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Mobil Bankacılıkta Müşterinin Devamlılık Niyetinin Belirleyicilerinin İncelenmesi: ECM ve D&M Modelinin Bütünleştirilmesi

Year 2023, , 137 - 152, 19.10.2023
https://doi.org/10.56337/sbm.1350089

Abstract

Çalışmanın amacı, müşterinin mobil bankacılık uygulamalarını kullanmaya devam etme niyeti davranışının belirleyicilerini araştırmaktır. Çalışma, güven ve öz yeterliliği dahil ederek beklenti-onay modeli (ECM) ve DeLone & McLean bilgi sistemi başarı modelinin (D&M Modeli) birleşimine dayalı genişletilmiş bir çerçeve geliştirmiş ve doğrulamıştır. Bu araştırmaya toplamda 448 mobil bankacılık kullanıcısı katılmıştır. Anketten toplanan verilere dayanarak, önerilen araştırma modelini oluşturan değişkenler arası ilişkileri incelemek için yapısal eşitlik modellemesi (YEM) kullanılmıştır. Sonuçlar, algılanan kullanışlılık, doğrulama, sistem kalitesi ve bilgi kalitesinin memnuniyetin ana belirleyicisi olduğunu göstermektedir. Ayrıca, memnuniyet, güven ve öz yeterliliğin devam niyeti üzerinde pozitif yönde bir etkiye sahip olduğu bulgusuna ulaşılmıştır.

