S azzullo, Se ena
A icle
Fos e ing digi al us in manu ac u ing companies:
Explo ing he impac o indus y 4.0 echnologies
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Fos e ing digi al us in manu ac u ing companies: Explo ing he impac o
indus y 4.0 echnologies
Se ena S azzullo
Uni e si y o Naples Fede ico II, Depa men o Indus ial Enginee ing, P.le Tecchio 80, 80125, Naples, I aly
ARTICLE INFO
JEL classi ica ion codes:
O33 (Technological Change: Choices and
Consequences •Di usion P ocesses)
Keywo ds:
Digi al ans o ma ion
FsQCA
Indus y 4.0
Manu ac u ing
T us
Technology
ABSTRACT
This s udy examines he mul i ace ed impac s o digi al inno a ions on o ganisa ional s uc u es and s ake-
holde s ‘commi men . The in eg a ion o digi al echnologies, including in o ma ion echnologies, IoT, AI, AR/
VR, blockchain, obo ics, and au oma ion, unde sco es he indispensable ole o us in con empo a y business
ope a ions. Focusing on I alian manu ac u ing i ms a he o e on o Indus y 4.0 implemen a ion, his esea ch
seeks o un a el he nuanced ac o s con ibu ing o digi al us . A comp ehensi e amewo k, de i ed om an
in eg a i e li e a u e e iew, ca ego ises wo dis inc g oups o ac o s in luencing a i m’s decision o es ablish
digi al us . Employing a con igu a ional app oach, speci ically Quali a i e Compa a i e Analysis (QCA), he
join impac s o mul iple ac o s on digi al us le els a e sc u inized, o e ing insigh s in o how di e en ele-
men s syne gise o igge digi al us . This s udy aims o b idge exis ing gaps in unde s anding he in ica e
dynamics o us wi hin o ganisa ions unde going digi al ans o ma ion.
In oduc ion
T us in he adop ion o Indus y 4.0–enabling echnologies,
commonly known as digi al us , has become a ecen opic o discus-
sion (Lumineau, Schilke & Wang, 2023). Inno a ions esul ing om he
ou h indus ial e olu ion a e dis up ing o ganisa ional s uc u e,
especially conce ning employee sen imen s and sel -es eem. The use o
digi al echnologies ac oss a ious business unc ions, including ope a-
ions, R&D, inance, ma ke ing, e c., has led o inc eased in o ma ion
lows and da a exchange, necessi a ing us -building wi hin he o ga-
nisa ion (Fe a io, Loi & Vigan`
o, 2021; In ala e al., 2021; Rakowska,
2021). Indus y 4.0 echnologies o e signi ican inno a ions ha can
d as ically inc ease an o ganisa ion’s p oduc i i y (Ho ´
a h & Szab´
o,
2019; I o e al., 2021). Howe e , he implemen a ion o dis up i e
changes can gi e ise o a ense a mosphe e wi hin companies, as
exclusi e dependence on in e nal esou ces is no easible. In his
con ex , he challenge becomes es ablishing us among s akeholde s
(Lumineau e al., 2023). P io s udies s ess he need o human-cen ic
app oaches ha os e us in indi iduals and he use o echnology o
success ul coope a ion and he a ainmen o pe sonal and o ganisa-
ional goals (E lie, Tucci & Gianiodis, 2017; Lank on, Mcknigh &
T ipp, 2015; Sindwani, 2022). To his end, o ganisa ions a e shi ing
owa ds in eg a ing Indus y 4.0 echnologies, mo ing om
human-cen ic o echnology-cen ic app oaches (Muba ak & Pe ai e,
2020). Howe e , he in oduc ion and di usion o echnologies a e
accele a ing p oduc ion p ocesses, sho ening p oduc li e cycles, and
d i ing a as e pace o inno a ion in companies. Fo his change o
occu , companies mus be eady o emb ace and alue i and de ine a
p ecise and pe sonalised pa h based on hei cha ac e is ics.
The le el o us is a c i ical ac o ha in luences how employees
eel, hink, and beha e abou a speci ic echnological change and is a key
componen ega ding employees’ accep ance and adap a ion o ech-
nology (Bahmanzia i, Pea son and C osby 2003; Smollan, 2013). Espe-
cially in he con ex o digi iza ion, employees’ us in he leade ship
d i ing digi iza ion is conside ed a necessa y p e equisi e o coope a-
ion and he success o employees in implemen ing digi iza ion (Van
Dam, O eg & Schyns, 2008; Ko e , 1995; Shah, I ani & Sha i , 2017). As
employees mus con inuously adap o hese changes o keep pace wi h
he e ol ing wo k en i onmen (Shah e al., 2017; Ul ich & Yeung,
2019), us in leade ship is a key ac o in achie ing indi idual and
wo kplace desi able ou comes (Yunus, Sapu a & Muhammad, 2022)
such as educing employees’ esis ance o change (Vakola, 2014).
Despi e g owing in e es in digi al us ela ed o he in oduc ion o
Indus y 4.0 echnologies, li le is known abou he ac o s wi hin an
o ganisa ion ha inc ease us le els. Mos s udies ha e p edominan ly
ocused on he consume pe spec i e when analyzing digi al us ,
emphasizing aspec s ela ed o online shopping and banking ans-
ac ions (Al-Debei e al., 2015; Cha e jee e ., 2023; Jasiulewicz e .,
E-mail add ess: [email p o ec ed].
Con en s lis s a ailable a ScienceDi ec
Jou nal o Inno a ion & Knowledge
jou nal homepage: www.else ie .com/loca e/jik
h ps://doi.o g/10.1016/j.jik.2024.100621
Recei ed 18 June 2024; Accep ed 2 No embe 2024
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
A ailable online 9 No embe 2024
2444-569X/© 2024 The Au ho (s). Published by Else ie España, S.L.U. on behal o Jou nal o Inno a ion & Knowledge. This is an open access a icle unde he
CC BY-NC-ND license (
h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/ ).
2023; Tul-K zyszczuk e al., 2024; Vasiliu-Fel es, 2024). These s udies
ypically in es iga e how consume s de elop us in digi al pla o ms,
secu e paymen sys ems, and p i acy policies, howe e , he e has been
signi ican ly less explo a ion o digi al us om an o ganiza ional
pe spec i e, pa icula ly wi hin companies. The dynamics o digi al us
wi hin a co po a e se ing a e di e en and mo e complex because hey
in ol e in e nal s akeholde s such as employees, managemen , and IT
depa men s. This includes unde s anding how digi al us e ol es wi h
he adop ion o new echnologies, how i impac s employee mo ale and
p oduc i i y, and how o ganiza ional cul u e and leade ship in luence
us le els in digi al p ocesses and in as uc u e. Shi ing he ocus o
he en e p ise con ex , i is possible o unco e c ucial insigh s in o he
mechanisms ha os e o hinde digi al us in companies unde going
digi al ans o ma ion. Digi al us encompasses he con idence ha
s akeholde s, including employees, ha e in he eliabili y, in eg i y, and
secu i y o digi al echnologies and he p ocesses associa ed wi h hem.
This us is c ucial because i di ec ly impac s he success ul adop ion
and u iliza ion o hese echnologies. Howe e , he ansi ion o a digi al
in as uc u e o en b ings challenges such as ea o obsolescence,
esis ance o change, and conce ns abou da a p i acy and secu i y.
These challenges highligh he necessi y o building a obus amewo k
o digi al us o acili a e smoo he implemen a ion and highe
accep ance a es o new echnologies.
