Lu, Huie; Shaha udin, Muhammad Shabi
A icle
Role o digi al ans o ma ion o sus ainable compe i i e
ad an age o SMEs: a sys ema ic li e a u e e iew
Cogen Business & Managemen
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Role o digi al ans o ma ion o sus ainable
compe i i e ad an age o SMEs: a sys ema ic
li e a u e e iew
Huie Lu & Muhammad Shabi Shaha udin
To ci e his a icle: Huie Lu & Muhammad Shabi Shaha udin (2024) Role o digi al
ans o ma ion o sus ainable compe i i e ad an age o SMEs: a sys ema ic li e a u e e iew,
Cogen Business & Managemen , 11:1, 2419489, DOI: 10.1080/23311975.2024.2419489
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Cogen Business & ManageMen
2024, VoL. 11, no. 1, 2419489
Role o digi al ans o ma ion o sus ainable compe i i e ad an age
o SMEs: a sys ema ic li e a u e e iew
Huie Lua,b and Muhammad Shabi Shaha udina
aschool o Managemen , uni e si i sains Malaysia, Penang, Malaysia; bschool o economic and ade Managemen , anhui
Voca ional College o De ense echnology, Lu’an, China
ABSTRACT
The digi al e olu ion has undamen ally changed how businesses c ea e alue. Small
and medium en e p ises (SMEs), wi h hei limi ed esou ces, mus adap o his new
landscape o main ain a compe i i e edge h ough digi al ans o ma ion (DT). This
pape explo es how SMEs can build sus ainable compe i i e ad an age (SCA) ia DT.
Using he WOS Co e Collec ion da abase, we conduc ed a comp ehensi e e iew and
bibliome ic analysis, examining 1,856 a icles on SCA, wi h a de ailed ocus on 57 ha
speci ically add ess DT. The indings show ha DT enhances SMEs’ inno a ion and
dynamic capabili ies, helping hem o e come esou ce cons ain s and be e espond
o ma ke shi s. Key digi al echnologies such as big da a, a i icial in elligence, and
digi al pla o ms a e c ucial in d i ing hese esul s. P ac ical insigh s a e also o e ed o
SMEs manage s o ailo digi al s a egies, op imize ope a ions, and build SCA.
1. In oduc ion
Sus ainable compe i i e ad an age (SCA) is c i ical o i ms o h i e and ou pe o m compe i o s o e
he long e m (Du e al., 2024; Wiggins & Rue li, 2002). In oday’s highly compe i i e en i onmen , busi-
nesses a e no longe con en wi h sho - e m gains and a e inc easingly ocused on building endu ing
compe i i e ad an ages (Huang e al., 2015; Ri qi e al., 2024). Howe e , om an economic pe spec i e,
compe i i e ac i i ies may cause p o i abili y and ma ke sha e o eg ess o he mean o e ime, which
can lead o he e osion o a i m’s compe i i e edge (Mau y, 2017; Wiggins & Rue li, 2002). The e o e, how
o sus ain compe i i e ad an age emains a cen al opic in academic discussions, pa icula ly conce ning
how small and medium en e p ises (SMEs) can achie e and main ain such an ad an age in a apidly
changing ma ke .
SMEs play a pi o al ole in bo h de eloped and de eloping economies, d i ing employmen and inno-
a ion (Ghe ghina e al., 2020; Mago & Modiba, 2022). Al hough he c i e ia o de ining SMEs di e
globally, hey a e commonly based on he numbe o employees and business e enue (Mon o o-Sanchez
e al., 2018). While SMEs end o exhibi g ea e agili y and adap abili y o en i onmen al changes, hey
o en ace cons ain s in esou ces and p o essional capaci y (Cos a e al., 2024; T oise e al., 2022). These
challenges p omp SMEs o con inually seek ways o sus ain hei SCA, pa icula ly in he con ex o
digi al ans o ma ion (DT).
Academic pe spec i es on he ela ionship be ween DT and compe i i e ad an age a e di ided. One
iew a gues ha he apid e olu ion o digi al echnologies unde mines he sus ainabili y o compe i i e
ad an age, making SCA empo a y and a e in oday’s complex economic en i onmen (D’A eni e al.,
2010; McG a h, 2013). In con as , ano he pe spec i e sugges s ha digi al echnologies, such as big
da a, digi al pla o ms, and blockchain, enable i ms o build and main ain SCA by imp o ing adap abili y
and pe o mance (Ga maki e al., 2023; K is o e sen e al., 2021; Liu e al., 2023; Sa az e al., 2023). This
© 2024 he au ho (s). Published by in o ma uK Limi ed, ading as aylo & F ancis g oup
CONTACT Muhammad shabi shaha udin [email p o ec ed] school o Managemen , uni e si i sains Malaysia, Penang, 11800, Malaysia
h ps://doi.o g/10.1080/23311975.2024.2419489
his is an open access a icle dis ibu ed unde he e ms o he C ea i e Commons a ibu ion License (h p://c ea i ecommons.o g/licenses/by/4.0/), which
pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed. he e ms on which his a icle has been
published allow he pos ing o he accep ed Manusc ip in a eposi o y by he au ho (s) o wi h hei consen .
ARTICLE HISTORY
Recei ed 21 Augus 2024
Re ised 12 Oc obe 2024
Accep ed 16 Oc obe 2024
KEYWORDS
Small and medium
en e p ises (SMEs);
Sus ainable compe i i e
ad an age; Digi al
ans o ma ion; Digi al
s a egy; Sys ema ic
li e a u e e iew
SUBJECTS
Small business
managemen ; S a egic
managemen ;
Managemen o
echnology & inno a ion
MAnAGEMEnT | RESEARCH ARTICLE
2 H. LU AnD M. S. SHAHARUDIn
iew emphasizes ha digi al capabili ies allow o ganiza ions o seize new oppo uni ies and achie e
supe io ou comes.
ne e heless, he mechanisms linking DT and SCA emain complex and mul i ace ed (Xue e al., 2022).
