‘No-growth’ entrepreneurial strategy in microenterprises
Bibliographic record
Abstract
It has been demonstrated that many small businesses have no desire for growth. In this article, we investigate whether a ‘no-growth’ strategy in microenterprises can still lead to performance enhancement. To explore this issue, we followed a panel of 13 microenterprises over 12 years with an ‘acted research’ protocol. This consisted of yearly intensive interactions between academics and panel participants including four group seminars, one interview with each owner-manager and firm observation. It resulted in a co-constructed model of ‘no-growth’ to which all study participants agreed. During the study, all 13 microenterprises reduced their employee count and pivoted their business models toward more exclusive offerings. Underpinned by the resource-based and dynamic capabilities theory, we demonstrate that a ‘no-growth’ strategy resulted in increase in margins, efficiency improvements and better work-life balance for the owner-managers and their collaborators. Theoretical, methodological and managerial implications are provided.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".