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The E ec o Implemen ing Co e Banking
Se ices on P o i abili y: Case S udy o All
B anches o a P i a e Bank in Mashhad
Mansou Dehghan
Depa men o Accoun ing, Neyshabu B anch, Islamic Azad Uni e si y,
Neyshabu , I an
Mahdi Gha oo i a d1
Depa men o Managemen , Economics and Accoun ing, Payame Noo
Uni e si y, PO BOX 19395-3697, Teh an, I an.
Babak Shamsi
Depa men o Accoun ing, Neyshabu B anch, Islamic Azad Uni e si y,
Neyshabu , I an
Seyed Hamid Seyed Heyda i
Depa men o Accoun ing, To ba e Jam B anch, Islamic Azad Uni e si y,
To ba e Jam, I an
Abs ac
Recen ly, he g ow h o in o ma ion echnology and inc easing compe i ion
among banks has conside ably a ec ed a ac ing cus ome s. Banking indus y
has made g ea changes o ans o m in o he co e banking. The p esen s udy
aims o assess he e ec o he implemen a ion o co e banking se ices on
p o i abili y. These se ices, as di e en b anches o elec onic banking, a e
consis ing o in e ne banking, mobile banking, elephone banking, poin o
sale (POS), ATM, and elec onic money which a e all es ed in he cu en
s udy. In o de o es esea ch hypo heses and he exis ing ela ionship
be ween a iables, needed da a has been collec ed and analyzed h ough he
applica ion o s epwise eg ession model. The achie ed indings indica e a
signi ican ela ionship be ween he applica ion o in e ne banking and ATM
and he a iable o p o i abili y, while he e is no signi ican ela ionship
be ween he applica ion o elephone banking, mobile banking, POS, and
elec onic money and p o i abili y.
Keywo ds: Co e banking, Elec onic banking, P o i abili y.
Ci e his a icle: Dehghan, M., Gha oo i a d, M., Shamsi, B., & Seyed Heyda i, S. H.
(2015). The E ec o Implemen ing Co e Banking Se ices on P o i abili y: Case S udy o All
1 Co esponding au ho ’s email: Mahdi. a [email protected]
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548
B anches o a P i a e Bank in Mashhad. In e na ional Jou nal o Managemen , Accoun ing
and Economics, 2(6), 547-557.
In oduc ion
Ge ing access o he in e ne ne wo k and elec onic ela ions among di e en
people and o ganiza ions in he i ual wo ld has p o ided economic and comme cial
exchanges. Elec onic banking is one o he essen ials o elec onic comme ce which
can acili a e global inancial sys ems o a ce ain ex en (Bikzad & Mola i, 2009).
Wi h he ise o elec onic banking and ad anced in o ma ion and communica ion
echnology sys ems in banking indus y, adi ional banking ac i i ies looks da ed. Thus,
banking is conside ed as a sub ield o in o ma ion p ocessing indus y which is o med
on he basis o no el concep s such as elec onic money, ATM, POS, and so on.
Due o he economical ad an ages o elec onic banking sys ems such as educing
cos s, inc easing p o i s and quali y o se ices o e ed o he cus ome s, emo ing
empo al and spa ial cons ain s, b oadening he domain o banking and ma ke ing
ac i i ies, no only do new banks apply elec onic banking, bu also old ones a emp o
o e elec onic se ices besides adi ional ones (Gouda zi & Zobeidi, 2008). Va ious
esea ches demons a e he g ow h o online banking all o e he wo ld, in a way ha
he a e o elec onic banking ela ions has exceeded %50 in he leading coun ies
(Pikka ainen e al., 2004). In I an, conduc ing banking a ai s wi hou loss o ime is
ega ded as a key o success which is c ucial in all banking compe i ions (Maleki &
Akba i, 2010).
The cu en s udy aims o in es iga e he e ec o co e banking se ices on
p o i abili y.
Co e banking
Co e banking is a gene al e m used o desc ibe he se ices p o ided by a g oup o
ne wo k bank b anches, bank cus ome s may occu s hei unds and o he simple
ansac ion om any o he membe . Thus Co e Banking Solu ion is a s ide-headed
owa ds enhancing he cus ome se ices h ough Any-whe e and Any- ime banking
(Manjush ee, 2014). Simply pu , co e banking helps cus ome s o emo e empo al and
spa ial cons ain s, and u ilize ne wo ks and elecommunica ions echnology o ans e
esou ces (money) in banking sys em (Heida pou & Tahmasbi, 2009).
