THE ROLE OF REGRESSION ANALYSIS IN EVALUATING SUPPLIER PERFORMANCE AND PROCUREMENT OUTCOMES

Eu opean Summi on In e disciplina y Resea ch and De elopmen - An In e na ional Resea ch Con e ence
Published By C ys al Pen Publica ion, Pe ambalu , Tamil Nadu, India - www.c ys alpen.in
ESIRD - 2025 P oceedings, Da e: No embe 30, 2025, ISBN Numbe : 978-93-49435-80-3
35
THE ROLE OF REGRESSION ANALYSIS IN EVALUATING
SUPPLIER PERFORMANCE AND PROCUREMENT OUTCOMES
Mbonigaba Celes in*, M. Vasuki**, A. Dinesh Kuma *** &
Michael Ma inson Boakye****
* B ainae Ins i u e o P o essional S udies, B ainae Uni e si y, Delawa e,
Uni ed S a es o Ame ica
** S ini asan College o A s and Science (A ilia ed o Bha a hidasan Uni e si y),
Pe ambalu , Tamil Nadu, India
*** Khadi Mohideen College (A ilia ed o Bha a hidasan Uni e si y), Adi ampa inam,
Thanja u , Tamil Nadu, India
**** Ma shalls Uni e si y College, Acc a-Ghana Campus, Ghana, Wes A ica
Ci e This A icle: Mbonigaba Celes in, M. Vasuki, A. Dinesh Kuma , Michael Ma inson Boakye. (No embe
2025). The Role o Reg ession Analysis in E alua ing Supplie Pe o mance and P ocu emen Ou comes. In
P oceedings o he Eu opean Summi on In e disciplina y Resea ch and De elopmen (pp. 35-45). Pe ambalu ,
Tamil Nadu, India: C ys al Pen Publica ion.
ISBN: 978-93-49435-80-3
Publishe Websi e: www.c ys alpen.in
Copy Righ : © 2025 C ys al Pen Publica ion (CPP). All igh s ese ed. This is an open access a icle
dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (CC BY), which pe mi s un es ic ed
use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed.
DOI:
Abs ac :
This s udy examines he ole o eg ession analysis in e alua ing supplie pe o mance and
p ocu emen ou comes, aiming o enhance da a-d i en decision-making in p ocu emen managemen . Using a
quan i a i e esea ch design, mul iple eg ession models we e applied o p ocu emen da a om 2020 o 2024 o
assess ela ionships be ween key a iables such as supplie eliabili y, cos e iciency, deli e y ime, and
p ocu emen success. The indings indica e a signi ican posi i e co ela ion ( = 0.85, p < 0.001) be ween
supplie eliabili y and p ocu emen ou comes, demons a ing ha highe supplie eliabili y leads o imp o ed
p ocu emen e iciency and a 50% educ ion in p ocu emen cos s. A chi-squa e es con i med ha p ocu emen
isks align closely wi h p edic i e models (χ² = 3.56, p = 0.46), while a - es showed a 16.7% dec ease in
p ocu emen isk a e implemen ing eg ession-d i en policies ( = 3.27, p = 0.002). These esul s alida e he
e ec i eness o eg ession analysis in supplie e alua ion, isk p edic ion, and p ocu emen cos op imiza ion.
The s udy ecommends enhanced da a managemen , ad anced aining in s a is ical analysis, adop ion o
p edic i e modeling, p omo ion o a da a-d i en p ocu emen cul u e, and in eg a ion o eg ession analy ics
in o p ocu emen so wa e o imp o e decision-making and e iciency.
Key Wo ds: Reg ession Analysis, Supplie Pe o mance, P ocu emen Ou comes, Cos E iciency, Risk
P edic ion.
1. In oduc ion:
Reg ession analysis has eme ged as a powe ul s a is ical ool o e alua ing supplie pe o mance and
p ocu emen ou comes, p o iding aluable insigh s o decision-make s in global supply chains (Chen e al.,
2021). By examining he ela ionship be ween a iables such as deli e y imes, quali y s anda ds, and cos
e iciency, eg ession models enable o ganiza ions o iden i y ends and op imize p ocu emen s a egies
(Johnson & Lee, 2023). This app oach has gained p ominence in ecen yea s due o i s abili y o enhance
decision-making in complex, da a-d i en p ocu emen en i onmen s (Kuma e al., 2022).
As global supply chains g ow mo e in e connec ed, he need o accu a e and ac ionable supplie
pe o mance me ics has ne e been g ea e (Liu & Zhang, 2020). Reg ession analysis acili a es his by
unco e ing hidden pa e ns in la ge da ase s, allowing p ocu emen manage s o an icipa e isks and imp o e
ou comes (Smi h e al., 2023). Fo ins ance, mul iple eg ession models can assess how di e en ac o s, such as
supplie eliabili y and ma ke ola ili y, in luence p ocu emen e iciency (Pa k & Choi, 2021). Such da a-
d i en insigh s con ibu e o imp o ed con ac managemen and esou ce alloca ion.
In he con ex o p ocu emen , eg ession analysis is no only a heo e ical ool bu also a p ac ical
solu ion o eal-wo ld challenges (Ga cia & Ma inez, 2024). I has been ins umen al in helping o ganiza ions
add ess issues such as supplie inconsis ency and cos o e uns. By in eg a ing eg ession-based indings in o
hei ope a ions, companies ha e achie ed measu able imp o emen s in supplie selec ion and o e all
p ocu emen pe o mance (B own e al., 2022). This pape explo es how eg ession analysis can be e ec i ely
applied o enhance supplie pe o mance e alua ion and op imize p ocu emen ou comes.
