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A RESEARCH ON THE FACTORS AFFECTING THE INTENTION TO USE DIGITAL BANKING

Year 2020, Volume: 2 Issue: 2, 69 - 85, 23.01.2021

Abstract

The main purpose of this study is to examine the factors that affect the bank customers' intention to use digital banking and to make an assessment based on the findings. For this purpose, the effects of perceived usefulness, perceived trust and perceived benefit on the intention to use digital banking were investigated. Data of this study were collected online from 225 people via structured questionnaires. The obtained data were analyzed and reported by SPSS and Smart PLS package programs. As a result of these analyzes; it is determined that the perceived usefulness, perceived trust and perceived benefit variables have a significant effect on intention to use digital banking.

References

  • Albashrawi, M., & Motiwalla, L. (2017). Understanding Mobile Banking Usage. Proceedings of the 2017 ACM SIGMIS Conference on Computers and People
  • Bhatiasevi, V. 2015. An extended UTAUT model to explain the adoption of mobile banking. Information Development.
  • Cheong, J. H., & Park, M. C. (2005). Mobile İnternet acceptance in Korea. Internet Research, 15, 125-140.
  • Civelek, M., (2018) “Yapısal Eşitlik Modellemesi Metodolojisi”, İstanbul: Beta Yayıncılık.
  • Çelik, H. E., ve V. Yılmaz., "LİSREL 9.1 ile Yapısal Eşitlik Modellemesi", İstanbul: Anı Yayınları, 2013.
  • Davis, F.D. (1989). ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS Quarterly, 13(3): 319-340.
  • Doğan, D. (2018), SmartPLS ile Veri Analizi, US: Charleston SC.
  • Eid, M.I. (2011). ‘Determinants of e-commerce customer satisfaction, trust, and loyalty in Saudi Arabia’, Journal of Electronic Commerce Research, 12(1): 78-93.
  • Eriksson, K., Kerem, K. & Nilsson, D. (2005). ‘Customer acceptance of internet banking in Estonia’, International Journal of Bank Marketing, 23(2): 200-216.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
  • Forsythe SM, Shi B. Consumer patronage and risk perceptions in internet shopping. J Bus Res 2003; 56:867–75.
  • Hair Jr, J. F., Hult, G. T. M., Ringle, C. ve Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM)(2. Baskı), Sage Publications.
  • Hair, J.F., Tomas, G., Hult, M., Ringle, C.M., Sarstedt, M. (2014), A Primer on Partial Least Square Structural Equations Modeling (PLS-SEM), Los Angeles: Sage.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
  • Henseler, J., Ringle, C. M. ve Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Sinkovics, R. R. ve Ghauri, P. N. (Ed.), New challenges to international marketing (Advances in international marketing) (277-319). Emerald Group Publishing Limited.
  • Huang S-M, Hung Y-C, Yen DC. (2005) A study on decision factors in adopting an onlinestock trading system by brokers in Taiwan. Decis Support Syst;40(2):315–28.
  • Kuisma T, Laukkanen T, Hiltunen M. (2007) Mapping the reasons for resistance to internet banking: a means-end approach. Int J Inform Manage;27(2):75–85.
  • Klarner, P., Sarstedt, M., Hoeck, M. ve Ringle, C. M. (2013). Disentangling the effects of team competences, team adaptability, and client communication on the performance of management consulting teams. Long Range Planning, 46(3), 258-286.
  • Kline, R. B. “Principles and Practice of Structural Equation Modeling”, (Third Edition). New York: The Gouilford Press, 2011.
  • Kurt, K, Turan, A. (2017). Mobil Bankacılık Uygulamalarının Benimsenmesine Yönelik Davranışsal Niyetleri Etkileyen Faktörler Üzerine Bir Araştırma. İşletme Bilimi Dergisi, 5 (3), 25-58.
  • Laukkanen, T. & Cruz, P. (2008). Comparing consumer resistance to mobile banking in Finland and Portugal. In Filipe, J. & Obaidat, M.S. (Eds) ICETE 2008, CCIS 48, Berlin Heidelberg: Springer-Verlag.
  • Lee, M.C. (2009). Factors ınfluencing the adoption of ınternet banking: An integration of TAM And TPB with perceined risk and perceived benefit. Electronic Commerce Research and Applications, 130-141.
  • Lin, F., Fofanah, S.S. & Liang, D. (2011). ‘Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success’, Government Information Quarterly, 28(2): 271-279.
  • Littler D, Melanthiou D. (2006). Consumer perceptions of risk and uncertainty and the implications for behaviour towards innovative retail services: the case of internet banking. J Retailing Consum Serv;13(6):431–43.
  • Özecan, M. (2018). Factors Affecting Mobile Banking Usage Intention, User Satisfaction and Word-Of-Mouth Intention. Doctoral Dissertation. İstanbul Bilgi University Institute of Social Sciences. İstanbul.
  • Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model, Internet Research, 14(3), 224–235.
  • Reavley N. (2005). Securing online banking. Card Technol Today;17(10):12–3.
  • Riquelme, H.E. & Rios, R.E. (2010). ‘The moderating effect of gender in the adoption of mobile banking, International Journal of Bank Marketing, 28(5): 328-341.
  • Sattler, H., Völckner, F., Riediger, C. ve Ringle, C. M. (2010). The impact of brand extension success drivers on brand extension price premiums. International Journal of Research in Marketing, 27(4), 319-328.
  • Shih, Y. ve Fang, K. (2004). The Use of Decomposed Theory of Planned Behaviour to Study Internet Banking in Taiwan, Internet Research, 14 (3): 213-223.
  • Ustasüleyman, T, Eyüboğlu, K. (2010). Bireylerin İnternet Bankacılığını Benimsemesini Etkileyen Faktörlerin Yapısal Eşitlik Modeli ile Belirlenmesi. BDDK Bankacılık ve Finansal Piyasalar Dergisi, 4 (2), 11-38.
  • Yıldırır, S, Kaplan, B. (2019). Mobil Uygulama Kullanımının Benimsenmesi: Teknoloji Kabul Modeli ile Bir Çalışma. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 10 (19), 22-51.
  • İnternet Kaynakları: https://www.tbb.org.tr/tr/bankacilik/banka-ve-sektor-bilgileri/istatistiki-raporlar/59, erişim tarihi: 14.12.2020