Kh awish and Al-Sadi (2012) de ine elec onic banking as he adop ion o elec onic
means in he deli e y o banking p oduc s and se ices. Such p oduc s and se ices
include deposi aking, lending and paymen p oduc s and p o ision o o he elec onic
paymen p oduc and se ices such as elec onic money du ing 24 hou s a day as well as
7 days a week.
The e o e, co e banking includes all elec onic channels which a e used by cus ome s
in o de o deposi accoun s, pay bills and pu chase wha hey need (Dandapani, 2008).
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Va ious co e banking se ices
In e ne banking
In e ne has g ea ly a ec ed elec onic banking. The e is no empo al and
geog aphical cons ain h ough he applica ion o in e ne banking. In e ne banking is
an elec onic paymen sys em which enables cus ome s o conduc inancial ansac ions
wi hou e e ing o he bank, jus h ough hei PCs o communica ions ne wo ks
(Tagha i a d e al., 2012).
ATM
Au oma ed elle machine (ATM) is an elec onic elecommunica ions de ice ha
enables he cus ome s o a inancial ins i u ion o pe o m inancial ansac ions. ATMs
a e o en loca ed inside a speci ic place which may be accessible 24 hou s a day. They
a e also conside ed as a b anch o he bank, since hey p o ide di e en se ices o e ed
in he bank (Maleki & Akba i, 2010).
POS
Poin o sale (POS) is he place whe e a e ail ansac ion is comple ed. I is he poin
a which a cus ome makes a paymen o he me chan in exchange o goods. A he
poin o sale he e aile would calcula e he amoun owed by he cus ome and p o ide
op ions o he cus ome o make paymen . Telephones o ne wo k communica ions may
be u ilized o conduc ansac ions h ough POS (Habib Zadeh & Mi majidi Hashjin,
2011).
Mobile banking
Mul idimensional se ices such as GPRS which a e accessible h ough mobiles
enable cus ome s o conduc inancial ansac ions like ge ing accoun balance and
inancial s a emen , eques ing check, and ans e ing om one accoun in o o he
accoun s (Fa noud, Sol ani & Za abiye, 2008, p. 356).
Telephone banking
Conduc ing small ansac ions be ween a cus ome and i s bank can be possible
h ough elephone banking which can be h ough h ee di e en me hods: audio
ansac ion, oice ecogni ion, and p e-planned elephones (Habib Zadeh & Mi majidi
Hashjin, 2011).
Elec onic money
Elec onic money in ol es he use o in e ne o o he ne wo ks o s o e o ansmi
money. This ype o money can be s o ed on sma ca ds o compu e ’s ha dwa e.
Elec onic money alls in o di e en ypes as ollows: elec onic ca d, elec onic walle ,
elec onic check, digi al money, and i ual ca d (Maleki & Akba i, 2010).
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P o i abili y
P o i is an impo an e m in business decision makings. A la ge olume o
accomplished esea ches and s udies in he ield o accoun ing a e wi h ega d o p o i .
P o i , as a guide o he di idend, can be applied by manage s, in es o s and inancial
analys s as an index o e alua ing managemen e ec i eness and p edic decision
makings. As a ma e o ac , all inancial and manu ac u ing p og ams, ac i i ies and
decisions a e e lec ed in he i m’s p o i abili y (Gha oo i a d, 2011).
Ne income ma gin (NIM) is u ilized in he cu en s udy o calcula e p o i abili y.
Due o he ac ha Riba and Bah e mus no be in ol ed in I anian banks, in e es is
calcula ed and subs i u ed wi h Riba and Bah e (Pazhouyan & Sha iei, 2008).
Re iew o li e a u e
Conduc ed esea ches in o eign coun ies indica e ha a ious indexes such as
p oduc i i y, e iciency and p o i abili y ha e been applied o e alua e he
implemen a ion o in o ma ion echnology sys ems in he banks’ economic
pe o mances. A sum o hei indings can be explained in he ollowing manne .
Kh awish and Al-Sadi (2011) in es iga ed he impac o e-banking on bank
p o i abili y in Jo dan and ound ha due o he cos s o applying e-banking se ices,
hey do no signi ican ly a ec p o i abili y based on ROE and ROA, while e-banking
se ices signi ican ly a ec he index o g oss p o i .
Simila esea ch was ca ied ou in Pakis an by Sum a e al. (2011). They indica ed
ha elec onic banking can inc ease bank p o i abili y.