The e o e, his a icle seeks o add ess he gaps in he exis ing
li e a u e by in es iga ing he ac o s ha unde lie digi al us . Exis ing
esea ch has p ima ily ocused on digi al us in consume con ex s o
speci ic indus ies such as inance and e-comme ce, lea ing a signi ican
gap in unde s anding how digi al us can be cul i a ed wi hin o ga-
niza ional se ings, pa icula ly in manu ac u ing sec o s. By explo ing
he unique dynamics o manu ac u ing i ms, his s udy aims o unco e
he speci ic ac o s ha in luence digi al us a a ious o ganiza ional
le els. The s udy is guided by he ollowing esea ch ques ions:
•Wha ac o s in luence digi al us ?
•How do hese ac o s in luence digi al us ?
In esponse o hese esea ch ques ions, a amewo k is p oposed
consis ing o wo dis inc g oups o ac o s ha can impac he le el o
digi al us , d awing on a comp ehensi e li e a u e e iew. The analysis
is concen a ed on manu ac u ing i ms in I aly ha ha e implemen ed
Indus y 4.0 echnologies in hei p oduc ion p ocesses. Th ough a
s uc u ed ques ionnai e, da a om 50 i ms a e collec ed. The e-
la ionships be ween a ious ac o s and he le el o digi al us we e
examined. Employing a con igu a ional app oach, namely quali a i e
compa a i e analysis (QCA) (Ragin, 1989), which conside s he com-
bined impac s o mul iple ac o s, his pape aims o s udy how di e en
ac o s wo k oge he o enhance digi al us le els. Gi en ha QCA is
designed o elucida e how speci ic condi ions join ly con ibu e o
de e mining an ou come, he me hod is ideal o assessing he combined
e ec s o ac o s in igge ing digi al us .
The pape is o ganised as ollows. Sec ion 2 e iews he exis ing
li e a u e ha o ms he backd op o his pape . Sec ion 3 in oduces
he da ase and me hodology. Sec ion 4 ou lines he implica ions, which
a e discussed hen in Sec ion 5. Finally, Sec ion 6 concludes he pape by
summa ising insigh s and limi a ions.
Theo e ical backg ound
Se e al ields ha e add essed he issue o analysing he concep o
us conside ing he mos dispa a e pe spec i es om medicine, and
sociology o economics and many o he s (Al-Dwai i & Kamala, 2009).
This shows ha us is a mul i ace ed concep applicable o nume ous
a eas, and o e he yea s, se e al academics ha e ied o gi e a
comp ehensi e de ini ion o his concep . S udies om he second hal o
he 20 h cen u y associa ed he e m us wi h he emo ional and
human sphe e (Ro e , 1967; Gibb, 1978). Since he 2000s, us has
acqui ed he exp ession o an expec a ion and an indi idual will
(Ba bale , 2009; Bos e al., 2002). To da e, us con inues o e ol e wi h
he inc easing a ay o echnological inno a ions, b oadening he
sou ces people can depend on beyond adi ional human ela ionships.
Howe e , he linge ing ques ion pe sis s ega ding he iden i ica ion o
uly eliable sou ces in his expansi e landscape. The agili y o us is
no a new phenomenon, he speed and i s isibili y a e new, indeed
ollowing he in oduc ion o Indus y 4.0 echnologies, he concep o
us has acqui ed a no el meaning. Muba ak and Pe ai e (2020)
de eloped a amewo k whe e digi al us is depic ed as he in e sec ion
o us and Indus y 4.0 echnologies. In his sense, digi al us can be
de ined as he s akeholde s’ con idence in he compe ence o ac o s,
echnologies, and p ocesses o c ea e eliable and secu e business ne -
wo ks (Muba ak & Pe ai e, 2020). This concep is ela ed o he ela-
ionship be ween indi iduals and he digi al en i onmen based on hei
pe cep ions and expec a ions. Fu he mo e, Ma cial and Laune (2019),
de ine digi al us as “ he gene al belie ha echnology, people, and
p ocesses ac o a e aligned in ways ha will mee people’s digi al ex-
pec a ions, such as a sense o us , secu i y, o con ol, o suppo he
c ea ion o a secu e digi al en i onmen ”. Recognising and unde -
s anding he ac o s ha in luence digi al us is c ucial in oday’s
in e connec ed and echnologically d i en socie y. As o ganiza ions
depend mo e on digi al echnologies, ecognizing key elemen s is i al
o secu e digi al en i onmen s. S ´
ephane Nappo o Soci´
e ´
e G´
en´
e ale
emphasized his by no ing, “I akes yea s o build epu a ion bu jus
minu es o a cybe inciden o des oy i ”. This eloquen quo e empha-
sises he ulne abili y o us in he digi al ealm. To na iga e he
apidly e ol ing h ea landscape, o ganisa ions mus adop a clea and
comp ehensi e s a egy o a oid a educ ion in us among s ake-
holde s. A comp ehensi e unde s anding o he elemen s impac ing
digi al us is essen ial o empowe o ganisa ions de eloping a obus
digi al en i onmen .
The o ma ion o digi al us is he e o e a complex in e play o
di e en ac o s. Nume ous heo ies and models ha e explo ed how o
enhance us in o ganiza ional con ex s. T us heo y and o ganiza-
ional beha io s ess he signi icance o us in he o ganiza ion, whe e
consis en ac ions, communica ion, and ai ness enhance a us wo hy
en i onmen (Lau & H¨
oyng, 2023; Sunil Kuma & Sumi ha, 2023).
Cus ome Rela ionship Managemen model highligh s how anspa en
communica ion, e hical beha iou , and consis en deli e y o p omises
by o ganiza ions can lead o inc eased cus ome sa is ac ion, loyal y,
and o e all us (Debna h, Da a & Mukhopadhyay, 2016; Demi el,
2022). Leade ship us p inciples u he posi ha us in leade ship is
c i ical o os e ing an en i onmen o us . Leade s who demons a e
in eg i y, compe ence, and bene olence signi ican ly enhance us
among employees (Bencsik e al., 2022). P e ious con ibu ions also
show how s a egic planning, managemen suppo , and alignmen wi h
o ganiza ional goals du ing digi al adop ion os e us (Lau & H¨
oyng,
2023). Suppo ing e idence om he li e a u e indica es ha p o iding
adequa e aining and suppo o employees enhances hei us in
digi al echnologies by imp o ing hei compe ence and con idence,
hus educing esis ance (Gkinko & Elbanna, 2023).
Gi en he mul i ude o pe spec i es, o explo e he a iables
impac ing digi al us , his s udy unde akes a comp ehensi e in eg a-
i e li e a u e e iew. This app oach is op imal o conduc ing a c i ical
analysis o he de elopmen o new concep ual amewo ks (Du ach,
Kemb o & Wieland, 2021; Mazumda , Raj & Sinha, 2005; Snyde , 2019).
Speci ically, his a icle d aws upon an in eg a i e e iew o published
s udies on digi al us and ela ed opics. In syn hesizing he p e ious
esea ch, o unde s and he complexi y o digi al us , his s udy d aws
upon he Technology Accep ance Model (TAM), which pos ula es ha
pe cei ed use ulness and pe cei ed ease o use signi ican ly de e mine
indi iduals’ accep ance and use o echnology (Da is, 1989). Two main
s eams o esea ch eme ge, ocused on o ganiza ion- ela ed and
p ocess- ela ed ac o s.
