Logoza , Kla dij
A icle
The ole o A i icial In elligence in Supply Chain
Managemen : A sys ema ic Li e a u e Re iew
ENTRENOVA - ENTe p ise REsea ch InNOVA ion
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Sugges ed Ci a ion: Logoza , Kla dij (2025) : The ole o A i icial In elligence in Supply Chain
Managemen : A sys ema ic Li e a u e Re iew, ENTRENOVA - ENTe p ise REsea ch InNOVA ion, ISSN
2706-4735, IRENET - Socie y o Ad ancing Inno a ion and Resea ch in Economy, Zag eb, Vol. 10,
Iss. 1, pp. 328-337,
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Vol. 10 No. 1
The ole o A i icial In elligence in Supply
Chain Managemen : A sys ema ic Li e a u e
Re iew
Kla dij Logoža
Uni e si y o Ma ibo , Facul y o Economics and Business, Slo enia
Abs ac
As he global business landscape con inues o e ol e, he in eg a ion o ad anced
echnologies has become impe a i e o enhancing e iciency and compe i i eness.
This pape explo es he mul i ace ed ole o A i icial In elligence (AI) in e olu ionizing
supply chain managemen (SCM). The adi ional supply chain pa adigm is being
eshaped by AI-d i en solu ions, p esen ing oppo uni ies o op imiza ion, agili y, and
esilience. The au ho conduc ed a sys ema ic li e a u e e iew e alua ion o he
published li e a u e om pee - e iewed jou nals in he majo da abases Scopus and
Web o Science. The analysis o li e a u e is a equency analysis o he li e a u e by
conside ing he yea o publica ions, he con ibu ion o leading jou nals and
publishe s, and he me hodology adop ed and he con en analysis o li e a u e. The
au ho ’s indings om he li e a u e e eal ha key AI applica ions in supply chain
managemen , such as demand o ecas ing, in en o y managemen , logis ics
op imiza ion, and isk mi iga ion enable o ganiza ions o make in o med decisions,
educe o ecas ing e o s, and op imize in en o y le els, ul ima ely imp o ing o e all
supply chain e iciency.
Keywo ds: Supply Chain Managemen , supply chain, A i icial In elligence,
JEL classi ica ion: M11, M19, O31
Pape ype: Resea ch a icle
Recei ed: 15 Decembe 2023
Accep ed: 28 May 2024
DOI: 10.54820/en eno a-2024-0027
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Vol. 10 No. 1
In oduc ion
O ganiza ional success depends hea ily on supply chains, and dis up ions in hese
chains can ha e se ious epe cussions. Exogenous shocks ha e p o ound e ec s ha
go beyond ou p io expe iences and change he en i onmen in which en e p ises
compe e (Zamani e al., 2022). Dis up ions can subs an ially in luence business
pe o mance in oday's supply chains since hey ope a e in a mo e compe i i e and
unce ain en i onmen (Azadegan e al., 2020). Acciden s (S ecke & Kuma , 2009),
na u al disas e s as well as man-made ones (Ellu u e al., 2019), such as he global
inancial c isis o 2008 and B exi (Belhadi e al., 2022a), he loss o essen ial supplie s
(Ponoma o & Holcomb, 2009), and many o he si ua ions can esul in such
dis up ions.
Businesses ypically c ea e business con inui y plans combined wi h isk
managemen measu es o mi iga e agains dis up ions o handle such issues
(Azadegan e al., 2020). Fo adi ional businesses o compe e in he age o he digi al
economy, company ope a ions mus be digi alized (Weill & Woe ne , 2018).
Technologies like In e ne o Things (IoT), AI, blockchain, and da a analy ics ha e
gained p ominence in ecen yea s. The adop ion o IoT, blockchain, cloud
compu ing, da a analy ics, and a i icial in elligence (AI), along wi h he g ow h and
ma u i y o pe inen digi al skills and capabili ies, a e c ucial in his ega d o he
digi al ans o ma ion o businesses (Ak e e al., 2022). Resea ch has demons a ed
ha ad anced echnologies, such as a i icial in elligence (AI) among o he s, a e
essen ial o ensu ing business con inui y, pa icula ly in he e en o ex e nal shocks
(Papadopoulos e al., 2020). Today's supply chains a e s eng hened by senso s and
ac ua o s like RFIDs, GPS and POS, ags, and o he sma de ices, all o which
cons an ly send and ecei e da a (Fosso Wamba e al., 2018). As a esul , AI can be
used o de elop p oac i e s a egies o p edic ing he likelihood o isks occu ing and
hei impac (Ba yannis e al., 2019), and o educe he nega i e e ec s and assis
decision-make s in handling di icul si ua ions.
