Susan o, He u e al.
A icle
Demys i ica ion o eadiness, secu i y, and echnological
enhancemen s in he adop ion o a cashless economy
Economies
P o ided in Coope a ion wi h:
MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Susan o, He u e al. (2024) : Demys i ica ion o eadiness, secu i y, and
echnological enhancemen s in he adop ion o a cashless economy, Economies, ISSN 2227-7099,
MDPI, Basel, Vol. 12, Iss. 11, pp. 1-35,
h ps://doi.o g/10.3390/economies12110285
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/329212
S anda d-Nu zungsbedingungen:
Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen
Zwecken und zum P i a geb auch gespeiche und kopie we den.
Sie dü en die Dokumen e nich ü ö en liche ode komme zielle
Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich
machen, e eiben ode ande wei ig nu zen.
So e n die Ve asse die Dokumen e un e Open-Con en -Lizenzen
(insbesonde e CC-Lizenzen) zu Ve ügung ges ell haben soll en,
gel en abweichend on diesen Nu zungsbedingungen die in de do
genann en Lizenz gewäh en Nu zungs ech e.
Te ms o use:
Documen s in EconS o may be sa ed and copied o you pe sonal
and schola ly pu poses.
You a e no o copy documen s o public o comme cial pu poses, o
exhibi he documen s publicly, o make hem publicly a ailable on he
in e ne , o o dis ibu e o o he wise use he documen s in public.
I he documen s ha e been made a ailable unde an Open Con en
Licence (especially C ea i e Commons Licences), you may exe cise
u he usage igh s as speci ied in he indica ed licence.
h ps://c ea i ecommons.o g/licenses/by/4.0/
Ci a ion: Susan o, He u, Noo
Tam ini, Fahmi Ib ahim, Ali ya Kayla
Sha a Susan o, Desi Se iana, and Leu
Fang Yie. 2024. Demys i ica ion o
Readiness, Secu i y, and Technological
Enhancemen s in he Adop ion o a
Cashless Economy. Economies 12: 285.
h ps://doi.o g/10.3390/
economies12110285
Academic Edi o : Weixin Yang
Recei ed: 21 June 2024
Re ised: 16 Augus 2024
Accep ed: 22 Augus 2024
Published: 24 Oc obe 2024
Copy igh : © 2024 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
economies
A icle
Demys i ica ion o Readiness, Secu i y, and Technological
Enhancemen s in he Adop ion o a Cashless Economy
He u Susan o 1,2,3 , Noo Tam ini 1,2,*, Fahmi Ib ahim 1, Ali ya Kayla Sha a Susan o 2,4, Desi Se iana 5,6
and Leu Fang Yie 2,3
1School o Business, Uni e si y Technology B unei, Banda Se i Begawan BE1410, B unei;
[email p o ec ed] o [email p o ec ed] (H.S.)
2Cen e o In e na ional Resea ch Collabo a ion o G aph Theo y and Combina o y, Membe s:
BRIN (Na ional Resea ch and Inno a ion Agency), Jaka a Pusa 10340, Indonesia; UTB (Uni e si y o
Technology B unei), Jalan Tungku Link Gadong BE1410, B unei; ITB (Ins i u e o Technology Bandung),
Bandung 40132, Indonesia; UI (Uni e si y o Indonesia), Depok 16424, Indonesia; THU (Tunghai Uni e si y),
Taichung 40704, Taiwan; IOU (In e na ional Open Uni e si y), Jaka a 12780, Indonesia;
[email p o ec ed] (A.K.S.S.); [email p o ec ed] (L.F.Y.)
3Cen e o A i icial In elligen and Cybe Secu i y, Na ional Resea ch and Inno a ion Agency,
Bandung 40135, Indonesia
4School o Compu ing and In o ma ics, Uni e si y Technology B unei, Banda Se i Begawan BE1410, B unei
5Digi al Psychology Resea ch G oup, Ins i u e o B unei S udies, Uni e si y B unei Da ussalam,
Banda Se i Begawan BE1410, B unei
6The Sou he n Co ec ional Cen e , BAPAS Jaka a Sela an, Minis y o Law and Human Righ s,
Jaka a 12940, Indonesia
*Co espondence: noo [email p o ec ed]
Abs ac : The adop ion o a cashless economy was accele a ed globally by he de as a ing impac o
he COVID-19 pandemic. B unei Da ussalam was no excluded om his end, as pandemic- ela ed
es ic ions we e implemen ed o ensu e he sa e y o i s popula ion. In ligh o he
COVID-19
c isis,
his esea ch pape examines he ac o s in luencing he eadiness and accep ance o a cashless
economy among wo king socie y in B unei Da ussalam. The in eg a ed concep s o he Technology
Accep ance Model (TAM) and Technology Readiness Index (TRI) a e applied o examine pe cep ions
impac ing hei accep ance and eadiness o con inue adop ing a cashless economy. The me hodology
includes a li e a u e e iew and he use o seconda y da a om go e nmen epo s and indus y pub-
lica ions. A quan i a i e app oach is employed, u ilizing an online su ey o collec non-p obabili y
samples om 212 esponden s. The main ins umen s used in he su ey a e s uc u ed ques ionnai es.
The s udy’s indings show ha ac o s such as he assessmen o paymen modes, echnological de-
elopmen , digi al li e acy, knowledge, egula o y policies, and secu i y conce ns signi ican ly a ec
wo king socie y’s pe cep ions, eadiness, and accep ance o a cashless economy. These esul s p o ide
insigh s o policymake s and s akeholde s on he key ac o s in luencing con inued cashlessness
adop ion and shaping socie al beha io owa ds cashless paymen s.
Keywo ds: adop ion; cashless paymen s; pe cep ions; echnology eadiness index; echnology
accep ance model; COVID-19 pandemic; wo king socie y; cashless economy
1. In oduc ion
A cashless economy e e s o an economic sys em whe e ansac ions a e p ima ily
conduc ed using ca ds, digi al paymen me hods, and o he non-physical o ms o money,
mo ing away om cash as he main mode o paymen . This concep has gained signi ican
global ac ion and has been widely an icipa ed by economic expe s as mone a y and pay-
men sys ems ha e e ol ed o e he yea s (S ouji 2020). Wi h echnological ad ancemen s
apidly ans o ming he inancial indus y, banking s uc u es and p ac ices ha e shi ed
Economies 2024,12, 285. h ps://doi.o g/10.3390/economies12110285 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 285 2 o 35
om adi ional cash-based ansac ions o mode n cashless banking, including digi al
banking se ices and ca d paymen s.
In he con ex o B unei, he Digi al Economy Mas e plan 2025 ou lines s a egies o
ans o m he na ion in o a Sma Na ion, as en isioned unde Wawasan B unei 2035. A key
componen o his ans o ma ion is he adop ion o digi al banking and paymen sys ems.
In line wi h B unei’s Sma Na ion ision, digi al ans o ma ion in he banking sec o was
ully implemen ed by 2019 (Digi al Economy Council 2020). A obus digi al ecosys em
is a key enable o a cashless economy, equi ing he ac i e pa icipa ion o s akeholde s,
including go e nmen bodies, inancial ins i u ions, and businesses. These s akeholde s
mus play a pi o al ole in c ea ing awa eness, p omo ing digi al paymen me hods, and
ensu ing he secu i y o digi al ansac ions.
The success o a cashless economy is also hea ily dependen on he socie al adop ion o
digi al paymen s. While he e m “cashless economy” does no imply he comple e elimina-
ion o cash, i highligh s a shi owa ds non-cash ansac ions. Fo ce ain in o mal sec o s,
cash emains a c i ical o m o paymen , especially when in e ac ing wi h o mal sec o s
(S ouji 2020). This dynamic is one o he key a eas o explo e when assessing socie y’s
eadiness and willingness o emb ace cashless ansac ions as a p ima y paymen me hod.
The public pe cep ion o a cashless economy is a c ucial ac o in i s accep ance.
A i udes and pe cep ions a e o en shaped by he le el o knowledge and unde s anding
people ha e on he subjec . S udies ha e shown ha indi iduals wi h highe le els o digi al
li e acy and awa eness a e mo e likely o adop and con inue using cashless paymen s
(A i u ha e al. 2020). In B unei, he COVID-19 pandemic accele a ed he adop ion o digi al
paymen s due o he necessi y o con enience and compliance wi h social dis ancing
measu es. Howe e , as he coun y mo es in o he endemic phase, changes in a i udes
owa ds cashless paymen s may occu , making i essen ial o s udy he ac o s ha in luence
con inued accep ance and he in en ion o use hese paymen me hods.
S akeholde s in he digi al ecosys em play a c ucial ole in he ongoing adop ion o
cashless paymen s. While his s udy ocuses on indi idual esponden s, hei esponses
will e lec he ac ions and measu es aken by hese s akeholde s in p o iding, ma ke ing,
and main aining cashless paymen sys ems. Fo example, he secu i y o digi al paymen s
is a key ac o in luencing use con idence. Ensu ing obus p o ec ion agains ca d aud
and digi al scams will boos he con idence o cashless paymen use s. In addi ion o
egula ly upda ing pla o ms wi h necessa y secu i y measu es, s akeholde s mus also
aise awa eness abou how o sa ely pe o m digi al ansac ions, which u he enhances
use con idence (Ansha i e al. 2021).
This is closely linked o digi al li e acy and compe ency. S udies ha e shown ha
digi al li e acy is a c i ical ac o in he adop ion o cashless paymen s, as i di ec ly in lu-
ences use accep ance and eadiness (Salman and Saleem 2017). People wi h lowe le els o
digi al li e acy a e gene ally mo e hesi an o emb ace and use cashless paymen s compa ed
o hose wi h highe le els o knowledge. This issue will be add essed in mo e de ail in
he s udy.
The p ima y goal o his esea ch is o assess he le el o accep ance and eadiness
among B unei’s wo king popula ion and income ea ne s in he wake o he COVID-19
pandemic, as well as o iden i y he key ac o s ha in luence he con inued adop ion o a
cashless economy in he coun y. The ollowing objec i es a e ou lined o achie e his goal:
•
To in es iga e he pe cep ions o B unei’s wo king popula ion ega ding he ansi ion
o a ully cashless economy.
•
To de e mine he ac o s ha in luence he accep ance o a cashless economy among
B unei’s wo king socie y.
•
To explo e he ela ionship be ween accep ance and eadiness o cashless paymen s
among income ea ne s.
Economies 2024,12, 285 3 o 35
In suppo o hese esea ch objec i es, he s udy will p opose a amewo k o ad anc-
ing he cashless economy based on he eadiness and accep ance o B unei’s wo king socie y.
This amewo k will o e ecommenda ions o help acili a e he con inued adop ion o
cashless paymen s in B unei Da ussalam.
The indings om his s udy a e expec ed o p o ide aluable insigh s in o he ela-
ionship be ween accep ance and eadiness o cashless paymen s ollowing he COVID-19
c isis, as well as add ess he ac o s in luencing hei con inued use. These insigh s will
bene i cashless paymen use s by o e ing a deepe unde s anding o i s po en ial impac s,
enabling hem o make in o med decisions when adop ing digi al paymen me hods.
Addi ionally, he esul s will assis s akeholde s—such as go e nmen bodies, he
banking indus y, and businesses—in de e mining he ex en o measu es needed o os e
con inued adop ion o cashless paymen s. By in luencing socie al beha io , hese s akehold-
e s can help shape a mo e cashless socie y. The indings will also guide he de elopmen o
ac ion plans o suppo B unei’s digi al economy s a egies, u he accele a ing he g ow h
o he cashless economy and con ibu ing o he ealiza ion o he Sma Na ion ini ia i e
unde Wawasan B unei 2035.
A cashless economy e e s o an economic sys em whe e ansac ions a e p ima ily
conduc ed using ca ds, digi al paymen me hods, and o he non-physical o ms o money.
This concep has gained signi ican popula i y wo ldwide, wi h expe s p edic ing i s
con inued g ow h alongside ad ancemen s in mone a y and paymen sys ems (S ouji 2020).
Technological expansion in he inancial sec o has apidly ans o med banking s uc u es,
shi ing om adi ional, cash-based ansac ions o mode n cashless se ices, including
ca d paymen s and digi al banking.
In B unei Da ussalam, he Digi al Economy Mas e plan 2025 ou lines s a egies o
ans o m he na ion in o a Sma Na ion as pa o Wawasan B unei 2035. A key aspec
o his ans o ma ion is he implemen a ion o digi al banking and paymen sys ems,
which was ully achie ed by 2019 (Digi al Economy Council 2020). Building a obus
digi al ecosys em is essen ial o he success o a cashless economy, wi h s akeholde s
such as go e nmen agencies, inancial ins i u ions, and businesses playing pi o al oles in
expanding and s eng hening his ecosys em. This in ol es c ea ing awa eness, p omo ing
digi al paymen op ions, and ensu ing he secu i y o digi al ansac ions.