The i s s eam add esses o ganiza ion- ela ed ac o s, adop ing a
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
2
beha iou al pe spec i e e alua ing how ex e nal s imuli, changes, o
challenges p omp employees o adap hei beha io s, skills, and s a-
egies. The second s eam concen a es on p ocess- ela ed ac o s,
ocusing on he aspec s ela ed o he e iciency and e ec i eness o
p ocesses.
When combined wi h o ganiza ional heo y and p ocess- ela ed
p inciples, he TAM p o ides a obus amewo k o examining how
a ious an eceden s a ec digi al us . O ganiza ional heo y p o ides
insigh s in o how o ganiza ional dynamics, such as cul u e and man-
agemen s a egies, shape us wi hin digi al en i onmen s (Hob oll,
2002; Lu hans & Yousse , 2007). Meanwhile, p e ious esea ch on
success ul p ocess managemen shows how he sys ema ic, e icien , and
anspa en execu ion o p ocesses impac s s akeholde s’ us in digi al
sys ems (T kman, 2010; Qian & Papadonikolaki, 2021). Table 1 sum-
ma ises he classi ica ion o o ganiza ional and p ocess- ela ed ac o s
iden i ied om he in eg a i e li e a u e.
Concep ual amewo k
The concep ual amewo k o his pape is designed o sys ema ically
analyze how o ganiza ion- ela ed ac o s and p ocess- ela ed ac o s
wo k o build and main ain digi al us wi hin an o ganiza ion.
Al hough p io esea ch has examined us om a ious angles—such
as i s emo ional dimensions and i s ole in digi al con ex s—a gap e-
mains in unde s anding digi al us in complex o ganiza ional ecosys-
ems (Czakon e al., 2024; Van De Scha e al., 2024). Recen esea ch
by Ma cial e al. (2024) in es iga es he ela ionship be ween em-
ployees’ digi al beha io s and us le els in he wo kplace, ocusing on
hei posi ion wi hin a socio- echnological ladde and hei in e ac ion
wi h ICT componen s. While his s udy highligh s he impo ance o
digi al beha io in us -building, i does no ully in eg a e digi al us
wi h exis ing o ganiza ional heo ies o p ocess amewo ks, lea ing a
gap in unde s anding how digi al us is cul i a ed a he in e sec ion o
echnology and o ganiza ional dynamics. Simila ly, Gkinko and Elbanna
(2023) explo e he ole o us in in e ac ions wi h AI-d i en echnol-
ogies, such as cha bo s. Thei esea ch unde sco es he impo ance o
us in AI-human in e ac ions bu , like Ma cial e al., does no add ess
how b oade o ganiza ional and p ocess- ela ed ac o s con ibu e o he
de elopmen and sus enance o digi al us . As digi al in e ac ions
expand beyond adi ional human- o-human us in o
human- echnology in e aces, he e is a p essing need o in eg a e
o ganiza ional and p ocess heo ies wi h digi al us o ully g asp i s
implica ions in mode n echnological se ings. To b idge his gap, he
p esen s udy aims o in eg a e he TAM wi h o ganiza ional and p ocess
p inciples o p o ide a mo e comp ehensi e unde s anding o digi al
us . TAM, in oduced by Da is (1989) posi s ha pe cei ed use ulness
and pe cei ed ease o use a e key de e minan s o indi iduals’ accep-
ance o echnology. Howe e , while TAM p o ides aluable insigh s
in o echnology adop ion, i does no ully add ess he ole o o gani-
za ional s uc u e, cul u e, and p ocesses in shaping digi al us . By
combining TAM wi h heo ies om o ganiza ional beha io —such as
Lu hans and Yousse (2007) on posi i e o ganiza ional beha io and
Hob oll’s (2002) conse a ion o esou ces model— his s udy in-
co po a es how o ganiza ional ac o s like leade ship, cul u e, and
aining in luence digi al us . In addi ion o o ganiza ional ac o s,
p ocess- ela ed p inciples a e c i ical o unde s anding how us is
ope a ionalized in digi al con ex s. Guo and Yao (2022) and Qian and
Papadonikolaki (2021) emphasize he impo ance o p ocess s anda d-
iza ion, isk managemen , and eedback mechanisms in ensu ing he
eliabili y and secu i y o digi al sys ems. These p ocesses no only
enhance echnology accep ance bu also ensu e ha digi al us is
main ained h ough consis en and anspa en ope a ions. Gi en hese
conside a ions, his s udy p esen s a no el amewo k (illus a ed in
Fig. 1) o be e unde s and he mul i ace ed na u e o digi al us . This
app oach p o ides a mo e holis ic iew o how a ious an eceden s
in e ac o in luence us in digi al en i onmen s. The p oposed
Table 1
Classi ica ion o ac o s a ec ing digi al us (Au ho ’s own elabo a ion).
Mac o-Fac o s Fac o s A ec ing
Digi al T us
Re e ences
ORGANIZATION-
RELATED
FACTORS
Top
Managemen
De ined
S a egies
(TMDS)
Pe cei ed
E ec i eness,
Repu a ion, Image,
Digi al Vision,
Leade -Membe
Exchange,
O ganiza ional
Poli ics
(Au-Yong-Oli ei a
e al., 2022; H¨
oyng
& Lau, 2023; Lau
& H¨
oyng, 2023)
Sp ead o Digi al
Cul u e (SDC)
Pe cei ed Value,
A i ude owa ds
Technology,
Technology
Readiness,
Beha iou al
In en ion, E hical
A ibu es,
Compe ence,
Inequi y,
Manage ial
Beha io ,
T anspa ency,
Technological
Impac , Beha io al
T ai , Cus ome
Sa is ac ion,
Loyal y, Posi i e
Expe iences,
In o ma ion
Quali y,
Dis inguishing
T us wo hiness,
Encou aging
T us wo hy
Beha io ,
Discou aging
Un us wo hy
Pa icipa ion,
Recommenda ion
Accu acy, T us
Li e acy Le els,
G a i ude,
Emo ional T us ,
No ma i e T us ,
O ganiza ional
No ms, C ea i e
Des uc ion,
Se ice Quali y,
B and Iden i y,
T us Sensi i i y,
Co po a e Social
Responsibili y,
Co po a e
Repu a ion, P ice
Sensi i i y, Repea
Pu chases
(Akhmedo a,
Vila-B une &
Mas-Machuca,
2020; Ash a i &
Easmin, 2023;
Ba ane e al.,
2021; Bilal e al.,
2024; Chohan
e al., 2022; Cse di
e al., 2022;
Dąb owska,
Ozimek &
H abynska, 2024;
Demi el, 2022;
Hallikainen,
Hi onen &
Laukkanen, 2020;
Mus a a e al.,
2022; Sama,
S e anidis &
Casselman, 2022;
Va ankhah
Ba enji, 2022;
Wzią ek-S a´
sko &
Pobiedzi´
nska,
2024; Yamamo o
e al., 2022; Yunus
e al., 2022)
Employees
Adap a ion (EA)
Cus ome
Con idence,
Go e nmen
Suppo ,
Managemen
Suppo , Social
Technologic
Ladde , ICT
Componen T us ,
Employee Digi al
Beha io s,
Emo ional T us ,
Cogni i e T us ,
O ganiza ional
T us , Design
Fea u es o T us
(Gkinko &
Elbanna, 2023;
Jain, Ajme a &
Da im, 2022;
Ma cial e al.,
2024)
Employees
T aining (ET)
Da a T us ,
Analy ical Models,
(Bencsik, Ha gi ai
& Kulachinskaya,
(con inued on nex page)
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
3
amewo k mo es beyond indi idual echnology accep ance o explo e
how he in e sec ion o echnology, o ganiza ional s uc u e, and p o-
cess p inciples shapes s akeholde s’ con idence in an o ganiza ion’s
digi al in e ac ions, o e ing a mo e obus and comp ehensi e
pe spec i e on digi al us in he mode n age. The concep ualiza ion o
his amewo k e ol es a ound wo key p oposi ions ha a icula e
how each se o ac o s in luences he o e all le el o digi al us .