Coppin e al. (2003) did a esea ch wi h ega d o all banks in Ba bados and ound
ha ATMs we e no p o i able a i s , since aining pe sonnel and cus ome s how o
use hem was expensi e. Bu when i was educa ed, e iciency inc eased om %3 o
%17.
Eyada and Kozak (2005) examined he ole o in o ma ion echnology in he p o i
and cos e iciency imp o emen s o banking sec o , and ound ha in es ing in
in o ma ion echnology sys ems can inc ease bank p o i abili y while dec ease cos
e iciency in p opo ion o p o i e iciency.
Siam (2006) assessed he ole o he elec onic banking se ices on he p o i s o
Jo danian banks, and concluded ha elec onic banking se ices nega i ely a ec bank
p o i abili y in he sho e m, while hey ha e a posi i e in luence in he long e m,
since bank in es men s a e all wi h ega d o in as uc u es and s a ’s aining.
Re iewing di e en da abases, scien i ic documen s and a icles, his conclusion can
be d awn ha ew esea ches we e conduc ed in I an in he ield o elec onic banking
some o which a e as ollows.
Gouda zi and Zobeidi (2008) applied combined da a o six comme cial banks in I an
(Teja a , Re ah Ka ga an, Sepah, Sade a , Mella , and Melli) o e a pe iod om 2000 o
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2005. They u ilized ixed e ec model and gene alized leas squa es me hod o conclude
ha he numbe o each bank’s ATMs posi i ely a ec s i s p o i abili y. She ab
(in e bank in o ma ion ans e ne wo k) sys em has also accele a ed and inc eased his
e ec . Thus, i can be alleged ha imp o ing elec onic banking has signi ican ly
a ec ed I anian banks’ p o i abili y.
Abdi e al. (2010) in es iga ed he e ec o new banking echnologies on he
o ganiza ions’ agili y. They did hei esea ch wi h he help o academics and banking
expe s. Findings o his s udy indica e ha he s a s’ knowledge and skills in he
applica ion o new banking echnologies ha e he mos co ela ion wi h se en
dimensions o lexibili y, accoun abili y, speed, in eg a ion and low complexi y, co e
compe encies, high quali y, p oduc imp o emen , and cul u e o change. Fu he mo e,
he s a s’ knowledge and skills a e signi ican ly associa ed wi h elec onic banking
indexes, widesp ead ne wo ks o in o ma ion exchange be ween cus ome s and bank,
and a o emen ioned dimensions.
Ba ada an e al. (2009) assessed he e ec o using bank ca ds among he cus ome s
o Bank Melli in Eas Aze baijan, and ound ha his usage can inc ease he cus ome s’
sa is ac ion and eeling o secu i y.
Resea ch ques ions, hypo heses and a iables
This s udy in ends o ind whe he he e is a signi ican ela ionship be ween he
applica ion o co e banking se ices and p o i abili y in di e en b anches o a bank in
Mashhad. To ind he answe , six ollowing hypo heses ha e been designed.
1. The e is a signi ican ela ionship be ween he applica ion o in e ne banking and
p o i abili y.
2. The e is a signi ican ela ionship be ween he applica ion o mobile banking and
p o i abili y.
3. The e is a signi ican ela ionship be ween he applica ion o elephone banking
and p o i abili y.
4. The e is a signi ican ela ionship be ween he applica ion o ATMs and
p o i abili y.
5. The e is a signi ican ela ionship be ween he applica ion o POSs and
p o i abili y.
6. The e is a signi ican ela ionship be ween he applica ion o elec onic money
and p o i abili y.
P o i abili y has been conside ed in his s udy as he dependen a iable, while o he
a iables o he applica ion o in e ne banking, mobile banking, elephone banking,
ATMs, POSs and elec onic money ha e been ega ded as independen a iables.
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Resea ch me hodology
Cause and e ec ela ionships be ween dependen and independen a iables ha e
been in es iga ed in he cu en s udy in o de o es s a is ical hypo heses and con i m
o ejec hem (Vazi eh Dous & Nik Nezhad Teh ani, 2007).
Ta ge popula ion and samples
Ta ge popula ion o he esea ch is consis ing o 59 b anches g ades 1, 2 and 3 in
Mashhad o e a pe iod om Ma ch 21, 2010 o Ma ch 18, 2012. Sampling has been
conduc ed on he basis o cus ome s’ academic deg ee and in e iewing wi h he
b anches’ head. Owing o he ac ha he cus ome s in b anches g ade 3 we e mos ly
illi e a e, hese b anches ha e been omi ed om sampling, hus 24 b anches ha e
emained as he esea ch sample.
