Müşterilerin Mobil Ödeme Hizmetleri Kullanım Davranışlarını ve Kullanıcı Tatminini Etkileyen Faktörlerin İncelenmesi

Yıl 2021, Cilt: 36 Sayı: 1, 171 - 190, 31.03.2021

Esma Durukal , Kevser Arman

https://doi.org/10.24988/ije.202136112

Cited By: 1

Öz

Geleneksel ödeme yöntemlerine alternatif bir ödeme aracı olan mobil ödeme hizmetleri kullanıcılara sağladığı sayısız avantaja rağmen halâ dünyada yaygın olarak kullanılmamaktadır. Son yıllarda mobil teknolojilere artan ilgi mobil ödeme hizmetleri kavramını gündeme getirmektedir. Bu çalışmanın amacı tüketicilerin mobil ödeme hizmetleri kullanımını öngörebilecek ana faktörlerin test edilmesinin yanı sıra böyle bir sistemi kullanmanın müşteri memnuniyetine sağlayabileceği katkıyı araştırmaktır. Çalışmada ele alınan IS Success modeli mobil ödeme hizmetlerinin başarısını ölçmeyi sağlarken, UTAUT ise mobil ödeme hizmetlerinin başarılı olmasına yol açan faktörleri ortaya koymaktadır. Araştırmada 246 kullanıcıya anket yapılmış, araştırma sonuçları yapısal eşitlik modeli LISREL programı ile analiz edilmiştir.

Anahtar Kelimeler

Mobil ödeme, UTAUT modeli, IS Success modeli, Müşteri tatmini

Examination of Factors Affecting the Customers' Mobile Payment Services Usage Behavior and User Satisfaction

Öz

Mobile payment services, which are an alternative payment method to traditional payment methods, are still not widely used in the world despite the numerous advantages that they provide to users. The increasing interest in mobile technologies in recent years brings the concept of mobile payment services to the agenda. The aim of this study is to test the main factors that can predict the use of mobile payment services by consumers, as well as to investigate the contribution that using such a system can provide to customer satisfaction. While the IS Success model discussed in the study allows to measure the success of mobile payment services, UTAUT reveals the factors leading to the success of mobile payment services. In the research, 246 users were surveyed and the results of the research were analyzed with the structural equation model LISREL program.

