Advertisement

Measuring the Effects of Messaging on Consumer Decision-Making Using Functional Near Infrared Spectroscopy

  • Jan WatsonEmail author
  • Amanda Sargent
  • Yigit Topoglu
  • Hongjun Ye
  • Rajneesh Suri
  • Hasan Ayaz
Conference paper
  • 5 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1201)

Abstract

Understanding the impact of messaging on choice from a neural perspective is a major research interest in the fields of cognitive science, psychology, business and communications. In this study, we investigated the impact of a pro-environmental audiovisual message on consumer electricity supply preference as well as the differences in consumer hemodynamic activity during electricity supply plan choice periods before and after the messaging intervention. Fifteen (8 female, mean age = 29 years) participants were recruited and presented with a set of binary choices between two different types of electricity supply plans before watching a messaging video and completing the set of choices again. Using functional near infrared spectroscopy (fNIRS) we monitored participants’ prefrontal hemodynamic activity during periods of electricity supply plan selection to attain measures related to neural activity. Consistent with our hypothesis, average oxygenated hemoglobin levels measured by fNIRS indicate an increase in hemodynamic activity during decision making after message viewing at the right- inferior frontal gyrus. Additionally, behavioral measures show an increase in pro-environmental electricity plan selection after exposure to the messaging intervention. These combined brain and behavioral measures provide a comprehensive assessment of consumer decision and demonstrate that fNIRS can be used in the neuroergonomic assessment of cognitive state in real-world environments via wearable sensors.

Keywords

Functional near infrared spectroscopy Neuroeconomics Neuroergonomics 

References

  1. 1.
    Pelletier, L.G., Sharp, E.: Persuasive communication and proenvironmental behaviours: how message tailoring and message framing can improve the integration of behaviours through self-determined motivation. Can. Psychol./Psychol. Can. 49(3), 210 (2008)CrossRefGoogle Scholar
  2. 2.
    Schmid, K.L., Rivers, S.E., Latimer, A.E., Salovey, P.: Targeting or tailoring? Maximizing resources to create effective health communications. Mark. Health Serv. 28(1), 32 (2008)Google Scholar
  3. 3.
    Kottemann, J.E., Davis, F.D.: Decisional conflict and user acceptance of multicriteria decision-making aids. Decis. Sci. 22(4), 918–926 (1991)CrossRefGoogle Scholar
  4. 4.
    Zysset, S., Wendt, C.S., Volz, K.G., Neumann, J., Huber, O., von Cramon, D.Y.: The neural implementation of multi-attribute decision making: a parametric fMRI study with human subjects. Neuroimage 31(3), 1380–1388 (2006)CrossRefGoogle Scholar
  5. 5.
    Pochon, J.-B., Riis, J., Sanfey, A.G., Nystrom, L.E., Cohen, J.D.: Functional imaging of decision conflict. J. Neurosci. 28(13), 3468–3473 (2008)CrossRefGoogle Scholar
  6. 6.
    Di Domenico, S.I., Rodrigo, A.H., Ayaz, H., Fournier, M.A., Ruocco, A.C.: Decision-making conflict and the neural efficiency hypothesis of intelligence: a functional near-infrared spectroscopy investigation. Neuroimage 109, 307–317 (2015)CrossRefGoogle Scholar
  7. 7.
    Di Domenico, S.I., Le, A., Liu, Y., Ayaz, H., Fournier, M.A.: Basic psychological needs and neurophysiological responsiveness to decisional conflict: an event-related potential study of integrative self processes. Cogn. Affect. Behav. Neurosci. 16(5), 848–865 (2016)CrossRefGoogle Scholar
  8. 8.
    Villegas, J., Matyas, C., Srinivasan, S., Cahyanto, I., Thapa, B., Pennington-Gray, L.: Cognitive and affective responses of Florida tourists after exposure to hurricane warning messages. Nat. Hazards 66(1), 97–116 (2013)CrossRefGoogle Scholar
  9. 9.
    Armitage, C.J., Conner, M.: Efficacy of the theory of planned behaviour: A meta-analytic review. Br. J. Soc. Psychol. 40(4), 471–499 (2001)CrossRefGoogle Scholar
  10. 10.
    Webb, T.L., Sheeran, P.: Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychol. Bull. 132(2), 249 (2006)CrossRefGoogle Scholar
  11. 11.
    Berkman, E.T., Falk, E.B.: Beyond brain mapping: Using neural measures to predict real-world outcomes. Curr. Dir. Psychol. Sci. 22(1), 45–50 (2013)CrossRefGoogle Scholar
  12. 12.
    Herrmann, M.J., Ehlis, A.-C., Fallgatter, A.J.: Prefrontal activation through task requirements of emotional induction measured with NIRS. Biol. Psychol. 64(3), 255–263 (2003)CrossRefGoogle Scholar
  13. 13.
    Harmon-Jones, E., Gable, P.A., Peterson, C.K.: The role of asymmetric frontal cortical activity in emotion-related phenomena: a review and update. Biol. Psychol. 84(3), 451–462 (2010)CrossRefGoogle Scholar
  14. 14.
    Ayaz, H., Onaral, B., Izzetoglu, K., Shewokis, P.A., McKendrick, R., Parasuraman, R.: Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development. Front. Hum. Neurosci. 7, 871 (2013)CrossRefGoogle Scholar
  15. 15.
    Mehta, R.K., Parasuraman, R.: Neuroergonomics: a review of applications to physical and cognitive work. Front. Hum. Neurosci. 7, 889 (2013)CrossRefGoogle Scholar
  16. 16.
    Ayaz, H., Dehais, F.: Neuroergonomics: The Brain at Work and in Everyday Life. Academic Press, Cambridge (2018)Google Scholar
  17. 17.
    Parasuraman, R., Rizzo, M.: Neuroergonomics: The Brain at Work. Oxford University Press, Oxford (2008)Google Scholar
  18. 18.
    Ayaz, H., Shewokis, P.A., Curtin, A., Izzetoglu, M., Izzetoglu, K., Onaral, B.: Using Mazesuite and functional near infrared spectroscopy to study learning in spatial navigation. JoVE (J. Visualized Exp.) (56), p. e3443 (2011)Google Scholar
  19. 19.
    McKendrick, R., Ayaz, H., Olmstead, R., Parasuraman, R.: Enhancing dual-task performance with verbal and spatial working memory training: continuous monitoring of cerebral hemodynamics with NIRS. Neuroimage 85, 1014–1026 (2014)CrossRefGoogle Scholar
  20. 20.
    Liu, Y., et al.: Measuring speaker–listener neural coupling with functional near infrared spectroscopy. Sci. Rep. 7, 43293 (2017)CrossRefGoogle Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Jan Watson
    • 1
    Email author
  • Amanda Sargent
    • 1
  • Yigit Topoglu
    • 1
  • Hongjun Ye
    • 2
  • Rajneesh Suri
    • 2
    • 3
  • Hasan Ayaz
    • 1
    • 3
    • 4
    • 5
    • 6
  1. 1.School of Biomedical Engineering, Science and Health SystemsDrexel UniversityPhiladelphiaUSA
  2. 2.LeBow College of BusinessDrexel UniversityPhiladelphiaUSA
  3. 3.Drexel Solutions InstituteDrexel UniversityPhiladelphiaUSA
  4. 4.Department of Psychology, College of Arts and SciencesDrexel UniversityPhiladelphiaUSA
  5. 5.Department of Family and Community HealthUniversity of PennsylvaniaPhiladelphiaUSA
  6. 6.Center for Injury Research and Prevention, Children’s Hospital of PhiladelphiaPhiladelphiaUSA

Personalised recommendations