Ta ana, Madjid; Di Cap io, Debo a; Ramin Ros amkhani
A icle
A o al quali y managemen ac ion plan assessmen model
in supply chain managemen using he lean and agile
sco es
Jou nal o Inno a ion & Knowledge (JIK)
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Sugges ed Ci a ion: Ta ana, Madjid; Di Cap io, Debo a; Ramin Ros amkhani (2025) : A o al quali y
managemen ac ion plan assessmen model in supply chain managemen using he lean and agile
sco es, Jou nal o Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 10, Iss.
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A o al quali y managemen ac ion plan assessmen model in supply chain
managemen using he lean and agile sco es
Madjid Ta ana
a,b
, Debo a Di Cap io
c,*
, Ramin Ros amkhani
d
a
Business Sys ems and Analy ics Depa men , Dis inguished Chai o Business Analy ics, La Salle Uni e si y, Philadelphia, USA
b
Business In o ma ion Sys ems Depa men , Facul y o Business Adminis a ion and Economics, Uni e si y o Pade bo n, Pade bo n, Ge many
c
Depa men o Economics and Managemen , Uni e si y o T en o, T en o, I aly
d
School o Managemen , Uni e si i Sains Malaysia, Penang, Malaysia
ARTICLE INFO
JEL codes:
C02
D20
D80
Keywo ds:
To al quali y managemen
Lean and agile
Supply chain managemen
Ac ion plan
P ocess capabili y index
ABSTRACT
Supply chain managemen (SCM) and o al quali y managemen (TQM) ep esen wo pa allel app oaches o
imp o ing o ganiza ional pe o mance. P e ious s udies ha e analyzed he SCM ea u es impac ing o ganiza-
ional pe o mance independen ly o he design o TQM p ac ices. Simila ly, he ecen li e a u e on SCM
o e looks TQM when inco po a ing lean and agile elemen s in SCM p ac ices and s a egies. Sca e ed a emp s
ha e been made o e alua e lean and agile SCM p ac ices and TQM ac ion plans, bu no conc e e in eg a ed
app oach has been de eloped. In pa icula , no s udy has p esen ed a s uc u ed analysis o quan i y he in lu-
ence o he SCM componen s on achie ing p ede e mined TQM goals. We p opose a comp ehensi e, ou -phase,
in eg a ed p ocedu e wi h a o al sco e o quan i a i ely assess lean and agile SCM o ill his esea ch gap. This
comp ehensi e sco e selec s he mos sui able TQM ac ion plan o inc easing p oduc i i y and sus ainabili y.
The ou phases o he p oposed p ocedu e include an ini ial quali a i e analysis o de ining indica o s, sub-
indica o s, and cha ac e is ics o he lean and agile app oach (Phase 1), he o mula ion o a ma hema ical
model o compu ing he o al sco e o he whole SCM app oach (Phase 2), he selec ion o an ac ion plan o
achie e TQM goals (Phase 3), and he alida ion o he p oposed amewo k and he esul s ob ained (Phase 4).
We show he applicabili y o he p oposed e alua ion p ocedu e in a eal-li e case s udy and demons a e ha he
gene al o mula ion o he ma hema ical model allows o ex ensions o he p oposed me hod o o he e alua ion
con ex s.
In oduc ion
Lean and agile a e wo supply chain managemen (SCM) s a egies
ha ocus on minimizing cos and was e while being highly lexible o
adap quickly o he con inuous changes ha SCM sys ems unde go
(Sal endy, 2007). Lean and agili y can be ega ded as quali y-changing
ools ha suppo s a egic decisions o inc ease an o ganiza ion’s
compe i i e ad an ages and deal wi h dynamic cus ome p e e ences
(S ini asan e al., 2020;Oli ei a-Dias e al., 2022).
To al quali y managemen (TQM) can be ega ded as a pa allel
concep o lean SCM and agile SCM. I e e s o a cus ome -o ien ed
p ocess ha con inuously imp o es he managemen o business ope -
a ions a all le els by ac i ely in ol ing all employees (Boaden, 1997;
Talha, 2004;Kujala and Ull ank, 2004;Meh a and Rangana han, 2008).
In his espec , iden i ying ac o s a ec ing he achie emen o TQM
goals ela ed o p oduc i i y and sus ainabili y ep esen s a key issue o
manage s and esea che s. Despi e he impac o SCM decisions on TQM
ac ions being clea and gene ally ecognized, he possible implica ions
o SCM wo k lows on assessing TQM goals a e usually o e looked
(Kannan and Tan, 2005;Vanichchinchai and Igel, 2009;Kau e al.,
2019;Soa es e al., 2017).
Mos p e ious s udies ha e combined lean and agile elemen s in SCM
wi hou conside ing ela ed TQM goals. Mo eo e , e en hough a -
emp s ha e been made o e alua e lean and agile SCM p ac ices and
TQM ac ion plans, no conc e e in eg a ed app oach has been de eloped.
This is ue bo h o quali a i e and quan i a i e s udies. The li e a u e
e iew sec ion p o ides many examples in his sense. In pa icula , none
o he exis ing s udies has ackled he p oblem o explici ly iden i ying
he ela ionship be ween he ac o s cha ac e izing an e icien design o
lean and agile SCM and hose yielding success ul TQM p ac ices.
* Co esponding au ho a : Depa men o Economics and Managemen , Uni e si y o T en o, T en o, I aly.
E-mail add esses: [email p o ec ed] (M. Ta ana), [email p o ec ed] (D. Di Cap io), [email p o ec ed] (R. Ros amkhani).
Con en s lis s a ailable a ScienceDi ec
Jou nal o Inno a ion &Knowledge
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Jou nal o Inno a ion & Knowledge 10 (2025) 100633
2
Ano he issue o e looked in he li e a u e is he possibili y o assigning a
sco e o hese ac o s o allow o a quan i a i e –hence, mo e objec i e
–assessmen o he ac ion plan o implemen o TQM.
The p esen s udy is mo i a ed by he ollowing esea ch ques ion:
“How can lean and agili y con ibu e o o al quali y managemen (TQM) in
supply chain managemen ?”. This ques ion is add essed by conside ing
wo pa icula issues: (1) Can speci ic lean and agile ac o s adequa ely be
de ined o accoun o TQM p inciples? (2) Can he impac o lean and agile
SCM on achie ing speci ic TQM goals be measu ed sys ema ically and
sys ema ically?”
To ill he esea ch gap ep esen ed by hese ques ions, we ocus on a
sys ema ic analysis o he lean and agile SCM and show ha i can lead o
success ul TQM. We in oduce a wide ange o lean and agile SCM ac-
o s. These ac o s a e ca ego ized as indica o s, sub-indica o s, and
cha ac e is ics and a e linked o he main domains o TQM.
