Tabea T essin e al. O ganiza ional S uc u e and Pu chasing Success
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 1
The In luence o O ganiza ional S uc u e
on In e na ional Pu chasing Success
Resea ch-in-P og ess
Tabea T essin
Hambu g Uni e si y o Technology, Ins i u e o
Human Resou ce Managemen and O ganiza ions,
Schwa zenbe gs aße 95 (D), 21073 Hambu g,
Ge many. Tel: +49 40 42878-3567.
Email: [email p o ec ed].
Nicole F anziska Rich e
No dakademie, P o esso ship o Ma ke ing and
Gene al Managemen , Koellne Chaussee 11, 25337
Elmsho n, Ge many, Tel: +49 4121 4090-241. Email:
nicole. ich e @no dakademie.de.
Da id F. Midgley
INSEAD, P o esso o Ma ke ing, Boule a d de Cons ance, 77305 Fon ainebleau Cedex, F ance, Tel: +33
160724977. Email: da [email protected].
Abs ac
In e na ional pu chasing is one o he mos impo an s a egic opics o manage s and
a ac s mo e and mo e in e es among esea che s. Ye , esea ch o en lacks s ong heo e ical
and sys ema ic insigh s on he in icacies o pu chasing success and does no make enough
use o ad anced empi ical me hods.
We apply a s uc u al equa ion modeling echnique o be e esea ch in o he in icacies o
highe o lowe pu chasing pe o mance owing o di e en o ganiza ional design choices. We
build ou model on he esou ce-based iew and on ansac ion cos economics and make use
o su ey da a o pu chase s engaging in in e na ional sou cing ac i i ies.
We ind ou impo an d i e s o pu chasing pe o mance, namely specializa ion,
con igu a ion, s anda diza ion and cen aliza ion. The impo ance o hese d i e s seems o be
con ingen on he sou cing en i onmen s, namely on he cha ac e is ics a ibu ed o high cos
and low cos coun ies.
Keywo ds: In e na ional Pu chasing, Global Sou cing, Eme ging Ma ke s, O ganiza ional S uc u e,
S uc u al Equa ion Modeling
Tabea T essin e al. O ganiza ional S uc u e and Pu chasing Success
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 2
1. In oduc ion
In e na ional pu chasing is one o he mos impo an s a egic opics o manage s, and
a ac s mo e and mo e in e es among esea che s (de Beuckelae & Wagne , 2007; Hul man,
Johnsen, Johnsen, & He z, 2012). Ye esea ch o en s ill lacks s ong heo e ical and
sys ema ic insigh s on he in icacies o pu chasing success and does no make enough use o
ad anced empi ical me hods (see o ins ance Mu ay, Ko abe, & Zhou, 2005; Quin ens,
Pauwels, & Ma hyssens, 2006b; T essin & Rich e , 2014).
Hence, while mos esea ch in he ield emains s uck in a desc ip i e discou se, we will
apply a s uc u al equa ion modeling echnique o be e esea ch in o he in icacies o highe
o lowe pu chasing pe o mance owing o di e en o ganiza ional design choices. In doing so,
we build ou causal model on he esou ce-based iew and ansac ion cos economics and make
use o a esea ch pla o m iden i ied in a ecen li e a u e e iew (T essin & Rich e , 2014).
2. The Causal Model and Resea ch Hypo heses
In he ollowing we ou line ou causal model o pu chasing success. The model has i e
o ganiza ional s uc u e cons uc s, namely cen aliza ion (e.g. Gonzalez-Pad on, Hul , &
Calan one, 2008), s anda diza ion (e.g. Giannakis, Do an, & Chen, 2012), specializa ion (e.g.
Wang, Singh, Samson, & Powe , 2011), con igu a ion (e.g. Ha mann, T au mann, & Jahns,
2008), and in ol emen (e.g. Giannakis e al., 2012), hypo hesized o posi i ely in luence
pu chasing and he ewi h i m pe o mance.
