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MARKETING STRATEGIES FOR PROMOTION OF ORGANIC FOODSTUFFS ON FOREIGN MARKETS

2021· article· en· W4212962783 on OpenAlexaboutno aff
Yaroslava Larina, Vira Fomishyna, O. Shaporenko

Bibliographic record

VenueEconomic innovations · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Development Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingPromotion (chess)BusinessAppealMarketing strategyConsumption (sociology)Industrial organization

Abstract

fetched live from OpenAlex

Topicality. Marketing becomes a necessary and effective tool for doing business, the basis of enterprise management, which is strategically focused on achieving market success. However, domestic companies - participants in the market of organic products have not yet fully realized the need to implement modern principles and tools of marketing. Special attention needs to be paid to the strategic aspects of the operation of such enterprises, in particular, the development of marketing strategies for promotion in domestic and foreign markets. Commercial and communication effects will depend on the correct choice of basic, foreign economic, competitive and functional strategies, promotion channels, formation of communication appeal, amount of invested funds, etc. Aim and tasks. The purpose of the article is to develop theoretical and methodological foundations for the formation and implementation of strategies for promoting organic food products in foreign markets, taking into account changes in consumer needs and demand dynamics. The objectives of the study include: identifying key trends in the consumption of organic products on the world market; clarification of the stages of formation of the marketing strategy of promotion of organic food products on foreign markets. Research results. The results of the research give grounds to claim that insufficient dynamics of growth of the domestic market of organic products transforms foreign economic activity into the main component of effective development of producers of organic food products. It is proved that the largest consumers of organic food are countries with a high level of socio-economic development and a high standard of living of the majority of the population. The following regularities of development of foreign markets of organic products are revealed: expansion of the range of organic products, steady tendency of growth of sales volumes, supported by import; high quality requirements, mandatory certification. The main markets for organic products are European markets, China, Canada, USA, Latin America. It was found that in foreign markets the most important problems in the field of promotion are the complexity of studying the marketing environment, identifying key characteristics of the target consumer and compliance with standards in a particular country. Conclusion. Based on the study, conclusions about the following stages formation of marketing strategy of advancement of organic foodstuff on foreign markets were made: defining the goals of promotion; assessment of factors influencing the strategy and complex of promotion; the actual development of the strategy; the choice of means of influencing consumers; budget calculation. The most important factors for the formation of marketing strategy to promote organic food products to foreign markets and ensure high performance of companies exporting organic products are: determining the type of buyer, target audience, product type, stage of the life cycle. It has been proven that in the process of bringing organic food products to the foreign market, it is advisable to apply a push strategy at the beginning, as intermediaries better understand the specifics of demand and local consumers. and in the future for the development of the market you can also use the strategy of attraction or mixed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.052
GPT teacher head0.238
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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