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Enregistrement W4400185775 · doi:10.32620/cher.2024.2.07

РОЗВИТОК МОБІЛЬНИХ ПЛАТЕЖНИХ СЕРВІСІВ: МАРКЕТИНГ FINTECH ПРОДУКТІВ

2024· article· en· W4400185775 sur OpenAlex

Pourquoi ce travail est dans la base

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Notice bibliographique

RevueTIME DESCRIPTION OF ECONOMIC REFORMS · 2024
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueDigital Transformation in Financial Services
Établissements canadiensOptech (Canada)
Organismes subventionnairesnon disponible
Mots-clésMobile paymentPaymentBusinessPromotion (chess)Context (archaeology)Financial servicesMarketingPayment service providerPersonalizationFinance

Résumé

récupéré en direct d'OpenAlex

In today's world, financial technology (FinTech) has become an integral part of everyday life, significantly changing the way people interact with financial services. One of the most dynamically developing industries is mobile payment services. They provide a fast, convenient and secure way to carry out financial transactions through mobile devices. However, despite the rapid spread of mobile payment services, there are a number of problems and challenges associated with their development and promotion on the market. The purpose of the study is to analyze the development of mobile payment services in the context of FinTech, as well as to develop effective marketing strategies for promoting these products on the market. The object of the study is mobile payment services as an innovative segment of FinTech and their marketing in the modern market, namely aspects related to the development, implementation, promotion and use of mobile payment services. Scientific publications and monographic editions, magazine articles and materials of scientific and practical conferences became the methodological basis of the research. Content analysis of scientific periodicals was used during the research; comparative critical analysis of existing approaches and methods of analysis of financial stability and tax burden; statistical methods of analysis. The main hypothesis of the research is that effective marketing strategies focused on technological innovation, personalization of user experience and taking into account the cultural characteristics of markets significantly increase the adoption and use of mobile payment services among consumers. Summary of the main material. Innovative technologies and platforms based on the concept of embedded finance and their potential to change and transform the financial sphere are highlighted. The technological, economic and regulatory aspects of the use of embedded finance are analyzed, and the key challenges and opportunities associated with their application are identified. As a result of the study, it is established that integrated finance can become a significant factor in accelerating the innovative development of the financial sector, improving the quality of financial services, and ensuring greater accessibility and efficiency in the provision of financial products and services. Originality and practical significance. The originality of the scientific article lies in the comprehensive approach to the study of mobile payment services through the prism of marketing strategies in the FinTech sector. Despite the considerable interest in the technological aspects of mobile payments, the issues of effective marketing of these products remain less studied. The practical significance of the article is that the research results can be used by both FinTech companies and marketing specialists to improve their strategies and increase the efficiency of mobile payment services. Conclusions and prospects for further research. The analysis showed that the introduction of the latest technologies, such as blockchain, artificial intelligence and biometric authentication methods, significantly increases the security and convenience of mobile payment services, which contributes to their popularization among consumers. The combination of technological innovation, personalization and cultural adaptation in marketing strategies is the key to successful promotion of mobile payment services. Further research is needed to assess the long-term consequences of introducing new technologies into mobile payment services. Particular attention should be paid to data security and confidentiality.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,744
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,002
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,036

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 Opus0,032
Tête enseignante GPT0,217
Écart entre enseignants0,185 · 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