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Paying Attention Doesn’t Always Pay off: The Effects of High Attention Load on Evaluations of Ideas

  • Goran Calic
  • Nour El Shamy
  • Khaled HassaneinEmail author
  • Scott Watter
Conference paper
Part of the Lecture Notes in Information Systems and Organisation book series (LNISO, volume 29)

Abstract

Creativity is a key driver of success for organizations in the digital age. Managers engaged in evaluating the creativity of new ideas are often subject to a myriad of technology-mediated distractors that compete for their attention. In this work in progress paper, we investigate whether attentional overload results in an upward bias for IT-mediated creativity evaluations. We report on promising early results that examines this phenomenon and set out to study its implications on IT design complexity.

Keywords

Creativity Cognitive load Cognition Electroencephalography Eye tracking Pupil dilation 

References

  1. 1.
    IBM: IBM 2010 Global CEO Study: Creativity Selected as Most Crucial Factor for Future Success. News releases (2010)Google Scholar
  2. 2.
    Gavetti, G.: Toward a behavioral theory of strategy. Organ. Sci. 23, 267–285 (2012)CrossRefGoogle Scholar
  3. 3.
    Bhagwatwar, A., Massey, A., Dennis, A.R.: Creative virtual environments: effect of supraliminal priming on team brainstorming. Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 215–224. (2013).  https://doi.org/10.1109/hicss.2013.152
  4. 4.
    Di Gangi, P.M, Wasko, M.M., Hooker, R.E.: Getting customers’ ideas to work for you: learning from dell how to succeed with online user innovation communities. MIS Q. Executive 9 (2010)Google Scholar
  5. 5.
    Dennis, A.R., Minas, R.K., Bhagwatwar, A.P.: Sparking creativity: improving electronic brainstorming with individual cognitive priming. J. Manage. Inf. Syst. 29. IEEE: 195–216. (2013).  https://doi.org/10.2753/mis0742-1222290407CrossRefGoogle Scholar
  6. 6.
    Davern, M., Shaft, T., Te’eni, D.: Cognition matters: enduring questions in cognitive IS research. J. Assoc. Inf. Syst. 13, 273–314 (2012)Google Scholar
  7. 7.
    Antunes, P., Ferreira, A.: Developing collaboration awareness support from a cognitive perspective. Proceedings of the Annual Hawaii International Conference on System Sciences. (2011).  https://doi.org/10.1109/hicss.2011.161
  8. 8.
    Kolfschoten, G.L.: Cognitive load in collaboration—brainstorming. Proceedings of the Annual Hawaii International Conference on System Sciences. (2011).  https://doi.org/10.1109/hicss.2011.107
  9. 9.
    Sweller, J.: Cognitive load theory, learning difficulty, and instructional design. Learn. Instr. 4, 295–312 (1994).  https://doi.org/10.1016/0959-4752(94)90003-5CrossRefGoogle Scholar
  10. 10.
    Wang, Q., Yang, S., Liu, M., Cao, Z., Ma, Q.: An eye-tracking study of website complexity from cognitive load perspective. Decis. Support Syst. 62, 1–10, Elsevier B.V. (2014).  https://doi.org/10.1016/j.dss.2014.02.007CrossRefGoogle Scholar
  11. 11.
    Heninger, W.G., Dennis, A.R., Hilmer, K.M.: Research note: individual cognition and dual-task inference in group support systems. Inf. Syst. Res. 17, 415–424 (2006).  https://doi.org/10.1287/isre.l060.0102CrossRefGoogle Scholar
  12. 12.
    Simonton, D.K.: Creative thought as blind variation and selective retention: why creativity is inversely related to sightedness. J. Theor. Philos. Psychol. 33, 253–266 (2012).  https://doi.org/10.1037/a0030705CrossRefGoogle Scholar
  13. 13.
    Sweller, J.: Cognitive load during problem solving: effects on learning. Cogn. Sci. 12, 257–285 (1988)CrossRefGoogle Scholar
  14. 14.
    Sweller, J., van Merrienboer, J.J.G., Paas, F.G.W.C.: Cognitive architecture and instructional design. Educ. Psychol. Rev. 10, 251–296 (1998)CrossRefGoogle Scholar
  15. 15.
    Miller, G.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63, 81–97 (1956)CrossRefGoogle Scholar
  16. 16.
    Potter, R.E., Balthazard, P.: The role of individual memory and attention processes during electronic brainstorming. MIS Q. 28, 621–643 (2004)CrossRefGoogle Scholar
  17. 17.
    Williams, M.L., Dennis, A.R., Stam, A., Aronson, J.E.: The impact of DSS use and information load on errors and decision quality. Eur. J. Oper. Res. 176, 468–481 (2007).  https://doi.org/10.1016/j.ejor.2005.06.064CrossRefGoogle Scholar
  18. 18.
