Influence of Strategic Orientation on SMEs Access to Finance in Nigeria
Bibliographic record
Abstract
The paper examined the influence of EO, MO, LO, and TO on SMEs financial capital accessibility in Nigeria. The purpose of this paper is to establish the role of firm strategic orientation in helping SMEs improve their financial access. A total of 362 questionnaires from SMEs in North Western Nigeria were used in this study. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to test the study hypotheses. Using SmartPLS 3.0 the findings indicates that strategic orientations are important drivers of firm success to finance. The result further suggests that SMEs who configured and utilized their strategic activities are more likely to get more cash flow, profit and retained earnings and will obtain a loan from external sources. To get an adequate financial capital SMEs need to improve their marketing activities, learn more from their experience and environment and lastly produce product with high technological improvement. At the same time they should avoid too much emphasis on taking risky business decision and investments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".