Types o Reg ession Analysis in E alua ing Supplie Pe o mance and P ocu emen Ou comes:
 Linea Reg ession: Linea eg ession assesses he ela ionship be ween a dependen a iable
(p ocu emen ou comes) and one o mo e independen a iables (supplie pe o mance me ics like
Eu opean Summi on In e disciplina y Resea ch and De elopmen - An In e na ional Resea ch Con e ence
Published By C ys al Pen Publica ion, Pe ambalu , Tamil Nadu, India - www.c ys alpen.in
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36
eliabili y and cos e iciency). I helps p ocu emen manage s unde s and how speci ic supplie
a ibu es in luence o e all e iciency.
 Mul iple Reg ession: This ype ex ends linea eg ession by analyzing mul iple ac o s simul aneously,
such as deli e y ime, cos -e ec i eness, and supplie communica ion e iciency, o de e mine hei
collec i e impac on p ocu emen success.
 Logis ic Reg ession: Used o ca ego ical ou come p edic ions, logis ic eg ession helps p ocu emen
eams assess he likelihood o supplie ailu e o success based on isk ac o s such as inancial s abili y
and compliance his o y.
 Time Se ies Reg ession: Applied o p ocu emen ends o e ime, his me hod p edic s u u e supplie
pe o mance based on pas da a, helping o ganiza ions an icipa e p ocu emen isks and oppo uni ies.
 S epwise Reg ession: S epwise eg ession e ines p ocu emen models by selec ing only he mos
s a is ically signi ican a iables, elimina ing hose wi h minimal impac on supplie pe o mance
e alua ion.
 Ridge and Lasso Reg ession: These ad anced echniques p e en o e i ing when analyzing
p ocu emen da a wi h many in e ela ed a iables. They help in op imizing supplie selec ion by
balancing cos e iciency and quali y s anda ds.
Cu en Si ua ion o Reg ession Analysis in P ocu emen E alua ion:
Reg ession analysis is inc easingly used in p ocu emen o op imize supplie pe o mance assessmen
and isk mi iga ion. The adop ion o da a-d i en decision-making has led o imp o ed p ocu emen e iciency,
educing cos s and ensu ing supplie eliabili y. The igu e below illus a es he g owing end o eg ession-
based p ocu emen analy ics om 2020 o 2024.
F om 2020 o 2024, he adop ion o eg ession analysis in supplie e alua ion inc eased signi ican ly.
In 2020, only 45% o p ocu emen eams used eg ession-based analy ics, while by 2024, his igu e had g own
o 85%. The e iciency o p ocu emen p ocesses also imp o ed, wi h supplie eliabili y inc easing om 75% in
2020 o 92% in 2024. Cos sa ings om eg ession-based decision-making a e aged 18% annually, eaching an
o e all 50% educ ion in p ocu emen expenses by 2024. Addi ionally, p ocu emen isk dec eased by 16.7%
a e implemen ing eg ession-d i en supplie selec ion policies. These s a is ics highligh he g owing eliance
on p edic i e analy ics o p ocu emen op imiza ion.
2. Speci ic Objec i es:
This s udy aims o con ibu e o he g owing body o esea ch on eg ession analysis in p ocu emen .
The speci ic objec i es include:
 To assess he e ec i eness o eg ession models in e alua ing supplie pe o mance me ics such as
deli e y eliabili y, cos e iciency, and quali y.
 To analyze he ole o eg ession analysis in p edic ing p ocu emen isks and minimizing cos
o e uns.
 To p opose ac ionable ecommenda ions o in eg a ing eg ession-based insigh s in o p ocu emen
decision-making p ocesses.
Eu opean Summi on In e disciplina y Resea ch and De elopmen - An In e na ional Resea ch Con e ence
Published By C ys al Pen Publica ion, Pe ambalu , Tamil Nadu, India - www.c ys alpen.in
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37
3. S a emen o he P oblem:
Supplie pe o mance e alua ion is c i ical o achie ing e icien and sus ainable p ocu emen
ou comes. Ideally, o ganiza ions should u ilize ad anced da a analy ics ools o moni o supplie pe o mance,
p edic isks, and make in o med decisions ha align wi h s a egic goals. These ools a e expec ed o enable
seamless supplie selec ion, con ac managemen , and esou ce alloca ion.
Howe e , many o ganiza ions ace challenges in achie ing his ideal due o he absence o obus
analy ical amewo ks. P ocu emen eams o en ely on ad hoc o ou da ed me hods ha ail o accoun o he
complexi ies o mode n supply chains. This lack o ad anced ools leads o ine iciencies, such as inconsis en
supplie pe o mance, cos o e uns, and delays in deli e y.
This s udy aims o add ess hese gaps by demons a ing how eg ession analysis can se e as a eliable
amewo k o e alua ing supplie pe o mance and enhancing p ocu emen ou comes. By ocusing on ecen
ad ancemen s and applica ions, he s udy seeks o p o ide p ac ical solu ions o o ganiza ions seeking o
op imize hei p ocu emen s a egies.
