A hi MC; Vini ha K
A icle
Mobile banking: An analysis o usage in he p esen e a
Global Business & Finance Re iew (GBFR)
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People & Global Business Associa ion (P&GBA), Seoul
Sugges ed Ci a ion: A hi MC; Vini ha K (2024) : Mobile banking: An analysis o usage in he
p esen e a, Global Business & Finance Re iew (GBFR), ISSN 2384-1648, People & Global Business
Associa ion (P&GBA), Seoul, Vol. 29, Iss. 2, pp. 47-56,
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I. In oduc ion
Mobile banking and using mobile phones as
comple e paymen solu ions s a ed ca ching up abou
a decade ago wi h he in oduc ion o a o dable
sma phones and he emendous g ow h o mobile
applica ion de elopmen s. Mobile banking usage ook
a majo leap in India a e Demone iza ion and
COVID-19, which a e he game change s in he mobile
Recei ed: No . 17, 2023; Re ised: Dec. 6, 2023; Accep ed: Jan. 6, 2024
† Co esponding au ho : A hi MC
E-mail: a [email protected]
banking a ena and helped change use s' mind-se in
handling money. Passbooks and checkbooks now
s a ed anishing slowly. UPI enablemen by banks
in India, is ano he main aid o his change, in he
mobile banking pla o m, as i p omo es he p o ec ion
o he people by b inging in an online sys em o
buy goods and pay ins an ly. Banks and paymen
se ices in India and many o he coun ies, a e
equi ed o adhe e o Know You Cus ome (KYC)
no ms om all use s using mobile paymen se ices
and KYC se es as a basic hygiene ac o now in
he paymen sec o . Some o he sa e y p ocesses
like iple alida ion, biome ics scanning like
GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 2 (MARCH 2024), 47-56
pISSN 1088-6931 / eISSN 2384-1648∣H ps://doi.o g/10.17549/gb .2024.29.2.47
ⓒ 2024 People and Global Business Associa ion
GLOBAL BUSINESS & FINANCE REVIEW
www.gb jou nal.o g1)
o inancial sus ainabili y and people-cen e ed global business
Mobile Banking: An Analysis o Usage in he P esen E a
A
hi MCa†, Vini ha Kb
aResea ch Schola , Facul y o Managemen , SRM Ins i u e o Science and Technology, SRM Naga , Ka ankula hu , 603203, Chengalpa u
Dis ic , TN, India
bAssis an P o esso , Facul y o Managemen , SRM Ins i u e o Science and Technology, SRM Naga , Ka ankula hu , 603203, Chengalpa
u
Dis ic , TN, India
A
B S T R A C T
Pu pose: This a icle aims o s udy mobile banking usage in ecen imes and o unde s and he ela ionship be ween
he pe cep ion o cus ome s and ac ual usage ends.
Design/me hodology/app oach: P ima y da a is collec ed using he su ey me hod and a ious cha s along wi h
he TAM (Technology Accep ance Model) cons uc ed using Sma PLS is used o unde s and he ela ionship.
Findings: The esul s showcase a s ong ela ionship be ween pe cei ed ease o use, use ulness, in en ion o use,
and ac ual usage o mobile banking. The indings demons a e ha mobile paymen s saw a su ge in he p esen
e a, bank isi s and chequebook usage d opped, and inc eased adop ion in he olde popula ion.
Resea ch limi a ions/implica ions: The limi a ions ha a e obse ed in his esea ch, a e ha i did no ocus
on some addi ional elemen s o mobile banking like mobile applica ions s abili y, cus ome ca e suppo , and se-
cu i y which can be analyzed using o he models like UTAUT o IS sys em.
O iginali y/ alue: The pape p esen s he pa onage and usage o mobile banking in ecen imes a e he pandemic
and ea lie demone iza ion in India. The analysis using he TAM model helped o check he cu en end and
use s' mind-se shi .
