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

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.

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

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.

___

  • Agarwal, R., Ahuja, M., Carter, P. E. & 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. & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103 (3), 411-423. https://doi.org/10.1037/0033-2909.103.3.411
  • Askool, S., Pan, Y. C., Jacobs, A. & Tan, C. (2019). Understanding proximity mobile payment adoption through technology acceptance model and organisational semiotics: An exploratory study. In 24th UK Academy for Information Systems International Conference, Oxford, UK, 9-10 April 2019.
  • Baabdullah, A., Nasseef, O. & 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. https://doi.org/10.1007 / 978-3-319-45234-0_25
  • Bentler, P. M. & Bonnet, D. G. (1980). Significance tests and goodness-of-fit in the analysis of covariance structure. Psychological Bulletin, 88 (3), 588-606. https://doi.org/10.1037/0033-2909.88.3.588
  • Bolat, Y. İ., Aydemir, M. ve Karaman, S. (2017). Uzaktan eğitim öğrencilerinin öğretimsel etkinliklerde mobil internet kullanımlarının teknoloji kabul modeline göre incelenmesi. Gazi Eğitim Fakültesi Dergisi, 37 (1), 63-91.
  • Browne, M. W. & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21 (2), 230-258. https://doi.org/10.1177/0049124192021002005
  • Byrne, B. M. (2001). Structural equation modeling, with AMOS: Basic concepts, applications and programming. Mahwah, New Jersey: Lawrence Erlbaum Associates.
  • Ceylan, H. H., Genç, E. ve Erem, I. (2013). Tüketicilerin internet bankacılığını benimsemesini etkileyen faktörlerin yapısal eşitlik modeli ile araştırılması. Anadolu Üniversitesi Sosyal Bilimler Dergisi,13 (3), 143-154.
  • Chau, P. Y. & 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. https://doi.org/10.1207/S15327744JOCE1302_3
  • Chen, L. D. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6 (1), 32-52. https://doi.org/10.1504 / IJMC.2008.015997
  • Chen, R. & He, F. (2003). Examination of brand knowledge, perceived risk and consumers’ intention to adopt an online retailer. Tom & Business Excellence, 40 (6), 677-693. https://doi.org/10.1080/1478336032000053825
  • Cho, Y. C. & 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. https://doi.org/10.19030/ijmis.v19i1.9086
  • Çabuk, S., Tanrıkulu, C. ve Gelibolu, L. (2014). Satışçıların teknoloji kabulü ve kişisel yenilikçiliğin teknoloji kabulüne etkisi. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 15 (1), 397-420.
  • 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. & Zmijewska, 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. & Zmijewska, A. (2007). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications, 1-17. https://doi.org/10.1016/j.elerap.2007.02.001
  • 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. https://doi.org/10.2307/249008
  • 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.
  • Dziuban, C. D., & Shirkey, E. C. (1974). When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin, 81 (6), 358-361. https://doi.org/10.1037/h0036316
  • Elkaseh, A. M., Wong, K. W. & 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. https://doi.org/10.7763/IJIET.2016.V6.683
  • Eriksson, K., Kerem, K. & Nilsson, D. (2005). Customer acceptance of internet banking in estonia. International Journal of Bank Marketing, 23 (2), 200- 216. https://doi.org/10.1108/02652320510584412
  • Eyüboğlu, K. ve Sevim U. (2016). Determinants of consumers’ adoption to shopping with QR code in Turkey. The Journal of International Social Research, 9 (43), 1830-1839.
  • Eyüboğlu, K. ve Sevim, U. (2017). Determinants of contactless credit cards acceptance in Turkey. Uluslararası Yönetim İktisat ve İşletme Dergisi, 13 (2), 311-330. http://dx.doi.org/10.17130/ijmeb.2017228687