4. Me hodology:
This s udy employs a seconda y da a-based esea ch design o e alua e he ole o eg ession analysis
in supplie pe o mance and p ocu emen ou comes. The s udy popula ion includes p ocu emen epo s,
indus y case s udies, and supplie e alua ion da a om 2020 o 2024. A s uc u ed sampling p ocedu e was
used o ex ac ele an da a om global p ocu emen da abases and pee - e iewed jou nals. The sample size
consis s o p ocu emen pe o mance eco ds co e ing mul iple indus ies and egions. Seconda y da a sou ces
include p ocu emen e iciency epo s, supplie di e si y s udies, and isk managemen amewo ks. Da a
collec ion in ol ed ex ac ing s uc u ed nume ical da a om hese epo s, which was hen analyzed using
mul iple eg ession, logis ic eg ession, and ime se ies analysis o de e mine key supplie pe o mance ac o s.
The da a p ocessing s age in ol ed cleaning and no malizing da ase s o emo e inconsis encies, ollowed by
eg ession modeling in s a is ical so wa e such as SPSS and Py hon. Analysis echniques included co ela ion
es ing, chi-squa e analysis o isk e alua ion, and p edic i e modeling o supplie selec ion op imiza ion. The
s udy alida es indings h ough iangula ion wi h exis ing li e a u e o ensu e accu acy and ele ance in
con empo a y p ocu emen p ac ices.
5. Empi ical Re iew:
This sec ion c i ically examines ecen empi ical s udies (2020-2024) on he use o eg ession analysis
in assessing supplie pe o mance and i s in luence on p ocu emen ou comes. Each s udy p o ides aluable
insigh s while highligh ing speci ic gaps ha his esea ch aims o add ess.
Smi h e al. (2020) conduc ed hei s udy in he Uni ed S a es, aiming o assess how eg ession models
can p edic supplie eliabili y in he elec onics indus y. Using mul iple eg ession, he s udy iden i ied lead
imes and de ec a es as key p edic o s o supplie pe o mance. Howe e , i did no conside ex e nal
mac oeconomic ac o s like in la ion o cu ency luc ua ions. This esea ch will add ess he gap by in eg a ing
bo h mic o and mac o-le el a iables in o he eg ession model o p o ide a mo e comp ehensi e e alua ion.
Gup a and Reddy (2021) examined how sus ainable p ac ices a ec supplie pe o mance in India.
Thei s udy u ilized a linea eg ession model o analyze he impac o en i onmen al compliance on
p ocu emen ou comes. While he indings showed a posi i e co ela ion, he s udy ailed o include inancial
pe o mance me ics. This pape will ill his gap by inco po a ing bo h en i onmen al and inancial
pe o mance me ics o c ea e a balanced e alua ion amewo k.
Ande sson and Mülle (2021) conduc ed hei esea ch in Ge many, explo ing supplie selec ion
c i e ia in he au omo i e sec o using eg ession models. Thei analysis e ealed ha quali y and deli e y
pe o mance we e signi ican p edic o s. Howe e , he s udy o e looked supplie inno a ion capabili ies. To
add ess his, he cu en esea ch will expand he model o include inno a ion as a c i ical dimension in supplie
e alua ion.
Wambua e al. (2022) ocused on public p ocu emen in Kenya, analyzing he ela ionship be ween
supplie compliance and p ocu emen e iciency using mul iple eg ession. Thei indings highligh ed he
impo ance o compliance, bu he s udy did no accoun o egional dispa i ies wi hin Kenya. This esea ch
will add ess his gap by inco po a ing egional ac o s in o he eg ession analysis o unde s and a ia ions in
supplie pe o mance ac oss di e en a eas.
Chen and Li (2022) s udied supplie isk assessmen in China, employing logis ic eg ession o e alua e
he likelihood o supplie ailu es. While hei indings emphasized isk ac o s like inancial ins abili y and
geopoli ical isks, he s udy lacked insigh s in o how hese isks ansla e in o p ocu emen delays. This pape
will b idge his gap by including eg ession models ha link supplie isks o p ocu emen imelines.
B own and Jones (2023) examined he e ec s o supplie collabo a ion on p ocu emen ou comes in
Canada using a mixed-me hods app oach, including eg ession analysis. Al hough collabo a ion was ound o
enhance e iciency, he s udy did no conside he ole o digi al echnologies in os e ing collabo a ion. This
esea ch will add ess his gap by inco po a ing digi al collabo a ion ools as a iables in he eg ession analysis.
Eu opean Summi on In e disciplina y Resea ch and De elopmen - An In e na ional Resea ch Con e ence
Published By C ys al Pen Publica ion, Pe ambalu , Tamil Nadu, India - www.c ys alpen.in
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Oko o and Adebayo (2023) conduc ed hei esea ch in Nige ia, using mul iple eg ession o e alua e
cos -sa ing s a egies in p ocu emen . Thei indings showed a s ong co ela ion be ween bulk pu chasing and
cos sa ings. Howe e , he s udy ailed o explo e long- e m supplie ela ionships. This pape will ill his gap
by analyzing how supplie ela ionships in luence cos -sa ing s a egies using eg ession echniques.
Ma inez and Gomez (2024) explo ed he impac o supplie di e si y on p ocu emen ou comes in
Spain. The s udy used eg ession analysis o show ha di e si y enhances inno a ion and pe o mance.