Keywo ds: Mobile banking, Pe cei ed use ulness, Pe cei ed ease o use, TAM, Sma PLS
ⓒ
Copy igh : The Au ho (s). This is an Open Access jou nal dis ibu ed unde he e ms o he C ea i e Commons A ibu ion
Non-Comme cial License (h ps://c ea i ecommons.o g/licenses/by-nc/4.0/) which pe mi s un es ic ed non-comme cial use, dis ibu ion
,
and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed.
GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 2 (MARCH 2024), 47-56
48
inge p in s, and pos ansac ion e-con i ma ion (as
s a ed by Ai el paymen bank) ha e gi en mo e
boos and con idence in mobile banking secu i y.
Recen ly, banks and paymen p o ide s changed he
one- ime passwo d om 4 digi s o 6 digi s o imp o e
secu i y measu es. Please no e ha 4-digi OTP is
hackable a he chance o 1 in 10,000, while he
6-digi OTP is hackable a he p obabili y o 1 in
1,000,000.
II. Analysis o P io Wo k
A S udy o Mobile Banking in he S a e o Ke ala
by Roshna Thomas e al., 2019, ocus on mobile
banking awa eness and as al e a i e o ATM, cheque,
he au ho analyze he bank isi s and ocus on basic
mobile banking expec a ions like ime sa ing,
accessibili y, mobili y e c along wi h demog aphics
a iables and on echnology accep ance on he whole.
The au ho s used nonpa ame ic es like chi squa e
es o associa ion, spea man's co ela ion. Ve onika
Lee e al., 2022, in hei s udy on explain abou
impac o pandemic in online pu poses ia e-comme ce
pla o ms in Uzbekis an. The au ho uses combina ion
SERVQUAL and TAM o check he adap ed
e-comme ce ma ke in Uzbekis an. I is obse ed
om he analysis, ha some o he pa ame e s like
esponsi eness and eliabili y a e no ound signi ican
o adop ion and he pa ame e s on cus ome
sa is ac ion is simila wi h pe cei ed use ulness and
ease o use. So he ex ension o TAM wi h
SEQVQUAL is ound no be no so use ul his his
case o online pu poses. Amin, H e al., 2012 in
he s udy ocus on ac o s ha de e mine he local
ci izens o Sabahan bank cus ome s' mo i e o adop
mobile banking. This s udy ex ends he applicabili y
o he echnology accep ance model (TAM) o mobile
banking and inco po a es pe cei ed use ulness and
pe cei ed ease o use along wi h pe cei ed c edibili y,
pe cei ed enjoymen and pe cei ed sel -e icacy, The
analysis indica e ha pe cei ed c edibili y, enjoymen ,
sel -e icacy a e main go e ning ac o s o Malaysia's
bank cus ome s in en ions o use mobile banking,
The s udy esul s indica e ha he pe cei ed use ulness
and ease o use has minimum impac on mobile
banking compa ed o pe cei ed c edibili y, enjoymen
and sel -e iciency which we e much mo e impo an
pa onage aspec s o mobile banking use. The
analysis migh indica e pa icula egion people's
mindse o due o low sample size. Zamil, 2011,
analyse he e ec o deploymen o mobile banking
om ma ke ing iewpoin in Jo dan aking su ey
om bank mange s poin o iew. Da a analysis is
done ia SPSS and analysis o a iance (ANOVA) is
used. The esul s p o e a s ong s a is ical signi icance
exis in implemen a ion o mobile banking adop ion
om ma king iewpoin by bank manage s in Jo dan
owing o ollowing ac o s: gende , age, quali ica ion
and loca ion o bank manage s. Fu he checking on
simila esea ch using TAM model, Huang, Y, 2013
used enhanced TAM model o s udy on sma phone
usage. The au ho used ex e nal ac o s like enjoymen ,
social in luence along wi h pe cei ed use ulness, and
pe cei ed con enience (simila o pe cei ed ease o
use) o check cus ome s' accep ance o sma phones.