To add ess his, he i s objec i e o his esea ch is o explo e how DT helps SMEs build and sus ain
SCA in compe i i e en i onmen s.
RQ1: How does DT con ibu e o he de elopmen and sus ainabili y o compe i i e ad an age in SMEs?
The second objec i e is o iden i y speci ic digi al echnologies ha enable SMEs o o e come esou ce
cons ain s and enhance hei SCA in apidly changing ma ke s.
RQ2: Wha speci ic digi al echnologies help SMEs o e come esou ce cons ain s and enhance hei SCA in a
apidly changing ma ke en i onmen ?
The emainde o his pape is o ganized as ollows: Sec ion 2 de ails he esea ch me hodology and
da a p ocessing. Sec ion 3 p esen s he da a analysis and esul s. Sec ion 4 p o ides a discussion, high-
ligh ing new indings, and answe s he esea ch ques ions. Sec ion 5 iden i ies gaps o u u e esea ch.
Finally, Sec ion 6 p esen s he conclusions.
2. Me hodology
To ensu e sys ema ici y and igo in ou li e a u e e iew, we employed he sys ema ic li e a u e e iew (SLR)
me hod. Following he ecommenda ions o K aus e al. (2020) and T an ield e al. (2003), we s uc u ed he
esea ch p ocess in o h ee s ages: planning, ope a ion, and dissemina ion, as illus a ed in Figu e 1.
Figu e 1. he li e a u e e iew p ocess.
COGEnT BUSInESS & MAnAGEMEnT 3
Fi s , in line wi h ou esea ch objec i e o in es iga ing he impac o DT on he SCA o SMEs, we
de eloped he esea ch ques ions, RQ1 and RQ2, and iden i ied ele an da a sou ces and sea ch c i e ia.
In he ope a ion s age, we ex ac ed he li e a u e om he designa ed da abases, sc eened he eligible
s udies, and analyzed he da a using Excel and VOS iewe . Finally, he e iew esul s we e compiled and
dissemina ed in he dissemina ion s age.
2.1. S age 1: Planning he e iew
Accu a e li e a u e da a is undamen al o conduc ing a SLR, as he p ecision o he da a is c i ical
(Wol swinkel e al., 2013; Zhou e al., 2023). A e de ining he esea ch objec i es and ques ions, we
de eloped a sea ch plan ou lining he scope o li e a u e selec ion, as shown in Table 1. We chose he
Web o Science (WOS) Co e Collec ion da abases, which a e widely ecognized by academics o hei
comp ehensi e co e age and high-quali y li e a u e (Chadegani e al., 2013). Following he ecommenda-
ions o K aus e al. (2020), we ocused on pee - e iewed published a icles and e iew a icles, excluding
con e ence p oceedings, books, and o he ma e ials.
Ou sea ch c i e ia included he opic ields ( i le, keywo ds, and abs ac ) and we e es ic ed o
English-language pape s. As shown in Table 1.
2.2. S age 2: Ope a ing he e iew
In his s age, we ca ied ou li e a u e ex ac ion, sc eening, and analysis. Fi s , we sea ched he li e a u e
da abases ollowing he p o ocol es ablished in he p e ious s age. Using ‘sus ainable compe i i e ad an-
age*’ as he opic keywo d, we ini ially selec ed 1935 pape s. Wi h he keywo ds ‘sus ainable compe i i e
ad an age’ AnD ‘SMEs’ OR ‘small and medium en e p ises’, 152 pape s we e iden i ied, and using ‘sus ain-
able compe i i e ad an age*’ AnD ‘digi al ans o ma ion*’ OR ‘digi aliza ion*’ OR ‘digi alisa ion*’ only 61
pape s we e ound.
In he WOS Co e Collec ion da abase, we selec ed ‘Full Reco d and Ci ed Re e ences’ o expo he
pape eco ds in o Excel shee s. A e wa d, we e iewed he documen ypes and excluded book chap-
e s and e ac ed pape s. The sc eened pape da a is shown in Table 2.
We u ilized he bibliome ic so wa e VOS iewe o analyze he li e a u e in his e iew. VOS iewe
sys ema ically examines li e a u e by analyzing keywo ds, au ho s, ins i u ions, jou nals, and o he ele-
an in o ma ion (Hosseini e al., 2018; Shaha udin e al., 2019). I is widely ecognized o i s e ec i e-
ness in isualizing complex ela ionships wi hin la ge se s o academic publica ions (Ki by, 2023). One o
i s key s eng hs is i s abili y o e icien ly handle la ge da ase s, gene a ing isual maps ha clea ly
illus a e clus e s o esea ch opics and collabo a ions.
Table 1. Li e a u e e iew pa ame e s.
Pa ame e Desc ip ion
sea ch da abase Web o science co e collec ion
sea ch ield opic = i le, abs ac , keywo ds, keywo ds plus
sea ch keywo ds ‘sus ainable compe i i e ad an age*’, ‘sus ainable compe i i e ad an age*’ anD ‘sMes*’ oR ‘small and
medium en e p ises*’, ‘sus ainable compe i i e ad an age*’ anD ‘digi al ans o ma ion*’ oR
‘digi aliza ion*’ oR ‘digi alisa ion*’
Language english
Documen ypes a icle and e iew a icle
ime span un il 21s sep embe 2024
Sou ce: au ho ’s elabo a ion.
Table 2. sea ch esul s o he da abase.
opic keywo ds a icle numbe sc eening esul
‘sus ainable compe i i e ad an age*’ 1935 1856
‘sus ainable compe i i e ad an age*’ anD ‘sMes*’ oR ‘small and medium en e p ises*’ 152 149
‘sus ainable compe i i e ad an age*’ anD ‘digi al ans o ma ion*’ oR ‘digi aliza ion*’ oR
‘digi alisa ion*’
61 57
Sou ce: au ho ’s elabo a ion.