Toge he , hey c ea e a comp ehensi e app oach o unde s anding and
os e ing digi al us in an o ganiza ion. Below, i is explained how each
p oposi ion is de eloped and each men ioned mac o- ac o , de ined in
Table 1, con ibu es o enhancing he le el o digi al us .
O ganiza ion- ela ed ac o s
A he hea o his amewo k a e o ganiza ional- ela ed ac o s ha
signi ican ly shape digi al us (Capes o e al., 2024; S i as a a e al.,
2022). These ac o s p o ide he s uc u al and cul u al suppo needed
o os e a secu e and us wo hy digi al en i onmen , aligning closely
wi h TAM’s emphasis on pe cei ed ease o use and use ulness. Fi e key
o ganiza ional ac o s ha e been iden i ied as c i ical o he de elop-
men o digi al us : Top Managemen De ined S a egies (TMDS),
Sp ead o Digi al Cul u e (SC), Employee Adap a ion (EA), Employee
T aining (ET), and Technos ess (TS). The ole o op managemen in
shaping digi al us canno be o e s a ed. TMDS a e pi o al in se ing
he di ec ion o digi al ans o ma ion wi hin he o ganiza ion. When
leade ship ac i ely de ines and suppo s digi al ini ia i es, hey no only
alloca e esou ces bu also embed digi al e o s wi hin he b oade
o ganiza ional goals, which inc eases pe cei ed use ulness among em-
ployees (Lu hans & Yousse , 2007). Resea ch indica es ha s a egic
in ol emen om leade ship os e s a sense o eliabili y and pu pose in
digi al ans o ma ion e o s, making hese echnologies eel mo e in-
eg a ed in o he o ganiza ional landscape. This alignmen is c ucial o
building digi al us because i eassu es employees ha he o ganiza-
ion is commi ed o secu ely and e ec i ely managing digi al ools (Lau
& H¨
oyng, 2023). Nume ous schola s ha e emphasized ha e ec i e
leade ship in he digi al con ex has a signi ican posi i e impac on a
i m’s o e all inno a ion pe o mance, c ea ing e ile g ound o he
de elopmen and enhancemen o digi al us (Beni ez e al., 2022;
Fa ima & Masood, 2024; Mo e al., 2023). By os e ing an en i onmen
conduci e o digi al ans o ma ion, digi al leade s c ea e he condi ions
necessa y o us o lou ish, as hey guide he o ganiza ion in adop ing
Table 1 (con inued)
Mac o-Fac o s Fac o s A ec ing
Digi al T us
Re e ences
In e p e i e
Capabili ies,
Digi al Skills,
Managemen
Suppo , Pe cei ed
Use ulness,
Pe cei ed Ease o
Use, Pe cei ed
Secu i y, Risk-F ee
Expe ience
2022; Ku niasa i,
Gunawan &
U omo, 2022))
PROCESS-
RELATED
FACTORS
P ocess
Au oma ion
(PA)
De ice
Au hen ica ion,
Da a T us ,
Augmen ed
In elligence,
Specula i e
Beha io , Asse
Speci ici y,
In e pe sonal
T us , T ansac ion
Cos s, P ope y
Righ s, Sys em-
Based T us ,
Cogni ion-Based
T us , In o ma ion
Sha ing, Sma
Con ac s,
Con ac
En o cemen ,
P ice, Pas
T ansac ions,
B oad-Scope T us ,
Thi d-Pa y
Ce i ica ions,
Legal S uc u es,
Goodwill T us ,
Communica ion
E ec i eness,
Rela ional Value,
Digi al
T ans o ma ion,
In o mal
Go e nance, T us
Issues, P ocess
Quali y, Risk,
T us Mining,
T us Policies,
P ocess Resilience,
Cogni i e T us ,
A ec i e T us ,
Taci Knowledge
Sha ing,
Technological and
O ganiza ional
Fac o s
(Capes o e al.,
2024; Fa uquee,
Paul aj & I awan,
2021; Guo & Yao,
2022; Komdeu &
Ingenbleek, 2021;
Mulle e al., 2021;
Qian and
Papadonikolaki
2021b; Singh &
Pa k, 2023)
Acciden
Reduc ion (AR)
Risk Managemen ,
Sa e y P o ocols,
Compliance
S anda ds, Haza d
Iden i ica ion,
Inciden Analysis
(Fa uquee e al.,
2021; Jain e al.,
2022; Kuma , Liu
& Shan, 2020;
Shin, 2019).
In o ma ion
T aceabili y (IT)
Da a Secu i y
Conce ns, Di ec -
T us , Public-
Re iew, Audi o -
T us , T us
Calcula ion
Func ions, T us in
Blockchain,
Pe cei ed
Secu i y, P i acy
P o ec ion,
A i udes Towa d
Blockchain, Use
T ai s, Da a
(Alqah ani &
Albaha , 2022;
Chahal & Singh,
2017; E z & Boily,
2019; Kuma &
Chop a, 2022;
Kuma , Liu &
Shan, 2020;
Mazzei e al.,
2020; Roge son &
Pa y, 2020; Tan
& Sa aniemi,
2023; T eiblmaie
& Go buno 2022;
Table 1 (con inued)
Mac o-Fac o s Fac o s A ec ing
Digi al T us
Re e ences
Access, Da a
Owne ship, Da a
Sha ing, P i acy,
P ope y Righ s,
Secu i y Fea u es,
U ili y Fea u es,
In eg i y,
Pe cei ed Risk,
T us , P i acy,
T us and
Visibili y,
In o ma ion
Accu acy, Speed o
In o ma ion,
In o ma ion
Abundance,
T anspa ency,
P i acy P o ec ion
T i edi e al.,
2022)
Cos and
Du a ion o
Digi al
T ans o ma ion
(CDM)
Cos E iciency,
Du a ion o
Implemen a ion,
Budge Adhe ence,
Time- o-Value,
Cos Reduc ion,
(Fa uquee e al.,
2021; Gkinko &
Elbanna, 2023;
Kuma e al.,
2020)
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
4
secu e, e icien , and inno a i e digi al p ac ices. This alignmen o
leade ship wi h echnological ad ancemen ein o ces employees’ con-
idence in he o ganiza ion’s digi al capabili ies, u he suppo ing he
p oposi ion ha o ganiza ional- ela ed ac o s a e key an eceden s o
digi al us . Ano he c i ical ac o is he SDC, which p omo es an
en i onmen whe e digi al ini ia i es a e emb aced and no malized. A
obus digi al cul u e os e s openness, inno a ion, and collabo a ion, all
o which a e key o ensu ing ha employees us and u ilize digi al ools
e ec i ely. S udies ha e shown ha o ganiza ions wi h a s ong digi al
cul u e see highe accep ance o new echnologies, as employees
pe cei e hem as bo h use ul and easy o use (Wzią ek-S a´
sko &
Pobiedzi´
nska, 2024; Yunus e al., 2022). Resea ch indica es ha cul u e
signi ican ly in luences echnology adop ion and de elopmen p ocesses
(Bu e al., 2024; Gu baxani & Dunkle, 2019; Leidne & Kaywo h,
2006). Leade s mus na iga e bo h in e nal and ex e nal cul u al land-
scapes o acili a e digi al ans o ma ion (Volbe da e al., 2021).