The COVID-19 pandemic signi ican ly accele a ed he adop ion o cashless paymen s
globally, including in B unei, whe e public sa e y es ic ions we e in oduced. This esea ch
aims o explo e he ac o s in luencing he eadiness and accep ance o a cashless economy
among B unei’s wo king popula ion. The s udy in eg a es he Technology Accep ance
Model (TAM) and he Technology Readiness Index (TRI) o assess he pe cep ions shaping
indi iduals’ willingness o con inue using cashless ansac ions.
The me hodology includes a li e a u e e iew and analysis o seconda y da a om
go e nmen epo s and indus y publica ions. A quan i a i e app oach is u ilized, wi h
da a collec ed ia an online su ey om a non-p obabili y sample o 212 esponden s.. The
p ima y ins umen o da a collec ion is a s uc u ed ques ionnai e.
The indings sugges ha ac o s such as he e alua ion o paymen me hods, ech-
nological ad ancemen s, digi al li e acy, egula o y policies, and secu i y conce ns signi i-
can ly in luence he pe cep ions, eadiness, and accep ance o a cashless economy among
B unei’s wo king socie y. These esul s p o ide aluable insigh s o policymake s and
s akeholde s, highligh ing he key d i e s o con inued adop ion and helping o shape
public a i udes owa d digi al ansac ions.
The main objec i e o his esea ch is o assess he le el o accep ance and eadiness
among wo king indi iduals and income ea ne s in B unei ollowing he COVID-19 pan-
demic, as well as o iden i y he ac o s impac ing he con inued g ow h o he cashless
economy. The speci ic aims a e o:
Economies 2024,12, 285 4 o 35
1.
In es iga e he pe cep ions o B unei’s wo king popula ion owa d ansi ioning o a
ully cashless economy.
2.
Iden i y he ac o s ha in luence he accep ance o a cashless economy among he
wo king socie y.
3.
Examine he ela ionship be ween accep ance and eadiness o cashless paymen s
among income ea ne s.
The indings om his s udy a e expec ed o cla i y he ela ionship be ween accep-
ance and eadiness o cashless paymen s pos -COVID-19 while add essing he con ibu -
ing ac o s in luencing hei ongoing use. These insigh s will bene i use s o cashless
paymen s by helping hem make in o med decisions based on enhanced knowledge. Fu -
he mo e, he esul s will guide s akeholde s, including go e nmen bodies, he banking
indus y, and businesses, in iden i ying necessa y ac ions o suppo con inued adop ion,
align wi h digi al economy s a egies, and ul ima ely con ibu e o he Sma Na ion ision
o Wawasan B unei 2035.
2. Li e a u e Re iew
2.1. Global Shi Towa ds Cashless Economies
A weal h o s udies wo ldwide has examined he shi owa d a cashless economy,
wi h a pa icula ocus on use eadiness and adop ion. In B unei, he mo e owa d a
cashless socie y gained signi ican momen um du ing he COVID-19 pandemic, as he need
o shi om con ac -based o con ac less ac i i ies became essen ial o daily li e.
2.2. His o ical De elopmen o Cashless Paymen Sys ems
Acco ding o Fab is (2019), cashless socie ies ha e exis ed since he ea ly days o
human ci iliza ion, when li elihoods elied on ba e and o he o ms o exchange ha
did no in ol e cu ency. Howe e , he mode n concep o a cashless socie y ep esen s a
mo e ad anced s age, whe e physical money is eplaced by digi al al e na i es, enabling
ansac ions o occu elec onically. The i s cashless paymen s eme ged in he 1950s, and
since hen, a a ie y o cashless ins umen s ha e been de eloped (Jain and Jain 2017).
Recen ends show ha cashless ansac ions a e now common no only in la ge inancial
exchanges bu also in e e yday small-scale ansac ions.
2.3. Technological Ad ancemen s
Technological ad ancemen s ha e been ins umen al in d i ing he shi owa d
cashless socie ies, wi h inno a ions in digi al paymen sys ems and mobile banking playing
a key ole. Coun ies wi h s ong e-comme ce in as uc u es and suppo i e go e nmen
policies, such as China, Sweden, and Finland, ha e led his ansi ion. In China, apid
u baniza ion and s a egic go e nmen ini ia i es ha e p opelled he widesp ead adop ion
o cashless paymen s, making he coun y a global leade in e-comme ce and digi al
paymen usage (Thomas 2013;Filipiak 2020). Sweden’s agg essi e policies ha e educed
cash ansac ions o jus 20% o all ansac ions, while Finland excels in ca d paymen
equency and In e ne banking pene a ion (Filipiak 2020).
2.4. Impac o COVID-19 on Cashless Economy
The COVID-19 pandemic had a p o ound impac on daily li e, pa icula ly in how
people made paymen s. B unei Da ussalam’s Minis y o Heal h emphasized he ease wi h
which COVID-19 could sp ead h ough physical con ac , p omp ing a shi o con ac less
me hods, including cashless paymen s (Abdul-Halim e al. 2022). Globally, mo emen
es ic ions and sa e y conce ns accele a ed he adop ion o cashless ansac ions. The
G20 I alian P esidency (2021) no ed ha he po en ial o cashless paymen s o enhance
inancial inclusion became mo e appa en du ing he pandemic as go e nmen s p omo ed
digi al paymen s o p o ec ulne able popula ions. Howe e , Ko kowski and Polasik
(2021) cau ioned ha his shi migh exace ba e inancial inclusion challenges, as p e-
pandemic cashless use s con inued wi h digi al paymen s while o he s s ill elied on cash.
Economies 2024,12, 285 5 o 35
Wisniewski e al. (2021) sugges ed ha he pandemic eshaped paymen habi s, as ea and
app ehension abou handling physical cash led many o adop cashless me hods, a end
likely o pe sis e en a e he pandemic.
2.5. Theo e ical Founda ions on he Con inued Use o Cashless Paymen s
Many s udies u ilize he Technology Accep ance Model (TAM) o unde s and use s’
in en ions o adop new echnology. TAM, de i ed om he Theo y o Reasoned Ac ion
(TRA), e alua es Technology Accep ance based on wo key ac o s: Pe cei ed Use ulness
(PU) and Pe cei ed Ease o Use (PEOU) (Da is 1989). Rou ay e al. (2019) highligh ed
he impo ance o hese ac o s and ex ended TAM by inco po a ing addi ional elemen s
such as in o ma ion quali y, sys em quali y, and se ice quali y. Ahuja and Joshi (2018)
iden i ied Ease o Use, Bene i s, T us , and Sel -E icacy as key ac o s in luencing cus ome
pe cep ions o e-walle s, hough hey acknowledged limi a ions in hei s udy due o a small
sample size. Simila ly, Maqableh e al. (2015) ound ha pe cei ed us —encompassing
epu a ion, secu i y, p i acy, and ansac ion size—plays a signi ican ole in he adop ion
o cashless paymen s.
The Technology Readiness Index (TRI) assesses use s’ eadiness o adop new echnolo-
gies. Mick and Fou nie (1998) no ed ha use s o en expe ience bo h posi i e and nega i e
emo ions when engaging wi h new echnologies. Pa asu aman (2000) u he a gued
ha he in ensi y o hese emo ions a ies among indi iduals, e lec ing hei openness
o emb acing inno a ions. Humbani and Wiese (2018) applied TRI o examine consume
eadiness o mobile paymen se ices, iden i ying bo h d i e s and ba ie s o adop ion.
Ka im and Muhammad (2022) ound ha Technology Readiness, Expec a ion Con i ma ion,
Use Sa is ac ion, and Pe cei ed Secu i y a e c i ical ac o s in luencing he con inued use
o cashless paymen s.
2.6. Theo e ical F amewo k
Da is (1989) de eloped he Technology Accep ance Model (TAM) o analyze use be-
ha io and p edic echnology adop ion. TAM ocuses on use s’ pe cep ions, emphasizing
ha a echnology’s Pe cei ed Use ulness and Ease o Use a e key ac o s in luencing i s
accep ance. Pa asu aman (2000) in oduced he concep o Technology Readiness, which
e e s o an indi idual’s willingness o adop and use new echnologies. The Technology
Readiness Index (TRI) assesses his eadiness by e alua ing ou dimensions: Op imism,
Inno a i eness, Discom o , and Insecu i y.
•
Op imism: a posi i e belie ha echnology o e s inc eased con ol, e iciency,
and lexibili y.
•Inno a i eness: a endency o be a echnology pionee and hough leade .
•
Discom o : a pe cei ed lack o con ol o e echnology and eeling o e whelmed
by i .
•Insecu i y: a dis us o echnology and skep icism abou i s abili y o wo k p ope ly.
2.7. Cu en T ends and Fu u e Di ec ions
Cu en ends e eal a signi ican ise in cashless ansac ions, d i en by echnological
ad ancemen s and shi ing consume beha io s, pa icula ly in he wake o COVID-19.
Fu u e esea ch should in es iga e he long- e m sus ainabili y o hese ends, he impac
o eme ging echnologies like blockchain and c yp ocu encies, and he ole o go e nmen
policies in os e ing inancial inclusion h ough cashless sys ems. Addi ionally, esea ch
should add ess po en ial challenges associa ed wi h a cashless socie y, such as da a p i acy
conce ns and he digi al di ide, o p o ide a comp ehensi e unde s anding o he e olu ion
o he cashless economy.
Globally, nume ous s udies ha e explo ed he cashless economy and use eadiness
and adop ion. In B unei, he momen um owa d a cashless socie y accele a ed due o
he COVID-19 pandemic, which necessi a ed a shi om con ac -based o con ac less
daily ac i i ies.
Economies 2024,12, 285 6 o 35
The de elopmen o cashless socie ies has deep his o ical oo s. Acco ding o Fab is
(2019), cashless socie ies ha e exis ed since ea ly human his o y when ba e ing and
o he non-cu ency exchange me hods we e used. Howe e , he mode n concep o a
cashless socie y ep esen s an ad anced s age whe e physical money is eplaced by digi al
equi alen s, acili a ing ansac ions in elec onic o m. The i s cashless paymen s we e
in oduced in he 1950s, and since hen, a ious cashless ins umen s ha e been de eloped
(Jain and Jain 2017). Recen ends indica e ha cashless ansac ions a e p e alen no only
in la ge inancial ansac ions bu also in smalle e e yday ansac ions.
Thomas (2013) no ed ha coun ies wi h widesp ead adop ion o cashless solu ions
and high usage a es a e conside ed ad anced. His esea ch highligh ed China as a leading
example, d i en by apid u baniza ion and suppo i e go e nmen policies ha p omo e
cashless paymen s. China has eme ged as a global leade in e-comme ce and cashless
echnology, alongside o he ad anced coun ies like Sweden and Finland (Filipiak 2020).
In Sweden, agg essi e policies and widesp ead adop ion by bo h businesses and socie y
ha e educed cash ansac ions o jus 20% o he o al (Filipiak 2020). Simila ly, Finland is
ad ancing owa d a cashless socie y, leading in bo h ca d paymen equency and In e ne
banking pene a ion.
Impac o COVID-19 pandemic on cashless economy
This s udy examines a c ucial aspec o daily li e—paymen me hods—which ha e
unde gone signi ican changes due o he COVID-19 pandemic. The B unei Da ussalam
Minis y o Heal h highligh ed ha COVID-19 sp eads easily h ough con ac wi h es-
pi a o y d ople s om an in ec ed pe son’s cough, sneeze, o exhala ion. These d ople s
can land on objec s and su aces, po en ially in ec ing o he s who ouch hese su aces
and hen ouch hei eyes, nose, o mou h (Abdul-Halim e al. 2022). Consequen ly, he e
was a global shi owa d con ac less ac i i ies, including cashless paymen s, o enhance
sa e y and minimize physical con ac . This ansi ion accele a ed inancial inclusion as
go e nmen s p omo ed digi al paymen s o p o ec ulne able popula ions du ing he
pandemic (G20 I alian P esidency 2021). While he pandemic spu ed widesp ead adop ion
o cashless ansac ions, Ko kowski and Polasik (2021) aised conce ns abou inancial
inclusion, no ing ha hose al eady using cashless paymen s con inued o do so, while
some pe sis ed wi h cash ansac ions despi e he pandemic. Wisniewski e al. (2021)
sugges ed ha he pandemic changed paymen habi s, d i ing use s away om physical
cash due o ea and app ehension, which may sus ain he adop ion o cashless ansac ions
e en as condi ions imp o e.
Theo e ical ounda ions o unde s anding he con inued use o cashless paymen s
include he Technology Accep ance Model (TAM). De eloped by Da is (1989), TAM is
based on he Theo y o Reasoned Ac ion (TRA) and ocuses on Pe cei ed Use ulness (PU)
and Pe cei ed Ease o Use (PEOU) as key ac o s in luencing Technology Accep ance.
