MODELLING CONSUMERS’ WILLINGNESS TO USE CARD-LESS BANKING SERVICES: AN INTEGRATION OF TAM AND TPB

Öz

This research seeks to fill the gap in online marketing literature by incorporating the theory of planned behaviour and technology acceptance model by examining the link between variables as well as exploring factors influencing non-users’ willingness to use card-less banking services in South Africa. To validate the integrated conceptual framework, primary data were collected from 573 randomly selected banking consumers. A Structural Equation Modelling (SEM) technique was used to analyse data relating to hypothesised relationships in the model. The paper revealed that all the framework variables influence consumer willingness to use card-less banking services. The research paper describes both scholarly and managerial implications of the outcomes and suggestions for future directions for study.

Anahtar Kelimeler

• E-retail Banking,Technology Acceptance Model,Theory of Planned Behaviour

Kaynakça

1. Ajzen, I. (1991). The theory of planned behaviour. Organizational behaviour and human decision processes, 50(2), 179-211. Ajzen, I. (2001). Nature and operation of attitudes. Annual review of psychology, 52(1), 27-58. Ajzen, I. (2002). Perceived behavioural control, self‐efficacy, locus of control, and the theory of planned behaviour 1. Journal of applied social psychology, 32(4),665-683. Al-Gahtani, S.S. (2011). Modeling the electronic transactions acceptance using an extended technology acceptance model. Applied computing and informatics, 9(1), 47-77. Ali, A., (2011), ‘Predicting individual investors’ intention to invest: An experimental analysis of attitude as a mediator’, International Journal of Human and Social Sciences 6(1), 57–73. Al-Jabri, I. M., & Sohail, M. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379-391. Amaro, S. & Duarte, P. (2015). An integrative model of consumers' intentions to purchase travel online. Tourism management, 46, 64-79. Anderson, J.C. & Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411. Artuğer, S. (2015). The effect of risk perceptions on tourists’ revisit intentions. European Journal of Business and Management, 7(2), 36-43. Asfour, H.K. & Haddad, S.I. (2014). The impact of mobile banking on enhancing customers’ e-satisfaction: An empirical study on commercial banks in Jordan.International Business Research 7(10), 145–169. Bagozzi, R.P. & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1),74-94. Bhosale, S.T. & Sawant, B.S. (2012). Security in e-banking via cardless biometric ATMs. International Journal of Advanced Technology and Engineering Research, 2(4), 9–12 Chavan, J. (2013). Internet banking: Benefits and challenges in an emerging economy. International Journal of Research in Business, 1(1), 19–26. Conner, M. & Armitage, C.J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of applied social psychology, 28(15), 1429-1464. Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. Davis, F.D., (1989), ‘Perceived usefulness, perceived ease of use and user acceptance of information technology’, MIS Quarterly 13(2), 319–340 Erkan, I. & Evans, C. (2016). The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Computers in Human Behaviour, 61, 47-55. Hair, J.F., Ringle, C.M. & Sarstedt, M. (2011). PLS-SEM: Indeed, a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152. Hanafizadeh, P., Hosseinioun, S.S. & Khedmatgozar, H.R., (2015), ‘Financial valuation of a business model as an intangible asset’, International Journal of E-Business Research 11(4), 17–31. Innova (2015). iMobile bank cardless cash, viewed 18 August 2019, from http://www.innova.com.tr/pdfs/9f550ad5-c61d-423f Internet World Stats (2019). Internet penetration in Africa, June 30, 2019. Online Accesss [https://www.internetworldstats.com/stats1.htm] Date of access: 18/08/2019 Istrate, C. (2014). Cardless withdrawal system for mobile banking applications. Journal of Mobile, Embedded and Distributed Systems, 5(1), 11–16 Kesharwani, A. & Singh Bisht, S. (2012). The impact of trust and perceived risk on internet banking adoption in India: An extension of technology acceptance model. International Journal of Bank Marketing, 30(4), 303-322. 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. Kinsman, J.E. (2019). Cardless banking in the Nelson Mandela Metropole: A means of financial inclusion for the excluded. Journal of Economic and Financial Sciences 12(1), a182. https://doi.org/10.4102/jef.v12i1.182. 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. Martins, C., Oliveira, T. & 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. Matikiti, R., Mpinganjira, M. & Roberts-Lombard, M., (2017), ‘Social media in tourism: Establishing factors influencing attitudes towards the usage of social networking sites for trip organisation’, Acta Commercii 17(1), a396. https://doi. org/10.4102/ac.v17i1.396 Moodley-Isaacs, N. (2011). Use your cellphone to draw cash, viewed 18 August 2019, from http://www.iol.co.za/personal-finance/my-money/banking/use-your-cellphone-to-draw-cash-1062775 Nunnally, J. C. (1994). Psychometric theory. 3rd ed.. New Delhi: Tata McGraw-Hill Education. 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. Terry, D. J., & Hogg, M. A. (2000). Attitudes, behaviour, and social context. Upper Saddle River,New Jersey: Psychology Press. 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. Venkatesh, V. & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204. Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 36(1), 157-178. Wang, C.C., Lo, S.K. & Fang, W. (2008). Extending the technology acceptance model to mobile telecommunication innovation: The existence of network externalities. Journal of Consumer Behaviour: An International Research Review, 7(2), 101-110. Wang, L., & Yi, Y. (2012). The impact of use context on mobile payment acceptance: An empirical study in China. In Advances in computer science and education (pp. 293-299). Berlin: Springer. Wu, J.H. & Wang, S.C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729. Xue, M., Hitt, L.M. & Chen, P.Y. (2011). Determinants and outcomes of internet banking adoption. Management science, 57(2), 291-307. Yee-Loong Chong, A., Ooi, K.B., Lin, B. & Tan, B.I., (2010). Online banking adoption: an empirical analysis. International Journal of bank marketing, 28(4), 267-287.