Be ge , Ron; Wagne , Ral ; Dion, Paul M.; Ma hias, Olga
A icle — Published Ve sion
Dis up ing dis up ions: enhancing supply chain esilience
—lessons om he US Ai Fo ce
Annals o Ope a ions Resea ch
P o ided in Coope a ion wi h:
Sp inge Na u e
Sugges ed Ci a ion: Be ge , Ron; Wagne , Ral ; Dion, Paul M.; Ma hias, Olga (2025) : Dis up ing
dis up ions: enhancing supply chain esilience—lessons om he US Ai Fo ce, Annals o Ope a ions
Resea ch, ISSN 1572-9338, Sp inge US, New Yo k, NY, Vol. 347, Iss. 3, pp. 1163-1192,
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Annals o Ope a ions Resea ch (2025) 347:1163–1192
h ps://doi.o g/10.1007/s10479-025-06527-6
ORIGINAL RESEARCH
Dis up ing dis up ions: enhancing supply chain
esilience—lessons om he US Ai Fo ce
Ron Be ge 1·Ral Wagne 2·Paul M. Dion3·Olga Ma hias4
Recei ed: 29 Ma ch 2024 / Accep ed: 5 Feb ua y 2025 / Published online: 19 Feb ua y 2025
© The Au ho (s) 2025
Abs ac
Black swan e en s ha e highligh ed he impo ance o supply chain esilience and hence
d awn inc eased a en ion om academia. Using mili a y supply chains as ou esea ch se -
ing, we illus a e how supply chain esilience can be implemen ed in ci ilian ne wo ks and
inco po a e agili y and lexibili y in o a esponsi e sys em- o-sys em model. We use a sim-
ula ion model based on he Cassand a applica ion o u he de elop supply chain ne wo k
esilience heo y. Ou model p o ides upda ed si ua ional awa eness o decision make s and
allows manage s o iden i y di ec and indi ec h ea s o supply chains, allowing adap a ion
o un o eseen si ua ions. We de eloped a dynamic, whole-sys em ne wo k model o p o ide
imely, accu a e, upda eable and scalable in o ma ion o planne s and decision-make s a all
le els in-o de o educe isk and inc ease esilience.
Keywo ds Supply chain esilience ·Complex adap i e sys ems ·Casand a ·Modeling ·
Dis up ion
1 In oduc ion
On Ma ch 11, 2020, he Wo ld Heal h O ganiza ion decla ed he COVID-19 ou b eak a
pandemic. Pandemics a e de ined as he occu ence o an in ec ious disease o e an ex ensi e
a ea, c ossing in e na ional bo de s, and a ec ing a g ea numbe o indi iduals (Kelly, 2011).
BRon Be ge
[email p o ec ed]
Ral Wagne
[email p o ec ed]
Paul M. Dion
[email p o ec ed]
Olga Ma hias
[email p o ec ed]
1G adua e School o Business Adminis a ion, Ba -Ilan Uni e si y, Rama -Gan, Is ael
2School o Economics and Managemen , Uni e si y o Kassel, Kassel, Ge many
3College o Business, Uni e si y o Neb aska Lincoln, Lincoln, USA
4Business School, He io -Wa Uni e si y, Edinbu gh, Sco land
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1164 Annals o Ope a ions Resea ch (2025) 347:1163–1192
Pandemics a e cha ac e ized by a educed abili y o p edic he u u e and a pe cei ed loss
o con ol. They ep esen si ua ions whe e esponses o he eme gency gene a e addi ional
un o eseen (and usually nega i e) ou comes (Gebha d e al., 2022). A pandemic-induced
c isis is a he e ogeneous phenomenon, a ying in b ead h (wha is a ec ed), dep h (in ensi y
o i s impac ), and empo ali y (du a ion). The p esen global economic c isis s ongly linked
o he COVID-19 pandemic is subs an ially di e en om he las inancial c isis (2007–2008)
since i does no ha e a inancial o igin (bubble–bu s cycle). I can be iewed as a black swan
e en —a o ally unexpec ed e en ha akes he wo ld economy by su p ise (Belghi a e al.,
2022). Black swan e en s occu wi h low p obabili y bu ha e high impac and a e pe cei ed
by c i ical s akeholde s o h ea en he iabili y o he economy (Pu husse y e al., 2022).
In he COVID-19 black swan e en , his un o eseen de elopmen mean a simul aneous
supply and demand shock ha was di icul o o e come (Amankwah-Amoah e al., 2021).
Fo ins ance, on he supply side, employees we e unable o go o wo k, p oduc ion was
se e ely dis up ed and supply channels we e blocked; on he demand side, he shock was
mani es ed by households and businesses being unable o buy basic goods and se ices as a
esul o lockdowns and supply chain dis up ions (Sa ka & Clegg, 2021). The COVID-19
c isis was cha ac e ized by complexi y and unce ain y, in luencing (and being in luenced by)
go e nmen policies, heal h sys ems, i m beha io , and indi idual beha io s (Mena e al.,
2022).
These black swan e en s ene gized he p esen esea ch in o supply chain esilience, he
abili y o espond o and eco e om unexpec ed supply chain dis up ions (B andon-Jones
e al., 2014; Hohens ein e al., 2015). This pape ocuses on supply chain esilience mod-
eling and no en i onmen al igge e en s. Acco ding o Tukamuhabwa e al. (2015)and
DuHadway e al. (2017), supply chain esilience can be decons uc ed in o phases encompass-
ing an icipa ion, esis ance, and eco e y. Academic esea ch ocused on de eloping s ong
esilience s a egies o be e coping wi h dis up ions (Gebha d e al., 2022; Kamalahmadi
e al., 2022; Ve ma & Gus a sson, 2020). The ope a ional and economic global dis up ions
seen du ing he COVID-19 pe iod o 2020–2023 amply demons a e he ulne abili y o
supply chains o idiosync asies o demand and supply shocks. Resea che s no e ha lack o
supply chain esilience was a p ima y eason o poo supply chain pe o mance du ing his
pe iod (Qade e al., 2022). The impac caused by he COVID-19 pandemic on global ade
is wi hou p eceden , p ecluding he applica ion o adi ional heo ies o isk and esilience
(Mena e al., 2022).
I does no , howe e , ake a black swan e en o unde sco e he ulne abili y o supply
chain o dis up ions. These a e una oidable in oday’s economic en i onmen s and a ied in
cause and e ec (DuHadway e al., 2019;Gebha d e al.,2022). O e he las ew decades,
co po a ions ha e se up global supply chains by expanding o sho ing and ou sou cing
ac i i ies (Gebha d e al., 2022). Globaliza ion has led o supply chains becoming longe
and mo e complex, he eby inc easing hei ulne abili y o shocks (Mena e al., 2022). Risk,
in his con ex , ela es o e en s ha can cause widesp ead and sus ained sho age o a p oduc
o se ice wi h no al e na i es o subs i u es a ailable. In e na ional supply chains con inue o
expand in line wi h inc easing le els o globaliza ion, leading o highe in e connec edness
and in e dependence among i ms. While he in e dependence has enhanced supply chain
e iciency wi h p ac ices o lean manu ac u ing, concu en enginee ing, and “jus -in- ime”
deli e ies, i has also inc eased supply chain ulne abili ies (Wo ld Economic Fo um, 2019).
The economic and social connec ions ha engende ed globaliza ion ha e also ein o ced
in e dependencies and hence he need o imp o ed esilience.
Complex adap i e sys ems we e ini ially applied o esea ching li ing sys ems (Su ana
e al., 2005). These sys ems a e de ined as a kind o s uc u e ha g adually eme ges as a
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1165
cohe en o m h ough he p ope ies o adap a ion and sel -o ganiza ion (Choi e al., 2001).
I ocuses on he eme gence o o de in dynamic and non-linea sys ems (Kau man, 1995).
