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Record W4321450065 · doi:10.32782/bses.78-5

MARKETING TOOLS FOR INCREASING THE COMPETITIVENESS OF SOCKS MANUFACTURERS ON THE MARKET

2022· article· en· W4321450065 on OpenAlexaboutno aff
Наталія Косар, Nataliia Kuzo, Svitlana Zatvarnytska

Bibliographic record

VenueBlack Sea Economic Studies · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsSOCKSBusinessProduct (mathematics)Factory (object-oriented programming)Quality (philosophy)CommerceMarket shareConsumption (sociology)MarketingProduction (economics)EconomicsEngineering

Abstract

fetched live from OpenAlex

The hosiery market in Ukraine is one of the most dynamic consumer goods markets, the demand for which is seasonal. It was established that there is no clear trend in demand changes. Ukrainian hosiery manufacturers are actively implementing new technologies, which allow them to export part of their products to European countries, the USA, Canada and others. It has been investigated that the largest manufacturers of hosiery products in Ukraine are Duna-Vesta LLC, Novomoskovsk Knitwear Factory, Zhytomyr Hosiery Factory JSC "Ukraine", Kharkiv Hosiery Factory LLC. Socks occupy a significant share in the total production and consumption of hosiery products. The enterprise's competitiveness in the market largely depends on how effectively it satisfies the needs of consumers. A survey of consumers of sock products was conducted, and it was established that the majority of respondents use socks to protect against the external environment and ensure foot hygiene. According to respondents, the most important characteristics of socks include product quality, product composition, color scheme, durability of socks, and price. When buying socks, respondents prefer retail chains and Internet stores, although about 50% of respondents also bought them in branded stores. Only 16.7% of respondents follow novelties in the hosiery market. Taking into account the obtained results, it is possible to single out such primary tools for increasing the competitiveness of domestic manufacturers of hosiery products on the market as improving the quality of goods, optimizing the product range, first of all, updating it taking into account the specific needs of various market segments, forming a flexible pricing policy, increasing brand recognition, expanding the sales networks and activation of sales promotion measures. To generate demand for new products, manufacturers need to promote them, using primarily sales promotion measures with a long-term effect, that is, those that increase consumer loyalty and promote the implementation of viral marketing. To expand the sales network of domestic manufacturers of hosiery products, it is advisable to use the opportunities of domestic marketplaces, which will allow them to get guaranteed traffic, quick access to the target audience, increase sales volumes, and reduce costs for personnel, traffic and data analytics.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.002

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 head0.037
GPT teacher head0.240
Teacher spread0.203 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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