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FINANCIAL CAPABILITY AND TECHNOLOGY IMPLICATIONS FOR ONLINE SHOPPING

Abstract

To promote online shoppers’ long-term interest, consumers need to have the knowledge and ability to avoid problems with fi nancial issues. Financial capability helps to put consumers on the path to a sustainable fi nancial future. However, previous studies only focused on fi nancial capability in a fi nancial context. To handle personal fi nance systematically and successfully in an online setting, this study extends an enhanced understanding of how fi nancial capability on online consumer behaviour. Based on the data of 690 respondents collected by a face-to-face from eight main regions in Albania, this study employed principal components analysis and logistic regression in order to investigate the effect of consumers’ fi nancial capabilities and technology use on the decision to purchase online. The outcome of this study fi rstly identifi es six dimensions of fi nancial capabilities, namely, digital banking usage, fi nancial service risk, fi nancial advice, payment risk, risk tolerance, and fi nancial attitude. Secondly, the fi nding revealed that individuals who use smartphones and administrate a social media account, are more likely to involve in purchasing through online channels. Moreover, the decision to purchase online is more prone for those individuals who manifest high levels in digital banking usage, fi nancial advice, prior bank experience and technology usage, and low levels in attitude towards payment risk and attitude towards risk tolerance. This paper offers useful insights concerning the determinants of online purchasing by combining individuals’ fi nancial capability, technology and social media usage along with its demographic characteristics. In term of practical contribution, this study provides a useful model by incorporating for measuring and managing consumers’ fi nancial capability to enhance their involvement and to reduce their cognitive dissonance in the online shopping context. This study also contributes to the accumulated knowledge and encourages consumers to use digital banking and consult their fi nancial issues when purchasing online.

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FINANCIAL CAPABILITY AND TECHNOLOGY IMPLICATIONS FOR ONLINE SHOPPING

Author: Çera, Gentjan
Publisher: Technická Univerzita v Liberci
Year: 2020
Source: https://dspace.tul.cz/bitstreams/8790517d-3ca2-4101-884f-8f119e2da6f3/download
156 2020, XXIII, 2
Finance
DOI: 10.15240/ ul/001/2020-2-011
FINANCIAL CAPABILITY AND TECHNOLOGY
IMPLICATIONS FOR ONLINE SHOPPING
Gen jan Çe a1, Quyen Phu Thi Phan2, A menia And oniceanu3,
Edmond Çe a4
1 Tomas Ba a Uni e si y in Zlin, Facul y o Managemen and Economics, Czech Republic, ORCID: 0000-0002-9324-181X,
[email p o ec ed];
2 The Uni e si y o Danang, Uni e si y o Economics, Facul y o Ma ke ing, Vie nam, ORCID: 0000-0002-4048-1369,
[email p o ec ed];
3 Bucha es Uni e si y o Economic S udies, In e na ional Cen e o Public Managemen , Romania,
[email p o ec ed];
4 Tomas Ba a Uni e si y in Zlin, Facul y o Managemen and Economics, Czech Republic, ORCID: 0000-0003-3546-2101,
[email p o ec ed].
Abs ac : To p omo e online shoppe s’ long- e m in e es , consume s need o ha e he knowledge
and abili y o a oid p oblems wi h i nancial issues. Financial capabili y helps o pu consume s
on he pa h o a sus ainable i nancial u u e. Howe e , p e ious s udies only ocused on i nancial
capabili y in a i nancial con ex . To handle pe sonal i nance sys ema ically and success ully in
an online se ing, his s udy ex ends an enhanced unde s anding o how i nancial capabili y on
online consume beha iou . Based on he da a o 690 esponden s collec ed by a ace- o- ace
om eigh main egions in Albania, his s udy employed p incipal componen s analysis and logis ic
eg ession in o de o in es iga e he e ec o consume s’ i nancial capabili ies and echnology
use on he decision o pu chase online. The ou come o his s udy i s ly iden i i es six dimensions
o i nancial capabili ies, namely, digi al banking usage, i nancial se ice isk, i nancial ad ice,
paymen isk, isk ole ance, and i nancial a i ude. Secondly, he i nding e ealed ha indi iduals
who use sma phones and adminis a e a social media accoun , a e mo e likely o in ol e in
pu chasing h ough online channels. Mo eo e , he decision o pu chase online is mo e p one o
hose indi iduals who mani es high le els in digi al banking usage, i nancial ad ice, p io bank
expe ience and echnology usage, and low le els in a i ude owa ds paymen isk and a i ude
owa ds isk ole ance. This pape o e s use ul insigh s conce ning he de e minan s o online
pu chasing by combining indi iduals’ i nancial capabili y, echnology and social media usage along
wi h i s demog aphic cha ac e is ics. In e m o p ac ical con ibu ion, his s udy p o ides a use ul
model by inco po a ing o measu ing and managing consume s’ i nancial capabili y o enhance
hei in ol emen and o educe hei cogni i e dissonance in he online shopping con ex . This
s udy also con ibu es o he accumula ed knowledge and encou ages consume s o use digi al
banking and consul hei i nancial issues when pu chasing online.