Neglec ing hese cul u al dynamics can hinde us -building wi hin
o ganiza ions and wi h pa ne s (Kolaga , Pa ida & Sj¨
odin, 2022).
Success ul cul u al e eshmen du ing ans o ma ions can d i e
necessa y shi s in mindse and capabili ies (Ghosh e al., 2022; Wa ne
& W¨
age , 2019). This cul u al suppo also aligns wi h TAM, as i en-
hances bo h he pe cei ed ease o use and use ulness o digi al ech-
nologies, c ucial ac o s o building us .
EA o digi al echnologies is ano he c ucial componen o os e ing
digi al us . Employees’ abili y o e ec i ely in eg a e digi al ools in o
hei wo k lows is o en in luenced by he le el o suppo p o ided by
he o ganiza ion. When o ganiza ions in es in os e ing adap abili y
h ough a suppo i e lea ning en i onmen , employees a e mo e likely
o pe cei e digi al ools as easy o use and bene icial, enhancing bo h
hei us in he echnology and hei willingness o adop i (Ma cial
e al., 2024). A s uc u ed adap a ion p ocess is key o os e ing digi al
us , especially among new employees. When expec a ions a e clea ly
communica ed and he onboa ding p ocess is consis en ac oss de-
pa men s, i no only p o ides cla i y bu also demons a es he o ga-
niza ion’s eliabili y and anspa ency (Su alo a e al., 2021). This
sense o p edic abili y helps employees eel mo e secu e in na iga ing
digi al sys ems and us ing he o ganiza ion’s digi al en i onmen . This
again aligns wi h TAM’s asse ion ha pe cep ions o ease o use and
use ulness d i e echnology accep ance. In andem wi h adap a ion, ET
is essen ial o building digi al us . Comp ehensi e and ongoing
aining p og ams equip employees wi h he skills and con idence
needed o use digi al ools e ec i ely (Gkinko & Elbanna, 2023).
E ec i e aining inc eases employees’ pe cei ed ease o use and
pe cei ed use ulness o hese ools, bo h o which a e cen al o TAM’s
amewo k. Acco ding o Goula e al. (2021), one o he main ba ie s
o e ec i e digi al ans o ma ion o manage s was he lack o
comp ehensi e employee aining in bo h pe sonal and echnical skills.
This aining is essen ial o building digi al us , as employees who a e
well-p epa ed h ough a ge ed aining p og ams a e mo e likely o eel
con iden in using new digi al ools and sys ems. As a esul , o ganiza-
ions ha p io i ize aining a e be e able o cul i a e digi al us by
ensu ing ha employees eel compe en and con iden in using he
echnology. Las ly, he issue o TS mus be add essed o sus ain digi al
us . TS e e s o he anxie y o s ess employees expe ience when
adap ing o new digi al ools and p ocesses. S udies ha e shown ha
o ganiza ions ha manage echnos ess e ec i ely— h ough suppo
sys ems and a posi i e wo k en i onmen —a e be e able o os e
digi al us (Ayyaga i e al., 2011; Ma cial e al., 2024). By educing he
nega i e impac s o echnology on employee well-being, o ganiza ions
can enhance us by making digi al ools eel mo e manageable and less
o e whelming. Toge he , hese o ganiza ional- ela ed ac o s—TMDS,
SDC, EA, ET, and TS— o m he bed ock o digi al us . I e ec i ely
managed, hese ac o s could c ea e an en i onmen whe e employees
eel suppo ed, equipped, and con iden in hei in e ac ions wi h digi al
ools, which aligns closely wi h TAM’s ocus on pe cei ed ease o use
and use ulness. In ligh o his, he ollowing p oposi ion is o mula ed:
P oposi ion 1.O ganiza ional- ela ed ac o s a e an eceden s o digi al
us .
P ocess- ela ed ac o s
P ocess- ela ed ac o s play a pi o al ole in shaping and in luencing
digi al us wi hin o ganisa ions. While o ganiza ional ac o s p o ide
he g oundwo k o digi al us , p ocess- ela ed elemen s ensu e i s
ope a ionaliza ion. P ocess- ela ed ac o s ha in luence digi al us
include P ocess Au oma ion (PA), Acciden Reduc ion (AR), In o ma ion
T aceabili y (IT), and Cos and Du a ion o Digi al T ans o ma ion
(CDM). PA enhances he eliabili y and e iciency o wo k lows. Au o-
ma ion minimizes human e o , educes edundancy, and s eamlines
ope a ions, making digi al p ocesses mo e p edic able and dependable.
This consis ency ins ils con idence among employees, who come o ely
on au oma ed sys ems as us wo hy componen s o hei wo k en i-
onmen . Resea ch shows ha au oma ion signi ican ly enhances
pe cei ed ease o use and pe cei ed use ulness, he eby os e ing digi al
us (Guo & Yao, 2022; Qian & Papadonikolaki, 2021). Ano he c i ical
p ocess- ela ed ac o is linked o sa e y, pa icula ly he ole o digi al
sys ems in Acciden Reduc ion (AR). Technologies ha imp o e wo k-
place sa e y no only p o ec employees bu also build us , as hey a e
seen as eliable and essen ial o main aining a secu e en i onmen .
Employees a e mo e likely o us sys ems ha con ibu e o hei
well-being, ein o cing he pe cep ion o hese echnologies as bo h
use ul and easy o in e ac wi h. S udies ha e shown ha when digi al
sys ems con ibu e o a sa e wo king en i onmen , us in hese sys-
ems inc eases (Shin, 2019). This aligns wi h TAM, as sa e y-enhancing
echnologies a e pe cei ed as use ul and easy o use. In o ma ion
aceabili y (IT) is also cen al o es ablishing us . T anspa en and
audi able digi al p ocesses allow o accoun abili y, ensu ing ha ac-
ions wi hin he sys em can be acked and e i ied. This anspa ency
builds us by demons a ing ha he echnology is no only unc ional
bu also ai and dependable. Resea ch indica es ha anspa ency and
aceabili y in in o ma ion p ocesses signi ican ly imp o e pe cei ed
Fig. 1. Concep ual amewo k (Au ho ’s own elabo a ion).
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
5
ease o use and pe cei ed use ulness, leading o highe le els o digi al
us (Tan & Sa aniemi, 2023; T eiblmaie & Go buno , 2022) em-
ployees can ace and audi digi al ac i i ies, hei con idence in he
sys em’s eliabili y and in eg i y inc eases, aligning wi h TAM’s
emphasis on pe cei ed use ulness and ease o use. Finally, CDM signi -
ican ly impac s digi al us because p ojec s ha a e comple ed e i-
cien ly, on ime, and wi hin budge a e iewed as mo e eliable,
os e ing us in bo h he p ocess and he digi al ools in ol ed. When
digi al ans o ma ions a e well-managed, employees a e mo e likely o
pe cei e he esul ing sys ems as aluable and s aigh o wa d, u he
ein o cing us in he o ganiza ion’s echnological di ec ion. S udies
sugges ha well-managed digi al ans o ma ions enhance pe cei ed
ease o use and pe cei ed use ulness, he eby os e ing digi al us
(Gkinko & Elbanna, 2023). D awing on hese p emises, he second
p oposi ion is de eloped:
P oposi ion 2.P ocess- ela ed ac o s a e an eceden s o digi al us .