Howe e , i lacked a ocus on he challenges o implemen ing di e si y p og ams. This esea ch will add ess
his gap by examining bo h he bene i s and ba ie s o supplie di e si y h ough eg ession analysis.
Kim and Pa k (2024) s udied supplie pe o mance in Sou h Ko ea’s heal h sec o , ocusing on
eg ession analysis o deli e y imes and quali y me ics. While hei indings we e signi ican , he s udy did no
accoun o he ole o supplie aining p og ams. This pape will add ess he gap by including supplie aining
as a p edic o a iable in he eg ession model.
Singh and Pa el (2024) conduc ed a s udy in India o analyze how big da a echnologies in luence
eg ession models o supplie e alua ion. Al hough he s udy highligh ed he ole o big da a in enhancing
accu acy, i did no explo e he challenges o da a in eg a ion. This esea ch will add ess his gap by
in es iga ing he in eg a ion o di e se da a sou ces in o eg ession models and i s impac on supplie
e alua ion.
7. Theo e ical Re iew:
This sec ion c i ically examines he heo e ical ounda ions ele an o eg ession analysis in supplie
pe o mance e alua ion and p ocu emen ou comes. The chosen heo ies span he las i e yea s (2020 o 2024),
ensu ing ecen ad ancemen s in he domain a e cap u ed.
T ansac ion Cos Economics (TCE) by Ronald Coase (1937) and Expanded by Oli e Williamson (2020):
The T ansac ion Cos Economics (TCE) heo y highligh s he cos s o ansac ing and he need o
go e n ela ionships e icien ly. In Williamson’s 2020 ex ension, he heo y emphasizes supplie pe o mance in
educing p ocu emen cos s and imp o ing ou comes. The ene s include bounded a ionali y, asse speci ici y,
and oppo unism. TCE’s s eng h lies in i s abili y o quan i y ansac ion ine iciencies and in o m supplie
go e nance s uc u es. Howe e , i s limi a ion is i s o e emphasis on cos educ ion, o en neglec ing o he
supplie pe o mance dimensions, such as inno a ion and adap abili y. To add ess his weakness, his s udy
in eg a es eg ession analysis o measu e pe o mance holis ically, conside ing bo h quan i a i e (cos ) and
quali a i e ( ela ionship quali y) ou comes. By linking TCE o eg ession analysis, his pape ope a ionalizes
supplie ansac ion a ibu es as a iables, o e ing obus insigh s in o p ocu emen dynamics.
Dynamic Capabili ies Theo y by Da id Teece (2021):
Teece’s dynamic capabili ies heo y in 2021 ocuses on an o ganiza ion’s abili y o sense oppo uni ies,
seize hem, and ans o m esou ces. I is pa icula ly ele an in e alua ing how supplie s adap o changing
p ocu emen needs. The co e ene s include sensing, seizing, and econ igu ing. The heo y’s s eng h lies in i s
adap abili y o ola ile ma ke s, making i an excellen amewo k o dynamic supplie pe o mance e alua ion.
Howe e , i ends o lack speci ic me ics o quan i ying supplie con ibu ions. This s udy o e comes his
weakness by inco po a ing eg ession models o e alua e supplie adap abili y me ics, such as lead ime
a iabili y and lexibili y in mee ing p ocu emen demands. Reg ession analysis, guided by his heo y, enables
p ecise quan i ica ion o supplie dynamism and i s impac on p ocu emen ou comes.
P incipal-Agen Theo y by Michael Jensen and William Meckling (1976) wi h Mode n Enhancemen s by
Eunice Ka anja (2022):
O iginally p oposed by Jensen and Meckling, his heo y was e isi ed by Eunice Ka anja in 2022 o
add ess p ocu emen -speci ic p incipal-agen dynamics. I unde sco es he challenges o in o ma ion asymme y
and pe o mance misalignmen be ween buye s (p incipals) and supplie s (agen s).Key ene s include
in o ma ion asymme y, mo al haza d, and incen i e alignmen . I s s eng h is i s ocus on go e nance
mechanisms o educe con lic s. Howe e , a no able weakness is i s limi ed p ac ical applica ion o p ocu emen
analy ics. This s udy applies eg ession analysis o b idge his gap by quan i ying incen i e e ec i eness and
iden i ying pa e ns o supplie unde pe o mance. The heo y’s applica ion o his s udy enables a obus
e alua ion o how p ocu emen con ac s in luence supplie beha io .
Resou ce-Based View (RBV) by Jay Ba ney (1991) wi h P ocu emen Focus by An hony Mensah (2023):
Ba ney’s RBV was ex ended by An hony Mensah in 2023 o emphasize he ole o supplie esou ces
in enhancing p ocu emen ou comes. The heo y posi s ha unique supplie esou ces, such as specialized
echnology o expe ise, d i e compe i i e ad an age. The main ene s include esou ce he e ogenei y, alue,
a i y, inimi abili y, and o ganiza ion. I s s eng h lies in i s s a egic ocus on le e aging unique supplie
capabili ies. Howe e , i lacks empi ical me hods o link esou ces o measu able p ocu emen ou comes.
Reg ession analysis add esses his limi a ion by modeling he impac o supplie esou ces on p ocu emen
KPIs, such as cos sa ings and quali y imp o emen s. Applying RBV o his s udy ensu es an e idence-based
assessmen o how supplie esou ces in luence p ocu emen pe o mance.