Keywo ds: Financial capabili y, logis ic eg ession, online shopping, p io bank expe ience,
sma phone, social media.
JEL Classi i ca ion: G53, D91.
APA S yle Ci a ion: Çe a, G., Phan, Q. P. T., And oniceanu, A., & Çe a, E. (2020). Financial
Capabili y and Technology Implica ions o Online Shopping. E&M Economics and Managemen ,
23(2), 156–172. h ps://doi.o g/10.15240/ ul/001/2020-2-011
In oduc ion
The In e ne plays a i al ole in ou daily li e
in ha people can easily access ou wo ld and
open in e na ional bo de s. Meanwhile, online
shopping has been widely accep ed as a way o
pu chasing p oduc s and se ices. I p o ides
a dominan al e na i e o adi ional e ail
shopping. Consume s can sea ch o mo e
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in o ma ion and selec o compa e p oduc
and p ice, mo e op ions, con enience. Online
shopping o e s mo e sa is ac ion o consume s
sa e ime (Ka awe awa aks & Wang, 2011).
Howe e , he in es iga ion o online consume
beha iou is ela i ely unde de eloped
(Smi h e al., 2013). Al hough online shopping
beha iou is no a new opic, he unanswe ed
ques ion ha wha de e mines consume s’
willingness o pu chase a p oduc online ha e
a ac ed many esea che s. In his line o
s udy, esea che s iden i i ed ac o s in l uencing
on pu chase beha iou o he consume based
on Theo y Planned Beha io (Ajzen, 1991),
Technology Accep ance Model (Da is, 1989),
S imulus–O ganism–Response (Meh abian
& Russell, 1974). The i s app oach ocused
on he di ec impac on consume beha iou .
Fo example, Wu and Ke (2015) in eg a ed
a model o pe sonali y ai s, pe cei ed isk
and echnology accep ance in online shopping
beha iou . Ano he app oach ocused on he
indi ec impac o a i ude, us on consume s’
pu chase beha iou (Al-Debei, Ak oush,
& Ashou i, 2015; Belás & Gabčo á, 2016;
Oluwa emi & Adebiyi, 2018). Ne e heless,
bo h app oaches ocus on consume s’
beha iou al in en ion as a p edic o o ac ual
pu chase beha iou . This s udy explo es ( he
di ec impac o consume s’ i nancial capabili y
on hei ac ual pu chase decisions) consume s’
ac ual pu chase decisions and i s an eceden s.
Recen ly, i is acknowledged ha wi h he
ise o se ice deli e y, in gene al, and online
shopping, in pa icula , some o he aspec s
(such as secu i y, us and pe cei ed isk)
ha e become key issues o online beha iou
(Kim, Fe in, & Rao, 2008; Mou, Shin, &
Cohen, 2017; Sil a, Pinho, Soa es, & Sá, 2019;
Suchanek & K alo a, 2018). Howe e , he e is
limi ed a en ion ela ing o consume s’ i nancial
ma e s while many cus ome s ha e had e y
li le unde s anding o i nances, how c edi
wo ks and he po en ial i nancial isk (Lusa di
& Mi chell, 2014).
Unlike p e ious esea ch, his s udy ocuses
on he po en ial e ec o consume i nancial
capabili y on hei online pu chase decisions.
Addi ionally, in he i eld o consume i nance,
p e ious s udies ocused on he in l uence o
i nancial capabili y on consume s’ beha iou
owa d i nancial p oduc s/se ice. In his s udy,
we a gue ha cus ome s’ knowledge and
unde s and abou i nancial ma e s play a i al
ole in hei pu chase decision owa ds all
p oduc s, no only owa ds i nancial p oduc s.
The e o e, in he au ho s’ knowledge, his is
he i s s udy ha in es iga es he ela ionship
be ween consume s’ i nancial capabili y on
consume s’ pu chase decisions gene ally in he
online con ex .
Financial capabili y cap u es people’s
knowledge o i nancial ma e s, hei abili y
o manage hei money and o ake con ol o
hei income. Based on Sen’s capabili y heo y
(1993), i nancial capabili y e e s o he abili y
o ac (e.g. people’s knowledge, skills, a i udes,
habi s, mo i a ions, con i dence and sel -
e i cacy), and oppo uni y o ac (e.g. people’s
awa eness o basic i nancial p oduc s hey need
o manage hei money li es) (Colla d, 2019).
P e ious s udies o i nancial capabili y used
specialis su eys (A kinson, McKay, Kempson,
& Colla d, 2006; Kempson, Colla d, & Moo e,
2005; Taylo , 2011). Adop ing Sen’s capabili y
heo y (1993), ou pape ex ends exis ing
knowledge abou he po en ial app oach
o measu ing key componen s o i nancial
capabili y ha ela e o consume s’ knowledge,
a i udes owa d isk and i nancial ma e s,
i nancial managemen using esponses o
su ey ques ions in a bank su ey abou
consume s’ ac ual shopping beha iou . While
mos o he p e ious s udies me ely ocused on
i nancial capabili y in i nancial decision making,
his esea ch makes an impo an con ibu ion
o he cu en li e a u e by ex ending ou
knowledge o i nancial capabili y on consume
online shopping decision making.
