Ma a eli e al. Analysis o banking solu ions
Towa ds an analysis o "banking solu ions" om he pe spec i e o
expo ing companies in B azil
Comple ed Resea ch Pape
Ma a Ma a eli
Uni e si y o La Rioja
ma ama a [email protected]
Juan Ca los Ayala
Uni e si y o La Rioja
juan-ca los.ayala@uni ioja.es
Al onso J. Gil
Uni e si y o La Rioja
al onso.g[email p o ec ed]
Abs ac
Banks in B azil play a majo ole in he in e na ionaliza ion p ocess o companies p o iding
inancial p oduc s and se ices. To examine his ole, a model con aining ou concep s is
analysed, hese being “banking solu ions” as he dependen a iable and “ ela ional capi al”,
“bank e iciency” and “ echnologies in se ices” as independen a iables. Th ough a
a iance-based s uc u al equa ion model (SEM), he ou come o his analysis e eals ha wo
independen a iables (“ ela ional capi al” and “bank e iciency”) ha e a signi ican and
posi i e impac on he use o banking solu ions. Also, om he expo company ision i is
ound ha “knowledge ba ie s” o expo mode a e he ela ionship be ween “bank
e iciency” and “banking solu ions”. Guidelines o po en ial u u e esea ch on he subjec
a e p o ided.
Keywo ds: Banking solu ions, ela ional capi al, bank e iciency, banking echnology
1. In oduc ion
In oday’s compe i i e en i onmen , i is c ucial ha bank manage s de elop he abili y o
es ablish c i ical bank selec ion ac o s o segmen s o he ma ke hey wish o a ac , o
se e and expand hei cus ome base. Rapid en i onmen al changes will need con inuing
a en ion and emphasis on o mula ing bank ma ke ing s a egies on he pa o manage ial
boa ds. Banks need o ensu e ha hei se ices co espond o hei clien s’ sho - and long-
e m needs. The ela ionship be ween bank and clien means mo e banking se ices and
p oduc s used by he clien and mo e p o i s o he banks.
Financial sys ems play a signi ican ole in he economic de elopmen o coun ies;
mo eo e , he a ie y o inancial ac i i ies ha di e be ween coun ies helps o explain a
signi ican p opo ion o he g ow h o economies. Coun ies, acco ding o hei le el o
de elopmen , ha e di e en ypes o pe o mance in hei banking sys ems. Fo B aun (2003),
in coun ies wi h low le els o inancial de elopmen , he numbe o indus ies wi h mo e
angible asse s is ela i ely la ge in size and g ows ela i ely as e han he numbe o
indus ies wi h mo e in angible asse s. In his con ex , his wo k has wo objec i es:
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 1
Ma a eli e al. Analysis o banking solu ions
• To analyse he in luence o h ee key elemen s in he s a egy o banks ha p o ide
inancial se ices o expo : bank ela ional capi al, bank e iciency and echnological
aspec s o se ices in he p o ision solu ions o bank se ices, which can simply be
de ined as he a ious ways in which a bank can help a cus ome .
• To examine he mode a ion o expo ba ie s, in pa icula he knowledge ba ie in
he expo p ocess. I is unde s ood ha ba ie s o expo s a e obs acles o he
in e na ionaliza ion p ocess o he company.
Th ough hese wo objec i es, we in end i s o de e mine om he pe spec i e o
expo ing companies sou ces o compe i i e ad an age o banks o p o ide assis ance in
expo se ices; second, we examine he knowledge ba ie as an elemen in ol ed in he
se ice ela ionship be ween expo e s and banks. Thus, we a gue ha he bank can in e ene
in helping he company o sol e expo p oblems.
The empi ical esea ch is ca ied ou among expo ing companies in B azil, an eme ging
coun y in which he banking sys em plays a key ole in helping expo s, aiding expo e s in
o e coming ba ie s o sell o o he coun ies and boos ing he le el o in e na ionaliza ion o
companies.
