ДОСЛІДЖЕННЯ ТЕНДЕНЦІЙ РОЗРАХУНКІВ ПЛАТІЖНИМИ КАРТКАМИ В ВОЄННИЙ ПЕРІОД
Notice bibliographique
Résumé
The purpose of the article is to study trends in transactions with payment cards issued by Ukrainian banks during a period when the country's economy is surviving in conditions of full-scale hostilities and to identify directions for the further development of payments by payment cards. Methodology of research. The goal set in the article was achieved using such research methods as analysis and synthesis, comparison, summarization and grouping, scientific abstraction, and economic and mathematical forecasting. Findings. An analysis of scientific opinion was conducted, and the conclusion was made that the obvious advantages of payment cards for all entities of monetary circulation led to the active development of the market for these payment instruments in most countries, including Ukraine. The dynamics of the number of issued and active payment cards for 2023 - 1st quarter of 2025, transactions using cards in Ukraine and abroad during this period were studied, and the main directions in which payments using this payment instrument are developing today were identified. An analysis of the volume of payment card transactions showed a 43% increase in the first quarter of 2025 compared to the first quarter of 2023, which was facilitated by the increase in financial literacy of the population, which realized the advantages of card payments and the further development of digitalization of the banking sector of Ukraine. It is noted that the main trend in the development of the payment card market in Ukraine over the period under review is the constant growth of non-cash card payments. It is explained that a significant number of Ukrainians continue to be forced to stay outside the country and therefore the volume of payment card transactions outside Ukraine is increasing. It was determined that payments with contactless and tokenized payment cards are growing particularly rapidly due to the development of digital technologies in banking. The main directions in which payments using this payment instrument are developing today have been identified. It has been concluded that with the development of digitalization of banking technologies, the volume of non-cash payments using payment cards is increasing, with the number of contactless and tokenized cards gradually increasing. Practical value. Using formulas developed by software tools that predict the number of contactless and tokenized payment cards, it is possible to calculate the volume of payment card payments for 2025 - 2026.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,007 |
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 ».