Anahtar Kelimeler

Mobile payment, UTAUT, IS success, cusstomer satisfaction

Kaynakça

• Abrahão, R., S., Moriguchi, S., N., Andrade, D., F. (2016). Intention of Adoption of Mobile Payment: An Analysis in the Light of the Unified Theory of Acceptance and Use of Technology (UTAUT). RAI Revista de Administração e Inovação, 13, 221–230.
• Adrian, B. (2002). Overview of The Mobile Payments Market 2002 through 2007. Gartner Research, R, 18–1818.
• Al-Saedi, K., Al-Emran, M., Abusham, E., ve El-Rahman, S. (2019). Mobile Payment Adoption: A Systematic Review of the UTAUT Model. 2019 International Conference on Fourth Industrial Revolution (ICFIR).
• Alshare, K. A., Mousa, A. A. (2011). The Moderating Effect of Espoused Cultural Dimensions on Consumer’s Intention to Use Mobile Payment Devices. Proc. 35th Int. Conf. Inf. Syst., no. Zhou 2011, 1–15.
• Aslam, W., Ham, M., Arif, I. (2017). Consumer Behavioral Intentions towards Mobile Payment Services: An Empirical Analysis in Pakistan. Market-Tržište, 29(2), 161-176.
• Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., Patil, P. (2019). Consumer Use of Mobile Banking (M-Banking) in Saudi Arabia: Towards an Integrated Model. International Journal of Information Management, 44, 38-52.
• Bandyopadhyay, K., Fraccastoro, K. (2007). The Effect of Culture on User Acceptance of Information Technology. Commun. Assoc. Inf. Syst., 19, 522–543.
• Bentler, P. M. (1990). Comparative Fit Indexes in Structural Models. Psychological Bulletin, 107(2), 238.
• Bentler, P., M., Yuan, K., H. (1999). Structural Equation Modeling with Small Samples: Test Statistics. Multivariate Behavioral Research, 34(2), 181-197.
• Büyüköztürk, Ş. (2002). Faktör Analizi: Temel Kavramlar ve Ölçek Geliştirmede Kullanım. Kuram ve Uygulamada Eğitim Yönetimi Dergisi, 32, 470-483.
• Byrne, B. (2009). Multivariate Applications Series. Structural Equation Modeling With AMOS: Basic Concepts, Applications, And Programming (2nd ed.). New York, NY, US: Routledge/Taylor & Francis Group.
• Chandra, S., Srivastava, S., Theng, Y.-L. (2010). Evaluating The Role of Trust in Consumer Adoption of Mobile Payment Systems: An Empirical Analysis. Communications of the Association for Information Systems, 27, 561–588.
• Comrey, A., Lee, H. (1992). A First Course in Factor Analysis, Hillsdale, NJ: Erlbaum.
• Çokluk, Ö., Şekercioğlu, Ö. Büyüköztürk, Ş. (2010). Sosyal Bilimler İçin Çok Değişkenli İstatistik. Ankara: PEGEM Akademi.
• Dahlberg, T. Mallat, N. Ondrus, J., Zmijewska, A. (2008). Past, Present And Future Of Mobile Payments Research: A Literature Review. Electronic Commerce Research and Applications 7 (2), 165–181.
• Delone, W. H., Mclean, E. R. (1992). Information Systems Success: The Quest For The Dependent Variable. Information Systems Research, 3 (1), 60–95.
• Delone, W. H., Mclean, E. R. (2003). The DeLone and Mclean Model Of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9–30.
• Dwivedi, Y. K., Kapoor, K. K., Williams, M. D., Ve Williams, J. (2013). Rfıd Systems in Libraries: an Empirical Examination of Factors Affecting System Use And User Satisfaction. International Journal of Information Management, 33(2), 367-377.
• E-ticaret Raporu, (2019). http://www.tubisad.org.tr/tr/images/pdf/dd-tusiad-eticaret-raporu-2019.pdf, (28.1.2020).
• Evers, A., Frese, M., Cooper, C. L. (2000). Revisions And Further Developments Of The Occupational Stress Indicator: Lısrel Results From Four Dutch Studies. Journal of Occupational and Organizational Psychology, 73(2), 221-240
• Hoe, S.L. (2008). Issues And Procedures in Adopting Structural Equation Modeling Technique. Journal of Applied Quantitative Methods, 3(1), 76-83.
• Hongxia, P., Xianhao, X., Weidan, L. (2011). Drivers and Barriers in the Acceptance of Mobile Payment in China. International Conference on E-Business, sayfa aralığı yok.