Building on he ansac ion and in o ma ion cos economics we ou line a posi i e impac o
cen aliza ion and s anda diza ion on pu chasing pe o mance and he ewi h on i m
pe o mance. Cen aliza ion e e s o he concen a ion o agg ega ion o decision-making
au ho i y in a single o ganiza ional uni , o ins ance a he headqua e s le el. The o e all
e iciency o a cen ally o ganized adminis a ion o global pu chasing ac i i ies is supposed o
be highe han in a decen alized s uc u e: Since adminis a i e unc ions in ol ing o ins ance
in o ma ion p ocessing and moni o ing p ac ices a e duplica ed in decen alized s uc u es (e.g.
Galb ai h, 1973; Ghoshal & Noh ia, 1993). S anda diza ion e e s o he deg ee o which
pu chasing ac i i ies a e de ined by ules, s anda d p ocedu es and ools (such as supplie s
a ing sys ems and audi ing, in o ma ion sha ing sys ems, pe o mance epo ing, isk planning,
and quali y managemen ools). These s anda ds a e designed o educe unce ain y and
a ia ion in he ou comes, and a e he ewi h supposed o posi i ely impac pu chasing and i m
pe o mance (Ga ido-Samaniego & Gu ié ez-Cillán, 2004; Johns on & Bonoma, 1981;
Ka jalainen & Salmi, 2013; Sanchez-Rod iguez, Hemswo h, Ma inez-Lo en e, & Cla el,
2006).
Building on he esou ce-based iew, we hypo hesize a posi i e impac o specializa ion,
con igu a ion and in ol emen on pu chasing and i m pe o mance. Specializa ion e e s o
he epe i i eness o asks (Glock & Hoch ein, 2011) and o he ex en o which specialized
skills a e exis en in he depa men . These skills comp ise: eam building, s a egic planning,
communica ion, echnical, and inancial skills (e.g. Giunipe o, Hand ield, & El an awy, 2006).
These pu chasing skills a e esou ces o he i m ha lead o ope a ional (pu chasing), and
hence, i m pe o mance (Ke k eld & Ha mann, 2012). Con igu a ion is de ined as he pu chasing
depa men ’s s a us in he company, and hus, i s s a egic impo ance and exe ion o in luence. Gi ing
s a egic in luence o he pu chasing depa men o especially o he Chie Pu chasing O ice leads o
highe esou ce access in he i m (in e ms o ime, human and inancial esou ces). This enhances he
pu chasing depa men ’s capabili ies and he ewi h leads o highe pu chasing and i m pe o mance
(e.g. Kusaba, Mose , & Rod igues, 2011; Webe , Hie e, Laue , & Ren z, 2010). In ol emen is he
Tabea T essin e al. O ganiza ional S uc u e and Pu chasing Success
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 3
ex en o in eg a ion o unc ional and hie a chical le els (Glock & Hoch ein, 2011) in he pu chasing
p ocess; o en he o e all size o a pu chasing eam is e e ed o as a measu e o in ol emen (Johns on
& Bonoma, 1981). A highe in ol emen inc eases he capabili ies used o decision-making and is
supposed o posi i ely impac pu chasing and i m pe o mance. In hei empi ical s udy, Na asimhan
and Das (2001) ind a posi i e e ec o c oss- unc ional in eg a ion on i m pe o mance and Bals,
Ha mann, and Ri e (2009) e eal a posi i e impac o collabo a ion on pu chasing pe o mance in
p ocu ing ma ke ing se ices.
3. The Sample and Resea ch Me hodology
In o de o es he abo e esea ch hypo heses, we make use o a sample o n=195 pu chase s
in e iewed in Ap il-May 2014 by means o a compu e assis ed elephone in e iew. The
sampling ame was aken om Hoppens ed ’s di ec o y o i ms and we ocused on i ms
belonging o he manu ac u ing indus y (i.e. Eu opean Union’s NACE codes 2****, 30***,
and 325**) and pu chasing hei goods om in e na ional supplie s. The expe ienced elephone
in e iewe s we e all ho oughly b ie ed be o ehand he s udy. Non- esponse pa e ns we e
checked ex-pos and did no poin o p oblems o su ey design. The majo i y o i ms su eyed
has be ween 250 and 1999 employees. The sample comp ises 37 di e en sou cing loca ions
(na ions in which he majo supplie is loca ed), and he ewi h o e s a good pla o m o he
p ojec .