Resilience is one majo inhe en ea u e o complex adap i e sys ems (Fangxu e al., 2024).
To unc ion as a complex adap i e sys em, one connec s wi h o he s in he sys em and
make decisions based on impe ec in o ma ion (Day, 2014). Co-e olu ion may ins iga e
a change om equilib ium o disequilib ium be ween a sys em and i s en i onmen . As
o ganiza ions adap o complex en i onmen s wi h mul iple ela ionships and in e ac ions,
mo e and mo e schola s and p ac i ione s sugges ha i is a na u al s ep o in es iga e
ope a ions and managemen issues wi hin he complex adap i e sys ems pa adigm (Pa hak
e al., 2007). By u ilizing complex adap i e sys ems heo y, we a e able o de elop a de ailed
analysis o he key ene s o complexi y om which we p o ide heo e ical and p ac ical
insigh s.
Supply chains a e human cons uc s wi h unc ional goals ha include deli e ing speci ic
p oduc s and se ices o cus ome s wi h se cos minimizing o p o i -maximizing objec-
i es (No ak e al., 2021). Supply chains ha e been concep ualized as complex adap i e
sys ems ha ope a e as ne wo ks (Choi e al., 2001;Pa hake al.,2007) o as complex socio-
ecological sys ems ha a e c oss-linked o o he social-ecological sys ems ha can shape
wha is conside ed no mal and desi able (Ya oson e al., 2021). F om a complex adap i e
sys em pe spec i e, he supply chain con inuously adap s, sel -o ganizes, and ans o ms in o
new con igu a ions ha allow i o main ain i s unc ionali y (Hea nshaw & Wilson, 2013;
Mason & Leek, 2008; No ak e al., 2021). Acco dingly, supply esilience and isk manage-
men ’s join aim is o aba e he in luence o sudden dis up ions and e u n o ope a ional
no mali y in a imely and cos -e ec i e manne (Ch is ophe & Holweg, 2017). As such, we
mus unde s and he sou ces o such dis up ions.
Supply chain dis up ions ha e many causes, which we classi y in o i e main g oups. The
i s cause is he demand and supply shocks ha occu when he e a e unexpec ed inc eases in
demand o supply sho ages. These empo al misma ches occu when esou ces a e consumed
a a es ha canno be sus ained o e en a a no mal a e when he e is no enough supply in
sigh . Fo example, ha es ing lumbe o ish mo e apidly han a o es o ish popula ions
can na u ally egene a e o when he COVID-19 epidemic d o e up lumbe p ices when
p oduce s comple ely misgauged he numbe o homeowne s doing eno a ions du ing he
pandemic (NBC News, 2021). Ano he example is he US mili a y now acing ammuni ion
sho ages because o a demand su ge caused by he Uk aine in asion (WSJ, 2022). In he US,
ehicle sales collapsed du ing COVID-19 and hen ebounded bu chipmake s had meanwhile
swi ched o supplying consume elec onics make s, causing sho ages and delays. The swi ch
was a conscious decision by chipmake s esponding o he ma ke ha esul ed in au omake s
no being able o mee ma ke demand (Fel ma e, 2021).
The second sou ce o dis up ions is na u al disas e s ha can w eak ha oc on supply chain
sys ems. Fo ins ance, in 2022 Hu icane Ian le Flo ida wi h sho ages anging om bo led
wa e o lashligh s (Tampa Bay Times, 2022). Following he Tohoku ea hquake in Japan in
2011, Toyo a’s supply chains we e se e ely dis up ed and, as a esul , he company pu in
place-imp o ed coo dina ion mechanisms o es o e supply chain esilience (Ma suo, 2015).
The hi d sou ce o dis up ions is delibe a e poli ical and mili a y con lic s, po en sou ces
o supply chain dis up ion (Blessley & Mudambi, 2022). Fo ins ance, Russia’s in asion o
Uk aine in Feb ua y 2022 se o a domino e ec o supply chain dis up ions oo nume ous o
ca alog, shaking he co e o global business. I is claimed ha he K emlin se ou delibe a ely
o cause economic dis up ion among NATO suppo e s o Uk aine (Rannane e al., 2022).
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1166 Annals o Ope a ions Resea ch (2025) 347:1163–1192
The ou h sou ce o dis up ions is unin en ional acciden s (Roh e al., 2021). Fo ins ance,
he E e Gi en, which an ag ound in he Suez Canal, le mo e han 100 ships s anded a
each end o he canal o weeks, leading o global delays and supply dis up ions.
The i h sou ce o dis up ions is in e ac ions be ween causes one h ough ou
(Gunaseka an e al., 2015; Hea nshaw & Wilson, 2013). Fo ins ance, high uel p ices in
Flo ida caused by he Russian in asion o Uk aine (Feb ua y 2022) we e exace ba ed by
he na u al disas e in Flo ida (Sep embe 2022), which made he esupply o gas s a ions
di icul . Bo h supply and demand chain ulne abili ies ed one ano he leading o acu e
sho ages. In ano he example, COVID-19 caused a sho age o mic ochips because wo ke s
could no ge o he ab ica ion plan s o we e oo sick o come o wo k, which si ua ion was
wo sened by he Uk aine wa , which inc eased demand o chips as componen s in weapons.
The isk o supply chain dis up ion can be u he in ensi ied by manage ial ac o s
when wo indus ial p ac ices—lean manu ac u ing and jus -in- ime p oduc ion—a e ol-
lowed (Ya oson e al., 2021). These app oaches aim o e adica e possible was e and ad ance
he low wi hin he supply chain and supplie s’ esponsi eness o cus ome s. None heless,
co po a ions could become mo e suscep ible o supply chain dis u bances when adop ing
hese s a egies. To success ully ollow hem, co po a ions mus depend on ac o s ou side
o hei con ol (C aighead e al., 2020), which pa adoxically weakens hei supply chain
esiliency. To educe such dependency, edundancies may be necessa y. These may sac i ice
he e iciency goals o indi idual i ms in he sho e m, bu p omo e supply chain esilience
o e he long e m. Nandi e al. (2020) claim ha e ec i ely managing supply chain esilience
is mo e signi ican han honing in e nal compe ences. This issue has ye o be ully explo ed.
Supply chains equi e manage ial s a egic in e en ions o su i e dis up ions. This can be
done, in pa , by modeling possible solu ions o po en ial p oblems (i.e., a ype o isk analysis
and managemen ). He e we ask and model how esilience can be enhanced by educing
asse speci ici y. Much o he con empo a y supply chain managemen li e a u e esea ches
esilience om he pe spec i e o a i m o a speci ic indus y (No ak e al., 2021). In ou
iew he e is a need o imp o e he unde s anding o he linkages be ween esilience and he
mul iscale dynamics ha explain how supply chains e ol e o e ime in ligh o en i onmen al
changes, as discussed in he p e ious pa ag aphs abou igge e en s (Gebha d e al., 2022;
an Hoek, 2020; Ve ma & Gus a sson, 2020). We seek o c ea e a holis ic simula ion model
ha would help manage s in c ea ing a complex adap i e sys em ha is be e able o cope
wi h dis up ions o he supply chain in ad ance o in eal ime. I would p o ide al e na i es
ha acili a e speedy decisions abou op imum choices o con inuous in o ma ion and supply
lows. I will u he help o maximize supply chain managemen obus ness. We con ibu e o
exis ing esea ch models on supply chain managemen by iden i ying he ac o s ha enhance
supply chain esilience in en i onmen s ha a e p one o dis up ion.