Rou ay e al. (2019) emphasized hese ac o s’ impo ance in consume beha io bu
expanded he model by in eg a ing dimensions o quali y, such as in o ma ion quali y,
sys em quali y, and se ice quali y. Ahuja and Joshi (2018) examined key ac o s a ec ing
pe cep ions o e-walle s, including Ease o Use, Bene i , T us , and Sel -E icacy, hough hey
no ed limi a ions due o a small sample size. Maqableh e al. (2015) ound ha pe cei ed
us , encompassing epu a ion, secu i y, p i acy, and ansac ion size, signi ican ly impac s
he adop ion o cashless paymen s.
The Technology Readiness Index (TRI), de eloped by Mick and Fou nie (1998), mea-
su es use s’ eadiness o new echnology. TRI assesses ac o s such as Op imism, In-
no a i eness, Discom o , and Insecu i y, e lec ing he o e all mindse and inclina ion
owa d echnology adop ion (Pa asu aman 2000). S udies by Humbani and Wiese (2018)
applied TRI o examine eadiness o mobile paymen s, iden i ying d i e s and inhibi o s
o adop ion beha io s. Simila ly, Ka im and Muhammad (2022) ound ha Technology
Readiness, along wi h Con i ma ion Expec a ion, Use Sa is ac ion, and Pe cei ed Secu i y,
in luences he con inued use o cashless paymen s.
Economies 2024,12, 285 7 o 35
Theo e ical F amewo k: Da is de eloped he Technology Accep ance Model in 1989
o s udy use beha io ega ding in o ma ion echnology and p edic adop ion. TAM
emphasizes use pe cep ions and he belie ha echnology mus be bo h use ul and use -
iendly o gain accep ance. The model ocuses on wo main ac o s: Pe cei ed Use ulness
and Pe cei ed Ease o Use. Pa asu aman (2000) de ined Technology Readiness as an
indi idual’s p opensi y o emb ace and use new echnologies o pe sonal and p o essional
goals. The Technology Readiness Index (TRI) measu es o e all Technology Accep ance
based on ou ac o s: Op imism, Inno a i eness, Discom o , and Insecu i y (Figu e 1).
Economies 2024, 12, x FOR PEER REVIEW 7 o 37
Theo e ical F amewo k: Da is de eloped he Technology Accep ance Model in 1989
o s udy use beha io ega ding in o ma ion echnology and p edic adop ion. TAM em-
phasizes use pe cep ions and he belie ha echnology mus be bo h use ul and use -
iendly o gain accep ance. The model ocuses on wo main ac o s: Pe cei ed Use ulness
and Pe cei ed Ease o Use. Pa asu aman (2000) de ined Technology Readiness as an indi-
idual’s p opensi y o emb ace and use new echnologies o pe sonal and p o essional
goals. The Technology Readiness Index (TRI) measu es o e all Technology Accep ance
based on ou ac o s: Op imism, Inno a i eness, Discom o , and Insecu i y (Figu e 1).
Figu e 1. Technology Accep ance Model (Da is 1989).
In Technology Readiness (TR), Pa asu aman (2000) iden i ies se e al key ac o s. Op-
imism e lec s a posi i e belie in echnology, wi h use s con iden ha i enhances con-
ol, e iciency, and lexibili y. Inno a i eness desc ibes a endency o be an ea ly adop e
and a hough leade in echnology. Discom o encompasses eelings o a lack o con ol
o e echnology and being o e whelmed by i s complexi ies. Las ly, Insecu i y in ol es a
dis us o echnology and skep icism abou i s eliabili y and e ec i eness (Figu e 2).
Figu e 2. Technology Readiness Index (Pa asu aman 2000).
3. Hypo hesis Fo mula ion
Se en hypo heses ha e been de eloped o es he p ima y objec i es o he esea ch.
3.1. Inno a i eness
H1: Pe sonal Inno a i eness wi h echnology leads o high pe cei ed ease o use owa ds he con-
inued adop ion o cashless paymen s.
H2: Pe sonal Inno a i eness wi h echnology leads o high pe cei ed use ulness owa ds he con-
inued adop ion o cashless paymen s.
Figu e 1. Technology Accep ance Model (Da is 1989).
In Technology Readiness (TR), Pa asu aman (2000) iden i ies se e al key ac o s.
Op imism e lec s a posi i e belie in echnology, wi h use s con iden ha i enhances
con ol, e iciency, and lexibili y. Inno a i eness desc ibes a endency o be an ea ly
adop e and a hough leade in echnology. Discom o encompasses eelings o a lack
o con ol o e echnology and being o e whelmed by i s complexi ies. Las ly, Insecu i y
in ol es a dis us o echnology and skep icism abou i s eliabili y and e ec i eness
(Figu e 2).
Economies 2024, 12, x FOR PEER REVIEW 7 o 37
Theo e ical F amewo k: Da is de eloped he Technology Accep ance Model in 1989
o s udy use beha io ega ding in o ma ion echnology and p edic adop ion. TAM em-
phasizes use pe cep ions and he belie ha echnology mus be bo h use ul and use -
iendly o gain accep ance. The model ocuses on wo main ac o s: Pe cei ed Use ulness
and Pe cei ed Ease o Use. Pa asu aman (2000) de ined Technology Readiness as an indi-
idual’s p opensi y o emb ace and use new echnologies o pe sonal and p o essional
goals. The Technology Readiness Index (TRI) measu es o e all Technology Accep ance
based on ou ac o s: Op imism, Inno a i eness, Discom o , and Insecu i y (Figu e 1).
Figu e 1. Technology Accep ance Model (Da is 1989).
In Technology Readiness (TR), Pa asu aman (2000) iden i ies se e al key ac o s. Op-
imism e lec s a posi i e belie in echnology, wi h use s con iden ha i enhances con-
ol, e iciency, and lexibili y. Inno a i eness desc ibes a endency o be an ea ly adop e
and a hough leade in echnology. Discom o encompasses eelings o a lack o con ol
o e echnology and being o e whelmed by i s complexi ies. Las ly, Insecu i y in ol es a
dis us o echnology and skep icism abou i s eliabili y and e ec i eness (Figu e 2).
Figu e 2. Technology Readiness Index (Pa asu aman 2000).
3. Hypo hesis Fo mula ion
Se en hypo heses ha e been de eloped o es he p ima y objec i es o he esea ch.
3.1. Inno a i eness
H1: Pe sonal Inno a i eness wi h echnology leads o high pe cei ed ease o use owa ds he con-
inued adop ion o cashless paymen s.
H2: Pe sonal Inno a i eness wi h echnology leads o high pe cei ed use ulness owa ds he con-
inued adop ion o cashless paymen s.
Figu e 2. Technology Readiness Index (Pa asu aman 2000).
3. Hypo hesis Fo mula ion
Se en hypo heses ha e been de eloped o es he p ima y objec i es o he esea ch.
3.1. Inno a i eness
H1: Pe sonal Inno a i eness wi h echnology leads o high pe cei ed ease o use owa ds he
con inued adop ion o cashless paymen s.
Economies 2024,12, 285 8 o 35
H2: Pe sonal Inno a i eness wi h echnology leads o high pe cei ed use ulness owa ds he
con inued adop ion o cashless paymen s.
Indi iduals who possess high inno a i eness wi h echnology ypically ha e a s onge
in insic mo i a ion o explo e and use new echnology. Those highly mo i a ed by inno a-
ion a e no wo ied abou whe he i is use - iendly and may s ill a emp o y and use i
(Dabholka and Bagozzi 2002).
3.2. Op imism
H3: Pe sonal Op imism abou echnology signi ican ly leads o high pe cei ed ease o use owa ds
he con inued adop ion o cashless paymen s.
H4: Pe sonal Op imism abou echnology signi ican ly leads o high pe cei ed use ulness owa ds
he con inued adop ion o cashless paymen s.
Acco ding o Pa asu aman (2000), a echnology op imis is someone who belie es
ha new echnologies o e inc eased con ol, lexibili y, and e iciency in hei daily li es.
This Op imism means ha indi iduals wi h a posi i e ou look a e likely o iew new
echnology a o ably, e en i hey ha e no ye used i . Thei p e-de e mined posi i e
a i ude in luences hei eadiness o emb ace and adop new echnological ad ancemen s.
3.3. Discom o
H5: Pe sonal Discom o wi h echnology signi ican ly leads o low pe cei ed ease o use owa ds
he con inued adop ion o cashless paymen s.
H6: Pe sonal Discom o wi h echnology signi ican ly leads o low pe cei ed use ulness owa ds
he con inued adop ion o cashless paymen s.
Discom o in ol es a pe cep ion o ha ing limi ed con ol o e echnology, which
can lead o eelings o being o e whelmed (Lin e al. 2007). Acco ding o Pa asu aman
(2000), indi iduals who expe ience discom o wi h new echnology o en belie e ha i
will domina e hei li es a he han se e hem. They may also eel ha echnology is
designed o hose wi h ad anced echnical knowledge a he han o he a e age use .
3.4. Insecu i y
H7: Pe sonal Insecu i y abou echnology signi ican ly leads o low pe cei ed ease o use owa ds
he con inued adop ion o cashless paymen s.
H8: Pe sonal Insecu i y abou echnology signi ican ly leads o low pe cei ed use ulness owa d
he con inued adop ion o cashless paymen s.
Insecu i y e e s o a lack o us in echnology and skep icism abou i s eliabili y and
e ec i eness (Lin e al. 2007). Resea ch sugges s ha indi iduals who eel insecu e abou
echnology a e mo e likely o ocus on po en ial isks a he han he bene i s. This app ehen-
sion o en leads hem o a oid adop ing new echnology al oge he (Blu and Wang 2020).
3.5. Pe cei ed Ease o Use and Pe cei ed Use ulness
H9: The e is a signi ican posi i e ela ionship be ween Pe cei ed Ease o Use and Pe cei ed
Use ulness ega ding he con inued adop ion o cashless paymen s.
Economies 2024,12, 285 15 o 35
Table 6. De ails o demog aphic p o ile.
Demog aphic P o ile
Gende •Male
•Female
Age g oup
•Below 20 yea s
•21–30 yea s
•31–40 yea s
•41–50 yea s
•51–60 yea s
•Abo e 60 yea s
Le el o educa ion
•Ce i ica e
•Unde g adua e deg ee
•Pos g adua e deg ee
•P o essional quali ica ion
•O he s
Mon hly income
•Below BND1000
•BND1000–BND2000
•BND2001–BND3000
•BND3001–BND4000
•BND4001–BND5000
•Abo e BND5000
Do you use cashless paymen s (Debi Ca ds/C edi
Ca ds/In e ne Banking/Mobile Banking/E-walle QR
Codes) when making o ans e ing paymen s?
•Yes
•No.
Two (2) cashless paymen modes mos ly used
•C edi and/o Debi Ca d
•In e ne Banking
•Mobile Banking
•E-walle QR Codes
Measu emen Model Assessmen
Measu emen model assessmen analyses he quali y o measu emen o imp o e i s
use ulness and accu acy. Wi h he quan i a i e app oach, he cons uc s o he ins umen
will be assessed o ac o loading, alidi y, and eliabili y. Conside ing he eliabili y and
alidi y o da a-collec ion ins umen s is c i ical when conduc ing and discussing esea ch.
Howe e , i is also c ucial o begin he measu emen model assessmen by examining
he ac o analysis o he a iable i ems o de e mine how well he i em ep esen s he
unde lying ac o .
Reliabili y and Validi y Analysis
Fo his s udy, con i ma o y ac o analysis will be pe o med o con i m he alidi y o
he hypo heses and measu emen ins umen s. This will be pe o med h ough Sma PLS
4. To ensu e how well he applied me hod o he ques ionnai e can measu e he esponses,
eliabili y and alidi y analysis will be pe o med. Reliabili y e e s o he consis ency
o a measu e. S udies by Heale and Twyc oss (2015), in measu ing beha io s ela ing o
nu sing p ac ices, explain ha pa icipan s comple ing a quan i a i e ins umen would
esul in p o iding he same esponse each ime i is comple ed. When analyzing eliabili y
o his s udy, in e nal consis ency will be assessed o de e mine he ex en o which hall
he i ems on a scale measu e a cons uc . In his sense, C onbach’s Alpha, being he
mos common es , will be used o de e mine he in e nal consis ency o he ques ionnai e
wi h a measu emen o es o scale be ween 0 and 1. Acco ding o Ta akol and Dennick
(2011), alpha alue inc eases when i ems co ela e. Howe e , i is also impo an o no e
ha a high alpha coe icien would no ep esen a high le el o in e nal consis ency
i he e we e a lack in he leng h o he es . The e o e, depending on he assessmen
Economies 2024,12, 285 16 o 35
conduc ed o indica o eliabili y, composi e eliabili y may also be applied o es ing
o i s eliabili y. Validi y analysis e e s o he accu acy o a measu e in a quan i a i e
s udy. In o he wo ds, i de e mines whe he esul s ob ained accu a ely ep esen he
desi ed measu e. In measu ing o alidi y, cons uc alidi y and c i e ion alidi y will be
measu ed by examining homogenei y and con e gen alidi y, espec i ely. Disc iminan
alidi y will also be measu ed o de e mine whe he he i ems measu e some hing else
unexpec edly. The he e o ai –mono ai (HTMT) a io o co ela ions app oach will be
applied o de e mine i . S udies by Hensele e al. (2015) ound i o be o supe io
pe o mance when compa ed o he Fo nell–La cke c i e ion.