Da a collec ion
P elimina y needed da a has been collec ed h ough inancial epo ing p og ams and
analy ical so wa e u ilized in he banks. In his ega d, he applica ion o co e banking
se ices in 2010 and 2011 has been conside ed as independen a iables o he esea ch,
while p o i abili y (ne income ma gin) has been ega ded as dependen a iable.
Seconda y in o ma ion has been assembled h ough desk esea ch such as documen s,
a icles, heses, lib a ies and in e ne . SPSS so wa e has been applied o conduc
s a is ical es s.
Da a analysis and hypo hesis es ing
Mul iple eg ession models ha e been u ilized in his s udy in o de o es six
esea ch hypo heses. P o i abili y has been conside ed in his s udy as he dependen
a iable, while o he a iables o he applica ion o in e ne banking, mobile banking,
elephone banking, ATMs, POSs and elec onic money ha e been ega ded as
independen a iables. The eg ession model can be w i en as ollows:
(1)
Whe e;
Xi e e s o independen a iables, α s ands o he ixed alue o in e cep , βi is he
impac ac o o independen a iables, ε is esidual, n e e s o he numbe o
independen a iables, and p o i abili y s ands o Ne income ma gin (NIM).
S epwise eg ession model has been used o da a analysis. The e o e, he da a whose
co ela ion wi h o he dependen o independen a iables a e accep able en e s he
model. O he a iables whose co ela ions a e no accep able (e.g., hose a iables
which ha e no signi ican e ec on he dependen a iable) canno en e he model. The
ob ained esul s o s epwise eg ession model o he dependen a iable o p o i abili y
a e shown in able 1.
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Table 1 Va iables which could en e he s epwise eg ession model
Model
En e ed a iables Exi ed a iables
1 The applica ion o ATMs ----------------
2 The applica ion o in e ne banking
----------------
On he basis o he able 1, only wo a iables ( he applica ion o ATMs and in e ne
banking) we e accep able o en e he model. O he a iables o co e banking se ices
did no ha e he accep able condi ion o en e he s epwise model.
Model 1 is consis ing o he a iable o he applica ion o ATMs, and model 2 is
consis ing o he a iable o he applica ion o in e ne banking. Due o he ac ha
o he co e banking se ices a iables did no ha e a signi ican e ec on p o i abili y,
hey canno en e he s epwise model.
Table 2 Coe icien o de e mina ion, adjus ed coe icien o de e mina ion, and Du bin
Wa son s a is ic in he model
Model
Co ela ion
coe icien Coe icien o
de e mina ion (R) Adjus ed coe icien
o de e mina ion Du bin-Wa son
s a is ic
1 0.719 0.499 0.488 -----------
2 0.808 0.644 0.611 2.035
Au oco ela ion o esiduals in eg ession model was calcula ed based on Du bin-
Wa son s a is ic. Non-exis ence o au oco ela ion among esiduals is essen ial. The
alues nea 2 o his s a is ic show non-exis ence o au oco ela ion among esiduals.
Du bin-Wa son s a is ic o he abo e model is 2.035 which is accep able ( able 2).
In able 2 Coe icien o de e mina ion o model 1 is abou 0.499 which is associa ed
wi h he independen a iable o he applica ion o ATMs. In model 2, coe icien o
de e mina ion is bigge (abou 0.644) o he independen a iable o he applica ion o
in e ne banking. I means ha %64.4 o p o i abili y changes a e oo ed in changes in
wo a iables o he applica ion o ATMs and in e ne banking.
Table 3 Va iance analysis o he model wi h he dependen a iable o p o i abili y
Model
Sou ce o
changes Sum o he
squa es Deg ee o
eedom Mean o
squa es Fishe
s a is ic (F) Signi icance
le el
1 Reg ession 138.789 1 149.89 17.121 0.001 Residuals 129.47 16 9.11
To al 278.46 17
2 Reg ession 198.03 2 91.50 14.12 0.000 Residuals 99.47 15 5.39
To al 278.46 17
In able 3 o model 1, which has only one independen a iable ( he applica ion o
ATMs), signi icance le el equals 0.001 (less han 0.05). Thus, wi h he con idence le el
o %95 i can be concluded ha he applica ion o ATMs signi ican ly a ec s
p o i abili y.