4 H. LU AnD M. S. SHAHARUDIn
2.3. S age 3: Dissemina e he e iew
A his s age, we will ca e ully discuss he analysis esul s and p esen ou conclusions. The emaining
sec ions o his pape will showcase ou indings.
3. Resul s
This sec ion p esen s he esul s o he SLR and bibliome ic analysis, including bibliome ic analysis o
li e a u e in he h ee esea ch a eas o SCA, SCA, and DT, SMEs’ SCA.
3.1. Keywo ds analysis o SCA
We u ilized VOS iewe o conduc an au ho keywo d analysis on 1,856 pape s ela ed o SCA, as illus-
a ed in Figu e 2. In his isualiza ion, he size o he node indica es he equency o occu ence o he
keywo d in he li e a u e, he colo o he node ep esen s he change in esea ch ho ness o di e en
keywo ds o e ime, and he hickness o he line e lec s he s eng h o he ela ionship be ween key-
wo ds. Besides SCA, he ou la ges nodes a e ‘compe i i e ad an age’, ‘knowledge managemen ’, ‘inno-
a ion’, and ‘sus ainabili y’, indica ing ha hese a e he dominan esea ch hemes in he li e a u e
analyzed. Compa ed wi h he ela i ely ea ly esea ch on ‘ esou ce-based iew’, ‘knowledge managemen ’,
‘dynamic capabili ies’, and ‘sus ainabili y’, hese ha e become ho opics in ecen yea s. This shows ha
esea ch is inc easingly ocusing on how o achie e SCA h ough inno a ion, knowledge managemen ,
and dynamic capabili ies.
Addi ionally, se e al opics in he uppe pa o he image, such as ‘digi al ans o ma ion’, ‘Indus y
4.0’, ‘open inno a ion’, ‘SMEs’, and ‘business model inno a ion’, a e displayed in yellow, indica ing ha in
ecen yea s, esea ch has inc easingly ocused on he impac o DT on main aining compe i i e ad an-
age. A he same ime, he e is g owing schola ly a en ion on how SMEs can enhance hei compe i i e
Figu e 2. sCa au ho keywo ds o e lay isualiza ion bibliog aphic coupling.
COGEnT BUSInESS & MAnAGEMEnT 5
ad an age h ough DT and inno a ion. Ea ly heo ies, such as he esou ce-based iew, con inue o se e
as ounda ional amewo ks o hese s udies.
3.2. Keywo ds analysis o SMEs’ SCA
Gi en he limi ed esea ch on he SCA o SMEs in he con ex o DT, we conduc ed sepa a e analyses o
he SCA o SMEs and he SCA wi hin he con ex o DT.
Ou o he 1,856 pape s on SCA, we iden i ied only 149 s udies ha speci ically ocus on SMEs’ SCA.
We analyzed hese s udies using VOS iewe and p esen ed he esul s in Figu e 3. As shown in he ig-
u e, apa om he SCA and SMEs nodes, he e a e no signi ican ly la ge nodes, indica ing ha esea ch
in his a ea is ela i ely agmen ed. Howe e , he colo o he nodes e eals ha in ecen yea s, opics
such as ‘eco- iendly p oduc ’, ‘business en i onmen ’, ‘en ep eneu ial capabili ies’, ‘adop ion beha io ’,
and ‘lea ning’ ha e become p ima y esea ch ocuses.
Fu he mo e, he clus e ela ionships show ha keywo ds such as ‘en ep eneu ial o ien a ion’ and
‘dynamic capabili ies’ eme ge a ound he co e hemes o SCA and SMEs; his indica es ha esea ch on
how SMEs can achie e SCA h ough inno a ion and dynamic capabili ies is an impo an esea ch di ec-
ion. ‘En ep eneu ial o ien a ion’ is closely associa ed wi h e ms like ‘en ep eneu ial ma ke ing’ and
‘business model inno a ion’, highligh ing he signi icance o inno a ion o ien a ion, ma ke s a egy, and
business model inno a ion in achie ing SCA. Meanwhile, keywo ds such as ‘open inno a ion’ and ‘abso p-
i e capaci y’ link o ‘dynamic capabili ies’, highligh ing he c ucial ole o a i m’s dynamic and abso p i e
capabili ies in main aining a compe i i e ad an age in apidly changing ma ke s.
3.3. Keywo ds analysis o SCA and DT
Figu e 4 highligh s he esea ch ho spo s in he ields o DT and SCA. The la ge nodes, such as
‘dynamic capabili ies’, ‘Indus y 4.0’, and ‘big da a’, indica e ha le e aging big da a and dynamic capa-
bili ies o achie e compe i i e ad an age wi hin he con ex o DT is a key esea ch ocus. The
blue-g een nodes, such as ‘sus ainabili y’ and ‘big da a analy ics’, sugges ha esea che s ha e been
Figu e 3. sMes’ sCa au ho keywo ds o e lay isualisa ion bibliog aphic coupling.
6 H. LU AnD M. S. SHAHARUDIn
explo ing hese opics egula ly since 2021 o ea lie . In con as , he yellow and g een nodes, such as
‘dis up i e inno a ion’ and ‘en ep eneu ial ecological o ien a ion’, ep esen eme ging esea ch a eas
om ecen yea s (2022–2024). Addi ionally, he hick lines be ween ‘digi al ans o ma ion’ and ‘dynamic
capabili ies’ demons a e he close ela ionship be ween hese wo concep s. The e a e also connec-
ions be ween ‘sus ainable compe i i e ad an age’, ‘con ingency heo y’, and ‘business model inno a-
ion’, indica ing ha esea che s a e in es iga ing how business model inno a ion can d i e SCA in he
con ex o DT.
