MétaCan
Menu
Back to cohort

SPECIFICITY OF REGIONAL INDUSTRIAL ENTERPRISES OPERATION AND THREATS TO THEIR ECONOMIC SECURITY

2017· article· en· W2908495864 on OpenAlexaboutno aff
A. A. Golovin, M. A. Parkhomchuk, A. Golovin

Bibliographic record

VenueProceedings of Southwest State University · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsSanctionsBusinessProduction (economics)Competition (biology)IndustrialisationOrder (exchange)Industrial organizationControl (management)Economic securityEconomic policyMarket economyEconomicsEconomic systemFinanceEconomic growth

Abstract

fetched live from OpenAlex

The economic sanctions of the United States, Canada, Australia, the EU in banking and technological sectors jeopardized Russia's national security. Moreover, the break of traditional technological chains of industrial enterprises in Russia and Ukraine set the task of accelerated import substitution. The economic situation inside the country is depressed, since internal reserves are insufficient for quick solution of the import substitution problem. An important condition to increase the efficiency of industrial production is the search for internal reserves at the local level, as well as ensuring sustainable operation of enterprises. The concept of sustainable operation of an enterprise includes its economic security, determined both by internal and external factors. In this paper a number of specific features of industrial production such as strict regulation and control by the state, a high level of specialization, technical complexity, the need for highly qualified specialists, and complexity of spatial placement is defined. Features of industrial production determine threats to the enterprise economic security. A high degree of regulation and control by the state creates the following threats: pressure of public authorities in order to obtain benefits, use of administrative resources in trade wars and raidership, frequent and drastic changes of laws, the risk of falling into dependence on officials, shareholders and partners. The focused narrow specialization of production negatively affects the ability of an enterprise to react quickly to market changes, and, first of all, the market conjuncture. This feature forms the following threats: falling demand for manufactured products, stiffening competition in a certain territory, aggravation of competition with enterprises producing similar goods, monopolization of the market, unfair competition. Due to technical complexity of the production process, the following threats arise: high degree of wear and tear of equipment, industrial injuries and manufacturing defects. A significant need for highly qualified specialists is conditioned by the complexity of the technological process and forms the following threats: labour shortage, low personnel qualifications, flow of highly qualified specialists to competitors, and the risky investments in personnel. The location of a number of industrial productions is bound to the locations of resources and markets. Metallurgical production is heavily dependent on the location of deposits of iron ore and coal. A number of industries gravitates to the market channels. Relationship of business owners and local authorities also influences enterprise location. Depending on the form of relationship, the enterprise is provided with the most comfortable or complicated business conditions. The considered specific features of ensuring economic security of industrial enterprises determined the arising threats. If security threats are known, they can be quantified, which will facilitate continuous monitoring of the situation. The program for ensuring economic security of an industrial enterprise should include continuous monitoring, a set of measures to neutralize threats and tools to minimize losses.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.256
Teacher spread0.209 · 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 teacher head, 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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of Southwest State UniversitySame topicEconomic and Technological Developments in RussiaFrench-language works237,207