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Strategic Positioning of Turkey Agricultural Products on the Agricultural World Market

2015· book-chapter· en· W2902871011 on OpenAlexaff
Hamadoun Sidibé

Bibliographic record

VenueAdvances in finance, accounting, and economics book series · 2015
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsAgricultureBusinessProduct (mathematics)PortfolioCash cropWorld marketInternational marketCommerceInternational tradeAgricultural economicsEconomicsGeographyFinance

Abstract

fetched live from OpenAlex

Applying a strategic management perspective, particularly the BCG tool, this chapter demonstrates that the agricultural products exported by Turkey are distributed unevenly on the four cells of the global agricultural markets matrix: almost of its products (236 products or 85.20% of its portfolio) are Question Marks, two products are a Star, one product is a Cash cow, and 38 products are Dogs. Such a situation creates important strategic choices for the leaders of the country and for its businesses. None of Turkey top ten exports were among the top ten growers in the world. Turkey is world export leader in ten products, but these products are not the world most growing markets, and the country should increase its relative market share in some of its ten top exports, and also consider developing organic product segments, and eliminate tobacco products in its portfolio.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.016
GPT teacher head0.187
Teacher spread0.171 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2015
Admission routes1
Has abstractyes

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