Factors Influencing the Adoption of Mobile Banking

Factors influencing the use of Mobile Banking:
The case of SMS-based Mobile Banking offered

CHAPTER ONE
INTRODUCTION
Mobile banking is an application of mobile computing which provides customers with the support needed to be able to bank anywhere, anytime using a mobile handheld device and a mobile service such as text messaging (SMS). Mobile banking removes space and time limitations from banking activities such as checking account balances, or transferring money from one account to another. In recent research and studies it was found that while mobile banking and more specifically SMS-based mobile banking applications have become popular in some countries and regions, they were still not widely used.
This study identifies and investigates the factors which influence customers’ decision to use a specific form of mobile banking, and specifically focuses on the evaluation of SMS-based mobile banking in the context of Tanzania a case study at CRDB Bank plc. The research model includes the basic concepts of the Technology Acceptance Model (TAM), as well as some constructs derived through a focus group discussion. The model is tested to determine its predictive power with respect to individual’s behaviour when considering the use of SMS-based mobile banking. A survey questionnaire was developed and employed to collect data from 10 SAUT university students in Tanzania. The results of the data analysis contributes to the body of knowledge in the area by demonstrating that context specific factors such as service quality and service awareness are influencing user perceptions about the usefulness of SMS mobile banking which in turn affect intention to use and adoption. Secondly, the study demonstrates, on the example of SMS-based mobile banking, how a hybrid approach involving qualitative data collection and a subsequent quantitative survey can help investigate how user perceptions about usefulness and ease of use are formed. Although the study has its limitations,

References: Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication Agarwal, R., & Prasad, J. (1997). The Role of Innovation Characteristics and Perceived Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000). Research report: The evolving relationship between general and specific computer self-efficacy – An Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour Babbie, E. (1990). Survey Research Methods (2nd Ed.). Belmont, California: Wadsworth Publishing Company. Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122–147. Bhatnagar, A., Misra, S., & Rao, H.R. (2000). On risk, convenience, and internet shopping behaviour Black, N.J., Lockett, A., Winklhofer, H., & Ennew, C. (2001). The adoption of Internet financial services: a qualitative study Brown, I., Cajee, Z., Davies, D., & Stroebel, S. (2003). Cell phone banking: predictors of adoption in South Africa- an exploratory study Bryman, A. (2001). Social Research Methods. New York: Oxford University Press. Calder, B. J. (1977). Focus groups and the nature of qualitative marketing research Cavana, R.Y., Delahaye, B.L., & Sekaran, U. (2001). Applied Business Research: Qualitative and Quantitative Methods Chan, S. C., & Lu, T. M. (2004). Understanding Internet Banking Adoption and use Behaviour: A Hong Kong perspective Chau, P. Y. K. (2001). Influence of computer attitude and self-efficacy on IT usage behaviour Chau, P.Y.K., & Lai, V.K.S. (2003). An empirical investigation of the determinants of user acceptance of Internet Banking Chen, K., & Rea, A. I. (2004). Protecting personal information online: a survey of user privacy concerns and control techniques Chin, W. C., & Todd, P. A. (1995). On the use, usefulness and ease of use of structural equation modelling in MIS research: A note of caution Converse, J.M. (1987). Survey Research in the United States: Roots and Emergence 1890-1960 Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision making the case of telephone shopping Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology Davis, L. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models Doll, W. J., Hendrickson, A., & Deng, X. (1998). Using Davis’s perceived usefulness and ease-of-use instruments for decision making: A confirmatory Edmunds, H. (1991). The Focus Group Research Handbook. Ntc Business Books. Fain, D., & Roberts, M. L. (1997). Technology vs. consumer behaviour: the battle for the financial services customer Featherman, S, M. (2002). Predicting e-services adoption: a perceived risk facets perspective Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research November 30, 2008, from www.ireach.ie Forman, A.M., & Sriram, V Gefen, D. (2002). Customer loyalty in e-commerce. Journal of association for information systems, 3, 27-50. Gehrt, K.C., & Yale, L.J. (1993). The dimensionality of the convenience phenomenon: a qualitative re-examination Gibbs, A. (1997). Focus groups. Social Research Update 19. Retrieved April 22, 2006, from http://www.soc.surrey.ac.uk/sru/SRU19.html Goldsmith, R. E., & Bridges, E. (2000). E-tailing vs. retailing: using attitudes to predict online buying behaviour Hair, J., Anderson, R., Tatham, R., & Black, W. (2006). Multivariate data analysis (6th Ed.) Hale, D., & Thakur, R. (2006). Self-service technologies and Generation Y: are they beyond the personal touch Heinonen, K. (2004). Time and Location as Customer Perceived Value Drivers, Economi och Samhalle 124, Swedish School of Economics and Business Hong, W., Thong, J. Y. L., Wong, W. M., & Tam, K. Y. (2001). Determinants of user acceptance of digital libraries: An empirical examination of individual