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THE PECULIARITIES OF THE FORMATION AND FUNCTIONING OF LOGISTICS FLOWS IN THE FURNITURE INDUSTRY

2022· article· en· W4320503535 on OpenAlex
Olha Pavlykivska, Evelina Kamyshnykova, Lesia Halyniak

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueHerald of Khmelnytskyi National University Economic sciences · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsFactory (object-oriented programming)BusinessUkrainianQuarter (Canadian coin)Supply chainFurniture industryCommerceMarketingOperations managementEngineeringComputer scienceGeography

Abstract

fetched live from OpenAlex

It is known that the reformatting of logistics has become a key challenge for Ukrainian enterprises. It is outlined the main logistical problems during wars, which include refusal to accumulate, change in storage conditions, difficulties with purchase of goods, complication of logistics operations. It is considered the logistical activities of the private enterprise “Husiatyn furniture factory “Elegant” (Ternopil region, Chortkivskyi district), in particular, a change of logistics chain supplying of the main raw material, upholstery fabric for furniture, since February 24, 2022. The efficiency of replenishment is characterized of the company’s car fleet in connection with the purchase of a cargo vehicle of a DAF car for the delivery of own products, primarily to the eastern and southern regions. The sales activity of the furniture factory “Elegant” was monitored in the section of three zones: West, Center and South. It is determined the sales share of each region in the total volume of sales of the furniture enterprise for the period from 2016 to 2021. It was established that the leading positions from the implemented sales belong to the Western region (46%) due to geographic location of the furniture factory. It was found that during the analyzed period, all the IV quarter of the year is the most effective in the regions. Such dynamics are inherent not only furniture companies. New Year and Christmas are the most favourite holidays for Ukrainians, but they are “hottest” time for shopping in Ukraine. Furniture products are not an exception. Just to prepare for the celebration of the New Year and Christmas consumers spend a significant part of the funds. It is analyzed the work of the Husiatyn furniture factory on a monthly basis since the beginning of the Russian invasion on the territory of our state. It is determined the critical periods and positive shifts in economic activity of a furniture company. After comparing the volume indicators sale of furniture products in physical and value terms according to similar months in January – September 2021 and 2022, we draw the conclusions about a real picture of the work of the furniture enterprise today

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)0.002
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 score0.647
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.044
GPT teacher head0.213
Teacher spread0.169 · 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