2. Li e a u e Re iew and Resea ch Hypo heses
A his poin , we examine ou cons uc s: banking solu ions, bank e iciency, bank
ela ional capi al and banking echnological se ices. Building on ea lie in es iga ions in he
banking ield, we de elop eigh hypo heses.
2.1. Banking solu ions
In he b oad sense, we de ine banking solu ions as he a ious ways in which a bank can
help a cus ome as a inancial ins i u ion. The e o e, he “banking solu ions” cons uc uni es
he concep s o banking se ices and p oduc s. The li e a u e con ains e idence o
p ac i ione s and academics using he wo ds “p oduc s” and “se ices” in qui e di e en
ways. Economis s discuss he e m “p oduc s” as a measu e o economic ac i i y o ou pu
which can be b oken down in o wo classes: angible p oduc s, which a e called goods, and
in angible p oduc s, which a e e med se ices (Akana i, 2005a).
The impo ance o he inancial se ices sec o has been mani es ed in he ecen
undamen al changes ha i has been expe iencing. These include de egula ion, inc easing
compe i ion, he highe cos s o de eloping new p oduc s, he apid pace o echnological
changes and inno a ion and mo e demanding cus ome s (Akama i, 2005a).
When choosing a bank as inancial suppo o i s p ocess o in e na ionaliza ion, a
company analyses se e al aspec s conside ed impo an in i s decision making, such as: he
p ices cha ged, he ypes o loans and inancing he bank o e s o i s cus ome s, ou es o
access o c edi , he condi ions o con ac s (such as e m in e es a es) and he p o ision o
speci ic se ices, as well as o he aspec s such as i s ela ionships wi h o he banks, he le el
o expe ise in he a ea o demand o c edi , e c.
The li e a u e con ains s udies analysing he di e ences be ween banks chosen by
companies o hei ope a ion; hese a e s udied acco ding o dimensions such as o igin
(domes ic o o eign), size (la ge o small), con ol (public o p i a e), sec o ( e ail, easu y,
business and c edi ) and ac o s ha de ine hei ole, s a egy and pe o mance (Cajuei o and
Tabak, 2007).
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 2
Ma a eli e al. Analysis o banking solu ions
Mos po en ial cus ome s gene ally e alua e bank o e ings. The selec ion o a bank wi h
which o ope a e includes qui e udimen a y ac o s, such as loca ion, amily ela ionship,
ecommenda ion, incen i es o e ed, image and epu a ion, compe i i e in e es a e, p oduc
ange, se ice expec a ion, low ees/o cha ges, b anch opening hou s and home banking
(De lin and Ge a d, 2004).
P o iding banking solu ions o cus ome s and o e ing inancial se ices app op ia e o
cus ome needs ha e been conside ed impo an pa s o bank s a egy (Guyo and Adan, 2013)
and hey become a e y impo an sou ce o suppo o cus ome sa is ac ion (Zineldin,
1996). In his ega d, i is no ed ha cus ome s end o be mo e in e es ed in he unc ional
quali y o inancial se ices han in he echnical quali y o he banks (Ulengin, 1998).
Fu he mo e, Mylonakis, Mallia is and Siomkos (1998) ound ele an e idence in he
selec ion c i e ia o he bank in ela ion o he quali y o he p oduc s and se ices o e ed o
he cus ome s. Fo example, lack o app op ia e p oduc s and se ices o small and medium
en e p ises is ano he impo an ba ie o accessing inancial se ices.
Ree es and Bedna (1996) a gued ha cus ome se ice appea ed mo e impo an han
se ices cos s in e alua ing and choosing be ween banks. To Ellio , Sha o and Singe (1996)
aspec s such as speed, p ice and access we e ound o be pa icula ly impo an o companies
in hei choice c i e ia ega ding banking.
Acco ding o Reina z and Kuma (2003), he mo e p oduc s and se ices pu chased by
he cus ome , he longe he bank keeps he company ha sells. In his sense, cus ome loyal y
becomes pa o bank sales ac ics, oge he wi h he exis ence o a ange o compe i i e
p oduc s. Thus, p oduc s can be pe cei ed di e en ly when he company s a s
in e na ionalizing and has o selec be ween one o ano he bank as he p ima y o seconda y
op ion in banking ope a ions (De lin and Ge a d, 2005).