His analysis shows ha enjoymen and social
in luence as ex e nal ac o s had impac pe cei ed
use ulness and pe cei ed con enience. In e es ingly
his analysis pe cei ed use ulness has no di ec and
posi i e ela ionship wi h in en ion o use which may
be due he beha io o a ge su ey esponden who
we e unde g adua e s uden s om Ko ea wi h majo
as business adminis a ion. Koenig-Lewis N. e al.,
2010 in hei a icle on p edic ing young consume s'
use o mobile banking se ices ied combing TAM
and IDT a iables o pe cei ed use ulness, pe cei ed
ease o use, in en ion o use, along wi h compa ibili y,
pe cei ed us , c edibili y and pe cei ed cos . Bu
he esul s show no signi ican impac o pe cei ed
cos , c edibili y, and pe cei ed us on in en ion o
use and only compa ibili y has signi ican impac
hus indica ing ha his ex ension o TAM model
is no b inging much bene i in he heo e ical model.
M. Aboelmaged and T. R. Gebba in hei pape on
mobile banking, ied in eg a ing Technology
A hi MC, Vini ha K
49
Accep ance Model (TAM) and Theo y o Planned
Beha iou (TPB). Along wi h pe cei ed use ulness,
ease o use, subjec i e no m and beha iou con ol
pa ame e s we e in oduced and esul s indica e ha
only subjec i e no m (how you iends ci cle hink
abou you mobile banking usage) has impac in
adop ion. Fu he he s udy indica e, pe cei ed
use ulness impac bo h adop ion and a i ude owa ds
usage and pe cei ed ease o use has impac on
pe cei ed use ulness al hough no di ec ly impac ing
a i ude owa ds usage o adop ion. I may be no ed
ha sample size is lowe in his case (abou 110
esponden s).
Al hough he e a e many s udies which uses TAM,
Ex ended TAM o combina ion o TAM wi h o he
models o mobile o in e ne banking adop ion o
usage, hese a icles ha ocusses on mobile banking
adop ion a e pandemic o sou h o India in pa icula
egion o Chennai which is Sou h India's mos ad anced
echnology dis ic was minimal. This s udy ies o
add ess his gap using he Technology Accep ance
Model o check mobile banking accep ance by
cus ome s om G ea e Chennai and u he insigh
in o cus ome isi s o banks and cheque book usage.
The objec i e o his a icle is o check and analyze
he beha io and pe cep ion o he consume s in
G ea e Chennai a ea in Sou h India on mobile
banking in ecen imes wi h he changes in he
mind-se o he people a e he pandemic and ea lie
demone iza ion. The aim is o unde s and he
pe cei ed ease o use and pe cei ed use ulness o
mobile banking and o unde s and i s e ec wi h
in en ion o use along wi h he slow sunse o
adi ional banking aids seen by consume s like
cheque book and passbooks using he use s' esponses.
Addi ionally, he pa e n o usage ac oss age g oups
is p esen ed o unde s and he usage pa e n among
a ious age g oups.
To summa ize, he s udy mainly ocuses on he
ollowing esea ch ques ions in e ms o impac
among use s in G ea e Chennai
1. How use s o mobile banking pe cei e i s
use ulness and ease o use and i s ela ion o
in en ion o use and ac ual usage?
2. Wha is he collec i e use beha io on gene al
mobile usage conside ing use ulness and ease
o use?
3. Is he e any subs an ial end o usage o mobile
banking in India age-wise be o e and a e
COVID-19 and i s dis up i eness o adi ional
banking me hods?
To add ess he esea ch ques ions one and wo
ollowing hypo hesis a e p oposed.
H1:
Pe cei ed Ease o use has impac in pe cei ed
use ulness o use mobile banking
H2:
Pe cei ed Use ulness has impac in en ion o
use mobile banking
H3:
Pe cei ed Ease o use has impac in en ion
o use mobile banking
H4:
In en ion o use mobile banking has impac
in ac ual usage o mobile banking
To add ess he esea ch ques ion h ee, da a ela ed
o mobile banking usage end and analysis ep esen ed
as cha is p o ided ( e e Figu e 2).
