The Indian government supports small and medium enterprises in adopting and using e-banking services as a part of its 'Digital India' campaign. Few studies have focused on the adoption of electronic banking by SMEs in India. Hence, it is imperative to understand the perception of SMEs to adopt e-banking services. The purpose of this paper was to empirically study the direction of relationships between perceived ease of use, perceived usefulness, perceived convenience, perceived self-efficacy, trust, perceived risk, government support, and intention to adopt online banking. A cross-sectional descriptive survey was carried out to gather quantitative data from 132 SMEs in Karnataka. The data were analyzed using the PLS method of structural equation modeling. The results showed that perceived usefulness, perceived risk, and perceived ease of use determined e-banking adoption. Trust was positively related to perceived risk of e-banking transactions. We found that perceived self-efficacy affected perceived ease of use that, in turn, determined perceived usefulness. Hence, the banks should provide training programmers to improve self-efficacy and allocate more resources to create an easy-to-use system and adopt risk reduction measures that inhibit identity theft and fraudulent activities over the Internet to foster trust among prospective SMEs. Unlike existing studies, our model included additional variables namely trust, perceived risk, perceived self-efficacy, and government support. This model could be applied to SMEs in other developing countries that are in the initial phases of adoption of online banking.

1. Amin, H. (2007). Internet banking adoption among young intellectuals. Journal of Internet Banking and Commerce, 12 (3), 1 - 13.
2. Amin, H. (2009). An analysis of online banking usage intentions: An extension of the technology acceptance model. International Journal of Business and Society, 10(1), 27 - 40.
3. Çelik, H. (2008). What determines Turkish customers’ acceptance of internet banking ? International Journal of Bank Marketing, 26(5), 353 - 370. DOI: 10.1108/02652320810894406
4. Cheng, T. C. E., Lam, D.Y.C., & Yeung, A.C.L. (2006). Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems, 42 (3), 1558 - 1572. DOI: 10.1016/j.dss.2006.01.002
5. Chong, A. Y.- L., Ooi, K. - B., Lin, B., & Tan, B. - I. (2010). Online banking adoption: An empirical analysis. International Journal of Bank Marketing, 28(4), 267 - 287. DOI : https://doi.org/10.1108/02652321011054963
6. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). Mahwah, NJ : Lawrence Erlbaum.
7. Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319 - 339.DOI : http://dx.doi.org/10.2307/249008
8. Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User acceptance of computer technology: Comparison of two theoretical models. Management Science, 35(8), 982 - 1003. DOI : https://doi.org/10.1287/mnsc.35.8.982
9. Dijkstra, T.K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics & Data Analysis, 81(1),10 - 23. DOI: 10.1016/j.csda.2014.07.008
10. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59 (4), 451 - 474. DOI:10.1016/S1071-5819(03)00111-3
11. Fornell, C.,& Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39 - 50. DOI: 10.2307/3151312.
12. Fornell, C., & Robinson, W. T. (1983). Industrial organization and consumer satisfaction/ dissatisfaction. Journal of Consumer Research, 9 (4), 403 - 412.
13. Gnanasambandam, C., Madgavkar, A., Kaka, N., Manyika, J., Chui, M., Bughin, J., & Gomes, M. (2012). Online and upcoming: The Internet’s impact on India. Mumbai : McKinsey & Company.
14. Gounaris, S., & Koritos, C. (2008). Investigating the drivers of internet banking adoption decision: A comparison of three alternative frameworks. International Journal of Bank Marketing, 26 (5), 282 - 304.
15. Grabner - Krauter, S., & Faullant, R. (2008). Consumer acceptance of Internet banking : The influence of internet trust. International Journal of Bank Marketing, 26 (7), 483 - 504.
16. Hair, J.F., Ringle, C.M., & Sarstedt, M. (2011). PLS-SEM : Indeed a silver bullet. Journal of Marketing Theory and Practice, 19 (2),139 - 151. DOI: 10.2753/MTP1069-6679190202
17. Hair, J.F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V.G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26 (2),106 - 121.
