FINANCIAL MECHANISM IN THE SYSTEM OF ECONOMIC VECTORS OF DEVELOPMENT OF HOTEL AND RESTAURANT AND AGRICULTURAL ENTERPRISES
Notice bibliographique
Résumé
The purpose of the work is to study the aspects of the financial mechanism of the hotel-restaurant and agricultural sectors of the economy that interact in the market for the provision of services and sales of products, the definition of its constituent elements, the justification of the proposal to improve the financial instruments of state influence on solving the problems of development of the hotel-restaurant sector and the agricultural sector in the conditions of the emergence of new risks and threats, as well as the need for Ukraine's integration into the global economic space. Results. Thus, it can be argued that the increase in the production of crop products contributes to the increase in the export potential of agriculture. Thanks to the introduction of a preferential regime for rural and urban products. At present, support for the main branches of production (agriculture, food industry) will provide an opportunity to ensure domestic demand and satisfy external demand. Ukraine has joined the countries of the world, which are committed to ensuring sustainable development in accordance with the global SDGs. In 2019, the directions of the country's economic audit and vectors of economic development until 2030 were developed in Ukraine. This document defines 30 development tasks and 170 basic indicators for achieving economic development, taking into account the specifics of the country. An important element in ensuring Ukraine's sustainable development is the financial component. This can be achieved by improving the functioning of certain sectors of the Ukrainian economy. The strategic importance of agricultural development is highlighted, and the interdependence of GDP growth and agricultural exports is calculated. The financial mechanism is influenced by world financial processes and globalisation, therefore it is expedient to adapt the leading experience of foreign countries. International practice shows that the reform of the financial mechanism of agricultural enterprises is carried out mainly at the expense of strengthening the direct and indirect levers of state influence. Government influence is exercised through price regulation of agricultural products and farm incomes, budgetary financing of agricultural activities, provision of affordable credit, transparent and comprehensible taxation, regulation of exports and imports of agricultural products, support for scientific and technical progress, social support for farmers, etc. The success of agriculture in the leading countries of Western Europe, the USA, Canada, China and Japan is due to the fact that the self-regulating mechanisms of the market have been limited by external levers. This is government support for agriculture through subsidies, prices, quotas, credit and tax policies, etc. Methodology. The article develops methods of financial risk management, which include identification, analysis and development of methods of neutralisation of financial risks of a company. Value/originality. The proposed model can be used to guide further GDP growth with the help of other factors. It is necessary to take into account other factors contributing to GDP growth. In general, each country chooses the optimal balance between different instruments for regulating agricultural enterprises, depending on the national characteristics of the development of the agricultural sector and the priority objectives of the agri-food policy. Prospects for further research are related to the development of optimal sources of financial support for agrarian entrepreneurship in Ukraine. Thus, summarising all the above, it can be noted that decision-making is one of the main issues in management, and in the current conditions of unpredictable challenges and changes, every manager faces the need to be creative in solving the tasks. That is why it is necessary for the management of hotel and restaurant facilities in this time of challenges and new business conditions to make certain adjustments to the management decision-making process, applying the considered managerial and organisational features. Since efficiency and consistency in making management decisions is one of the indicators of effective management of any organisation.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».