Iden i ying common ea u es be ween lean and agile ac o s and
TQM elemen s c ea es ideal condi ions o designing a comp ehensi e
e alua ion p ocedu e o measu e he impac o lean and agile SCM on
achie ing speci ic TQM goals. The p ima y objec i e o his p ocedu e is
o p o ide a ool ha assis s expe s and manage s in selec ing sui able
in e en ion s a egies.
The e alua ion p ocedu e p oposed in his s udy is based on a
quali a i e-quan i a i e app oach ha elies on he con inuous ull
coope a ion o esea che s and p ac i ione s. This e alua ion scheme is
designed o e lec wo main objec i es. The i s objec i e is o de ine
he o al sco es o lean and agile SCM app oaches o accoun o he links
be ween lean and agile indica o s and TQM p inciples. The second
objec i e is o use he o al sco es o selec he ac ions o implemen in an
o ganiza ion o achie e p ede e mined TQM goals.
The inno a i e aspec s o he p oposed p ocedu e a e ela ed o he
empi ical in es iga ion ha was conduc ed in a eal-li e o ganiza ion o
complemen he heo e ical amewo k. Indica o s, sub-indica o s, and
hei cha ac e is ics a e speci ically de ined o e alua e he lean and
agile SCM p ac ices conce ning he possibili y o achie ing p ea anged
TQM goals. The sys ema ic de ini ion o hese indica o s and sub-
indica o s was possible hanks o he collabo a ion o he TQM p ac i-
ione s who pa icipa ed in he empi ical in es iga ion. Well-de ined
and expe ience-based TQM goals a e iden i ied, and hei pi o al ole
in assessing he p ac ical alidi y o he p oposed p ocedu e is demon-
s a ed. A ma hema ical model is in oduced o add objec i i y o he
da a p o ided by he p ac i ione s h ough subjec i e e alua ion. The
ma hema ical o mulas can be coded o an easy and au oma ed
compu a ion o all he necessa y sco es. Excel was used in he empi ical
s udy due o i s simplici y and common use, bu many o he so wa e can
be used o p og am he sco e sp eadshee . The ac i e in ol emen o
TQM p ac i ione s in all he phases o he p oposed p ocedu e is he key
o an accu a e global assessmen ha encompasses assigning o al sco es
o lean and agile SCM, choosing he TQM ac ion plan o implemen , and
alida ing he o ganiza ion’s esul s in e ms o p oduc i i y and
sus ainabili y.
The es o he pape p oceeds as ollows. Sec ion 2 p o ides a
li e a u e e iew o he ele an wo k p oduced o e he las wo de-
cades. Sec ion 3 illus a es he esea ch amewo k and ou lines he
p oposed ou -phase e alua ion p ocedu e. Sec ion 4 explains he
me hod ollowed in selec ing he TQM expe s whose e alua ions a e
essen ial o implemen he p oposed p ocedu e. Sec ion 5 desc ibes he
i s phase o he p oposed p ocedu e, he quali a i e phase. Sec ion 6
desc ibes he second phase, ha is, he quan i a i e phase. The ma he-
ma ical model de ined o compu e he o al sco e o lean and agile SCM
is explained in his sec ion. Sec ion 7 desc ibes he hi d phase, he
guidelines o he TQM p ac i ione s o ecommend he igh ac ion plan
o achie ing TQM goals. Sec ion 8 desc ibes he ou h phase, he e-
sul s assessmen phase. Sec ion 9 discusses he main indings, hei im-
plica ions, and possible ex ensions. Sec ion 10 concludes.
Li e a u e e iew
This sec ion ocuses on he s udies published o e he las wo de-
cades on SCM and TQM p ac ices and he e ec s ha possible syne gis ic
ela ionships be ween hem may ha e on an o ganiza ion’s
pe o mance.
P e ious s udies on he impac o SCM and TQM on o ganiza ional
pe o mance
Many s udies ha e sugges ed ha TQM and SCM s eng hen o ga-
niza ional compe i i eness and imp o e cus ome sa is ac ion. The
impac o he main a eas o SCM on TQM has been in es iga ed ela i e
o o he ini ia i es, such as en e p ise esou ce planning and elec onic
comme ce. This impac endo sed a comple e in eg a ion o SCM ac oss
o ganiza ional alue chains, wi h a c oss-bounda y ocus on ansac ion
cos educ ion (Gunaseka an and McGaughey, 2003).
TQM and SCM ha e e ol ed simila ly o each he same goal:
cus ome sa is ac ion. Howe e , TQM and SCM ha e di e en s a ing
poin s and p ima y goals, making an in eg a ed implemen a ion com-
plex. Acco ding o se e al au ho s, TQM should aim o enhance in e nal
pa ne ships (employee), while SCM should ocus on ex e nal pa ne -
ships (business pa ne s). Bo h pa ne ships mus be enhanced o
s eng hen u he he “ o al”in TQM and he “en i e supply chain”in
SCM (Vanichchinchai and Igel, 2009). O he esea che s ha e ollowed a
di e en in e p e a ion: TQM should cen e on con inuous quali y
imp o emen and pa icipa ion, while SCM emphasizes supplie e-
la ionships, managemen , and on- ime deli e y o p oduc s and se ices
(Talib e al., 2011a,b).
The ela ionships be ween TQM and SCM ha e been analyzed using
business models like Kanji’s Business Excellence model. This model uses
TQM p inciples o help companies achie e business excellence and
compensa e o he inadequacies o exis ing SCM models by c ea ing
new ones (Kanji &Wong, 1999).
The cos de i ing om wo king wi hou TQM concep s has also been
conside ed (Liapis e al., 2013), while spo adic a emp s we e made o
assess SCM and TQM p ac ices conce ning i ms’supply pe o mance
(Vanichchinchai, 2014). Bo h issues ha e been ackled mos ly in
empi ical s udies, wi h he assessmen o SCM componen s sepa a ed
om TQM.
The p oblem o in eg a ing SCM p ac ices wi h TQM ones has
a ac ed he a en ion o esea che s and p ac i ione s mo e and mo e
o e he las decade.
Di e en combina ions o SCM-TQM p ac ices we e p oposed o an
en e p ise o ope a e e icien ly, and case s udies we e conduc ed o
suppo hei p ac ical implemen a ion (Sha ma and Modgil, 2015). The
esul s ob ained om he p ac ical deploymen s o ai ly inno a i e SCM
app oaches we e used o in e he ac o s cha ac e izing a success ul
TQM (Jung and Chung (2016). Syne gis ic ela ionships be ween he
SCM and TQM pa adigms p o ed mo e help ul han pu e SCM ini ia i es
in enhancing o e all business pe o mance (Sidhu e al., 2019). Com-
mon p ac ices in TQM and SCM we e iden i ied based on key ac o s
iden i ied empi ically (Kau e al., 2019). Some SCM models inco po-
a ed ope a ion managemen echniques, allowing us o conclude he
ela i e in luence o TQM and SCM and he impac o TQM and agile
p oduc ion and g een SCM p ac ices on o ganiza ional pe o mance
(G een e al., 2019). Assessmen me hodologies we e p oposed o
quali y- ela ed pe o mance measu es in ol ing supply chain isk
(Ganguly, 2020).
