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Enregistrement W4401450576 · doi:10.52340/eab.2024.16.02.07

Impact of Digital Banking Services on Consumer Satisfaction

2024· article· en· W4401450576 sur OpenAlex
Nugzar Todua, Nino Gogitidze

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Notice bibliographique

RevueEconomics and Business · 2024
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueTechnology Adoption and User Behaviour
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBusinessMarketingBusiness managementRetail bankingCustomer satisfactionDigital transformationIndustrial organizationBusiness administrationCommerceComputer science

Résumé

récupéré en direct d'OpenAlex

<p style="text-align: right;"><a href="https://search.crossref.org/search/works?q=10.52340%2Feab.2024.16.02.07&from_ui=yes">doi.org/10.52340/eab.2024.16.02.07</a> <p style="text-align: justify;">The main factors affecting the use of digital banking services by customers in Georgian banks are studied in the article. Based on diverse literature, appropriate hypotheses and a conceptual model of research have been developed. The questionnaire survey method is used for the research. Data were collected through a random sampling of consumers and a self-administered questionnaire. The collected data is used to process correlation, regression, and factor analysis. The reliability of the research analysis was confirmed, and the main factors identified were awareness, ease of use, trust, and social media marketing activities, which have a positive effect on the intention to use digital banking, which, in turn, has a positive impact on satisfaction and use of Internet banking. As a result of the research, it was determined that consumers in the banking sector of Georgia should be encouraged to use digital banking services through various marketing activities. This paper provides theoretical guidance on the characteristics of digital banking services and the main factors influencing their use by customers. The research has practical applications for commercial banks operating in Georgia, which can adapt this model to the natural environment. This model will help banks use digital banking services to increase customer satisfaction and improve existing digital products.<br />The results of the study show that close digital interaction with customers through social media has a positive effect on increasing trust; customers perceive the use of digital services as less risky, which encourages the actual use of Internet banking. Therefore, the variables studied are an effective driving force for Georgian banks` digital marketing strategy, which increases their chances of meeting customer expectations. Based on the results of the research, bank marketing should be aimed at the continuous improvement of digital banking services, which will promote the perception of more benefits among customers and, therefore, increase satisfaction with the received services. This optimistic outlook on the potential improvements in customer satisfaction can inspire the audience to take action.<br />It is expected that the results of the study will improve the existing knowledge about the characteristics of digital banking services and the main factors of their use by customers. In this study, reliable tools are used to study the factors affecting the use of digital banking services. Therefore, the conducted research allows for the development of such recommendations, the consideration of which will improve digital banking services in the Georgian market. Above all, commercial banks operating in Georgia can adapt this model by using digital banking services to increase customer satisfaction, as well as to improve existing applications and digital products. The use of the resources presented in the study is recommended in the process of forming digital banking services. Based on the conducted research, Georgian banks should provide consumers with instructions that encourage them to actively use digital services. Acquaintance with the results of the present study is recommended for both middle and top managers to make the service quality improvement process more flexible and help the marketing portfolio take a leading position in the banking industry. This reiteration of the research`s importance can make the audience feel valued and integral to the industry`s operations. <p style="text-align: justify;"><strong>References:</strong><br />• Ahmad S., Bhatti S. H., & Hwang Y. (2020). E-Service Quality and Actual use of E-Banking: Explanation through the Technology Acceptance Model. Information Development, 36(4), 503-519.<br />• Akıl S., & Ungan M. C. (2022). E-Commerce Logistics Service Quality: Customer Satisfaction and Loyalty. Journal of Electronic Commerce in Organizations (JECO), 20(1), 1-19.<br />• Alarifi A. A., & Husain K. S. (2023). The Influence of Internet Banking Services Quality on E-Customers’ Satisfaction of Saudi Banks: Comparison Study before and During COVID-19. International Journal of Quality & Reliability Management, 40(2), 496-516.<br />• Alfarizi M. (2023). Interaction of Customer Satisfaction and Digital Service Retention: Evidence of PLS from Indonesian Islamic Banking. 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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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,198
Score d'incertitude au seuil0,346

Scores Codex et Gemma par catégorie

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

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 Opus0,053
Tête enseignante GPT0,343
Écart entre enseignants0,290 · 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