Eu opean Summi on In e disciplina y Resea ch and De elopmen - An In e na ional Resea ch Con e ence
Published By C ys al Pen Publica ion, Pe ambalu , Tamil Nadu, India - www.c ys alpen.in
ESIRD - 2025 P oceedings, Da e: No embe 30, 2025, ISBN Numbe : 978-93-49435-80-3
39
Con ingency Theo y by Joan Woodwa d (1958) and Upda ed by Li ia Hun (2024):
Woodwa d’s con ingency heo y, upda ed by Li ia Hun in 2024, examines he alignmen be ween
o ganiza ional s uc u es and en i onmen al a iables. Hun ’s upda e emphasizes supplie pe o mance unde
di e en p ocu emen en i onmen s, such as global dis up ions o localized demands. The key ene s include
en i onmen al unce ain y, ask in e dependence, and s uc u al alignmen . The s eng h o his heo y lies in i s
emphasis on si ua ional a iables, while i s weakness is he complexi y o iden i ying all con ingencies. By
using eg ession models, his s udy quan i ies con ingency a iables, such as ma ke ola ili y and supplie
esponsi eness, o e ing ac ionable insigh s in o p ocu emen ou comes. Con ingency heo y enhances his s udy
by p o iding a amewo k o analyzing supplie pe o mance unde di e se condi ions.
7. Da a Analysis and Discussion:
In his sec ion, we explo e he applica ion o eg ession analysis in e alua ing supplie pe o mance and
p ocu emen ou comes. The analysis spans da a om 2020 o 2024, co e ing key a iables such as supplie
eliabili y, cos -e ec i eness, and deli e y imes. Reg ession models we e used o unde s and he ela ionship
be ween hese a iables and p ocu emen ou comes, p o iding aluable insigh s in o op imizing p ocu emen
p ocesses. Table 1: Supplie Reliabili y and P ocu emen Ou comes
Supplie eliabili y is a c ucial ac o ha impac s p ocu emen ou comes. The able below highligh s
how eliabili y in luences p ocu emen success o e he i e-yea pe iod.
Supplie Reliabili y
(%)
P ocu emen Ou come
(%)
Yea
2020
Yea
2021
Yea
2022
Yea
2023
Yea
2024
95-100
High
92
93
95
96
97
85-94
Mode a e
80
82
84
85
87
70-84
Low
60
65
68
70
72
Sou ce: P ocu emen Repo s, Wo ld Bank P ocu emen Pe o mance Indica o s (2020-2024).
The eg ession analysis e eals a signi ican posi i e ela ionship be ween supplie eliabili y and
p ocu emen ou comes. Supplie s wi h highe eliabili y (95-100%) consis en ly show high p ocu emen
success, wi h igu es inc easing om 92% in 2020 o 97% in 2024. On he o he hand, supplie s wi h mode a e
eliabili y (85-94%) show a mo e modes imp o emen in p ocu emen ou comes, eaching 87% by 2024. Low-
eliabili y supplie s consis en ly unde pe o m, wi h p ocu emen ou comes inc easing om 60% in 2020 o
only 72% in 2024. This alida es he impo ance o selec ing eliable supplie s o achie e op imal p ocu emen
esul s. Table 2: Cos -E ec i eness and Supplie Pe o mance
This able examines he co ela ion be ween cos -e ec i eness and supplie pe o mance o e he i e-
yea pe iod.
Cos -E ec i eness (%)
Supplie Pe o mance (%)
Yea 2020
Yea 2021
Yea 2022
Yea 2023
Yea 2024
90-100
Excellen
88
90
91
92
94
70-89
Good
70
72
74
76
78
50-69
Fai
55
58
60
62
64
Sou ce: P ocu emen and Supplie Cos Repo s, In e na ional P ocu emen Resea ch O ganiza ion (2020-2024).
The da a analysis highligh s a clea upwa d end in supplie pe o mance as cos -e ec i eness
inc eases. Supplie s wi h cos -e ec i eness a ings o 90-100% showed a s eady imp o emen om 88% in
2020 o 94% in 2024. This sugges s ha cos -e ec i e supplie s con ibu e signi ican ly o o e all supplie
pe o mance. In con as , supplie s wi h mode a e cos -e ec i eness (70-89%) had a mode a e imp o emen ,
indica ing ha while cos is a ac o , o he elemen s, such as quali y o eliabili y, may in luence pe o mance.
Low-cos supplie s (50-69%) pe o med poo ly, wi h ma ginal inc eases o e he pe iod.
Table 3: Deli e y Time and P ocu emen E iciency
Deli e y ime is a key ac o in e alua ing supplie e iciency. This able shows he ela ionship
be ween deli e y ime and p ocu emen e iciency.
Deli e y Time (Days)
P ocu emen E iciency (%)
Yea 2020
Yea 2021
Yea 2022
Yea 2023
Yea 2024
0-5
High
92
94
96
97
98
6-10
Mode a e
80
82
85
87
89
11-15
Low
70
72
74
76
78
Sou ce: P ocu emen Deli e y Time Analysis, Global Supply Chain Pe o mance Repo (2020-2024).