In line wi h p e ious con ibu ions (Huang e al., 2022; Yao and Li
2023), analyzing hese p oposi ions using sQCA will p o ide a nuanced
unde s anding o how a ious combina ions o ac o s con ibu e o
digi al us . This me hodological app oach allows o unco e he
complex causal ela ionships ha d i e us in digi al en i onmen s,
he eby o e ing aluable insigh s o bo h esea che s and p ac i ione s
(K aus, Ribei o-So iano & Schüssle , 2017; Roig-Tie no, Hua ng &
Ribei o-So iano, 2016). Fu he mo e, sQCA’s capaci y o empi ical
iden i ica ion o success pa hs and i s adap abili y o ollow-up analysis
make i a aluable ool o gaining comp ehensi e insigh s in o digi al
us dynamics. By in eg a ing he Technology Accep ance Model wi h
o ganiza ional and p ocess heo ies, a mo e holis ic unde s anding o
he an eceden s o digi al us can be de eloped, ul ima ely con ib-
u ing o mo e e ec i e digi al ans o ma ion s a egies.
Me hodology
Da a
The sampling s a egy o his s udy was designed wi h se e al key
conside a ions o ensu e he ele ance and dep h o he analysis. I alian
manu ac u ing companies we e selec ed o ocus on a sec o ha is
c i ically impo an o he coun y’s economy as well as signi ican ly
impac ed by echnological ad ancemen s (Ga y & Shih, 2009). The
manu ac u ing sec o was chosen o comp ehensi ely ocus on he im-
pac s o echnologies on bo h he p oduc ion p ocess and he o ganisa-
ional and manage ial aspec s. The companies we e selec ed by choosing
hose belonging o he ATECO sec ion: Manu ac u ing Ac i i ies and
who ha e collabo a ed wi h he Uni e si y o Naples Fede ico II in p io
digi aliza ion p ojec s. By selec ing companies om he ATECO sec ion
o Manu ac u ing Ac i i ies, he s udy ensu es ha he sample is
well-de ined and ep esen a i e o he manu ac u ing indus y. The
ATECO code, which is analogous o in e na ional classi ica ion sys ems
like ISIC, p o ides a s anda dized way o ca ego ize businesses, ensu ing
consis ency and compa abili y in he da a collec ed (Is a , 2007; Uni ed
Na ions, 2008). Fu he mo e, he p e-exis ing ela ionship o companies
in Uni e si ies’ p ojec s inc eased he willingness o companies o
pa icipa e and p o ided a sample al eady amilia wi h echnological
ad ancemen s, which is ele an o he s udy’s ocus on echnology
impac s (Pe kmann & Walsh, 2007; Rosenbe g, 1990). The companies
we e selec ed o co e a wide ange o sizes (mic o, small, medium, and
la ge en e p ises), geog aphic a eas (No h, Cen e , Sou h and Islands),
and indus y sec o s (e.g., Food, Pha maceu ical/Cosme ics, Mechani-
cal, Elec ical/Elec onic). This di e si y ensu es ha he indings can be
gene alized ac oss di e en con ex s wi hin he manu ac u ing sec o
(Pa on, 2014; Yin, 2014). Companies in ol ed in p io digi aliza ion
p ojec s we e speci ically a ge ed o align wi h he s udy’s emphasis on
echnology’s impac . This ensu es ha he pa icipan s ha e ele an
expe ience and insigh s in o he echnological changes and hei e ec s
on manu ac u ing p ocesses and o ganiza ional s uc u es (B ynjol sson
& McA ee, 2014; Geissbaue , Vedso & Sch au , 2016). Ou o o e 300
companies con ac ed, 62 ag eed o pa icipa e, and 50 we e deemed
sui able o analysis. This selec ion p ocess ensu ed ha he inal sample
was no only willing bu also me he c i e ia necessa y o he s udy,
hus enhancing he eliabili y and alidi y o he esul s (Ba uch &
Hol om, 2008; G o es & Pey che a, 2008). Table A1 in he appendix
p esen s de ails o he pa icipan s who ook pa in he s udy.
Analy ical app oach
Once he s udy’s a iables had been iden i ied h ough he li e a u e
e iew, he ques ionnai e was designed. The su ey was in I alian and
comp ised o ou sec ions. The i s sec ion in es iga es companies’
adop ion o Indus y 4.0 echnologies by explo ing he ypes imple-
men ed om he 9 mac o-ca ego ies de ined by Bos on Consul ing
G oup (Rüβmann e al., 2015) and ime since in oduc ion. In his i s
sec ion, he sample o esponden s was na owed down o only hose
om companies ha ha e adop ed Indus y 4.0 echnologies o a leas
one yea . The second sec ion ega ds esponden s and he company’s
socio-demog aphic in o ma ion. In he hi d sec ion, esponden s we e
in i ed o answe by exp essing hei le el o ag eemen o disag eemen
on a i e-i em Like scale anging om 1 =“S ongly disag ee” o 5 =
“S ongly ag ee” abou o ganiza ional- ela ed ac o s and
p ocess- ela ed ac o s. Fo ins ance, conce ning he TMDS a iable, he
inqui y was amed as ollows: "Following he in oduc ion o Indus y
4.0 echnologies, he op managemen has es ablished app op ia e
s a egies o p omo e digi al ans o ma ion”. Finally, in he ou h
sec ion, esponden s we e asked o a e hei le el o eelings o us
a e he implemen a ion and use o echnologies on a i e-i em Like
scale anging om 1 =“S ongly disag ee” o 5 =“S ongly ag ee”. In
pa icula , he ques ion was: “A e he implemen a ion and u iliza ion
o Indus y 4.0 echnologies, he e has been an inc ease in employees’
us in hem”. Mo e in de ail, he ques ionnai e was designed no o gi e
he in e iewee he imp ession o speci ically analysing us le els o
ensu e unbiased esponses.
