Abstract
Blue of all colors seems to be generally preferred by humans and animals. Consequently, the use of this color in ecommerce context has several positive effects such as increased trustworthiness and aesthetic ratings. These effects are, in this study, hypothesized to be caused by specific neural processes in the prefrontal cortex of human decision makers. Consequently, this study tackles the research question whether there is a distinct neural activation pattern for blue websites that helps to explain why blue is often most favored. To investigate this, one website is designed and manipulated in color to which user reactions are measured by employing functional near-infrared spectroscopy (fNIRS). The results of this study show that blue colored websites seem to require generally less processing power related to cognitive processing while revealing increases in brain structures related to processing pleasant and aesthetic stimuli.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Heller, E.: Wie Farben auf Gefühl und Verstand wirken. Droemer, München (2000)
Granger, G.W.: Objectivity of colour preferences. Nature 170, 778–780 (1952)
McManus, I.C., Jones, A.L., Cottrell, J.: The aesthetics of colour. Perception 10, 651–666 (1981)
Herbert, P.: The Colors Used by the Ten Most Popular Sites. https://paulhebertdesigns.com/web_colors/
Bäumer, T., Leinberger, S., Beck, K., Kolb, F., Pfeifer, A.: Wahl ohne Qual – Wie Farben unsere Entscheidungen färben. Wirtschaftspsychologie 2019, 108–118 (2019)
Bonnardel, N., Piolat, A., Le Bigot, L.: The impact of colour on Website appeal and users’ cognitive processes. Displays 32, 69–80 (2011)
Chang, W., Lin, H.: The impact of color traits on corporate branding. Afr. J. Bus. Manag. 4, 3344–3355 (2010)
Becker, S.A.: An exploratory study on Web usability and the internationalization of US e-businesses. J. Electron. Commer. Res. 3, 265–278 (2002)
Singh, S.: Impact of color on marketing. Manag. Decis. 44, 783–789 (2006)
Cyr, D., Head, M., Larios, H.: Colour appeal in website design within and across cultures: a multi-method evaluation. Int. J. Hum. Comput. Stud. 68, 1–21 (2010)
Seckler, M., Opwis, K., Tuch, A.N.: Linking objective design factors with subjective aesthetics: an experimental study on how structure and color of websites affect the facets of users’ visual aesthetic perception. Comput. Human Behav. 49, 375–389 (2015)
Fortmann-Roe, S.: Effects of hue, saturation, and brightness on color preference in social networks: gender-based color preference on the social networking site Twitter. Color Res. Appl. 38, 196–202 (2013)
Palmer, S.E., Schloss, K.B.: An ecological valence theory of human color preference. Proc. Natl. Acad. Sci. U. S. A. 107, 8877–8882 (2010)
Liu, X., Hong, K.S.: Detection of primary RGB colors projected on a screen using fNIRS. J. Innov. Opt. Health Sci. 10, 1–11 (2017)
Zeki, S., Marini, L.: Three cortical stages of colour processing in the human brain. Brain 121, 1669–1685 (1998)
Young, T.: The bakerian lecture: on the theory of light and colours. Philos. Trans. R. Soc. Lond. 92, 12–48 (1802)
Grassmann, H.: Zur Theorie der Farbenmischung. Ann. der Phys. und Chemie. 165, 69–84 (1853)
MacDonald, L.W.: Using color effectively in computer graphics. IEEE Comput. Graph. Appl. 20–35 (1999)
Hunt, R.W.G.: Measuring Colour. Fountain Press, UK (1998)
Newton, I.: Opticks (1704)
von Goethe, J.W.: Zur Farbenlehre. Tübingen (1810)
Chevreul, M.E., Martel, C.: The Principles of Harmony and Contrast of Colours, and Their Applications to the Arts. Longman, Brown, Green, and Longmans, Harlow (1855)
Munsell, A.H.: a pigment color system and notation. Am. J. Psychol. 23, 236 (1912)