Figu e 4 also p esen s se e al esea ch clus e s, each ocused on dis inc esea ch hemes. In he DT
clus e , keywo ds like ‘Indus y 4.0’, ‘big da a’, ‘in o ma ion echnology’, and ‘dynamic capabili ies’ empha-
size he di ec ion o echnology-d i en ans o ma ion, he applica ion o dynamic capabili ies, and he
in eg a ion o big da a wi hin DT. The SCA clus e includes e ms like ‘business model inno a ion’ and
‘con ingency heo y’, highligh ing ha achie ing SCA h ough inno a i e business models and con in-
gency heo y is a signi ican esea ch ocus. In he dynamic capabili ies clus e , keywo ds such as ‘dis up-
i e inno a ion’ and ‘abso p i e capaci y’ e lec he impo ance o hese capabili ies in main aining
compe i i eness wi hin apidly changing ma ke en i onmen s. The p esence o echnological hemes,
such as big da a, a i icial in elligence, and Indus y 4.0, indica es ha le e aging hese echnologies o
enhance compe i i e ad an age is a key esea ch di ec ion. The s ong connec ions be ween ‘big da a’,
‘digi al ans o ma ion’, and ‘sus ainable compe i i e ad an age’ sugges ha big da a analy ics plays a
c ucial ole in helping i ms achie e and main ain compe i i e ad an age.
3.4. De ailed analysis o key li e a u e
Based on ou esea ch objec i es, which ocus on he con ibu ion o DT o he SCA o SMEs, as well as
he key echnologies and capabili ies ha in luence SMEs’ SCA, we conduc ed a de ailed analysis o 57
esea ch pape s ela ed o DT and SCA. The analysis co e ed aspec s such as publica ion yea , esea ch
me hods, heo e ical amewo ks, esea ch con en , key indings, and inno a ions. Table 3 displays he
analysis esul s.
Figu e 4. sCa and D au ho keywo ds o e lay isualisa ion bibliog aphic coupling.
COGEnT BUSInESS & MAnAGEMEnT 7
Based on he selec ed li e a u e on DT and SCA, we conduc ed a de ailed analysis o he ield. The
i s a icle on his opic was published in 2017, and he numbe o publica ions began o g ow apidly
in 2022, indica ing ha he ela ionship be ween SCA and DT is gaining inc easing a en ion om schol-
a s. Among he heo ies equen ly employed in hese s udies, esou ce-based heo y (RBT) is he mos
p ominen , appea ing in 26.32% o he o al li e a u e. Dynamic capabili ies heo y is equally p e alen ,
sha ing he same p opo ion as RBT. Inno a ion heo y and s a egic heo y ollow, wi h p opo ions o
14.04 and 12.28%, espec i ely. These indings indica e ha nume ous schola s pe cei e inno a ion as a
c ucial elemen in os e ing SCA, and widesp ead consensus suppo s he implemen a ion o DT as a
s a egic ini ia i e.
In e ms o esea ch me hods, su eys combined wi h eg ession analysis o s uc u al equa ion mod-
eling a e he mos commonly used app oaches, ep esen ing hal o he analyzed s udies. The ex ensi e
applica ion o case s udies, pa icula ly in ea lie esea ch, accoun s o 24.56% o he o al. Addi ionally,
19.3% o he s udies u ilized in e iews, including bo h semi-s uc u ed and in-dep h in e iews. no ably,
wo pape s published in 2024 employed sQCA in combina ion wi h o he quan i a i e me hods, while
one pape om 2023 used sQCA exclusi ely o analysis. This end sugges s a g owing di e si y o
esea ch me hodologies wi hin he ield.
We compiled he keywo ds om 57 a icles in Excel and pe o med a s a is ical analysis, wi h he
esul s shown in Table 3. Aside om ou selec ed hemes o SCA and DT, he mos equen ly men ioned
keywo ds we e ‘capabili ies’ (24.56%) and ‘inno a ion’ (19.3%). Capabili ies mainly e e o dynamic capa-
bili ies and big da a capabili ies, while inno a ion esea ch ocuses on echnological inno a ion and busi-
ness model inno a ion. Consequen ly, we equen ly men ioned ‘ echnology’ (8.77%), ‘big da a’ (12.28%),
and ‘business model’ (12.28%). These esul s align wi h ou p e ious analysis using VOS iewe , indica ing
ha in he con ex o DT, enhancing compe i i e ad an age h ough hese echnologies and inno a ions
(Bilal e al., 2024) is a signi ican esea ch ocus.
4. Discussion o he esul s
This s udy aimed o in es iga e wo key esea ch ques ions (RQ1 and RQ2) ela ed o how DT impac s
he SCA o SMEs and he speci ic digi al echnologies and capabili ies ha acili a e his p ocess. In his
sec ion, we will i s add ess RQ1, examining he ole o DT in building and sus aining CA in compe i i e
Table 3. sCa and D opic pape analysis s a is ics able.
a ge Con en no %
Yea 2024 8 14.04
2023 22 38.60
2022 16 28.07
2021 6 10.53
2017–2020 5 8.77
heo y Resou ce-based heo y 15 26.32
Dynamic capabili y heo y 15 26.32
inno a ion heo y 8 14.04
s a egic heo y 7 12.28
g ounded heo y 2 3.51
s akeholde heo y 2 3.51
Me hod Ques ionnai e 26 45.61
Case s udy 14 24.56
in e iew 11 19.30
seM (PLs-seM, aMos) 26 45.61
Reg ession analysis (sPss, s a a) 6 10.53
sQCa 3 5.26
Key wo ds D and digi aliza ion and digi alisa ion 44 77.19
sCa 13 22.81
Capabili y and capabili ies 14 24.56
inno a ion 11 19.30
Dynamic capabili y 7 12.28
Big da a 7 12.28
Business model 7 12.28
echnology 5 8.77
Sou ce: au ho ’s elabo a ion.