The i ems used o ope a ionalize he cons uc s a e all aken om he li e a u e (some imes
wi h sligh adap a ions) – we e e ed o he ollowing ope a ionaliza ions in designing ou
measu emen models: Cen aliza ion is aken om Quin ens, Pauwels, and Ma hyssens
(2006a), s anda diza ion is a selec ion o ools p esen ed by Ka jalainen and Salmi (2013).
Specializa ion is a collec ion o he mos impo an skills o pu chasing p o essionals (collec ed
by Giunipe o & Pea cy, 2000; Pe e sen, F aye , & Scannell, 2000; T en & Monczka, 2003).
Con igu a ion is aken om Paul aj (2011) and he scale used o in ol emen is based on Bals
e al. (2009). Ou dependen cons uc s a e pu chasing pe o mance, ope a ionalized as changes
in pu chasing ime, cos and quali y due o in e na ional sou cing ac i i ies (see González-
Beni o, 2007, 2010), and i m pe o mance in e ms o imp o emen s o inancial (p o i a ge
achie emen ) and non- inancial (cus ome sa is ac ion, compe i i e ad an age) pe o mance in
he pas yea s (see Chen, Tsou, & Huang, 2009).
To empi ically es ou hypo heses we make use o PLS-SEM and Sma PLS 3.0 (Ringle,
Wende, & Becke , 2014). Following he p ocedu es ou lined in Hai , Hul , Ringle, and Sa s ed
(2014), we e alua ed he measu emen models i s . All measu emen models a e unc i ical wi h
loadings, mos ly abo e 0.7. Rega ding ou o ma i e cons uc s, some weigh s a e insigni ican ;
ye , ollowing he p ocedu e ecommended by Hai e al. (2014), we enounce elimina ing any
o ma i e indica o s (specializa ion, s anda diza ion) o he sake o he cons uc s’
comple eness. Ha ing checked he measu emen models, we will concen a e on he esul s
de i ed o he s uc u al o inne model in he ollowing.
4. Discussion o Resul s
The ollowing igu e p esen s he causal model hypo hesized and he esul s o he o al
sample (‘All’) as well as o wo subsamples, namely esul s o hose i ms sou cing om high
cos coun ies (‘HCC’) e sus i ms sou cing om low cos coun ies (‘LCC’). The la e is
inco po a ed, as con ingency app oaches in pu chasing sugges ha ela ionships a e con ingen
on en i onmen al ac o s (an assump ion which will need u he heo e ical elabo a ion in
Tabea T essin e al. O ganiza ional S uc u e and Pu chasing Success
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 4
p og essing wi h his p ojec ).
Figu e 1: Causal model and esul s
Fi s , looking a he o al sample, we ind ha pu chasing pe o mance has a signi ican and
posi i e e ec on i m pe o mance. Second, we ind ha ou ou o ou o ganiza ional
s uc u e cons uc s ha e a posi i e and signi ican impac on pu chasing pe o mance (all
excep o in ol emen ). The ewi h, we a e able o explain a mode a e sha e o a iance in
pu chasing pe o mance (namely 20 %). Hence, bo h, ansac ion cos economics and he
esou ce-based iew con ibu e o explaining he in icacies o highe o lowe pu chasing
pe o mance. The explana o y powe o he model mo eo e inc eases conside ably, as soon as
we a e looking a ou subg oups – i.e. he ela ionships ound seem o be con ingen on
en i onmen al ac o s, namely on he cha ac e is ics o high and low-cos coun ies.
