Skip to main content
SpringerLink
Log in

User Performance in the Face of IT Interruptions: The Role of Executive Functions

  • Conference paper
  • First Online:
Information Systems and Neuroscience

Part of the book series: Lecture Notes in Information Systems and Organisation ((LNISO,volume 32))

Abstract

Information systems (IS) research has studied the consequences of IT interruption on user performance. However, our knowledge thus far of the cognitive mechanisms involved in processing different interruption types is limited. In response to this research gap, the present research-in-progress paper proposes that IT intrusions (unnecessary interruptions) and IT interventions (relevant interruptions) impose different types of load on users’ cognitive resources. The study employs a self-regulation framework and borrows from the literature on executive functions (EFs), which are a set of general-purpose cognitive processes that control thought and actions. The moderating role of individuals’ differences in terms of three EF capabilities as well as the effect of EF loads on task performance are hypothesized. A three-factor (Interruption Frequency × Interruption Type × Executive Function Capability) mixed-design experiment using electroencephalography is proposed to test the generated hypotheses.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

Similar content being viewed by others

References

  1. Baethge, A., & Rigotti, T. (2013). Interruptions to workflow: Their relationship with irritation and satisfaction with performance, and the mediating roles of time pressure and mental demands. Work & Stress, 27(1), 43–63.

    Article  Google Scholar 

  2. Murphy, M. (2016). Interruptions at work are killing your productivity.

    Google Scholar 

  3. Rissler, R., Nadj, M., Adam, M., & Maedche, A. (2017). Towards an integrative theoretical framework of IT-mediated interruptions.

    Google Scholar 

  4. Jett, Q. R., & George, J. M. (2003). Work interrupted: A closer look at the role of interruptions in organizational life. Academy of Management Review, 28(3), 494–507.

    Article  Google Scholar 

  5. Galluch, P. S., Grover, V., & Thatcher, J. B. (2015). Interrupting the workplace: Examining stressors in an information technology context. Journal of the Association for Information Systems, 16(1), 1.

    Article  Google Scholar 

  6. Riedl, R., Kindermann, H., Auinger, A., & Javor, A. (2012). Technostress from a neurobiological perspective. Business & Information Systems Engineering, 4(2), 61–69.

    Article  Google Scholar 

  7. Spira, J. B., & Feintuch, J. B. (2005). The cost of not paying attention: How interruptions impact knowledge worker productivity. Report from Basex.

    Google Scholar 

  8. Addas, S., & Pinsonneault, A. (2015). The many faces of information technology interruptions: A taxonomy and preliminary investigation of their performance effects. Information Systems Journal, 25(3), 231–273.

    Article  Google Scholar 

  9. Speier, C., Vessey, I., & Valacich, J. S. (2003). The effects of interruptions, task complexity, and information presentation on computer-supported decision-making performance. Decision Sciences, 34(4), 771–797.

    Article  Google Scholar 

  10. Addas, S., & Pinsonneault, A. (2018). E-mail interruptions and individual performance: Is there a silver lining? Management Information Systems Quarterly, 42(2), 381–405.

    Article  Google Scholar 

  11. Lu, S. A., Wickens, C. D., Prinet, J. C., Hutchins, S. D., Sarter, N., & Sebok, A. (2013). Supporting interruption management and multimodal interface design: Three meta-analyses of task performance as a function of interrupting task modality. Human Factors, 55(4), 697–724.

    Article  Google Scholar 

  12. Gupta, A., Li, H., & Sharda, R. (2013). Should I send this message? Understanding the impact of interruptions, social hierarchy and perceived task complexity on user performance and perceived workload. Decision Support Systems, 55(1), 135–145.

    Article  Google Scholar 

  13. Jenkins, J. L., Anderson, B. B., Vance, A., Kirwan, C. B., & Eargle, D. (2016). More harm than good? How messages that interrupt can make us vulnerable. Information Systems Research, 27(4), 880–896.

    Article  Google Scholar 

  14. Barley, S. R., Meyerson, D. E., & Grodal, S. (2011). E-mail as a source and symbol of stress. Organization Science, 22(4), 887–906.

    Article  Google Scholar 

  15. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100.

    Google Scholar 

  16. Del Missier, F., Mäntylä, T., & Bruine de Bruin, W. (2010). Executive functions in decision making: An individual differences approach. Thinking & Reasoning, 16(2), 69–97.

    Google Scholar 

  17. Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16(3), 174–180.

    Google Scholar 

  18. Toplak, M. E., West, R. F., & Stanovich, K. E. (2013). Practitioner review: Do performance-based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry, 54(2), 131–143.

    Article  Google Scholar 

  19. Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21(1), 8–14.

    Google Scholar 

  20. Carver, C. S., & Scheier, M. F. (2004). Self-regulation of action and affect. In Handbook of self-regulation: Research, theory, and applications (pp. 13–39).

    Google Scholar 

  21. Smith, E. E., & Jonides, J. (1997). Working memory: A view from neuroimaging. Cognitive Psychology, 33(1), 5–42.

    Google Scholar 

  22. Tams, S., Thatcher, J. B., & Grover, V. (2018). Concentration, competence, confidence, and capture: An experimental study of age, interruption-based technostress, and task performance. Journal of the Association for Information Systems, 19, 9.

    Article  Google Scholar 

  23. Foroughi, C. K., Malihi, P., & Boehm-Davis, D. A. (2016). Working memory capacity and errors following interruptions. Journal of Applied Research in Memory and Cognition, 5(4), 410–414.

    Article  Google Scholar 

  24. Jann, K., Koenig, T., Dierks, T., Boesch, C., & Federspiel, A. (2010). Association of individual resting state EEG alpha frequency and cerebral blood flow. Neuroimage, 51(1), 365–372.

