Technology plays a vital role in all sectors of an economy. During COVID-19 we witnessed many new technologies in different industries. Digital India acts as the excellence of mobile and internet banking services and those disrupted the brick and mortar banking services. During COVID-19 Fin-tech companies such as Phone pay, Pay tm, Mobikwik, and U Pay achieves tremendous growth for digital retail payments through the concepts of Unified Payment Interface (UPI) and mobile wallets. Artificial intelligence and block chain are the disruptive technologies that will bring sustainable business practices to different sectors of an economy including the banking and financial services industry Cashless transactions, National Electronic Fund Transfer, Electronic Clearing Service, branchless approaches for banking transactions such as kiosks, micro ATMs, and ATMs are the various technologies implemented by the scheme of Pradhan Mantri Jan-Dhan Yojana in India for financial inclusion. The main objective of the current study is to find the acceptance level of financial and banking services disruptive technology among rural people in Tamil Nadu, India. The study used primary data sources to make relationships among the variables, 384 sample sizes at 5% of error were taken for the large populations. The study adopted a convenient sample technique and data were collected from the rural people in Tamil Nadu. PLS-SEM was adopted to make the relationship among the variables. The study found that there is a significant relationship between the disruptive technology dimensions such as perceived usefulness, perceived ease of use, portability, perceived value, and trust in attitude and intention to use digital financial services. However, there is no relationship found between the perceived value of attitude and portability on intention to use financial services.

1.
Nayyar
,
D.
Asian transformations: An inquiry into the development of nations
Oxford University Press
, (
2019
).
2.
Abdel-Basset
,
M.
,
Chang
,
V.
, &
Nabeeh
,
N. A.
An intelligent framework using disruptive technologies for COVID-19 analysis
.
Technological Forecasting and Social Change
,
163
,
120431
(
2021
).
3.
Priyadarshini
V.
,
M.S.
Ahmed
,
R.
Sathya
,
V. Chandra
Lekha
,
D.
Koteeswari
,
S.
Ragothaman
.
Does Central Bank Digital Currency (CBDC) Disrupt the Crypto Currencies Market In India? - A Case Study
,
Journal of the Oriental Institute
, Vol.
71
, Issue.
4
(3),
66
71
(
2022
).
4.
Agur
,
I.
,
Peria
,
S. M.
, &
Rochon
,
C.
Digital financial services and the pandemic: Opportunities and risks for emerging and developing economies
.
International Monetary Fund Special Series on COVID-19, Transactions
,
1
,
2
1
(
2020
).
5.
Walsh
,
S. T.
, &
Linton
,
J. D.
Infrastructure for emergent industries based on discontinuous innovations
.
Engineering Management Journal
,
12
(
2
),
23
32
(
2000
).
6.
Christensen
,
C. M.
The on-going process of bui lding a theory of disruption
.
Journal of Product innovation management
,
23
(
1
),
39
55
(
2006
).
7.
Christensen
,
C. M.
The innovator’s dilemma: when new technologies cause great firms to fail
.
Harvard Business Review Press.
(
2013
).
8.
Christensen
,
R. H. B.
Analysis of ordinal data with cumulative link models—estimation with the R-package ordinal
.
R-package version
,
28
,
145
(
2015
).
9.
Maddux
,
J. E.
, &
Rogers
,
R. W.
Protection motivation and self-efficacy: A revised theory of fear appeals and attitude change
.
Journal of experimental social psychology
,
19
(
5
),
469
479
(
1983
).
10.
Moore
,
G. C.
, &
Benbasat
,
I.
Development of an instrument to measure the perceptions of adopting an information technology innovation
.
Information systems research
,
2
(
3
),
192
222
(
1991
).
11.
Rogers
,
E. M.
Diffusion of Innovations: modifications of a model for telecommunications. In Die diffusion von innovationen in der telekommunikation
,
Springer, Berlin, Heidelberg
,
25-38
(
1995
).
12.
Davis
,
F. D.
Perceived usefulness, perceived ease of use, and user acceptance of information technology
.
MIS quarterly
,
319
340
(
1989
).
13.
Venkatesh
,
V.
, &
Davis
,
F. D.
A theoretical extension of the technology acceptance model: Four longitudinal field studies
.
Management science
,
46
(
2
),
186
204
(
2000
).
14.
Venkatesh
,
V.
,
Morris
,
M. G.
,
Davis
,
G. B.
, &
Davis
,
F. D.
User acceptance of information technology: Toward a unified view
.
MIS quarterly
,
425
478
(
2003
).
15.
Ahmed
,
M. S.
, &
Sajid
,
S. A.
Technology impact on e-banking towards customer satisfaction in public & private sectors bank [with special reference to Vellore district of Tamil Nadu-India].
International Journal of Scientific and Technology Research
,
8
(
12
),
255
259
(
2019
).
16.
Priyadarshini
,
V.
,
Margabandhu
,
S.
,
Koteeswari
,
D.
,
Ahmed
,
M. S.
,
Sathya
,
R.
, &
Ragothaman
,
S.
Impact of online class service quality on students’ satisfaction on Post COVID-19: Evidence from selected self-financing Engineering Institutions
,
Journal of Survey in Fisheries Sciences
,
664
680
(
2023
).
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