DİJİTAL BANKACILIK KULLANIM NİYETİNE ETKİ EDEN FAKTÖRLER ÜZERİNE BİR ARAŞTIRMA

Year 2020, Volume: 2 Issue: 2, 69 - 85, 23.01.2021

Abstract

Bu araştırmanın temel amacı, banka müşterilerinin dijital bankacılık kullanım niyetine etki eden faktörleri incelemek ve elde edilen bulgulara dayanarak değerlendirme yapmaktır. Bu amaç doğrultusunda algılanan kullanışlılık, algılanan güven ve algılanan fayda değişkenlerinin dijital bankacılık kullanım niyeti üzerindeki etkisi araştırılmıştır. Araştırmanın verileri yapılandırılmış anket formu vasıtasıyla toplamda 225 online olarak toplanmıştır. Elde edilen bu verilerin SPSS ve Smart PLS paket programları ile analizleri gerçekleştirilmiş ve raporlanmıştır. Yapılan analizler sonucunda; algılanan kullanışlılık, algılanan güven ve algılanan fayda değişkenlerinin dijital bankacılık kullanım niyeti üzerinde anlamlı bir etkisinin olduğu tespit edilmiştir.

References

  • Albashrawi, M., & Motiwalla, L. (2017). Understanding Mobile Banking Usage. Proceedings of the 2017 ACM SIGMIS Conference on Computers and People
  • Bhatiasevi, V. 2015. An extended UTAUT model to explain the adoption of mobile banking. Information Development.
  • Cheong, J. H., & Park, M. C. (2005). Mobile İnternet acceptance in Korea. Internet Research, 15, 125-140.
  • Civelek, M., (2018) “Yapısal Eşitlik Modellemesi Metodolojisi”, İstanbul: Beta Yayıncılık.
  • Çelik, H. E., ve V. Yılmaz., "LİSREL 9.1 ile Yapısal Eşitlik Modellemesi", İstanbul: Anı Yayınları, 2013.
  • Davis, F.D. (1989). ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS Quarterly, 13(3): 319-340.
  • Doğan, D. (2018), SmartPLS ile Veri Analizi, US: Charleston SC.
  • Eid, M.I. (2011). ‘Determinants of e-commerce customer satisfaction, trust, and loyalty in Saudi Arabia’, Journal of Electronic Commerce Research, 12(1): 78-93.
  • Eriksson, K., Kerem, K. & Nilsson, D. (2005). ‘Customer acceptance of internet banking in Estonia’, International Journal of Bank Marketing, 23(2): 200-216.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
  • Forsythe SM, Shi B. Consumer patronage and risk perceptions in internet shopping. J Bus Res 2003; 56:867–75.
  • Hair Jr, J. F., Hult, G. T. M., Ringle, C. ve Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM)(2. Baskı), Sage Publications.
  • Hair, J.F., Tomas, G., Hult, M., Ringle, C.M., Sarstedt, M. (2014), A Primer on Partial Least Square Structural Equations Modeling (PLS-SEM), Los Angeles: Sage.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
  • Henseler, J., Ringle, C. M. ve Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Sinkovics, R. R. ve Ghauri, P. N. (Ed.), New challenges to international marketing (Advances in international marketing) (277-319). Emerald Group Publishing Limited.
  • Huang S-M, Hung Y-C, Yen DC. (2005) A study on decision factors in adopting an onlinestock trading system by brokers in Taiwan. Decis Support Syst;40(2):315–28.
  • Kuisma T, Laukkanen T, Hiltunen M. (2007) Mapping the reasons for resistance to internet banking: a means-end approach. Int J Inform Manage;27(2):75–85.
  • Klarner, P., Sarstedt, M., Hoeck, M. ve Ringle, C. M. (2013). Disentangling the effects of team competences, team adaptability, and client communication on the performance of management consulting teams. Long Range Planning, 46(3), 258-286.