References

  • Abu-Shanab, E., & Ghaleb, O. (2012). Adoption of mobile commerce technology: An involvement of trust and risk concerns. International Journal of Technology Diffusion (IJTD), 3(2), 36-49.
  • Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110.
  • Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., Lal, B., & Williams, M. D. (2015). Consumer adoption of Internet banking in Jordan: Examining the role of hedonic motivation, habit, self-efficacy and trust. Journal of Financial Services Marketing, 20(2), 145-157.
  • Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29(1), 118-139.
  • Albashrawi, M., & Motiwalla, L. (2019). Privacy and personalization in continued usage intention of mobile banking: An integrative perspective. Information Systems Frontiers, 21(5), 1031-1043.
  • Almasri, A. K. M. (2016). Proposed M-Learning Model Based on Two Models (Technology Acceptance Model and DeLone and McLean IS success Model). International Journal of Computer Applications, 142(4), 5-10.
  • Altuntaş, B. (2017). Y kuşağının mobil öğrenme uygulama tercihini etkileyen faktörlerin incelenmesi. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 6(6), 89-104.
  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
  • Asnakew, Z. S. (2020). Customers’ continuance intention to use mobile banking: development and testing of an integrated model. The Review of Socionetwork Strategies, 14(1), 123-146.
  • 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.
  • Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191.
  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, 351-370.
  • Chen, C. W. D., & Cheng, C. Y. J. (2009). Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model. Behaviour & Information Technology, 28(4), 335-345.
  • Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information systems research, 6(2), 118-143.
  • Chong, A. Y. L. (2013). Understanding mobile commerce continuance intentions: an empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22-30.
  • Chung, N., & Kwon, S. J. (2009). Effect of trust level on mobile banking satisfaction: a multi-group analysis of information system success instruments. Behaviour & Information Technology, 28(6), 549-562.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
  • 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.
  • Erdoğan, G. (2023). Bireylerin Mobil Bankacılığı Benimsemesini Etkileyen Faktörler: Genişletilmiş Birleşik Teknoloji Kabulü ve Kullanımı Teorisi (UTAUT) Modeli Çerçevesinde Bir Araştırma. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 121-142.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18, 39-50.
  • Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015-1033.
  • Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study–A case of China. Computers in Human Behavior, 53, 249-262.
  • Giovanis, A., Assimakopoulos, C., & Sarmaniotis, C. (2018). Adoption of mobile self-service retail banking technologies: The role of technology, social, channel and personal factors. International Journal of Retail & Distribution Management, 47(9), 894-914.
  • GSMA, (2021). The State of Mobile Internet Connectivity 2021. https://www.gsma.com/r/wp-content/uploads/2021/09/The-State-of-Mobile-Internet-Connectivity-Report-2021.pdf, (Access: 13.06.2022) Hair, J.F. Jr, Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis: A Global Perspective, 7th ed., Pearson Education International, NJ.
  • Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., & Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian bank clients. Telematics and informatics, 31(1), 62-78.
  • Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps?–An expectation confirmation model with perceived value. Electronic commerce research and applications, 14(1), 46-57.
  • Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students' self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260-272.
  • Jupiter Research, (2019). Mobile Banking Users to Exceed 1.75 billion by 2019. https://www.juniperresearch.com/press/mobile-banking-users-exceed-1-75-billion-by-2019, (Access: 15.06.2022)
  • Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283-311.
  • 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.
  • Kumar, R. R., Israel, D., & Malik, G. (2018). Explaining customer’s continuance intention to use mobile banking apps with an integrative perspective of ECT and Self-determination theory. Pacific Asia Journal of the Association for Information Systems, 10(2), 5.
  • Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with computers, 21(5-6), 385-392.
  • Mansour, M. M. O. (2020). Acceptance of mobile banking in Islamic banks: integration of DeLone and McLean IS model and unified theory of acceptance and use of technology. International Journal of Business Excellence, 21(4), 564-584.
  • Mason, R. O. (1978). Measuring information output: A communication systems approach, Information & management, 1(4), 219-234.
  • Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of management review, 20(3), 709-734.
  • McIlroy, A., & Barnett, S. (2000). Building customer relationships: do discount cards work. Managing Service Quality: An International Journal, 10(6), 347-355.
  • Motiwalla, L. F., Albashrawi, M., & Kartal, H. B. (2019). Uncovering unobserved heterogeneity bias: Measuring mobile banking system success. International Journal of Information Management, 49, 439-451.
  • Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information technology continuance intention: A systematic literature review. International Journal of E-Business Research (IJEBR), 12(1), 58-95.
  • Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research, 17(4), 460-469.
  • Rabaa’i, A. A., & AlMaati, S. (2021). Exploring the determinants of users’ continuance intention to use mobile banking services in Kuwait: Extending the expectation-confirmation model. Asia Pacific Journal of Information Systems, 31(2), 141-184.
  • Rahi, S., & Ghani, M. A. (2019). Integration of expectation confirmation theory and self-determination theory in internet banking continuance intention. Journal of Science and Technology Policy Management, 10(3), 533-550.
  • Rahi, S., Mansour, M. M. O., Alharafsheh, M., & Alghizzawi, M. (2021). The post-adoption behavior of internet banking users through the eyes of self-determination theory and expectation confirmation model. Journal of Enterprise Information Management, 34(6), 1874-1892.
  • 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.
  • Shannon, C.E., & Weaver, W. (1949). The mathematical theory of communication. University of Illinois Press, Urbana, IL, 1949.
  • Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65-75.
  • Shaw, N. (2014). The mediating influence of trust in the adoption of the mobile wallet. Journal of Retailing and Consumer Services, 21(4), 449-459.
  • Statista, (2021). Forecast number of mobile devices worldwide from 2020 to 2025 (in billions). https://www.statista.com/statistics/245501/multiple-mobile-device-ownership-worldwide/, (Access: 12.06.2022)
  • Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management & Data Systems, 116(3), 508-525.
  • Tam, C., & Oliveira, T. (2016). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233-244.
  • Tam, C., & Oliveira, T. (2017). Understanding mobile banking individual performance: The DeLone & McLean model and the moderating effects of individual culture. Internet Research, 27(3), 538-562.
  • Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243-257.
  • TBB, (2021). Digital, Internet and Mobile Banking Statistics. https://www.tbb.org.tr/Content/Upload/istatistikiraporlar/ekler/1604/Dijital-Internet-Mobil_Bankacilik_Istatistikleri-Mart_2021.pdf, (Access: 16.06.2022)
  • Thakur, R. (2018). The role of self-efficacy and customer satisfaction in driving loyalty to the mobile shopping application. International Journal of Retail & Distribution Management, 46(3), 283-303.
  • Wang, S. W., Ngamsiriudom, W., & Hsieh, C. H. (2015). Trust disposition, trust antecedents, trust, and behavioral intention. The Service Industries Journal, 35(10), 555-572.
  • Vatanasombut, B., Igbaria, M., Stylianou, A. C., & Rodgers, W. (2008). Information systems continuance intention of web-based applications customers: The case of online banking. Information & management, 45(7), 419-428.
  • Yan, A. W., Md-Nor, K., Abu-Shanab, E., & Sutanonpaiboon, J. (2009). Factors that affect mobile telephone users to use mobile payment solution. International Journal of Economics and Management, 3(1), 37-49.
  • Yang, K. (2010). The effects of technology self-efficacy and innovativeness on consumer mobile data service adoption between American and Korean consumers. Journal of International Consumer Marketing, 22(2), 117-127.
  • Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20-34.
  • Zahedi, F. M., & Song, J. (2008). Dynamics of trust revision: Using health infomediaries. Journal of Management Information Systems, 24(4), 225-248.
  • Zhou, T. (2012). Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective. Computers in human behavior, 28(4), 1518-1525.
  • Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision support systems, 54(2), 1085-1091.

Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model

Year 2023, , 137 - 152, 19.10.2023
https://doi.org/10.56337/sbm.1350089

Abstract

The purpose of the study is to investigate the determinants of the customer’s continuance intention (CIN) behavior to use mobile banking applications. The study established and validated an extended framework based upon the combination of expectation-confirmation model (ECM) and DeLone & McLean information system success model (D&M Model) by including trust and self-efficacy. A total number of 448 users of mobile banking participated in this research. Based upon the applicable data gathered from a survey, structural equation modeling (SEM) was used to test the proposed research. The results indicate that perceived usefulness, confirmation, system quality, and information quality are the main predictors of satisfaction (SAT). Furthermore, the results revealed that SAT, trust, and self-efficacy have significant impact on CIN.

References

  • Abu-Shanab, E., & Ghaleb, O. (2012). Adoption of mobile commerce technology: An involvement of trust and risk concerns. International Journal of Technology Diffusion (IJTD), 3(2), 36-49.
  • Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110.
  • Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., Lal, B., & Williams, M. D. (2015). Consumer adoption of Internet banking in Jordan: Examining the role of hedonic motivation, habit, self-efficacy and trust. Journal of Financial Services Marketing, 20(2), 145-157.
  • Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29(1), 118-139.
  • Albashrawi, M., & Motiwalla, L. (2019). Privacy and personalization in continued usage intention of mobile banking: An integrative perspective. Information Systems Frontiers, 21(5), 1031-1043.
  • Almasri, A. K. M. (2016). Proposed M-Learning Model Based on Two Models (Technology Acceptance Model and DeLone and McLean IS success Model). International Journal of Computer Applications, 142(4), 5-10.
  • Altuntaş, B. (2017). Y kuşağının mobil öğrenme uygulama tercihini etkileyen faktörlerin incelenmesi. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 6(6), 89-104.
  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
  • Asnakew, Z. S. (2020). Customers’ continuance intention to use mobile banking: development and testing of an integrated model. The Review of Socionetwork Strategies, 14(1), 123-146.
  • 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.
  • Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191.
  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, 351-370.
  • Chen, C. W. D., & Cheng, C. Y. J. (2009). Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model. Behaviour & Information Technology, 28(4), 335-345.
  • Compeau, D. R., & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information systems research, 6(2), 118-143.
  • Chong, A. Y. L. (2013). Understanding mobile commerce continuance intentions: an empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22-30.
  • Chung, N., & Kwon, S. J. (2009). Effect of trust level on mobile banking satisfaction: a multi-group analysis of information system success instruments. Behaviour & Information Technology, 28(6), 549-562.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
  • 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.
  • Erdoğan, G. (2023). Bireylerin Mobil Bankacılığı Benimsemesini Etkileyen Faktörler: Genişletilmiş Birleşik Teknoloji Kabulü ve Kullanımı Teorisi (UTAUT) Modeli Çerçevesinde Bir Araştırma. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 121-142.
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18, 39-50.
  • Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015-1033.
  • Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study–A case of China. Computers in Human Behavior, 53, 249-262.
  • Giovanis, A., Assimakopoulos, C., & Sarmaniotis, C. (2018). Adoption of mobile self-service retail banking technologies: The role of technology, social, channel and personal factors. International Journal of Retail & Distribution Management, 47(9), 894-914.
  • GSMA, (2021). The State of Mobile Internet Connectivity 2021. https://www.gsma.com/r/wp-content/uploads/2021/09/The-State-of-Mobile-Internet-Connectivity-Report-2021.pdf, (Access: 13.06.2022) Hair, J.F. Jr, Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis: A Global Perspective, 7th ed., Pearson Education International, NJ.
  • Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., & Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian bank clients. Telematics and informatics, 31(1), 62-78.
  • Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps?–An expectation confirmation model with perceived value. Electronic commerce research and applications, 14(1), 46-57.
  • Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students' self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260-272.
  • Jupiter Research, (2019). Mobile Banking Users to Exceed 1.75 billion by 2019. https://www.juniperresearch.com/press/mobile-banking-users-exceed-1-75-billion-by-2019, (Access: 15.06.2022)
  • Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283-311.
  • 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.
  • Kumar, R. R., Israel, D., & Malik, G. (2018). Explaining customer’s continuance intention to use mobile banking apps with an integrative perspective of ECT and Self-determination theory. Pacific Asia Journal of the Association for Information Systems, 10(2), 5.
  • Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with computers, 21(5-6), 385-392.
  • Mansour, M. M. O. (2020). Acceptance of mobile banking in Islamic banks: integration of DeLone and McLean IS model and unified theory of acceptance and use of technology. International Journal of Business Excellence, 21(4), 564-584.
  • Mason, R. O. (1978). Measuring information output: A communication systems approach, Information & management, 1(4), 219-234.
  • Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of management review, 20(3), 709-734.
  • McIlroy, A., & Barnett, S. (2000). Building customer relationships: do discount cards work. Managing Service Quality: An International Journal, 10(6), 347-355.
  • Motiwalla, L. F., Albashrawi, M., & Kartal, H. B. (2019). Uncovering unobserved heterogeneity bias: Measuring mobile banking system success. International Journal of Information Management, 49, 439-451.
  • Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information technology continuance intention: A systematic literature review. International Journal of E-Business Research (IJEBR), 12(1), 58-95.
  • Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research, 17(4), 460-469.
  • Rabaa’i, A. A., & AlMaati, S. (2021). Exploring the determinants of users’ continuance intention to use mobile banking services in Kuwait: Extending the expectation-confirmation model. Asia Pacific Journal of Information Systems, 31(2), 141-184.
  • Rahi, S., & Ghani, M. A. (2019). Integration of expectation confirmation theory and self-determination theory in internet banking continuance intention. Journal of Science and Technology Policy Management, 10(3), 533-550.
  • Rahi, S., Mansour, M. M. O., Alharafsheh, M., & Alghizzawi, M. (2021). The post-adoption behavior of internet banking users through the eyes of self-determination theory and expectation confirmation model. Journal of Enterprise Information Management, 34(6), 1874-1892.
  • 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.
  • Shannon, C.E., & Weaver, W. (1949). The mathematical theory of communication. University of Illinois Press, Urbana, IL, 1949.
  • Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65-75.
  • Shaw, N. (2014). The mediating influence of trust in the adoption of the mobile wallet. Journal of Retailing and Consumer Services, 21(4), 449-459.
  • Statista, (2021). Forecast number of mobile devices worldwide from 2020 to 2025 (in billions). https://www.statista.com/statistics/245501/multiple-mobile-device-ownership-worldwide/, (Access: 12.06.2022)
  • Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management & Data Systems, 116(3), 508-525.
  • Tam, C., & Oliveira, T. (2016). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233-244.
  • Tam, C., & Oliveira, T. (2017). Understanding mobile banking individual performance: The DeLone & McLean model and the moderating effects of individual culture. Internet Research, 27(3), 538-562.
  • Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243-257.
  • TBB, (2021). Digital, Internet and Mobile Banking Statistics. https://www.tbb.org.tr/Content/Upload/istatistikiraporlar/ekler/1604/Dijital-Internet-Mobil_Bankacilik_Istatistikleri-Mart_2021.pdf, (Access: 16.06.2022)
  • Thakur, R. (2018). The role of self-efficacy and customer satisfaction in driving loyalty to the mobile shopping application. International Journal of Retail & Distribution Management, 46(3), 283-303.
  • Wang, S. W., Ngamsiriudom, W., & Hsieh, C. H. (2015). Trust disposition, trust antecedents, trust, and behavioral intention. The Service Industries Journal, 35(10), 555-572.
  • Vatanasombut, B., Igbaria, M., Stylianou, A. C., & Rodgers, W. (2008). Information systems continuance intention of web-based applications customers: The case of online banking. Information & management, 45(7), 419-428.
  • Yan, A. W., Md-Nor, K., Abu-Shanab, E., & Sutanonpaiboon, J. (2009). Factors that affect mobile telephone users to use mobile payment solution. International Journal of Economics and Management, 3(1), 37-49.
  • Yang, K. (2010). The effects of technology self-efficacy and innovativeness on consumer mobile data service adoption between American and Korean consumers. Journal of International Consumer Marketing, 22(2), 117-127.
  • Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20-34.
  • Zahedi, F. M., & Song, J. (2008). Dynamics of trust revision: Using health infomediaries. Journal of Management Information Systems, 24(4), 225-248.
  • Zhou, T. (2012). Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective. Computers in human behavior, 28(4), 1518-1525.
  • Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision support systems, 54(2), 1085-1091.
There are 62 citations in total.

