IMPACT OF DIGITALISATION AND INVESTMENTS IN INTANGIBLE CAPITAL ON THE NON-FINANCIAL PERFORMANCE OF FIRMS IN SLOVENIA
Bibliographic record
Abstract
Article examines the impact of digitalisation and intangible capital investment on the non-financial performance of firms in Slovenia. Article examines the relationship between: (1) digitalisation and firms’ nonfinancial performance; (2) digitalisation and firms’ attitude to digitalisation; (3) investments in intangible capital and firms’ non-financial performance; where we (4) also expect differences by industry and between firms operating in global value chains. Considering survey data, the SEM approach shows that, digitalisation and intangible investment both have positive effects on non-financial performance. Level of digitalisation depends on the importance attributed to digitalisation, whereas the importance of digitalisation depends on the expected long-term benefits of digitalisation for the firm. Level of digitalisation is dependent on the anticipated long-term benefits of digitalisation. These have a positive, yet non-significant impact on a firm’s level of digitalisation. Despite business agility having an impact on the importance of digitalisation for businesses that is less than the expected benefits, it is still highly significant. Other results were not statistically significant. Keywords: intangible capital, digitalisation, firm performance
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".