Blockchain, AI, and IoT ha e eme ged as e icien means o enhance he esilience
o supply chains. Ad anced echnologies ha e e olu ionized supply chain
managemen by p o iding ools and solu ions o enhance isibili y, op imize
ope a ions, and mi iga e isks. In es ing in ad anced echnologies o e s o ganiza ions
a ange o po en ial bene i s o supply chain esilience. These bene i s include
inc eased isibili y in o supply chain ope a ions, as e esponse imes o dis up ions,
cos educ ions h ough au oma ion, and imp o ed decision-making capabili ies
(Wagne & Bode, 2008). Quan i ying he impac o echnology on supply chain
esilience is essen ial o o ganiza ions o assess he e ec i eness o hei in es men s.
Key pe o mance indica o s and me ics, such as on- ime deli e y a es, in en o y
u no e , and demand o ecas accu acy, can p o ide insigh s in o he angible
bene i s o echnology adop ion (Sa kis e al., 2020).
Applica ion o A i icial In elligence in he supply chain
AI is de ined as "a sys em's abili y o in e p e ex e nal da a co ec ly, o lea n om
such da a, and o use hose lea nings o achie e speci ic goals and asks h ough
lexible adap a ion" (Haenlein & Kaplan, 2019) in he con ex o da a analysis. AI e e s
o a sys em's capaci y o lea n by examining he da a om he ex e nal en i onmen
and using ha knowledge o modi y exis ing plans o c ea e new ones in esponse o
en i onmen al changes (G o e e al., 2022). This comp ises me hods and algo i hms
ha allow us o in e knowledge om inpu da a, whe he we know he ou pu s' inal
o ms (Ba yannis e al., 2019; Rod iguez-Espindola e al., 2020). In e ms o concep and
oppo uni y de elopmen , cu en AI sys ems a e excellen a ge ing o e he
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in o ma ion p ocessing limi a ions o humans. Deep neu al ne wo ks, which need and
can analyse eno mous amoun s o da a, a e cu en ly a majo componen o AI
sys ems (Ng, 2017). Wi h his capabili y, we see a e i able abundance o AI sys ems
ha can assis people in coming up wi h concep s, oppo uni ies, and solu ion
s a egies by analysing a lo mo e da a han a pe son can handle and iden i ying
in iguing opics o esea ch.
AI is ound o be he mos impac ul applica ion in manu ac u ing in his cen u y
and ypically le e ages cen alized compu ing and da a s o age in as uc u e o
s udy con inuous da a lows o eal- ime decision-making (Nasa e al., 2020).
Howe e , complex conce ns, including da a secu i y and in e ope abili y, ad e sa ial
a acks, mo ali y, and e hics, a e aced by AI sys ems (Awad e al., 2018). AI is iewed
as a "black box" o a g ea e o lesse ex en , and dis us su ounds he applica ion o
i s analysis esul s o c ucial decision-making. Fo he pas 20 yea s, nume ous i ms
ha e a emp ed o digi ize hei business ope a ions, and mo e ecen ly, he e m
"Indus y 4.0" has become a business buzzwo d (Wollschlaege e al., 2017). Since i s
incep ion, AI has been acknowledged as a key echnology ha acili a es
communica ion be ween machines and de ices (Guzman & Lewis, 2020). Due o he
complexi y o he jobs in ol ed in he supply chain, AI can s eamline ope a ions by
p ocessing eno mous olumes o da a while also sol ing p oblems mo e quickly and
accu a ely (Schniede jans e al., 2020). AI has he abili y o help supply chain
manage s make quick, in o med decisions ha can help hem o esee issues.