  • Fornell C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1), 39-50. https://doi.org/10.2307/3151312
  • George, D. & 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. & Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, 44 (3), 276-286. https://doi.org/10.1016 / j.im.2007.01.001
  • Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2006). Multivariate data analysis (Seventh Edition). New Jersey: Pearson Prentice Hall.
  • Hu, P. J., Chau, P.Y.K., Shheng, O. R L. & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16 (2), 91-112. https://doi.org/10.1080/07421222.1999.11518247
  • Hu, Z., Ding, S., Li, S., Chen, L. & Yang, S. (2019). Adoption intention of FinTech services for bank users: An empirical examination with an extended Technology Acceptance Model. Symmetry, 11 (3), 1-16. https://doi.org/10.3390/sym11030340
  • Igbaria, M., Zinatelli, N., Cragg, P. & Cavaye, A. L. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 21 (3), 279-305. https://doi.org/10.2307/249498
  • İşbankası, (2012). İş Bankası’ndan Ödeme Sistemlerinde Devrim Yaratacak Uygulama: Parakod. https://www.isbank.com.tr/TR/hakkimizda/haberlerve-medya/haberler/, Erişim Tarihi: 28.08.2019.
  • James, T., Pirim, T., Boswell, K., Reithel, B. & 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, 18 (3), 1-24. https://doi.org/10.4018/joeuc.2006070101
  • Kalyoncuoğlu, S. (2018). Tüketicilerin online alışverişlerindeki sanal kart kullanımlarının teknoloji kabul modeli ile incelenmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 20 (2), 193-213.
  • Keil, M., Beranek, P. M. & Konsynski, B. R. (1995). Usefulness and ease of use: field study evidence regarding task considerations. Decision Support Systems, 13, 75-91. https://doi.org/10.1016/0167-9236(94)e0032-m
  • Kim, C., Mirusmonov, M. & Lee, I. (2009). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26 (3), 310-322. https://doi.org/10.1016/j.chb.2009.10.013
  • Kotler, P. (2000). Pazarlama yönetimi. Nejat Muallimoğlu (Çev.). 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: 28.08.2019.
  • Lee, M. K. O., Cheung, C. M. K. & Chen, Z. (2005). Acceptance of Internetbased learning medium: The role of extrinsic and intrinsic motivation. Information & Management, 42 (8), 1095-1104. https://doi.org/10.1016/j.im.2003.10.007
  • Li, J., Wang, J., Wangh, S. & Zhou, Y. (2019). Mobile payment with Alipay: An application of extended technology acceptance model. IEEE Acces, 7, 50380-50387. https://doi.org/10.1109/ACCESS.2019.2902905
  • Malaquias, R. F. & Hwang, Y. (2019). Mobile banking use: A comparative study with Brazilian and U. S. participants. International Journal of Information Management, 44, 132- 140. https://doi.org/10.1016/j.ijinfomgt.2018.10.004
  • Mallat, N. (2007). Exploring consumer adoption of mobile payments - a qualitative study. The Journal of Strategic Information Systems, 16 (4), 1- 14. https://doi.org/10.1016/j.jsis.2007.08.001
  • Marsh, H. W., Balla, J. R. & Mcdonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103 (3), 391-410. https://doi.org/10.1037/0033-2909.103.3.391
  • Menzi, N., Önal, N. ve Çalışkan, E. (2012). Mobil teknolojilerin eğitim amaçlı kullanımına yönelik akademisyen görüşlerinin teknoloji kabul modeli çerçevesinde incelenmesi. Ege Eğitim Dergisi, 3 (1), 40- 55.
  • Meydan, C. H. ve Şeşen. H. (2015). Yapısal eşitlik modellemesi Amos uygulamaları (2. Baskı). Ankara: Detay Yayıncılık.
  • Monsuwé, T. P., Dellaert, B. G. C. & Ruyter, K. (2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management, 15 (1), 102-121. https://doi.org/10.1108/09564230410523358
  • Moon, J. W. & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38 (4), 217-230. https://doi.org/10.1016/S0378-7206(00)00061-6
  • Ohk, K., Park, S. B. & 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. https://doi.org/10.14257 / astl.2015.84.18