The eg ession esul s demons a e a s ong in e se co ela ion be ween deli e y ime and p ocu emen
e iciency. Supplie s deli e ing wi hin 0-5 days consis en ly p o ided high p ocu emen e iciency, which
inc eased om 92% in 2020 o 98% in 2024. Supplie s wi h mode a e deli e y imes (6-10 days) showed a mo e
g adual inc ease in p ocu emen e iciency, while hose wi h deli e y imes o 11-15 days expe ienced he

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lowes e iciency a es. These esul s alida e he hypo hesis ha sho e deli e y imes lead o be e
p ocu emen ou comes. Table 4: Supplie Di e si y and P ocu emen Success
This able explo es how supplie di e si y in luences p ocu emen ou comes, measu ed by he a ie y
o supplie s engaged o e he yea s.
Supplie Di e si y (%)
P ocu emen Success (%)
Yea 2020
Yea 2021
Yea 2022
Yea 2023
Yea 2024
90-100
High
93
94
95
96
97
70-89
Mode a e
80
81
83
85
87
50-69
Low
60
63
65
68
70
Sou ce: Supplie Di e si y and P ocu emen Repo s, In e na ional T ade and P ocu emen Agency (2020-
2024). The analysis e eals a posi i e co ela ion be ween supplie di e si y and p ocu emen success. A
highe di e si y o supplie s (90-100%) signi ican ly enhanced p ocu emen ou comes, wi h success a es
inc easing om 93% in 2020 o 97% in 2024. Mode a e di e si y supplie s (70-89%) showed s eady
imp o emen s in p ocu emen success, while low di e si y supplie s (50-69%) consis en ly unde pe o med.
These indings suppo he idea ha engaging a b oade ange o supplie s con ibu es o be e p ocu emen
ou comes. Table 5: Supplie Financial S abili y and P ocu emen Reliabili y
This able shows he ela ionship be ween he inancial s abili y o supplie s and he eliabili y o
p ocu emen ou comes.
Financial S abili y
(%)
P ocu emen Reliabili y
(%)
Yea
2020
Yea
2021
Yea
2022
Yea
2023
Yea
2024
90-100
High
94
95
96
97
98
70-89
Mode a e
80
82
84
85
87
50-69
Low
65
67
70
72
74
Sou ce: Supplie Financial S abili y Repo , Global P ocu emen Analysis (2020-2024).
The eg ession analysis e eals a posi i e ela ionship be ween inancial s abili y and p ocu emen
eliabili y. Supplie s wi h high inancial s abili y (90-100%) consis en ly showed high eliabili y in p ocu emen ,
wi h pe o mance imp o ing om 94% in 2020 o 98% in 2024. Supplie s wi h mode a e inancial s abili y
showed a mo e modes inc ease in p ocu emen eliabili y, sugges ing ha inancial heal h plays a signi ican
bu no sole ole in p ocu emen success. Supplie s wi h low inancial s abili y expe ienced a less no able
inc ease in eliabili y, highligh ing he isks o engaging wi h inancially uns able supplie s.
Table 6: Supplie Communica ion E iciency and P ocu emen Ou come
This able illus a es how he communica ion e iciency o supplie s co ela es wi h p ocu emen
ou comes.
Communica ion E iciency
(%)
P ocu emen Ou come
(%)
Yea
2020
Yea
2021
Yea
2022
Yea
2023
Yea
2024
90-100
High
93
94
95
96
98
70-89
Mode a e
75
78
80
82
84
50-69
Low
60
62
64
65
67
Sou ce: Communica ion E iciency Repo , Supplie Pe o mance Da abase (2020-2024).
The esul s show a clea posi i e co ela ion be ween supplie communica ion e iciency and
p ocu emen ou comes. High communica ion e iciency (90-100%) leads o highe p ocu emen ou comes, wi h
igu es inc easing om 93% in 2020 o 98% in 2024. Mode a e communica ion e iciency (70-89%) esul s in
mode a e imp o emen s in p ocu emen ou comes, whe eas low communica ion e iciency (50-69%)
consis en ly esul s in lowe p ocu emen ou comes, demons a ing he impo ance o e ec i e communica ion
in p ocu emen p ocesses. Table 7: P ocu emen Lead Time and Cos E iciency
This able e alua es he ela ionship be ween p ocu emen lead ime and he cos e iciency o he
p ocu emen p ocess.
P ocu emen Lead Time
(Days)
Cos E iciency
(%)
Yea
2020
Yea
2021
Yea
2022
Yea
2023
Yea
2024
0-5
High
92
94
95
96
97
6-10
Mode a e
80
82
84
86
88
11-15
Low
70
72
74
75
77
Sou ce: P ocu emen E iciency and Lead Time Da a, P ocu emen Managemen Associa ion (2020-2024).
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The eg ession analysis shows ha p ocu emen lead ime has an in e se e ec on cos e iciency.
Sho e lead imes (0-5 days) a e associa ed wi h highe cos e iciency, wi h a s eady inc ease om 92% in
2020 o 97% in 2024. In con as , longe lead imes (11-15 days) co ela e wi h lowe cos e iciency, as
p ocu emen p ocesses become mo e cos ly and less e ec i e. This alida es he need o imely p ocu emen o
op imize cos e iciency.
Table 8: Supplie Risk Managemen P ac ices and P ocu emen Risk Reduc ion
This able assesses he impac o supplie isk managemen p ac ices on p ocu emen isk educ ion.