• Hooper, D., Coughlan, J., Mullen, M. R. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. The Electronic Journal of Business Research Methods, 6 (1), 53 – 60.
• Joreskog, K. G. Sorbom, D. (1986). LISREL6 – Computer Program. Moorseville, IN, Scientific Software.
• Kalaycı, Ş. (2006). Spss Uygulamalı Çok Değişkenli İstatistik Teknikleri. Ankara, Turkey: Asil Yayın Dağıtım.
• Kalinic, Z., Marinkovic, V., Molinillo, S., Liébana-Cabanillas, F. (2019). A Multi-Analytical Approach To Peer-To-Peer Mobile Payment Acceptance Prediction. Journal Of Retailing And Consumer Services 49, 143–153.
• Karnouskos, S., Fokus, F. (2004). Mobile Payment: A Journey Through Existing Procedures And Standardization Initiatives. Ieee Communications Surveys And Tutorials, 6(4), 44–66.
• Khalilzadeh, J., Ozturk, A., B., Bilgihan, A. (2017). Security-Related Factors in Extended Utaut Model For NFC Based Mobile Payment in the Restaurant Industry. Computers in Human Behavior, 70, 460–474.
• Kim, H. W., Xu, Y., Koh, J. (2004). A Comparison Of Online Trust Building Factors Between Potential Customers And Repeat Customers. Journal Of The Association For Information Systems, 5(10), 13.
• Kline, P. (1994). An Easy Guide To Factor Analysis:. New York: Routledge.
• Koenig-Lewis, N., Marquet, M., Palmer, A., Zhao, A., L. (2015). Enjoyment And Social İnfluence: Predicting Mobile Payment Adoption. The Service Industries Journal, 35 (10), 537–554.
• Kohli, R., Devaraj, S., Mahmood, M. A. (2004). Understanding Determinants Of Online Consumer Satisfaction: A Decision Process Perspective. Journal Of Management Information Systems, 21(1), 115–136.
• Lee, J. W., Kwag, M. (2019). Structural Equation Modelling With Second-Order Confirmatory Factor Analysis: Critical Factors Influencing Consumer Behavior in Medical Tourism. In Quantitative Tourism Research İn Asia, (223-243). Springer, Singapore.
• Luna, I. R. D., Liébana-Cabanillas, F., Sánchez-Fernández, J., Muñoz-Leiva, F. (2018). Mobile Payment is not all the Same: The Adoption of Mobile Payment Systems Depending on The Technology Applied. Technological Forecasting and Social Change.
• Mobil Ödeme Hizmetleri, (2015). https://www.btk.gov.tr/uploads/pages/slug/mobil-odeme-hizmetleri.pdf, (30.1.2020).
• Molina-Castillo, F., Lopez-Nicolas, C., Reuver, M. (2020). Mobile Payment: The Hiding Impact of Learning Costs on User Intentions. Journal of Theoretical and Applied Electronic Commerce Research, 15 (1), 1–12.
• Mun, Y. P., Khalid, H., Nadarajah, D. (2017). Millennials’ Perception on Mobile Payment Services in Malaysia. Procedia Computer Science, 124, 397–404.
• Örs, M. E. (2018). Development of a Tehcnology Acceptance Odel For Mobile Payment Systems. The Middle East Technical University, Master Thesis.
• Özdemir, A. (2013). Yönetim Biliminde İleri Araştırma Yöntemleri ve Uygulamalar. (3. Baskı Ed.): Beta Yayınevi.
• Rennie, K.M. (1997). Exploratory And Confirmatory Rotation Strategies in Exploratory Factor Analysis. Paper Presented at the Annual Meeting of The Southwest Educational Research Association (Austin, January).
• Roscoe, J. T. (1975). Fundamental Research Statistics for Behavioral Sciences. Holt, Rinehart and Winston, New York.
• Rosnidah, I., Muna, A., Musyaffi, A., M., Siregar, N., F. (2019). Critical Factor of Mobile Payment Acceptance in Millenial Generation: Study on the UTAUT Model. Advances in Social Science, Education And Humanities Research, 306, 123–127.
• 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.
• Schumacker, R. E., Lomax, R.G. (2004). A Beginner’s Guide To Structural Equation Modeling (2nd Ed.). Mahlah, New Jersey, London: Lawrence Erlbaum Associates.
• Schumacker, R.E., Lomax, R.G. (2010). A Beginner’s Guide To Structural Equation Modeling. 3rd Ed., Routledge, New York, Ny.