Fuzzy se quali a i e compa a i e analysis
The me hodology employed is quali a i e compa a i e analysis
(QCA). QCA is a da a analysis echnique ha combines he logic o a
quali a i e app oach wi h quan i a i e me hods (Ragin, 2008). In
pa icula , in his esea ch, uzzy se quali a i e analysis (FsQCA) has
been chosen o iden i y necessa y and unnecessa y condi ions o he
mani es a ion o he ou come and o de e mine which combina ions o
condi ions a e mo e impo an han o he s. The choice ell on his
app oach because i o e comes he weaknesses o adi ional s a is ical
me hodologies (e.g., s uc u al equa ion modelling, simple eg essions,
e c.) and allows esea che s o p edic complex and unce ain phe-
nomena (Daniel & Daniel, 2019; Tapsell & Woods, 2010). Indeed, ac-
co ding o Kuma e al. (2022), he e has been an inc ease in he numbe
o s udies adop ing FsQCA and complex heo y in business and man-
agemen esea ch, wi nessing he s eng hs and po en ial o his me h-
odology in he ield. Fu he mo e, his app oach is pa icula ly use ul
wi h a limi ed sample size (up o 50 cases) (G eco e al., 2022;
He n´
andez-Pe lines, Mo eno-Ga cia & Y´
a˜
nez-A aque, 2016). The
me hodology comp ises se e al s eps. The p ocess begins wi h da a
calib a ion, con e ing aw da a in o uzzy se sco es be ween 0 and 1,
whe e 1 indica es ull membe ship and 0 indica es non-membe ship
(Ragin, 2008). This s udy used indi ec calib a ion, selec ing h esh-
olds based on da a dis ibu ion, wi h alues o 4, 3, and 2 o calib a ion
as p esen ed in Table 2. Fo ins ance, "S ongly ag ee" is calib a ed o 1,
"S ongly disag ee" o 0, and "Neu al" o 0.5. Nex , a u h able is
cons uc ed o iden i y causal combina ions su icien o p oduce he
ou come. The able includes all possible combina ions o causal condi-
ions and shows he numbe o cases o each combina ion, as well as he
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
6
consis ency o each con igu a ion in p oducing he ou come. Necessa y
condi ions a e analyzed o de e mine i hei p esence is essen ial o he
ou come (Ragin, 2008). FsQCA hen uses Boolean minimiza ion o
iden i y combina ions o condi ions su icien o he ou come, e alu-
a ed based on consis ency (how o en he ou come occu s wi h a speci ic
condi ion) and co e age (how much o he ou come is explained by each
con igu a ion) (Ragin, 2008; Schneide & Wagemann, 2012; Thiem,
Baumga ne & Bol, 2015). Consis ency abo e 0.7 indica es a necessa y
condi ion, while su icien condi ions equi e consis ency abo e 0.7 and
co e age o a leas 0.5. FsQCA p oduces h ee solu ions: complex,
pa simonious, and in e media e. The complex solu ion a oids simpli-
ying assump ions, he pa simonious solu ion minimizes condi ions, and
he in e media e solu ion balances complexi y by in eg a ing some
simpli ying hypo heses (Schneide e al., 2010; Schneide & Wagemann,
2012). The wo models analysed a e as ollows:
Model 1: Digi al T us = (TMDS, SDC, EA, ET, TS);
Model 2: Digi al T us = (PA, AR, IT, CDM).
Analysis o he esul s
Desc ip i e analysis
Table 3 p o ides he socio-demog aphic cha ac e is ics o bo h he
su ey esponden s and hei companies. Mos esponden s we e male
(82 %), wi h a smalle p opo ion being emale (18 %). Responden s
we e ai ly e enly dis ibu ed ac oss age g oups, wi h 26 % unde 35, 26
% be ween 36 and 45, and 48 % o e 35. A signi ican po ion o e-
sponden s held a mas e ’s deg ee (62 %) o abo e (Doc o a e - 22 %).
Fu he mo e, he majo i y o esponden s held manage ial oles (74 %),
while some we e in p oduc ion a eas (12 %), and comme cial/admin-
is a i e a eas (10 %).
Conce ning he socio-demog aphic ac o s o he companies, he
p esence o women in he wo k o ce is e y low, wi h 38 % epo ing
<20 % women and also <20 % o he employees holding a bachelo ’s
deg ee. The a e age age o employees skewed owa ds he 36–45 age
g oup (64 %). The mechanical sec o was he mos ep esen ed (30 %),
ollowed by he ood sec o (22 %), elec ical/elec onic (10 %), and
o he s wi h smalle pe cen ages. Companies we e sp ead ac oss he
No h (46 %), Cen e (28 %), and Sou h/Islands (26 %). Mos companies
ell in o he small (32 %) and medium (40 %) size ca ego ies.
Conce ning he adop ion o Indus y 4.0 echnologies, cloud ech-
nology is widely adop ed, wi h hal o he companies in he s udy
le e aging cloud se ices. This indica es a signi ican eliance on cloud
in as uc u e o da a s o age, p ocessing, and o he business ope a-
ions. Big Da a Analy ics (BDA) is also p e alen , being adop ed by a
subs an ial po ion o companies (36 %). This sugges s a ecogni ion o
he impo ance o analysing la ge da ase s o gain aluable insigh s and
in o m decision-making p ocesses. Blockchain echnology adop ion is
mode a e, wi h 16 % o companies inco po a ing i in o hei ope a ions.
This may indica e a speci ic in e es in decen alised and secu e ans-
ac ional sys ems. A i icial in elligence (AI) adop ion is on pa wi h
blockchain, indica ing ha a no able bu no dominan p opo ion o
Table 2
Fuzzy-se membe ship calib a ions (Au ho ’s own elabo a ion).
Va iable Name Type Fully
in
C osso e Fully
ou
Mean De
S .
Digi al T us le el
(DT)
Ou come 4 3 2 3.74 0.69
Top Managemen
De ined
S a egies
(TMDS)
An eceden 4 3 2 4.08 0.77
Sp ead o Digi al
Cul u e (SDC)
An eceden 4 3 2 4.02 0.91
Employee
Adap a ion
(EA)
An eceden 4 3 2 2.98 0.86
Employees
T aining (ET)
An eceden 4 3 2 3.96 0.60
P ocess
Au oma ion
(PA)
An eceden 4 3 2 3.82 1.01
Acciden
Reduc ion (AR)
An eceden 4 3 2 3.88 1.03
In o ma ion
T aceabili y
(IT)
An eceden 4 3 2 4.32 0.68
Cos and
Du a ion o
Digi al
T ans o ma ion
(CDM)
An eceden 4 3 2 3.88 0.82
Table 3
Socio-demog aphic s a is ics (Au ho ’s own elabo a ion).
Socio-demog aphic Fac o s o he esponden s
F equency Pe cen age
Gende
Female 9 18 %
Male 40 80 %
P e e no o disclose 1 2 %
Age g oup
unde 35 13 26 %
36–45 13 26 %
o e 35 24 48 %
Educa ion
High school 8 16 %
Mas e ’s deg ee 31 62 %
Doc o a e 11 22 %
Role
Manage ial oles ( op execu i es, CEOs) 37 74 %
Employees in p oduc ion a eas 6 12 %
Employees in he comme cial and adminis a i e a eas 5 10 %
O he s 2 4 %
Socio-demog aphic ac o s o he companies
Women in he Wo kplace
<20 % 19 38 %
>80 % 3 6 %
20 %−40 % 17 34 %
40 %−60 % 8 16 %
60 %−80 % 3 6 %
A e age age o employees
18–25 1 2 %
26–35 12 24 %
36–45 32 64 %
o e 45 5 10 %
Employees Bachelo ’s Deg ee Holde s
unde 20 % 21 42 %
20 %−40 % 15 30 %
41 %−60 % 9 18 %
61 %−80 % 3 6 %
o e 80 % 2 4 %
Indus y sec o
Mechanical 15 30 %
Food Sec o 11 22 %
Elec ical/Elec onic 5 10 %
Pha maceu ical/Cosme ics 5 10 %
Fu ni u e 2 4 %
Indus ial Au oma ion - Mecha onics 2 4 %
Plas ic 2 4 %
O he 8
Geog aphic a ea
No h 23 46 %
Cen e 14 28 %
Sou h and islands 13 26 %
Company size
Mic o (<10 employees) 4 8 %
Small (<50 employees) 16 32 %
Medium (<250 employees) 20 40 %
La ge (o e 250 employees) 10 20 %
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
7
companies a e in eg a ing AI echnologies. AI can enhance a ious as-
pec s o business ope a ions, including au oma ion and p edic i e ana-
ly ics. In e ne o Things (IoT) adop ion is compa a i ely lowe , wi h
only 10 % o companies implemen ing IoT echnologies. This migh
sugges ha while IoT has i s applica ions, i is no as uni e sally
emb aced as o he echnologies. In addi ion, conce ning he empo al
dimension associa ed wi h he adop ion and in eg a ion o Indus y 4.0
echnologies among he su eyed companies, a signi ican majo i y,
comp ising 76 % o esponden s, alls wi hin he 1–3-yea span, indi-
ca ing a ecen and widesp ead emb ace o hese inno a i e echnolo-
gies. Meanwhile, a no able 20 % o companies ha e been na iga ing he
Indus y 4.0 landscape o a du a ion spanning 4–10 yea s, showcasing a
sus ained commi men o echnological ad ancemen . A smalle ye
no ewo hy 4 % o esponden s boas ema kable longe i y in he in e-
g a ion p ocess, wi h hei jou ney ex ending o e a decade. Table 4
summa ises he esul s discussed.