III. Li e a u e Re iew
A. Ad ances in Digi al Paymen s and Mobile
Banking
On he e olu ion o paymen s, Roge W. H. Bons
e al., 2012 in his pape explain ha banking unc ions
ha e e ol ed on a la ge scale wi h he shi om
physical o elec onic paymen s, eplacing sa ings
books, deposi ce i ica es wi h online se ices and
digi al al e na i es. Luigi Wewege, 2020, men ions
in his a icle ha in he banks, he oo all is d opping
by app oxima ely ou isi s pe yea , and he e is
an expec a ion ha mobile ansac ions will ise o
121% in he 2017-2022 pe iod. The e is also an
expec a ion ha in he nex i e yea s, bank ansac ions
on lap ops/desk op de ices will also d op o a
signi ican ex en , and 88% o he in e ac ions and
mobile de ices will d i e he ansac ions. Seung-
GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 2 (MARCH 2024), 47-56
50
Bum Haa e al., 2021 alk abou making mobile
paymen s ewa ding, he banks should conside
p o iding incen i es on usage simila o c edi ca ds
o make he consume s become epea use s and o e
discoun s and coupons which wo ked well o c edi
ca ds. Also, ewa d poin s o pu chases migh be
use ul o make m-paymen s a ac i e and enjoyable.
Asongu, Simplice and Nwachukwu, Jacin a C., 2016
in hei a icle, alk abou 4 changes mobile phones
b ough in he banking a ea: Fi s cell phones a e
used like a i ual c edi ca d. I uses PIN and bank
accoun numbe which is sa ed in he SIM ca d o
use i in he same way as he bank's i ual ca d.
Secondly, he phone is used as poin o sale (POS)
e minal. They gi e simila paymen unc ions like
in e ail s o es o ou le s. Thi dly, he mobile phone
can wo k like an au oma ic elle machine (ATM).
Fou hly mobile used as i ual bank o making
paymen s and ans e s.
B. Impac o Pandemic in Online Paymen s
As pe S ephanie Walden, and Daphne Fo eman,
2020, e en a e he pandemic, he end o g ow h
in mobile banking and paymen is e y likely o
s ay due o cus ome changed beha io . A he s a
o he pandemic, some banks upg aded cus ome s'
physical c edi and debi ca ds o include " ap o
pay" echnology. Acco ding o Yuyang Zhao and
Fe nando Bacao, 2021, mobile paymen ansac ions
du ing he pandemic e icien ly suppo he su i al
o a ious businesses and main ain he social
economy's de elopmen unde an eme gency. Rega ding
mobile banking du ing COVID-19, Nilu a Kha un
e al., 2021 say mobile banking is ex ensi ely used
by all ci izens du ing COVID-19 as i gi es hem
inancial access sa ely and easily. A hi M.C., and
Shanmugam K., 2020, in hei pape , say, ha he
economic up ising o going away om cash and
mo ing o digi al ansac ions has begun in India
o he p e ious ew yea s, and due o he pandemic
condi ion in India, he e has been an inc eased need
o go wi h con ac less ansac ions. Ellen Schindle ,
2021, explains in he las yea o he COVID-19 pe iod,
we see mo e applica ions booming wi h inno a i e
mobile solu ions by Banks and Paymen se ice
p o ide s. Examples a e emo e connec i i y ia li e
cha and secu e messaging. Ve onika Lee e al., 2022,
in hei s udy on explain abou impac o pandemic
in online pu poses ia e-comme ce pla o ms in
Uzbekis an. They ound ha 68% o people ag eed ha
hei pu chases in online e-comme ce si es inc eased
ma kedly om 2018 o 2020 and he esponden s
(abou 74%) a e eage o con inue o pu chase o goods
ia e-comme ce pla o ms e en a e COVID-19.
C. Theo e ical Backg ound and F amewo k
The popula models ha can be used o mobile
banking adop ion a e mainly TAM, Ex ended TAM
o called as TAM 2, Inno a ion Di usion Theo y
(IDT), and he uni ied heo y o accep ance and use
o echnology (UTAUT), and a ew combina ions
o hese models.