Too ajipou e al. (2021) and Fosso Wamba e al. (2021) ound ha p oac i e AI sys ems
imp o e se ice quali y and please consume s by making on- ime, undamaged
deli e ies. E e y minu e and e e y mile coun in he supply chain, and AI employs
algo i hms ha can sa e ime and cos by op imizing ou es and deli e y (Wen e al.,
2018).
The usage o AI o isk managemen as well as c ea ing and main aining esilience
in supply chains, is cu en ly o inc easing in e es (Ba yannis e al., 2019; Modgil e al.,
2022; Sande s, 2016). The e a e s ill se e al a eas ha lack unde s anding, despi e his
a en ion. While echnology has been examined a a ela i ely abs ac le el, a ecen
majo e iew o supply chain esilience concen a ed on esea ch conduc ed o e
he pas 20 yea s, de ailing he ypes o dis up ions, hei impac on he supply chain,
and eco e y s a egies o mi iga ing hese (Ka saliaki e al., 2022). O he esea che s
ha e concen a ed on iden i ying and classi ying he a ious AI isk managemen
app oaches (Ba yannis e al., 2019; Hamdi e al., 2018) and e alua ing he a ious
supply chain esilience echniques (Belhadi e al., 2022a). In bo h ins ances,
academics appea o be less in e es ed in how AI impac s esilience and he a ious
s ages o isk managemen ( eadiness, esponse, eco e y, and adap abili y). O he s
ha e disco e ed ha AI os e s he g ow h o dynamic skills, which can in u n help he
company's supply chain esilience (Modgil e al., 2022).
When mul idimensional da a a e engaged in dynamic scena ios like supply chain
dis up ion, AI as a echnology has he capaci y o analyse and assess al e na i es. As
in o ma ion becomes inc easingly a ailable h oughou global supply chains, so do
he expec a ions o AI’s use o his in o ma ion (Sande s e al., 2019). supply chains’
e iciency and p oduc i i y a e se o inc ease signi ican ly due o he use o AI o e
he nex decade. In he supply chain spec um, he in oduc ion o AI implemen a ions
adds alue by acili a ing supply ne wo k design and econ igu a ion h ough e ing
and classi ying po en ial s akeholde s (e.g., al e na i e supplie s), acili ies, and
echnologies (Go indan e al., 2017); analysing big da a o explaining and assessing
isks hus p omo ing supply chain esilience (Papadopoulos e al., 2017); suppo ing
nea eal- ime, au oma ed and op imal decision-making ia analysing la ge amoun s
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o da a om di e se sou ces (e.g., web, social media, in o ma ion sys ems o in ol ed
supply chain ac o s) o add ess unce ain y and demand ola ili y (Ba yannis e al.,
2019); and enabling lea ning, easoning and sel -co ec ion o supply chain
ope a ions whils p omo ing alida ion o in o ma ion o pa icula pu poses such as
con ac ing (Shen e al., 2019). The in oduc ion o AI in supply chain managemen
acili a es he o ches a ion and op imiza ion o ne wo k ope a ions ia: e ealing
complex beha iou al pa e ns h ough mul i ace ed analysis o da a (e.g.,
classi ica ion, op imiza ion, clus e ing); pe cei ing he su ounding en i onmen o
in o m au onomous ac i i ies and p oac i ely add ess eme ging pe o mance and
quali y issues; in o ming supply chain design, simula ion and planning; and enabling
nego ia ion-based collabo a i e modelling (Too ajipou e al., 2021).
Me hodology
This pape will conduc a sys ema ic li e a u e e iew (SRL) on he ole o AI in supply
chain managemen . Supply chain managemen is inc easingly c ucial in oday's
dynamic business landscape. This pape explo es how AI can be u ilised o enhance
supply chain managemen . We shed ligh on echnology's pi o al ole in ensu ing
supply chain obus ness h ough SLR. The pape aims o examine how supply chain
esilience can be inc eased by adop ing AI. Fo his pu pose, we de ined SLR on
inc easing he esilience o he supply chain by adop ing AI based on he ollowing
esea ch ques ions:
RQ1: In wha ways migh he esilience o supply chain bene i om he adop ion
o AI?