SCM and TQM p ac ices can impac each o he and ope a ional
pe o mance di e en ly and a a ious le els. Fo ins ance, by es ing
al e na e models, Sha ma and Modgil (2020) concluded ha SCM and
TQM p ac ices in luence ope a ional pe o mance, bu TQM also
di ec ly impac s SCM componen s. Thus, TQM p ac ices in luence he
o e all ope a ional pe o mance. Kau e al. (2020a,b,c) assessed
o ganiza ional pe o mances based on he implemen a ion o SCM-TQM
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
3
combined ini ia i es and o SCM and syne gis ic SCM app oaches. The
co ela ion be ween dependen and independen ac o s and compe i-
i e dimensions o SCM and SCM-TQM app oaches was also s udied.
Kau e al. (2021) iden i ied he ba ie s impeding a success ul imple-
men a ion o SCM-TQM p ac ices and anked such ba ie s based on a
VIKOR app oach. Shaikh e al. (2023) a gued ha TQM ini ia i es a e
di ec ly co ela ed o imp o emen s in SCM while bo h posi i ely a ec
an o ganiza ion. A sys ema ic li e a u e e iew o he endy opics
ela ed o TQM and SCM elemen s has been p esen ed by Mahdikhani
(2023), among o he s.
Finally, he mos ecen s udies ela ed o TQM wi nessed much mo e
he e ogeneous and in e disciplina y de elopmen s. Fo ins ance, Shan
e al. (2023) p oposed a mul i- ac o concep ual model o analyze he
ela ionship be ween supply chain pa ne ships and inno a ion pe o -
mance. Following a knowledge-managemen app oach, supply chain
pa ne ships and inno a ion pe o mance a e desc ibed by ac o s and
measu emen me ics ypical o TQM p ac ices. Liu e al. (2024) s udied
he impac o ma ke accessibili y on inno a ion pe o mance, consid-
e ing supply chain esilience as an in luence pa h. Ma ke accessibili y is
shown o in luence signi ican ly inno a ion pe o mance, in con as o
i s educed impac on inno a ion quali y. Mahajan e al. (2023) in es-
iga ed he ela ionship be ween TQM and in en o y managemen and
concluded ha in en o y managemen highly co ela es wi h he in-
en o y u no e a io. Howe e , unlike TQM, i is un ela ed o i m
pe o mance. Tou ighi e al. (2024) ocused on how pa icipa i e lead-
e ship and cul u al ac o s in luence employees’speaking-up beha io
and knowledge-sha ing wi hin supplie de elopmen . P ac ical impli-
ca ions in ol e os e ing a highly inclusi e and collabo a i e wo k
en i onmen aligning wi h TQM goals.
P e ious s udies on he impac o lean and agile SCM on quali y concep s
Table 1 ou lines he e o s made by he exis ing li e a u e o s udy
he ole played by lean and agile SCM in de eloping quali y concep s.
These ables p esen s udies acili a ing he connec ion be ween lean
and agile SCM and TQM. Howe e , hese s udies ha e been inadequa e
in suppo ing a comp ehensi e e alua ion o he decisions o achie e
TQM goals.
In summa y, based on he li e a u e e iew, i can be concluded ha
he p e ious s udies did no o e a comp ehensi e app oach o he
in e ac ion be ween SCM and TQM. Thei scope is aluable bu oo
limi ed o allow o a success ul analysis o TQM, s a ing wi h quali-
a i e elemen s o quan i a i e da a collec ed wi hin lean and agile SCM
sys ems.
Me hodology
Compa ed o he p e ious ones, he inno a i e idea o his s udy is o
ocus on making a compelling connec ion be ween he componen s o
lean and agile SCM and he main domains o TQM. The cu en pape
in oduces an e alua ion p ocedu e whe e a quan i a i e assessmen o
an o ganiza ion’s lean and agile SCM sys em is pe o med and used o
assis TQM p ac i ione s in selec ing he igh cou se o ac ion o
achie ing p ea anged and well-de ined TQM goals.
The me hodology ollows he ypical mul ic i e ia decision-making
app oach whe e esea che s’knowledge and p ac i ione s’expe ience
a e combined o d aw and weigh ele an ac o s. The gene al esea ch
amewo k is based on coo dina ion and in eg a ion. We coo dina e he
e o s o all he ac o s in ol ed in he s udy: academic esea che s and
selec ed TQM p ac i ione s. We in eg a e di e en and o en dis an
pe spec i es o an accu a e de ini ion and comp ehensi e assessmen o
he ac o s in e linking SCM and TQM wi hin lean and agile
en i onmen s. Fig. 1 ep esen s he p oposed esea ch amewo k. The
a ows indica e he links ep esen ing b oad (in e nal wo-way a ows)
and speci ic (ex e nal a ow) iewpoin s.
We e e o Ros amkhani and Ramayah (2023) o he componen
s uc u e o SCM. Rega ding he TQM domains, we iden i y hem wi h
he se en essen ial p inciples o TQM in oduced by Bes e ield e al.
(2012) and Oakland e al. (2020): quali y ools, p oduc design,
cus ome ocus, supplie quali y, p ocess managemen , employee
commi men , and con inuous imp o emen . We ocus on he i s i e o
hese domains o TQM, ha is, hose allowing o co esponding con-
cep s in SCM.
The ollowing sec ions will in oduce he speci ic lean and agile in-
dica o s and he TQM goals.
Table 1
P e ious s udies on lean and agile SCM app oaches o quali y concep s.
Au ho (s) Focus
Al es e al. (2012) Cause-e ec ela ion be ween lean p oduc ion adop ion
and p omo ion o hinke s.
Cos an ino e al. (2012) Con igu a ion p oblem o agile SCM.
Chen e al. (2013) E iciency and e ec i eness o lean SCM.
Ju ado and Funen ez
(2014)
Lean managemen , SCM, and sus ainabili y.
To o ella e al. (2017) All aspec s o lean SCM.
Beni ez e al. (2017) Lean, g een, and esilien SCM.
Zhu e al. (2018) In eg a ion o p oduc dele ion, sus ainabili y, and lean
SCM.
Lye e al. (2019) Con ibu ion o lea ning o ien a ion and supply chain
pa ne ship esou ces.
Roshan e al. (2019) Agile supply chain and pha maceu ical supply chain in
c isis.