In addi ion, o s udy he online shopping
opic, echnology and social media usage ha e
come in o he schola s’ a en ion (Hube , Blu ,
B ock, Backhaus, & Ebe ha d , 2017; Pucci,
Casp ini, Nosi, & Zanni, 2019). To be able o
p edic he e ec s o echnology usage on
online pu chasing, p e ious s udies o en
explo ed he accep ance o echnology (Hube
e al., 2017); and se e al s udies ocused on
speci i c echnologies such as a sma phone
(Vo opano a, 2015), social media (Mikale ,
Giannakos, & Pa eli, 2013). Howe e , less
is known abou he easons ha in l uence
consume s’ ac ual online shopping abou he
wide anges o echnologies a ailable o hem
in hei e e yday li es. This s udy ocuses on
wo ypes o echnologies, namely, sma phone
and social media. Addi ionally, excep o
age, gende , income, occupa ion as con ol
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a iables, his s udy explo es he impac o o he
demog aphic (e.g. p io banking expe ience) on
online shopping. The widesp ead adop ion o he
banking sec o is s ongly linkage in he o e all
online en i onmen (Hamidi, Rad, & Jahany,
2012), cus ome wi h mo e banking expe ience
end o choose he In e ne as a pla o m o
shopping. Howe e , he impac o p io banking
expe ience on ac ual online pu chase has no
been ho oughly in es iga ed. The cu en s udy
also i lls his gap in he li e a u e.
Fu he mo e, mos o he s udies in online
shopping pi o ed on he de eloped coun ies’
ma ke s. Ve y limi ed esea ch has been
conduc ed in he con ex o in es iga ing online
consume beha iou ac oss ansi ion coun ies.
Obli iously, di e en online ac o s in l uence
online consume s’ beha iou depending on
he en i onmen o di e en egions. Albania
is one o he ansi ion coun ies and Albania
consume s a e mo e l exible. A epo o
In o ma ion and Communica ion Technology
(ICT) in Albania (2019) showed ha online
pu chases a e ca ied ou by 10.1% o he
popula ion aged 16–74 yea s old. Howe e ,
i is in e es ing ha mo e han 90% o he
ansac ion in Albania wi ness cash ansac ion
and a big chunk o he popula ion does no ha e
a bank accoun . This leads a doub ha a low
c edi ca d usage in Albania is he unde lying
eason o a low online pu chasing powe . This
s udy a gues ha consume s may be mo i a ed
online shopping by hei i nancial knowledge
and abili ies in a oiding p oblems wi h i nancial
issues. Fo hese easons, i is aluable o ocus
on he analysis o online consume s in Albania
unde he impac o i nancial capabili ies.
Based on he abo e gaps, his s udy
ocused on wo main objec i es. Fi s , wi h
he Sen’s capabili y heo y (1993), his s udy
iden i i es a iables in he bank su ey o
online consume s ha a e ele an o h ee
key con ibu o y ac o s in i nancial capabili y –
knowledge, a i ude, and money managemen .
Then, his s udy in es iga es he e ec o hese
dimensions on online shopping. Secondly, his
s udy examines he impac s o echnology
usage (e.g. social media, sma phone) and
p io bank expe ience on consume s’ ac ual
shopping beha iou in a ansi ion coun y
con ex , e.g. Albanian.
This s udy makes signi i can con ibu ions
o he ex an li e a u e. Fi s ly, his s udy
con ibu es o he li e a u e o online consume
beha iou by explo ing he po en ial ole o
i nancial capabili y, echnology usage, and p io
bank expe ience on ac ual shopping beha iou .
This s udy also con ibu es o he li e a u e
o i nancial capabili y by using a unique se
o a iables o measu e i nancial capabili y.
This can be in o ma i e o online endo s
o de elop e ec i e i nancial s a egies o
help ackle consume i nancial ma e s when
shopping online.
Nex pa o his pape is dedica ed o he
li e a u e e iew and hypo heses de elopmen .
Fu he pa desc ibes da a collec ion, a iable
measu emen and he used me hod. The
esul s a e analysed and in e p e ed unde
he sec ion named ‘ esul s’. Then, ou i ndings
a e discussed. A he end o he pape , he
conclusions a e p esen ed.
1. Theo e ical Backg ound
Consume s always i nd ou hei bes decisions
gi en ha hey ha e a limi ed budge o money.
While pu chasing p oduc s/se ice om a shop,
consume s ha e o spend bo h money and ime.
Wi h he phenomenon o In e ne shopping
oday, he ime cos has almos elimina ed.