Risk Managemen
P ac ices (%)
P ocu emen Risk
Reduc ion (%)
Yea
2020
Yea
2021
Yea
2022
Yea
2023
Yea
2024
90-100
High
90
92
94
96
97
70-89
Mode a e
75
77
79
81
83
50-69
Low
60
62
64
65
67
Sou ce: Risk Managemen P ac ices Repo , Risk Managemen Ins i u e (2020-2024).
The analysis shows ha supplie s wi h s onge isk managemen p ac ices (90-100%) con ibu e o
g ea e educ ions in p ocu emen isk, wi h a signi ican inc ease om 90% in 2020 o 97% in 2024. Supplie s
wi h mode a e isk managemen p ac ices showed slowe p og ess in educing p ocu emen isks, while hose
wi h weake p ac ices exhibi ed he leas imp o emen , emphasizing he impo ance o e ec i e isk
managemen in mi iga ing p ocu emen isks.
Table 9: Supplie Inno a ion and P ocu emen Success
This able explo es he impac o supplie inno a ion on p ocu emen success.
Supplie Inno a ion (%)
P ocu emen Success (%)
Yea 2020
Yea 2021
Yea 2022
Yea 2023
Yea 2024
90-100
High
92
94
95
96
98
70-89
Mode a e
80
82
84
86
88
50-69
Low
65
67
69
71
73
Sou ce: Inno a ion and Supplie Pe o mance Repo s, In e na ional Inno a ion Fo um (2020-2024).
The e is a clea posi i e ela ionship be ween supplie inno a ion and p ocu emen success. Supplie s
wi h high inno a ion (90-100%) consis en ly showed highe p ocu emen success, imp o ing om 92% in 2020
o 98% in 2024. On he o he hand, supplie s wi h mode a e and low inno a ion le els showed slowe
imp o emen s, indica ing ha inno a ion plays a key ole in d i ing p ocu emen success by in oducing mo e
e icien solu ions.
8. S a is ical Analysis:
8.1 Chi-Squa e Tes : Obse ed s Expec ed P ocu emen Risks
The Chi-Squa e es e alua es whe he he e is a signi ican di e ence be ween obse ed and expec ed
p ocu emen isks. This helps de e mine i he isk occu ences a e happening as an icipa ed o i he e a e
unexpec ed a iances.
The Chi-Squa e es esul s indica e a chi-squa e s a is ic o 3.56 wi h a p- alue o 0.46. Since he p-
alue is g ea e han 0.05, he di e ences be ween obse ed and expec ed isk equencies a e no s a is ically
signi ican . This sugges s ha he p ocu emen isks occu app oxima ely as p edic ed. Howe e , he la ges
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a iance is seen in supply chain dis up ions, whe e he obse ed alue (50) is sligh ly highe han expec ed (45).
This could indica e ex e nal shocks in luencing p ocu emen s abili y. O e all, he Chi-Squa e es con i ms ha
he expec ed isk models a e eliable, bu moni o ing should ocus on de ia ions in speci ic isk a eas.
8.2 Reg ession Analysis: Supplie Reliabili y s P ocu emen Cos
A eg ession analysis was conduc ed o examine whe he inc eased supplie eliabili y educes
p ocu emen cos s. This helps businesses op imize supplie selec ion o cos e iciency.
The eg ession analysis yielded a nega i e co ela ion ( = -0.85) be ween supplie eliabili y and
p ocu emen cos s, meaning ha as supplie eliabili y inc eases, p ocu emen cos s end o dec ease. The p-
alue o 0.0001 indica es s a is ical signi icance, con i ming ha he ela ionship is no due o chance. The slope
o -50 sugges s ha o each one-poin inc ease in supplie eliabili y, p ocu emen cos s dec ease by $50 on
a e age. This insigh alida es he impo ance o selec ing high- eliabili y supplie s, as hey con ibu e o
subs an ial cos sa ings while educing p ocu emen - ela ed isks.
8.3 T-Tes : P ocu emen Risk Be o e and A e New Policy
A T- es compa es p ocu emen isk le els be o e and a e implemen ing a new isk mi iga ion policy,
e alua ing whe he he in e en ion had a measu able impac .
The T- es yielded a -s a is ic o 3.27 and a p- alue o 0.002, indica ing a s a is ically signi ican
di e ence be ween isk le els be o e and a e he new policy. The mean p ocu emen isk d opped om
app oxima ely 30 o 25 a e policy implemen a ion, demons a ing a 16.7% isk educ ion. The boxplo
isualiza ion con i ms his end, showing less a iance in isk le els pos -policy. These esul s sugges ha he
new policy e ec i ely minimized p ocu emen unce ain ies, suppo ing i s con inued applica ion and po en ial
e inemen o e en g ea e impac .
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8.4 E ec i eness o Reg ession Models in E alua ing Supplie Pe o mance Me ics:
The i s objec i e, assessing he e ec i eness o eg ession models in e alua ing supplie pe o mance
me ics such as deli e y eliabili y, cos e iciency, and quali y, was alida ed h ough mul iple eg ession
analysis. The esul s e ealed a signi ican posi i e ela ionship be ween supplie eliabili y and p ocu emen
ou comes ( = 0.87, p < 0.001), con i ming ha highe eliabili y leads o imp o ed p ocu emen success.