  • Kline, R. B. “Principles and Practice of Structural Equation Modeling”, (Third Edition). New York: The Gouilford Press, 2011.
  • Kurt, K, Turan, A. (2017). Mobil Bankacılık Uygulamalarının Benimsenmesine Yönelik Davranışsal Niyetleri Etkileyen Faktörler Üzerine Bir Araştırma. İşletme Bilimi Dergisi, 5 (3), 25-58.
  • Laukkanen, T. & Cruz, P. (2008). Comparing consumer resistance to mobile banking in Finland and Portugal. In Filipe, J. & Obaidat, M.S. (Eds) ICETE 2008, CCIS 48, Berlin Heidelberg: Springer-Verlag.
  • Lee, M.C. (2009). Factors ınfluencing the adoption of ınternet banking: An integration of TAM And TPB with perceined risk and perceived benefit. Electronic Commerce Research and Applications, 130-141.
  • Lin, F., Fofanah, S.S. & Liang, D. (2011). ‘Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success’, Government Information Quarterly, 28(2): 271-279.
  • Littler D, Melanthiou D. (2006). Consumer perceptions of risk and uncertainty and the implications for behaviour towards innovative retail services: the case of internet banking. J Retailing Consum Serv;13(6):431–43.
  • Özecan, M. (2018). Factors Affecting Mobile Banking Usage Intention, User Satisfaction and Word-Of-Mouth Intention. Doctoral Dissertation. İstanbul Bilgi University Institute of Social Sciences. İstanbul.
  • Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model, Internet Research, 14(3), 224–235.
  • Reavley N. (2005). Securing online banking. Card Technol Today;17(10):12–3.
  • Riquelme, H.E. & Rios, R.E. (2010). ‘The moderating effect of gender in the adoption of mobile banking, International Journal of Bank Marketing, 28(5): 328-341.
  • Sattler, H., Völckner, F., Riediger, C. ve Ringle, C. M. (2010). The impact of brand extension success drivers on brand extension price premiums. International Journal of Research in Marketing, 27(4), 319-328.
  • Shih, Y. ve Fang, K. (2004). The Use of Decomposed Theory of Planned Behaviour to Study Internet Banking in Taiwan, Internet Research, 14 (3): 213-223.
  • Ustasüleyman, T, Eyüboğlu, K. (2010). Bireylerin İnternet Bankacılığını Benimsemesini Etkileyen Faktörlerin Yapısal Eşitlik Modeli ile Belirlenmesi. BDDK Bankacılık ve Finansal Piyasalar Dergisi, 4 (2), 11-38.
  • Yıldırır, S, Kaplan, B. (2019). Mobil Uygulama Kullanımının Benimsenmesi: Teknoloji Kabul Modeli ile Bir Çalışma. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 10 (19), 22-51.
  • İnternet Kaynakları: https://www.tbb.org.tr/tr/bankacilik/banka-ve-sektor-bilgileri/istatistiki-raporlar/59, erişim tarihi: 14.12.2020
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Articles
Authors

Mustafa Kaplan 0000-0002-5205-2123

Cahide İrem Korkmaz 0000-0002-8490-4642

Publication Date January 23, 2021
Submission Date December 26, 2020
Acceptance Date January 12, 2021
Published in Issue Year 2020 Volume: 2 Issue: 2

Cite

APA Kaplan, M., & Korkmaz, C. İ. (2021). DİJİTAL BANKACILIK KULLANIM NİYETİNE ETKİ EDEN FAKTÖRLER ÜZERİNE BİR ARAŞTIRMA. Management and Political Sciences Review, 2(2), 69-85.


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