Technostress and the hierarchical levels of personality: a two-wave study with multiple data samples

Maier, Christian; Laumer, Sven; Wirth, Jakob; Weitzel, Tim

doi:10.1080/0960085x.2019.1614739

Cited by 126 publications

(124 citation statements)

References 108 publications

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“…They provide theoretical and empirical evidence that conditions that create technostress, or technostressors, constitute technology use‐related demands (Ayyagari et al, ; Tarafdar et al, ). The consequences of technostress for the individual include reduced job satisfaction, innovation, productivity, end user satisfaction, and performance (Ragu‐Nathan, Tarafdar, Ragu‐Nathan, & Qiang, ; Tarafdar et al, ; Tarafdar, Tu, & Ragu‐Nathan, ), and increased burnout (Ayyagari et al, ; Maier, Laumer, Wirth, & Weitzel, ). In an experiment relating to a task done on a computer, stress from simulated interruptions led to a decline in performance on that task (Galluch, Grover, & Thatcher, ).…”

Section: Literature Backgroundmentioning

confidence: 99%

Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior

Tarafdar

Maier

Laumer

et al. 2019

Information Systems Journal

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This paper investigates under what conditions stress fromthe use of SNS is linked to addiction to the use of the same SNS. Integrating three theoretical strands-the concept of feature-rich Information Technology (IT), the theory of technology frames, and distraction as a coping behaviour-we theorize two types of coping behaviours in response to stressors experienced from the use of SNS. These are -distraction through use of the same SNS and distraction through activities outside the use of the SNS. We hypothesize relationships between stressors from SNS use, the two coping behaviours and SNS addiction. We further articulate the role of SNS use habit. We test the hypotheses through a three-wave survey of 444 Facebook users with data collected at three different points in time. The paper's contributions are to theorize and empirically validate the psychological concept of distraction as a coping behaviour in response to stress from the use of SNS and, in doing so, explain why there may be a link between technostress from and technology addiction to the use of the same SNS.

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Section: Literature Backgroundmentioning

confidence: 99%

Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior

Tarafdar

Maier

Laumer

et al. 2019

Information Systems Journal

Self Cite

170

135

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“…The ''onset'' of techno-stressors depends on multiple risk factors. Next to technological factors (Ayyagari et al 2011), personality traits predispose users to perceive techno-stressors (Maier et al 2019;. For example, neurotic individuals who tend to experience negative emotions easily, are likely to perceive technostress.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, we see that we need to study personality profiles to understand user perceptions, because some personality profiles predispose to perceptions such as stress, but others do not. Since technostress research has focused mainly on the influence of individual personality traits (Maier et al 2019), it leaves room for comprehensively explaining the predisposing role of personality profiles and the interaction among risk factors, e.g., multiple personality traits. The contribution of one risk factor in terms of a personality trait might depend on the manifestation of another personality trait, and a high and a low level of a personality trait might influence techno-stressor perception.…”

Section: Introductionmentioning

confidence: 99%

Personality Profiles that Put Users at Risk of Perceiving Technostress

et al. 2020

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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.

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“…Besides these contributions, the presented paper underlies several limitations. First, the generalizability of the findings is restricted as only German millennials are interviewed and we did not control for potential personality differences [55] or any other biased relation to IT [56]. Moreover, there is a possible distortion in the selection of participants as recruiting of interviewees took place within the personal network of the authors.…”

Section: Discussionmentioning

confidence: 99%

AI Recruitment: Explaining job seekers’ acceptance of automation in human resource management

Ochmann¹,

Laumer²

2020

WI2020 Zentrale Tracks

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Organizations are increasingly adopting automation in human resource management (HRM). Subsumed under the term "AI recruitment" organizations try to restructure HRM and apply innovative technologies to achieve a higher level of efficiency. Considering the ongoing "war for talent", it is also crucial to discuss candidates' expectations regarding these automated recruiting methods. In this research, we develop a research model explaining the acceptance of AI-based recruiting methods by job seekers. Based on UTAUT2 as a theoretical lens and 23 semi-structured interviews we discuss factors that influence job seekers' acceptance of automation in HRM. The proposed model addresses research gaps in acceptance research in general and the use of technologies in the recruiting process in particular. We also discuss implications for technology acceptance research and provide some suggestions for the examination of a more passive use of IT.

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Technostress and the hierarchical levels of personality: a two-wave study with multiple data samples

Cited by 126 publications

References 108 publications

Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior

Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior

Personality Profiles that Put Users at Risk of Perceiving Technostress

AI Recruitment: Explaining job seekers’ acceptance of automation in human resource management

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