Mobil Ödeme Teknolojisi Kabulünün Teknoloji Kabul Modeli ile İncelenmesi: Ampirik Bir Araştırma

Yıl 2020, , 119 - 145, 30.06.2020

Ceylan Bozpolat , Hülya Seyhan

https://doi.org/10.18074/ckuiibfd.619852

Cited By: 6

Öz

Bu çalışma banka
müşterilerinin mobil ödeme teknolojisini kabul etme süreçlerinde etkili olan
faktörleri belirlemek amacıyla yapılmıştır. Bu bağlamda Davis (1989) tarafından
geliştirilen Teknoloji Kabul Modeli (TAM) referans alınmıştır. Çalışmaya
ilişkin verileri toplamak amacıyla Nevşehir ilinde kolayda örnekleme metodu ile
belirlenen 500 mobil ödeme kullanıcısına anket uygulanmıştır. Elde edilen
veriler ile öncelikle Açıklayıcı ve Doğrulayıcı Faktör Analizi, sonrasında ise
Path Analizi yapılmıştır. Açıklayıcı faktör analizi sonucunda Davis (1989)
TAM’ın alt değişkenlerini destekleyen faktörler ortaya çıkmıştır. Doğrulayıcı
faktör analizinin uyum değerleri ise kabul edilebilir uyum göstermiştir. Path
analizi sonucunda doğrudan etki bakımından algılanan kullanım kolaylığının
algılanan fayda; algılanan faydanın tutum; tutumun ise niyet üzerinde pozitif
yönde etkisi olduğu görülmüştür. Sonuçlar dolaylı etki bakımından
incelendiğinde ise algılanan kullanım kolaylığının, tutumu ve niyeti şekillendiren
en güçlü değişken olduğu tespit edilmiştir. Mobil ödeme teknolojisinin kabulünü
öngörmek için TAM’ın sınandığı bu çalışma, literatüre katkı sağlamakta ve
sonuçları çözüm sağlayıcılara faydalı bilgiler sunmaktadır.

Anahtar Kelimeler

Mobil Ödeme, Teknoloji Kabul Modeli, Path Analizi

Investigation of Mobile Payment Technology Acceptance with Technology Acceptance Model: An Empirical Research

Öz

This
study was carried out to determine the factors that affect the process of
accepting mobile payment technology of bank customers. In this context, the
Technology Acceptance Model (TAM) developed by Davis (1989) is taken as
reference. In order to collect the data related to the study, a questionnaire
was applied to 500 mobile payment users determined by easy sampling method in
Nevsehir. Explanatory and Confirmatory Factor Analysis and then Path Analysis
were performed with the obtained data. As a result of the explanatory factor
analysis, Davis (1989) revealed the factors that support the sub-variables of
TAM. The agreement values of the confirmatory factor analysis showed acceptable
agreement. As a result of path analysis, perceived usefulness of perceived ease
of use in terms of direct effect; attitude of perceived usefulness; attitude
has a positive effect on intention. When the results were examined in terms of
indirect effect, perceived ease of use was found to be the most powerful
variable shaping attitude and intention. This study, in which TAM is tested to
predict the acceptance of mobile payment technology, contributes to the
literature and the results provide useful information to solution providers.