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Fo model 2, which has wo independen a iables ( he applica ion o ATMs and
in e ne banking), signi ican le el equals 0.000 (less han 0.05). Thus, wi h he
con idence le el o %95 i can be concluded ha he applica ion o ATMs and in e ne
banking can signi ican ly a ec s p o i abili y.
Table 4 Reg ession coe icien s wi h he dependen a iable o p o i abili y
Model
Va iables S anda d
coe icien
Nons anda d coe icien s T
s a is ic
Signi icance
le el
S anda d
e o Coe icien
1
Fixed alue ------ 1.370 2.887 2.077 0.051
The
applica ion
o ATMs 0.695 0.001 0.004 4.210 0.001
2
Fixed alue ------ 1.395 0.69 0.464 0.623
The
applica ion
o ATMs 0.523 0.001 0.003 2.879 0.007
The
applica ion
o in e ne
banking
0.41 0.021 0.044 2.321 0.019
In able 4 o he inal model (model 2), signi icance le els o wo independen
a iables equal 0.007 and 0.019 (less han 0.05), while signi icance le els o ixed
alues a e 0.623 and 0.05. The e o e, he ollowing manne can be w i en:
P o i abili y= 0.523 ( he applica ion o ATMs) + 0.41 ( he applica ion o in e ne
banking)
Discussion
In his s udy, he designed hypo heses a e ega ded as H1, while null hypo heses a e
H0.
Fi s hypo hesis es ing
Acco ding o Table 4, since he a iable o he applica ion o in e ne banking exis s
in he inal model and he signi icance le el equals 0.019 (less han 0.05), H0 is ejec ed
wi h he con idence le el o %95. Thus, i can be concluded ha he applica ion o
in e ne banking signi ican ly a ec s p o i abili y. On he o he hand, eg ession
coe icien equals +0.41, i means ha he applica ion o in e ne banking and
p o i abili y a e di ec ly and signi ican ly associa ed wi h each o he .
Second hypo hesis es ing
Acco ding o Table 4, he applica ion o mobile banking does no exis in he inal
model. Thus, H0 is no ejec ed wi h he con idence le el o %95, and he a iables o
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he applica ion o mobile banking and p o i abili y a e no signi ican ly associa ed wi h
each o he .
Thi d hypo hesis es ing
Acco ding o Table 4, he applica ion o elephone banking does no exis in he inal
model. Thus, H0 is no ejec ed wi h he con idence le el o %95, and he a iables o
he applica ion o elephone banking and p o i abili y a e no signi ican ly associa ed
wi h each o he .
Fou h hypo hesis es ing
Acco ding o Table 4, since he a iable o he applica ion o ATMs exis s in he
inal model and he signi icance le el equals 0.007 (less han 0.05), H0 is ejec ed wi h
he con idence le el o %95. Thus, i can be concluded ha he applica ion o ATMs
signi ican ly a ec s p o i abili y. On he o he hand, eg ession coe icien equals
+0.523, i means ha he applica ion o ATMs and p o i abili y a e di ec ly and
signi ican ly associa ed wi h each o he .
Fi h hypo hesis es ing
Acco ding o Table 4, he applica ion o POS does no exis in he inal model. Thus,
H0 is no ejec ed wi h he con idence le el o %95, and he a iables o he applica ion
o POS and p o i abili y a e no signi ican ly associa ed wi h each o he .
Six h hypo hesis es ing
Acco ding o Table 4, he applica ion o elec onic money does no exis in he inal
model. Thus, H0 is no ejec ed wi h he con idence le el o %95, and he a iables o
he applica ion o elec onic money and p o i abili y a e no signi ican ly associa ed
wi h each o he .
Conclusion
The achie ed esul s o es ing esea ch hypo heses indica e ha he applica ion o
in e ne banking and ATMs signi ican ly and di ec ly a ec s p o i abili y, hus
imp o ing hese wo a iables and encou aging cus ome s o apply hem a e sugges ed
o be aken in o conside a ion. In his ega d, all banks a e ecommended o enable
cus ome s o use elec onic ools.
On he o he hand, he achie ed indings o his s udy demons a e ha he
applica ion o o he co e banking se ices such as mobile banking, elephone banking,
POS, and elec onic money does no signi ican ly a ec p o i abili y. Due o he ac
ha hese se ices ha e been ecen ly o e ed in I an, hey a e no welcomed as much as
o he banking se ices, as a esul , hey canno be so p o i able, and mo e o less
applica ion o hese se ices canno change he inal p o i abili y. Banks a e
ecommended o encou age cus ome s and change hei iewpoin s abou new co e
banking se ices and elec onic ools.
