Human resources management 4.0: Literature review and trends
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
Digitalization across a range of industry and service sectors is transforming the workplace and human resources. The adoption of disruptive technologies associated with the Fourth Industrial Revolution, also known as Industry 4.0, is reshaping the way people work, learn, lead, manage, recruit, and interact with each other. The aim of this study is to contribute to the theoretical development of human resource management (HRM) in the context of Industry 4.0, promoting directions for the sector and HRM professionals, organizations, and the workforce that are required to face the challenges of Industry 4.0. To achieve this objective, this study performs a systematic literature review and content analysis of 93 papers from 75 journals. The main results of the research show that digital trends resulting from Industry 4.0 affect the field of HRM in 13 different themes, promoting trends and challenges for HRM, the workforce, and organizations. This paper seeks to promote insights for studies on the interference of digitalization in HR for the evolution of the digital age, as well as for companies that want to become more productive, human, and digital.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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