Gorn, G.J., Chattopadhyay, A., Sengupta, J., Tripathi, S.: Waiting for the web: how screen color affects time perception. J. Mark. Res. 41, 215–225 (2004)
Elliot, A.J.: Color and psychological functioning: a review of theoretical and empirical work. Front. Psychol. 6, 1–8 (2015)
Pridmore, R.W.: Chromatic induction: opponent color or complementary color process? Color Res. Appl. 33, 77–81 (2008)
Patil, D.: Coloring consumer’s psychology using different shades the role of perception of colors by consumers in consumer decision making process: a micro study of select departmental stores in Mumbai city, India. J. Bus. Retail Manag. Res. 7, 60–74 (2012)
Pandir, M., Knight, J.: Homepage aesthetics: the search for preference factors and the challenges of subjectivity. Interact. Comput. 18, 1351–1370 (2006)
Tuch, A.N., Bargas-Avila, J.A., Opwis, K., Wilhelm, F.H.: Visual complexity of websites: effects on users’ experience, physiology, performance, and memory. Int. J. Hum. Comput. Stud. 67, 703–715 (2009)
Zheng, X.S., Chakraborty, I., Lin, J.J.W., Rauschenberger, R.: Correlating low-level image statistics with users’ rapid aesthetic and affective judgments of web pages. In: Conference on Human Factors in Computing Systems – Proceedings, pp. 1–10 (2009)
Abegaz, T., Dillon, E., Gilbert, J.E.: Exploring affective reaction during user interaction with colors and shapes. Procedia Manuf. 3, 5253–5260 (2015)
Soldat, A.S., Sinclair, R.C., Mark, M.M.: Color as an environmental processing cue: external affective cues can directly affect processing strategy without affecting mood. Soc. Cogn. 15, 55–71 (1997)
Engel, S., Zhang, X., Wandell, B.: Colour tuning in human visual cortex measured with functional magnetic resonance imaging. Nature 388, 68–71 (1997)
Nathans, J., Thomas, D., Hogness, D.S.: Molecular genetics of human color vision: the genes encodiung blue, green, and red pigments. Science (80-.) 232, 193–202 (1986)
Holzmann, D.C.: What’s in a color? The unique human health effects of blue light. Environ. Health Perspect. 118, A22–A27 (2010)
Mehta, R., Zhu, R.J.: Blue or red? Exploring the effect of color on cognitive task performances. Science (80-.) 323, 1226–1229 (2009)
Anllo-Vento, L., Luck, S.J., Hillyard, S.A.: Spatio-temporal dynamics of attention to color: evidence from human electrophysiology. Hum. Brain Mapp. 6, 216–238 (1998)
Valdez, P., Mehrabian, A.: Effects of color on emotions. J. Exp. Psychol. Gen. 123, 394–409 (1994)
Labrecque, L.I., Milne, G.R.: Exciting red and competent blue: the importance of color in marketing. J. Acad. Mark. Sci. 40, 711–727 (2012)
Moshagen, M., Thielsch, M.T.: Facets of visual aesthetics. Int. J. Hum. Comput. Stud. 68, 689–709 (2010)
Moshagen, M., Thielsch, M.T.: VisAWI Manual (Visual Aesthetics of Websites Inventory) (2013)
Krampe, C., Gier, N., Kenning, P.: The application of mobile fNIRS in marketing research – detecting the ‘first-choice-brand’ effect. Front. Hum. Neurosci. 12, 433 (2018)
Kim, H.Y., Seo, K., Jeon, H.J., Lee, U., Lee, H.: Application of functional near-infrared spectroscopy to the study of brain function in humans and animal models. Mol. Cells 40, 523–532 (2017)
Pollmann, K., Vukelić, M., Birbaumer, N., Peissner, M., Bauer, W., Kim, S.: fNIRS as a method to capture the emotional user experience: a feasibility study. In: Kurosu, M. (ed.) HCI 2016, Part III. LCNS, vol. 9733, pp. 37–47. Springer, Cham (2016)
Hill, A.P., Bohil, C.J.: Applications of optical neuroimaging in usability research. Ergon. Des. 24, 4–9 (2016)
Irani, F., Platek, S.M., Bunce, S., Ruocco, A.C., Chute, D.: Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders. Clin. Neuropsychol. 21, 9–37 (2007)
Huppert, T.J., Hoge, R.D., Diamond, S.G., Franceschini, M.A., Boas, D.A.: A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans. Neuroimage 29, 368–382 (2006)