Based on he li e a u e e iew, a his poin we discuss he main easons ha lead he
company o choose one o ano he bank o i s ope a ions in he in e na ional a ena: (1) he
inancial cos s and he size o he bank; (2) he geog aphical dis ance o he bank in ela ion o
he company and he capilla ies o he bank; (3) he echnology used by he bank; (4) he
bank’s epu a ion, adi ion, expe ise in in e na ional ade; (5) inancial and non- inancial
p oduc s o e ed by companies o o eign ade; (6) he pe cep ion o he e iciency, agili y
and sa e y o he bank; (7) he bank chosen by he con olle company, supplie o impo e ;
(8) he bank’s lexibili y in nego ia ions o e inancial suppo in he in e na ional a ena
(Ma a eli, 2014).
In gene al, he e a e many di e en ypes o banking solu ions. Many au ho s ha e
poin ed ou di e en ypes o new angible and in angible banking p oduc s (e.g. Akama i,
Thwai es and Bu gess, 1999; Akama i, 2005b). We include he ollowing aspec s as pa o
ou model:
• Funding lines
• C edi limi s
• Sa is ac ion o he con olle company equi emen s
• Se ice a es
2.2. E iciency in banking se ices
The concep o e iciency is no limi ed only o ope a ional cos minimiza ion bu is also
ela ed o gaining new clien s, managing cos s and p o iding quali y se ices (G igo oudis,
Tsi si idi, and Zopounidis, 2013). In ela ion o his, inancial ins i u ions a e e-examining
how hey cu en ly pe cei e hei cus ome s’ needs and de eloping he business plans needed
o align hem s a egically o emain compe i i e (Abdullah, Suhaimi, Saban and Hamali,
2011).
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 3
Ma a eli e al. Analysis o banking solu ions
Acco ding o Acha ya, Kagan and Lingam (2008), bank e iciency lies in p o iding a
se ice mix ela ed o he bes p ac ices o he company. These se ices can be iden i ied as:
• Agili y in se ice deli e y
• Con ol exchange
• Agili y in ope a ions
• Flexibili y in nego ia ions
• In o ma ion sa e y
These i e aspec s a e ela ed o quali y managemen (Sánchez-F anco and Ma ín-
Velicia, 2011). The e o e, we p opose he ollowing hypo hesis:
H1: F om he pe spec i e o he expo companies, he pe cei ed e iciency o bank
se ice deli e y has a posi i e e ec on he use o banking solu ions.
2.3. The impo ance o ela ional capi al in banking se ice s a egy and bank e iciency
As Dye and Singh (1998) no ed, he po en ial o a company o c ea e compe i i e
ad an age depends no only on i s esou ces bu also on i s ela ional asse s, i.e. i s
ela ionships wi h o he key i ms, o i s ela ional capi al. Rela ional capi al is de ined as he
se o all ela ionships – ma ke ela ionships, powe ela ionships and coope a ion –
es ablished be ween companies, ins i u ions and people, which s em om a s ong sense o
belonging and a highly de eloped capaci y o coope a ion (Capelo and Faggian, 2005).
Rega ding he banking sec o , i is no ed ha in ellec ual capi al is a sou ce o
pe o mance (Wang, Lu and Wang, 2013). Speci ically, we a e e e ing o he ela ional
capi al o banks, which may indica e some pa icula sou ces o ela ional capi al; o
example, we ha e no ed a bank’s epu a ion as an impo an ac o in he choice o decision
make s o use he bank o i s ope a ions in in e na ional business (Ongena, Tüme -Alkan and
Ve mee , 2011). In gene al, we can poin ou some sou ces o ela ional capi al:
• B anch ne wo k
• Rela ionships wi h o he banks
• Bank known ab oad
• T adi ion in in e na ional business
• Teams specialized in in e na ional ade
• Sou ce e e ence in o eign ade
The e o e, we sugges he ollowing hypo heses:
H2: F om he pe spec i e o he expo companies, he bank’s ela ional capi al has a
posi i e e ec on he use o i s banking solu ions.
