Revitalising Small Business Growth Strategies: Exploring the Risk-Benefit of Strategic Management Approaches
Bibliographic record
Abstract
The growth of small and medium scale business is today, one of the objectives of government due to the role these businesses has to play in the development process of an economy. It is thus not surprising the various government interventions through incentives and grants in this subsector, and the imperative for a search for better ways of achieving growth. This paper is premised on this background with the overall objective of examining the risk-benefits of strategic management approaches of revitalising the growth strategies of SMEs. From a survey design adopted, data were collected from a sample 167 SMEs operators in AkwaI bom State, Nigeria and analysis using frequency and correlation statistics. The result indicated that strategic management approaches such as the balance scorecard, SWOT analysis, Porters’ Five Factor Forces, and PEST analysis all have the risk-benefits of positively influencing the growth strategies of SMEs such as product development, market development, market penetration and diversification but that most SMEs do not usually give adequate consideration of these approaches before selecting and implementing their strategies. The paper concluded that SMEs failures are due to their inadequate consideration of strategic management approaches in the choice of growth strategies and recommended that SMEs should adopt an integrative strategic analysis of the various strategic factors in their operational environment before selecting and implementing their growth strategies. This way, they would grow sustainably and profitably and contribute meaningfully to the growth and development of the economy.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".