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Journals / Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi / 2026 / Cilt: 36 Sayı: 2

Examining the Factors Affecting Customers' Adoption of Mobile Banking with Structural Equation Model

Müşterilerin Mobil Bankacılığa Uyumunu Etkileyen Faktörlerin Yapısal Eşitlik Modeli ile İncelenmesi

İlkay Altındağ(Necmettin Erbakan Üniversitesi)0000-0001-5359-8964
Pages
254–263
Publication Date
2020-08-17
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The collected data set was tested by the Structural Equation Model method.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Mobile banking is an application used on a smartphone or tablet that allows you to perform your banking transactions by connecting to the internet from your mobile device without having to go to the branch.
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Key Findings & Data:Mobile banking usage showed a rapid increase in the last 10 years in Turkey as well as all over the world.
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Conclusion & Impact:The collected data set was tested by the Structural Equation Model method.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Yapısal Eşitlik Modeli · Teknoloji Kabul Modeli · Mobil Bankacılık

Abstract

Mobile banking is an application used on a smartphone or tablet that allows you to perform your banking transactions by connecting to the internet from your mobile device without having to go to the branch. Mobile banking usage showed a rapid increase in the last 10 years in Turkey as well as all over the world. However, the fact that some bank customers do not prefer mobile banking for different reasons increases the importance of investigating the factors that affect customers' adoption of mobile banking. It is important that banks adopt the latest information technology system to better understand changing customer needs. The Technology Acceptance Model (TAM) is an information systems theory is used to measure the response of consumers to technological change. The main objective in this research is to analyze the relationships among the factors that determine the attitude of bank customers using mobile banking application via the TAM theory. This research data was collected from surveys applied to public, private and participation bank customers in Konya province. The collected data set was tested by the Structural Equation Model method.

Özet

Mobil bankacılık, şubeye gitmek zorunda kalmadan bir akıllı telefon veya tablet ile mobil cihazınızdan internete bağlanarak bankacılık işlemlerinizi gerçekleştirmenizi sağlayan bir uygulamadır. Mobil bankacılık kullanımı son 10 yılda Türkiye'de ve tüm Dünyada hızlı bir artış göstermektedir. Bununla birlikte, bazı banka müşterilerinin mobil bankacılığı henüz tercih etmemesi, müşterilerin mobil bankacılığı benimsemesini etkileyen faktörlerin araştırılmasının önemini artırmaktadır. Değişen müşteri ihtiyaçlarını daha iyi anlamak için bankaların en son bilgi teknolojisi sistemini benimsemesi önemlidir. Teknoloji Kabul Modeli (TAM), tüketicilerin teknolojik değişime tepkisini ölçmek için kullanılan bir bilgi sistemleri teorisidir. Bu araştırmanın temel amacı, mobil bankacılık uygulamasını kullanan banka müşterilerinin tutumlarını TAM teorisi ile analiz etmektir. Bu araştırma verileri Konya ilindeki kamu, özel ve katılım bankası müşterilerine uygulanan anketlerden toplanmıştır. Elde edilen veriler Yapısal Eşitlik Modeli yöntemi ile test edilmiştir.

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Cite This Article

Altındağ, İ. (2020). Examining the Factors Affecting Customers' Adoption of Mobile Banking with Structural Equation Model. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, Cilt: 36 Sayı: 2, 254–263. https://ajindex.com/articles/1266902

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References (33)