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Appendix A
Table A1.
no i le au ho , YeaR heo y Resea ch me hods Keywo ds
1Dynamic capabili ies and
digi aliza ion as
an eceden s o inno a ion
and sus ainable
pe o mance: empi ical
e idence om
Vie namese sMes
Vo hai e al., 2024 Dynamic capabili y
heo y, inno a ion
heo y
Ques ionnai e
me hod,
s uc u al
equa ion
modeling (seM)
Dynamic capabili ies,
digi aliza ion, business model
inno a ion, sus ainable
business pe o mance,
Vie nam small- and
medium-sized en e p ises
2D i e s o decision-making
owa ds o digi al
ans o ma ion
ul ich e al., 2024 Co po a e beha io
heo y, digi al
ans o ma ion
heo y
Ques ionnai e
su ey,
eg ession
analysis, uzzy
se quali a i e
compa a i e
analysis ( sQCa)
Digi al ans o ma ion,
compe i i e ad an age,
s a egy managemen ,
p o i abili y
3sus ainable compe i i e
ad an age unde digi al
ans o ma ion: an
eco-s a egy pe spec i e
Du e al., 2024 Dynamic capabili y
heo y,
en ep eneu ial
eco-sys em
o ien a ion heo y
sQCa, seM (sPss
and aMos)
en ep eneu ial ecological
o ien a ion, dynamic
capabili ies, sus ainable
compe i i e ad an age,
digi al ans o ma ion, uzzy
se quali a i e compa a i e
analysis ( sQCa)
4 echnological in eg a ion o
imi a ion de e ence o
new en an s: e idence
om he Japanese digi al
imaging indus y in
1990–2014
Hamada, 2024 Resou ce-based
heo y, inno a ion
heo y
Case s udy,
quali a i e
esea ch
P oduc a chi ec u e design,
digi al imaging indus y,
en y de e ence, DsLR
came a ma ke , echnological
de elopmen
5Digi al ans o ma ion a
hi d-pa y logis ics
p o ide s: challenges and
bes p ac ices
M ubu & naude, 2024 inno a ion di usion
heo y
semi-s uc u ed
in-dep h
in e iews,
quali a i e
esea ch
Digi al ans o ma ion,
hi d-pa y logis ics,
challenges, bes p ac ices,
sou h a ica
6Digi ally ans o ming he
o ganiza ion h ough
knowledge managemen :
a socio- echnical sys em
(s s) pe spec i e
homas, 2024 social- echnical sys em
heo y
in-dep h in e iews,
quali a i e
esea ch
Knowledge managemen , digi al
ans o ma ion, d i e s,
social- echnical sys em
heo y (s s), inno a ion
7 he in e play o lean six
sigma, indus y 4.0, and
dynamic capabili ies:
pa hways o sus ainable
compe i i e ad an age
Ri qi e al., 2024 Dynamic capabili y
heo y
Ques ionnai e,
PLs-seM
Lean six sigma (Lss), indus y
4.0 (i4.0), dynamic
capabili ies (DC), sus ainable
compe i i e ad an age (sCa),
explana o y sequence model
8 he impac o digi alisa ion
on he p o i abili y o
la ge us banks
Chesini & gia e a, 2024 Knowledge base
heo y
Quan i a i e
esea ch
Digi alisa ion, digi al banking,
p o i abili y, bank,
knowledge-based heo y,
con en analysis
9new p oduc de elopmen
capabili y, sus ainable
compe i i e ad an age,
digi al ans o ma ion,
and ma ke ing
pe o mance: e idence
om hailand
sookbum oong &
Pho nlapha achako n,
2023
Dynamic capabili y
heo y
Ques ionnai e, seM,
mul iple
eg ession
analysis
new p oduc de elopmen
capabili y, sus ainable
compe i i e ad an age,
digi al ans o ma ion,
ma ke ing pe o mance
10 s a egic o ien a ion,
dynamic capabili ies, and
digi al ans o ma ion o
comme cial banks: a
uzzy-se QCa app oach
Cheng e al., 2023 s a egic o ien a ion
heo y, dynamic
capabili y heo y
Ques ionnai e,
sQCa
s a egic o ien a ion, dynamic
capabili ies, digi al
ans o ma ion, sQCa
(Con inued)
COGEnT BUSInESS & MAnAGEMEnT 17
no i le au ho , YeaR heo y Resea ch me hods Keywo ds
11 Digi al ans o ma ion in
co po a e banking:
owa d a blended se ice
model
LLóska & uo ila, 2024 Compe i i e ad an age
heo y, inno a ion
heo y
semi-s uc u ed
in e iews, case
s udy, quali a i e
analysis
Business model de elopmen ,
se ice inno a ion, cus ome
ela ionship managemen ,
banks, compe i i e
ad an age, alue c ea ion,
in o ma ion echnology
12 he e ec o elec onic
human esou ce
managemen sys ems on
sus ainable compe i i e
ad an ages: he oles o
sus ainable inno a ion
and o ganiza ional agili y
alqa ni e al., 2023 Dynamic capabili y
heo y,
o ganiza ional
agili y heo y
Ques ionnai e,
PLs-seM
elec onic human esou ce
managemen sys ems,
sus ainable compe i i e
ad an age, sus ainable
inno a ion, o ganiza ional
agili y
13 Business p ocess
eenginee ing o
designing a
knowledge-enabled
cus ome -cen ic
compe i i eness s a egy
al-shamma i, 2023 Knowledge
managemen
heo y, business
p ocess
eenginee ing
heo y
sys ema ic li e a u e
e iew,
quali a i e
esea ch
Business p ocess eenginee ing,
BPR, digi al ans o ma ion,
knowledge managemen ,
cus ome ela ionship
managemen , CRM, cus ome
knowledge, compe i i eness
s a egy
14 Leading digi al business
model ans o ma ion in
he K-pop indus y: he
case o sM en e ainmen
Cho e al., 2023 s a egic lea ning
heo y, leade ship
heo y
Case s udy,
semi-s uc u ed
in e iew,
quali a i e
esea ch
K-pop, digi al business model
ans o ma ion, ma ke
pionee , s a egic lea ning,
cha isma ic leade ship,
o ganiza ional capabili ies,
sM en e ainmen
15 Big da a analy ics capabili y
and con ibu ion o i m
pe o mance: he
media ing e ec o
o ganiza ional lea ning
on i m pe o mance
ga maki e al., 2023 Resou ce-based
heo y, dynamic
capabili y heo y,
g ounded heo y
in-dep h in e iew,
quali a i e
esea ch
Big da a analy ics, big da a
analy ics capabili y, digi al
ans o ma ion,
o ganiza ional lea ning,
