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Personality Profiles that Put Users at Risk of Perceiving Technostress

Author

Listed:
  • Katharina Pflügner

    (University of Bamberg)

  • Christian Maier

    (University of Bamberg)

  • Jens Mattke

    (University of Bamberg)

  • Tim Weitzel

    (University of Bamberg)

Abstract

Some information systems research has considered that individual personality traits influence whether users feel stressed by information and communication technologies. Personality research suggests, however, that personality traits do not act individually, but interact interdependently to constitute a personality profile that guides individual perceptions and behavior. The study relies on the differential exposure-reactivity model to investigate which personality profiles of the Big Five personality traits predispose users to perceive techno-stressors. Using a questionnaire, data was collected from 221 users working in different organizations. That data was analyzed using fuzzy set Qualitative Comparative Analysis. Based on the results, six different personality profiles that predispose to perceive high techno-stressors are identified. By investigating personality traits in terms of profiles, it is shown that a high and a low level of a personality trait can influence the perception of techno-stressors. The results will allow users and practitioners to identify individuals who are at risk of perceiving techno-stressors based on their personality profile. The post-survey analysis offers starting points for the prevention of perceived techno-stressors and the related negative consequences for specific personality profiles.

Suggested Citation

  • Katharina Pflügner & Christian Maier & Jens Mattke & Tim Weitzel, 2021. "Personality Profiles that Put Users at Risk of Perceiving Technostress," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 389-402, August.
    • Handle: RePEc:spr:binfse:v:63:y:2021:i:4:d:10.1007_s12599-020-00668-7
    DOI: 10.1007/s12599-020-00668-7
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    References listed on IDEAS

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    1. T. S. Ragu-Nathan & Monideepa Tarafdar & Bhanu S. Ragu-Nathan & Qiang Tu, 2008. "The Consequences of Technostress for End Users in Organizations: Conceptual Development and Empirical Validation," Information Systems Research, INFORMS, vol. 19(4), pages 417-433, December.
    2. Wagemann, Claudius & Buche, Jonas & Siewert, Markus B., 2016. "QCA and business research: Work in progress or a consolidated agenda?," Journal of Business Research, Elsevier, vol. 69(7), pages 2531-2540.
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    5. Martin Gerlach & Beatrice Farb & William Revelle & Luís A. Nunes Amaral, 2018. "A robust data-driven approach identifies four personality types across four large data sets," Nature Human Behaviour, Nature, vol. 2(10), pages 735-742, October.
    6. Gimpel, Henner & Lanzl, Julia & Manner-Romberg, Tobias & Nüske, Niclas, 2018. "Digitaler Stress in Deutschland: Eine Befragung von Erwerbstätigen zu Belastung und Beanspruchung durch Arbeit mit digitalen Technologien," Working Paper Forschungsförderung 101, Hans-Böckler-Stiftung, Düsseldorf.
    7. Shirish C. Srivastava & Shalini Chandra & Anuragini Shirish, 2015. "Technostress creators and job outcomes : theorising the moderating influence of personality traits," Post-Print hal-01249895, HAL.
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    Cited by:

    1. Tim Kollmer & Andreas Eckhardt, 2023. "Dark Patterns," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(2), pages 201-208, April.

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