  1. Luo, X., Li, H., Zhang, J., Shim, J. P. 2010. Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision support systems, 49(2), 222-234.
  2. Gu, J. C., Lee, S. C., Suh, Y. H. 2009. Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.
  3. Chang, C. C. 2015. Exploring mobile application customer loyalty: The moderating effect of use contexts. Telecommunications policy, 39(8), 678-690.
  4. Seyrek, I. H., Akşahin, A. 2016. Mobil Bankacılık Uygulamaları Kalite Faktörlerinin Analitik Hiyerarşi Prosesi ile Karşılaştırılması, International Review of Economics and Management, 4(3), 47-61.
  5. Lin, H. F. 2013. Determining the relative importance of mobile banking quality factors. Computer Standards & Interfaces 2013, 35(2), 195–204.
  6. Çelik H., E., Yılmaz, V., Pazarlıoğlu, V., Technology Acceptance Model and an Application, Finans Politik & Ekonomik Yorumlar, Vol. 47, No:540.
  7. Davis, F.D. 1986. A technology acceptance model for empirically testing new end-user information systems: theory and results, PhD dissertation, Massachusetts Institute of Technology, Cambridge, MA.
  8. Davis, F.D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS, Quarterly, 13(3), pp. 319-339.
  9. Abdullah, F., Ward, R. 2016. Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analyzing commonly used external factors. Computers in Human Behavior, 56, 238-256.
  10. Lin, C. A., Kim, T. 2016. Predicting user response to sponsored advertising on social media via the technology acceptance model. Computers in Human Behavior, 64, 710-718.
  11. Chen, C. F., Xu, X., Arpan, L. 2017. Between the technology acceptance model and sustainable energy technology acceptance model: Investigating smart meter acceptance in the United States. Energy research & social science, 25, 93-104.
  12. Dumpit, D. Z., Fernandez, C. J. 2017. Analysis of the use of social media in Higher Education Institutions (HEIs) using the Technology Acceptance Model. International Journal of Educational Technology in Higher Education, 14(1), 5.
  13. Taherdoost, H. 2018. A review of technology acceptance and adoption models and theories. Procedia Manufacturing 2018, 22, 960-967.
  14. Verma, P., Sinha, N. 2018. Integrating perceived economic wellbeing to technology acceptance model: The case of mobile based agricultural extension service. Technological Forecasting and Social Change, 126, 207-216.
  15. Kalyoncuoğlu, S. 2018. Tüketicilerin online alışverişlerindeki sanal kart kullanımlarının teknoloji kabul modeli ile incelenmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 20(2), 193-213.
  16. To, W. M., Tang, M. N. 2019. Computer-based course evaluation: an extended technology acceptance model. Educational Studies, 45(2), 131-144.
  17. Binyamin, S. S., Rutter, M. J., Smith, S. 2019. Extending the Technology Acceptance Model to Understand Students' use of Learning Management Systems in Saudi Higher Education. International Journal of Emerging Technologies in Learning, 14(3).
  18. https://www.tbb.org.tr/tr/banka-ve-sektor-bilgileri/istatistiki-raporlar/Dijital,_Internet_ve_Mobil_ Bankacilik_ Istatistikleri/3814 (Access date: 30.12.2019).
  19. Lee, W. J., Kim, T. U., Chung, J. Y. 2002. User acceptance of the mobile Internet. In Proceedings of the First International Conference on Mobile Business, pp. 8-9.
  20. Lu, J., Yu, C. S., Liu, C., Yao, J. E. 2003a. Technology Acceptance Model for Wireless Internet, Internet Research: Electronic Network Application Policy, 13, 206-222
  21. Lu, J., C. Liu, C.S. Yu, J.E. Yao 2003b Exploring Factors Associated with Wireless Internet Via Mobile Technology Acceptance in Mainland China, Communications of the International Information Management Association, 3, 101-120.
  22. Rosenbaum, H., Kleber B. 2004. A Socio-Technical Analysis of M-Commerce in Japan:Research in Progress, AMCIS Proceedings, 334.
  23. Cheong, J.H., Park M. 2005. Mobile Internet Acceptance in Korea, Internet Research, 15(2), 125-140.
  24. Dai, H., Palvi, P. C. 2009. Mobile commerce adoption in China and the United States: a cross-cultural study. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 40(4), 43-61.
  25. Bolat, Y. İ., Aydemir, M., Karaman, S. 2017. Uzaktan Eğitim Öğrencilerinin Öğretimsel Etkinliklerde Mobil İnternet Kullanımlarının Teknoloji Kabul Modeline Göre İncelenmesi. Gazi University Journal of Gazi Educational Faculty (GUJGEF), 37(1)
  26. Uğur, N., G., Turan, A., H., 2016, Mobile application Acceptance model: A scale development Study Hacettepe Journal of Economics and Administrative Sciences, Vol. 34, Issue 4, p. 97-125.
  27. Pastırmacıoğlu, B., Çalışkan, S. Determining a Mobile Internet Acceptance Model of Special Education Teacher Candidates, iJIM 2018, Vol. 12, No. 4
  28. Çelik, H. E., Yılmaz, V. 2016. LISREL 9.1 ile yapısal eşitlik modellemesi: Temel kavramlar uygulamalar programlama. Anı Yayıncılık, Ankara, 261 p.
  29. Hoyle, R. H., 1995. Structural equation modeling: Concepts, issues, and applications, Thousand Oaks, California: Sage Publications, 312.
  30. Raykov, T., Marcoulides, G. A. 2006. A first course in structural equation modeling, Mahwah, NJ: Lawrence Erlbaum Associates.
  31. Çelik, H. E. 2009. Yapısal Eşitlik Modellemesi ve Bir Uygulama: Genişletilmiş Online Alışveriş Kabul Modeli, Doktora Tezi, Osmangazi Üniversitesi Fen Bilimleri Enstitüsü, Eskişehir.
  32. Schermelleh-Engel, K., Moosbrugger, H., Müller, H. 2003. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
  33. Jöreskog, K.G., Sörbom, D. 1993. LISREL 8 User’s Reference Guide; PRELIS 2 User’s Reference Guide, Scientific Software International, Chicago.