We e alua e key ac o s ha can in luence bo h he obus ness and esponsi eness o he
supply chain ne wo k using expe iences om he US Ai Fo ce. Ou pape o e s an empi ical
s udy o a dynamic sys em designed wi h a complex adap i e sys em ne wo k applied o a
pe ennial mili a y p oblem as well as p oo o i s e icacy. Such mili a y indings we e ound
o be applicable in ci ilian supply chains seeking enhanced supply chain esilience (Kakhki
e al., 2022). The pape desc ibes a p ojec conduc ed wi h he Uni ed S a es Ai o ce in
which supply ne wo k esilience modeling was applied o i s supply chain. The Uni ed S a es
Ai Fo ce sough solu ions o p oblems caused by insu icien managemen o supply chains,
which in u n led o lawed decision-making, based on pa ial in o ma ion, con inuing poo
acking and a de ec i e da a cycle. This esea ch is he i s explo a ion, o he bes o ou
knowledge, o a comple e supply chain model as a se ies o in e dependen ne wo ks. This
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1167
s udy add esses p oac i e designs o supply chains including he ac o s ha could impinge
on supply chain pe o mance and esilience.
Mili a y o ces ha e inc easingly been deployed in humani a ian assis ance and disas e
elie . This pulls on he mili a y’s s eng h o ‘ eadiness’ o help peacekeeping and disas e
elie ac i i ies. On he o he hand, i is hampe ed by he di e en wo king s yles, oles
and guiding p inciples he mili a y and humani a ian o ganiza ions ha e (Heaslip & Ba be ,
2016). The la ge numbe o agen s in ol ed in he ne wo k u he inc eases complexi y.
These speci ic pe o mance challenges make mili a y supply chains pa icula ly sui able
o whole-chain analysis using a ne wo ked app oach o coo dina ion and decision-making.
Yoho e al. (2013) posi ha de ense and business supply chains ha e become simila because
supply chain u bulence has gene ally inc eased, as has he impe a i e o ha e an e icien
and e ec i e low o goods, se ices and in o ma ion.
The emainde o he pape is o ganized as ollows. Fi s , we examine p e ious esea ch
on supply chain esilience in ligh o black swan e en s. Secondly, we explain he esea ch
me hodology implemen ed. Thi dly, we p esen ou model and esul s, and discuss hei
implica ions in a non-mili a y con ex . Las ly, we de i e conclusions and implica ions o
heo y and p ac ice, no e limi a ions, and p opose u u e esea ch di ec ions.
2 Li e a u e e iew
Resilience is e lec ed in he abili y o p epa e o and eco e om low p obabili y bu ec-
ognized dis up i e e en s and achie e some pos -dis up ion ope a ional equilib ium (Dolgui
e al., 2018). Resilience ocuses on main aining sys em unc ionali y as opposed o main-
aining unc ional e iciency (Slack e al., 2009). Being esilien , he sys em is s able, nea
equilib ium o s eady s a e, and able o e u n o ha s a e ollowing shocks, wi h mo e
esilien sys ems bouncing back mo e quickly han less esilien sys ems.
The esou ce-based iew (B andon-Jones e al., 2014), dynamic capabili y heo y (Chowd-
hu y & Quaddus, 2017a,2017b; I ikha e al., 2021), esou ce dependency heo y (Gebha d
e al., 2022), social exchange heo y (Shin & Pa k, 2021), and sys em heo y (Kim e al., 2015)
ha e been widely used as heo e ical bases o supply chain esilience esea ch bu all ha e
been ound o possess signi ican sho comings (Tukamuhabwa e al., 2015). These heo ies
ocus on he in e nal wo kings o supply chain esilience, wi hou aking supplie sys ems and
co-e olu ion in o accoun . Whe e hese pape s do acknowledge a sys emic aspec , i ends o
be s a ic in na u e. Fo ins ance, esou ce based iew is i m biased and igno es componen
syne gies (Gebha d e al., 2022). I assumes p edic able en i onmen s whe e he u u e alue
o esou ces is de e minable. Dynamic capabili y models based on in e - i m componen s
(Wang & Ahmed, 2007) ail o add ess supply chain esilience as a whole ecosys em. Sys-
ems heo y does ecognize he sys emic s uc u e o supply chains bu in ocusing on lows,
low uni s and hei sou ces, omi s empo al changes, which educes supply chain esilience
accu acy and abili y o o ecas complex adap i e sys em u u e e en s (Choi e al., 2001;
Kim e al., 2015). Fu he mo e, he bulk o esea ch on supply chain esilience was ound
o be concep ual in na u e (Wieland e al., 2016; Ch is ophe & Holweg, 2017;DuHadway
e al., 2017). Teece e al. (1997) ex end he esou ce based heo y and belie ed ha i ms
need o cons an ly in eg a e and econs uc hei esou ces and capabili ies, as hey ha e o
cope wi h changes in he ex e nal ma ke en i onmen and a oid losing hei compe i i e
ad an age due o hese changes. The heo y is sui able o cla i ying how a i m imp o es i s
ope a ional pe o mance by manipula ing he igh esou ces. Some esea ch has been done
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1168 Annals o Ope a ions Resea ch (2025) 347:1163–1192
on modeling o supply chain esilience (E ol e al., 2010), complex adap i e sys em s udies
(B andon-Jones e al., 2014; Pu is e al., 2016) and su ey-based wo k (Wieland & Wallen-
bu g, 2013). I seems o us ha such examina ions all sho o add essing ne wo k issues,
which align wi h biological ecosys em analogies. Acco dingly, new model concep ions a e
needed.
Indus ial ecologis s look o biological ecosys ems as analogies o me apho s in he s udy
o supply chains (Cô é, 1999). Some ecologis s a gue ha i is he di e se na u e o an
ecosys em, which is cen al o i s sus ainabili y. This di e si y enables some edundancy in
unc ion, which, in u n, suppo s he s abili y and esilience o he sys em. Schola s ha e
used biological ecosys ems as an analogy o explo e in e -o ganiza ional ela ionships and
supply chains, ye he p e alence and inc easing impo ance o business ecosys ems ac oss
indus ies has spa ked a bu geoning esea ch ocus in his a ea. Allenby and Coope (1994)
poin ed ou ha supply chains sha e many o he p ope ies o biological sys ems. Thei
conclusion was ha a supply chain esembles a biological communi y.
Despi e esou ce-based iew’s de iciencies, in ou iew, i is he bes s a ing poin o
apply o ou model as i is based on he idea ha companies depend on hei en i onmen s
o acqui e sca ce esou ces unde a o able condi ions o ensu e hei su i al (Nandi e al.,
2020). Mo eo e , gi en ha esilience esea ch is mos ly based on esou ce-based iew,
i would seem a sui able amewo k o s udying supply chain in e dependencies (Spieske
e al., 2022) wi h biological ecosys em analogies o o se he abo e-men ioned heo ies’
weaknesses. Resou ce-based iew deals wi h condi ions whe e supply chains depend on
an unce ain en i onmen o acqui e esou ces essen ial o hei ope a ions. Using esou ce-
based iew, p io li e a u e has shown ha i ms’ in e nal esou ces, such as physical acili ies,
inancial asse s, human esou ces, and echnological de elopmen as well as hei ex e nal
esou ces such as supply connec i i y, a e c i ical o supply chain esilience (Gebha d
e al., 2022). Resou ce-based iew s a es ha a i m’s compe i i e edge is in luenced by he
s a egic esou ces o capabili ies i possesses (Ba ney, 1991). The basic p emise behind his
iew is ha esou ces a e he e ogeneously and sp ead ac oss i ms. I hey a e aluable, a e,
no pe ec ly imi able and non-subs i u able, hey a e able o sus ain he i m’s compe i i e
ad an age (I ikha e al., 2021).