S uc u al Model Assessmen
P io o examining he hypo hesis p oposed, he s uc u al model will be es ed. S uc-
u al momen assessmen ocuses on analyzing he ela ionship be ween independen
a iables, dependen a iables, he media o connec ion be ween wo a iables, o mod-
e a ion analysis wi h an addi ional a iable a ec ing he ela ionship, ha include he
pa h coe icien (ß), he coe icien o de e mina ion (R
2
), and he e ec size (F
2
) in he
assessmen o he s uc u al model. Fo his s udy, he pa h coe icien and he coe icien
o de e mina ion will be analyzed o alida e he s uc u al model. The boo s apping
p ocess will be applied o de e mine whe he he pa h coe icien is s a is ically signi ican
o o he wise. Assessmen will be done h ough PLS-SEM so wa e, which can e alua e he
signi icance and ele ance o pa h coe icien s, upon which he model’s explana o y and
p edic i e powe can be assessed. I is c ucial o no e ha he ini ial s ep in he e alua ion
o s uc u al model cons uc s is he assessmen o whe he he e a e issues o collinea i y.
S uc u al models showing high mul icollinea i y can a ec he pa h coe icien and change
he sign o hese coe icien . The e o e, a es o collinea i y will be pe o med p io o
s uc u al model assessmen s which is shown in Figu e 4.
Economies 2024, 12, x FOR PEER REVIEW 16 o 37
else unexpec edly. The he e o ai –mono ai (HTMT) a io o co ela ions app oach will
be applied o de e mine i . S udies by Hensele e al. (2015) ound i o be o supe io pe -
o mance when compa ed o he Fo nell–La cke c i e ion.
S uc u al Model Assessmen
P io o examining he hypo hesis p oposed, he s uc u al model will be es ed.
S uc u al momen assessmen ocuses on analyzing he ela ionship be ween independ-
en a iables, dependen a iables, he media o connec ion be ween wo a iables, o
mode a ion analysis wi h an addi ional a iable a ec ing he ela ionship, ha include
he pa h coe icien (ß), he coe icien o de e mina ion (R
2
), and he e ec size (F
2
) in he
assessmen o he s uc u al model. Fo his s udy, he pa h coe icien and he coe icien
o de e mina ion will be analyzed o alida e he s uc u al model. The boo s apping p o-
cess will be applied o de e mine whe he he pa h coe icien is s a is ically signi ican o
o he wise. Assessmen will be done h ough PLS-SEM so wa e, which can e alua e he
signi icance and ele ance o pa h coe icien s, upon which he model’s explana o y and
p edic i e powe can be assessed. I is c ucial o no e ha he ini ial s ep in he e alua ion
o s uc u al model cons uc s is he assessmen o whe he he e a e issues o collinea i y.
S uc u al models showing high mul icollinea i y can a ec he pa h coe icien and
change he sign o hese coe icien . The e o e, a es o collinea i y will be pe o med
p io o s uc u al model assessmen s. Figu e 4 below shows he s uc u al model assess-
men p ocedu e acco ding o Joseph F. Hai e al. (2020).
Figu e 4. S uc u al model assessmen pe o med.
5. Finding
The s udy employed pa ial leas -squa es s uc u al equa ion modeling (PLS-SEM)
o igo ously assess he measu emen model, a obus echnique well sui ed o complex
p edic i e modeling and heo y-building. PLS-SEM is pa icula ly ad an ageous o han-
dling in ica e esea ch models and smalle sample sizes, p o iding lexibili y in manag-
ing mul iple dependen cons uc s and accommoda ing non-no mal da a dis ibu ions.
This me hodology was chosen o explo e he causal ela ionships be ween cons uc s e-
la ed o he cashless economy, including eadiness, secu i y, and echnological enhance-
men . PLS-SEM is ideal o explo a o y esea ch whe e heo e ical amewo ks may s ill
be de eloping.
To ensu e he eliabili y and alidi y o he cons uc s, se e al measu es we e imple-
men ed. Reliabili y was e alua ed using C onbach’s Alpha and composi e eliabili y (CR),
while con e gen alidi y was con i med h ough a e age a iance ex ac ed (AVE) al-
ues exceeding he 0.50 h eshold. Disc iminan alidi y was assessed using he Fo nell–
La cke c i e ion and he he e o ai –mono ai (HTMT) a io o ensu e ha each cons uc
was dis inc . Fo cons uc s like “Insecu i y”, which may show lowe eliabili y coe i-
cien s, po en ial inconsis encies we e add essed by e iewing i em wo ding, he concep-
ual domain, and con ex ual ac o s o he s udy.
The s uc u al model analysis was comp ehensi e, wi h signi ican pa h coe icien s
clea ly linked o he s udy’s hypo heses o esea ch ques ions. A concise summa y o e-
sul s was p esen ed in abula o ma o easy e e ence, enhancing cla i y. The in e p e-
a ion o indings emphasized hei implica ions o b oade esea ch ques ions, discuss-
ing unexpec ed esul s o de ia ions om p io li e a u e. Possible explana ions o hese
S ep 1:
Assess
collinea i y
issues in he
s uc u al model
S ep 2:
Assess he
signi icance and
ele ance o he
s uc u al model
ela ionships
S ep 3:
Assess he
model’s
explana o y
powe
S ep 4:
Assess he model
p edic i e powe
Figu e 4. S uc u al model assessmen pe o med.
5. Finding
The s udy employed pa ial leas -squa es s uc u al equa ion modeling (PLS-SEM) o
igo ously assess he measu emen model, a obus echnique well sui ed o complex p e-
dic i e modeling and heo y-building. PLS-SEM is pa icula ly ad an ageous o handling
in ica e esea ch models and smalle sample sizes, p o iding lexibili y in managing mul i-
ple dependen cons uc s and accommoda ing non-no mal da a dis ibu ions. This me hod-
ology was chosen o explo e he causal ela ionships be ween cons uc s ela ed o he
cashless economy, including eadiness, secu i y, and echnological enhancemen .
PLS-SEM
is ideal o explo a o y esea ch whe e heo e ical amewo ks may s ill be de eloping.
To ensu e he eliabili y and alidi y o he cons uc s, se e al measu es we e imple-
men ed. Reliabili y was e alua ed using C onbach’s Alpha and composi e eliabili y (CR),
while con e gen alidi y was con i med h ough a e age a iance ex ac ed (AVE) alues
exceeding he 0.50 h eshold. Disc iminan alidi y was assessed using he Fo nell–La cke
c i e ion and he he e o ai –mono ai (HTMT) a io o ensu e ha each cons uc was
dis inc . Fo cons uc s like “Insecu i y”, which may show lowe eliabili y coe icien s, po-
en ial inconsis encies we e add essed by e iewing i em wo ding, he concep ual domain,
and con ex ual ac o s o he s udy.
Economies 2024,12, 285 17 o 35
The s uc u al model analysis was comp ehensi e, wi h signi ican pa h coe icien s
clea ly linked o he s udy’s hypo heses o esea ch ques ions. A concise summa y o esul s
was p esen ed in abula o ma o easy e e ence, enhancing cla i y. The in e p e a ion o
indings emphasized hei implica ions o b oade esea ch ques ions, discussing unex-
pec ed esul s o de ia ions om p io li e a u e. Possible explana ions o hese anomalies,
such as sample cha ac e is ics o measu emen issues, we e explo ed, and di ec ions o
u u e esea ch we e sugges ed.
Resul s we e in eg a ed wi h he s udy’s o e a ching esea ch ques ions, demons a -
ing how each s a is ical ou come con ibu es o unde s anding he dynamics o he cashless
economy, eadiness, secu i y, and echnological ad ancemen . This syn hesis p o ided
a cohesi e na a i e, highligh ing he s udy’s con ibu ions o heo y, p ac ice, and pol-
icy. Fo example, insigh s on secu i y may in o m egula o y changes, while indings
on echnological enhancemen could guide imp o emen s in use in e aces o cashless
paymen sys ems.
In conclusion, he Da a Analysis sec ion c i ically e alua ed he s udy’s limi a ions and
sugges ed a eas o u u e esea ch, enhancing he s udy’s schola ly igo and con ibu ing
o ongoing academic discou se. P ac ical implica ions we e discussed in de ail, o e ing
ecommenda ions o policymake s, indus y p ac i ione s, and esea che s o ad ance
cashless economy ini ia i es. S a egies o imp o ing secu i y in digi al ansac ions and
inc easing public eadiness o a cashless economy we e pa icula ly emphasized (Table 7).
Table 7. Summa y o hypo heses and esul s.
Hypo hesis Pa h Coe icien Signi icance (p-Value) Suppo ed (Yes/No)
H1 0.35 <0.01 Yes
H2 −0.12 0.05 No
H3 0.45 <0.01 Yes
. . . . . . . . . . . .
Demog aphic Analysis
A o al o 219 esponses (N = 219) we e collec ed o e 4 weeks h ough an online su ey,
o ming he quan i a i e ounda ion o his s udy. Ini ially, he su ey was dis ibu ed
ia Wha sApp and email o iends and amily, ensu ing a b oad each wi hin known
ne wo ks. To u he expand he esponden base, he dis ibu ion was la e ex ended o
include andom pa icipan s. To main ain da a in eg i y, all su ey ques ions we e se as
manda o y, ensu ing ha each esponden p o ided comple e answe s. As a esul , all
esponses ecei ed a e conside ed alid o analysis.
Tables 7–9p esen he demog aphic p o ile o he esponden s (=219). Acco ding o
Table 7, he sample consis s p edominan ly o emale esponden s, wi h 144 pa icipan s
(64.86%), compa ed o 75 male esponden s (33.78%). This gende dis ibu ion highligh s a
highe emale ep esen a ion in he s udy.
Table 8. Demog aphic p o ile by gende and age (N = 219).
Responden P o iles F equency % Cumula i e %
Gende Male 75 33.78% 34.2%
Female 144 64.86% 100%
Age G oup
Below 20 Yea s 12 5.41% 5.50%
21–30 Yea s 21 9.46% 15.1%
31–40 Yea s 49 22.07% 37.4%
41–50 Yea s 112 50.45% 88.6%
51–60 Yea s 23 10.36% 99.1%
Abo e 60 Yea s 2 0.90% 100%
Economies 2024,12, 285 18 o 35
Table 9. Demog aphic p o ile by educa ion, employmen , and income le el (N = 219).
Responden P o iles F equency % Cum %
Educa ion Le el
Ce i ica e/Diploma Le el 77 34.68% 35.2%
Unde g adua e Deg ee 61 27.48% 63.0%
Pos g adua e Deg ee 68 30.63% 94.1%
P o essional Quali ica ion 11 4.95% 99.1%
O he s 2 0.90% 100%
Employmen
S a us
Employed (Go e nmen ) 113 50.90% 51.6%
Employed (P i a e) 78 35.14% 87.2%
Sel -employed 6 2.70% 90.0%
Unemployed 16 7.21% 97.3%
Re i ed 6 2.70% 100%
Mon hly G oss
Income
Below BND1000 31 13.96% 14.2%
BND1000–BND2000 33 14.86% 29.2%
BND2001–BND3000 36 16.22% 45.7%
BND3001–ND4000 44 19.82% 65.8%
BND4001–BND5000 55 24.77% 90.9%
Abo e BND5000 20 9.01% 100%
In e ms o age dis ibu ion, mos esponden s all wi hin he 41–50 yea s age g oup,
accoun ing o o e hal o he sample (50.45%). The nex la ges age g oup is 31–40 yea s,
ep esen ing 22.07% o esponden s. Smalle pe cen ages o pa icipan s a e sp ead ac oss
o he age g oups: 21–30 yea s (9.46%), 51–60 yea s (10.36%), below 20 yea s (5.41%), and
abo e 60 yea s (0.90%). This demog aphic b eakdown p o ides a comp ehensi e o e iew
o he esponden cha ac e is ics, indica ing a di e se ange o ages, wi h a concen a ion in
he middle-age ca ego ies. These demog aphic insigh s will be essen ial in con ex ualizing
he indings o he s udy and unde s anding how di e en age and gende g oups pe cei e
he issues explo ed.
Table 8o e s a de ailed b eakdown o esponden s’ demog aphic p o iles, ca ego ized
by educa ion le el and employmen s a us. The da a shows ha mos esponden s ha e
a ained ei he a Ce i ica e/Diploma o a Pos g adua e Deg ee, ep esen ing 34.68% and
30.63% o he sample, espec i ely. Those wi h an Unde g adua e Deg ee cons i u e 27.48%
o he esponden s. These s a is ics indica e a highly educa ed pa icipan pool, wi h a
signi ican p opo ion ha ing achie ed ad anced educa ion.