Details

Primary Language English
Subjects Digital Marketing
Journal Section 2023:2 Papers
Authors

Görkem Erdoğan 0000-0002-2417-2718

Publication Date October 19, 2023
Published in Issue Year 2023

Cite

APA Erdoğan, G. (2023). Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model. Sosyal Bilimler Metinleri, 2023(2), 137-152. https://doi.org/10.56337/sbm.1350089
AMA Erdoğan G. Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model. Sosyal Bilimler Metinleri. October 2023;2023(2):137-152. doi:10.56337/sbm.1350089
Chicago Erdoğan, Görkem. “Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model”. Sosyal Bilimler Metinleri 2023, no. 2 (October 2023): 137-52. https://doi.org/10.56337/sbm.1350089.
EndNote Erdoğan G (October 1, 2023) Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model. Sosyal Bilimler Metinleri 2023 2 137–152.
IEEE G. Erdoğan, “Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model”, Sosyal Bilimler Metinleri, vol. 2023, no. 2, pp. 137–152, 2023, doi: 10.56337/sbm.1350089.
ISNAD Erdoğan, Görkem. “Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model”. Sosyal Bilimler Metinleri 2023/2 (October 2023), 137-152. https://doi.org/10.56337/sbm.1350089.
JAMA Erdoğan G. Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model. Sosyal Bilimler Metinleri. 2023;2023:137–152.
MLA Erdoğan, Görkem. “Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model”. Sosyal Bilimler Metinleri, vol. 2023, no. 2, 2023, pp. 137-52, doi:10.56337/sbm.1350089.
Vancouver Erdoğan G. Examining the Determinants of the Customer’s Continuance Intention in Mobile Banking: Integrating ECM and D&M Model. Sosyal Bilimler Metinleri. 2023;2023(2):137-52.