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Record W4361853509 · doi:10.55365/1923.x2023.21.21

Competitive Potential Branding Model of Subjects of Agro-food Economy Sector Ukraine

2023· article· en· W4361853509 on OpenAlex
Петро Макаренко, V. P. Pilyavsky, Inna Мykolenko, O.O. Varchenko

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of Economics and Finance · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture Market Analysis Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAgricultureCompetitive advantageValue (mathematics)UkrainianSupply chainAgribusinessEconomic sectorIndustrial organizationEconomicsEconomyMarketing

Abstract

fetched live from OpenAlex

The article examines the special conditions for the development of the competitive potential branding model of subjects of agro-food sector of economy of Ukraine.It is proven that the branding model in the system of subjects competitive potential of the agri-food sector of the economy ensures the value and effectiveness of the agricultural raw materials supply chain in the market with a low degree of processing, and also regulates the interindustry interaction of its participants.It is substantiated that the methodological basis of the competitive potential branding model of subjects of the agro-industrial sector of the economy is the calculation of the additional value of products in the supply chain of agricultural raw materials on the market with a low degree of processing, by combining global and national "Input-Output" indicators of a certain country, in the flow of bilateral trade The method of evaluating the competitive positioning of subjects of the agro-food sector of the economy on the market is presented.A collection of brand evaluation methods is grouped according to the factor indicator of the development of competitive branding of agro-food products.The economic activity of the dairy industry and the dairy production structure in the priority regions of Ukraine were analyzed.World and Ukrainian leaders of dairy companies on the market have been identified.Moreover, it has been proven that the competitive branding of subjects of the agro-industrial sector of the economy of Ukraine in the integration interaction with the EU countries contributes to the acceleration of investment activities for the modernization of the dairy production technology and their quality.An assessment of market attractiveness and competitive potential of the leaders of branded dairy products in Ukraine was carried out.The "McKinsey" matrix was built and the positions of dairy product leaders on the market were determined.Proposed measures to increase the competitive potential of dairy companies of the agro-food sector of the Ukrainian economy according to the composite scoring index Market Score, which determines the market opportunities and branding capabilities of the studied entities on the market.The difficulties faced by dairy companies of the agro-food sector of the economy of Ukraine during the war and the ways to solve them are analyzed as well.

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.

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 score0.569
Threshold uncertainty score0.186

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 communication0.0000.000
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 head0.017
GPT teacher head0.191
Teacher spread0.174 · 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