Antecedents of attitudes towards and usage behavior of mobile banking amongst Generation Y students
-
DOIhttp://dx.doi.org/10.21511/bbs.12(2).2017.08
-
Article InfoVolume 12 2017, Issue #2, pp. 78-90
- Cited by
- 2146 Views
-
970 Downloads
This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
Despite the benefits that mobile banking has to offer, coupled with positive mobile penetration rates, the use of mobile devices to perform banking transactions and access financial information is not as widespread as expected. The significantly sized Generation Y cohort is a rewarding market segment for retail banks. In South Africa, however, this cohort’s mobile banking adoption is largely under-researched. Understanding the antecedents that positively influence Generation Y students’ attitudes towards and usage behavior of mobile banking will assist retail banks in their efforts to tailor their business and marketing strategies effectively towards this cohort, and in doing so, foster increased acceptance of their mobile channels. As such, the purpose of this study was to extend the technology acceptance model (TAM) and determine the influence of perceived ease of use, relative advantage, subjective norms, perceived behavioral control, perceived integrity and the perceived system quality of mobile banking on South African Generation Y students’ attitudes towards and usage behavior of mobile banking. Following a descriptive research design, self-administered questionnaires were completed by a non-probability convenience sample of 334 students registered at the campuses of three registered public South African universities located in the Gauteng province. Data analysis included correlation analysis and structural equation modeling. The findings suggest that while perceived ease of use, perceived integrity and the perceived system quality predict Generation Y students’ mobile banking usage behavior, subjective norms, perceived behavioral control and the perceived relative advantage of mobile banking predict attitudes towards mobile banking, which, in turn, predict their mobile banking usage behavior.
- Keywords
-
JEL Classification (Paper profile tab)G20, M31, O30
-
References78
-
Tables5
-
Figures1
-
- Fig. 1. Structural model B
-
- Table 1. Sample description
- Table 2. Descriptive statistics and reliability measures
- Table 3. Correlation coefficients
- Table 4. Measurement model estimates, construct reliability and validity, and correlation coefficients
- Table 5. Standardized regression coefficients for the structural paths
-
- Aboelmaged, M. G., and Gebba, T. R. (2013). Mobile banking adoption: an examination of technology acceptance model and theory of planned behavior. International Journal of Business Research and Development, 2(1), 35-50.
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
- Ajzen, I., and Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Pearson Prentice Hall.
- Akturan, U., and Tezcan, N. (2012). Mobile banking adoption of the youth market: perceptions and intentions. Marketing Intelligence & Planning, 30(4), 444-459.
- Alsajjan, B., and Dennis, C. (2009). Internet banking acceptance model: cross-market examination. Journal of Business Research, 63(9-10), 957-963.
- Arnaboldi, F., and Claeys, P. (2008). Internet banking in Europe: a comparative analysis.
- Bevan-Dye, L., and Akpojivi, U. (2015). South African Generation Y students’ self-disclosure on Facebook. South African Journal of Psychology, 43(1), 114-129.
- BuddComm. (2017). South Africa - Mobile Infrastructure, Operators and Broadband - Statistics and Analyses.
- Byrne, B. M. (2010). Structural equation modelling with AMOS: basic concepts, applications and programming. New York: Routledge.
- Cox, D., Kilgore, T. L., Purdy, T., and Sampath, R. (2008). Catalysts for change: the implications of Gen Y consumers for banks.
- Crabbe, M., Standing, C., Standing, S., and Karjaluoto, H. (2009). An adoption model for mobile banking in Ghana. International Journal of Mobile Communications, 7(5), 515-543.
- Daneshgadeh, S., and Yildirim, S. Ӧ. (2014). Empirical investigation of internet banking usage: the case of Turkey. Procedia Technology, 16, 322-331.
- Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. Massachusetts: MIS. (Thesis – PhD).
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
- Delafrooz, N., Taleghani, M., Karami, R., and Moradi, A. (2013). Factors affecting the adoption of Internet banking. International Journal of Business and Behavioral Sciences, 3(2), 82-100.
- DeLone, W. H., and McLean, E. R. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1), 60-95.
- DeLone, W. H., and 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.
- Eastman, J. K., and Liu, J. (2012). The impact of generational cohorts on status consumption: an exploratory look at generational cohort and demographics on status consumption. Journal of Consumer Marketing, 29(2), 93-102.
