Acquiring market flexibility via niche portfolios
Bibliographic record
Abstract
Purpose This paper seeks to establish that the instability of niche markets, and their predisposition to catastrophic collapse, makes market flexibility a prerequisite for long‐term survival among niche marketers. It describes the two ways by which a niche marketer can acquire this market flexibility and demonstrates the advantages of the second of these two approaches, i.e. the development of a portfolio of separated niches. Design/methodology/approach An in‐depth discussion of niche instability/implosion, and how niche market flexibility can be acquired to increase the survivability of such events, provides the context for a single in‐depth case study of a company employing a systematic niche market flexibility approach. A multi‐method approach was adopted drawing on both interviews and documentary evidence. Findings Planning for flexibility is essential for long‐term survival as a niche marketer. Two broad approaches to achieve this exist – i.e. contingency and portfolio planning – which are not mutually exclusive. The portfolio approach offers specific advantages and examples of its successful applications exist. Research limitations/implications This is a single case study. Practical implications The article has significant implications for practice, as fragmentation of markets and globalisation of production makes niche marketing desirable/essential for many players. Originality/value The area of planning for flexibility using a niche portfolio marketing strategy is under‐researched at present.
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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 | 0.015 | 0.002 |
| 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 | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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 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".