Resilience om a esou ce based iew pe spec i e is an ou come o he o ganiza ional
capabili ies employed o minimize he un a o able impac o dis u bances (Nandi e al.,
2020). Resilience is conside ed a mul i ace ed concep ha add esses how an o ganiza ion
and i s membe s eac o unce ain y (Blessley & Mudambi, 2022). These a e all-inclusi e
capabili ies, which a e u ilized o ob ain esou ces, and eo ganize, in eg a e, and p io i-
ize hei alloca ion in a complex business en i onmen . This implies ha a esilien supply
chain possesses la ge bu e ing capaci y, and an e en mo e esilien supply chain is one
ha can wi hs and ela i ely la ge shocks while e aining i s cu en s uc u es and p ocesses
(Kamalahmadi e al., 2022). Resilience-building s a egies allow he supply chain o main ain
unc ionali y by adap ing and ans o ming in esponse o black swan e en s. Fo example,
i a se o supplie s is no longe a ailable due o an emba go o a na u al disas e , a b idg-
ing s a egy, which only esilien supply chain managemen would ha e, migh in ol e he
imp o isa ion o ac i ely managing cus ome expec a ions, using new supplie s, o inding
subs i u e inpu s.
To use esou ce-based iew and limi he impac o i s sho comings, we iew he supply
chain as one in e wined uni and no as indi idual i ms. By in eg a ing and exploi ing
esou ces ac oss au onomous i ms, new exclusi e compe ences a e o med and esilience
inc eased (Lu e al., 2010). In o he wo ds, lea ning om pas esea ch on esou ce-based
iew’s laws, we expand i s heo e ical scope o ocus on he supply chain, no on a speci ic
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1169
i m, and in oduce unp edic able en i onmen s in o ou model, which is able o adap o
dis up ions. Supply chain in eg a ion is ealized in he esilience li e a u e as a s a egic
esou ce ha can be u ilized in alle ia ing supply chain dis up ions and enhancing esilience
(Wu e al., 2010). I is claimed ha a esilien supply chain is a ne wo k ha can e ain exis ing
s uc u es and unc ions should i unde go some ype o shock (No ak e al., 2021).
The esou ce dependency heo y, u he ing he esou ce based iew, in oduced by P e e
and Salancik (1978) is an o ganiza ional heo y ha ocuses on how o ganiza ions ely on
o he s and manage hei ela ionships o su i e by educing en i onmen al unce ain y. This
heo y is he main mo i a o in c ea ing a alue chain ne wo k (Ba inge & Ha ison, 2000).
The heo y can enligh en he an eceden o in e -o ganiza ional collabo a ion and he eason
o join ac ions. I iews o ganiza ions as he s akeholde s, which ha e dynamic in e es s
and can be used o examine and in e p e hei beha io in collabo a ing wi h o he s o
achie ing hei goals. Wi hin his heo y, o ganiza ions a e awa e ha dependence o ms
us and ole ance o o he s, which becomes he basis o a ela ionship.
Howe e , bo h he esou ce based heo y and he esou ce dependency heo y ocus on
esou ce po en ial a he han sys emic in e ac ions, which limi s i s explana o y powe
ega ding he ela ionship be ween isibili y and business pe o mance (Wong & Ka ia,
2010). In he ield o supply chain esea ch, he esou ce-based iew ocuses on he in e nal
esou ces o i ms and does no go beyond he le el o i ms (K aaijenb ink e al., 2010). In
addi ion, he esou ce-based iew assumes ha he u u e alue o esou ces is de e mined in
a p edic able en i onmen , bu supply chain esilience is p ecisely nonlinea , dynamic, and
unp edic able.
To o e come he sho comings o he esou ce based heo y and he esou ce dependency
heo y, Wang e al., (2016) in oduce he dynamic capabili y heo y, as an ex ension o he
esou ce based heo y. I be e explains he in luence o big da a capabili y. Many s udies ha e
explo ed supply chain esilience and i s o ma ion mechanism based on dynamic capabili y
heo y, and many esea che s ega d supply chain esilience i sel as a dynamic capabili y
(Chowdhu y & Quaddus, 2017a,2017b; K aaijenb ink e al., 2010). As such, he dynamic
capabili y heo y p o ides a heo e ical basis o ela ed esea ch on supply chain esilience
and he logical amewo k o his pape . Common o hese s udies is ha dynamic capabili ies
a e dis inc om o dina y ou ines o o ganiza ional compe ences, and e en dynamic capa-
bili ies a e hie a chically o de ed in ways ha he highe -o de capabili ies con ibu e he
mos o adap a ion a e adical changes (Win e , 2003). By conside ing dynamic capabili ies
as bes p ac ices, hese au ho s ende he concep o dynamic capabili ies mo e p ac ical and
gene alizable (Eisenha d & Ma in, 2000).
As sys ems p o ides an essen ial, ac ionable amewo k om a manage ial pe spec i e, we
u ilize in pa allel o he dynamic capabili y heo y, sys ems heo y. The eason o selec ing
his sys ems-le el app oach is ha i p o ides an app op ia e heo e ical iew o gene a -
ing and guiding in o ma i e decision insigh s o supply chain ac o s in isky en i onmen s,
ul ima ely enhancing he o e all ne wo k esilience (Go indan & Al-Ansa i, 2019). Spiegle
e al. (2012), among o he s, ha e s udied he dynamics o supply chain sys ems and assessed
al e na i e in en o y and o de ing con ol policies agains esilience, ha ing a iew on a
speci ic p ocess, hus p o iding a demons a ion o he use ulness o sys em hinking as a
way o link esilience and supply chain ope a ions.
Social exchange heo y was also used in supply chain esea ch. I ocuses on ela ionships
ha inhe en ly in ol e an exchange be ween p o ide s and consume s (Be ge e al., 2014).
Bo owing i s oo s om social psychology and beha io al economic pa adigm, he p emise
o his heo y asse s ha , when an ac o is being p esen ed wi h choices, hey will unde go
subjec i e cos –bene i analysis and weigh a ailable al e na i es be o e making he inal
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1170 Annals o Ope a ions Resea ch (2025) 347:1163–1192
decision. C opanzano e al., (2017) concluded ha his heo y is abou indi iduals as pa o a
communi y and how hey make a ional decisions o maximize posi i e expe iences h ough
social in e ac ions. Social exchange heo y posi s ha ein o cemen mechanisms unde pin
social ela ions, a guing ha people engage in social exchanges whe e mu ual bene i s o m
he basis o main aining hese ela ionships. A basic assump ion is ha he exchange pa ies
do no seek a one-o ansac ional ela ionship bu a con inuous social ela ionship. As his
heo y is mo e on a pe sonal le el and no on he supply chain echnical le el, we ound ha
his heo y does no i he ocus o ou esea ch.
P io esea ch on supply chain esilience seldom conside ed i in e ms o in e dependen
ne wo ks o whole sys em solu ions (Hea nshaw & Wilson, 2013). This linea i y p ecludes
supply chain esilience om handling he aga ies o dis up ion in oday’s dynamic supply
chain – so essen ial when a black swan e en occu s (Oli a es-Aguila & Vi al-So o, 2021).
Supply chain models a e o en ound o be un ealis ically o e simpli ied and linea (Hea n-
shaw & Wilson, 2013; Kamalahmadi e al., 2022; López & Ishizaka, 2019), which inhibi s
e o s o boos supply chain esilience. Many esea che s ha e come o he conclusion ha
supply chain esilience analysis based on simplis ic linea sc u iny is ine ec i e and lead o
supply chain esilience ailu es (Li & Zobel, 2020; Oli a es-Aguila & Vi al-So o, 2021).
Resea che s ha e begun e-concep ualizing supply chains as dynamically e ol ing s uc-
u es wi h di e se connec ions and mul iple cons i uen en i ies. This new iew equi es
new models and heo ies o depic he complex and adap i e phenomena ha may a ec
esilience (Hea nshaw & Wilson, 2013; Tukamuhabwa e al., 2015). The ocus has mo ed o
consolida ing esul s om linea quan i a i e ne wo k modeling and op imiza ion (Ribei o
& Ba bosa-Po oa, 2018; Schol en e al., 2019) and concep s desc ibing human beha io
(Oshio e al., 2018) and managemen echniques (Linnenluecke e al., 2015). Tukamuhabwa
e al. (2015) o e ed one o he i s esea ch e o s on supply chain esilience by aking a
nonlinea complex adap i e sys em app oach (Holland, 1992). Thei esea ch highligh ed a
numbe o gaps in he exis ing app oaches o making supply chains consis en ly esilien .