Anahtar Kelimeler

Mobile Payment, Technology Acceptance Model, Path Analysis

Kaynakça

• Agarwal, R., Ahuja, M., Carter, P. E., ve Gans, M. (1998). Early and Late Adopters of IT Innovations: Extensions to Innovation Diffusion Theory. In Proceedings of the DIGIT Conference, 1-18.
• Anderson, J.C., ve Gerbing, D.W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411-423.
• Baabdullah, A., Nasseef, O., ve Alalwan, A. (2016). Consumer Adoption of Mobile Government in the Kingdom of Saudi Arabia: The Role of Usefulness, Ease of Use, Perceived Risk and Innovativeness. Social Media: The Good, the Bad, and the Ugly, 267-279.
• Bentler, P. M., ve Boonnet, D. G. (1980). Significance Tests and Goodness-of-Fit in the Analysis of Covariance Structure. Psychological Bulletin, 88(3), 588–606.
• Bolat, Y. İ., Aydemir, M., ve Karaman, S. (2017). Uzaktan Eğitim Öğrencilerinin Öğretimsel Etkinliklerde Mobil İnternet Kullanımlarının Teknoloji Kabul Modeline Göre İncelenmesi. 37 (1), 63- 91.
• Browne, M. W., ve Cudeck, R. (1992). Alternative Ways of Assessing Model Fit. Sociological Methods & Research, 21(2), 230-258.
• Byrne, B.M.. (2001). Structural Equation Modeling, with AMOS: Basic Concepts, Applications and Programming. Lawrence Erlbaum Associates, Mahwah, New Jersey.
• Chau, P. Y., ve Lai, V. S. (2003). An Empirical Investigation of the Determinants of User Acceptance of Internet Banking. Journal of Organizational Computing and Electronic Commerce, 13(2), 123-145.
• Chen, L. D. (2008). A Model of Consumer Acceptance of Mobile Payment. International Journal of Mobile Communications, 6(1), 32-52.
• Cho, Y. C., ve Sagynov, E. (2015). Exploring Factors That Affect Usefulness, Ease Of Use, Trust, And Purchase Intention In The Online Environment. International Journal of Management & Information Systems, 19 (1), 21- 36.
• Çivici, T., ve Kale, S. (2007). Mimari Tasarım Bürolarında Bilişim Teknolojilerinin Kullanımını Etkileyen Faktörler: Bir Yapısal Denklem Modeli. 4. İnşaat Yönetimi Kongresi, 119- 128.
• Dahlberg, T., Mallat, N., Ondrus, J., ve Zmijewsska, A. (2006). Mobile Payment Market and Research - Past, Present and Future. Working Papers on Information Systems, 6(48), 1- 16.
• Dahlberg, T., Mallat, N., Ondrus, J., ve Zmijewsska, A. (2007). Past, Present and Future of Mobile Payments Research: A Literature Review. Electronic Commerce Research and Applications, 1- 17.
• Davis, F. D. (1986). A Technology Acceptance Model for Empirically Testing New Enduser Information System: Theory and Results. Doctoral Dissertation, Sloan School of Management, Massachusetts Institute of Technology.
• Davis, F. D. (1989). Perceived Usefulness Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13 (3), 319- 340.
• Doshi, P. V. (2018). Relationship of Perceived Ease use and Perceived Usefulness on Usage of E-Commerce Site. International Journal of Academic Research and Development, 3 (1), 495- 498.
• Elkaseh, A. M., Wong, K. W., ve Fung C. C. (2016). Perceived Ease of Use and Perceived Usefulness of Social Media for e-Learning in Libyan Higher Education: A Structural Equation Modeling Analysis. International Journal of Information and Education Technology, 6 (3), 192- 199.
• Eriksson, K., Kerem, K., ve Nilsson, D. (2005). Customer Acceptance of Internet Banking in Estonia. International Journal of Bank Marketing, 23(2), 200-216.
• Fornell C., ve Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50.
• Gefen, D., ve Keil, M. (1998). The Impact of Developer Responsiveness on Perceptions of Usefulness and of Use" An Extension of the Technology Acceptance Model. The DATA BASE for Advances in Information Systems, 29 (2), 35- 49.
• George, D., ve Mallery, P. (2016). SPSS for Windows Step by Step: A Simple Guide and Reference. (14th ed.), New York: Routledge Taylor & Francis.
• Ha, I., Yoon, Y., ve Choı, M. (2007). Determinants of Adoption of Mobile Games Under Mobile Broadband Wireless Access Environment. Information & Management, 44(3), 276-286.
• Hair, J. F., William C. Black; Barry J. Babin ve Rolph E. Anderson (2006). Multivariate Data Analysis. New Jersey: Pearson Prentice Hall.
• Hu, P. J., Chau, P.Y.K., Shheng, O. R L., ve Tam, K. Y. (1999). Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Journal of Management Information Systems, 16 (2), 91–112
• Igbaria, M., Zinatelli, N., Cragg, P., ve Cavaye, A. L. (1997). Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model. MIS Quarterly, 21(3), 279-305.
• İşbankası (2012). İş Bankası’ndan Ödeme Sistemlerinde Devrim Yaratacak Uygulama: Parakod. https://www.isbank.com.tr/TR/hakkimizda/haberler-ve-medya/haberler/ (Erişim Tarihi: 28 Ağustos 2019).