Rega ding employmen s a us, go e nmen employees a e he la ges g oup, accoun -
ing o 50.9% o he esponden s. This is ollowed by hose wo king in he p i a e sec o ,
who make up 35.14% o he sample. A smalle segmen , 2.70%, a e sel -employed, while
9.91% a e cu en ly unemployed, o aling 21 indi iduals. Despi e hei unemploymen
s a us, hese indi iduals a e conside ed aluable o he s udy as hey may s ill ha e o he
income sou ces and ep esen po en ial u u e membe s o he wo k o ce.
In e ms o income dis ibu ion, mos esponden s all wi hin he mon hly income
b acke o BND4001 o BND5000, making up 24.77% o he sample. This is ollowed by
hose ea ning be ween BND3001 and BND4000, who ep esen 19.82% o esponden s.
Including unemployed esponden s in he da a analysis p o ides a mo e comp ehensi e
iew o income dynamics and economic pa icipa ion ac oss a ious segmen s o socie y,
highligh ing po en ial u u e ea nings and con ibu ions o he wo k o ce.
To add ess he esea ch ques ions, he s udy ocuses on indi idual cus ome s who
use cashless paymen me hods, using his segmen as he sample o u he analysis. As
illus a ed in Table 9, ou o he 219 esponden s who ini ially pa icipa ed, 14 indi iduals
we e iden i ied as non-cashless paymen use s and we e he e o e excluded om he
analysis. The emaining 205 esponden s, who use cashless paymen me hods, p o ide he
basis o he subsequen analysis (Table 10).
Economies 2024,12, 285 19 o 35
Table 10. Responden s based on cashless paymen use (N = 219).
Responden P o iles F equency %
Cashless Paymen Use No 14 6.31%
Yes 205 92.34%
Among hese 205 cashless paymen use s, a signi ican po ion, 34.10%, epo s us-
ing cashless paymen s 3 o 5 imes a day. In con as , an equal pe cen age o espon-
den s, 27.30%, use cashless paymen s ei he once o wice a day. This dis ibu ion indi-
ca es a ela i ely high equency o cashless paymen usage among a subs an ial numbe
o esponden s.
Rega ding he modes o cashless paymen s p e e ed by esponden s, he majo i y
show a s ong p e e ence o c edi and debi ca ds, wi h 95.10% using hem o ansac ions.
Mobile banking ollows as he second mos popula me hod, used by 76.60% o esponden s.
These p e e ences highligh he dominance o adi ional ca d paymen s and he g owing
ole o mobile banking in cashless ansac ions.
Figu es 5and 6p o ide isual ep esen a ions o hese indings. Figu e 5depic s a ba
g aph illus a ing he equency o daily cashless paymen usage among he 205 esponden s,
while Figu e 6p esen s a ba g aph showing he pe cen age o each cashless paymen
me hod u ilized. These igu es o e a clea o e iew o he usage pa e ns and p e e ences
among cashless paymen use s, acili a ing a deepe unde s anding o he da a.
Economies 2024, 12, x FOR PEER REVIEW 19 o 37
illus a ed in Table 9, ou o he 219 esponden s who ini ially pa icipa ed, 14 indi iduals
we e iden i ied as non-cashless paymen use s and we e he e o e excluded om he anal-
ysis. The emaining 205 esponden s, who use cashless paymen me hods, p o ide he
basis o he subsequen analysis (Table 10).
Among hese 205 cashless paymen use s, a signi ican po ion, 34.10%, epo s using
cashless paymen s 3 o 5 imes a day. In con as , an equal pe cen age o esponden s,
27.30%, use cashless paymen s ei he once o wice a day. This dis ibu ion indica es a
ela i ely high equency o cashless paymen usage among a subs an ial numbe o e-
sponden s.
Rega ding he modes o cashless paymen s p e e ed by esponden s, he majo i y
show a s ong p e e ence o c edi and debi ca ds, wi h 95.10% using hem o ansac-
ions. Mobile banking ollows as he second mos popula me hod, used by 76.60% o e-
sponden s. These p e e ences highligh he dominance o adi ional ca d paymen s and
he g owing ole o mobile banking in cashless ansac ions.
Figu es 5 and 6 p o ide isual ep esen a ions o hese indings. Figu e 5 depic s a
ba g aph illus a ing he equency o daily cashless paymen usage among he 205 e-
sponden s, while Figu e 6 p esen s a ba g aph showing he pe cen age o each cashless
paymen me hod u ilized. These igu es o e a clea o e iew o he usage pa e ns and
p e e ences among cashless paymen use s, acili a ing a deepe unde s anding o he
da a.
Table 10. Responden s based on cashless paymen use (N = 219).
Responden P o iles F equency %
Cashless Paymen Use No 14 6.31%
Yes 205 92.34%
Figu e 5. F equency % o cashless paymen use in a day (N = 205).
2.40%
27.30% 27.30%
34.10%
8.80%
0%
5%
10%
15%
20%
25%
30%
35%
40%
No used
daily
Once Twice Th ee o Fi e
imes
Six imes and
mo e
F equency o Cashless Paymen Use in a Day
Figu e 5. F equency % o cashless paymen use in a day (N = 205).
Economies 2024, 12, x FOR PEER REVIEW 20 o 37
Figu e 6. Pe cen age o cashless paymen modes used (N = 205).
P elimina y Da a Analysis
Be o e conduc ing any s a is ical analyses, a ho ough da a sc eening p ocess was
unde aken o ensu e he alidi y and comple eness o he collec ed da a. Ou o he ini ial
219 esponses, 14 we e excluded om he da ase . This exclusion was based on he iden-
i ica ion o non- esponse bias, pa icula ly ela ed o ques ions conce ning indica o s cen-
al o he s udy. These 14 esponden s we e classi ied as non-cashless paymen use s, and
hei esponses did no mee he s udy’s c i e ia o alid da a, ende ing hem unusable
o he esea ch.
Ex eme Values/Ou lie s: The accu acy and eliabili y o s a is ical analysis depend
hea ily on he quali y o he da a, which mus be sc eened o missing alues and ex eme
ou lie s (Pallan 2020). In his s udy, da a cleaning was pe o med using SPSS so wa e o
iden i y and add ess ou lie s and ex eme alues, wi h he goal o achie ing a no mal
dis ibu ion o he da ase . Ma coulides and Saunde s (2006) emphasize ha emo ing
ex eme alues and ou lie s is c ucial be o e conduc ing s a is ical es s, as hey can skew
esul s and a ec he alidi y o he indings.
Du ing he da a-cleaning p ocess, a no mali y es was conduc ed using SPSS, which
iden i ied h ee cases wi h ex eme alues. These cases we e emo ed o ensu e ha he
inal da ase adhe ed o no mali y assump ions. Consequen ly, he e ised da ase in-
cluded 203 alid esponses. Table 11 illus a es he esponses and cons uc s associa ed
wi h he ex eme alues and ou lie s iden i ied du ing his p ocess. This ca e ul sc eening
and cleaning o he da a ensu es ha he emaining da ase is obus and sui able o sub-
sequen s a is ical analysis.
Table 11. Ex eme alues iden i ied and excluded.
Responden No. OPT INN DIS INS PEOU PU CA
36 1 1 2 2 1 1 1
77 2 2 3 2 1 1 2
189 1 1 3 3 2 1 1
No e: One (1) = S ongly Disag ee, Two (2) = Disag ee, Th ee (3) = Neu al, Fou (4) = Ag ee, Fi e (5)
= S ongly Ag ee.
No mali y o Da a
A no mali y es is commonly u ilized o de e mine whe he he da a a e collec ed
om a no mally dis ibu ed popula ion. Resea ch da a e i ied o be no mally dis ibu ed
will enable he s udy o apply pa ame ic es s such as a - es , ANOVA, co ela ion, and
95.10%
40.50%
76.60%
13.20%
4.90%
59.50%
23.40%
86.80%
0%
25%
50%
75%
100%
C edi o Debi
Ca d
In e ne Banking Mobile Banking E-walle / QR
Code
Yes No
Figu e 6. Pe cen age o cashless paymen modes used (N = 205).
Economies 2024,12, 285 20 o 35
P elimina y Da a Analysis
Be o e conduc ing any s a is ical analyses, a ho ough da a sc eening p ocess was
unde aken o ensu e he alidi y and comple eness o he collec ed da a. Ou o he
ini ial 219 esponses, 14 we e excluded om he da ase . This exclusion was based on he
iden i ica ion o non- esponse bias, pa icula ly ela ed o ques ions conce ning indica o s
cen al o he s udy. These 14 esponden s we e classi ied as non-cashless paymen use s,
and hei esponses did no mee he s udy’s c i e ia o alid da a, ende ing hem unusable
o he esea ch.
Ex eme Values/Ou lie s: The accu acy and eliabili y o s a is ical analysis depend
hea ily on he quali y o he da a, which mus be sc eened o missing alues and ex eme
ou lie s (Pallan 2020). In his s udy, da a cleaning was pe o med using SPSS so wa e
o iden i y and add ess ou lie s and ex eme alues, wi h he goal o achie ing a no mal
dis ibu ion o he da ase . Ma coulides and Saunde s (2006) emphasize ha emo ing
ex eme alues and ou lie s is c ucial be o e conduc ing s a is ical es s, as hey can skew
esul s and a ec he alidi y o he indings.
Du ing he da a-cleaning p ocess, a no mali y es was conduc ed using SPSS, which
iden i ied h ee cases wi h ex eme alues. These cases we e emo ed o ensu e ha he
inal da ase adhe ed o no mali y assump ions. Consequen ly, he e ised da ase included
203 alid esponses. Table 11 illus a es he esponses and cons uc s associa ed wi h
he ex eme alues and ou lie s iden i ied du ing his p ocess. This ca e ul sc eening and
cleaning o he da a ensu es ha he emaining da ase is obus and sui able o subsequen
s a is ical analysis.
Table 11. Ex eme alues iden i ied and excluded.
Responden No.
OPT INN DIS INS PEOU PU CA
36 1 1 2 2 1 1 1
77 2 2 3 2 1 1 2
189 1 1 3 3 2 1 1
No e: One (1) = S ongly Disag ee, Two (2) = Disag ee, Th ee (3) = Neu al, Fou (4) = Ag ee, Fi e (5) = S ongly Ag ee.
No mali y o Da a
A no mali y es is commonly u ilized o de e mine whe he he da a a e collec ed
om a no mally dis ibu ed popula ion. Resea ch da a e i ied o be no mally dis ibu ed
will enable he s udy o apply pa ame ic es s such as a - es , ANOVA, co ela ion, and
eg essions o i s s a is ical analysis. Essen ially, o pa ame ic es s, he assump ion o
no mali y needs o be checked, as he alidi y o he es depends on i . The no mali y o
da a is achie ed when he signi ican c i ical alues a e mo e han 0.05 (p- alues> 0.05)
(Ghasemi and Zahediasl 2012). One o he echniques in checking o no mali y o da a
is he Kolmogo o –Smi no es pe o med using he SPSS so wa e. A p e ious s udy
by Mohd Sapian and No ziah Ismail (2021) applied his es me hod based on he numbe
o esponses collec ed exceeding50 esponses applied his es . Table 12 illus a es he
esul o he Kolmogo o –Smi no es pe o med whe e all he a iables indica e ha
no mal dis ibu ion canno be assumed, as signi ican p- alues a e less han 0.05, he e o e
ejec ing he null hypo hesis ha he da a a e no mally dis ibu ed. As he no mali y o
da a canno be assumed, i can be concluded ha da a analysis will be u he es ed using
he non-pa ame ic echniques o Sma PLS e sion 4.
Economies 2024,12, 285 21 o 35
Table 12. Resul o no mali y o all cons uc s.
Va iables
Kolmogo o –Smi no
S a is ic Sig.
Op imism (OPT) 0.146 0.000
Inno a i eness (IN) 0.095 0.000
Discom o (DIS) 0.080 0.003
Insecu i y (INS) 0.117 0.000
Pe cei ed Ease o Use (PEOU) 0.248 0.000
Pe cei ed Use ulness (PU) 0.152 0.000
Con inued Adop ion o Cashless Paymen s (CA)
0.117 0.000
H0 = Da a a e no mally dis ibu ed
Desc ip i e Analysis
Desc ip i e analysis was cons uc i ely used o desc ibe and summa ize signi ican
da a poin s as well as iden i y pa e ns wi hin he a iables o gain accessible insigh s
p io o pe o ming u he da a analysis (Bush 2020). U ilizing SPSS so wa e, desc ip i e
s a is ics o he mean, s anda d de ia ion, and equency we e used o desc ibe he ob ained
da a. Based on six independen a iables and one dependen a iable de eloped o he
s udy, he mean and s anda d de ia ion we e compu ed o de e mine he median and
cen al endencies. Table 13 shows he measu emen o he cen al endencies o bo h
he independen and dependen cons uc s. The analysis was ac o ed based on a5-poin
Like scale o each ques ion wi h a scale om one (s ongly disag ee) o i e (s ongly
ag ee). Based on he calcula ions, independen a iables Discom o , wi h a low mean o
2.971 and s anda d de ia ion o 0.74, and Insecu i y, wi h a low mean o 3.02 and de ia ion
o 0.77,indica e ha esponden s nei he ag ee no disag ee abou ha ing lack o con ol
and eelings o dis us owa ds cashless paymen s. Independen a iables o Op imism,
Inno a i eness, Pe cei ed Ease o Use, and Pe cei ed Use ulness showed highe means,
anging om 3.43 o 4.28,wi h a s anda d de ia ion o 0.703 o 0.870, which indica es
ha mos esponden s ag eed wi h he ques ions unde each a iable. Pe cei ed Ease
o Use showed he highes mean o 4.28, gi ing a u he indica ion ha esponden s
ag ee ha cashless paymen s a e easy o use a he han esponden s being disag eeable
owa ds hem.