• Shamdasani, P., Mukherjee, A., Malhotra, N. (2008). Antecedents And Consequences Of Service Quality in Consumer Evaluation Of Self-Service Internet Technologies. Service Industries Journal, 28(1), 117–138.
• Shankar, A., Datta, B. (2018). Factors Affecting Mobile Payment Adoption Intention: An Indian Perspective. Global Business Review, 19(3_Suppl), 72–89.
• Shareef, M. A., Dwivedi, Y. K., Stamati, T., Williams, M. D. (2014). Sq Mgov: A Comprehensive Service-Quality Paradigm For Mobile Government. Information Systems Management, 31(2), 126–142.
• Sharma, S.C. (1996). Applied Multivariate Techniques. John Wiley And Sons. New York.
• Slade, E., Williams, M., Dwivedi, Y., Piercy, N. (2015). Exploring Consumer Adoption of Proximity Mobile Payments. Journal of Strategic Marketing, 23(3), 209–223.
• Soni, M., Jain, K., Kumar, B. (2019). Factors Affecting The Adoption Of Fashion Mobile Shopping Applications. Journal of Global Fashion Marketing, 10(4), 358–376.
• Stapleton, C.D. (1997). Basic Concepts And Procedures of Confirmatory Factor Analysis. Paper Presented at The Annual Meeting of The Southwest Educational Research Association (Austin, January).
• Suhr, D. (2006). Exploratory or Confirmatory Factor Analysis. Sas Users Group International Conference (1 - 17), Cary: Sas Institute, Inc.
• Thakur, R., Srivastava, M. (2014). Adoption Readiness, Personal Innovativeness, Perceived Risk and Usage Intention Across Customer Groups For Mobile Payment Services in India. Internet Research, 24 (3), 369–392.
• Türker, C. (2019). Tüketicilerin Yeni Teknolojiler Benimsemelerinin Teknoloji̇ Kabul Modeli Boyutları İtibariyle İncelenmesi̇: Mobil Ödeme Sistemleri̇ Üzerine Bir Araştırma. Yüksek Lisans Tezi, İstanbul Üniversitesi, İşletme Anabilim Dalı, İstanbul.
• Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D. (2003). User Acceptance of İnformation Technology: Toward a Unified View. Mis Quarterly, 27(3). 425–478.
• Venkatesh, V., Thong, J., Xu, X. (2012). Consumer Acceptance And Use Of İnformation Technology: Extending The Unified Theory of Acceptance And Use of Technology. Mis Quarterly, 36(1), 157–178.
• Verkijika, S., F. (2020). An Affective Response Model For Understanding the Acceptance of Mobile Payment Systems. Electronic Commerce Research And Applications, 39, 1–14.
• Verma, S., Chaurasia, S., S., Singh, V. (2020). Understandıng the Corpus of Mobıle Payment Servıces Research: An Analysis of The Literature Usıng Co-Cıtatıon Analysis And Social Network Analysis. Journal of Information Systems and Technology Management –Jistem Usp V, 17,1–36.
• Weston, R. Gore, P., A. (2006). A Brief Guide To Structural Equation Modeling. the Counselıng Psychologıst, 34 (5), 719-751.
• Yang, Q., Gong, X., Zhang, K.,Z., Liu, H., Lee, M.,K.,O. (2020). Self-Disclosure in Mobile Payment Applications: Common And Differential Effects of Personal and Proxy Control Enhancing Mechanisms. International Journal of Information Management, 1–20.
• Yang, S., Lu, Y., Gupta, S., Cao, Y., Zhang, R. (2012). Mobile Payment Services Adoption Across Time: An Empirical Study of The Effects Of Behavioral Beliefs, Social Influences, And Personal Traits. Computers in Human Behavior, 28(1), 129–142.
• Yang, Y., Liu, Y., Li, H., Yu, B. (2014). Understanding Perceived Risks in Mobile Payment Acceptance. Industrial Management & Data Systems, 115 (2), 253–269.
• Yaşlıoğlu, M. M. (2017). Sosyal Bilimlerde Faktör Analizi ve Geçerlilik: Keşfedici ve Doğrulayıcı Faktör Analizlerinin Kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74–85.
• Yazıcıoğlu, Y., Erdoğan, S. (2004). Spss Uygulamalı Bilimsel Araştırma Yöntemleri. Detay Yayıncılık, Ankara.
• Zhou, T. (2013). An Empirical Examination of Continuance Intention of Mobile Payment Services. Decision Support Systems, 54(2), 1085–1091.