Strangman, G., Culver, J.P., Thompson, J.H., Boas, D.A.: A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. Neuroimage 17, 719–731 (2002)
Ferrari, M., Quaresima, V.: A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. Neuroimage 63, 921–935 (2012)
Funane, T., Atsumori, H., Katura, T., Obata, A.N., Sato, H., Tanikawa, Y., Okada, E., Kiguchi, M.: Quantitative evaluation of deep and shallow tissue layers’ contribution to fNIRS signal using multi-distance optodes and independent component analysis. Neuroimage 85, 150–165 (2014)
Brigadoi, S., Ceccherini, L., Cutini, S., Scarpa, F., Scatturin, P., Selb, J., Gagnon, L., Boas, D.A., Cooper, R.J.: Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data. Neuroimage 85, 181–191 (2014)
Leff, D.R., Orihuela-Espina, F., Elwell, C.E., Athanasiou, T., Delpy, D.T., Darzi, A.W., Yang, G.Z.: Assessment of the cerebral cortex during motor task behaviours in adults: a systematic review of functional near infrared spectroscopy (fNIRS) studies. Neuroimage 54, 2922–2936 (2011)
Scholkmann, F., Kleiser, S., Metz, A.J., Zimmermann, R., Mata Pavia, J., Wolf, U., Wolf, M.: A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage 85, 6–27 (2014)
Gefen, D., Ayaz, H., Onaral, B.: Applying functional near infrared (fNIR) spectroscopy to enhance MIS research. AIS Trans. Hum. Comput. Interact. 6, 55–73 (2014)
Cui, X., Baker, J.M., Liu, N., Reiss, A.L.: Sensitivity of fNIRS measurement to head motion: an applied use of smartphones in the lab. J. Neurosci. Methods 245, 37–43 (2015)
Zhao, H., Cooper, R.J.: Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system. Neurophotonics 5(1), 011012 (2017)
Tak, S., Ye, J.C.: Statistical analysis of fNIRS data: a comprehensive review. Neuroimage. 85, 72–91 (2014)
Tachtsidis, I., Scholkmann, F.: False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward. Neurophotonics 3, 039801 (2016)
Brigadoi, S., Cooper, R.J.: How short is short? Optimum source–detector distance for short-separation channels in functional near-infrared spectroscopy. Neurophotonics 2, 1–9 (2015)
Goodwin, J.R., Gaudet, C.R., Berger, A.J.: Short-channel functional near-infrared spectroscopy regressions improve when source-detector separation is reduced. Neurophotonics 1, 015002 (2014)
Santosa, H., Zhai, X., Fishburn, F., Huppert, T.: The NIRS Brain AnalyzIR toolbox. Algorithms 11, 73 (2018)
Zhang, D., Zhou, Y., Hou, X., Cui, Y., Zhou, C.: Discrimination of emotional prosodies in human neonates: A pilot fNIRS study. Neurosci. Lett. 658, 62–66 (2017)
Pinti, P., Scholkmann, F., Hamilton, A., Burgess, P., Tachtsidis, I.: Current status and issues regarding pre-processing of fNIRS neuroimaging data: an investigation of diverse signal filtering methods within a general linear model framework. Front. Hum. Neurosci. 12, 1–21 (2019)
Saager, R.B., Berger, A.J.: Direct characterization and removal of interfering absorption trends in two-layer turbid media. J. Opt. Soc. Am. A. 22, 1874 (2005)
Yücel, M.A., Selb, J., Aasted, C.M., Lin, P.Y., Borsook, D., Becerra, L., Boas, D.A.: Mayer waves reduce the accuracy of estimated hemodynamic response functions in functional near-infrared spectroscopy. Biomed. Opt. Express 7, 3078 (2016)
Delpy, D.T., Cope, M., van der Zee, P., Arridge, S., Wray, S., Wyatt, J.: Estimation of optical pathlength through tissue from direct time of flight measurement. Phys. Med. Biol. 33, 1433–1442 (1988)
Kocsis, L., Herman, P., Eke, A.: The modified Beer-Lambert law revisited. Phys. Med. Biol. 51, N91–N98 (2006)
Benjamini, Y., Hochberg, Y.: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B. 57, 289–300 (1995)
Bird, C.M., Berens, S.C., Horner, A.J., Franklin, A.: Categorical encoding of color in the brain. Proc. Natl. Acad. Sci. U. S. A. 111, 4590–4595 (2014)
