Strategies for Sustaining Small Business Beyond 10 Years
Bibliographic record
Abstract
Small business owners in the restaurant industry face financial, operational, and competitive challenges that often lead to failure. Identifying practical solutions to these setbacks is critical to empowering entrepreneurs and fostering sustainable strategies for long-term success. Grounded in Lazear's jack-of-all-trades theory, the purpose of this qualitative multiple case study was to explore effective business planning strategies used by small restaurant owners to stay competitive and sustainable beyond the first 10 years of operation. The participants were five small restaurant owners in Western Canada, each with over 10 years of experience. Data were collected through semistructured interviews, public records, and organizational documents. Thematic analysis revealed key strategies: consistent industry benchmarketing, staff training, and adopting technologies like point-of-sale systems. Other strategies comprised strategic planning, adaptability, and customer relationship management. Recommendations include conducting periodic business evaluations, prioritizing employee development, and leveraging technology to enhance operations. The implications for positive social change include the potential to implement business planning strategies that improve small business sustainability, thereby fostering employee well-being, supporting local economies, and utilizing local suppliers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".