The TAM model was i s in oduced by F ed
Da is in 1986. Mobile banking adop ion and usage
can be well modeled by TAM. Acco ding o F ed
Da is e al. in 1986, he echnology accep ance model
(TAM) is an in o ma ion sys ems heo y ha models
how use s come o accep and use echnology. F ed
Da ies, 1986 s a ed ha use s' mo i a ion can be
explained by h ee ac o s: Pe cei ed Use ulness
(PU), Pe cei ed Ease o Use (PEU), and A i ude
owa d using he sys em. PE is he deg ee o which
a use belie es ha using a pa icula sys em will
imp o e his day oday wo k pe o mance and de ined
PEU as he deg ee o which a pe son belie es ha
usage a speci ic sys em would be ee his men al
and physical e o ( e e Figu e 1).
Ex ended TAM de eloped by Venka esh and
Da is, 2000 explained PU and usage in en ions by
social in luence and pe cep i e ins umen al p ocesses
along wi h PEU. The cons uc s link social in luence s
(like olun a iness, image, and subjec i e no m) and
pe cep i e ins umen al p ocesses (like quali y, es
demons abili y, job ele ance, and PEU). IDT concep
A hi MC, Vini ha K
51
was p omo ed by E e e Roge s who classi ies
Di usion o Inno a ions in o i e ea u es o inno a ion:
complexi y, compa ibili y, iabili y, obse abili y,
and ela i e ad an age (Roge s, E e e 2003). The
uni ied heo y o accep ance and use o echnology
(UTAUT) is a echnology accep ance model ha aims
o ind he cus ome 's pu pose in using an in o ma ion
sys em and ollow usage beha io . De eloped by
Venka esh, Mo is, Da is, G. B., & Da is, F. D.
(2003) he model con ains ou key in en ion heo ies;
social in luence (SI), e o expec ancy (EE), pe o mance
expec ancy (PE), and acili a ing condi ions (FC).
The e a e also ou mode a o s: age, gende , expe ience,
and olun a iness o use. The mos popula model
o s udy new echnology accep ance is TAM which
is used in his a icle o explain mobile banking
adop ion and usage.
IV. Me hodology
The s udy is conduc ed o ob ain da a on adop ing
a digi al paymen sys em in India and has been done
ac oss ci izens o G ea e Chennai, India who a e
mobile banking use s. Online su ey mode was
adop ed, and 300 esponses we e ecei ed. Responses
ela ed o opics on isi s o banks, chequebook usage,
and end o mobile banking usage we e collec ed
along wi h demog aphic- ela ed ques ions. Responses
ela ed o pe cei ed use ulness, ease o use, in en ion
o use, and ac ual usage we e also collec ed on a
Like 's Scale o 1 o 5 anging om s ongly disag ee,
o disag ee, neu al, ag ee, and s ongly ag ee.
The mobile banking use s we e he in ended
esponden s and co e ed all age g oups, bo h gende s
and income g oups. The ques ionnai e is p o ided
o esponden s ia Google Fo ms, and he link is
sen ia email and social media pla o m, Wha sApp.
Da a analysis is done using cha s and he Sma PLS
model o s uc u al equa ion (SEM) modeling.
V. Ou comes
A. Consume s Visi o Banks
A e he in oduc ion o mobile banking, coupled
wi h echnological ad ancemen and a o dable
sma phones we see only 17% o use s go o banks
equen ly, i.e., mo e han one ime a mon h.
Occasional isi o s isi once o wice in a qua e
mainly o loans, locke usage, o o he pe sonal
se ices om banks ( e e Table 1).
B. Chequebook Usage
Consume s' chequebook usage end compa ed o
online ans e s analysis show he mindse o he
use s. In addi ion, he banks discou age cheque usage
by inc easing clea ance ime, and mul iple au ho i-
za ions. Ano he ad an age o mobile banking is;
checking balance in he accoun s any ime wi h ease.
This educes o e d a issues and he bouncing o
cheques ( e e Table 2).