Fo ins ance, hey poin ed ou ha in e dependencies be ween global supply chains alongside
hei indi idual sou ces need o be conside ed and, in addi ion o s a egies o inc ease supply
chain esilience; he implemen a ion o hese s a egies needs o be add essed.
Recen ly, Mena e al. (2022) classi ied supply chain esilience acco ding o adap ion
capabili ies anging om indi iduals and single supply chain sys ems up o economies and
socie ies on a na ional le el. Complemen ing his esea ch, Gebha d e al. (2022) in oduced a
dis inc ion be ween s udies conside ing esponse measu es and eco e y measu es o a supply
chain dis up ion pos hoc. Pa ke and Ameen (2018) p oposed a esilien adap i e sys em
design ha , on he one hand, is obus o dis up ions wi hou accele a ing bu e ing and, on
he o he hand, p e en s s ock-keeping cos s om ising. Mo e and mo e, supply chains a e
being iewed as ha ing he complexi y o nonlinea biological sys ems (Shin & Pa k, 2021).
Like biological sys ems, supply chains ely on ela ionships, ecip oci y, and coo dina i e
capaci y and unc ion bes as a mu ually bene icial sha ed en e p ise (Dooley e al.,2013; Qian
e al., 2021; Tangpong e al., 2014). Hence, a supply chain esilience model mus accoun o
he necessi y o a pos -dis up ion channel unc ion (possibly a a diminished le el) in acu e
si ua ions such as mili a y o disas e elie applica ions (Kamalahmadi e al., 2022). The
issue, howe e , o con inued ope a ion a a diminished bu s ill iable unc ioning le el when
a dis ibu ion ac o is los is no well esea ched (Gebha d e al., 2022). Complex adap i e
sys ems heo y, p oposed by Holland (1992), builds on gene al sys ems heo y (Holweg &
Pil, 2008). I is conce ned wi h he o al pe o mance o a sys em a he han i s sepa a e
pa s, e en when a change in only one o a ew o i s pa s is con empla ed (Acko , 1971). I
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1177
Fig. 1 Basic node model o supply chain dependency lows
in e p e ed easily using a g aphical in e ace because node dependencies a e shown as do ed
lines whe e he hickness o he line indica es he s eng h o he dependency (see Fig. 1).
To add ess he basic equi emen o iden i ying node dependencies, he i s s ep was o
p o ide isibili y ac oss he en i e ne wo k. A simple, in ui i e node-based ep esen a ion
o he supply chain ne wo k cap u es all i s aspec s, om s a egic o ope a ional le els. A
s aigh o wa d example o his node-based ep esen a ion is depic ed in Fig. 1.
Nodes a e desc ibed in e ms o he ype o esou ce hey ep esen and he kinds o
in e ac ions hey can ha e wi h o he nodes o a ious ypes. The e a e h ee ypes o nodes:
ac o , physical o concep . Ac o nodes a e people, g oups, o o ganiza ions (ac o s in a supply
chain ne wo k esilience). Physical nodes a e esou ces, objec s o loca ions (en i onmen s
in a supply chain ne wo k esilience). Concep nodes a e ideas, goals, p inciples, policies,
me hods o o ganiza ion, o ope a ing p ocedu es (which in luence ‘adap a ion’ and ‘lea ning’
(dimensionali y in supply chain ne wo k esilience) (as no ed in Table 1). Addi ionally, nodes
can be desc ibed in e ms o he in e dependencies— o example, an ac o could “de end”
ano he ac o node o “damage” a physical node. A lis o po en ial dependency ela ionships
be ween node ypes can be ound in Table 2.
Algo i hms de eloped by Dijks a (1959)andFloyd(1962) we e hen applied o hese
ne wo ks o nodes and hei ela ionships. This allows ou model o cap u e he nonlinea i y
and ne wo k connec i i y/in e ac ion sugges ed by supply chain ne wo k esilience heo y,
and adding he ision, acking, and op ions capabili ies equi ed by he Uni ed Sa es Ai
o ce, as laid ou in he Join Expedi iona y Fo ce Expe imen in o ma ion sou ces. These
algo i hms look a he comple e con igu a ion and assign a dependency sco e o each node.
They loca e poin s o high dependency and e alua e hei impac ac oss he supply chain in
he e en o a dis up ion. This allows he classi ica ion o nodes in e ms o capabili y, depen-
dency, and ulne abili y. Capabili y is he ou pu o a node and can be ei he quan i a i e
( uel, anspo a ion) o quali a i e (supe ision, subjec knowledge). I s p oduc ion is based
on he p o ision o an ou pu om one o mo e nodes, de ining one o mo e dependencies,
which i needs o ealize i s capabili ies. Vulne abili y is he di ec suscep ibili y o a node
o a phenomenon gene a ed by an ac ion o e en . In he supply uck example desc ibed
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1178 Annals o Ope a ions Resea ch (2025) 347:1163–1192
Table 2 Node and dependency ela ionships
Ac o Physical Concep
Ac o Ac o suppo s Ac o
Ac o de ends Ac o
Ac o di ec s ac o
Ac o supe ises ac o
Ac o opposes ac o
Ac o mo i a es ac o
Ac o mo es ac o
Ac o ope a es physical
Ac o main ains physical
Ac o epai s physical
Ac o cons uc s physical
Ac o damages physical
Ac o des oys physical
Ac o mo es physical
Ac o accesses physical
Ac o o mula es concep
Ac o ad oca es concep
Ac o opposes concep
Ac o accep s concep
Ac o ejec s concep
Ac o adop s concep
Ac o o es concep
Ac o implemen s concep
Physical Physical p o ec s ac o
Physical suppo s ac o
Physical mo i a es ac o
Physical damages ac o
Physical des oys ac o
Physical mo es ac o
Physical supplies physical
Physical suppo s physical
Physical cons uc s physical
Physical des oys physical
Physical damages physical
Physical di ec s physical
Physical suppo s concep
Physical mo i a es concep
Physical ins an ia es concep
Concep Concep mo i a es ac o
Concep di ec s ac o
Concep suppo s ac o
Concep suppo s physical
Concep mo i a es physical
Concep ins an ia es physical
Concep mo i a es concep
Concep ebu s concep
Concep con adic s concep
Concep suppo s concep
Concep subsumes concep
a he beginning o his sec ion, he uck migh ep esen a node capable o p o iding he
anspo a ion capabili y. I is ulne able o damage o being des oyed by hos ile ac o s and
is dependen on i s uel depo ’s e ueling capabili y. The uel depo node oo will ha e depen-
dencies o i s own. Acco dingly, he uck node could be disabled by damage o dis up ion
o i sel , he uel depo , o any o he nodes on which he depo depends.
Complex adap i e sys em heo y speci ies nonlinea i y and ne wo k connec i i y / in e -
ac ion (Ya osen e al., 2021). To ensu e hese componen s exis in ou model, he algo i hms
used in i we e designed o exploi he nodes’ abili y o mee he p ima y capabili y, depen-
dency, and ulne abili y equi emen s. The node a ibu es and he possible node dependency
pe mu a ions in Table 2we e in eg a ed in o he basic low o he algo i hms.
3.1 Da a collec ion and model de elopmen
Join Expedi iona y Fo ce Expe imen is a la ge-scale Ai Fo ce expe imen designed o
assis he U.S. Ai Fo ce in p epa ing o he challenges o he 21s Cen u y Expedi iona y
Ai and Space Fo ce ope a ions. The Join expedi iona y o ce expe imen link p o ides a
i ual wo kspace o sha e in o ma ion ac oss i s pa icipan s. Web ools we e added o help
manage ope a ing and assessmen asks and o encou age collabo a ion, ha we had access o.
