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Record W4313391270 · doi:10.37634/efp.2022.11(3).2

Peculiarities of importing vehicles from the USA

2022· article· en· W4313391270 on OpenAlex

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

VenueEconomics Finances Law · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Systems and Logistics Management
Canadian institutionsnot available
Fundersnot available
KeywordsCommon value auctionBusinessInternational tradeIndustrial organizationInternational economicsEconomics

Abstract

fetched live from OpenAlex

Introduction. In recent years, there is a tendency of growth in imports of vehicles. This situation is due to the formation of demand in the domestic market. Domestic enterprises are unable to meet this demand. The structure of imports is dominated by imports from EU countries (67.61%), but other markets such as the USA and countries of America (27.72%), North Korea (2.29%) and other countries are gaining new momentum. Imports of vehicles from the USA, Canada, Georgia and North Korea have now undergone certain logistical changes, because a large number of seaports are under occupation. This situation has caused a change in the route through the ports of the EU countries. Nevertheless, the prospects for expanding imports of vehicles from the USA are significant, because this market is represented by newer models, a wide range and nomenclature, cheaper segment, the availability of purchase due to the presence of a number of online auctions. The purpose of the paper is to form a detailed model of vehicle imports from the USA. The following methods were used in writing the paper: analysis, comparison, explanation, theoretical generalization, grouping, etc. Results. The paper analyzes the features of vehicle imports from the USA, presents the characteristics of the largest auctions representing used, damaged and new vehicles, describes how to participate in auctions, gives the structure of vehicle imports for 2021, identifies the prospects for vehicle imports. Also, in the publication there is a detailed model of import of vehicles from the USA, which provides a step-by-step description of import from the moment of searching at the auction to the moment of customs clearance in Ukraine, considering specifics of loading, delivery to the port of departure, choice of logistic method of sea transportation, insurance method, making changes in the supply chain by building new routes through the EU countries and customs clearance. Conclusions. The use of this model by a number of companies starting to import vehicles from the USA or planning to import, as well as having problems at certain stages of the import process, will allow to take into account all the nuances of this process and avoid mistakes. A detailed import model takes into account not only the selection of vehicles at auctions, but also transportation, insurance, shipping, and customs clearance.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.049
GPT teacher head0.202
Teacher spread0.153 · 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