Responses Dis ibu ion
F equen Visi s o Bank 17%
Occasional Visi s o Bank 45%
Seldom Visi Bank 38%
Table 1. T end o cus ome isi s o banks
Responses on Chequebook usage Dis ibu ion
Used g ea e han 1 ime pe mon h 12%
Ra ely Used 45%
Ne e used 43%
Table 2. Chequebook usage
Pe cei ed
Use ulness
Pe cei ed
Ease o Use
In en ion
o use Ac ual use
Figu e 1. TAM model
GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 2 (MARCH 2024), 47-56
52
C. Mobile Paymen Usage a e COVID-19
based on Use Su ey
In his pa , we asked esponden s abou he usage
pa e n o mobile paymen s a e COVID-19. The
below cha shows he de ails. The e is a su ge in
usage among he olde gene a ions (>60 yea s o
age), and hey quickly mo ed o mobile banking
han expec ed ( e e Figu e 2).
D. Sma PLS Ou pu and Model analysis
The su ey ou pu was modelled using TAM and
cons uc ed using Sma PLS ( e e Figu e 3).
Fac o loading:
Explains he ela ionship be ween
ac o s and a iables, many ac o s show a s ong
co ela ion (whe e loading is >0.7) and ew
ac o s show mode a e co- ela ion (whe e loading
is >0.5 <0.7) - e e Table 3.
Figu e 2. Age-wise change in end o mobile paymen s a e COVID-19
Figu e 3. Sma PLS ou pu
A hi MC, Vini ha K
53
Model i ness:
S anda dized Roo Mean Residual
(SRMR): SRMR is he di e ence be ween he
obse ed co ela ion and he model-implied
co ela ion. I gi e he a e age amoun o he
di e ences be ween obse ed and expec ed
co ela ions as an absolu e measu e o model
i c i e ion. SRMR <0.08 indica es he model
is i ( e e Table 4).
No med Fi Index (NFI):
I calcula es he Chi-
squa e alue o he p oposed model and
compa es i agains a meaning ul benchma k.
NFI >0.8 indica es a good i ( e e Table 4).
R Squa e:
R squa e alue >0.8 indica es a s ong
ela ionship be ween dependen a iables and
independen a iables. I is he coe icien o
de e mina ion and shows he pe cen age o he
a iance o he dependen a iable explained
by he independen a iables ( e e Table 4).
Cons uc Reliabili y and Validi y:
Reliabili y and
alidi y a e used o check how well a me hod,
o a echnique measu es he collec ed da a.
Reliabili y is abou he s abili y o a measu e
and alidi y is abou he co ec ness o a
measu e. C onbach's Alpha and ho_A h eshold
is g ea e han 0.7 o all he a iables indica ing
high eliabili y and alidi y ( e e Table 5).
Collinea i y S a is ics (VIF):
Collinea i y indica es
independen a iables' co ela ion in he s udy.
In ou analysis, he Va iance In la ion Fac o
(VIF) which gi es indica ion o collinea i y was
less han 4 o all he dimensions s udied in he
esea ch, indica ing ha he e is no collinea i y
p oblem among he s udy dimensions ( e e
Table 5).
Pa h Coe icien (T S a is ics & P Values):
The
pa h analysis in SEM is he pa ial co ela ion
coe icien among he dependen a iable and
an independen a iable, co ec ed o o he
independen a iables. The - alue > 1.96 and
p- alue < 0.05 o all he ela ionships indica e
a signi ican co ela ion ( e e Table 6) and
indica ing he hypo heses H1 o H4 a e accep ed
and he in luence is signi ican .
E. Analysis Findings
The Sma PLS analysis o he da a indica es ha
he e is a s ong ela ionship be ween pe cei ed ease
o use and use ulness and i s associa ion wi h in en ion
o use and ac ual usage (Hypo hesis H1 o H4).