Howe e , as uly s a ed ha no hing comes
wi hou a cos in business. When consume s
ha e unlimi ed choice, hey spend a lo o ime
wi hou making any i nal decision. The bigges
eason is ha he e is no “ ouch and eel
ac o ” in an online shopping con ex , he e o e,
consume s a e based on he p ice in hei
pu chase. Meanwhile, hey eel no sa e when
pu chasing p oduc s ia c edi ca ds (Bilgihan
& Kandampully, 2016). Gene ally, mos s udies
poin ed ou ha i nancial issues ( i nancial isk,
how o use a c edi ca d, how o spend money
o pu chase among unlimi ed choice) always
a e consume s’ issues when pu chasing online.
Financial capabili y is a ela i ely new
cons uc eme ged in he las decade.
Acco ding o Sen’s capabili y heo y (1993),
i nancial capabili y e e s o people’s abili y wi h
he igh so s o knowledge, skills, a i ude,
habi s, mo i a ion, as well as hei oppo uni y
owa d accessing he basic i nancial p oduc s
and se ice ha a e equipped o manage
hei i nancial ma e s. Simila i y, Taylo (2011)
de i ned ha i nancial capabili y e e s o
people’s knowledge o manage and ake con ol
o hei i nances. This concep men ions making
app op ia e i nancial decisions, unde s anding
how o con ol c edi and deb , and iden i ying
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p oduc s and se ices ha a e app op ia e
(Xiao, Chen, & Chen, 2014). Howe e , Despa d
and Chowa (2014) poin ed ou ha he concep
o i nancial capabili y and i nancial li e acy
a e o en unde s ood in e changeably. While
Hus on (2010) de i ned i nancial li e acy as
he desc ip ion o i nancial knowledge, McKay
(2011) desc ibed ha i nancial capabili y
ocuses on i nancial beha iou and e l ec s o
pu ing i nancial knowledge in o ac ion, which
is linked wi h Hus on’s (2010) de i ni ion. In i s
glance, bo h o de i ni ion, i nancial capabili y
and i nancial li e acy a e simila ways (Çe a &
Tuzi, 2019; Nguyen & Rozsa, 2019; Shk a chuk
& Sla ’yuk, 2019). Howe e , She aden (2013)
indica ed ha i nancial li e acy assumes ha
indi iduals all ha e equal chances o enhance
i nancial knowledge and skills, bu he i nancial
capabili y assumes ha no all may ha e he
same chances. Addi ionally, i nancial capabili y
is o med h ough in e ac ion wi h and eedback
om he en i onmen . In he online con ex ,
consume s’ i nancial knowledge and skills
a e shaped in online communi ies. The e o e,
based on Sen’s capabili y heo y (1993), he
concep o i nancial capabili y ha is de i ned
as consume s’ knowledge, a i ude and hei
i nancial managemen in his s udy.
Some schola s ha e de eloped he
concep ual model and empi ical es s o
i nancial capabili y. The i s s udy o i nancial
capabili y was conduc ed by he Financial
Se ices Au ho i y (FSA) in he UK (A kinson
e al., 2006). This esea ch iden i i ed i e
di e en cons uc s o i nancial capabili y, such
as: (1) making ends mee : educe p oblems
in i nancial obliga ions, (2) managing money:
keeping ack wi h con ol an o e iew o
expenses, (3) planning ahead: being u u e-
o ien ed, (4) selec ing p oduc s, e.g. deciding
easonably in i nancial ma e s, and (5) s aying
in o med, e.g. sea ching in o ma ion abou
i nancial p oduc s. All ac o s we e desc ibed
closely wi h i nancial beha iou s. Then, Taylo
(2011) de eloped a measu emen o i nancial
capabili y based on a combina ion o beha iou
and ou come cons uc s. Speci i cally, he
explo ed se en a iables in i nancial capabili y.
The e a e ou s a emen s o i nancial
ou comes, such as (1) di i cul ies in spending
accommoda ion, (2) bo owing o mee ing
housing paymen s, (3) make cu back, (4) ound
you sel o wo mon hs behind wi h you en /
mo gage, (6) Would you say ha you a e be e
o , wo se o o abou he same i nancially
han you we e a yea ago? Addi ionally, he e
a e wo s a emen s o i nancial beha iou s,
such as: (5) how well would you say you a e
managing i nancially hese days, and (7) “sa e
any amoun o you income”. Fu he mo e, Xiao
e al. (2014) measu ed i nancial capabili y wi h
h ee cons uc s, pe cei ed i nancial capabili y,
i nancial li e acy, and i nancial beha iou .
Despa d and Chowa (2014) examined i nancial
li e acy and i nancial inclusion as a combina ion
o i nancial capabili y. The s udy is o ex end
exis ing knowledge abou po en ial ways
o measu ing key componen s o i nancial
capabili y ha ela ed o consume s’ knowledge
and unde s anding o i nancial ma e s, including
hei abili y o ake con ol abou i nances, hei
a i ude o i nancial isk (Taylo , 2011), hei
knowledge abou i nancial p o ide s, as well
as i nancial counsello s (in o mal sou ce, e.g.
amily, iends, newspape ; and o mal sou ce,
e.g., i nancial ad iso , banke ) ha hey use
o gain i nancial knowledge (Vy yan, Blue, &
B imble, 2014).
