Description

The purpose of the current study is to reveal personality profiles that predispose to the experience of techno-stressors within an organizational setting. These insights are useful because techno-stressors lead to considerable costs and adverse health effects. We use the theoretical lens of the transaction-based model of stress to study the effect of the Big Five personality traits on techno-stressors. We distributed a self-rating questionnaire among 221 individuals and analyzed data using fuzzy set Qualitative Comparison Analysis. The results reveal that six different personality profiles lead to the experience of techno-stressors. The study contributes to research by revealing that personality traits need to be investigated in profiles when studying their role in technostress and that different profiles of the Big Five predispose to techno-stressors. The results are useful for practitioners as they allow the prevention of techno-stressors and negative consequences by detecting users who are at risk at an early stage.

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Feb 28th, 8:00 AM

Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress

The purpose of the current study is to reveal personality profiles that predispose to the experience of techno-stressors within an organizational setting. These insights are useful because techno-stressors lead to considerable costs and adverse health effects. We use the theoretical lens of the transaction-based model of stress to study the effect of the Big Five personality traits on techno-stressors. We distributed a self-rating questionnaire among 221 individuals and analyzed data using fuzzy set Qualitative Comparison Analysis. The results reveal that six different personality profiles lead to the experience of techno-stressors. The study contributes to research by revealing that personality traits need to be investigated in profiles when studying their role in technostress and that different profiles of the Big Five predispose to techno-stressors. The results are useful for practitioners as they allow the prevention of techno-stressors and negative consequences by detecting users who are at risk at an early stage.

 

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