HR technologies and HR-staff technostress: an unavoidable or combatable effect?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Drawing on the job demands-resources and IS literatures, the purpose of this paper is to identify organizational factors that mitigate technostress in the HR department; and to evaluate how technostress and techno-insecurity affect technology’s impact on job satisfaction. Design/methodology/approach This research draws on a web-based survey of 169 US and Canadian firms targeting HR executives as key informants. An HR-context-specific, technostress model was tested with structural equation modeling. Exploratory factor analysis evaluated the structural properties of all multi-item scales and supported their usage. Moderated regression analysis further assessed whether the age and scope of technology portfolios affected certain relationships. Findings As predicted, department work stress was less likely to increase when there was HR technology (HRT) governance involvement and top management support for this class of technologies. Heightened techno-insecurity had the opposite effect, another anticipated outcome. HR’s IT-knowledge actually increased technostress, a counterintuitive result. In turn, HRTs were less likely to improve job satisfaction when technostress and techno-insecurity were high. Top management HRT support and an HR innovation climate better enabled portfolios to enhance satisfaction. Moderating influences were detected as well. As hypothesized, techno-insecurity had a stronger negative effect on job-satisfaction impact for younger portfolios, while innovation climate had a weaker relationship with techno-insecurity where portfolios were limited in scope. Research limitations/implications External validity would be strengthened by not only increasing sample sizes for the USA and Canada, but also targeting more nations for data collection. In addition, incorporating more user-oriented constructs in the present model (e.g. group potency, collective efficacy) may enhance its explanatory power. Practical implications These findings underscore the need to consider HR-staff attitudes in technology rollouts. To the extent HR technologies generate technostress, they at a minimum are impediments to department satisfaction, which may have important ramifications for usage and service. The results further establish that initiatives can be taken to offset this problem, both in terms of the ways portfolios are internally supported and how they are managed. Originality/value This is the first study to formally assess how collective work-attitudes in the HR department are affected by HR technologies. Prior research has focused on user-reactions to HRT features or their wider influence on stakeholder perceptions. It is also the first investigation to empirically test potential technostress inhibitors in HR settings.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it