g ounded heo y
16 Pla o m business model
inno a ion in he
digi aliza ion e a: a
“d i e -p ocess- esul ”
pe spec i e
Jia e al., 2023 Business Model
inno a ion (BMi)
heo y, alue
co-c ea ion heo y
Longi udinal single
case s udy,
semi-s uc u ed
in e iews,
li e a u e e iew,
ield
obse a ions
Pla o m, business model
inno a ion, digi aliza ion e a,
alue co-c ea ion
17 unlocking sus ainable
compe i i e ad an age:
explo ing he impac o
echnological inno a ions
on pe o mance in
Mexican sMes wi hin he
ou ism sec o
León-gómez e al., 2023 Compe i i e ad an age
heo y, echnology
inno a ion heo y
elephone su ey,
PLs-seM
en i onmen al sus ainabili y,
echnological inno a ion,
pe o mance, PLsseM,
in o ma ion and
communica ion echnologies
(iC ), digi aliza ion
18 he impac o digi al
ans o ma ion on supply
chain capabili ies and
supply chain compe i i e
pe o mance
ning & Yao, 2023 Con ingency heo y,
esou ce-based
heo y
Ques ionnai e, seM Digi al ans o ma ion, supply
chain capabili y, sus ainable
compe i i e pe o mance,
con ingency heo y
19 Digi al ans o ma ion and
he ci cula economy:
c ea ing a compe i i e
ad an age om he
ansi ion owa ds ne
ze o manu ac u ing
oko ie e al., 2023 Resou ce-based heo y Li e a u e e iew,
semina s,
in e iews
Digi al ans o ma ion,
esou ce-based iew, ne -ze o
manu ac u ing, ci cula
economy, sus ainable
compe i i e ad an age,
engaged schola ship
20 How digi al ans o ma ion
p omo es dis up i e
inno a ion? e idence
om Chinese
en ep eneu ial i ms
Pang & Wang, 2023 Dynamic capabili y
heo y,
c oss-o ganiza ional
collabo a ion
heo y
Ques ionnai e
su ey, mul iple
eg ession
analysis
Digi al ans o ma ion,
in e o ganiza ional
collabo a ion, dis up i e
inno a ion, dynamic
capabili ies, en ep eneu ial
i ms
21 he media o ole o ask
pe o mance in he e ec
o digi al li e acy on i m
pe o mance
sadik a li e al., 2023 Human capi al heo y Ques ionnai e, sPss
analysis
Digi al li e acy, i m
pe o mance, human capi al,
ask pe o mance, whi e
colla
22 sus ainable supply chain,
digi al ans o ma ion,
and blockchain
echnology adop ion in
he ou ism sec o
sa az e al., 2023 Resou ce-based heo y Ques ionnai e, seM
(aMos)
Table 1. Con inued.
(Con inued)
18 H. LU AnD M. S. SHAHARUDIn
no i le au ho , YeaR heo y Resea ch me hods Keywo ds
23 gaining use con idence in
banking indus y’s ques
o digi al ans o ma ion:
a p oduc -se ice sys em
managemen pe spec i e
shin & Cheng, 2023 Resou ce-based
heo y, consume
alue heo y
Ques ionnai e, seM
(aMos)
P oduc -se ice sys ems,
banking indus y, Fin ech
quali y, Fin ech use
con idence, esou ce-based
iew, u ili a ian, condi ional,
and social alues
24 o ganisa ional esilience,
ambidex e i y and
pe o mance: he oles o
in o ma ion echnology
compe encies, digi al
ans o ma ion policies
and pa adoxical
leade ship
ieu e al., 2024 Resou ce-based
heo y, dynamic
capabili y heo y
Ques ionnai e,
PLs-seM
i compe encies, o ganisa ional
ambidex e i y, o ganisa ional
esilience, pa adoxical
leade ship, business
pe o mance, digi al
ans o ma ion policies
25 Da a capi al in es men
s a egy in compe ing
supply chains
XXin e al., 2024 game heo y, supply
chain heo y
h ee-s age
non-coope a i e
game model,
nume ical
simula ion
supply chain compe i ion, da a
capi al in es men (DCi),
h ee-s age non-coope a i e
game, s ackelbe g game
26 Resea ch on in luencing
ac o s and pa h o
digi al ans o ma ion o
manu ac u ing en e p ises
ZZhang & Wang,g, 2024 g ounded heo y,
esou ce-based
heo y, dynamic
capabili y heo y
Ques ionnai e, seM Manu ac u ing en e p ises,
digi al ans o ma ion, digi al
dynamic capabili y
27 he e ec s o ins i u ions,
i m-le el ac o s and
a ional decision-making
on en ep eneu ial
beha io s o MsMes:
lessons and oppo uni ies
o ansi ion
communi ies
K yeziu e al., 2023 ins i u ional heo y,
a ional decision
heo y
Ques ionnai e
su eys,
quan i a i e
analysis (sPss
and s a a)
en ep eneu ial beha io ,
ins i u ions, i m-le el ac o s,
a ional decision-making,
MsMes
28 C ea ion o sus ainable
g ow h wi h explainable
a i icial in elligence: an
empi ical insigh om
consume packaged
goods e aile s
Behe a e al., 2023 Resou ce-based
heo y, compe i i e
s a egy heo y
Ques ionnai e, seM explainable a i icial in elligence,
sus ainable g ow h,
sus ainable compe i i e
ad an age, in o ma ion
sys ems business alue,
compe i i e s a egy
29 Ha es ing he powe o
loca ion da a o imp o e
cus ome s’ expe ience
and des ina ion
a ac i eness
si i idou & Fouskas,
2023
s akeholde heo y Field su ey Loca ion da a, cus ome
expe ience, des ina ion
a ac i eness, loca ion
echnologies, digi al
ans o ma ion,
in e o ganisa ional ela ions
30 Da a-d i en human esou ce
and da a-d i en alen
managemen in in e nal
and ec ui men
communica ion s a egies:
an empi ical su ey on
i alian i ms and insigh s
o eu opean con ex
Con e & siano, 2023 Human esou ce
managemen
heo y
Ques ionnai e
su eys,
quan i a i e
analysis (sPss)
Big da a, indus y 4.0, human
esou ce, alen managemen ,
digi al ans o ma ion
31 he impac o indus y 4.0
on he econcilia ion o
dynamic capabili ies:
e idence om he
eu opean manu ac u ing
indus ies
Felsbe ge e al., 2022 Resou ce-based
heo y, dynamic
capabili y heo y
Mul iple case s udy,
semi-s uc u ed
in e iews,
ques ionnai es
and
sel -assessmen
o ms.