Siok, W.T., Kay, P., Wang, W.S.Y., Chan, A.H.D., Chen, L., Luke, K.K., Tan, L.H.: Language regions of brain are operative in color perception. Proc. Natl. Acad. Sci. U. S. A. 106, 8140–8145 (2009)
Cela-Conde, C.J., Marty, G., Maestú, F., Ortiz, T., Munar, E., Fernández, A., Roca, M., Rosselló, J., Quesney, F.: Activation of the prefrontal cortex in the human visual aesthetic perception. Proc. Natl. Acad. Sci. U. S. A. 101, 6321–6325 (2004)
Wang, M.Y., Lu, F.M., Hu, Z., Zhang, J., Yuan, Z.: Optical mapping of prefrontal brain connectivity and activation during emotion anticipation. Behav. Brain Res. 350, 122–128 (2018)
Taren, A.A., Venkatraman, V., Huettel, S.A.: A parallel functional topography between medial and lateral prefrontal cortex: evidence and implications for cognitive control. J. Neurosci. 31, 5026–5031 (2011)
Hutcherson, C.A., Plassmann, H., Gross, J.J., Rangel, A.: Cognitive regulation during decision making shifts behavioral control between ventromedial and dorsolateral prefrontal value systems. J. Neurosci. 32, 13543–13554 (2012)
Chen, M.Y., Jimura, K., White, C.N., Todd Maddox, W., Poldrack, R.A.: Multiple brain networks contribute to the acquisition of bias in perceptual decision-making. Front. Neurosci. 9, 1–13 (2015)
Greening, S.G., Finger, E.C., Mitchell, D.G.V.: Parsing decision making processes in prefrontal cortex: response inhibition, overcoming learned avoidance, and reversal learning. Neuroimage 54, 1432–1441 (2011)
Mitchell, D.G.V., Luo, Q., Avny, S.B., Kasprzycki, T., Gupta, K., Chen, G., Finger, E.C., Blair, R.J.R.: Adapting to dynamic stimulus-response values: differential contributions of inferior frontal, dorsomedial, and dorsolateral regions of prefrontal cortex to decision making. J. Neurosci. 29, 10827–10834 (2009)
Heekeren, H.R., Marrett, S., Ruff, D.A., Bandettini, P.A., Ungerleider, L.G.: Involvement of human left dorsolateral prefrontal cortex in perceptual decision making is independent of response modality. Proc. Natl. Acad. Sci. U. S. A. 103, 10023–10028 (2006)
Sanfey, A.G., Rilling, J.K., Aronson, J.A., Nystrom, L.E., Cohen, J.D.: The neural basis of economic decision-making in the Ultimatum Game. Science (80-.) 300, 1755–1758 (2003)
Deppe, M., Schwindt, W., Kugel, H., Plaßmann, H., Kenning, P.: Nonlinear responses within the medial prefrontal cortex reveal when specific implicit information influences economic decision making. J. Neuroimaging 15, 171–182 (2005)
Gilron, R., Gutchess, A.H.: Remembering first impressions: Effects of intentionality and diagnosticity on subsequent memory. Cogn. Affect. Behav. Neurosci. 12, 85–98 (2012)
Dolcos, F., Iordan, A.D., Dolcos, S.: Neural correlates of emotion - cognition interactions: a review of evidence from brain imaging investigations. J. Cogn. Psychol. 23, 669–694 (2011)
Ellard, K.K., Barlow, D.H., Whitfield-Gabrieli, S., Gabrieli, J.D.E., Deckersbach, T.: Neural correlates of emotion acceptance vs worry or suppression in generalized anxiety disorder. Soc. Cogn. Affect. Neurosci. 12, 1009–1021 (2017)
Britton, J.C., Phan, K.L., Taylor, S.F., Welsh, R.C., Berridge, K.C., Liberzon, I.: Neural correlates of social and nonsocial emotions: An fMRI study. Neuroimage 31, 397–409 (2006)
Etkin, A., Egner, T., Kalisch, R.: Emotional processing in anterior cingulate and medial prefrontal cortex. Trends Cogn. Sci. 15, 85–93 (2011)
Cela-Conde, C.J., Garcia-Prieto, J., Ramasco, J.J., Mirasso, C.R., Bajo, R., Munar, E., Flexas, A., del-Pozo, F., Maestu, F.: Dynamics of brain networks in the aesthetic appreciation. Proc. Natl. Acad. Sci. 110, 10454–10461 (2013)
Koenigs, M., Tranel, D.: Irrational economic decision-making after ventromedial prefrontal damage: evidence from the ultimatum game. J. Neurosci. 27, 951–956 (2007)