Gio anni and Ca iola
(2020)
Technologies on lean p ac ices and g een supply chains.
Na h and Ag awal (2020) In es iga e whe he supply chain agili y and lean
managemen p ac ices a e an eceden s o supply chain
social sus ainabili y.
Shashi e al. (2020) Dynamic business en i onmen and agile SCM.
Jana (2021) Analyzing di e en supply chain s uc u es in lean
appa el manu ac u ing.
Sen hil and Mu hukannan
(2021)
Lean s uc u e p ojec o lean SCM.
Omoush e al. (2022) In ellec ual capi al, SCA, collabo a i e knowledge, and
sus ainabili y.
Medina e al. (2022) The e ec s o abso p i e capabili y and SCA.
Kazancoglu e al. (2022) Conside ing lexibili y and agili y in SCM.
Basu e al. (2022) The esilience and agili y o au omo i e spa e pa s
SCM.
Dubey e al. (2022) The necessi y o ha ing agili y in SCM.
Sheka ian e al. (2022) The e ec o lexibili y and agili y on imp o ing SC
esponsi eness.
Abdelilah e al. (2023) In es iga e he an eceden s o supply chain agili y and
i s impac on a i m’s ope a ional pe o mance.
Can ele e al. (2023) In es iga e he po en ial combina ions o i m and
supply chain sus ainabili y p ac ices and supply chain
agili y o high i m pe o mance.
Kuma Singh and Modgil
(2023)
Iden i ying e ec i e pe o mance p ac ices in
au omo i e lean supply chains.
Sangwa e al. (2023) A lean pe o mance measu emen sys em o an
au omo i e supply chain.
Vanichchinchai, (2023). The di e ences ac oss selec ed con ex ual ac o s on he
Toyo a Way, agile manu ac u ing, and hei sub-
elemen s.
Khawka e al. (2024) Ca ego iza ion o c i ical success ac o s o
implemen ing lean SCM.
Mish a e al. (2024) Unco e he c i ical enable s o an agile supply chain in
he manu ac u ing sec o amids dis up ions.
Nikneshan e al. (2024) The e ec o lean and agile inno a ion on lean and agile
supply chains.
Panig ahi e al. (2024) Lean SCM c i ical ac o assessmen o con inuous
imp o emen in manu ac u ing.
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
4
P oposed e alua ion p ocedu e
Wi hin his amewo k, we p opose a comp ehensi e and in eg a ed
ou -phase p ocedu e o assessing he impac o lean and agile SCM on
he domains o TQM and he consequen achie emen o speci ic TQM
goals. The phases o he p oposed e alua ion p ocedu e a e ou lined
below. A de ailed desc ip ion o each phase will be p o ided in he
ollowing sec ions.
Phase 1 (Quali a i e phase): This phase consis s o de ining quali-
a i e concep s, including indica o s, sub-indica o s, and ele an
cha ac e is ics, ha can link he lean and agili y o SCM o TQM goals.
The TQM goals a e also iden i ied in his phase.
In summa y: Resea che s and p ac i ione s de ine indica o s, sub-
indica o s, and ele an cha ac e is ics.
Phase 2 (Quan i a i e phase): This phase in oduces he ma he-
ma ical model. E alua ion ma ices and weigh ec o s a e de ined o a
quan i a i e assessmen o he concep s o Phase 1 and o assign o al
sco es o bo h he lean and he agile app oaches.
In his phase, he esea che s code he ma hema ical o mula ion
using so wa e known o he p ac i ione s. We ha e p epa ed an Excel
sp eadshee o compu e pa ial and o al sco es since Excel is a wo ld-
wide known and ela i ely easy- o-use so wa e. A he same ime, he
selec ed TQM p ac i ione s analyze all he concep s o Phase 1 and
p o ide he necessa y da a o un he ma hema ical model.
In summa y: (a) Resea che s de ine e alua ion ma ices, weigh
ec o s, and all he o mulas o assign a sco e o each indica o and sub-
indica o and a o al sco e o bo h lean SCM and agile SCM sepa a ely;
(b) Resea che s code all he o mulas using an Excel sp eadshee (o
ano he so wa e known o he p ac i ione s); (c) Senio p ac i ione s
assign impo ance weigh s o indica o s, sub-indica o s, and cha ac e -
is ics; (d) Gene al p ac i ione s p o ide a quan i a i e e alua ion o he
cha ac e is ics; and (e) All p ac i ione s use he Excel sp eadshee o
compu e he pa ial and o al sco es o lean and agile SCM.
Phase 3 (Ac ion plan ecommenda ion): De e mining he ac ion
plan o ecommend o he a ge o ganiza ion and implemen ing he
ecommended ac ions.
In summa y: P ac i ione s choose he ac ion plan based on a speci ic
classi ica ion schema and o e see he implemen a ion o he co e-
sponding ac ions, ensu ing ha he selec ed app oach o TQM is
pu sued.
Phase 4 (Assessmen o esul s): Valida ing he me hodology and
e i ying whe he he e has been an ac ual imp o emen in e ms o
p oduc i i y and sus ainabili y using P ocess Capabili y Indices (PCI).
In summa y: Independen p ac i ione s (ex e nal expe s) a e called
o ac as e e ees and e alua e he me hodology’s alidi y based on he
conc e e esul s ob ained o he a ge o ganiza ion.
Fig. 2 p esen s a schema ic ep esen a ion o he ou phases abo e,
desc ibing he ac o s ( esea che s and p ac i ione s) in ol ed in each
Fig. 1. Gene al esea ch amewo k.
Fig. 2. The p oposed e alua ion p ocedu e.
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
5
phase.
Selec ing TQM expe s
TQM p ac i ione s play a c ucial ole in all he phases ou lined
abo e. They a e called o pe o m all he quali a i e and quan i a i e
e alua ions ha will ake place h ough he di e en phases. The as-
sessmen s p o ided by senio and gene al p ac i ione s allow da a
collec ion o he ma hema ical model. The p ac i ione s analyze he
da a h ough an Excel sp eadshee . Finally, a second g oup o p ac i-
ione s, i.e., ex e nal expe s, ac as e e ees o app aise he alidi y and
eliabili y o he esul s ob ained. Consequen ly, selec ing TQM p ac i-
ione s is he i s key issue o conside .
Fig. 3 ou lines he di e en le els o TQM knowledge conside ed o
selec ing he expe s. The ca ego ies o expe s in ol ed in ou e alua-
ion p ocedu e, hei expe ise, and hei ole a e summa ized in Ap-
pendix A.