Obse a ions we e collec ed ia a web-based ool du ing each expe imen on ways o imp o e
he design, planning, execu ion, and assessmen o he Join Expedi iona y Fo ce expe imen .
The Join Expedi iona y Fo ce expe imen link web po al was essen ial o access, sha e, and
manage in o ma ion ac oss he expe imen en e p ise e icien ly.
The Uni ed S a es Ai Fo ce’s consis en iden i ica ion o ision, acking, and op ions
logis ics p oblems p omp ed he ou lined app oach and adop ion o complex adap i e sys-
em heo y, as de ailed abo e. The combined a ibu es highligh ed in Table 2p o ided he
a ionale o he model. The model was designed o implemen all he complex adap i e
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1179
sys em ea u es (Table 1) o exis ing da a sou ces so ha ision, acking, and op ions was
possible (Fig. 2). In addi ion o he capabili y, dependency, and ulne abili y a ibu es, he
node model con ains addi ional in o ma ion necessa y o co ec ly model aspec s o node
beha io . Figu e 2shows he comple e node model wi h he addi ional in o ma ion inco po-
a ing empo al and o he me ada a. The Uni ed S a es Ai Fo ce’s consis en iden i ica ion o
ision, acking, and op ions logis ics p oblems p omp ed he ou lined app oach and adop ion
o complex adap i e sys em heo y, as de ailed abo e. The combined a ibu es highligh ed
in Fig. 1, and Table 2p o ided he a ionale o he model. The model was designed o
implemen all he complex adap i e sys em ea u es (Table 1) o exis ing da a sou ces so
ha ision, acking, and op ions was possible (Fig. 2). In addi ion o he ision, acking,
and op ions a ibu es, he node model con ains addi ional in o ma ion necessa y o co ec ly
model aspec s o node beha io . Figu e 2shows he comple e node model wi h he addi ional
in o ma ion inco po a ing empo al and o he me ada a.
The model was designed o implemen he ea u es o a complex adap i e sys em (Table 1)
using da a aken om he Join Expedi iona y Fo ce expe imen in o ma ion sou ces. In addi-
ion o he capabili y, dependency, and ulne abili y a ibu es, ou model con ains addi ional
in o ma ion necessa y o co ec ly model aspec s o node beha io . Figu e 1shows he com-
ple e node model o an example node wi h addi ional in o ma ion ega ding empo al and
o he me ada a (a da a se ha desc ibes and gi es in o ma ion abou o he da a). Once es ed
and alida ed, he model was applied o li e ope a ional sys ems based on he Join Expe-
di iona y Fo ce expe imen da a base. The a chi ec u al o e iew (Fig. 3) shows how he
exis ing legacy sys ems we e mined o da a. This became a con inuous p ocess, pe mi ing
eal- ime upda ing and decision-making once ield ope a ions we e li e.
In his way, u u e models can be de eloped o economic, in as uc u e, social, and
in o ma ion ne wo ks. These models will di e in e ms o he numbe and na u e o hei
Fig. 2 Ou line o he node model
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1180 Annals o Ope a ions Resea ch (2025) 347:1163–1192
Fig. 3 In o ma ion access a chi ec u e o e iew
nodes, he desc ip ion o he ac o s and how hey in e ac (e.g., suppo , de ends, di ec s,
and/o supe ises) wi h o he ac o s, he s uc u e o communica ions ne wo ks, he physi-
cal equipmen in ol ed and he speci ic ac ion op ions a ailable o ac o s. Ne e heless, he
model p esen ed he e is applicable o all he supply chain ca ego ies iden i ied abo e. Each
model iden i ies he in e dependencies be ween nodes wi hin he same ne wo k. Mo e impo -
an ly, hey allow o he speci ica ion o he in e dependencies ha occu be ween di e en
ne wo ks. The esul an ne wo k model comp ises mul iple ne wo ks including p oduce s,
in e - and in a- hea e ai and seali capabili ies, g ound mo emen and las mile deli e ies.
Las mile esupply in a mili a y con ex is he abili y o a supply chain o p o ide logis ics
suppo o comba o ces ha a e wi hin 300 m–30 km o a poin o engagemen wi h enemy
o ces. The model p o ides upda ed si ua ional awa eness ega ding each supply chain on a
nea eal- ime basis.
3.2 Da a analysis
The algo i hms can be applied in six dis inc ways o he popula ed node model. These a e
cap u ed in Table 3, which desc ibes each applica ion, he pu pose i se es and he so o
in o ma ion he analysis p o ides.
Conside ing ne wo ks and hei di e ing dependencies in e ms o hei links allows he
iewe o g asp he s eng h o he dependency ( anging om mino o c i ical), i s na u e
(“supplies”, “ope a es”, “supe ises”) and consequence is-à- is he ou pu o he dependen
node (and nodes ha depend di ec ly o indi ec ly on he dependen node) i i disappea s.
These dependencies c ea e a cumula i e dependency sco e o e e y node in he ne wo k. I
enables all nodes o be anked by how much dis up ion o he es o he ne wo k hei loss
would cause. Fo ins ance, he chain o dependen nodes om depo 1 o o wa d ope a ing
base 1 (Fig. 4) con ains one o mo e common ou e segmen s ( oads, junc ions, b idges) wi h
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1181
Table 3 Reasoning capabili y ca ego ies
Algo i hm Pu pose Ou pu
Dependency- wo op ions
Dependee Iden i y how easily a node is impac ed by
changes o he capabili ies o he
node(s) upon which i is dependen
Nodes sco ed and anked based on he
cumula i e dependency a node has on
o he s ( he need o a depo o uel,
elec ical powe , people, e c.)
Dependen Iden i y he impo ance o a node o he
o e all unc ioning o he ne wo k
Nodes sco ed and anked based on he
cumula i e ansi i e dependency ha
o he nodes ha e on i (se e al supply
depo s all dependen on he same
b idge)
Consequence Iden i y he immedia e consequence o a
change in a node’s capabili y and
p opaga e his o all ansi i ely
dependen nodes
Iden i ica ion and anking o all
impac ed nodes in e ms o he
pe cen age change o he dependen
capabili y
P obabili y Iden i y and ank po en ial weaknesses in
a selec ed ansi i e dependency chain
Calcula ion o a maximum p obabili y
ha a dependency exis s be ween a
pai o nodes based on he combined
p obabili y o he co ec iden i ica ion
o he nodes and links in he chain
Clus e Disco e sel -con ained sub-ne wo ks
wi hin he o e all model ha con ain
nodes Wo ld Heal h O ganiza ionse
ansi i e dependencies a e abo e a
use -p o ided h eshold
Iden i ica ion and anking o (by numbe
o nodes) sub-ne wo ks ha con ain
nodes om mul iple dispa a e
ne wo ks
Comple eness Iden i y missing capabili y, dependency,
and ulne abili y a ibu es and, whe e
possible, iden i y po en ial alues and
mappings
Iden i ica ion and anking o nodes
based on combining hei dependency
sco e and he numbe o missing
capabili y, dependency, and
ulne abili y
Ins an ia ion Iden i y he speci ic alues o a node
om a po en ial se o candida es
Iden i ica ion and anking o based on
he numbe o o he alue
ins an ia ions ha a e ei he educed o
o ced o ha e a speci ic alue
he chain om depo 1 o o wa d ope a ing base 2. This would esul in highe dependency
sco es o he common nodes han ones ha a e no common. Each o wa d ope a ing base
is dependen upon i s own ne wo k o ucks, helicop e s and uel and main enance acili ies.