Simila ly, cos -e ec i eness showed a s ong co ela ion wi h supplie pe o mance ( = 0.82, p < 0.001),
indica ing ha supplie s wi h highe cos e iciency end o pe o m be e . Addi ionally, quali y compliance was
a key de e minan , wi h a eg ession coe icien o 0.75 (p < 0.001), a i ming ha supe io p oduc quali y
enhances p ocu emen e iciency. These indings con i m ha eg ession models e ec i ely e alua e supplie
pe o mance me ics and p o ide ac ionable insigh s o p ocu emen op imiza ion.
8.5 Role o Reg ession Analysis in P edic ing P ocu emen Risks and Minimizing Cos O e uns:
The second objec i e, analyzing he ole o eg ession analysis in p edic ing p ocu emen isks and
minimizing cos o e uns, was con i med using a combina ion o logis ic eg ession and chi-squa e es s. The
logis ic eg ession model demons a ed ha p ocu emen isks such as supplie insol ency, ma ke ola ili y,
and deli e y delays signi ican ly impac p ocu emen cos s, wi h a p edic i e accu acy o 86%. A chi-squa e es
compa ing expec ed and obse ed p ocu emen isks yielded a chi-squa e s a is ic o 3.56 (p = 0.46), indica ing
ha p ocu emen isks align closely wi h p edic ions, suppo ing he eliabili y o he isk assessmen models.
Fu he mo e, a pai ed - es compa ing p ocu emen cos s be o e and a e implemen ing isk mi iga ion
s a egies showed a s a is ically signi ican educ ion ( = 3.27, p = 0.002), con i ming ha p edic i e eg ession
models con ibu e o cos con ol and isk educ ion in p ocu emen .
8.6 Ac ionable Recommenda ions o In eg a ing Reg ession-Based Insigh s in o P ocu emen Decision-
Making:
The hi d objec i e, p oposing ac ionable ecommenda ions o in eg a ing eg ession-based insigh s
in o p ocu emen decision-making p ocesses, was alida ed by examining p ocu emen e iciency imp o emen s
o e ime. Reg ession models demons a ed ha supplie di e si y posi i ely in luenced p ocu emen success (
= 0.79, p < 0.001), emphasizing he impo ance o engaging a b oade ange o supplie s. Addi ionally,
communica ion e iciency showed a signi ican impac on p ocu emen ou comes ( = 0.76, p < 0.001),
highligh ing he necessi y o s ong supplie ela ionships. The ole o inancial s abili y in p ocu emen
eliabili y was also con i med ( = 0.83, p < 0.001), ein o cing he ecommenda ion ha inancially s able
supplie s should be p io i ized o ensu e p ocu emen success. These esul s a i m ha eg ession analysis
p o ides aluable insigh s o e ining p ocu emen decision-making s a egies.
8.7 O e all Co ela ion Coe icien and In e p e a ion:
The o e all co ela ion coe icien ac oss all p ocu emen pe o mance me ics was ound o be = 0.85
(p < 0.001), indica ing a s ong posi i e ela ionship be ween supplie pe o mance a iables and p ocu emen
ou comes. This esul con i ms ha eg ession analysis is a powe ul s a is ical ool o e alua ing, p edic ing,
and op imizing p ocu emen e iciency. The in eg a ion o eg ession-based insigh s enables p ocu emen eams
o make da a-d i en decisions, educe isks, and imp o e supplie selec ion, ul ima ely leading o enhanced
p ocu emen success.
9. Challenges and Bes P ac ices:
Challenges:
The applica ion o eg ession analysis in e alua ing supplie pe o mance and p ocu emen ou comes
p esen s a ious challenges ha impac i s e ec i eness. One o he p ima y obs acles is he quali y and
a ailabili y o da a. In many p ocu emen en i onmen s, da a is agmen ed, inconsis en , o incomple e, making
i di icul o cons uc eliable eg ession models. Addi ionally, p ocu emen eams o en lack he necessa y
s a is ical expe ise o in e p e eg ession ou pu s accu a ely, leading o misin o med decision-making. Ano he
challenge is he dynamic na u e o supply chains, whe e ex e nal ac o s such as economic shi s, geopoli ical
isks, and ma ke luc ua ions can al e supplie pe o mance. S anda d eg ession models may ail o cap u e
hese complexi ies, necessi a ing mo e ad anced p edic i e modeling echniques. Fu he mo e, o ganiza ional
esis ance o adop ing da a-d i en app oaches is a pe sis en ba ie . Many p ocu emen manage s s ill ely on
adi ional e alua ion me hods, dis ega ding he insigh s eg ession models o e . Implemen ing eg ession-
based decision-making also equi es in es men s in echnology, such as p ocu emen analy ics so wa e and da a
in eg a ion ools, which may no be eadily a ailable o all o ganiza ions. Las ly, while eg ession analysis can
e eal co ela ions, i does no always es ablish causali y, leading o po en ial misin e p e a ions ha could
nega i ely impac supplie selec ion and p ocu emen s a egies.
Bes P ac ices:
To o e come hese challenges, o ganiza ions should adop bes p ac ices ha enhance he e ec i eness
o eg ession analysis in p ocu emen decision-making. Fi s , es ablishing obus da a collec ion and
managemen amewo ks ensu es ha p ocu emen eams ha e access o accu a e and comp ehensi e da ase s
o analysis. This includes s anda dizing da a o ma s, in eg a ing supplie pe o mance acking sys ems, and
le e aging au oma ion o da a en y and alida ion. Second, capaci y building is c ucial o ganiza ions should