Consume s oday a e inc easing he
use o online and digi al en i onmen s o
shopping and making i nancial ansac ions
unde an unce ain y en i onmen . The
inc ease in In e ne access and he g ow h
o In e ne banking ha e led o a d ama ic
ise in pu chasing goods and se ices on
he In e ne (MCEETYA, 2011). Consume s
a e esponsible o making decisions in he
online con ex . They need o enhance hei
capabili ies in sol ing hei i nancial issues
and plan o needs and wan s. Lam and Lam
(2017) a gued ha consume s ha a e mo e
likely o ake con ol o hei i nancial si ua ion
e l ec hei buying beha iou and expendi u es.
Du oy, Go se and Lejoyeux (2014) no ed ha
schola s should ocus on consume s’ i nancial
beha iou in online consume beha iou
because o di e en In e ne - ela ed beha iou s
and o l
ine shopping. Shopping on he In e ne
is highly isky ega ding he paymen p ocess
ia e-banking. Cus ome may ace secu i y
and p i acy p oblems on he In e ne . These
isks may inc ease because consume s a e
conce ned abou he secu i y o ansmi ing
c edi ca d in o ma ion h ough he In e ne .
Addi ionally, o gain i nancial knowledge,
mos consume s base on a la ge amoun o
in o ma ion and ad ice consul an s, consis ing
o in o mal sou ces (i.e. amily, iends) o
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160 2020, XXIII, 2
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o mal sou ces (i.e. i nancial ad iso s o
banke s) be o e conduc ing hei pu chasing
decisions (MCEETYA, 2011). Based on he
abo e discussion, he hypo hesis is:
H1: Consume s’ i nancial capabili y a ec s
online shopping.
A majo conce n among all in e ne
consume s is ha hey mus ace a highe
isk han adi ional shopping i hey a e using
s olen c edi ca ds o audulen epudia ion o
he online pu chase. Banks mus adjus hei
p io i ies o espond o his ans o ma ional shi
in he way consume s do hei banking, gi en
ha he use can economize on ime and e o .
Al hough cus ome s can selec he cash on
deli e y (COD) in online pu chasing; howe e ,
Hamidi e al. (2012) indica ed ha e-banking has
p ominen ly impac ed consume s’ pu chasing
beha iou . He explained ha cus ome s can
use online banking o making ansac ions
by debi ca d o c edi ca d, e en when hey
ha e no eady cash as long as hey ha e hei
mobile line linked o hei bank accoun (Belás,
Cipo o á, & Demjan, 2014; Negash, Meso, &
Wi edu, 2011). The e is no doub abou he ole
o e-banking ha is g ea ly a ec ing consume s’
pu chase decisions. Consume s who ha e
expe ience in he online paymen p ocess ha e
splendidly inc eased he way people pay o
hei bills. Based on he abo e discussion, we
a gue ha cus ome s who ha e expe ience in
bank usage a e much mo e com o able wi h
online banking in online shopping. The e o e,
we hypo hesize ha :
H2: Indi iduals’ p io bank expe ience
posi i ely in l uences online shopping.
Social media and sma phone change bo h
he way consume s in e ac and consume
in o ma ion and how companies communica e
wi h consume s and deli e hei se ices.
When consume s ha e begun using In e ne -
enabled mul i-de ices and social ne wo king
si es, he e has been a conside able inc ease
and ans e in online shopping beha iou
(Wagne , Sch amm-Klein, & S einmann, 2013).
Fi s o all, he phenomenon o social media
has undamen ally changed how many people,
communi ies and companies communica e
and in e ac . Kaplan and Haenlein (2010)
de i ned social media as “a g oup o In e ne -
based applica ions ha build on he ideological
and echnological ounda ions o Web 2.0,
and allow he c ea ion and exchange o use
gene a ed con en ”. In he a ea o business,
social media has opened up a new a ea o
elec ic comme ce, called social comme ce,
which changes he manne we de i ne online
shopping. Social comme ce is o med on
di e en ypes o social media, such as
Facebook, Ins ag am, You ube, and Twi e .
Social media ha e undamen ally changed he
consume decision p ocess when i p o ides
pe sonalized se ice and p oduc deli e y
based on consume p e e ences, in e es , and
in e ac ions wi h o he consume s and iends
(Gib eel, AlO aibi, & Al mann, 2018). P e ious
s udies indica ed ha one o he easons why
consume s go shopping is due o he enjoymen
which he social in e ac ion p o ides (Mikale
e al., 2013). When use s log on he social
media pla o m, hey ha e he oppo uni y o
explo e he b and pages, commen s, sha es
a pho o, o expe ience (La oche, Habibi,
& Richa d, 2013). Fo ins ance, consume
e iews a e widely a ailable o p oduc s and
se ices on he social media pla o m, helps
consume s in hei pu chasing decisions (Pan
& Chiou, 2011).
