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Record W2060398647 · doi:10.1017/s1742170514000489

Niche marketing and farm diversification processes: Insights from New Zealand and Canada

2015· article· en· W2060398647 on OpenAlexaffabout
Robert P. Hamlin, John Knight, Ron Cuthbert

Bibliographic record

VenueRenewable Agriculture and Food Systems · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsOlds College
Fundersnot available
KeywordsNiche marketNicheBusinessDiversification (marketing strategy)Industrial organizationPortfolioAgricultureMarketingEcologyBiologyFinance

Abstract

fetched live from OpenAlex

Abstract In many developed countries agriculture is undergoing significant changes. Traditional commodity markets are increasingly being supplemented or even displaced by niche markets served by firms producing specialty products. The purpose of this paper is to determine why firms seek out niche markets and what contributes to their success. This paper investigates the characteristics that make niche markets attractive to small and medium-sized agricultural firms and the ways in which these firms become highly adapted for their chosen niche. Results indicate that forming alliances and the development of horizontal and vertical networks are among the most common and most important strategies employed by successful niche marketers. The study found that firms market niche products as part of a portfolio of products that often includes an anchoring commodity. Results also suggest that aggressive growth and pricing strategies may negatively impact a firm's ability to sustain barriers to entry. The development of a niche positioning strategy is often the outcome of a reaction to an existing situation rather than of a priori strategic planning.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.165
Teacher spread0.151 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2015
Admission routes2
Has abstractyes

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