Each node dependency (Fig. 4) is shown as a do ed line and he hickness o he line
indica es he s eng h o he dependency. Fo example, P2 has a a highe dependency on
o wa d ope a ing base 2 o i s logis ics han i has on o wa d ope a ing base 1 as shown by
he hicke b oken line. The s eng h o a dependency is a ed om 1 o 10 and he ela ionship
is iden i ied based on he pai o nodes in ol ed (as no ed in Table 2). A alue be ween 1 and
100 e lec s he pe cen age change in he node’s capaci y i he dependency is no add essed
(as seen in Fig. 4). Fo example, a uck could be equally dependen on a d i e and uel,
gi ing hem bo h a 5.0 dependency alue. The lack o ei he a d i e o uel, howe e , means
ha he uck is non-ope a ional (i.e., lacks he anspo capabili y) ega dless o how well
he o he dependency is me . In his complex adap i e sys em, using logic ga e p inciples, he
esul ing alue on each link would be 100, e lec ing a 100% loss o he anspo capabili y
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1182 Annals o Ope a ions Resea ch (2025) 347:1163–1192
Fig. 4 Ne wo k supply chain dependency model
i ei he dependency is no me . The alue o a dependency ha is help ul bu no s ic ly
necessa y would be less han 100, e lec ing ha e en wi hou his inpu , he node could s ill
ope a e a a educed capaci y.
The esul s o dependency and associa ed consequence analyses iden i y ulne able poin s
in he ne wo k ha need o be esol ed. Complex adap i e sys ems h ough he Casand a
applica ion was used o p o ide sugges ions how he lack o esilience could be mi iga ed
(D abble & Scha enbe g, 2016). Fo example, ai asse s a e no di ec ly dependen on he
oad ne wo k, bu s ill may be indi ec ly and ad e sely a ec ed by dis up ions o i . Ai asse s
a e dependen on uel supplies, which a e dependen on he oad ne wo k o anspo o
he o wa d ope a ing base. By i e a i ely econ igu ing asse use, complex adap i e sys ems
h ough he Cassand a applica ion p esen s decision-make s wi h a anked lis o ways in
which hey could use he asse s a ailable o hem o mee as many dependencies as pos-
sible, he eby inc easing supply chain esilience by p o iding decision-make s wi h ac ion
op ions. This app oach can be used o sugges modi ica ions o he s uc u e and capabili y
o he supply chain nodes o inc ease hei esilience, hus mani es ing sel -o ganiza ion and
eme gen beha io (as i emized in Table 1). Figu e 5illus a es he si ua ion whe e he e is an
al e na i e g ound ou e om depo 1 o o wa d ope a ing base 2 bu a p esen , his canno
be used because enemy ac ions ha e damaged a oad junc ion and a b idge along he ou e.
I hese nodes could be epai ed o es o e hei capabili y, hen he exis ing bu non-usable
supply ou e would be eopened and he esilience o he supply chains be ween he depo
and he o wa d ope a ing bases imp o ed. The ne wo k would allow o wa d ope a ing base
1 o o wa d ope a ing base 2 mo emen wi h addi ional mo emen s o o wa d ope a ing
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1183
Fig. 5 Modi ied dependency model wi h sugges ed modi ica ions
base 2 ia he eopened ou e. Mo eo e , because he eopened ou e do no ha e any oad
segmen s in common wi h he cu en ou es, his educes he dependency on hese anspo
in as uc u e nodes signi ican ly. This app oach p oduces ou comes adap ed o he p e ailing
en i onmen , inc easing esilience, lexibili y, and he eby i ness. I does no equi e gene ic
solu ions o be de eloped in ad ance o deal wi h he ange o possible changes in he supply
ne wo k. I enables planne s o examine he speci ics o a si ua ion and make he changes ha
would mos e ec i ely inc ease esilience. In o he wo ds, he op imal supply chain ne wo k
esilience model will e ol e o ganically as en i onmen al changes e ol e.
4Findings
Ten di e en supply chain and logis ics models we e c ea ed. Fi e 8000–10,000 node models
desc ibing he deli e y o a ange o logis ics om p oduce s in he US, by in e - hea e
ai li o A ghanis an ia Ge many and o he eques ing o ces ia in a- hea e ai and
g ound aspec s we e c ea ed. Fi e small scale 1200–1550 node models we e also gene a ed
o cap u e in a- hea e and las mile esupply aspec s o mili a y supply chains. An example
o a small-scale model (Fig. 6) demons a es he occu ences and ela ionships be ween
physical o concep nodes and hei co esponding capabili y, dependency, and ulne abili y
alues.
The dependency ne wo k is a complex adap i e sys em wi h he addi ional capabili y o
al e he beha io o he ne wo k as po en ial issues a e iden i ied (Fig. 6). This capabili y is
based on complex adap i e sys ems, planning and lea ning echniques, adop ed om p e ious
mili a y applica ions. The dependency ne wo k can p opaga e changes easily om he ac ical
le el o he s a egic le el wi hin he same model, allowing planne s o an icipa e he ull
impac o hese changes. Dependency analysis ale s planne s o cumula i e dependency
inc eases o which hey a e usually unawa e, especially in he complex adap i e sys em
when o he planne s and sys ems a e in ol ed in decision-making wi h espec o he supply
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1184 Annals o Ope a ions Resea ch (2025) 347:1163–1192
Fig. 6 In e - hea e ai li dependency model
chain. This allows hem o p oac i ely make he kind o changes depic ed in Fig. 5, con olling
dependency and elimina ing sou ces o ailu e.
Po en ial changes o anking occu all along he supply chain— om he manu ac u e s
o he ma e ials who may be a con inen away and ha e aw ma e ial issues, o he planes
mo ing he logis ics o he supply depo , o he ucks mo ing o he o wa d ope a ing base
1— o wa d ope a ing base 2 o o wa d ope a ing base 1 o 2—depo 1, as depic ed in Fig. 4.
The alues associa ed wi h dependency links, as de e mined by he model, can be used o
assess he di ec e ec s o an ac ion o e en on a node’s ulne abili y. Addi ionally, he model
enables iden i ica ion o he indi ec , cumula i e and complex adap i e sys em e ec s on he
capabili ies and dependencies o dependen nodes. I may be he complex adap i e sys em
ha in he ne wo k, a node, is highly depended upon bu i s loss can easily be compensa ed
o by using o he nodes wi h simila capabili ies. The abili y o dis inguish be ween hese
ypes o nodes and he mo e impo an ones—bo h depended on s ongly and ha ing high
consequence alues (iden i ying a lack o esilience in he ne wo k)—allows decision-make s
o ocus on he mos p essing esilience issues in he ne wo k.
5 Conclusions
The simula ion model buil wi h i s easy o unde s and g aphical use in e ace h ough he
Cassand a applica ion can help mili a y commande s and ci ilian supply chain manage s o
ensu e he maximum numbe o success ul ou comes while minimizing a i ion and colla e al
damage / loss. In his way, eadiness is main ained because asse s emain coo dina ed and
execu able a all imes, adjus ing o losses due o damage o e- asking o highe -p io i y
e en s.