Analysis o necessa y and su icien condi ions
The analysis o necessa y and su icien condi ions was pe o med
h ough sQCA so wa e. In he models, calib a ed a iables a e deno ed
wi h he su ix "_c", and he ilde (~) e e s o he absence o he con-
di ion. As men ioned in Sec ion 3.3, consis ency mus be highe han
0.70 o condi ions o be necessa y (Ragin, 2006, p. 293). In model 1,
a iables TMDS_c, SDC _c and ET_c a e deemed necessa y o he
mani es a ion o he ou come. Speci ically, he a iable SDC_c exhibi s
he highes consis ency le el. The op managemen should communica e
o employees he impo ance o adop ing new echnologies by os e ing
a digi al cul u e wi hin he o ganisa ion. In model 2, all he a iables a e
necessa y o he mani es a ion o he ou come. The a iable IT_c has he
highes consis ency le el, indica ing a s ong connec ion be ween his
a iable and he ou come. P esumably, he bene i s in e ms o con ol
and eliabili y ha e been demons a ed and app ecia ed a e he
implemen a ion o echnologies, hus jus i ying he impac on digi al
us le els. Con e sely, consis ency alues o nega ed condi ions a e all
<0.7 in bo h models. Resul s a e summa ised in Table 5.
Following he analysis o necessa y condi ions, su icien condi ions
a e e alua ed (Tables 6 and 7). Rega ding model 1, The in e media e
and complex solu ions (TDMS_c * SDC_c * ET_c) p o ide a high deg ee o
explana ion and eliabili y o digi al us , wi h high consis ency (0.88)
and co e age (0.88). The pa simonious solu ions, while somewha
e ec i e, do no ma ch he obus ness o he in e media e solu ion.
Conside ing model 2, The IT_c condi ion in he pa simonious solu ion is
highly e ec i e wi h a aw co e age o 0.997 and a consis ency o 0.85,
uniquely co e ing almos all ou come cases. In he in e media e and
complex solu ions, bo h CDM_c * IT_c and AR_c * IT_c con igu a ions
demons a e high co e age and consis ency, wi h AR_c * IT_c showing
he highes consis ency. These wo combina ions o condi ions lead o
s ong digi al us wi h high consis ency, espec i ely equal o 0.87 o
he i s combina ion and 0.92 o he second combina ion. Bo h com-
bina ions sha e he p esence o IT_c which is also a necessa y condi ion.
Discussion
The analysis o digi al us in Model 1 and Model 2 e eals i s
mul i ace ed na u e and he in e ac ions be ween a ious in luencing
ac o s. Model 1 iden i ies TMDS, SDC, and ET as he mos signi ican
o ganiza ional ac o s a ec ing digi al us . These ac o s a e necessa y
o he ou come o occu , and hei combina ion c ea es a su icien
condi ion o os e ing us . The model highligh s ha he combina ion
o TMDS, SDC, and ET leads o he highes consis ency and co e age o
building digi al us (Consis ency: 0.881). This demons a es ha dig-
i al us is no jus a ma e o s a egy o aining in isola ion bu e-
qui es a synch onized e o ac oss all h ee a eas. The heo e ical
no el y lies in his iadic ela ionship whe e digi al cul u e ampli ies
he e ec s o s a egic di ec ion and aining, showing a pa h o u u e
esea ch on mul i- ac o digi al adap a ion models. This is consis en
wi h Kane e al. (2015) who ound ha o ganiza ions p io i izing
s a egy o e echnology a e mo e success ul in digi al ans o ma ion.
Thei esea ch emphasizes ha a clea digi al s a egy led by op man-
agemen is c i ical o success, echoing ou indings on TMDS’s impac
on digi al us . O ganiza ional beha io esea ch also suppo s he need
o op managemen suppo and s a egic alignmen in building a
us wo hy digi al en i onmen (Lau & H¨
oyng, 2023; Lu hans and
Yousse , 2007).
The ole o SDC aligns wi h Kane e al.’s iew ha a s ong digi al
cul u e is essen ial o achie ing digi al ma u i y. Ou indings con i m
ha a cul u e o openness and collabo a ion enhances us in digi al
ools, pa alleling he Cus ome Rela ionship Managemen (CRM) model
ha links anspa ency and inno a ion o us and sa is ac ion (Yunus
e al., 2022). Addi ionally, ET’s signi icance mi o s Venka esh e al.
(2016) who s essed ha use knowledge and compe ence a e i al o
os e ing posi i e a i udes owa d new echnologies. E ec i e aining
boos s employees’ con idence in using digi al ools, inc easing hei us
in hese echnologies (Gkinko & Elbanna, 2023), unde sco ing he need
o comp ehensi e aining p og ams o add ess pe cei ed ease o use
and use ulness (Ma cial e al., 2024).
In Model 2, p ocess- ela ed ac o s a e examined, e ealing di e en
Table 4
Indus y 4.0 adop ion and di usion le el (Au ho ’s own elabo a ion).
Le el o adop ion o Indus y 4.0 echnologies F equency Pe cen age
Cloud 25 50 %
BDA 18 36 %
Blockchain 8 16 %
AI 8 16 %
IoT 5 10 %
Time om he in oduc ion and implemen a ion o
Indus y 4.0 echnologies
1–3 yea s 38 76 %
4–10 yea s 10 20 %
o e 10 yea s 2 4 %
Table 5
Analysis o necessa y condi ions (Au ho ’s own elabo a ion).
Model 1
Va iables Consis ency Co e age
TMDS_c 0.941401 0.861305
SDC_c 0.949045 0.871345
EA_c 0.568153 0.923395
ET_c 0.938854 0.841324
TS_c 0.495541 0.876126
~TMDS_c 0.157962 0.873239
~SDC_c 0.147771 0.800000
~EA_ c 0.555414 0.843327
~TS_c 0.624204 0.881295
~ET_c 0.157962 1.000000
Model 2
Va iables Consis ency Co e age
CDM_c 0.880255 0.846814
PA_c 0.878981 0.892626
AR_c 0.892994 0.912760
IT_c 0.997452 0.845572
~CDM_c 0.222930 0.951087
~PA_c 0.219108 0.757709
~AR_c 0.248408 0.840517
~IT_c 0.071338 0.756757
No es: Highligh ed ows indica e ha he condi ion’s consis ency eaches he
0.75 e e ence poin .
(Abb e ia ions: Top Managemen De ined S a egies (TMDS); Sp ead o Digi al
Cul u e (SDC); Employee Adap a ion (EA); Employee T aining (ET); Techno-
s ess (TS); P ocess Au oma ion (PA); Acciden Reduc ion (AR); In o ma ion
T aceabili y (IT); Cos and Du a ion o Digi al T ans o ma ion (CDM)).
S. S azzullo
Jou nal o Inno a ion & Knowledge 9 (2024) 100621
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