H3: F om he pe spec i e o he expo companies, he bank’s ela ional capi al has a
posi i e e ec on bank e iciency.
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 4
Ma a eli e al. Analysis o banking solu ions
2.4. The banking echnology se ice, banking solu ions and bank e iciency
In ecen yea s, he de elopmen o echnology-based solu ions in sel -se ice o ma s
has mean ha banks ha e changed he way in which clien s access many banking se ices
(Bobbi and Dabholka , 2001). Inno a i e echnologies may gain a compe i i e edge and
achie e highe p oduc ion e iciency (Acha ya, Kagan and Lingam, 2008). Fo banks, he use
o se ice echnologies enables signi ican cos educ ions while enhancing se ice e iciency
and e ec i eness (C onin, 2003; P oença and Rod igues, 2011). Bo h aspec s a e ela ed o
banking solu ions and bank e iciency. Two i ems a e no ed ega ding banking echnology:
• Technology applied o banking se ices
• In e ne solu ions
The e o e, we de elop he ollowing hypo heses:
H4: F om he pe spec i e o he expo companies, inno a i e echnologies ha e a
posi i e e ec on banking solu ions.
H5: F om he pe spec i e o he expo companies, inno a i e echnologies ha e a
posi i e e ec on bank e iciency.
2.5. The mode a ing e ec o expo ba ie s
Nume ous in es iga ions ha e poin ed o he exis ence o ba ie s o limi a ions o
in e na ional business ac i i y (Leonidou, 1995a, b). Wi hin hese ypes o ba ie s, he lack o
quali ied pe sonnel in in e na ional ade has been iden i ied in he expo a ea as one o he
mos c i ical p oblems (Leonidou, 2004). Companies ha ace di icul ies in he expo
p ocess de i ed, o example, om hei own skills sho age in human capi al, ha e
di e en ia ed pe cep ions o bank se ices o capabili ies o sol e hei p oblems as hey
selec banks ha can help o sol e hese p oblems. The e o e, we no e he ollowing
hypo heses:
H6: F om he pe spec i e o he expo companies, expo ba ie s mode a e posi i ely
he ela ionship be ween a bank’s ela ional capi al and banking solu ions.
H7: F om he pe spec i e o he expo companies, expo ba ie s mode a e posi i ely
he ela ionship be ween bank e iciency and banking solu ions.
H8: F om he pe spec i e o he expo companies, expo ba ie s mode a e posi i ely
he ela ionship be ween banking echnology se ices and banking solu ions.
Figu e 1 shows he o e all model o analysis, summa izing he eigh hypo heses
p oposed.
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 5

Ma a eli e al. Analysis o banking solu ions
Figu e 1: Resea ch model
3. Me hod
3.1. Sample and da a collec ion
To ob ain he sample, we s a ed wi h he Ca alogue o B azilian Expo e s (CEB)
da abase, which p o ides in o ma ion ega ding expo s aken om he o icial eco ds o he
Sec e a y o Fo eign T ade (SECEX), an in e nal a ea o he Minis y o Planning, Indus y
and Fo eign T ade (MDIC) o B azil. The inal sample consis ed o 318 companies: 76
ag ibusiness companies, 171 in he p ocessing indus y, 15 in mining and qua ying and 56 in
he se ices sec o . The sampling e o is ± 4.6% wi h a 95% con idence le el.
The ins umen used o he collec ion o in o ma ion was a sel -adminis e ed
ques ionnai e. The ques ionnai e design was based on he heo e ical app oaches shown in he
i s pa o his wo k. The ques ionnai e was sen o he company, speci ically o hose
esponsible o he expo business, as his was conside ed he mos di ec way o ob ain da a
om he companies. O he di e en p ocedu es o collec ing su ey da a ( o example,
pe sonal in e iew, elephone in e iew, pos al su ey, sel -adminis e ed ques ionnai e,
ne wo k su ey), we chose o conduc he su ey in his s udy using he ne wo k app oach
h ough he In e ne .