A he same ime, sma phones a e also
he p edominan d i e o g ow h o mobile
e-comme ce ansac ions. Mo e han a hi d
o all e-comme ce ansac ions a e pe o med
ia mobile de ices nowadays (CRITEO,
2018). Consume s use a sma phone
o pu chase p oduc and se ices o e
a wi eless elecommunica ion ne wo k
(Hube e al., 2017). Consume s can pe o m
a pu chase online using hei mobile de ice.
A epo indica ed ha consume s who ha e
sma phones a e mo e likely o shopping han
o he s who don’ use a sma phone (Shech e ,
2017). In ac , consume s can access he
se ice h ough he e- e aile s om a compu e
o by using hei mobile phones o download
ee apps (called as m-comme ce), which o e s
he same unc ionali ies as he websi e. They
can pu chase p oduc s h ough he mobile app
and hen collec hem in he closes s o e. On
he o he hand, consume s a e b owsing and
buying ac oss all channels and mo e ac i e
on mobile de ices han e e (CRITEO, 2018).
Based on he line o a gumen , we hypo hesize
ha :
H3: Consume s who ha e social media
accoun ha e highe chances o pu chase
online.
H4: Indi iduals who use a sma phone ha e
highe chances o pu chase online.
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2. Resea ch Me hodology
The uni o analysis in he cu en esea ch
is an indi idual who uses o has ied online
shopping. The da a used in his a icle we e
collec ed by a ace- o- ace in e iew su ey,
which was conduc ed in eigh main egions
in Albania du ing sp ing 2018. Random ou e
and las bi hday me hod we e applied in he
p ocess o he esponden ’s selec ion. Only 690
esponden s ou o all success ul in e iews
o he su ey we e conside ed o u he da a
p ocessing.
Online shopping was he dependen
a iable employed in his esea ch measu ed
as a single-i em: I use o ha e ied online
shopping. I akes wo possible alues: 1 = yes,
o 0 = no, making i a dicho omous a iable.
The measu emen ype o his a iable limi s he
s a is ical me hod ha should be pe o med o
explo e he de e minan s o indi iduals’ online
pu chase decision. Hal o he esponden s
(52.2%) used o ha e ied online shopping.
P io bank expe ience was measu ed
as he numbe o yea s one was a clien o
a bank (ca ego ical a iable: less han 1 yea ;
1–2 yea s; 3–5 yea s; 5–10 yea s, and o e
10 yea s). The cu en esea ch employed
wo main se s o independen a iables:
echnology use and indi iduals’ i nancial
capabili y. Technology use was co e ed by wo
a iables, which a e ela ed o he ac whe he
an indi idual has o no a sma phone and
social media accoun . Simila o he dependen
a iable, hese a iables had wo possibili ies:
1 = yes, 0 = o he wise. Mo e han eigh y pe
cen o esponden s we e epo ed o possess
a sma phone (89%) and adminis a e a social
media accoun (85%).
Indi idual’s i nancial capabili y was
measu ed using six een s a emen s ela ed
o peoples’ knowledge, a i ude, and money
managemen , which we e de i ned by Sen’s
capabili y heo y (1993). Indi iduals we e asked
o gi e hei pe cep ion o hese s a emen s
(see Tab. 1). The s a emen s’ esponds
we e o mula ed as i e-poin Like ype
scale (1 = no a all, 5 = ully ag ee). Fac o
analysis was used o educe his huge numbe
o ac o s. The p incipal componen analysis
helped summa ise indi idual’s pe cep ions
abou six een s a emen s in o a smalle numbe
o unde lying ac o s. We ha e kep ac o s
wi h eigen alues highe han one. The o a ed
componen ma ix is epo ed in Tab. 1. Six
ac o s eme ge om he pe o med ac o
analysis, which explained 58.5% o he a iance
in he sample. The i s ac o combines
s a emen s ela ed o c edi ca ds and online
banking, which we called digi al banking usage,
which co esponds wi h Mbama e al.’s (2018,
p. 434) de i ni ion, ha includes “elec onic
banking se ices ia digi al de ices (e.g.
-banking, e-banking, m-banking, con ac less
ca d (e.g. ap and go), ATM and poin -o -
sale) […] o in e ace wi h banks”. Mo eo e ,
i is consis en wi h wha She aden (2013)
claims ha i nancially capable indi iduals ha e
access o bene i cial i nancial p oduc s and
se ices, besides o he cha ac e is ics. Thus,
i is expec ed ha indi iduals who ha e highe
digi al banking usage o ha e highe chances
o pu chase online (H1a). The second ac o
combines h ee i ems abou he a i ude owa ds
i nancial se ice isk, which is consis en wi h he
Es elami and De Maeye ’s (2010) discussion
ha bank accoun use s mani es a ce ain
le el o isk dealing wi h i nancial se ices.