- Erasmus, E., Rothmann, S., and Van Eeden, C. (2015). A structural model of technology acceptance. SA Journal of Industrial Psychology, 41(1), 1-12.
- Ernst & Young. (2009). Mobile money: an overview for global telecommunications operators.
- Ernst & Young. (2017). Global banking outlook 2017: uncertainty is no excuse for inaction.
- FinScope South Africa. (2015). FinScope South Africa 2015.
- Fishbein, M., and Ajzen, I. (1975). Belief, attitudes, intention and behavior: an introduction to theory and research. Phillippines: Addison-Wesley.
- Galadima, T. O., Akinyemi, I. O., and Asani, E. O. (2014). The impact of knowledge-based trust (Kbt) on the adoption and acceptability of cashless economy in Nigeria. International Journal of Computer Science & Information Technology, 6(2), 171-180.
- Gao, T., Rohm, A. J., Sultan, F., and Huang, S. (2012). Antecedents of consumer attitudestoward mobile marketing: a comparative study of youth markets in the United Statesand China. Thunderbird International Business Review, 54, 211-224.
- Greaves, M., Zibarras, L. D., and Stride, C. (2013). Using the theory of planned behavior to explore environmental behavioral intentions in the workplace. Journal of Environmental Psychology, 34(1), 109-120.
- GSMA. (2017). The mobile economy 2017.
- Gu, J. C., Lee, S. C., and Suh, Y. H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.
- Gumussoy, C. A., Calisir F., and Bayram, A. (2007). Understanding the behavioral intention to use ERP systems: an extended technology acceptance model. Proceedings of the International Conference on Industrial Engineering and Engineering Management (IEEE), Singapore.
- Guritno, R. S., and Siringoringo, H. (2013). Perceived usefulness, ease of use, and attitude towards online shopping usefulness towards online airlines ticket purchase. Procedia - Social and Behavioral Sciences, 81, 212-216.
- Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate data analysis: a global perspective. New Jersey: Pearson Prentice Hall.
- Hanafizadeh, P., Behboudi, M., Koshksaray, A. A.m and Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian clients. Telematics and Informatics, 31(1), 62-78.
- Hu, P. J., Chau, P. Y. K., Lui Sheng, O. R., and Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112.
- IT news Africa. (2015). Will digital finance play a bigger role in SA in 2015?
- Kanchan, A., Banerjee, B., Wilson, D., and Sullivan, W. (2012). Trends in retail banking channels: improving client service and operating costs.
- Kane, S. (2016). Gen Y/Millennial lawyers in the legal workplace. What are the characteristics of Generation Y/millennials?
- Khasawneh, M. H. A. (2015). A mobile banking adoption model in the Jordanian market: an integration of TAM with perceived risks and perceived benefits. Journal of Internet Banking and Commerce, 20(3), 1-26.
- Kleijnen, M., Wetzels, M., and de Ruyter, K. (2004). Consumer acceptance of wireless finance. Journal of Financial Services Marketing, 8(3), 206-217.
- Koh, C. E., Prybutok, V. R., Ryan, S. D., and Wu, Y. (2010). A model for mandatory use of software technologies: an integrative approach by applying multiple levels of abstraction of informing science. Informing Science: The International Journal of an Emerging Transdiscipline, 13, 177-203.
- KPMG. (2015a). Digital offerings in mobile banking – the new normal.
- KPMG. (2015b). Mobile banking 2015.
- KPMG South Africa. (2014). SA banking is top notch.
- Lee, K. S., Lee, H. S., and Kim, S. Y. (2007). Factors influencing the adoption behavior of mobile banking: a South Korean perspective. Journal of Internet Banking and Commerce, 12(2), 1-9.
- Lee, M. C. (2009). Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.
- Lin, H. F. (2011). An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31(3), 252-260.
- Maduku, D. K. (2011). Understanding retail bank customers’ attitude towards and usage of cell phone and Internet banking services in Gauteng, South Africa. Johannesburg: UJ. (Dissertation – MCom).
- Maduku, D. K. (2013). Predicting retail customers’ attitude towards Internet banking service in South Africa. Southern African Business Review, 17(3), 76-100.
- Malhotra, N. K. (2010). Marketing research: an applied orientation. New Jersey: Pearson Prentice Hall.
- Markert, J. (2004). Demographics of age: generational and cohort confusion. Journal of Current Issues and Research in Advertising, 26(2), 11-25.
- Marous, J. (2013). Banking leaders discuss 2014 strategic planning priorities.
- Martins, C., Oliveira, T., and Popovič, A. (2014). Understanding the Internet banking adoption: a unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
- Mazhar, F., Rizwan, M., Fiaz, U., Ishrat, S., Razzaq, M. S., and Khan, T. N. (2014). An investigation of factors affecting usage and adoption of Internet & mobile banking in Pakistan. International Journal of Accounting and Financial Reporting, 4(2), 478-501.
- Niaura, A. (2013). Using the theory of planned behavior to investigate the determinants of environmental behavior among youth. Environmental Research, Engineering and Management, 1(63), 74-81.
- Nor, K. M., and Pearson, J. M. (2008). An exploratory study into the adoption of Internet banking in a developing country: Malaysia. Journal of Internet Commerce, 7(1), 29-73.
- Olatokun, W., and Owoeye, O. J. (2012). Influence of individual, organizational and system factors on attitude of online banking users. Proceedings of Informing Science & IT Education Conference, 389-403.
- Pallant, J. (2010). SPSS survival manual: a step by step guide to data analysis using SPSS. England: Open University Press.
- Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Educational Technology & Science, 12(3), 150-162.
- Püschel, J., and Mazzon, J. A. (2010). Mobile banking: proposition of an integrated adoption intention framework. International Journal of Bank Marketing, 28(5), 389-409.
- PwC (PricewaterhouseCoopers). (2011). When the growing gets tough: how retail banks can thrive in a disruptive, mobile, regulated world.
- PwC (PricewaterhouseCoopers). (2014). Retail banking 2020 – evolution or revolution?
- Saibaba, S., and Murthy, T. N. (2013). Factors influencing the behavioral intention to adopt Internet banking: an empirical study in India. Journal of Arts, Science & Commerce, 4(1), 77-91.
- Sayid, O., Echchabi, A., and Aziz, H. A. (2012). Investigating mobile money acceptance in Somalia: an empirical study. Pakistan Journal of Commerce & Social Sciences, 6(2), 269-281.
- Schiffman, L. G., Kanuk, L. L., and Wisenblit, J. (2010). Consumer behavior. Pearson Prentice Hall.
- Schlitzkus, L. L., Schenarts, K. D., and Schenarts, P. J. (2010). Is your residency program ready for Generation Y? Journal of Surgical Education, 67(2), 108-111.
- Shanmugam, A., Savarimuthu, M. T., and Wen, T. C. (2014). Factors affecting Malaysian behavioral intention to use mobile banking with mediating effects of attitude. Academic Research International, 5(2), 236-253.
- Sharif, K. J., Kalafatis, S. P., and Samouel, P. (2005). Cognitive and behavioral determinants of trust in small and medium-sized enterprises. Journal of Small Business & Enterprise Development, 12(3), 409-421.
- Sharp, J. H. (2007). Development, extension, and application: a review of the technology acceptance model. Information Systems Education Journal, 5(9), 1-11.
- Shezi, L. (2016). SA’s 26.8 million internet users spend almost three hours a day on social media.
- Sommer, L. (2011). The Theory of Planned Behavior and the impact of past behavior. International Business & Economics Research Journal, 10(1), 91-110.
- Special, W. P., and Li-Barber, K. T. (2012). Self-disclosure and student satisfaction with Facebook. Computers and Human Behavior, 28, 624-630.
- Standard Bank. (2015). Future of banking in Africa is mobile.
- Surendran, P. (2012). Technology acceptance model: a survey of literature. International Journal of Business and Social Research, 2, 175-178.
- Tome, L., Johnston K. A., Meadows, A., and Nyemba-Mudenda, M. (2014). Barriers to open source ERP adoption in South Africa. The African Journal of Information Systems, 6, 26-47.
- Van de Schoot, R., Lugtig, P., and Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9, 486-492.
- Wessels, L., and Drennan, J. (2010). An investigation of consumer acceptance of m-banking. International Journal of Bank Marketing, 28(7), 547-568.
- Ya‘gobi, N. M., and Rad, Z. N. (2015). Effective behavioral factors on customers’ intention to use mobile banking services. Case study: Saderat bank branches of Mashhad. Arth Prabandh: A Journal of Economics and Management, 4(2), 128-143.
- Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527-540.
- Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Services, 54(2), 1085-1091.