• Jackson, C. M., Chow, S., ve Leitch, R. A. (1997). Toward an Understanding of the Behavioral Intention to Use an Information System. Decision Sciences, 28 (2), 357- 389.
• James, T., Pirim, T., Boswell, K., Reithel, B., ve Barkhi, R. (2006). Determining the Intention to Use Biometric Devices: An Application and Extension of the Technology Acceptance Model. Journal of Organizational and End User Computing (JOEUC), 18(3), 1-24.
• Karahanna, E., Srtaub, D. W., ve Chervany, N. L. (1999). Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs. MIS Quarterly, 23 (2), 183–213.
• Keil, M., Beranek, P. M., ve Konsynski, B. R. (1995). Usefulness and Ease of Use: Field Study Evidence Regarding Task Considerations. Decision Support Systems, 13, 75–91.
• Kim, C., Mirusmonov, M., ve Lee, I. (2009). An Empirical Examination of Factors Influencing the Intention to Use Mobile Payment. Computers in Human Behavior, 26(3), 310-322.
• Kotler, P. (2000). Pazarlama Yönetimi. (Çeviren: Nejat Muallimoğlu), İstanbul: Beta Basım A.Ş.
• Kutsal, S. (2018). Dünden Bugüne Dijital Ödeme Sistemlerinin Evrimi. https://digitalage.com.tr/dunden-bugune-dijital-odeme-sistemlerinin-evrimi/ (Erişim Tarihi: 28 Ağustos 2019).
• Lee, M. K. O., Cheung, C. M. K. ve Chen, Z. (2005). Acceptance of Internet- Based Learning Medium: The Role of Extrinsic and Intrinsic Motivation. Information & Management, 42 (8), 1095- 1104.
• Mallat, N. (2007). Exploring Consumer Adoption of Mobile Payments - A Qualitative Study. The Journal of Strategic Information Systems, 16(4), 1- 14.
• Marsh, H. W., Balla, J. R., ve Mcdonald, R. P. (1988). Goodness-of-Fit Indexes in Confirmatory Factor Analysis: The Effect of Sample Size. Psychological Bulletin, 103(3), 391-410.
• Meydan, C. H., ve Harun, Ş. (2015). Yapısal Eşitlik Modellemesi Amos Uygulamaları. 2. Baskı, Ankara: Detay Yayıncılık.
• Monsuwé, T. P., Dellaert, B. G. C., ve Ruyter, K. (2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management, 15 (1), 102- 121.
• Moon, J. W., ve Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web Context. Information & Management, 38(4), 217-230.
• Ohk, K., Park, S. B., ve Hong, J. W. (2015). The Influence of Perceived Usefulness, Perceived Ease of Use, Interactivity, and Ease of Navigation on Satisfaction in Mobile Application. Advanced Science and Technology Letters, 84, 88- 92.
• Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning. Educational Technology & Society, 12 (3), 150–162.
• Pedersen, P. E., ve Nysveen, H. (2003). Usefulness and Self-Expressiveness: Extending TAM to Explain the Adoption of A Mobile Parking Service. 16th Bled eCommerce Conference, 705-717.
• Raza, S. A., Umer, A., ve Shah, N. (2017). New Determinants of Ease of Use and Perceived Usefulness for Mobile Banking Adoption. Int. J. Electronic Customer Relationship Management, 11 (1),44- 65.
• Schermelleh- Engel, K., Moosbrugger, H., ve 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.
• Schierz, P. G., Schilke, O., ve Wirtz, B. W. (2010). Understanding Consumer Acceptance of Mobile Payment Services: An Empirical Analysis. Electronic Commerce Research and Applications, 9(3), 209-216.
• Shih, H. P. (2004). An Empirical Study on Predicting User Acceptance of E- Shopping on the Web. Information & Management, 41, 351- 368.
• Suh, B., ve Han, I. (2002). Effect of trust on customer acceptance of Internet banking. Electronic Commerce research and applications, 1(3-4), 247-263.
• Szajna, B. (1996). Empirical evaluation of the Revised Technology Acceptance Model. Management Science, 42 (1), 85– 92.
• Tassabehji, R., ve Kamala, M. A. (2009). Improving e-Banking Security with Biometrics: Modelling User Attitudes and Acceptance. In 2009 3rd International Conference on New Technologies, Mobility and Security, 1-6.
• Taylor, S., ve Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19 (4), 561- 570.
• TDK (2019). Büyük Türkçe Sözlük. http://www.tdk.gov.tr/ (Erişim Tarihi: 29.Ağustos 2019).
• Vallerand, R. J., Deshaies, P., Cuerrier, J., Pelletier, L. G. ve Mongeau, C. (1992). Ajzen and Fishbein’s Theory of Reasoned Action as Applied to Moral Behavior: A Cofirmatory Analysis. Journal of Personality and Social Psychology, 62(1), 98-109.
• Wessels, L., ve Drennan, J. (2010). An Investigation of Consumer Acceptance of M-Banking. International Journal of Bank Marketing, 28(7), 547-568.
• Yang, H. D., ve Yoo, Y. (2004). It's all about attitude: revisiting the technology acceptance model. Decision Support Systems, 38(1), 19-31.
• Yap, B. W., ve Khong, K. W. (2006). Examining the Effects of Customer Service Management (CSM) on Perceived Business Performance via Structural Equation Modelling. Applied Stochastic Models in Business and Industry, 22(5-6), 587-605.