Selec ing he TQM p ac i ione s (Phases 1 o 3)
To e alua e he empi ical alidi y o he p oposed amewo k and
e alua ion p ocedu e, we con ac ed 33 o ganiza ions ope a ing in he
Middle Eas . The o ganiza ions we e asked o he a ailabili y o hei
TQM expe s. One o ganiza ion was chosen as he a ge o ganiza ion o
check he applicabili y and alidi y o he p oposed ou -phase e alua-
ion p ocedu e.
Two ypes o p ac i ione s had o be selec ed: (1) gene al p ac i ione s
o e alua e he lean and agile indica o s, sub-indica o s, and cha ac-
e is ics conce ning he TQM domains; (2) senio p ac i ione s o weigh
he lean and agile indica o s, sub-indica o s, and cha ac e is ics.
Gene al p ac i ione s
Fo he gene al p ac i ione s, we p oceeded as ollows. Fi s , we
ega ded he g oup o 33 o ganiza ions ha ag eed o pa icipa e in ou
s udy as he esea ch popula ion and de e mined he sample size o
gua an ee accu acy when ga he ing da a.
Fo popula ions ha a e no oo la ge, a sample can be selec ed using
a a ian o Coch an’s o mula (Nanjundeswa aswamy and Di aka ,
2021):
n=Nz2pq
Nd2+z2pq −d2(1)
whe e:
nis he sample size
Nis he communi y size
dis he ole able e o (be ween 0.01 and 0.1)
zis he s anda d de ia ion in he a e age a iabili y
pis he app oxima e p e alence a e o which he su ey is
conduc ed
qequals 1 −p
This o mula is ob ained o small popula ions by combining he
s anda d Coch an’s o mula n0=z2pq
d2(sample size o a la ge popula ion
p opo ion) wi h he adjus men o mula n=n0/[1+n0−1
N].
Thus, we calcula ed he popula ion sample size using Eq. (1) and he
ollowing alues o he pa ame e s:
N=33,d=0.1,z=1.96,p=0.5,q=0.5 (2)
Ob aining he sample size:
n=25 (3)
Once he sample size was known, we had o de ine a ule o choose
25 o ganiza ions ou o he 33 a ailable. The popula ion o 33 o gani-
za ions was ca ego ized acco ding o he i e main domains o TQM
conside ed in his s udy. Table 2 ou lines hese i e domains.
Each o he 33 o ganiza ions was associa ed wi h one o mo e do-
mains. Hence, 25 o ganiza ions we e selec ed so ha i was possible o
di ide hem in o i e g oups o i e uni s each. Finally, we in i ed one
ep esen a i e om each o he 25 o ganiza ions and pu he ep esen-
a i e in he co esponding g oup.
The in i a ions o expe s we e sen based on he in o ma ion p o-
ided by he expe s hemsel es ega ding hei pe sonal and o gani-
za ional expe iences h ough a ques ionnai e. This ques ionnai e –
included in Appendix B –assessed he possible candida es based on he
ollowing indica o s: educa ional le el, manage ial posi ion, wo k
Fig. 3. Knowledge le els o TQM expe s.
Table 2
The main domains o TQM conside ed in his s udy.
Main Domains o TQM conside ed in his s udy
T
1
Quali y Tools
T
2
P oduc Design
T
3
Cus ome Focus
T
4
Supplie Quali y
T
5
P ocess Managemen
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
6
expe ience (yea ), and amilia i y wi h lean and agile SCM. The human
esou ces managemen depa men s o he 25 selec ed o ganiza ions
e i ied he in o ma ion collec ed h ough he ques ionnai e.
Senio p ac i ione s
Fo he senio p ac i ione s, we p oceeded as ollows. Fo each g oup
o gene al p ac i ione s, one senio p ac i ione was in i ed om one o
he i e o ganiza ions o he gene al p ac i ione s in he g oup. In his
way, a g oup o i e senio p ac i ione s was c ea ed. The in o ma ion
collec ed wi h he ques ionnai e was used again o guide he choice o
he senio expe s.
Selec ing he TQM ex e nal expe s (Phase 4)
The esea ch alida ion was ca ied ou based on independen ex-
pe ’s opinions. This is in line wi h many esea che s’pe spec i es.
Expe judgmen s a e one o he bes ools o conduc ing con en ali-
da ion, gi en ha he expe s’compe ence has been co ec ly assessed
based on expe ience, sui able educa ion, and le el o opic amilia i y
(Pe ez and Ma inez, 2008;Fe n´
andez-G´
omez e al., 2020).
Fo his s udy, we asked he a ge o ganiza ion o con ac TQM
ex e nal expe s hey us ed and had al eady con ac ed o p ojec
e alua ion. Howe e , we p o ided he o ganiza ion wi h a ques ion-
nai e o he expe s o app ise he p oposed me hodology and i s
applicabili y. The ques ionnai e is included in Appendix C.
Phase 1: quali a i e phase
Lean and agile indica o s o link SCM o he main domains o TQM
Rega ding he leading indica o s, we build on he esea ch o Ros-
amkhani and Ka basian (2020) and Ros amkhani and Ramayah (2023),
who in oduced wo di e en ca ego ies o indica o s o leading com-
me cial, indus ial, and mili a y o ganiza ions o implemen and exploi
lean and agile app oaches in SCM success ully.
Lean and agile SCM ha e he same componen s. Thus, in he quali-
a i e phase, he di e ences be ween he lean and agile con ex s a e
e lec ed by in oducing inno a i e indica o s, sub-indica o s, and hei
cha ac e is ics. Table 3 shows he leading indica o s p oposed in his
s udy.
As shown in Table 3, he leading lean and agile indica o s a e de ined
as being in one- o-one co espondence wi h he componen s o lean and
agile SCM, espec i ely. A he same ime, each indica o is associa ed
wi h one o mo e o he main domains o TQM. As men ioned abo e, his
s udy ocuses on he i e p ima y domains o TQM, as ou lined in
Table 2.
Fig. 4 p esen s he ela ionships be ween he p oposed lean and agile
indica o s and he conside ed TQM domains. These ables summa ize
which lean/agile indica o co e s which TQM domain and, ice e sa,
which TQM domain is e lec ed by which indica o .
Finally, Table 4 lis s he goals o TQM conside ed in his s udy. These
goals ha e been de ined wi h he help o he selec ed TQM p ac i ione s
based on hei expe ience and da a om he o ganiza ions in ol ed in
he s udy (see Appendix D).
In oducing lean and agile sub-indica o s and he co esponding
cha ac e is ics
One o he main con ibu ions o he cu en pape is o show ha
i e o he main domains o TQM can be co e ed by co ec ly de ining
no only leading indica o s bu also sub-indica o s and hei cha ac e -
is ics in lean and agile SCM. In p inciple, his ype o ca ego iza ion can
be de eloped based on a ca e ul and sys ema ic li e a u e e iew and he
esea che s’knowledge. In ou case, we used a li e a u e e iew o
ex ac he leading indica o s. We combined ou knowledge and expe-
ience wi h hose o he TQM p ac i ione s o de e mine he declina ion
o sub-indica o s and cha ac e is ics.