RQ2: Wha a e he challenges o implemen ing AI o inc ease supply chain
esilience?
Topic agmen a ion and connec ions o o he ields g ow as managemen esea ch
expands in olume and scope, and because o ha , T an ield e al. (2003) in oduced
he managemen ield o a ool known as SLR. An SLR o e s a anspa en , unbiased,
and comp ehensi e summa y o he body o knowledge cu en ly a ailable in ela ion
o a esea ch ques ion (Tsa na e al., 2014), and se e as a bene icial ins umen o
managemen esea ch (Pa i & Lo usso, 2018; Siddaway e al., 2019).
Based on AI in he supply chain, we conduc ed he s udy using SLR o examine ou
esea ch ques ions. We ollowed he s eps p esc ibed by SLR p ocesses, which a e
ou lined by Go indan and Hasanagic (2018) and Ma hiyazhagan e al. (2021). SLR
ocuses on he supply chain's cu en s a e and o ganiza ions' challenges in enhancing
esilience. The pape explo es he ole o AI in imp o ing in en o y managemen ,
enhancing supply chain isibili y, and imp o ing isk assessmen . Addi ionally, he
e iew add esses he bene i s and challenges o implemen ing AI in he supply chain.
Da abase
The ini ial s age o he bibliog aphic analysis is da abase c ea ion. Da abases a e a
use ul ool o scien ome ic analysis, and he mos comp ehensi e index o indexed
jou nals was c ea ed using he Scopus and Web o Science (WoS) da abases. WoS
con ains housands o pee - e iewed social sciences, echnology, and medicine
publica ions, Scopus da abase was chosen as well since i p o ides ho ough
bibliog aphic da a and high-quali y, dependable co e age (Mongeon & Paul-Hus,
2016). A e conduc ing a da abase sea ch in June 2023, 277 a icles om he WoS
da abase and 804 a icles om he Scopus da abase esul ed in he p elimina y esul s
o he a icle sea ch, con e ence pape s we e omi ed. Di e en keywo ds we e
chosen as a sea ch echnique o disco e simila a icles because his s udy aims o
unde ake a bibliog aphic analysis o scien i ic a icles. Two g oups o wide keywo ds
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we e es ablished o his s udy o a oid es ic ing he desi ed pape s while
simul aneously emo ing undesi ed esul s (Cunha e al., 2019).:
• G oup 1: AI- ela ed documen s o be selec ed: “a i icial in elligence (AI)”.
• G oup 2: supply chain managemen - ela ed documen s o be selec ed:
“supply chain”, “logis ics”.
• A e ex ac ing he a icles om he wo da abases, WoS and Scopus, he
sea ch was limi ed o pee - e iewed a icles in English. The publica ion pe iod
was no limi ed and ensu ed a comp ehensi e sea ch; duplica e a icles we e
emo ed. By e iewing he i les and abs ac s, 2412 we e selec ed and
a chi ed o u he analysis. A icles we e hen e iewed o ensu e hey
ma ched he keywo d sea ch, abs ac s we e assessed based on he esea ch
objec i e, and duplica es we e emo ed. The o al numbe o a icles was
educed o 1241 o be analysed in he nex s age.
We conduc ed a s uc u ed Boolean- ype keywo d sea ch in he WoS and Scopus
da abases (Ai azidou e al., 2016). The Boolean keywo d sea ch was conduc ed using
he ollowing combina ion in he “A icle i le, Abs ac , Keywo ds” ield: (a i icial
in elligence) AND (supply chain OR logis ics). The sea ch was u he limi ed o jou nal
a icles w i en in English. The ime ho izon o publica ions was le un es ic ed.