3.2. Da a analysis
Ou esea ch model was es ed using s uc u al equa ion modelling, namely by means o
he pa ial leas squa es (PLS) echnique and u ilizing he SMARTPLS so wa e e sion 3.0
(Hensele , Ringle and Sa s ed , 2015).
H8
H7
H6
H4
H5
H2
Banking
Solu ions
(BS)
H3
H1
Technology in
Se ices
(TS)
Knowledge Ba ie (KB)
Bank
E iciency
(BE)
Rela ional
Capi al
(RC)
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 6
Ma a eli e al. Analysis o banking solu ions
4. Resul s
4.1. Measu emen model analysis
A ac o ial s uc u e analysis was conduc ed using ac o analysis o he p ima y
componen s wi h Va imax o a ion h ough SPSS e sion 22.0, which enabled us o p o e he
exis ence o ou ac o s ha coincide wi h cons uc s we e med: ela ional capi al, bank
e iciency, bank solu ions and echnology in se ices. The Kaise –Meye –Olkin (KMO) alue
o 0.879 indica es an adequa e i be ween he da a and he ac o ial model. On he o he hand,
in he analysis o he o al a iance explained, ou componen s we e ound o summa ize
72.878% o o al a iabili y ( he i s componen explaining 21.793%, he second 20.238%,
he hi d 19.038% and he ou h 11.834%). These ou componen s co espond o he ou
cons uc s o med by e lec i e indica o s.
We also analysed he eliabili y o he model. Fi s , we analysed he s anda dized oo
mean squa e esidual (SRMR) as a goodness o (model) i measu e o PLS-SEM. The alue
o 0.1 ound is conside ed adequa e o he model (Hensele e al., 2014; Hu and Ben le ,
1998). The eliabili y o he indices mus be analysed h ough hei loadings (λ). In ou case,
all ac o ial loadings, p o ed o be no less han 0.4 (Hai , Ringle and Sa s ed , 2011),
explaining hei inclusion in he model. Thus, a g oup o scales wi h a o al o 17 i ems
emains (see Table 1).
Table 1: Measu emen model: c oss-loadings
I ems
Rela ional
Capi al
(RC)
Bank
E iciency
(BE)
Banking
Solu ions
(BS)
Technology
in Se ices
(TS)
Rela ionships wi h o he banks
.838
Sou ce e e ence in o eign ade
.833
B anch ne wo k
.824
T adi ion in in e na ional business
.789
Teams specialized in in e na ional ade
.773
Bank known ab oad
.745
Agili y in se ice deli e y
.884
Ope a ional agili y
.868
Con ol exchange
.838
In o ma ion sa e y
.765
Flexibili y in nego ia ions
.761
C edi limi s
.870
Funding lines
.796
Se ice a es
.758
Sa is ac ion o con olle company equi emen s
.661
In e ne solu ions
.961
Technology in bank se ices
.941
The eliabili y o he cons uc s was examined using C onbach’s alpha and he composi e
eliabili y index (CRI). The exis ence o con e gen alidi y was con i med by means o he
a e age a iance ex ac ed (AVE). As shown in Table 2, ei he he C onbach’s alpha alues o
he CRI alues su pass he c i ical alue o 0.8 o all a iables (Nunnally and Be ns ein,
1994) and he alues o AVE a e abo e 0.5 (Fo nell and La cke , 1981).
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 7
Ma a eli e al. Analysis o banking solu ions
Table 2: Cons uc eliabili y and con e gen alidi y
CR C onbach’s α AVE
Rela ional capi al 0.915 0.890 0.642
Bank e iciency 0.914 0.881 0.680
Banking solu ions 0.856 0.779 0.601
Technology in se ices 0.950 0.896 0.905
The analysis o he measu emen model in ol es e i ying he exis ence o disc iminan
alidi y. In his ega d, a new app oach o assessing disc iminan alidi y in a iance-based
SEM is he he e o ai -mono ai (HTMT) a io o co ela ions p oposed by Hensele , Ringle
and Sa s ed (2015). Based on he c i e ia o HTMT0,85 disc iminan alidi y issues o in e -
cons uc co ela ions we e no ound (0,70 o less), as shown in Table 3.