indus y 4.0, ope a ions
managemen , dynamic
capabili ies, case s udy
esea ch, manu ac u ing
indus y
32 Can big da a analy ics help
o ganisa ions achie e
sus ainable compe i i e
ad an age? a
de elopmen al enqui y
shah, 2022 Resou ce-based
heo y,
knowledge-based
heo y,
Li e a u e e iew,
induc i e
me hod
Big da a analy ics,
knowledge-based iew,
ma u i y model,
esou ce-based iew,
sus ainable compe i i e
ad an age, digi al age
33 a big da a s a egy o
ein o ce
sel -sus ainabili y o
pha maceu ical
companies in he digi al
ans o ma ion e a: a case
s udy o egyp ian
pha maceu ical
companies
Hassanin & Hamada,
2022
Dynamic capabili y
heo y
Li e a u e e iew,
case s udy and
semi-s uc u ed
in e iews
Big da a, digi al ans o ma ion,
egyp ian pha maceu ical
companies, s a egy, ba ie s
Table 1. Con inued.
(Con inued)
COGEnT BUSInESS & MAnAGEMEnT 19
no i le au ho , YeaR heo y Resea ch me hods Keywo ds
34 How mul idimensional
digi al empowe men
a ec s echnology
inno a ion pe o mance:
he mode a ing e ec o
adap abili y o
echnology embedding
Li e al., 2022 Resou ce-based
heo y,
knowledge-based
heo y,
Ques ionnai e, seM Digi al empowe men , echnology
inno a ion pe o mance,
adap abili y o echnology
embedding, high–end
equipmen manu ac u ing
en e p ises, sus ainable
compe i i e ad an age
35 Pa e ns and p inciples o
he de elopmen o
digi al ecosys ems
Lipo enko e al., 2022 Digi al ecosys em
heo y, inno a i e
business model
heo y
Li e a u e e iew,
case s udy
inno a i e business models,
digi al en i onmen , global
compe i i eness, s a is ical
analysis
36 seeking he esilience o
se ice i ms: a s a egic
lea ning p ocess based
on digi al pla o m
capabili y
LLiu e al., 2023 Dynamic capabili y
heo y, s a egic
lea ning heo y
Ques ionnai e, seM Digi al pla o m capabili y,
s a egic lea ning, esilience,
se ice i ms, legal
en i onmen
37 he co ela ion be ween
digi al echnology and
digi al compe i i eness
Ma ince ic, 2022 Compe i i eness
heo y, digi al
ans o ma ion
heo y
sys ema ic li e a u e
e iew me hod
in o ma ion – communica ion
echnologies (iC ),
digi aliza ion,
compe i i eness, digi al
ans o ma ion, digi al
echnologies, digi al
compe i i eness, business
ma ke , business
38 s a egic capabili ies o
business model
digi aliza ion
Menchini e al., 2022 social ma e iali y
heo y, en e p ise
a chi ec u e heo y
su ey me hod,
ocus g oup
esea ch, analysis
o a iance
Ma u i y in digi al business
models, en e p ise
a chi ec u e, socioma e iali y
39 achie ing compe i i e
sus ainable ad an ages
(Csas) by applying a
heu is ic-collabo a i e isk
model
nunes e al., 2022 Risk managemen
heo y, social
ne wo k analysis
heo y
Case s udy o ganiza ional isk managemen ,
o ganiza ional ne wo k
analysis, c i ical success
ac o s, business in elligence
a chi ec u e, sus ainabili y;
o ganiza ional digi al
ans o ma ion, indus y 4.0
40 g een alen managemen
and employees’
inno a i e wo k beha io :
he oles o a i icial
in elligence and
ans o ma ional
leade ship
oodugbesan e al., 2023 VRio heo y,
s akeholde heo y
Ques ionnai e,
PLs-seM
g een alen managemen ,
inno a i e wo k beha io ,
sus ainable compe i i e
ad an age, ans o ma ional
leade ship, a i icial
in elligence, PLs-seM
41 CoViD-19 u bulence and
posi i e shi s in online
pu chasing by consume s:
modeling he enable s
using isM-MiCMaC
analysis
ssha ma e al., 2023 Consume beha io
heo y, supply
chain heo y
expe opinion
me hod,
in e p e i e
s uc u al
modeling
me hod and
MiCMaC analysis
supply chain, MiCMaC, online
pu chase, CoViD-19,
changing buying beha io ,
digi iza ion-comme ce, isM
analysis
42 Resea ch on digi al
ans o ma ion based on
complex sys ems:
isualiza ion o
knowledge maps and
cons uc ion o a
heo e ical amewo k
Xu e al., 2022 Complex sys ems
heo y
Knowledge
mapping,
bibliome ic
analysis
Digi al ans o ma ion,
o ganiza ion managemen
sys em, bibliome ics; isual
analysis, sus ainable
compe i i e ad an age
43 Digi al ans o ma ion o
manu ac u ing
en e p ises: an empi ical
s udy on he ela ionships
be ween digi al
ans o ma ion, bounda y
spanning, and sus ainable
compe i i e ad an age
Xue e al., 2022 Resou ce-based
heo y,
bounda y-c ossing
heo y
Ques ionnai e
su ey, s a i ied
eg ession
analysis
44 Big da a capabili y and
sus ainable compe i i e
ad an age: he media ing
ole o ambidex ous
inno a ion s a egy
Zhang e al., 2022 Dynamic capabili y
heo y,
ambidex ous
inno a ion heo y
Ques ionnai e
su ey, s a i ied
eg ession
analysis
Big da a capabili y, exploi a i e
inno a ion s a egy,
explo a i e inno a ion
s a egy, balanced dimension
o ambidex ous inno a ion
s a egy, combined dimension
o ambidex ous inno a ion
s a egy, sus ainable
compe i i e ad an age
Table 1. Con inued.