18. Hernandez, J.M.C., & Mazzon, J.A. (2007). Adoption of internet banking: Proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing, 25 (2),72 - 88. DOI : http://dx.doi.org/10.1108/02652320710728410
19. Jahangir, N., & Begum, N. (2008). The role of perceived usefulness, perceived ease of use, security and privacy, and customer attitude to engender customer adaption in the context of electronic banking. Africa Journal of Business Management, 2 (1), 32 - 40.
20. Kesharwani, A., & Tripathy, T. (2012). Dimensionality of perceived risk and its impact on Internet banking adoption: An empirical investigation. Services Marketing Quarterly, 33 (2), 177 - 193. DOI : https://doi.org/10.1080/15332969.2012.662461
21. Lassar, W.M., Manolis, C., & Lassar, S.S. (2005). The relationship between consumer innovativeness, personal characteristics, and online banking adoption. International Journal of Bank Marketing, 23 (2), 176 - 199.
22. 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. Doi: https://doi.org/10.1016/j.elerap.2008.11.006
23. Littler, D., & Melanthiou, D. (2006). Consumer perceptions of risk and uncertainty and the implications for behaviour towards innovative retail services: The case of Internet banking. Journal of Retailing and Consumer Services, 13(6), 431 - 443. DOI: 10.1016/j.jretconser.2006.02.006
24. Mohapatra, S., Sahoo, D., & Kesharwani, A. (2015). Outsourcing of information technology: An empirical study in the Indian banking industry. Indian Journal of Finance, 9(7), 7 - 21. DOI:10.17010/ijf/2015/v9i7/72350
25. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879 - 891.
26. Roy, S.K., Balaji, M.S., Keshaewani, A., & Sekhon, H. (2015). Predicting Internet banking adoption in India: A perceived risk perspective. Journal of Strategic Marketing, 25(5-6), 418 - 438. DOI : https://doi.org/10.1080/0965254X.2016.1148771
27. Shukla, S. (2016). Performance of the Indian banking industry : A comparison of public and private sector banks. Indian Journal of Finance, 10 (1), 41 - 55. DOI: 10.17010/ijf/2016/v10i1/85843
28. Singh, D., & Singh, H. (2016). Market penetration by Indian banks: Motives and motivators. Indian Journal of Finance, 10 (3), 28 - 42. DOI: 10.17010/ijf/2016/v10i3/89020
29. Sripalawat, J., Thongmak, M., & Ngramyarn, A. (2011). M-banking in metropolitan Bangkok and a comparison with other countries. The Journal of Computer Information Systems, 51 (3), 67 - 76. DOI: 10.1080/08874417.2011.11645487
30. Tang, J. E., & Chiang, C. (2009). Towards an understanding of the behavioral intention to use mobile knowledge management. WSEAS Transactions on Information Science and Application, 6 (9), 1601 - 1613.
31. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186 - 204. DOI : http://dx.doi.org/10.1287/mnsc.46.2.186.11926
32. Yang, A.S. (2009). Joint production in banking industry. Indian Journal of Finance, 3 (6), 45 - 55.
33. Yiu, C.S., Grant, Y.K., & Edgar, D. (2007). Factors affecting the adoption of Internet banking in Hong Kong - Implications for the banking sector. International Journal of Information Management, 27 (5), 336 - 351. DOI: 10.1016/j.ijinfomgt.2007.03.002
34. Yoon C., & Kim S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electronic Commerce Research and Applications, 6 (1), 102 - 112. DOI:10.1016/j.elerap.2006.06.009
35. Zahir, M., & Gharleghi, B. (2015). Adoption of Internet banking in Maldives, the most important determinants. Asian Social Science, 11(2), 181 - 189. DOI: 10.5539/ass.v11n2p181