Table 3: Disc iminan alidi y
Rela ional capi al Bank e iciency Banking solu ions Technology in se ices
Rela ional capi al -
Bank e iciency 0.594 -
Banking solu ions 0.538 0.700 -
Technology in se ices 0.525 0.510 0.359 -
4.2. S uc u al model analysis
To de e mine he s a is ical signi icance o he pa h coe icien s o he model, a boo s ap
esampling echnique was employed wi h 5,000 subsamples (Hai , Ringle and Sa s ed , 2011).
The s uc u al model e alua es he magni ude and he signi icance o he ela ionship be ween
he dis inc a iables. I is a ma e o analysing he explained a iance o he endogenous
a iables (R2), he pa h coe icien s o s anda dized eg ession weigh s (ß) and he espec i e
le els o signi icance, h ough he S one–Geisse (Q2) es (see Figu e 2).
Figu e 2: S uc u al model
-0.029 (0.380)
R
BE
² = 0.350
RCB² = 0.392
0.501*** (6.077)
0.261*** (4.555)
0.423*** (7.494)
0.211** (2.211)
Rela ional
Capi al
(RC)
Banking
Solu ions
(BS)
Technology in
Se ices
(TS)
Bank
E iciency
(BE)
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 8
Ma a eli e al. Analysis o banking solu ions
The ollowing ela ionships we e ound o be signi ican : (1) bank e iciency and banking
solu ions (ß=0.501***); (2) ela ional capi al and banking solu ions (ß=0.211**); (3)
ela ional capi al and bank e iciency (ß=0.423***); (4) echnology in se ices and banking
solu ions (ß= -0.029); (5) echnology in se ices and banking e iciency (ß= 0.261***) (see
Table 4). Thus, H1, H2, H3 and H5 a e alida ed.
Table 4: S uc u al model esul s (baseline model)
RES² = 0.350
RCB² = 0.392
Hypo hesis Sugges ed e ec Pa h coe icien s - alue (boo s ap) Suppo
H1: BE→BS + 0.501*** 6.077 Yes
H2: RC→BS + 0.211** 2.211 Yes
H3: RC→BE + 0.423*** 7.494 Yes
H4: TS→BS + -0.029 0.380 No
H5: TS→BE + 0.261*** 4.555 Yes
*p < 0,05; **p < 0,01; ***p < 0,001; no signi ican (based on (499), one- ailed es ); (0,05;499) = 1,64791345, (0,01;499) =
2,333843952; (0,001;499) = 3,106644601
Tables 5 and 6 show he mode a ion p ocesses in he p oposed ela ionships. Table 5
indica es he ela ionship o ela ional capi al and banking solu ions.
Table 5: S uc u al model esul s wi h mode a ion o he knowledge ba ie in he ela ionship
be ween ela ional capi al and banking solu ions
RBS² =0.414
RBE² = 0.350
Hypo hesis Pa h coe icien s - alue (boo s ap) Suppo
H1: BE→BS 0.433*** 5.370 Yes
H2: RC→BE 0.215** 2.842 Yes
H3: RC→BE 0.423*** 7.726 Yes
H4: TS→BS 0.061 0.660 No
H5: TS→BE 0.261*** 4.541 Yes
H6: RCxKB→BS 0.091* 1.732 Yes
*p < 0,05; **p < 0,01; ***p < 0,001; no signi ican (based on (499), one- ailed es ); (0,05;499) = 1,64791345, (0,01;499) =
2,333843952; (0,001;499) = 3,106644601
As shown in Table 5, hypo hesis H6 is con i med and he knowledge ba ie mode a es
he ela ionship be ween ela ional capi al and banking solu ions.
Table 6 no es he ela ionship o ela ional capi al and banking solu ions.
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 9