Tables 5–7show he sub-indica o s and cha ac e is ics p oposed o
he lean indica o s. Tables 8–10 show he sub-indica o s and cha ac-
e is ics p oposed o he agile indica o s.
Phase 2: quan i a i e phase
This phase en ails he esea che s’in ol emen in designing a
ma hema ical model ha allows o a cohe en e alua ion o an SCM
sys em and he e o o he gene al and senio p ac i ione s o acqui e
all he da a (quan i a i e assessmen ) necessa y o apply he ma he-
ma ical o mulas. Mo e p ecisely, his phase comp ises he ollowing
s eps:
1) Resea che s de ine a sui able ma hema ical model
2) Resea che s code he ma hema ical o mula using so wa e known o
he p ac i ione s.
3) P ac i ione s p o ide he da a o he model: (a) gene al p ac i ione s
e alua e he cha ac e is ics, and (b) senio p ac i ione s assign
weigh s o all indica o s, sub-indica o s, and cha ac e is ics.
4) P ac i ione s use he coded p og am o de e mine all pa ial and o al
sco es.
P oposed ma hema ical model
This sec ion p o ides a o mal model o assign a o al sco e o an SCM
app oach based on a de e mined se o indica o s, sub-indica o s, and
co esponding cha ac e is ics.
The key idea behind his o mal model is o allow o mul iple ini ial
e alua ions o he basic elemen s o he SCM app oach, ha is, he
cha ac e is ics. Va ious e alua ions o single cha ac e is ics a e possible
conside ing di e en g oups o expe s. In ou case, i e g oups o gen-
e al p ac i ione s e alua ed each cha ac e is ic.
The o he ini ial da a equi ed o he model a e he impo ance
weigh s o all he indica o s, sub-indica o s, and cha ac e is ics. A g oup
o expe s usually assigns hese weigh s. In ou case, a g oup o senio
p ac i ione s p o ided he weigh s.
I dese es o be no ed ha his is a gene al model and can also be
used in o he e alua ion con ex s. We s a wi h he no a ions and some
Table 3
Lean and agile indica o s s. SCM componen s.
Lean SCM Agile SCM SCM
Componen s
Indica o P oposed Main Lean
Indica o s
Indica o P oposed Main
Lean
Indica o s
I
1
Cus ome
sa is ac ion
I
1
Rapid esponse Cus ome s
I
2
P edic ing all
p ocesses
I
2
Consump ion
es ima ion
Fo ecas ing
I
3
Flexible p oduc
design
I
3
Modula p oduc
design
Designing
I
4
C ea ing eliable
p ocesses
I
4
C ea ing lexible
p ocesses
P ocessing
I
5
C ea ing equi ed
p ocesses
I
5
C ea ing all
alued p ocesses
In en o y
I
6
E ec i eness o he
supplie s
I
6
Using in o ma ion
echnology
Pu chasing
I
7
Rein o cemen o
he supplie s
I
7
In ol ing
supplie s in
de elopmen
Supplie s
I
8
Co ec placemen
o he p oduc s
I
8
Keeping he wo k
en i onmen
clean
Loca ion
I
9
On- ime and
eliable deli e y o
p oduc
I
9
Equipping a e -
sales se ice
cen e s
Logis ics
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
7
basic de ini ions.
HThe o al numbe o indica o s de ined o he SCM app oach
IiThe i h indica o ; i=1,...,H
JiThe o al numbe o sub-indica o s o he i h indica o Ii
Iij is he j h sub-indica o o Ii;i=1, ..., H;j=1,...,Ji
Kij The o al numbe o cha ac e is ics o he j h sub-indica o Iij o he i h
indica o Ii
Iijk The k h cha ac e is ic o Iij;i=1,...,H;j=1,...,Ji;k=1,...,Kij
F he numbe o g oups in which he expe s e alua ing he cha ac e is ics
(gene al p ac i ione s) a e di ided.
s (Ii)The sco e o Iiassigned by he h g oup o expe s; i=1,...,H; =1,...,F
s (Iij)The sco e o Iij assigned by he h g oup o expe s; i=1,...,H;j=1,...,Ji;
=1,..., F
s (Iijk)The sco e o Iijk assigned by he h g oup o expe s; i=1,...,H;j=1,...,Ji;k
=1,..., Kij; =1,...,F
s (Ii)The sco e ec o associa ed wi h Ii:
o all i=1,..., H,s (Ii) = ( s1(Ii)s2(Ii)... sF(Ii) )
s (Iij)The sco e ec o associa ed wi h Iij:
o all i=1,..., Hand j=1, ..., Ji,s (Iij)=(s1(Iij)s2(Iij)... sF(Iij))
s (Iijk)The sco e ec o associa ed wi h Iijk:
o all i=1,..., H,j=1, ..., Jiand k=1,..., Kij,s (Iijk)=
(s1(Iijk)s2(Iijk)... sF(Iijk))
s(Ii)The o al (a e age) sco e o Ii;i=1, ..., H
(con inued on nex column)
(con inued)
s(Iij)The o al (a e age) sco e o Iij;i=1, ..., H;j=1,...,Ji
s(Iijk)The o al (a e age) sco e o Iijk;i=1, ..., H;j=1, ...,Ji;k=1,..., Kij
w(Ii)The weigh o Ii;i=1,...,H
w(Iij)The weigh o Iij;i=1, ..., H;j=1, ..., Ji
w(Iijk)The weigh o Iijk;i=1, ..., H;j=1, ...,Ji;k=1,..., Kij
TS The o al (a e age) sco e o he SCM app oach based on all he indica o s
conside ed.
The sum o he weigh s o indica o s (Ii), sub-indica o s (Iij), and
cha ac e is ics (Iijk) mus be as ollows:
∑
H
i=1
w(Ii) = 1 (4)
∑
H
i=1∑
Ji
j=1
w(Iij)=1 (5)
∑
H
i=1∑
Ji
j=1∑
Kij
k=1
w(Iijk)=1 (6)
As men ioned abo e, we assume ha he mul iple ini ial sco es o he
single cha ac e is ics and all he weigh s a e known. Thus, he da a o
he ma hema ical model a e as ollows:
•s (Iijk)=(s1(Iijk)s2(Iijk)... sF(Iijk)),i=1,...,H,j=1,...,Ji,k=
1,..., Kij
•w(Ii),i=1,...,H
•w(Iij),i=1,...,H,j=1,...,Ji
•w(Iijk),i=1,..., H,j=1, ..., Ji,k=1, ..., Kij
Fig. 4. The p oposed lean and agile indica o s s he main domains o TQM.