    Stipacek, A., Grabner, R.H., Neuper, C., Fink, A., Neubauer, A.C.: Sensitivity of human EEG alpha band desynchronization to different working memory components and increasing levels of memory load. Neurosci. Lett. 353, 193–196 (2003).  https://doi.org/10.1016/j.neulet.2003.09.044CrossRefGoogle Scholar
  19. 19.
    Krause, C.M., Sillanmäki, L., Koivisto, M., Saarela, C., Häggqvist, A., Laine, M., Hämäläinen, H.: The effects of memory load on event-related EEG desynchronization and synchronization. Clin. Neurophysiol. 111, 2071–2078 (2000).  https://doi.org/10.1016/S1388-2457(00)00429-6CrossRefGoogle Scholar
  20. 20.
    Klimesch, W., Schimke, H., Pfurtscheller, G.: Alpha frequency, cognitive load and memory performance. Brain Topogr. 5, 241–251 (1993)CrossRefGoogle Scholar
  21. 21.
    Parasuraman, R.: Neuroergonomics: brain, cognition, and performance at work. Curr. Dir. Psychol. Sci. 20, 181–186 (2011)CrossRefGoogle Scholar
  22. 22.
    Lavric, A., Forstmeier, S., Rippon, G.: Differences in working memory involvement in analytical and creative tasks: an ERP study. Cogn. Neurosci. 11, 1613–1618 (2000).  https://doi.org/10.1097/00001756-200006050-00004CrossRefGoogle Scholar
  23. 23.
    Riedl, R., Léger, P.-L.: Fundamentals of NeuroIS. In: Studies in Neuroscience, Psychology and Behavioral Economics. Berlin, Heidelberg: SpringerGoogle Scholar
  24. 24.
    Fink, A., Benedek, M.: EEG alpha power and creative ideation. Neurosci. Biobehav. Rev. 44, 111–123, Elsevier Ltd. (2014).  https://doi.org/10.1016/j.neubiorev.2012.12.002CrossRefGoogle Scholar
  25. 25.
    Fink, A., Benedek, M., Grabner, R.H., Staudt, B., Neubauer, A.C.: Creativity meets neuroscience: experimental tasks for the neuroscientific study of creative thinking. Methods 42, 68–76 (2007).  https://doi.org/10.1016/j.ymeth.2006.12.001CrossRefGoogle Scholar
  26. 26.
    Dietrich, A., Kanso, R.: A review of EEG, ERP, and neuroimaging studies of creativity and insight. Psychol. Bull. 136, 822–848 (2010).  https://doi.org/10.1037/a0019749CrossRefGoogle Scholar
  27. 27.
    Sandkühler, S., Bhattacharya, J.: Deconstructing insight: EEG correlates of insightful problem solving. PLoS ONE 3, e1459 (2008).  https://doi.org/10.1371/journal.pone.0001459. (Edited by Paul Zak)CrossRefGoogle Scholar
  28. 28.
    de Dreu, C.K.W., Nijstad, B.A., Baas, M., Wolsink, I., Roskes, M.: Working memory benefits creative insight, musical improvisation, and original ideation through maintained task-focused attention. Pers. Soc. Psychol. Bull. 38, 656–669 (2012).  https://doi.org/10.1177/0146167211435795CrossRefGoogle Scholar
  29. 29.
    Smith, S.M. Getting into and Out of Mental Ruts: A Theory of Fixation, Incubation, and Insight. The MIT Press (1995)Google Scholar
  30. 30.
    Kasof, J.: Creativity and breadth of attention. Creativity Res. J. 10, 303–315 (1997).  https://doi.org/10.1207/s15326934crj1004_2CrossRefGoogle Scholar
  31. 31.
    West, M.A.: Sparkling fountains or stagnant ponds: an integrative model of creativity and innovation implementation in work groups. Appl. Psychol. 51, 355–387 (2002)CrossRefGoogle Scholar
  32. 32.
    Finke, R.A., Smith, S.M., Ward, T.B.: Creative Cognition Theory, Research, and Applications. MIT Press, Cambridge, Massachusetts (1996)Google Scholar
  33. 33.
    Campbell, D.T.: Blind variation and selective retentions in creative thought as in other knowledge processes. Psychol. Rev. 67, 380–400 (1960)CrossRefGoogle Scholar
  34. 34.
    Getzels, J.W. Creativity, intelligence, and problem finding: retrospect and prospect. Front. Creativity Res., 88–102 (1987)Google Scholar
  35. 35.
    Watter, S., Heisz, J.J., Karle, J.W., Shedden, J.M., Kiss, I.: Modality-specific control processes in verbal versus spatial working memory. Brain Res. 1347, 90–103 (2010).  https://doi.org/10.1016/j.brainres.2010.05.085CrossRefGoogle Scholar
  36. 36.
    Kiss, I., Watter, S., Heisz, J.J., Shedden, J.M.: Control processes in verbal working memory: an event-related potential study. Brain Res. 1172, 67–81 (2007).  https://doi.org/10.1016/j.brainres.2007.06.083CrossRefGoogle Scholar
  37. 37.
    Du, Q., Qiao, Z., Fan, W., Zhou, M., Zhang, X., Wang, A.G.: Money talks: a predictive model on crowdfunding success using project description. In ACIS 2015, 1–8 (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Goran Calic
    • 1
  • Nour El Shamy
    • 1
  • Khaled Hassanein
    • 1
    Email author
  • Scott Watter
    • 2
  1. 1.DeGroote School of BusinessMcMaster UniversityHamiltonCanada
  2. 2.Department of Psychology, Neuroscience and BehaviourMcMaster UniversityHamiltonCanada

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