Technology Acquisition and SMEs Performance, the Role of Innovation, Export and the Perception of Owner-Managers
Bibliographic record
Abstract
Sufficient literature supports small and medium ‘enterprises’ (SMEs) significant role in emerging and mature economies. Still, the same research highlights varying challenges that innovative firms in developing economies face, like access to formal credit and external markets. This study examines the effect of a capital budget’s proportion for acquiring new technology and sale performance between 2017–2019 using a sample of 101 Kenyan SMEs. The ordinary least square moderated mediation results indicate that: (1) the proportion of the capital budget allocated for the acquisition of technology positively and significantly influences sales; (2) the index of moderated mediation suggests that the perception of firm owner-managers towards the availability of formal credit moderates the mediated relationship between the capital budget’s portion spent on technology and sales as mediated by innovation activities. However, the index is insignificant for the second mediator, export longevity. However, in the final model, both the level of innovation and export longevity positively and substantially affect sales.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".