Table 4
The goals o TQM conside ed in his s udy.
TQM goals conside ed in his s udy
G
1
On- ime deli e y o p oduc s and se ices
G
2
Accu a e deli e y o p oduc s and se ices
G
3
Imp o ing cus ome sa is ac ion con inuously
G
4
C ea ing high mo i a ion in he wo k en i onmen
G
5
Inno a ion in he p oduc o se ice c ea ion p ocess
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
8
Fo all i=1,...,H,j=1, ..., Jiand k=1,...,Kij, we compu e he o al
sco e o Iijk:
s(Iijk)=1
F∑
F
=1
s (Iijk)(7)
Then, he sco es o sub-indica o s a e ob ained om hose o he cha -
ac e is ics. Fo all i=1,...,Hand j=1,...,Ji, we compu e he sco e ec o
and he o al sco e o Iij as ollows:
s (Iij)=(s (Iij1)s (Iij2)... s (IijK))×⎛
⎜
⎜
⎝
w(Iij1)
w(Iij2)
...
w(IijK)
⎞
⎟
⎟
⎠
=⎛
⎜
⎜
⎝
s1(Iij1)s1(Iij2)... s1(IijK)
s2(Iij1)s2(Iij2)... s2(IijK)
... ... ... ...
sF(Iij1)sF(Iij2)... sF(IijK)
⎞
⎟
⎟
⎠
×⎛
⎜
⎜
⎝
w(Iij1)
w(Iij2)
...
w(IijK)
⎞
⎟
⎟
⎠
(8)
s(Iij)=1
F∑
F
=1
s (Iij)(9)
Simila ly, he sco es o he indica o s a e ob ained om hose o he
sub-indica o s. Fo all i=1,...,H, we compu e he sco e ec o and he
o al sco e o Iias ollows:
s (Ii) = ( s (Ii1)s (Ii2)... s (IiJ) ) × ⎛
⎜
⎜
⎝
w(Ii1)
w(Ii2)
...
w(IiJ)
⎞
⎟
⎟
⎠
=⎛
⎜
⎜
⎝
s1(Ii1)s1(Ii2)... s1(IiJ)
s2(Ii1)s2(Ii2)... s2(IiJ)
... ... ... ...
sF(Ii1)sF(Ii2)... sF(IiJ)
⎞
⎟
⎟
⎠
×⎛
⎜
⎜
⎝
w(Ii1)
w(Ii2)
...
w(IiJ)
⎞
⎟
⎟
⎠
(10)
s(Ii) = 1
F∑
F
=1
s (Ii)(11)
Finally, ollowing he same idea, a sco e ec o can be de ined
conside ing all he indica o s a he same ime. Tha is, a sco e ec o can
be de ined o he whole SCM app oach as ollows:
Table 5
Sub-indica o s and cha ac e is ics o I
1
, I
2
, and I
3
in lean SCM.
Main
Indica o s
Sub-indica o s Cha ac e is ics
I
1
Cus ome
Sa is ac ion
I
11
Facili a ed
Communica ion
I
111
(C ea ing Fla O ganiza ional
S uc u e)
I
112
(Flow o Fluen and F ee
In o ma ion)
I
12
Cus ome
Complain s
I
121
(Clea De ini ions o Handling)
I
122
(Encou aging Employees o
Handle Complain s Rapidly)
I
13
Responsi eness
I
131
(O ganiza ional Rapid
Responsi eness o Cus ome )
I
132
(Rele an Employees
Communica ion wi h Cus ome
Di ec ly)
I
2
P edic ing all
P ocesses
I
21
Resou ces
Managemen
I
211
(Resou ces Es ima ion in
O ganiza ion Accu a ely)
I
212
(Iden i ica ion in In e nal and
Ex e nal Resou ces Managemen )
I
22
P ocesses
Managemen
I
221
(P ocess Sys em Applica ion in all
Aspec s wi hin he O ganiza ion)
I
222
(O ganiza ion P ocesses Re-
enginee ing)
I
223
(P ocess-O ien a ion View by all
Employees)
I
23
Ou sou cing
Managemen
I
231
(Unde s anding Supplie s’Role in
SCM)
I
232
(Supplie T aining E ec i ely)
I
233
(Supplie s Pa icipa ion P ope ly)
I
24
To al Quali y
Managemen
I
241
(Using Ad anced Techniques by
Rele an Employees)
I
242
(P e en i e Ac ions Be o e
Co ec i e Ac ions)
I
3
Flexible P oduc
Design
I
31
Quali ied
Employees
I
311
(Employing he Flexible
Employees)
I
312
(Employing he C oss-Func ional
Employees)
I
313
(Implemen ing he Requi ed
T aining)
I
32
P oduc Change
Powe
I
321
(C ea ing he Changeable Sys em)
I
322
(Empowe men o Requi ed Skills)
I
323
(E ec i e Encou agemen o New
Designs)
I
33
Con inuous
Imp o emen
I
331
(Inno a ion o he O ganiza ional
Employees)
I
332
(C ea i i y o he O ganiza ional
Employees)
Table 6
Sub-indica o s and cha ac e is ics o I
4
, I
5
, and I
6
in lean SCM.
Main
Indica o s
Sub-indica o s Cha ac e is ics
I
4
C ea ing Reliable
P ocesses
I
41
P oduc o Se ice Li e
Cycle
I
411
(Time o Launch
P oduc ion o Se ice)
I
412
(Du a ion o P oduc
Ope a ion o Se ice)
I
42
Using S anda d Pa s o
Me hods
I
421
(A ailabili y o S anda d
Pa s)
I
422
(A ailabili y o Me hods/
P ocedu es)
I
43
Using T oubleshoo ing
P ocesses
I
431
(Minimizing he Requi ed
Time o Find he Faul )
I
432
(Minimizing he Requi ed
Cos o Find he Faul )
I
5
C ea ing Requi ed
P ocesses
I
51
Using Simul aneous
Bila e al P ocesses
I
511
(Ha ing Quali a i e
Aspec s)
I
512
(Ha ing Quan i a i e
Aspec s)
I
52
Using Cus ome - ocused
P ocesses
I
521
(Maximizing Quali y o
P oduc o Se ice)
I
522
(Minimizing Cos o
P oduc o Se ice)
I
523
(Maximizing On- ime
Deli e y)
I
53
Using S ong P ocesses in
all Le els
I
531
(To be Comple e)
I
532
(To be Comp ehensi e)
I
533
(To be Consis en and
Clea )
I
54
Using A o dable
P ocesses
I
541
(Minimizing P ocess
Time)
I
542
(Minimizing P ocess Cos )
I
6
E ec i eness o he
Supplie s
I
61
Supplie Assessmen
be o e Pu chasing
I
611
(Alloca ion o E alua ion
Tables)
I
612
(Ca ego izing Supplie s o
A, B, C, and D)
I
613
(P epa ing an Au ho ized
Lis o Pu chasing)
I
62
Supplie Con ol du ing
Pu chasing
I
621
(P epa ing a Lis o
Con ol Poin s)
I
622
(P o ision o App op ia e
Con ol Tools)
I
623
(Checking Quali y
Ce i ica es o I ems/Se ices)
I
63
Sa is ac ion Reco d a e
Pu chasing
I
631
(Alloca ion o Sco ing o
he Selec ed Supplie s)
I
632
(Ca ego izing Sa is ac ion
Sco e om Pu chasing)
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
15
Appendix D
Da a used o d aw he guidelines o in e p e o al sco es o lean/agile SCM
Figs. D1 and D2
Fig. D1. Da a p o ided by he 25 o ganiza ions (all da a e e o 2002–2020).