Figu e 1
Summa y o he S eps o SLR o AI in he Supply Chain
Scopus
Da abase
WoS
Da abase
Iden i ica ion
Findings om he
da abase sea ch
n = 338
Sc eening
Eligibili y
Included
Findings om he
da abase sea ch
n = 126
Duplica ed en ies
n = 6
Duplica e eco ds emo ed
n = 458
Dele ed subsc ip ion
n = 209
A icle i les and abs ac s
assessed o eligibili y
n = 249
Final collec ion o a icles
n = 32
Sou ce: Au ho ’s illus a ion
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Figu e 1 summa izes he s eps in his sec ion using he p e e en ial epo ed i ems o
sys ema ic e iews and me a-analysis (PRISMA) p o ided by Mohe e al. (2009). By
sea ching o hese e ms in he pape ’s i le, keywo ds, and abs ac using he
da abases’ sea ch ea u e, 464 pape s we e e ie ed om he wo da abases. This
keywo d sea ch wo k was done on July 9, 2023, and conside ed he ull pape
publica ion yea up o 2023. In he second s age, inclusion and exclusion c i e ia we e
applied o ge he mos ele an pape s acco ding o ou e iew heme shown as he
sc eening s age in Figu e 1. Based on he language o he pape , he exclusion o
duplica es, he inclusion o pee - e iewed jou nal a icles alone, open access, and
he inclusion o publica ions based on he subjec in wo da abases (Scopus and
WoS), we ob ained 249 pape s. In he hi d s ep, we assessed i he comple e a icle
ocuses on how AI impac s supply chain managemen . A e he 249 pape s we e
analysed, 32 a icles we e selec ed o he inal s udy.
Con en analysis
A esea ch echnique based on obse a ions called con en analysis is used o
objec i ely assess he con en o w i en ma e ials. By iden i ying he main heme o a
ex 's con en s and o ganizing, ca ego izing, and compa ing ex s, con en analysis is
a echnique ha can aid in he e alua ion o la ge amoun s o da a in a s uc u ed
and sys ema ic manne (Kazemi e al., 2019). This echnique also esul s in he
in e ence o an o e all esul (Özyu & Özyu , 2015).
This pape conside s he applica ions o AI in he supply chain. I aims o p o ide a
mo e accu a e and in eg a ed unde s anding o AI and i s e ec s on supply chain
managemen .
Resul s
Bene i s o he adop ion o AI o Supply Chain Managemen
The main bene i s o adop ing AI o supply chain managemen a e enhanced supply
chain isibili y, be e isk assessmen , as e esponse imes, cos educ ions, and
imp o ed decision-making capabili ies.
G ounded in o ganiza ional in o ma ion p ocessing heo y, Belhadi e al. (2021a)
ound ha du ing dis up i e and unexpec ed e en s, he supply chain could main ain
o e en enhance he supply chain pe o mance h ough in o ma ion p ocessing and
adap a ion capabili ies p o ided by AI echniques. When he supply chain is dis up ed
o an ex ended pe iod, echnology like AI can be used by i ms o imp o e supply
chain esilience by synch onizing manu ac u ing and in en o y planning. AI can play
a c i ical ole in balancing demand and supply o minimize he e ec s o dis up ion
unde ex emely unce ain condi ions. (Modgil e al., 2022).
AI o e s he chance o supply chains o achie e g ea e le els o us and
anspa ency, which is he key d i e o making a supply chain esilien enough o
handle and h i e in unce ain e en s; as in e ne pene a ion ises and AI is used,
supply chains a e becoming in elligen wi h li le supe ision equi ed and in addi ion,
a supply chain wi h AI capabili ies can aid wi h speedy decision-making as well as
planning o he supply chain's con inui y unde a ange o di e en condi ions (Singh
e al., 2023).
Wi h hei empi ical s udy o 318 companies, Wang & Pan (2022) con i med ha he
adop ion o AI echnology posi i ely impac s he elas ici y and pe o mance o he
supply chain, also con i ming ha implemen ing new echnology can gi e businesses
a long- e m compe i i e ad an age, as well as supplying esh pe spec i es and a
ounda ion o u he s udy on implemen ing AI.
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Challenges o implemen ing AI in Supply Chain Managemen
AI has p o en e ec i e ool o educe in o ma ion asymme y and inc ease
anspa ency ac oss supply chains (Bumblauskas e al., 2020; Ebinge & Omondi, 2020).
Howe e , mul iple, and di e si ied da a a che ypes o en exis in end- o-end supply
chains. Key challenges in implemen ing hese echnologies a e o en ela ed o limi ed
p ocessing capabili ies o uns uc u ed, incomple e, and some imes inaccu a e da a
(Choi e al., 2020). The challenges o AI implemen a ion comp ise echnical, e hical,
legal, manage ial, and socio-economic conside a ions.
