Document Type : Research Article

Author

Dayananda Sagar College of Arts, Science and Commerce, Bengaluru.

Abstract

Technology transition is norm for any business survival and growth. Across the globe business environment doesn’t permit any leverage on technology adoption.  The recent pandemic further made it mandatory for every organization to transform into technology enabled business operation. Many sectors were forced to adopt faster technology change to keep pace of business. Banking sector is no exception for this. After merging under single umbrella SBI has initiated technology transition and attempting to offer technology at fingertips both for its employees and customers. In recent press release SBI announced adoption of automation, AI and Machine learning in most of its back-end jobs for operational efficiency and cost advantage. These initiatives cannot be deployed in isolation; it has to have human interface to complete business process. And natural human response for any change is resistance. This is not easier transition rather this is continuous process with many challenges. The major issues are employees’ adoptability to the changing technology in the job performance. Individual perception and intentions are major determinant factors for any technology adoption. Technology Adoption Model elaborately explains human behavioral responses to new technology. Perceived usefulness and Perceived ease of use are two major attributes to the behavior intentions. This study attempts to test these attributes among bank employees with respect to implementation of information technology in banking service. Resistance for any change is human nature, but preparedness to overcome this resistance is need of hour for organizational and employee survival.

Keywords

Main Subjects

  1. Ajzen, I. and Fishbein, M. (1980), “Understanding attitudes and Predicting Social behavior,” Prentice- hall, Englewood Cliffs, NJ
  2. Ajzen, I. (1985), “From intentions to action: Theory of planned behavior”, in Jkuhl, J.B. (ED) Action Control: From cognition to behavior, Springer Verlag, New York, NY, pp11-39
  3. Ajzen, I. (1991), “ Theory of Planned behavior”, organizational behavior and human decision process, Vol.50, No.2. pp179-211
  4. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  5. Davis F. D, Bagozzi R. P, Warshaw P. R. User acceptance of computer technology: a comparison of two theoretical models. Manage Sci 1989 Aug;35(8):982-1003. [CrossRef]
  6. Taylore, S. and Todd, P.A. (1995) ‘Understanding the information technology usage: A test of competing models” Information system research, Vol. 6, No. 2, pp144-74
  7. Davis, F.D. and Venkatesh, V. (1996), “A critical assessment of potential Measurement biases in the technology acceptance model: three experiments,” Internet Journal of Human Computer Studies, Vol.45, No., pp19-45
  8. Venkatesh, V. and Davis, F.D. (1996), “A model of antecedents of perceived ease of use: a development and test,” Decision Science. Vol27, No. 3, pp451-81
  9. Dimoka, A, and Davis, D, F. (2008), Where does TAM resids in the brain? The neutral mechanism underlying technology adoption, retrieved from https://aisel.aisnet.org/icis2008/169/
  10. Ganhwar, H., Date, H., Ramaswamy, R.(2014), Understanding determinants of cloud computing adoption using an integrated TAM-TOE model, retrieved from https://www.emerald.com/insight/content/doi/10.1108/JEIM-08-2013-0065/full/pdf
  11. Sanghai, S. (2020) Full digitization of banking sector: how this can be achieved, retrieved from https://economictimes.indiatimes.com/industry/banking/finance/banking/full-digitalisation-of-banking-sector-how-this-can-be-achieved/articleshow/74408411.cms?from=mdr White Papers
  12. Deloitte (2020), Covid -19 Impact on banking in India-Finding the silver lining retrieved from https://www2.deloitte.com/content/dam/Deloitte/in/Documents/financial-services/in-fsi-Impact-of-Covid19onBanking-in-India_BrandPart2-noexp.pdf
  13. McKinsey, (2021) Indian Bank Risks Rs 12 trillion Covid-19 hit, Says McKinsey, retrieved from https://www.consultancy.in/news/3482/indian-banks-risk-rs-12-trillion-covid-19-hit-says-mckinsey