Hunt, L.T., Dolan, R.J., Behrens, T.E.: Hierarchical competitions subserving multi-attribute choice. Nat. Neurosci. 17, 1613–1622 (2014)

    Article  Google Scholar 

  8. Keeney, R.L., Raiffa, H.: Decisions with Multiple Objectives - Preferences, and Value Tradeoffs. Wiley, New York (1976)

    Google Scholar 

  9. Khushaba, R.N.: Consumer neuroscience: assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Syst. Appl. 40, 3803–3812 (2013)

    Article  Google Scholar 

  10. Kothe, C.A., Makeig, S.: Estimation of task workload from EEG data: new and current tools and perspectives. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2011)

    Google Scholar 

  11. Laeng, B., Sirois, S., Gredebäck, G.: Pupillometry: a window to the preconscious? Perspect. Psychol. Sci. 7, 18–27 (2012)

    Article  Google Scholar 

  12. Mohr, P.N.C., Biele, G., Heekeren, H.: Neural processing of risk. J. Neurosci. 30, 6613–6619 (2010)

    Article  Google Scholar 

  13. Morin, C.: Neuromarketing: the new science of consumer behavior. Society 48, 131–135 (2011)

    Article  Google Scholar 

  14. Porter, G., Troscianko, T., Gilchrist, I.D.: Effort during visual search and counting: insights from pupillometry. Q. J. Exp. Psychol. 60, 211–229 (2007)

    Article  Google Scholar 

  15. Rangel, A., Camerer, C., Montague, P.R.: A framework for studying the neurobiology of value-based decision making. Nat. Rev. Neurosci. 9, 545–556 (2008)

    Article  Google Scholar 

  16. Riedl, R., Davis, F.D., Hevne, R., Alan, R.: Towards a NeuroIS research methodology: intensifying the discussion on methods, tools, and measurement. J. Assoc. Inf. Syst. 15, I (2014)

    Google Scholar 

  17. Sanfey, A.G., Rilling, J.K., Aronson, J.A., Nystrom, L.E., Cohen, J.P.: The neural basis of economic decision-making in the ultimatum game. Science 5626, 1755–1758 (2003)

    Article  Google Scholar 

  18. Sharma, N., Gedeon, T.: Objective measures, sensors and computational techniques for stress recognition and classification: a survey. Comput. Methods Programs Biomed. 108, 1287–1301 (2012)

    Article  Google Scholar 

  19. Slanzi, G., Balazs, J., Velásquez, J.D.: Predicting Web user click intention using pupil dilation and electroencephalogram analysis. In: IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE (2016)

    Google Scholar 

  20. Smith, D.V., Huettel, S.A.: Decision neuroscience: neuroeconomics. Wiley Interdiscip. Rev. Cogn. Sci. 1, 854–871 (2010)

    Article  Google Scholar 

  21. Sylcott, B., Cagan, J., Tabibnia, G.: Understanding consumer tradeoffs between form and function through metaconjoint and cognitive neuroscience analyses. J. Mech. Des. 135 (2013). https://doi.org/10.1115/1.4024975

    Article  Google Scholar 

  22. Weber, M., Borcherding, K.: Behavioral influences on weight judgments in multi-attribute decision making. Eur. J. Oper. Res. 67, 1–12 (1993)

    Article  Google Scholar 

  23. Zhao, Y.L., Siau, K.: Cognitive neuroscience in information systems research. J. Database Manag. 27, 58–73 (2016)

    Article  Google Scholar 

Download references

Acknowledgments

This study was partially sponsored by the Brazilian Research Council (CNPq) for which the authors are most grateful.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eduarda Asfora Frej .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Roselli, L.R.P., Frej, E.A., de Almeida, A.T. (2018). Neuroscience Experiment for Graphical Visualization in the FITradeoff Decision Support System. In: Chen, Y., Kersten, G., Vetschera, R., Xu, H. (eds) Group Decision and Negotiation in an Uncertain World. GDN 2018. Lecture Notes in Business Information Processing, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-92874-6_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-92874-6_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92873-9

  • Online ISBN: 978-3-319-92874-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics