Skip to main content
Log in

Understanding the intention to use mobile banking by existing online banking customers: an empirical study

  • Original Article
  • Published:
Journal of Financial Services Marketing Aims and scope Submit manuscript

Abstract

The Indian banking sector can take advantage of the proliferation of smartphones as well as the government’s encouragement of cashless transactions to accelerate the use of mobile and online banking. The purpose of this study is to understand the initial acceptance of mobile banking by existing online banking users. Few studies have focused on online banking users’ behavioural intention to use similar services (such as mobile banking) in India. To this end, a theoretical model was developed using the technology acceptance model, which was extended to cover the adoption factors that influence users of online banking to use mobile banking. These adoption factors comprise perceived ease of use, perceived security, mobile self-efficacy, social influence and customer support. The dependent variable is customers’ behavioural intention to use mobile banking. A partial least squares structural equation modelling analysis was used to test the theoretical model with sample data from 420 online banking customers of various public, private, foreign and co-operative banks in India. The study found that the adoption factors had a significant impact on customers’ behavioural intention to use mobile banking. The findings of this study provide insight into digital banking channels, contribute to existing research on digital banking adoption and will educate banks and financial institutions on the adoption of mobile banking in India.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Alalwan, A., Y. Dwivedi, N. Rana, B. Lal, and M. Williams. 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.

    Google Scholar 

  • Baabdullah, A.M., A.A. Alalwan, N.P. Rana, P. Patil, and Y.K. Dwivedi. 2019. An integrated model for m-banking adoption in Saudi Arabia. International Journal of Bank Marketing 37(2): 452–478.

    Google Scholar 

  • Bandura, A. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84(2): 191–215.

    Google Scholar 

  • Bandura, A. 1986. Social foundations of thought and action. Upper Saddle River, NJ: Prentice-Hall.

    Google Scholar 

  • Barnes, S., and B. Corbitt. 2003. Mobile banking: Concept and potential. International Journal of Mobile Communications 1(3): 273.

    Google Scholar 

  • BCG. 2019. Encashing on Digital: Financial services in 2020. The Boston Consulting Group, Facebook.

  • Bharti, M. 2016. Impact of dimensions of mobile banking on user satisfaction. The Journal of Internet Banking and Commerce 21(1): 1–22.

    Google Scholar 

  • Bhatt, A., and S. Bhatt. 2016. Factors affecting customers adoption of mobile banking services. The Journal of Internet Banking and Commerce 21(1): 161.

    Google Scholar 

  • Chen, L. 2008. A model of consumer acceptance of mobile payment. International Journal of Mobile Communications 6(1): 32.

    Google Scholar 

  • Cheng, T., D. Lam, and A. Yeung. 2006. Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems 42(3): 1558–1572.

    Google Scholar 

  • Chiu, J.L., N.C. Bool, and C.L. Chiu. 2017. Challenges and factors influencing initial trust and behavioral intention to use mobile banking services in the Philippines. Asia Pacific Journal of Innovation and Entrepreneurship 11(2): 246–278.

    Google Scholar 

  • Compeau, D., and C. Higgins. 1995. Computer self-efficacy: Development of a measure and initial test. MIS Quarterly 9(2): 189.

    Google Scholar 

  • Cruz, P., L.B.F. Neto, P. Munoz-Gallego, and T. Laukkanen. 2010. Mobile banking rollout in emerging markets: Evidence from Brazil. The International Journal of Bank Marketing 28(5): 342–371.

    Google Scholar 

  • Danyali, A.A. 2018. Factors influencing customers’ change of behaviors from online banking to mobile banking in Tejarat Bank, Iran. Journal of Organizational Change Management 31(6): 1226–1233.

    Google Scholar 

  • Davis, F.D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13: 319–340.

    Google Scholar 

  • De Leon, M.V. 2019. Factors influencing behavioural intention to use mobile banking among retail banking clients. Jurnal Studi Komunikasi 3(2): 118–137.

    Google Scholar 

  • Fornell, C., and D.F. Larcker. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18: 39–50.

    Google Scholar 

  • Garland, R. 1991. The mid-point on a rating scale: Is it desirable. Marketing Bulletin 2(1): 66–70.

    Google Scholar 

  • Geisser, S. 1974. A predictive approach to the random effect model. Biometrika 61(1): 101–107.

    Google Scholar 

  • Ghani, M.A., S. Rahi, N.M. Yasin, and F.M. Alnaser. 2017. Adoption of internet banking: extending the role of technology acceptance model (TAM) with e-customer service and customer satisfaction. World Applied Sciences Journal 35(9): 1918–1929.

    Google Scholar 

  • Giovanis, A., P. Athanasopoulou, C. Assimakopoulos, and C. Sarmaniotis. 2019. Adoption of mobile banking services. International Journal of Bank Marketing 37(5): 1165–1189.

    Google Scholar 

  • Hair, J.F., R. Anderson, R. Tatham, and W. Black. 2006. Multivariate data analysis. 6th ed. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Hair, J., C. Ringle, and M. Sarstedt. 2011. PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice 19(2): 139–152.

    Google Scholar 

  • Hair, J.F., C.M. Ringle, and M. Sarstedt. 2013. Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning 46(1–2): 1–12.

    Google Scholar 

  • Hamidi, H., and M. Safareeyeh. 2019. A model to analyze the effect of mobile banking adoption on customer interaction and satisfaction: A case study of m-banking in Iran. Telematics and Informatics 38: 166–181.

    Google Scholar 

  • Hanafizadeh, P., M. Behboudi, A. Abedini Koshksaray, and M. Jalilvand ShirkhaniTabar. 2014. Mobile-banking adoption by Iranian bank clients. Telematics and Informatics 31(1): 62–78.

    Google Scholar 

  • Harris, M., K.C. Cox, C.F. Musgrove, and K.W. Ernstberger. 2016. Consumer preferences for banking technologies by age groups. International Journal of Bank Marketing 34(4): 587–602.

    Google Scholar 

  • Hassan, H.E., and V.R. Wood. 2020. Does country culture influence consumers’ perceptions toward mobile banking? A comparison between Egypt and the United States. Telematics and Informatics 46: 1–14.

    Google Scholar 

  • Hinkin, T. 1998. A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods 1(1): 104–121.

    Google Scholar 

  • Hong, S., and K. Tam. 2006. Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research 17(2): 162–179.

    Google Scholar 

  • IBEF. 2019. Banking. India Brand Equity Foundation.

  • InMobi. 2019. The changing face of the Indian mobile user 2019 Mobile Marketing Handbook, Inmobi.

  • Jayawardhena, C. 2004. Measurement of service quality in internet banking: The development of an instrument. Journal of Marketing Management 20(1/2): 185–207.

    Google Scholar 

  • Jeong, B.K., and T.E. Yoon. 2013. An empirical investigation on consumer acceptance of mobile banking services. Business and Management Research 2(1): 31–40.

    Google Scholar 

  • Juniperresearch.com. 2019. Mobile banking users to exceed 1.75 billion by 2019, representing 32% of the global adult population. [online] https://www.juniperresearch.com/press-release/digital-banking-pr1. Accessed 20 March 2019.

  • Khalifa, M., and K.N. Shen. 2008. Drivers for transactional B2C m-commerce adoption: Extended theory of planned behavior. Journal of Computer Information Systems 48(3): 111.

    Google Scholar 

  • Khan, M.S., and S.S. Mahapatra. 2009. Service quality evaluation in internet banking: an empirical study in India. International Journal of Indian Culture and Business Management 2(1): 30–46.

    Google Scholar 

  • 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: 128.

    Google Scholar 

  • Koksal, M. 2016. The intentions of Lebanese consumers to adopt mobile banking. International Journal of Bank Marketing 34(3): 327–346.

    Google Scholar 

  • KPMG. 2019. Fintech in India—Powering mobile payments. KPMG.

  • Laforet, S., and X. Li. 2005. Consumers’ attitudes towards online and mobile banking in China. International Journal of Bank Marketing 23(5): 362–380.

    Google Scholar 

  • Laukkanen, Tommi, and Pasanen Mika. 2008. Mobile banking innovators and early adopters: How they differ from other online users? Journal of Financial Services Marketing 13(2): 86–94.

    Google Scholar 

  • Lin, H.F. 2013. Determining the relative importance of mobile banking quality factors. Computer Standards and Interfaces 35(2): 195–204.

    Google Scholar 

  • Luarn, P., and H.H. Lin. 2005. Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior 21(6): 873–891.

    Google Scholar 

  • McKnight, D., V. Choudhury, and C. Kacmar. 2002. Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research 13(3): 334–359.

    Google Scholar 

  • Mortimer, G., L. Neale, S. Hasan, and B. Dunphy. 2015. Investigating the factors influencing the adoption of m-banking: A cross cultural study. International Journal of Bank Marketing 33(4): 545–570.

    Google Scholar 

  • Mutahar, A., N. Daud, R. Thurasamy, O. Isaac, and R. Abdulsalam. 2018. The mediating of perceived usefulness and perceived ease of use. International Journal of Technology Diffusion 9(2): 21–40.

    Google Scholar 

  • Nunnally, J. 1978. Psychometric theory. New York, NY: McGraw-Hill.

    Google Scholar 

  • Oruç, Ö.E., and Ç. Tatar. 2017. An investigation of factors that affect internet banking usage based on structural equation modeling. Computers in Human Behavior 66: 232–235.

    Google Scholar 

  • Pikkarainen, T., K. Pikkarainen, H. Karjaluoto, and S. Pahnila. 2004. Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research 14(3): 224–235.

    Google Scholar 

  • Podsakoff, P., S. MacKenzie, J. Lee, and N. Podsakoff. 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88(5): 879–903.

    Google Scholar 

  • Püschel, J., J. Afonso Mazzon, C. Mauro, and J. Hernandez. 2010. Mobile banking: proposition of an integrated adoption intention framework. International Journal of Bank Marketing 28(5): 389–409.

    Google Scholar 

  • Rahi, S., and M.A. Ghani. 2019. Investigating the role of UTAUT and e-service quality in internet banking adoption setting. The TQM Journal 31(3): 491–506.

    Google Scholar 

  • Ringle, C., S. Wende, and J. Becker. 2015. SmartPLS 3 (Version 3.2. 3). Boenningstedt: SmartPLS GmbH.

  • Santos, J. 2003. E-service quality: a model of virtual service quality dimensions. Managing Service Quality: An International Journal 13(3): 233–246.

    Google Scholar 

  • Sathye, M. 1999. Adoption of Internet banking by Australian consumers: An empirical investigation. International Journal of Bank Marketing 17(7): 324–334.

    Google Scholar 

  • Shankar, A., C. Jebarajakirthy, and M. Ashaduzzaman. 2020. How do electronic word of mouth practices contribute to mobile banking adoption? Journal of Retailing and Consumer Services 52: 101920.

    Google Scholar 

  • Shankar, A., and P. Kumari. 2016. Factors affecting mobile banking adoption behavior in India. The Journal of Internet Banking and Commerce 21(1).

  • Stone, M. 1974. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society. Series B (Methodological) 36(2): 111–133.

    Google Scholar 

  • Tan, E., and J.L. Lau. 2016. Behavioural intention to adopt mobile banking among the millennial generation. Young Consumers 17(1): 18–31.

    Google Scholar 

  • Tarhini, A., M. El-Masri, M. Ali, and A. Serrano. 2016. Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon. Information Technology and People 29(4): 830–849.

    Google Scholar 

  • Tran, H.T.T., and J. Corner. 2016. The impact of communication channels on mobile banking adoption. International Journal of Bank Marketing 34(1): 78–109.

    Google Scholar 

  • Venkatesh, V., and F. Davis. 1996. A model of the antecedents of perceived ease of use: Development and test. Decision Sciences 27(3): 451–481.

    Google Scholar 

  • Venkatesh, V., and F.D. Davis. 2000. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science 46(2): 186.

    Google Scholar 

  • Venkatesh, V., M. Morris, G. Davis, and F. Davis. 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly 27(3): 425–478.

    Google Scholar 

  • Wang, Y.S., Y.M. Wang, H.H. Lin, and T.I. Tang. 2003. Determinants of user acceptance of internet banking: an empirical study. International Journal of Service Industry Management 14(5): 501–519.

    Google Scholar 

  • White, H., and F. Nteli. 2004. Internet banking in the UK: Why are there not more customers? Journal of Financial Services Marketing 9(1): 49–56.

    Google Scholar 

  • Zeithaml, V.A., A. Parasuraman, and A. Malhotra. 2002. Service quality delivery through web sites: A critical review of extant knowledge. Journal of the Academy of Marketing Science 30(4): 362–375.

    Google Scholar 

  • Zhang, T., C. Lu, and M. Kizildag. 2018. Banking “on-the-go”: Examining consumers’ adoption of mobile banking services. International Journal of Quality and Service Sciences 10(3): 279–295.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sindhu Singh.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, S., Srivastava, R.K. Understanding the intention to use mobile banking by existing online banking customers: an empirical study. J Financ Serv Mark 25, 86–96 (2020). https://doi.org/10.1057/s41264-020-00074-w

Download citation

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/s41264-020-00074-w

Keywords

Navigation