The human element in digital transformation: The role of talent management for SMEs
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
The role of digitalization for business performance has attracted significant research interest. While many studies have advanced the literature with insights on digital tools and strategies, what is less well understood is the role of the human factor in this process. The objective of this study is to assess the role of the human element in the digitalization of small and medium-sized enterprises (SMEs). Theoretically, we draw on sociotechnical theory and dynamic capabilities to underline the importance of integrating the technology and human aspects for enhancing SME performance. Empirically, we use a representative dataset of 1,000 Bulgarian SMEs and perform structural equations modeling. Our findings reveal that the existence of digital strategies by themselves may not lead to improved performance unless they are well integrated with the appropriate talent management practices that support organizational agility. The results underscore the importance of considering the pathways through which digital strategy affects organizational performance for SMEs.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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