A technostress–entrepreneurship nexus in the developing world
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
Abstract Research indicates that entrepreneurs are relying on digital technology for their entrepreneurial endeavours, yet there is little knowledge on how to balance technology usage and wellbeing. Drawing on the concept of technostress and 643 observations of nascent South African entrepreneurs’ interactions with digital technology, we advance knowledge at the technostress–entrepreneurship nexus. Partial least squares structural equation modelling (PLS-SEM) results reveal how digital self-efficacy moderates their behaviour and inability to balance digital technology usage with wellbeing. These results confirm entrepreneurship passion and perceived behavioural control as predictors of technostress amongst these entrepreneurs. They also suggest that the benefits of digital technology are not a predictor of technostress in African entrepreneurship; thus, extending a conceptual overlay of digital technology, digital self-efficacy, entrepreneurial passion (EP), and behaviour to define the mechanisms underlying a technostress–entrepreneurship nexus. The results show social, policy, and research implications in today’s technology-driven environments characterised by a mixture of midrange to complete digital transformations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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