A majo echnical challenge o adop ing AI in business ope a ions ela es o he
a ailabili y and use o da a. Da a a ailable o i ms is o en uns uc u ed and di icul
o sha e be ween he supply chain membe s. S uc u ing his da a can be e y cos ly.
Fu he mo e, he da a used o a speci ic case migh no be gene alizable (Cub ic,
2020). Fo example, p oblems can a ise by (small) da ase s, which do no accu a ely
e lec eali y, o by o e i ing he AI algo i hm o he aining da a se . On he o he
end, a lack o aining da a may lead o educed pe o mance o he elabo a ed AI
algo i hms (Cub ic, 2020). In addi ion, a lack o s anda diza ion o in o ma ion can
lead o di icul ies in choosing he igh AI solu ion. The e is a end owa d
indi idualizing companies’ digi al solu ions ia in e nal da a a chi ec u e (Ebinge &
Omondi, 2020).
Ano he challenge a ising om he use o da a o AI is he possibili y o p i acy
igh s in ingemen (Leone, 2017). Fu he mo e, p ojec da ase s o en con ain
con iden ial in o ma ion, leading o signi ican echnical ba ie s o adop ing AI-d i en
solu ions in indus ial applica ions. Addi ionally, he applica ion o AI may impose
social p oblems wi h e hnical and acial p o iling, hus aising p i acy conce ns
(Dau e gne, 2020). Fu he mo e, due o he ea ly de elopmen and applica ion
s age, many AI-based solu ions a e demons a ed only in pilo / ial demons a o s and
o e limi ed p ac ical solu ions (Ebinge & Omondi, 2020). Acco dingly, he e is o en
a lack o manage ial awa eness abou he implemen a ion bene i s o AI in
co po a ions (Cub ic, 2020).
Las ly, despi e he bene i s s emming om he implemen a ion o AI in an indus ial
con ex , a ange o signi ican social isks is in ol ed (Di Vaio e al., 2020). As
echnologies like au onomous d i ing a e de eloping as , unemploymen issues o
p o essional uck d i e s migh a ise in he long e m (Sande s e al., 2019). The
possibili y o AI-d i en solu ions eplacing human labou will exace ba e social and
echnical enginee ing ensions (Cama éna, 2020).
Conclusion
This pape explo es he i al ole o AI in enhancing supply chain managemen . In an
inc easingly complex and ola ile global landscape, supply chains ace a ious
dis up ions ha can signi ican ly impac business ope a ions. To mi iga e hese
challenges, o ganiza ions a e u ning o ad anced echnologies o bols e hei supply
chain esilience.
This pape p o ides an in-dep h analysis o he bene i s and challenges ela ed o
adop ing ad anced echnologies in supply chain managemen . The pape highligh s
he ole o AI in enhancing supply chain managemen , comp ehensi ely e iews he
exis ing li e a u e on he opic, and iden i ies he challenges and oppo uni ies
associa ed wi h implemen ing hese echnologies. We explain how he echnology
wo ks, i s ele ance o supply chain ope a ions, and he po en ial bene i s i can o e
in e ms o enhancing esilience.
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ENTRENOVA - ENTe p ise REsea ch InNOVA ion
Vol. 10 No. 1
The main bene i s o AI o supply chain managemen a e enhanced supply chain
isibili y, be e isk assessmen , as e esponse imes, cos educ ions, and imp o ed
decision-making capabili ies. Implemen ing AI can be challenging o o ganiza ions,
as i equi es signi ican in es men , expe ise, and a willingness o change. This pape
highligh s he o ganiza ional, echnical, ope a ional, and e hical challenges
connec ed wi h he adop ion o ad anced echnologies.
Re e ences
1. Ai azidou, E., Tsolakis, N., Iako ou, E., & Vlachos, D. (2016). The eme ging ole o wa e
oo p in in supply chain managemen : A c i ical li e a u e syn hesis and a hie a chical
decision-making amewo k. Jou nal o Cleane P oduc ion, 137, 1018-1037.