In o al, he mos impo an d i e o pu chasing pe o mance is specializa ion. Hence,
specializa ion is key o achie ing a good pu chasing pe o mance in e ms o educing cos s,
inc easing quali y and educing ime. Among he skills used o ope a ionalize specializa ion,
we ind ha especially in e cul u al, cos analy ical, and echnical skills seem o be he mos
ele an d i e s o pe o mance. This is ollowed a a dis ance by con igu a ion, s anda diza ion
and cen aliza ion - all showing a he compa able pa h coe icien s. Cen alized s uc u es in
which pu chasing p ocess s ages such as con ac managemen , supplie selec ion and
e alua ion a e cen alized in one uni a e p omising in e ms o inc easing he pe o mance o
pu chasing depa men s. Likewise s anda diza ion o p ocedu es and ools such as cos -bene i
analyses, pe o mance acking, quali y, and isk managemen induces a highe pe o mance.
Finally, con igu ing he pu chasing depa men in such a way ha i has a pu chasing s a egy
and goals aligned wi h wha he op managemen en isages, d i es he pe o mance o
pu chasing ac i i ies up.
These ela ionships a y o a e con ingen on he pu chasing en i onmen s. In high cos
coun ies, wo aspec s a e o speci ic ele ance, namely con igu a ion o pu chasing
depa men s and s anda diza ion o p ocedu es and ools. I.e. when sou cing om high cos
coun ies, pu chasing depa men s should be gi en isibili y in op managemen and alignmen
HCC 0.121
LCC 0.476***
All 0.292**
Resou ce-based View T ansac ion Cos App oach
Fi m
Pe o mance
COMP_ADV
CUST_SATIS
PROFIT_
TARGET
Pe o mance
Fac o (LVS)
Cen aliza ion
Con igu a ion
S anda diza ion
Specializa ion
In ol emen
Pu chasing
Pe o mance
CONTRACT
DEF_NEED
SUPPL_EVAL
SUPPL_SELECT
CONTRACT
DEF_NEED
SUPPL_EVAL
SUPPL_SELECT
CPO
GOALS
PU_STRAT
TECH_SKILLS
COMM
COST_ANALY
IND_KNOWL
INTERCULT_SKILLS
AUCTIONS
CONTRACT
COST_BEN_ANALY
EPROC
FORECAST
PERF_TRACK
QUAL_MGMT
RISK_MGMT
H1: +
H6: +
H2: +
H3: +
H4: +
H5: +
HCC 0.238***
LCC 0.077
All 0.118*
HCC 0.116
LCC 0.409***
All 0.253***
HCC 0.119
LCC 0.134*
All 0.111**
HCC 0.055
LCC 0.058
All 0.055
HCC 0.318***
LCC 0.042
All 0.126*
R² Pu chasing
Pe o mance
Fi m
Pe o mance
HCC 0.312 0.015
LCC 0.279 0.227
All 0.197 0.085
0.757
0.705
0.818
0.764
0.672
-0.053
0.491
0.030
0.393
-0.111
0.151
-0.209
0.141
0.348
0.215
0.437
0.316
0.716
0.819
0.723
0.772
0.734
0.677
0.746
0.679
0.866
0.676
Tabea T essin e al. O ganiza ional S uc u e and Pu chasing Success
2nd In e na ional Symposium on Pa ial Leas Squa es Pa h Modeling, Se ille (Spain), 2015 5
wi h co po a e s a egies. Mo eo e , managemen needs o make su e ha s anda ds a e
es ablished and ollowed h oughou all pu chasing ac i i ies o be e icien . In low cos
coun ies, wo o he aspec s a e o ele ance: Specializa ion, i.e. he skills a ailable in he
pu chasing depa men . Hence, i ms need o make su e ha hei s a ing speci ically ocuses
on in e cul u al, cos analy ical, and echnical skills o hei pu chase s. Second, cen aliza ion
is key o inc easing pu chasing pe o mance. I.e. i ms which cen alized hei pu chasing
depa men s wi hin he home coun y pe o med be e han decen alized i ms when sou cing
om low cos coun ies.
Bo h subg oup models ha e a good explana o y powe (o 28% espec i ely 31%). Thus, i
is wo h o u he in es iga e in o he con ingency e ec s which seem o be immanen in
pu chasing pe o mance models. Hence, bo h heo y building and empi ical es ing o
con ingency e ec s a e en isaged nex s eps in p og essing wi h his esea ch.
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