  • Özer, A. C., Poyraz, E. ve Kızgın, Y. (2019). Nakitsiz toplum yaratmada elektronik ödeme araçlarının benimsenmesi. Business & Management Studies: An International Journal, 7 (2), 735-755. http://dx.doi.org/10.15295/bmij.v7i2.1032
  • Özer, G., Özcan, M. ve Aktaş, S. (2010). Muhasebecilerin bilgi teknolojisi kullanımının teknoloji kabul modeli (TKM) ile incelenmesi. Journal of Yasar University, 1, 3278-3293.
  • 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. & Nysveen, H. (2003). Usefulness and self-expressiveness: Extending TAM to explain the adoption of a mobile parking service. 16th Bled e-Commerce Conference, 705-717.
  • 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. https://doi.org/10.1108/10662240410542652
  • Raza, S. A., Umer, A. & 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. https://doi.org/10.1504/IJECRM.2017.086751
  • 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.
  • Schierz, P. G., Schilke, O. & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9 (3), 209-216. https://doi.org/10.1016/j.elerap.2009.07.005
  • Shih, H. P. (2004). An empirical study on predicting user acceptance of eshopping on the web. Information & Management, 41, 351-368. https://doi.org/10.1016/S0378-7206(03)00079-X
  • Sipior, J. C., Ward, B. T. & Connolly, R. (2011). The digital divide and tgovernment in the united states: Using the technology acceptance model to understand usage. European Journal of Information Systems, 20 (3), 308- 328. https://doi.org/10.1057/ejis.2010.64
  • Straub, D., Keil, M. & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management, 33 (1), 1-11. https://doi.org/10.1016/S0378-7206(97)00026-8
  • Suh, B. & Han, I. (2002). Effect of trust on customer acceptance of internet banking. Electronic Commerce Research and Applications, 1 (3-4), 247- 263. https://doi.org/10.1016/S1567-4223(02)00017-0
  • Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42 (1), 85-92. https://doi.org/10.1287/mnsc.42.1.85
  • Tassabehji, R. & 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. https://doi.org/10.1109/NTMS.2009.5384806
  • Taylor, S. & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19 (4), 561-570. https://doi.org/10.2307/249633
  • TDK, (2019). Büyük Türkçe Sözlük. http://www.tdk.gov.tr/, Erişim Tarihi: 29.08.2019.
  • Tüfekci, Ö. K. (2014). Karekodların pazarlama iletişimi rolünü teknoloji kabul modeli ile açıklamaya yönelik bir araştırma. Pamukkale İşletme ve Bilişim Yönetimi Dergisi, (1), 36-52. https://doi.org/10.5505/pibyd.2014.65375
  • Ustasüleyman, T. ve Eyüboğlu, K. (2010). Bireylerin internet bankacılığını benimsemesini etkileyen faktörlerin yapısal eşitlik modeli ile belirlenmesi. BDDK Bankacılık ve Finansal Piyasalar, 4 (2), 11-38.
  • Vallerand, R. J., Deshaies, P., Cuerrier, J., Pelletier, L. G. & 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. https://doi.org/10.1037/0022-3514.62.1.98
  • Wessels, L. & Drennan, J. (2010). An investigation of consumer acceptance of mbanking. International Journal of Bank Marketing, 28 (7), 547-568. https://doi.org/10,1108/02652321011085194
  • Yang, H. D. & Yoo, Y. (2004). It's all about attitude: revisiting the technology acceptance model. Decision Support Systems, 38 (1), 19-31. https://doi.org/10.1016/S0167-9236(03)00062-9
  • Yap, B. W. & 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. https://doi.org/10.1002/asmb.648
  • Zhang, T., Lu, C. & Kizildag, M. (2018). Banking “on- the- go”: Examining consumers’ adoption of mobile banking services. International Journal of Quality and Service Sciences, 10 (3), 279-295. https://doi.org/10,1108/IJQSS-07-2017-0067
  • Zmijewska, A., Lawrence, E. & Steele, R. (2004). Towards understanding of factors influencing user Acceptance of Mobile Payment Systems. IADIS International Conference WWW/Internet 2004, Madrid, Spain, (2), 270-277.
Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi-Cover
  • ISSN: 1308-5549
  • Başlangıç: 2011
  • Yayıncı: Çankırı Karatekin Üniversitesi