Pe cei ed use ulness and ease o use in luence
Sa u a ed
model
Es ima ed
model
SRMR 0.035 0.084
d_ULS 0.289 1.644
d_G 0.281 0.32
Chi-squa e 497.24 547.673
NFI 0.926 0.919
R-squa e R-squa e
adjus ed
Ac ual Usage 0.597 0.596
In en ion o use 0.837 0.833
Pe cei ed Use ulness 0.701 0.7
Table 4. Model i , NFI and R Squa e
Fac o Va iable Loading
ACU1
Ac ual Usage
0.954
ACU2 0.902
ACU3 0.927
BIQ1
In en ion o Use
0.955
BIQ2 0.893
BIQ3 0.955
PEU1
Pe cei ed
Ease o Usage
0.877
PEU2 0.765
PEU3 0.901
PEU4 0.9
PEU5 0.883
PEU6 0.849
PU1
Pe cei ed
Use ulness
0.87
PU2 0.861
PU4 0.882
PU5 0.896
PU6 0.893
PU7 0.878
PU8 0.911
Table 3. Fac o loading
GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 2 (MARCH 2024), 47-56
54
in en ion o use which in u n, makes use s use mobile
banking applica ions. The model analysis was u he
con i med wi h esponses seen on o he ques ions
ela ed o ewe isi s o he bank, use o chequebook,
and he end o mobile banking usage age-wise be o e
and a e he Pandemic.
VI. Conclusion
A. Implica ions
The a icle co e s bo h pe spec i es o heo y and
p ac ice. F om a heo e ical pe spec i e, he indings
will con ibu e o exis ing li e a u e p o iding insigh s
o mobile banking usage om echnology ad anced
popula ion like Sou h India, Chennai whe e a e
pandemic we see a shi in usage by age g oup. The
model analysis exhibi s ha , he accep ance o mobile
banking by use s and he usage is d i en by pe cei ed
ease o use and use ulness. Fi s , he mobile banking
ad an ages seen by use s especially in e ms o ease
o use and use ulness due o mobile applica ions
becoming mo e use - iendly and uncomplica ed o
all gene a ions. The change in mind se o people
a e he pandemic is a d i ing ac o . Secondly, he
signi icance o TAM model i men o echnology
ad ancemen s on banking sec o i.e. mobile banking
is e iden . Thi dly, he quali a i e analysis on o he
impo an aspec s ha p omo es mobile banking and
wha we e he ocus a eas o add ess gi es mo e
insigh s in cus ome adop ion heo y. Fou h he s udy
endo ses ha he echnology accep ance li e a u e
by implying ha pe cei ed use ulness and ease o
use impac on any new echnology accep ance.
F om p ac ical implica ions pe spec i e, he
signi ican impac o pe cei ed use ulness and ease
o use clea ly indica es ha he mo e use iendly
he mobile banking applica ions, he mo e he
adop ion and con inued usage. The inc ease in banks'
mobile applica ions usage a e pandemic ac oss age
g oups is an indica ion ha shows he popula i y
and ease o use o mobile paymen s and he need
o ocus on 60 plus age g oup. The banking sec o
had come a long way mo ing away om cheque
book and pe sonal isi s o banks o digi al paymen s,
mobile and online banking and ound he clock se ice.
O iginal sample
(O)
Sample mean
(M)
S anda d
de ia ion
(STDEV)
T s a is ics
(|O/STDEV|) P alues
Pe cei ed Ease o Use
->Pe cei ed Use ulness 0.837 0.837 0.035 24.256 0
Pe cei ed Ease o Use ->
In en ion o use 0.393 0.393 0.103 3.819 0
Pe cei ed Use ulness ->
In en ion o use 0.21 0.208 0.106 1.983 0.047
In en ion o use ->
Ac ual Usage 0.773 0.772 0.058 13.396 0
Table 6. Pa h coe icien ou pu
Va iable C onbach's alpha Composi e
eliabili y ( ho_a)
Composi e
eliabili y ( ho_c)
A e age a iance
ex ac ed (AVE)
Ac ual Usage 0.92 0.925 0.949 0.861
In en ion o use 0.927 0.936 0.954 0.873
Pe cei ed Use ulness 0.931 0.935 0.946 0.746
Pe cei ed Use ulness 0.962 0.963 0.968 0.768
Table 5. Reliabili y,
alidi y and Collinea i y analysis using
V
IF