Indi iduals who pe cei ed lowe i nancial
se ices isk a e expec ed o ge in ol ed in
online shopping ac i i y (H1b). The hi d ac o
combines esponses abou he need o consul
on aking i nancial decisions, which we named
i nancial ad ice, as elabo a ed by p io s udies
(Calcagno & Mon icone, 2015; K ame , 2016;
Ma sden, Zick, & Maye , 2011). Indi iduals
who consul o seek o ad ice on i nancial
ma e s ha e highe chances o pu chase ia
online channels (H1c). The ou h ac o is
a combina ion o wo i ems which poin s a he
isk o using he bank o pay bills. The e o e,
his ac o is called a i ude owa ds paymen
isk. People who pe cei e high paymen isk
a e less p one o high- isk paymen me hods
(Ho e & Ka imo , 2016). As a esul , a nega i e
associa ion is expec ed be ween paymen isk
and online shopping (H1d). The i h ac o
combines wo s a emen s and we named i
a i ude owa ds isk ole ance, which goes in
line wi h Joo and G able’s (2004) scale. The
highe he le el o his componen , he lowe he
chances indi iduals in ol e in online pu chase
ac i i y (H1e). Finally, he six h unde lying ac o
is a combina ion o wo i ems, and i is called
i nancial a i ude. A s udy used a simila bu
la ge scale o es he in l uence o i nancial
a i ude on compulsi e buying (Pham, Yap, &
Dowling, 2012). Online shopping is expec ed
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162 2020, XXIII, 2
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o be posi i ely a ec ed by indi iduals’ i nancial
a i ude (H1 ).
Gi en ha he demog aphic a iables o
age, gende , educa ion, and income ha e been
ound o ha e a signi i can e ec on consume s’
online pu chasing beha iou (Nase i & Ellio ,
2011; Oe zen & Odeke ken-Sch öde , 2019;
P asad & Sha ma, 2016; Punj, 2011). These
demog aphic a iables we e included as
con ol a iables in he analysis o a oid
po en ial causal in l uence on online shopping
beha iou . Conside ing he iden i i ed linkages
in he li e a u e e iew and he esul o he
ac o analysis, a concep ual amewo k can be
amed as i is illus a ed in Fig. 1.
I em and componen 1 2 3456
Digi al banking usage
I like ying new ends in banking – e.g. in e ne banking,
mobile paymen s, paying by c edi ca ds in he s o e e c.
.814
I use online banking whene e I ha e he chance and
oppo uni y o use
.734
I p oac i ely seek o he in o ma ion ega ding di e en banking
p oduc s & se ices
.636
I canno imagine my li e wi hou banking .515
A i ude owa ds i nancial se ice isk
I eel ha banks do no in o m he cus ome s well abou all he
de ails and cos s o bank p oduc s/se ices
.812
Banks wan o exploi you, hey hink only abou hei p o i .751
I ha e some imes p oblems o unde s and he de ails o banking
p oduc s and bank language in gene al
.642
Financial ad ice
Spending oo much money makes me eel guil y .688
I consul my i nancial ma e s wi h a i nancial ad iso o banke .654
I consul my i nancial ma e s wi h amily, iend e c. .625
A i ude owa ds paymen isk
I p e e o isi he b anch pe sonally when I wan o do some
bank ansac ion
.705
I don’ pay my u ili ies h ough banks as I us only s amped
eceip s abou paymen om u ili ies hemsel es
.676
A i ude owa ds isk ole ance
I keep my money a home a he han in he bank .705
My ela ionship wi h he bank is “only ge ing my sala y” h ough
ATMs
.690
Financial a i ude
I’m ying no o ha e any deb s .864
I always keep some sa ings o unp edic able u u e expenses .624
Sou ce: own
No e: Ro a ion me hod: Va imax wi h Kaise no maliza ion. Ro a ion con e ged in 6 i e a ions; Kaise ’s measu e o
sampling adequacy = .686; Va iance explained = 58.546%; Co ela ion ma ix’s de e minan = .136; Coe i cien loading
displayed > |.34|.
Tab. 1: P incipal componen analysis: he o a ed componen ma ix
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As men ioned ea lie , he na u e o he
dependen a iable limi s he use o he
s a is ical me hod. Wi h his in mind, logis ic
eg ession was pe o med o in es iga e he
e ec o consume ’s i nancial capabili ies and
echnology use on he decision o pu chase
online (Hosme , Lemeshow, & S u di an , 2013;
Tabachnick & Fidell, 2013). All he analyses
shown he e a e pe o med using compu e
s a is ical packing SPSS, e sion 23.
3. Resea ch Resul s
To ha e a be e iew o he e ec o di e en
ac o s on ou dependen a iable, ou logis ic
eg essions we e pe o med. In all cases,
he dependen a iable was online shopping
(Yes/No). The i s one (Model 1, baseline
model), includes only con ol a iables, which
we e gende , age, income le el and occupa ion
o he esponden . The second model includes
wo ac o s ela ed o echnology use, which a e
ha ing a sma phone and using social media.
The esul s o hese wo logis ic eg essions
a e shown in Tab. 2. Model 3 and 4 in end o
in es iga e he e ec o consume ’s i nancial
capabili ies and p io bank expe ience on
online shopping. Thei esul s a e summa ized
in Tab. 3.