2. Ak e , S., Michael, K., Uddin, M. R., McCa hy, G., & Rahman, M. (2022). T ans o ming business
using digi al inno a ions: he applica ion o AI, blockchain, cloud and da a analy ics.
Annals o Ope a ions Resea ch, 308(1), 7-39.
3. Awad, E., Dsouza, S., Kim, R., Schulz, J., Hen ich, J., Sha i , A., Bonne on, J.-F., & Rahwan, I.
(2018). The Mo al Machine expe imen . Na u e, 563(7729), 59-64.
4. Azadegan, A., Syed, T. A., Blome, C., & Tajeddini, K. (2020). Supply chain in ol emen in
business con inui y managemen : e ec s on epu a ional and ope a ional damage
con ainmen om supply chain dis up ions. Supply Chain Managemen : An In e na ional
Jou nal, 25(6), 747-772.
5. Ba yannis, G., Validi, S., Dani, S., & An oniou, G. (2019). Supply chain isk managemen and
a i icial in elligence: S a e o he a and u u e esea ch di ec ions. In e na ional Jou nal
o P oduc ion Resea ch, 57(7), 2179–2202.
6. Belhadi, A., Mani, V., Kamble, S.S., Khan, S. A. R., & Ve ma, S. (2021). A i icial in elligence-
d i en inno a ion o enhancing supply chain esilience and pe o mance unde he e ec
o supply chain dynamism: an empi ical in es iga ion. Annals o Ope a ions Resea ch.
7. Belhadi, A., Kamble, S., Fosso Wamba, S., & Quei oz, M. M. (2022). Building supply-chain
esilience: an a i icial in elligence-based echnique and decision-making amewo k.
In e na ional Jou nal o P oduc ion Resea ch, 60(14), 4487-4507.
8. Bumblauskas, D., Mann, A., Dugan, B., & Ri me , J. (2020). A blockchain use case in ood
dis ibu ion: Do you know whe e you ood has been? In e na ional Jou nal o In o ma ion
Managemen , 52, 102008.
9. Cama éna, S. (2020). A i icial in elligence in he design o he ansi ions o sus ainable ood
sys ems. Jou nal o Cleane P oduc ion, 271, 122574.
10. Choi, T.-M., Guo, S., & Luo, S. (2020). When blockchain mee s social-media: Will he esul
bene i social media analy ics o supply chain ope a ions managemen ? T anspo a ion
Resea ch Pa E: Logis ics and T anspo a ion Re iew, 135, 101860.
11. Cub ic, M. (2020). D i e s, ba ie s and social conside a ions o AI adop ion in business and
managemen : A e ia y s udy. Technology in Socie y, 62, 101257.
12. Cunha, L., Ce yno, P., & Lei as, A. (2019). Social supply chain isk managemen : A axonomy,
a amewo k and a esea ch agenda. Jou nal o Cleane P oduc ion, 220, 1101-1110.
13. Dau e gne, P. (2022). Is a i icial in elligence g eening global supply chains? Exposing he
poli ical economy o en i onmen al cos s. Re iew o In e na ional Poli ical Economy, 29(3),
696-718.
14. Di Vaio, A., Boccia, F., Land iani, L., & Palladino, R. (2020). A i icial In elligence in he Ag i-
Food Sys em: Re hinking Sus ainable Business Models in he COVID-19 Scena io.
Sus ainabili y, 12(12).
15. Ebinge , F., & Omondi, B. (2020). Le e aging Digi al App oaches o T anspa ency in
Sus ainable Supply Chains: A Concep ual Pape . Sus ainabili y, 12(15).
16. Ellu u, S., Gup a, H., Kau , H., & Singh, S. P. (2019). P oac i e and eac i e models o disas e
esilien supply chain. Annals o Ope a ions Resea ch, 283(1), 199-224.
17. Fosso Wamba, S., Bawack, R. E., Gu h ie, C., Quei oz, M. M., & Ca illo, K. D. A. (2021). A e we
p epa ing o a good AI socie y? A bibliome ic e iew and esea ch agenda.
Technological Fo ecas ing and Social Change, 164, 120482.