Naqvi, N., Shiv, B., Bechara, A.: The role of emotion in decision making: a cognitive neuroscience perspective. Curr. Dir. Psychol. Sci. 15, 260–264 (2006)
Delli Pizzi, S., Chiacchiaretta, P., Mantini, D., Bubbico, G., Ferretti, A., Edden, R.A., Di Giulio, C., Onofrj, M., Bonanni, L.: Functional and neurochemical interactions within the amygdala–medial prefrontal cortex circuit and their relevance to emotional processing. Brain Struct. Funct. 222, 1267–1279 (2017)
Buhle, J.T., Silvers, J.A., Wage, T.D., Lopez, R., Onyemekwu, C., Kober, H., Webe, J., Ochsner, K.N.: Cognitive reappraisal of emotion: a meta-analysis of human neuroimaging studies. Cereb. Cortex. 24, 2981–2990 (2014)
Motzkin, J.C., Philippi, C.L., Wolf, R.C., Baskaya, M.K., Koenigs, M.: Ventromedial prefrontal cortex lesions alter neural and physiological correlates of anticipation. J. Neurosci. 34, 10430–10437 (2014)
Doi, H., Nishitani, S., Shinohara, K.: NIRS as a tool for assaying emotional function in the prefrontal cortex. Front. Hum. Neurosci. 7, 1–6 (2013)
Plassmann, H., O’Doherty, J., Rangel, A.: Orbitofrontal cortex encodes willingness to pay in everyday economic transactions. J. Neurosci. 27, 9984–9988 (2007)
Brown, S., Gao, X., Tisdelle, L., Eickhoff, S.B., Liotti, M.: Naturalizing aesthetics: brain areas for aesthetic appraisal across sensory modalities. Neuroimage 58, 250–258 (2011)
Snyder, H.R., Banich, M.T., Munakata, Y.: Choosing our words: retrieval and selection processes recruit shared neural substrates in left ventrolateral prefrontal cortex. J. Cogn. Neurosci. 23, 3470–3482 (2011)
Sakagami, M., Pan, X.: Functional role of the ventrolateral prefrontal cortex in decision making. Curr. Opin. Neurobiol. 17, 228–233 (2007)
Wager, T.D., Davidson, M.L., Hughes, B.L., Lindquist, M.A., Ochsner, K.N.: Prefrontal-subcortical pathways mediating successful emotion regulation. Neuron 59, 1037–1050 (2008)
Leung, H.C., Cai, W.: Common and differential ventrolateral prefrontal activity during inhibition of hand and eye movements. J. Neurosci. 27, 9893–9900 (2007)
Heinen, S.J., Rowland, J., Lee, B.T., Wade, A.R.: An oculomotor decision process revealed by functional magnetic resonance imaging. J. Neurosci. 26, 13515–13522 (2006)
Hoshi, Y., Huang, J., Kohri, S., Iguchi, Y., Naya, M., Okamoto, T., Ono, S.: Recognition of human emotions from cerebral blood flow changes in the frontal region: a study with event-related near-infrared spectroscopy. J. Neuroimaging 21, 94–101 (2011)
Müller-Putz, G.R., Riedl, R., Wriessnegger, S.C.: Electroencephalography (EEG) as a research tool in the information systems discipline: foundations, measurement, and applications. Commun. Assoc. Inf. Syst. 37, 911–948 (2015)
Darley, W.K., Smith, R.E.: Gender differences in information processing strategies: an empirical test of the selectivity model in advertising response. J. Advert. 24, 41–56 (1995)
Putrevu, S.: Exploring the origins and information processing differences between men and women: implications for advertisers. Acad. Mark. Sci. Rev. 10, 1–16 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Nissen, A. (2020). Why We Love Blue Hues on Websites: A fNIRS Investigation of Color and Its Impact on the Neural Processing of Ecommerce Websites. In: Davis, F.D., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A.B., Fischer, T. (eds) Information Systems and Neuroscience. NeuroIS 2020. Lecture Notes in Information Systems and Organisation, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-60073-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-60073-0_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-60072-3
Online ISBN: 978-3-030-60073-0
eBook Packages: Computer ScienceComputer Science (R0)