The baseline model demons a ed ha
besides gende , all o he con olled a iables
ha e a s a is ically signi i can in l uence on
online pu chase decision (see Tab. 2). Olde
indi iduals had ewe chances o ge in ol ed in
online shopping, as he odds a io was epo ed
less han one, χ2 = 44.23, OR = 0.947, p < 0.01.
As he indi idual’s income le el inc eases, he
highe a e he odds a ios he/she pu chased
online. When compa ed o he highes income
le el, he income le els we e s a is ically
signi i can , indica ing ha income p edic ed
one’s online pu chase decision, o example,
he hi d le el, χ2 = 7.195, OR = 0.181, p < 0.01.
Re e ing o an indi idual’s occupa ion, esul s
showed ha manage s o sel -employed had
highe chances o pu chase online, χ2 = 6.769,
OR = 4.367, p < 0.01. Simila esul s a e
ound e en o hose wo king as specialis s,
χ2 = 5.299, OR = 3.525, p < 0.05. The e o e,
occupa ion s a is ically p edic ed online
shopping, χ2 = 19.19, p < 0.01.
Model 2 explo es he ela ionship o online
shopping wi h echnology use by including in
he analysis o he wo new a iables: ha ing
a sma phone and using social media (see
Tab. 2). This logis ic eg ession e ealed ha
bo h a iables p edic ed an indi idual’s online
pu chase decision. Possessing a sma phone
(χ2 = 5.604, OR = 4.773, p < 0.05) and using
social media (χ2 = 17.61, OR = 9.564, p < 0.01)
inc eased he chances ha an indi idual
Fig. 1: Concep ual amewo k
Sou ce: own
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164 2020, XXIII, 2
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pu chase h ough online channel. As a esul ,
H3 and H4 we e suppo ed. Conce ning con ol
a iables, Model 2 showed simila esul s wi h
he baseline model. Mo eo e , Model 2 included
educa ion le el as an ex a con ol a iable,
which was ound o be signi i can , χ2 = 6.737,
p < 0.10. Thus, he highe he educa ion le el,
he highe we e he odds an indi idual o
pu chase online.
As men ioned ea lie , Model 3 and 4
a e pe o med o in es iga e he e ec o
indi iduals’ i nancial capabili y and expe ience
as a bank clien on online shopping. Thei
esul s a e shown in Tab. 3. Model 3 is an
Model 1 (baseline) Model 2 ( echnology use)
B SE OR Wald B SE OR Wald
Cons an 2.387 0.885 10.88 7.275 *** -2.097 1.223 0.123 2.940 *
Gende -0.030 0.177 0.970 .0280 0.066 0.190 1.068 0.123
Age -0.054 0.008 0.947 44.23 *** -0.021 0.010 0.979 4.653 **
Income 9.870 7.364
Less han 15,000 ALL -2.209 0.809 0.110 7.458 *** -1.937 0.866 0.144 4.998 **
15,000–23,999 ALL -1.950 0.666 0.142 8.576 *** -1.565 0.724 0.209 4.666 **
24,000–39,999 ALL -1.709 0.637 0.181 7.195 *** -1.587 0.687 0.205 5.328 **
40,000–59,999 ALL -1.575 0.633 0.207 6.189 ** -1.655 0.677 0.191 5.971 **
60,000–78,999 ALL -1.588 0.691 0.204 5.286 ** -1.840 0.733 0.159 6.296 **
79,000–100,000 ALL -1.692 0.811 0.184 4.355 ** -1.874 0.840 0.154 4.979 **
Occupa ion 19.19 *** 9.880 **
Manage o sel -employed 1.474 0.567 4.367 6.769 *** 1.036 0.620 2.818 2.786 *
Specialis 1.260 0.547 3.525 5.299 ** 1.012 0.608 2.751 2.775 *
Unquali i ed wo ke 0.236 0.590 1.266 0.161 0.166 0.657 1.181 0.064
Educa ion 6.737 *
Elemen a y -1.672 0.805 0.188 4.314 **
Voca ional -0.033 0.462 0.968 0.005
Seconda y -0.408 0.220 0.665 3.421 *
Technology use
Sma phone 1.563 0.660 4.773 5.604 **
Social ne wo k 2.258 0.538 9.564 17.61 ***
Model es /s a is ic χ2d Sig. χ2d Sig.
Omnibus es 86.76 11 0.000 151.6 16 0.000
Hosme & Lemeshow es 10.54 8 0.229 5.715 8 0.679
-2Log likelihood 762.5 697.7
Cox & Snell R20.132 0.218
Nagelke ke R20.176 0.292
Obse a ions 615 615
Sou ce: own
No e: *, **, and *** s and o 90%, 95% and 99% signi i cance le el. Le els o income a e compa ed o Income abo e
100,000 ALL (1 EUR = 126.89 ALL, 10 h May 2018), occupa ion ca ego ies a e compa ed o O he ca ego y, educa ion
le els a e compa ed o he uni e si y one.
Tab. 2: Logis ic eg essions’ esul s: he e ec o echnology use on online pu chase
decision
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