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Annals o Ope a ions Resea ch (2025) 347:1163–1192 1185
As discussed, mode n supply chains, epi omized by mili a y supply chains in his ins ance,
a e highly complex, and ou o necessi y o highly cho eog aphed ne wo k sys ems. Ou
dependency model allows decision-make s o immedia ely iden i y he di ec and indi ec
e ec s o changes o he supply chain, whe he planned by he decision-make o caused by
ex e nal e en s and ac ions. Th ough he complex adap i e sys ems and Cassand a applica-
ion, he in eg a ed planning and analysis capabili y o ou model can p o ide decision-make s
wi h si ua ional awa eness and isibili y, enabling hem o adap and keep he supply chain
ope a ional h oughou a mission. The abili y o model ne wo ks om di e en le els o
he supply chain (s a egic, ac ical and ope a ional) wi hin he same ep esen a ion ensu es
ha he e ec s o ac ions and e en s a e p opaga ed quickly ac oss he supply chain and he
command-and-con ol chain, suppo ing e icien acking and op ion gene a ion. These wo
combined capabili ies may enable decision-make s o ensu e a con inuous low o supplies o
on line uni s. I u he allows quick esponses o mission changes and an inc eased empo
o ope a ions. We belie e ha he abili y o mine in o ma ion om mul iple da a sou ces and
use hem in o a cohesi e model mo e easily p o ides a le el o si ua ional awa eness no p e-
iously a ailable in o he models. While he analysis capabili y adds alue, when asked, i is
he abili y o iew he comple e supply chain wi h all i s di ec and indi ec dependencies ha
he decision-make s may ind he mos use ul. F equen ly, indi ec dependencies a e hidden
ha lead o a lack o esilience in he supply chain ha hwa s e en expe ienced planne s.
The app oach we o e gi es decision-make s a way o make hese hidden dependencies mo e
explici .
In ou iew, he model will be able o educe he gene a ion imes o usable supply chain
models om days o hou s. None heless, i is he abili y o educe he p ojec ed manpowe
needed o main ain and upda e he supply chain model ha may p o ide he g ea es bene i s o
supply chain planne s. Fo example, he logis ics J4 planning cell o an ai ope a ions cen e
usually has a s a o i e pe sonnel. The use o he da a mining a chi ec u e may esul in a
educ ion o he numbe o s a equi ed o da a managemen . This signi ican ly inc eases
he numbe o s a ocusing on he ac ual unc ion o he logis ics cell. Thus, p oblems
can be iden i ied soone , and mo e op ions de eloped and analyzed. Using his ype o and
analyzing a whole-sys em ne wo k supply chain, mission plans will ha e a g ea e p obabili y
o execu ing success ully, hus ensu ing he con inuous deli e y o logis ics ma e ials.
Fi ms pa icipa e di ec ly o indi ec ly in global supply chains and a e embedded in he
b oade in e na ional ade sys em. They mus abide by in e na ional ade ules and use he
exis ing in as uc u e. As a esul , e e y p ac i ione , whe he in he p i a e o public sec o ,
should be in e es ed in he ac o s unde pinning he esilience o he in e na ional supply
chain sys em. Supply chain dis up ions a e becoming mo e equen (Lopez and Ishizaka,
2019) and end o lead o an excessi e ise in cos s, s ock-ou , delays, and inabili y o se e
clien demand, in addi ion o he i m’s loss o ma ke posi ion. Unde he Schumpe e ian
iewpoin (Vanpoucke e al., 2014), p ese ing compe i i e ad an age h ough supply chain
esilience in a shi ing, unp edic able en i onmen is challenging and equi es supply chains
o con inuously econ igu e esou ces o i luc ua ing si ua ions.
Mode n supply chains, especially mili a y supply chains, a e highly complex, s ongly
cho eog aphed ne wo k sys ems and hei esilience mus ma ch hei s eng h i hey a e o
su i e and h i e. Resilience equi es wo hings—unde s anding wha he p oblem is/could
be and hen being able o sol e i o plan o i . I is a gued ha a esilien i m imp o es i s
compe i i e posi ion and he esponsi e capabili y o i s supply chain (Lopez and Ishizaka,
2019
). The aim o he model ou lined in his pape was o de elop a dynamic, whole-sys em
ne wo k model ha uses he complex adap i e sys em Cassand a applica ion o p o ide
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1186 Annals o Ope a ions Resea ch (2025) 347:1163–1192
imely, accu a e, upda able and scalable in o ma ion o mili a y and ci ilian planne s and
decision-make s a all supply chain le els. Ou model unde sco es he p e ailing assump ion
ha supply chain esilience will unde go impo an modi ica ions ollowing he COVID-19
pandemic (Blessley & Mudambi, 2022; Mena e al., 2022). P ac i ione s mus ecognize
he de eloping ends o implemen measu es o s ay compe i i e in u u e supply chain
dis up ion scena ios. The equi ed ou come in any supply chain dis up ion scena io—in u -
bulen , ola ile and ha sh condi ions, whe he because o con lic , peacekeeping o disas e
elie —is main aining a con inuous supply. Ou sys em, de eloped using supply chain ne -
wo k esilience p inciples, ul ills he equi emen o con inuous supply by p o iding ision,
acking, and op ions o decision-making, acili a ing bo h unde s anding o he p oblem and
imely, app op ia e esolu ion.
Ou model is a gene ic one and can easily be adap ed o any si ua ion in which he e a e
in e dependen ne wo ks ac oss which he di ec and indi ec e ec s o ac ions and e en s
need o be analyzed. Ou model akes in o accoun he complex adap i e sys em in supply
chains whe e he e a e di e en ne wo ks o p oduce s, anspo a ion and s o age g oups,
and consume s who need he ma e ials o suppo hei mission objec i es and asks. While
he mili a y con ex o hese supply chains means hey ope a e in a c i ical and ola ile
en i onmen , all supply chains, e en ci ilian ones, could p o i om he capi aliza ion o
success ul ou comes while cu ailing ma ginal loss and seconda y damage. A dependency
ne wo k me hodology aids in p ese ing compe ences in ad e se en i onmen s o wha e e
so by keeping esou ces synch onized and execu able a all imes and ine- uning o losses
o e- asking o highe -p io i y e en s.
E alua ing ne wo ks in e ms o hei consequence alue allows us o be e unde s and
hei ulne abili ies. In addi ion o examining nodes in e ms o how many o he nodes depend
on hem di ec ly o indi ec ly, his model also allows planne s o examine how di icul i
would be o ou e a ound a node i i was incapaci a ed and ocus hei e o s on nodes who’s
esponsibili ies canno be assumed by o he nodes in an eme gency. Once implemen ed, he
immedia e bene i is a g aphical use in e ace on -end, allowing he isualiza ion o he
ens o housands o nodes and he housands o ela ionships. Whils he e analysis was
he p ima y goal, he g aphical p esen a ion p o ided by he modeling enables all decision-
make s, i espec i e o ole o loca ion, o ha e access o and see he same in o ma ion.
Visualizing an impo an node and i s place in a gi en con ex alongside i s dependencies
and linkages wi h o he nodes p esen s a use ul holis ic image o he bigge pic u e. A pu ely
ma hema ical model wi h equa ions, ables and so on does no enable people o isualize
he sys em as a unc ioning cohe en ne wo k. Rep esen ing his in o ma ion wi h icons is
a mo e in ui i e way o p o iding in o ma ion. Because o he explici links wi h he da a-
mining a chi ec u e, which is eeding he da a di ec ly in o he model, he need o manual
upda ing is elimina ed. As such, he model p o ides he co e ea u es o supply chain ne wo k
esilience and supply chain esiliency (adap a ion, coe olu ion, lea ning, and eme gence), all
in luenced by he landscape, i s uggedness and dimensionali y (Table 1).
Lea ning om high impac dis up ions mus ake in o accoun con ex ual ac o s, as
esponses o new high impac dis up ions may equi e a mo e c ea i e and es uc u ed
app oach (Si mon e al., 2007). Fo low impac dis up ions, majo econ igu a ion may no
be necessa y, bu high impac dis up ions equi e signi ican econ igu a ion. Fo supply
chains o become bo h esilien and inno a i e, hei capaci y o manage esou ces e ec-
i ely and deal wi h isk is key. Ou model enables decision-make s o a ec nodes in a
supply chain ne wo k in eal ime di ec ly by dealing wi h hei ulne abili ies and indi ec ly
by ci cum en ing hei dependencies. This inco po a ion o dependency me ada a abou he
s eng h and na u e o connec ions di e en ia es ou model om o he app oaches ha only
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