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Enregistrement W3206915092 · doi:10.24025/2306-4420.62.2021.241830

CLUSTER POLICY OF UKRAINE: TARGET INTERESTS OF REGIONS AND DEVELOPMENT OF ENVIRONMENTAL MANAGEMENT

2021· article· en· W3206915092 sur OpenAlexaff
Olesya Finagina, Інна Бітюк, Eugene Buryak, Olexander Zaporozhets

Notice bibliographique

RevueProceedings of Scientific Works of Cherkasy State Technological University Series Economic Sciences · 2021
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Issues in Ukraine
Établissements canadiensInnovation Cluster (Canada)
Organismes subventionnairesnon disponible
Mots-clésDiversification (marketing strategy)Economic systemConsolidation (business)EconomicsEntrepreneurshipEconomic geographyBusinessMarketing

Résumé

récupéré en direct d'OpenAlex

The article provides a theoretical and methodological generalization and proposes a new solution to the current scientific problem, which is to substantiate practical recommendations for the formation and development of the scientific direction of the cluster economy and expand the use of modern environmental management. A number of literary sources and characteristics of the process of development of scientific thought on the formation of a modern system of knowledge of cluster economics and cluster policy, environmental management and circular economy are presented and systematized. The cluster economy, its theoretical and methodological content as system knowledge and reflection in the newest generalized provisions - social and ecological management are substantiated. The theoretical and genetic development of integration processes in modern regional management is determined taking into account the vectors of social progress, combination of knowledge of economics, innovation, sociology, market theory and entrepreneurship. It is emphasized that integration processes always have general or local action impact on the phenomena and processes of human activity, provide positive or negative dynamics of individual socio-economic phenomena and processes. It is integration as a driving force that shapes the potential of society and the economy of the state and its territories. The key factors of social progress that led to the study of the process of integration in the economy and management are identified: the accelerated formation of the world market and its impact on national economies, changing the borders of regions; consolidation, centralization and diversification of capital, accelerated diversification of production and services; mass production and its dependence on scientific and technological progress, environmental and social standards; territorial redistribution of the world, zones of economic influence and the latest formats of regionalization. The focus is on the fact that the cluster, as a manifestation of economic integration in modern activities, sectoral and regional authorities, is the primary tool for stimulating markets, business, qualitative and quantitative improvement of the business environment, attracting investment, a tool for balancing government and business. It is noted that clusters become the center of industrial policy, balance regional interest groups, stimulate and adjust regional development, accelerate the commercialization of national scientific heritage. Such components of the potential of cluster formation of regions as: science and education are determined; resource base; savings of enterprises and the population; small and medium business and infrastructure to support small and medium business. The realization of the potential of clustering should be based on a system of security against existing risks, the construction of which can quickly form a platform for mutual action, collective decision-making, organizational and control measures. The managerial vision of formation of the strategic purpose of cluster formation taking into account the principles of consolidation and harmonization of key interests is substantiated. The author 's vision of modern tendencies of economic progress, which form the latest vision of economic, ecological, social interests as an integrated manifestation, combination of social, economic and cultural spheres of mankind, is substantiated. The thesis of need and relevance by involving transdisciplinary knowledge and methods of regulating the processes of regional reproduction is presented and substantiated; integration and differentiation of management knowledge; anthropogenic security of human development; systemic socialization on the platform of cluster and circular economies. It is proved that integration as a tool for combining the system of modern knowledge of management and economics forms the potential of society and directs the vectors of economic activity to the standards of trust and socialization. The knowledge of management in the formation of cluster economy of Ukraine on the basis of system integration and balance of national interests is considered and systematically analyzed with recommendations for further study of the existing specifics of social progress, knowledge management and practice of improving the effectiveness of government and business. The author's vision of classification of interests in stimulating cluster formation of enterprises and measures of regional cluster policy on the platforms of action of principles - trust, knowledge-intensive measures, targeted information support, compliance with European integration values ​​is substantiated and given. The obtained conclusions and recommendations on regional cluster policy confirm the prospects of the movement of the regions of Ukraine to the most progressive forms of environmental management with the involvement of regional, sectoral cluster projects and EU programs. The effectiveness and fundamental vectors of the EU regional policy, aimed at building a new model of cluster economy on the basis of trust and balance of interests of business entities, government and the population, are specified.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,037
Score d'incertitude au seuil0,074

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0030,001
Science ouverte0,0000,003
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,203
Écart entre enseignants0,181 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2021
Routes d'admission1
Résumé présentoui

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Même revueProceedings of Scientific Works of Cherkasy State Technological University Series Economic SciencesMême sujetEconomic Issues in UkraineTravaux en français237 207