(Con inued)
20 H. LU AnD M. S. SHAHARUDIn
no i le au ho , YeaR heo y Resea ch me hods Keywo ds
45 How o s imula e employees’
inno a i e beha io :
in e nal social capi al,
wo kplace iendship and
inno a i e iden i y
Zhao e al., 2022 social iden i y heo y,
conse a ion o
esou ces heo y
Ques ionnai es, seM
(sPss and
aMos)
in e nal social capi al, inno a i e
iden i y, wo kplace
iendship, employees’
inno a i e beha io ,
psychological ac o s
46 en ep eneu ship, digi al
capabili ies, and
sus ainable business
model inno a ion: a case
s udy
gao e al., 2022 Dynamic capabili ies
heo y,
en ep eneu ship
heo y
Case s udy,
quan i a i e da a
analysis
47 in luence o digi al
echnologies and i s
echnological dynamics
on company
managemen
Ma ince ic & Kozina,
2021
Dynamic heo y o
echnology, digi al
ans o ma ion
heo y
Ques ionnai e,
eg ession
analysis
Digi aliza ion, digi al s a egy,
digi al ans o ma ion, digi al
echnology, expo
companies, in o ma ion and
communica ion echnologies
(iC ), managemen
48 supply chain managemen
concep and digi al
economy: digi al supply
chain echnological
inno a ion
Chupano a e al., 2021 supply chain
managemen
heo y, digi al
ans o ma ion
heo y
Li e a u e e iew,
expe su ey
Digi al ans o ma ion, p oduc
quali y, supply chain
managemen
49 a i icial in elligence and
business s a egy owa ds
digi al ans o ma ion: a
esea ch agenda
Ki sios & Kama io ou,
2021
s a egic managemen
heo y, in o ma ion
echnology heo y
sys ema ic li e a u e
e iew me hod
a i icial in elligence, business
s a egy digi al
ans o ma ion, in o ma ion
echnology, indus y 4.0,
sus ainable compe i i e
ad an age
50 s abili y in u bulen imes?
he e ec o
digi aliza ion on he
sus ainabili y o
compe i i e ad an age
Knudsen e al., 2021 Big da a and ne wo k
e ec heo y,
compe i i e
ad an age heo y
Quali a i e analysis,
case s udy
Big da a, ne wo k e ec s,
digi aliza ion, compe i i e
ad an age
51 he e ec s o business
analy ics capabili y on
ci cula economy
implemen a ion, esou ce
o ches a ion capabili y,
and i m pe o mance
K is o e sen e al., 2021 Resou ce-based
heo y, esou ce
coo dina ion heo y
Ques ionnai e,
PLs-seM
Digi al ci cula economy, big
da a analy ics, ci cula
economy capabili y,
sus ainabili y, policy
implica ion, digi aliza ion
52 global challenge: F om
in a-company s a
managemen o wo king
wi h he alen
odego , 2021 alen managemen
heo y
Li e a u e e iew,
case s udy,
empi ical
analysis
skills misma ch, skills gap, s a
sho age, alen , alen
disco e y and de elopmen ,
demand by occupa ional
g oups
53 suppo ing he sus ainabili y
o na u al ibe -based
alue chains o sMes
h ough digi aliza ion
Kamišalić e al., 2020 Digi al ans o ma ion
and sus ainabili y
heo y, alue chain
heo y
Case s udy Digi aliza ion, digi aliza ion
index, sMe, small and
medium-sized en e p ises,
alue chain, na u al ibe ,
sus ainabili y, indus y 4.0
54 Digi alisa ion as a d i e o
indus ial enewal
– pe cep ion and
quali a i e e idence om
he usa
Yli-Vii ala e al., 2020 Pa h dependence
heo y, s a egic
enewal heo y
Quali a i e esea ch,
semi-s uc u ed
in e iews
Digi alisa ion, indus ial enewal,
pa h dependence,
manu ac u ing
55 echnology adop ion o he
in eg a ion o online–
o line pu chasing
sa as ano e al., 2019 omnichannel e ail
heo y, inno a i e
s a egy heo y,
compe i i e
ad an age heo y
Mul iple case s udy,
quali a i e
analysis
echnology and inno a ion
managemen , digi al
ans o ma ion, in-s o e
echnology, omnichannel
e ailing, pionee ing s a egy
56 equipmen main enance
business model
inno a ion o sus ainable
compe i i e ad an age in
he digi aliza ion con ex :
Conno a ion, ypes, and
measu ing
Chen e al., 2018 Business model
inno a ion heo y,
alue c ea ion
heo y
Documen analysis,
semi-s uc u ed
in e iews,
ques ionnai e
su eys
equipmen main enance,
business model inno a ion,
equipmen main enance
business model inno a ion
conno a ion, measu ing;
digi aliza ion, sus ainable
compe i i e ad an age
57 he case o a comple e
model o s a egic
esou ce u ili y in spo
and en e ainmen
managemen
Hayduk, 2017 Resou ce-based
heo y, dynamic
capabili y heo y
li e a u e e iew,
case s udy
s a egic managemen ,
esou ces, spo ,
en e ainmen
Table 1. Con inued.