Table 13. Cen al endencies o all cons uc s.
Cons uc s Mean SD
Op imism 3.978 0.870
Inno a i eness 3.438 0.753
Discom o 2.971 0.740
Insecu i y 3.023 0.772
Pe cei ed Ease o Use 4.281 0.708
Pe cei ed Use ulness 4.046 0.703
Con inued Adop ion o Cashless Paymen s 4.061 0.767
In e ms o he dependen a iable, Con inued Adop ion o Cashless Paymen s had a
high mean alue o 4.06 wi h a s anda d de ia ion o 0.76. This u he shows ha mos
esponden s a e ag eeable o con inuing o adop and use cashless paymen s.
Dissec ing i u he in o each i em o he cons uc p o ides u he insigh in o he
esponden s’ le el o ag eemen wi h he ques ions posed in he su ey dis ibu ed. This
will be u he discussed in Sec ion 5. Table 14 shows he cen al endencies acco ding o
he ques ion i ems unde each cons uc .
Economies 2024,12, 285 22 o 35
Table 14. Cen al endencies o each indica o .
Cons uc s I ems Mean SD.
Inno a i eness
INN1 I ind cashless paymen s o be men ally s imula ing 3.41 0.839
INN2 I can usually igu e ou how o use cashless paymen s
wi hou help om o he s 3.82 0.923
INN3
I am among he i s in my ci cle o iends o adop cashless
paymen s when i is in oduced 3.39 1.134
INN4
I eel ha o he people come o me o ad ice on how o use
cashless paymen s 3.13 0.972
Op imism
OPT1 Cashless paymen s gi e me lexibili y in making paymen s 4.24 0.954
OPT2 Cashless paymen s i my li es yle 4.06 0.913
OPT3 Cashless paymen s make me mo e p oduc i e in my
pe sonal li e 3.91 0.996
OPT4
Cashless paymen s make me mo e e icien in my p o ession
3.79 0.996
OPT5 I eel con iden ha cashless paymen s will ollow h ough
wi h wha I ins uc hem o do 3.88 0.963
Discom o
DIS1 I eel i is no sa e o do ansac ions online 2.73 0.870
DIS2 Some imes, I hink ha cashless paymen s a e no designed
o use by o dina y people 2.65 0.986
DIS3 I is emba assing when I ha e ouble wi h cashless
paymen s while o he people a e wa ching 3.15 1.125
DIS4 I eel ha cashless paymen s ha e isks ha a e no known
un il a e people ha e used hem 3.35 0.986
Insecu i y
INS1 I eel cashless paymen s expose my inancial
in o ma ion online 2.93 1.005
INS2
I do no eel con iden buying o doing business wi h a place
ha only accep s cashless paymen s 2.51 0.998
INS3
Any cashless paymen ansac ion should be con i med la e
wi h a sepa a e communica ion 3.63 1.145
Pe cei ed Ease o Use
PEOU1 I use cashless paymen s based on my own pe sonal wan s 4.20 0.780
PEOU2 In my opinion, he use o cashless paymen s is lexible (can
be used any ime and anywhe e) 4.29 0.812
PEOU3 O e all, cashless paymen s a e easy o use 4.36 0.777
Pe cei ed use ulness
PU1 I eel cashless paymen s enable me o make
paymen s e ec i ely 4.17 0.787
PU2 I eel cashless paymen s help o manage my inancesbe e 3.69 0.990
PU3 I ind cashless paymen s make i easie o accomplish my
paymen ac i i ies 4.13 0.776
PU4 I eel cashless paymen s a ea p ac ical op ion o making
paymen 4.20 0.726
Con inued Adop ion o
Cashless paymen s
CA1 I ha e been an ac i e use o cashless paymen s o
some ime 4.13 0.856
CA2 I in end o con inue using cashless paymen s in he u u e 4.25 0.805
CA3
I in end o inc ease he equency o cashless paymen s in my
daily li e 3.86 0.915
CA4 I will always ecommend ha o he s use cashless paymen s 4.00 0.855
Economies 2024,12, 285 23 o 35
The measu emen model e alua es he ela ionship be ween la en a iables and hei
co esponding measu emen s. As ou lined in Sec ion 3, he assessmen o cons uc alidi y
and C onbach’s Alpha will be conduc ed o ensu e he quali y o hese measu emen s
be o e p oceeding o hypo hesis es ing. To pe o m his assessmen , bo h SPSS so wa e
and PLS-SEM h ough Sma PLS V4.0 will be employed. P e ious esea ch by Zamil e al.
(2022) has demons a ed ha PLS-SEM is e ec i e in add essing complex modeling issues,
including non-no mal da a dis ibu ions. This dual app oach will acili a e a comp ehensi e
e alua ion o he measu emen model’s obus ness and alidi y.
Reliabili y and Validi y Tes
Validi y and eliabili y a e c ucial elemen s when e alua ing an ins umen o mea-
su emen quali y (Kimbe lin and Win e s ein 2008). As he s udy implemen s a ques ion-
nai e as he ins umen o ob ain da a o measu emen and analysis, i s abili y o measu e
consis en ly needs o be examined. Fo his s udy, he assessmen begins wi h e alua ing
he ou e model using PLS-SEM and es ing o indica o eliabili y. Assessmen o he
ou e model suppo s alidi y by p o ing how well each i em ep esen s he unde lying
cons uc s (Joeseph F. Hai e al. 2014). I ems wi h high ou e loadings indica e ha he
i ems a e mo e in common and, he e o e, suppo he alidi y o he cons uc . S udies
by Hai e al. (2014) u he ecommend ha ac o loading should be a leas 0.708 o
he accep able eliabili y o i s i em. Using PLS-SEM, he esul o he ou e loadings can
be ound in Table 15, which shows ha all 11 i ems o he dependen a iables mee he
ecommended alues o o e 0.708, deducing indica o eliabili y o Con inued Adop ion,
Pe cei ed Ease o Use, and Pe cei ed Use ulness. Loadings o i ems o he independen
cons uc s, howe e , showed 5 i ems wi h weake loadings below he cu -o poin o 0.708.
The weake indica o s a e hose unde cons uc s o Inno a i eness (INN1, INN4), Dis-
com o (DIS3, DIS4), and Insecu i y (INS3). Ou o he weak loadings, i em INS3 showed
an unaccep able loading o
−
0.071, he e o e p omp ing he emo al o his i em om he
cons uc be o e p oceeding wi h u he analysis (Joeseph F. Hai e al. 2011). The numbe s
in blue indica ed as highe sco e o Reliabili y and Validi y Tes o indica o s.
Though SPSS’s C onbach’s Alpha was ini ially applied o he pilo es pe o med
in Sec ion 3, s udies by Haji-O hman and Yusu (2022) sugges using PLS-SEM, which
p io i izes he i ems acco ding o hei indi idual eliabili y. This also aligns wi h he
assessmen s ecommended by Hai e al. (2020) based on he esul s o ou e loadings.
Table 15 shows u he eliabili y a e disca ding i em INS3 om he cons uc s and
unning he es using PLS-SEM. All cons uc s adop ed in he ques ionnai es a e ound
o be accep ably eliable wi h C onbach’s Alpha. Howe e , based on composi e eliabili y
alues, he e was a lack o eliabili y ound unde he Insecu i y cons uc , as composi e
eliabili y alues a e accep able o abo e 0.70 (Joeseph F. Hai e al. 2020). Ne e heless,
o his s udy, he eliabili y alue o Insecu i y is accep ed based on C onbach’s Alpha.
Howe e , i is also i al o acknowledge he possibili y o he edundancy o he i ems
should in e nal consis ency esul in alues highe han 0.95. Fo he cons uc s assessed,
he highes eliabili y alues a e he Op imism cons uc s a 0.939, which could be due
o he high numbe o i ems o he cons uc . Ne e heless, he eliabili y o all he
cons uc s is ound o be accep able, and i ems a e usable o u he es ing. In assessing
alidi y, con e gen alidi y was conduc ed using he Sma PLS So wa e o ind ou how
a measu es ha a e expec ed o be heo e ically ela ed co ela e wi h one ano he in
p ac ice. A e age a iance ex ac ed (AVE) is one o he common measu emen s o e alua e
con e gen alidi y. Hai e al. (2014) s a e ha con e gen alidi y is suppo ed when each
i em has ou e loadings abo e 0.70 and when each cons uc ’s a e age a iance ex ac ed
(AVE) is 0.50 o highe . As shown in Table 16, alidi y es ing esul s in all a iables wi h
AVE alues eaching abo e he 0.5 cu -o poin , meaning ha hese cons uc s ha e passed
he alidi y es . High AVE alues o 0.792 o Op imism and 0.778 o Con inued Adop ion
imply ha bo h cons uc s e ealed mo e a iance ins ead o e o s in cons uc s.
Economies 2024,12, 285 24 o 35
Table 15. Ou e loadings esul s o indica o eliabili y.
INN OPT DIS INS PEOU PU CA
INN1 0.674 0.434 −0.043 −0.088 0.398 0.429 0.357
INN2 0.803 0.482 −0.157 −0.285 0.507 0.463 0.438
INN3 0.843 0.396 −0.15 −0.333 0.364 0.452 0.509
INN4 0.697 0.351 −0.062 −0.289 0.253 0.39 0.413
OPT1 0.477 0.868 −0.092 −0.221 0.593 0.5 0.559
OPT2 0.491 0.885 −0.231 −0.313 0.517 0.517 0.598
OPT3 0.516 0.916 −0.187 −0.291 0.537 0.57 0.547
OPT4 0.497 0.879 −0.163 −0.321 0.455 0.497 0.513
OPT5 0.491 0.902 −0.176 −0.307 0.49 0.516 0.537
DIS1 −0.203 −0.209 0.742 0.475 −0.07 −0.139 −0.243
DIS2 −0.071 −0.195 0.85 0.4 −0.102 −0.161 −0.248
DIS3 −0.043 0.02 0.65 0.213 −0.039 −0.109 −0.025
DIS4 −0.05 −0.065 0.618 0.406 0.088 −0.056 −0.086
INS1 −0.222 −0.252 0.504 0.796 −0.154 −0.224 −0.302
INS2 −0.315 −0.286 0.458 0.882 −0.219 −0.302 −0.357
INS3 0.023 0.037 0.182 −0.071 0.121 0.115 0.057
PEOU1 0.476 0.469 −0.059 −0.145 0.803 0.55 0.543
PEOU2 0.387 0.489 −0.059 −0.23 0.896 0.658 0.577
PEOU3 0.49 0.565 −0.125 −0.287 0.91 0.643 0.674
PU1 0.534 0.461 −0.063 −0.322 0.631 0.793 0.603
PU2 0.453 0.459 −0.253 −0.254 0.367 0.743 0.489
PU3 0.447 0.532 −0.161 −0.289 0.64 0.9 0.666
PU4 0.472 0.481 −0.154 −0.275 0.66 0.857 0.64
CA1 0.509 0.558 −0.224 −0.385 0.625 0.648 0.879
CA2 0.466 0.6 −0.203 −0.348 0.678 0.682 0.933
CA3 0.518 0.492 −0.196 −0.309 0.512 0.566 0.8
CA4 0.518 0.533 −0.253 −0.377 0.607 0.682 0.912
Table 16. Reliabili y and alidi y esul s (a e exclusion o indica o INS3).
Cons uc s C onbach’s Alpha CR AVE
Inno a i eness 0.768 0.842 0.574
Op imism 0.939 0.950 0.792
Discom o 0.729 0.810 0.519
Insecu i y 0.708 0.620 0.472
Pe cei ed Ease o Use 0.846 0.904 0.759
Pe cei ed Use ulness 0.846 0.895 0.681
Con inued Adop ion o Cashless Paymen s 0.904 0.933 0.778
Fo nell and La cke (2016) sugges ha disc iminan alidi y is es ablished i a la en
a iable e eals mo e a iance in i s i ems ins ead o o he cons uc s wi hin he same
model. Fo his s udy, he he e o ai –mono ai (HTMT) a io o co ela ion was elied
on in acco dance wi h he c i e ia de eloped by Hensele e al. (2015) o u he assess
o disc iminan alidi y. Nume ous s udies sugges HTMT is he supe io me hod in
pe o ming he analysis wi h highe sensi i i y a es o de ec disc iminan alidi y when
compa ed o he Fo nell and La cke me hod. Hai e al. (2020) ecommend he cu -o
poin s o 0.85 and 0.90 as accep able alues when in e p e ing he esul s o HTMT. As
shown in Table 17 o HTMT esul s, all alues a e below he ecommended alue o 0.90,
which con i ms ha all cons uc s ha e accep able le els o disc iminan alidi y.