Fig. D2. To al sco es o SCM e sus a e ages o pe cen age ealiza ions o TQM goals.
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
16
Appendix E
Implemen a ion o he p oposed ma hema ical model o he a ge o ganiza ion
E.1. Assessmen o lean SCM o he a ge o ganiza ion
This sec ion includes he Excel sp eadshee s ac ually used by he TQM p ac i ione s o assess he lean app oach o SCM o he a ge o ganiza ion
o achie e TQM goals. To simpli y he compu a ions, he p ac i ione s spli he se o indica o s in h ee subse s and illed in an Excel sp eadshee pe
each se . Fig. E1 shows he assessmen o lean SCM conside ing he subse {I1,I2,I3}. Simila ly, Figs. E2 and E3 show he assessmen o lean SCM
conside ing he subse s {I4,I5,I6}and {I7,I8,I9}, espec i ely. The o al sco e o he lean app oach is he o al o all pa ial sco es p o ided by he h ee
sp eadshee s.
Fig. E1. Excel sp eadshee o he calcula ion o TSlean
{I1,I2,I3}.
Fig. E2. Excel sp eadshee o he calcula ion o TSlean
{I4,I5,I6}.
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
17
Fig. E3. Excel sp eadshee o he calcula ion o TSlean
{I7,I8,I9}.
E.2. Assessmen o agile SCM o he a ge o ganiza ion
This sec ion includes he Excel sp eadshee s used by he TQM p ac i ione s o assess he agile app oach o SCM o he a ge o ganiza ion o
achie e TQM goals. As o he lean app oach, he p ac i ione s assessed agile SCM using h ee Excel sp eadshee s. Fig. E4 shows he assessmen o agile
SCM based on he subse {I1,I2,I3}. Simila ly, Figs. E5 and E6 show he assessmen o agile SCM conside ing he subse s {I4,I5,I6}and {I7,I8,I9},
espec i ely. Hence, he o al sco e o he whole app oach was compu ed by summing oge he he pa ial sco es p o ided by he h ee subse s o
indica o s.
Fig. E4. Excel sp eadshee o he calcula ion o TSagile
{I1,I2,I3}.
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
18
Fig. E5. Excel sp eadshee o he calcula ion o TSagile
{I4,I5,I6}.
Fig. E6. Excel sp eadshee o he calcula ion o TSagile
{I7,I8,I9}.
E.3. De ails o calcula ions o pa ial sco es
Fo he sake o comple eness and o u he cla i y how he ma hema ical model wo ks, we show he de ails o some o he e alua ion ma ices,
weigh ec o s, and calcula ions yielding he pa ial sco e o lean SCM based on he i s h ee indica o s, ha is, TSlean
{I1,I2,I3}. These a e he nume ical
alues o Fig. E1. The calcula ions leading o he o he o al sco es o lean and agile SCM in Figs. E2 o E6 a e de eloped simila ly.
The gene al p ac i ione s assign he cha ac e is ics’sco e ec o s. The o al sco es a e compu ed as a e ages o he componen s o he co e-
sponding sco e ec o s.
s (I111) = ( s1(I111)s2(I111)s3(I111)s4(I111)s5(I111) ) = ( 66757)
M. Ta ana e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100633
19
s(I111) = 1
5∑
5
=1
s (I111) = 6+6+7+5+7
5=6.20
s (I112) = ( s1(I112)s2(I112)s3(I112)s4(I112)s5(I112) ) = ( 54968)
s(I112) = 1
5∑
5
=1
s (I112) = 5+4+9+6+8
5=6.40
P oceed simila ly o all he emaining cha ac e is ics.
s (I11) =
⎛
⎜
⎜
⎜
⎜
⎝
6 5
6 4
7 9
5 6
7 8
⎞
⎟
⎟
⎟
⎟
⎠
×(0.5
0.5)= ( 5.5 5 8 5.5 7.5)
s(I11) = 1
5∑
5
=1
s (I11) = 5.5+5+8+5.5+7.5
5=6.30
s (I12) =
⎛
⎜
⎜
⎜
⎜
⎝
5 6
6 6
7 8
3 8
7 7
⎞
⎟
⎟
⎟
⎟
⎠
×(0.6
0.4)= ( 5.4 6 7.4 5 7 )
s(I12) = 1
5∑
5
=1
s (I12) = 5.4+6+7.4+5+7
5=6.16
s (I13) =
⎛
⎜
⎜
⎜
⎜
⎝
5 7
7 5
7 9
9 7
6 8
⎞
⎟
⎟
⎟
⎟
⎠
×(0.5
0.5)= ( 66887)
s(I13) = 1
5∑
5
=1
s (I13) = 6+6+8+8+7
5=7.00
P oceed simila ly o he emaining sub-indica o s.
s (I1) =
⎛
⎜
⎜
⎜
⎜
⎝
5.5 5.4 6
5 6 6
8 7.4 8
5.5 5 8
7.5 7 7
⎞
⎟
⎟
⎟
⎟
⎠
×⎛
⎝
0.3
0.4
0.3⎞
⎠= ( 5.61 5.7 7.8 6.1 7.2)
s(I1) = 1
5∑
5
=1
s (I1) = 5.61 +5.7+7.8+6.1+7.2
5=6.45
P oceed simila ly o he emaining indica o s.
s ({I1,I2,I3}) =
⎛
⎜
⎜
⎜
⎜
⎝
5.61 6.42 5.66
5.7 6.7 6.1
7.8 6.9 5.7
6.1 6.5 5.1
7.2 7 5.6
⎞
⎟
⎟
⎟
⎟
⎠
×⎛
⎝
0.1
0.15
0.15 ⎞
⎠= ( 2.37 2.48 2.66 2.34 2.60 )
TSlean
{I1,I2,I3}=2.37 +2.48 +2.66 +2.34 +2.60
5=2.49
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