    Article  Google Scholar 

  25. Neuper, C., Grabner, R. H., Fink, A., & Neubauer, A. C. (2005). Long-term stability and consistency of EEG event-related (de-) synchronization across different cognitive tasks. Clinical Neurophysiology, 116(7), 1681–1694.

    Article  Google Scholar 

  26. Jaušovec, N. (1996). Differences in EEG alpha activity related to giftedness. Intelligence, 23(3), 159–173.

    Article  Google Scholar 

  27. Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29(2–3), 169–195.

    Article  Google Scholar 

  28. Jaušovec, N., & Jaušovec, K. (2001). Differences in EEG current density related to intelligence. Cognitive Brain Research, 12(1), 55–60.

    Google Scholar 

  29. Kane, M. J., Bleckley, M. K., Conway, A. R., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology: General, 130(2), 169.

    Article  Google Scholar 

  30. Dreisbach, G., & Haider, H. (2009). How task representations guide attention: Further evidence for the shielding function of task sets. Journal of Experimental Psychology. Learning, Memory, and Cognition, 35(2), 477.

    Article  Google Scholar 

  31. Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160.

    Google Scholar 

  32. Washburn, D. A., Gulledge, J. P., James, F., & Rumbaugh, D. M. (2007). A species difference in visuospatial working memory: Does language link “what” with “where”? International Journal of Comparative Psychology, 20, 1.

    Google Scholar 

  33. Zook, N. A., Davalos, D. B., DeLosh, E. L., & Davis, H. P.(2004). Working memory, inhibition, and fluid intelligence as predictors of performance on Tower of Hanoi and London tasks. Brain and Cognition, 56(3), 286–292.

    Google Scholar 

  34. Baddeley, A. (2007). Working memory, thought, and action (Vol. 45). Oxford: OUP Oxford.

    Google Scholar 

  35. Roux, F., & Uhlhaas, P. J. (2014). Working memory and neural oscillations: Alpha–gamma versus theta–gamma codes for distinct WM information? Trends in Cognitive Sciences, 18(1), 16–25.

    Google Scholar 

  36. Lange, F., Lange, C., Joop, M., Seer, C., Dengler, R., Kopp, B., & Petri, S. (2016). Neural correlates of cognitive set shifting in amyotrophic lateral sclerosis. Clinical Neurophysiology, 127(12), 3537–3545.

    Google Scholar 

  37. Elchlepp, H., Best, M., Lavric, A., & Monsell, S. (2017). Shifting attention between visual dimensions as a source of switch costs. Psychological Science, 28(4), 470–481.

    Google Scholar 

  38. Klimesch, W., Sauseng, P., & Hanslmayr, S. (2007). EEG alpha oscillations: The inhibition–timing hypothesis. Brain Research Reviews, 53(1), 63–88.

    Google Scholar 

  39. Hummel, F., Andres, F., Altenmüller, E., Dichgans, J., & Gerloff, C. (2002). Inhibitory control of acquired motor programmes in the human brain. Brain, 125(2), 404–420.

    Article  Google Scholar 

  40. Klimesch, W., Doppelmayr, M., Schwaiger, J., Auinger, P., & Winkler, T. (1999). Paradoxical’alpha synchronization in a memory task. Cognitive Brain Research, 7(4), 493–501.

    Article  Google Scholar 

  41. Klimesch, W., Schimke, H., & Schwaiger, J. (1994). Episodic and semantic memory: An analysis in the EEG theta and alpha band. Electroencephalography and Clinical Neurophysiology, 91(6), 428–441.

    Article  Google Scholar 

  42. Müller-Putz, G. R., Riedl, R., & Wriessnegger, S. C. (2015). Electroencephalography (EEG) as a research tool in the information systems discipline: Foundations, measurement, and applications. CAIS, 37, 46.

    Google Scholar 

  43. Mehrotra, A., Pejovic, V., Vermeulen, J., Hendley, R., & Musolesi, M. (2016). My phone and me: Understanding people’s receptivity to mobile notifications. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM.

    Google Scholar 

  44. Fischer, J. E., Greenhalgh, C., & Benford, S. (2011). Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services. ACM.

    Google Scholar 

  45. Shrot, T., Rosenfeld, A., Golbeck, J., & Kraus, S. (2014). Crisp: An interruption management algorithm based on collaborative filtering. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. DeGroote School of Business, McMaster University, Hamilton, Canada

    Seyedmohammadmahdi Mirhoseini, Khaled Hassanein & Milena Head

  2. Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, Canada

    Scott Watter

Authors
  1. Seyedmohammadmahdi Mirhoseini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Khaled Hassanein
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Milena Head
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Scott Watter
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Seyedmohammadmahdi Mirhoseini .

Editor information

Editors and Affiliations

  1. Information Systems and Quantitative Sciences (ISQS), Texas Tech University, Lubbock, TX, USA

    Fred D. Davis

  2. University of Applied Sciences Upper Austria, Steyr, Oberösterreich, Austria

    René Riedl

  3. Department of Information Systems, University of Liechtenstein, Vaduz, Liechtenstein

    Jan vom Brocke

  4. Department of Information Technology, HEC Montréal, Montreal, QC, Canada

    Pierre-Majorique Léger

  5. Department of Information Systems, Kennesaw State University, Kennesaw, GA, USA

    Adriane Randolph

  6. Department for Digital Business, University of Applied Sciences Upper Austria, Steyr, Oberösterreich, Austria

    Thomas Fischer

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mirhoseini, S., Hassanein, K., Head, M., Watter, S. (2020). User Performance in the Face of IT Interruptions: The Role of Executive Functions. In: Davis, F., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A., Fischer, T. (eds) Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-030-28144-1_5

Download citation

Publish with us

Policies and ethics

Search

Navigation