Economies 2024,12, 285 31 o 35
main ain and boos his end, se ice p o ide s should ocus on inc easing awa eness
and unde s anding o cashless paymen s, ensu ing obus secu i y measu es, and add ess-
ing use s’ conce ns abou aud and iden i y he . By imp o ing consume knowledge
and con idence, p o ide s can suppo he con inued g ow h and accep ance o cashless
paymen sys ems.
7. Conclusions and Recommenda ions
7.1. Conclusions
This esea ch sough o e alua e he accep ance and eadiness o B unei’s wo king
popula ion owa d cashless paymen s ollowing he COVID-19 pandemic and o examine
he ends in luencing he con inued adop ion o cashless ansac ions in he coun y. As
B unei ansi ions o an endemic s age, he emphasis on echnology adop ion has shi ed
om heal h- ela ed “push ac o s” o use -d i en “pull ac o s” based on p e e ences and
pe cei ed bene i s.
The s udy’s indings indica e ha di e en dimensions o Technology Readiness
a ec Pe cei ed Use ulness and Pe cei ed Ease o Use in dis inc ways. Inno a i eness
posi i ely impac s bo h Pe cei ed Use ulness and Ease o Use, while Op imism in luences
Pe cei ed Ease o Use alone. In con as , he dimensions o Discom o and Insecu i y do
no signi ican ly impac Pe cei ed Use ulness o Ease o Use, which challenges p e ious
esea ch indings.
In conclusion, unde s anding how pe sonali y ai s in luence Technology Accep ance
is c ucial. Se ice p o ide s should ac o hese ela ionships in o he de elopmen and
implemen a ion o cashless paymen sys ems. S a egies should be de ised o enhance o
main ain Technology Readiness acco ding o use s’ pe sonali ies, as hese ai s signi ican ly
impac adop ion and usage. Consume accep ance is essen ial o planning and in es ing
in new echnologies, gi en he subs an ial ime and cos in ol ed o se ice p o ide s.
The ongoing adop ion o cashless paymen s b ings no able bene i s, pa icula ly o he
banking sec o , such as educed ope a ing cos s. The g ow h o cashless b anches in B unei
e lec s inc easing consume engagemen wi h cashless ansac ions and unde sco es he
b oade shi owa ds a cashless economy.
7.2. Recommenda ions
I is impo an o ecognize ha some consume s in B unei emain hesi an abou
he cu en cashless paymen op ions a ailable in he ma ke . Unde s anding indi iduals’
abili y o lea n, accep , and e en ually adap o new echnology is c ucial. Du ing he
COVID-19 pandemic, he B unei go e nmen accele a ed he shi owa ds a cashless econ-
omy due o mo emen es ic ions and s anda d ope a ing p ocedu es (SOPs) implemen ed
o p o ec he popula ion om he in ec ious disease. Va ious o ganiza ions, including
go e nmen -linked companies, banks, se ice p o ide s, and businesses, adop ed di e en
s a egies o aise awa eness abou cashless paymen s, helping use s g adually lea n and
adap o hese sys ems h ough campaigns and in o ma ional e o s.
F om wo pe spec i es—o ganiza ions and consume s— he adop ion o cashless pay-
men s p esen s di e en conside a ions. Fo consume s, he use o physical c edi o debi
ca ds emains a undamen al op ion o cashless ansac ions, bu i may no be uni e -
sally p e e ed. Conce ns abou secu i y and he po en ial comp omise o p i a e and
con iden ial in o ma ion pe sis , a ec ing he con inued adop ion o cashless paymen s.
Recognizing ha e en basic cashless paymen modes like c edi o debi ca ds can e oke
insecu i y, i is c ucial o majo p o ide s such as banks and in ech companies o en-
hance he sa e y and e iciency o inancial ansac ions. This can be achie ed by educing
consume insecu i y h ough obus aud de ec ion, secu e au hen ica ion p ocesses in-
cluding biome ics, and p o ec i e measu es such as ansac ion limi s. Employing eliable
hi d-pa y secu e paymen sys ems can also bols e consume con idence.
Awa eness and knowledge abou he bene i s o cashless paymen s—such as Ease o
Use and Use ulness—a e essen ial in no only eassu ing exis ing use s bu also encou aging
Economies 2024,12, 285 32 o 35
hose who ha e no ye adop ed hese me hods. By combining inc eased secu i y measu es
wi h educa ional e o s, o ganiza ions can enhance consume con idence and d i e g ea e
adop ion o cashless paymen s. To suppo his, a p oposed amewo k o he con inued
adop ion o cashless paymen s, based on use accep ance and eadiness, is sugges ed
(see Figu e 8). This amewo k could se e as a e e ence o u u e s udies and guide
o ganiza ions in os e ing he con inued use o cashless paymen s in B unei. Wi h ongoing
ini ia i es by he go e nmen and a ious o ganiza ions, B unei’s cashless ansac ion
ma ke is poised o signi ican g ow h, con ibu ing o he ealiza ion o he Sma Na ion
Agenda and Wawasan 2025.
Economies 2024, 12, x FOR PEER REVIEW 33 o 37
ongoing ini ia i es by he go e nmen and a ious o ganiza ions, B unei’s cashless ans-
ac ion ma ke is poised o signi ican g ow h, con ibu ing o he ealiza ion o he Sma
Na ion Agenda and Wawasan 2025.
Con inued Adop ion o Cashless Economy
Consume Accep ance
1) Consume p o ec ion
2) Secu i y le els o he cashless paymen s se ice p o ide on he con iden iali y o pe sonal in o -
ma ion and con iden deli e y o consume paymen ins uc ion
Consume s Readiness
1) Knowledge and educa ion on cashless paymen s (awa eness, no i ica ion, ma ke ing p omo ion, o campaigns)
Go e nance
- key egula o y and legisla i e
Ini ia i es os e ing he
con inued ansi ion o cashless
o digi al paymen s
- Role o s akeholde s in
enabling cashless socie ies
- Focusing on
Consume p o ec ion,
inno a ion, esilience, secu ed
Technology
In eg al cashless paymen
expe iences
and sys ems
Cul u e (cash and cashless
p ac ices)
- B unei demog aphic
- Popula ion Habi s and
adi ions (such as e-zaka s.
physical zaka )
- Popula ion us in he
go e nmen ini ia i es o
digi aliza ion
- Financial inclusion (including
unbanked indi iduals)
Figu e 8. Sugges ed cashless economy amewo k.
Au ho Con ibu ions: Concep ualiza ion, me hodology, unding acquisi ion, H.S.; so wa e, ali-
da ion, N.T.; o mal analysis, F.I.; in es iga ion, esou ces, da a cu a ion, A.K.S.S.; w i ing—o iginal
d a p epa a ion, w i ing— e iew, and edi ing, D.S.; isualiza ion, supe ision, p ojec adminis a-
ion, L.F.Y. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding: Uni e si i Teknologi B unei (UTB) Special Resea ch G an Re e ence Numbe :
UTB/GSR/1/2024 (10).
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : The da a p esen ed in his s udy a e a ailable on eques om he
co esponding au ho due o con iden iali y p i acy conce ns, e hical es ic ions, and p op ie a y
in o ma ion easons.
Acknowledgmen s: He u Susan o (H.S.) is he Main Con ibu o and Lead Au ho . The emaining
a e con ibu o s: Noo Tam ini (N.T.), Fahmi Ib ahim (F.I.), Ali ya Kayla Sha a Susan o (A.K.S.S.),
Desi Se iana (D.S.), and Leu Fang Yie (L.F.Y). We would like o hank o he pa ies ha di ec ly and
indi ec ly suppo ed his esea ch h ough he Cen e o In e na ional Resea ch Collabo a ion, in-
cluding he School o Business, Uni e si i Teknologi B unei, B unei Da ussalam, he Cybe Secu i y
Figu e 8. Sugges ed cashless economy amewo k.
Au ho Con ibu ions: Concep ualiza ion, me hodology, unding acquisi ion, H.S.; so wa e, alida-
ion, N.T.; o mal analysis, F.I.; in es iga ion, esou ces, da a cu a ion, A.K.S.S.; w i ing—o iginal
d a p epa a ion, w i ing— e iew, and edi ing, D.S.; isualiza ion, supe ision, p ojec adminis a-
ion, L.F.Y. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding: Uni e si i Teknologi B unei (UTB) Special Resea ch G an Re e ence Numbe : UTB/GSR/1/
2024 (10).
In o med Consen S a emen : No applicable.
Economies 2024,12, 285 33 o 35
Da a A ailabili y S a emen : The da a p esen ed in his s udy a e a ailable on eques om he
co esponding au ho due o con iden iali y p i acy conce ns, e hical es ic ions, and p op ie a y
in o ma ion easons.
Acknowledgmen s: He u Susan o (H.S.) is he Main Con ibu o and Lead Au ho . The emaining a e
con ibu o s: Noo Tam ini (N.T.), Fahmi Ib ahim (F.I.), Ali ya Kayla Sha a Susan o (A.K.S.S.), Desi
Se iana (D.S.), and Leu Fang Yie (L.F.Y). We would like o hank o he pa ies ha di ec ly and indi-
ec ly suppo ed his esea ch h ough he Cen e o In e na ional Resea ch Collabo a ion, including
he School o Business, Uni e si i Teknologi B unei, B unei Da ussalam, he Cybe Secu i y Resea ch
G oup, he Na ional Resea ch and Inno a ion Agency, Indonesia and Tunghai Uni e si y, Taiwan.
Con lic s o In e es : The au ho s decla e no con lic o in e es .
Re e ences
Abdul-Halim, Nu ul Ain, Ali Va aei-Zadeh, Hani uzila Hani ah, Ai PingTeoh, and Khaled Nawase . 2022. Unde s anding he
de e minan s o e-walle con inuance usage in en ion in Malaysia. Quali y and Quan i y 56: 3413–39. [C ossRe ] [PubMed]
Ahuja, Anjali, and Richa Joshi. 2018. Cus ome Pe cep ion owa ds Mobile Walle . IJRDO-Jou nal o Business Managemen 4: 52–60.
Ansha i, Muhammad, Muni ah Ajee ah A ine, No zaidah Nu hidayah, Hidaya ul Aziyah, and Md Hasnol Alwee Salleh. 2021. Fac o s
in luencing indi idual in adop ing eWalle . Jou nal o Financial Se ices Ma ke ing 26: 10–23. [C ossRe ]
A i u ha, Anupong, Ra ipa Ak ajindanon, Supawadee Hamanee, Racha a Rung akulchai, Wo adech Na K om, and Mada Chaya a o.
2020. The Pe cep ion and A i ude o Consume s owa d he In en ion o Use Digi al Paymen Sys em in Cashless Socie y E a in
Thailand. Jou nal o Resea ch and De elopmen Ins i ude 7: 1–14.
Balak ishnan, Vimala, and No Liyana Mohd Shuib. 2021. D i e s and inhibi o s o digi al paymen adop ion using he Cashless
Socie y Readiness—Adop ion model in Malaysia. Technology in Socie y 65: 101554. [C ossRe ]
Blu , Ma kus, and Cheng Wang. 2020. Technology eadiness: A me a-analysis o concep ualiza ions o he cons uc and i s impac on
echnology usage. Jou nal o he Academy o Ma ke ing Science 48: 649–69. [C ossRe ]
Bush, Thomas. 2020. Desc ip i e Analysis: How-To, Types, Examples. Re ie ed om Pes le Analysis. A ailable online: h ps://
pes leanalysis.com/desc ip i e-analysis/#measu es_o _cen al_ endency (accessed on 20 Augus 2024).
Chan, Ka Hoong, TuanHock Ng, and HweeYee Ng. 2020. A e Malaysians Ready o he Cashless Socie y? E idence om Malaysia’s
Unde g adua es. Global Business and Managemen Resea ch: An In e na ional Jou nal 12: 78–89.
Chen, Shih-Chih, Shing-Han Li, and Chien-Yi Li. 2012. Recen Rela ed Resea ch in Technology Accep ance Model: A Li e a u e Re iew.
Aus alian Jou nal o Business and Managemen Resea ch 1: 124–27. [C ossRe ]
Chin, Wynne W. 1998. The pa ial leas squa es app oach o s uc u al equa ion modeling. Mode n Me hods o Business Resea ch 295:
295–336.
