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Record W2184341969

TECHNICAL-ECONOMICAL COMPETITIVENESS OF FOOD INDUSTRY

2014· article· en· W2184341969 on OpenAlexaboutno aff
Ghelase Daniela, Daschievici Luiza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsCompetitor analysisBusinessIndustrial organizationCompetitive advantageQuality (philosophy)PopulationWork (physics)Food industryMarketingEngineering
DOInot available

Abstract

fetched live from OpenAlex

In the literature, different definitions of competitiveness exist. The EU Commission (2003) uses as a definition of competitiveness: the ability of an economy to provide its population with high and rising standards of living and a high level of employment for all those willing to work, on a sustainable basis‖. Another definition which is more focused on the manufacturing (Lall, 2001) sectors states: competitiveness in industrial activities means developing relative efficiency along with sustainable growth. According to Canada‘s Agri-Food competitiveness Task Force competitiveness is defined as: the sustained ability to profitably gain and maintain market share (Martin, Westgren v Fischer and Schornberg, 2007). At the firm level, the view of competitiveness can be given as (Buckley, et al., 1988): A firm is competitive if it can produce products and services of superior quality and lower costs than its domestic and international competitors. This paper presents a new approach of technical-economical competitiveness for food industry, and a new type of competitive management of them, so that their technical-economical performance be maximized.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.960

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)0.0010.000

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 head0.019
GPT teacher head0.211
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations0
Published2014
Admission routes1
Has abstractyes

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