Dabholka , P a ibha, and Richa d Bagozzi. 2002. An A i udinal Model o Technology-Based Sel -Se ice: Mode a ing E ec s o
Consume T ai s and Si ua ional Fac o s. Jou nal o The Academy o Ma ke ing Science 30: 184–201. [C ossRe ]
Da is, F ed D. 1989. Pe cei ed Use ulness, Pe cei ed Ease o Use, and Use Accep ance o In o ma ion Technology. MIS Qua e ly 13:
319–40. [C ossRe ]
De Vaus, Da id. 2001. Resea ch Design in Social Resea ch. Thousand Oaks: Sage Publica ions, pp. 1–296.
Digi al Economy Council. 2020. Digi al Economy Mas e plan 2025; Banda Se i Begawan: Digi al Economy Council, B unei Da ussalam,
pp. 1–23. A ailable online: h p://www.m ic.go .bn/DE2025/documen s/Digi alEconomyMas e plan2025.pd (accessed on 20
Augus 2024).
E do
ˇ
gmu, Niha , and Mu a Esen. 2011. An in es iga ion o he e ec s o echnology eadiness on echnology accep ance in e-HRM.
P ocedia—Social and Beha io al Sciences 24: 487–95. [C ossRe ]
Fab is, Nikola. 2019. Cashless Socie y—The Fu u e o Money o a U opia? Jou nal o Cen al Banking Theo y and P ac ice 8: 53–66.
[C ossRe ]
Filipiak, Pio . 2020. COVID-19: The Vi al Sp ead o Cashless Socie y? A ailable online: h ps://www. .com/pa ne con en /
coma ch/co id-19- he- i al-sp ead-o -cashless-socie y.h ml (accessed on 20 Augus 2024).
Fo nell, Claes, and Da id F. La cke . 2016. E alua ing s uc u al equa ion models wi h unobse able a iables and measu emen e o .
Jou nal o Ma ke ing Resea ch This 18: 39–50. [C ossRe ]
G20 I alian P esidency. 2021. The Impac o COVID-19 on Digi al Financial Inclusion. Singapo e: Global Pa ne ship o Financial Inclusion
(GPFI) by he Wo ld Bank, pp. 1–29.
Geo ge, Da en, and Paul Malle y. 2003. SPSS o Windows S ep-by-S ep: A Simple Guide and Re e ence, 14.0 upda e (7 h ed.). Bos on: Allyn
& Bacon. A ailable online: h p://www.unesdoc.unesco.o g/a k:/48223/p 0000387364/PDF/387364eng.pd .mul i (accessed on
15 Augus 2024).
Ghasemi, Asgha , and Saleh Zahediasl. 2012. No mali y es s o s a is ical analysis: A guide o non-s a is icians. In e na ional Jou nal
o Endoc inology and Me abolism 10: 486–89. [C ossRe ]
Godoe, P eben, and T ond S illaug Johansen. 2012. Unde s anding adop ion o new echnologies: Technology eadiness and echnology
accep ance as an in eg a ed concep . Jou nal o Eu opean Psychology S uden s 3: 38. [C ossRe ]
Economies 2024,12, 285 34 o 35
Hai , Joe F., Ch is ian M. Ringle, and Ma ko Sa s ed . 2011. PLS-SEM: Indeed a Sil e Bulle . Jou nal o Ma ke ing Theo y and P ac ice 19:
139–52. [C ossRe ]
Hai , Joe F., Ma ko Sa s ed , Lucas Hopkins, and Volke G. Kuppelwiese . 2014. Pa ial leas squa es s uc u al equa ion modeling
(PLS-SEM): An eme ging ool in business esea ch. Eu opean Business Re iew 26: 106–21. [C ossRe ]
Hai , Joe F., Ma hew C. Howa d, and Ch is ian Ni zl. 2020. Assessing measu emen model quali y in PLS-SEM using con i ma o y
composi e analysis. Jou nal o Business Resea ch 109: 101–10. [C ossRe ]
Haji-O hman, Yusu , and Mohd Sholeh Sheh Yusu . 2022. Assessing Reliabili y and Validi y o A i ude Cons uc Using Pa ial Leas
Squa es S uc u al Equa ion Modeling (PLS-SEM). In e na ional Jou nal o Academic Resea ch in Business and Social Sciences 12:
378–85. [C ossRe ]
Heale, Robe a, and Alison Twyc oss. 2015. Validi y and eliabili y in quan i a i e s udies. E idence-Based Nu sing 18: 66–67. [C ossRe ]
[PubMed]
Hensele , Jö g, Ch is ian M. Ringle, and Ma ko Sa s ed . 2015. A new c i e ion o assessing disc iminan alidi y in a iance-based
s uc u al equa ion modeling. Jou nal o he Academy o Ma ke ing Science 43: 115–35. [C ossRe ]
Humbani, Michael, and Melanie Wiese. 2018. A Cashless Socie y o All: De e mining Consume s’ Readiness o Adop Mobile Paymen
Se ices. Jou nal o A ican Business 19: 409–29. [C ossRe ]
Jain, Vishal, and Pa ul Jain. 2017. A Jou ney owa ds a Cashless Socie y. In Banking Sec o in Oman: S a egic Issues, Challenges and
Fu u e Scena ios. Musca : College o Banking and Financial S udies, pp. 61–72.
Ka im, Fazida, and No hilmi Muhammad. 2022. Con inuance In en ion on Mobile Walle : In eg a ed Technology Readiness and
Expec a ion-Con i ma ion Model Analysis. Jou nal o Tianjin Uni e si y Science and Technology 55: 107–31. [C ossRe ]
Khalid, Khawaja, Haim Hilman, and Dileep Kuma . 2012. Ge along wi h quan i a i e esea ch p ocess. In e na ional Jou nal o Resea ch
in Managemen 2: 15–29.
Kimbe lin, Ca ole L., and Almu G. Win e s ein. 2008. Validi y and eliabili y o measu emen ins umen s used in esea ch. Ame ican
Jou nal o Heal h-Sys em Pha macy 65: 2276–84. [C ossRe ]
Kını¸s, Fa ma, and Cem Tano a. 2022. Can I T us My Phone o Replace My Walle ? The De e minan s o E-Walle Adop ion in No h
Cyp us. Jou nal o Theo e ical and Applied Elec onic Comme ce Resea ch 17: 1696–715. [C ossRe ]
Ko kowski, Radoslaw, and Michal Polasik. 2021. COVID-19 pandemic inc eases he di ide be ween cash and cashless paymen use s
in Eu ope. Economics Le e 209: 110139. [C ossRe ]
Lin, Chien Hsin, Hsin Yu Shih, and Pe e J. She . 2007. In eg a ing echnology eadiness in o echnology accep ance: The TRAM model.
Psychology and Ma ke ing 24: 641–57. [C ossRe ]
Maqableh, Mahmoud, Ra’ed Moh’d Taisi Masa’deh, Ri a O. Shannak, and Khalid M. Naha . 2015. Pe cei ed T us and Paymen
Me hods: An Empi ical S udy o Ma ka VIP Company. In e na ional Jou nal o Communica ions, Ne wo k and Sys em Science s8:
409–27. [C ossRe ]
Ma coulides, Geo ge A., and Ca ol Saunde s. 2006. Edi o ’s Commen s: PLS: A Sil e Bulle ? MIS Qua e ly 30: iii–ix. [C ossRe ]
Mick, Da id Glen, and Susan Fou nie . 1998. Pa adoxes o echnology: Consume cognizance, emo ions, and coping s a egies. Jou nal
o Consume Resea ch 25: 123–43. [C ossRe ]
Mohd Sapian, Nu syazana, and Si i No ziah Ismail. 2021. The Impac o Using Cashless T ansac ions Among Malaysian Consume s
Towa ds Paymen Sys ems Pe o mance. Resea ch in Managemen o Technology and Business 2: 420–36. A ailable online: h p:
//publishe .u hm.edu.my/pe iodicals/index.php/ m b (accessed on 20 Augus 2024).
Moh’d Taisi Masa’deh, Ra’ed, Ri a O. Shannak, and Mahmoud Mohammad Maqableh. 2013. A s uc u al equa ion modeling
app oach o de e mining an eceden s and ou comes o s uden s’ a i ude owa d mobile comme ce adop ion. Li e Science Jou nal
10: 2321–33.
Pallan , Julie. 2020. SPSS Su i al Manual: A S ep by S ep Guide o Da a Analysis Using IBMSPSS. Maidenhead: McG aw-Hill Educa ion.
Pa asu aman, A. Pa su. 2000. Technology Readiness Index (T i): A Mul iple-I em Scale o Measu e Readiness o Emb ace New
Technologies. Jou nal o Se ice Resea ch 2: 307–20. [C ossRe ]
Pa asu aman, A. Pa su, and Cha les L. Colby. 2015. An Upda ed and S eamlined Technology Readiness Index: TRI 2.0. Jou nal o
Se ice Resea ch 18: 59–74. [C ossRe ]
Rahman, Mah uzu , Izlin Ismail, and Shamshul Bah i. 2020. Analysing consume adop ion o cashless paymen in Malaysia. Digi al
Business 1: 100004. [C ossRe ]
Rou ay, Susmi, Reema Khu ana, Ruchi Payal, and Rakesh Gup a. 2019. A Mo e owa ds Cashless Economy: A Case o Con inuous
Usage o Mobile Walle s in India. Theo e ical Economics Le e s 9: 1152–66. [C ossRe ]
Salman, Mohammad, and Im an Saleem. 2017. Role o Digi al Compe ence in Cashless Economy. IOSR Jou nal o Business and
Managemen (IOSR-JBM) 19: 49–53. [C ossRe ]
Seka an, Uma, and Roge Bougie. 2010. Resea ch Me hods o Business: A Skill Building App oach. Hoboken: John Wiley & Sons.
Sohaib, Osama, Walaya Hussain, Muhammad Asi , Muhammad Ahmad, and Manuel Mazza a. 2020. APLS-SEM Neu al Ne wo k
App oach o Unde s anding C yp ocu ency Adop ion. IEEE Access 8: 13138–50. [C ossRe ]
S ouji, Je emy. 2020. Digi al Paymen s, he Cashless Economy, and Financial Inclusion in he Uni ed A ab Emi a es: Why Is E e yone
S ill T ansac ing in Cash? Jou nal o Risk and Financial Managemen 13: 260. [C ossRe ]
Subawa, Nyoman S i, Ni Komang A is a Dewi, and Adie Wahyudi Ok a ia Gama. 2021. Di e ences o Gende Pe cep ion in Adop ing
Cashless T ansac ion Using Technology Accep ance Model. Jou nal o Asian Finance, Economics and Business 8: 617–24. [C ossRe ]
Economies 2024,12, 285 35 o 35
Ta akol, Mohsen, and Reg Dennick. 2011. Making sense o C onbach’s alpha. In e na ional Jou nal o Medical Educa ion 2: 53–55.
[C ossRe ] [PubMed]
Teo, Siew Chein, Pei Li Law, and Ah Choo Koo. 2020. Fac o s A ec ing Adop ion o E-Walle s Among You hs in Malaysia. Jou nal o
In o ma ion Sys em and Technology Managemen 5: 39–50. [C ossRe ]
Thomas, Hugh. 2013. Exclusi e Insigh s om Mas e Ca d Ad iso s Measu ing P og ess owa d a Cashless Socie y. Pu chase: Mas e Ca d
Ad iso s, pp. 1–5. A ailable online: h p://www.mas e ca dad iso s.com/_asse s/pd /Mas e Ca dAd iso s-CashlessSocie y.
pd (accessed on 20 Augus 2024).
Walczuch, Ri a, Jos Lemmink, and Sand a S eukens. 2007. The e ec o se ice employees’ echnology eadiness on echnology
accep ance. In o ma ion and Managemen 44: 206–15. [C ossRe ]
Wisniewski, Tomasz Pio , Michal Polasik, Radosław Ko kowski, and And ea Mo o. 2021. Swi ching om Cash o Cashless Paymen s
du ing he COVID-19 Pandemic and Beyond. SSRN Elec onic Jou nal, 337–352. [C ossRe ]
Yuso , Nu Ha izah, Muhammad Ridhwan Sa i in, and Azlina Zainal Abidin. 2022. Fac o s In luencing P ac ice o Cashless Pu chase
du ing COVID-19 Mo emen Con ol O de (MCO) in Malaysian Socie y. In e na ional Jou nal o Academic Resea ch in Business and
Social Sciences 12: 702–14. [C ossRe ]
Zamil, Ahmad M. A., Saqib Ali, Pe a Poulo a, and Minhas Akba . 2022. Anounce o p e en ion o a pound o cu e? Mul i-le el
modelling on he an eceden s o mobile-walle adop ion and he mode a ing ole o e-WoM du ing COVID-19. F on ie s in
Psychology 13: 1–18. [C ossRe ]
Disclaime /Publishe ’s No e: The s a emen s, opinions and da a con ained in all publica ions a e solely hose o he indi idual
au ho (s) and con ibu o (s) and no o MDPI and/o he edi o (s). MDPI and/o he edi o (s) disclaim esponsibili y o any inju y o
people o p ope y esul ing om any ideas, me hods, ins uc ions o p oduc s e e ed o in he con en .
