Sahibzada, Uma Fa ooq; Janjua, Nadia Aslam; A sha i, Leila; Shakil, Muhammad
A icle
Leading he ansi ion owa d sus ainabili y h ough
digi al capabili ies and digi al inno a ion: The ole o
employee cha ac e is ics
Jou nal o Inno a ion & Knowledge (JIK)
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: Sahibzada, Uma Fa ooq; Janjua, Nadia Aslam; A sha i, Leila; Shakil, Muhammad
(2025) : Leading he ansi ion owa d sus ainabili y h ough digi al capabili ies and digi al
inno a ion: The ole o employee cha ac e is ics, Jou nal o Inno a ion & Knowledge (JIK), ISSN
2444-569X, Else ie , Ams e dam, Vol. 10, Iss. 3, pp. 1-12,
h ps://doi.o g/10.1016/j.jik.2025.100723
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Leading he ansi ion owa d sus ainabili y h ough digi al capabili ies and
digi al inno a ion: The ole o employee cha ac e is ics
Uma Fa ooq Sahibzada
a
, Nadia Aslam Janjua
b
, Leila A sha i
c,*
, Muhammad Shakil
d
a
Business School o he C ea i e Indus ies, Uni e si y o he C ea i e A s, Epsom Campus (KT18 5BE), Uni ed Kingdom. Add ess2: Liaoning Uni e si y, Asia-
Aus alia Business School
b
Dongbei Uni e si y o Finance and Economics, China, School o Tou ism and Ho el Managemen
c
School o Managemen , RMIT Uni e si y, Melbou ne, Aus alia
d
Teesside In e na ional Business School, Teesside Uni e si y, Middlesbo ough, Uni ed Kingdom
ARTICLE INFO
JEL Code:
Q01
O10
O15
Keywo ds:
Sus ainabili y pe o mance
Digi al inno a ion
Digi al capabili ies
Digi al o ien a ion
IT indus y
Employee
ABSTRACT
Acco ding o he Uni ed Na ions (UN), digi al inno a ion and sus ainabili y pe o mance a e key pa hways o
achie ing he Sus ainable De elopmen Goals. Howe e , exis ing esea ch has o en o e looked he oles o
digi al capabili y and o ien a ion in d i ing digi al inno a ion. This s udy employed D ucke ’s p oduc i i y
heo y o examine he ela ionship be ween en ep eneu ial leade ship and digi al inno a ion. Two s udies we e
conduc ed on China’s in o ma ion echnology (IT) indus y. S udy 1 used a h ee-wa e design (N =299), while
S udy 2 used a wo-wa e design (N =341). Resul s demons a e a signi ican co ela ion be ween en ep e-
neu ial leade ship, digi al inno a ion, and sus ainabili y pe o mance, highligh ing he media ing oles o
employee digi al capabili y and digi al o ien a ion in he ela ionship be ween en ep eneu ial leade ship and
digi al inno a ion. This s udy con ibu es o sus ainabili y esea ch by explo ing employee-based media ing
ac o s. The indings enhance he unde s anding o how IT o ganiza ions can os e employee dedica ion and
commi men o achie ing highe le els o digi al inno a ion and sus ainabili y pe o mance h ough en ep e-
neu ial leade ship, ul ima ely suppo ing he b oade UN SDGs.
In oduc ion
The inc eased emphasis on accomplishing he Sus ainable De elop-
men Goals (SDGs) se ou by he Uni ed Na ions (UN) has p o oundly
ans o med he global business en i onmen , d awing signi ican
a en ion o o ganiza ions’ sus ainabili y pe o mance and inno a ion as
he mos eliable pa hway o achie ing he Sus ainable De elopmen
Goals (SDGs) (Dzhunushalie a & Teube , 2024; Malik e al., 2024; Pan &
Nishan , 2023). Digi al inno a ion se es as he backbone o digi al
ans o ma ion and is necessa y o capabili y building owa d
u u e- ocused g ow h (Kane e al., 2015; Ochinanwa a e al., 2023;
Opland e al., 2022). Al hough digi al inno a ion is c ucial o o gani-
za ional g ow h, i also poses signi ican challenges o many o gani-
za ions. These challenges o en s em om he misalignmen be ween
employee- ocused p ac ices and e ol ing o ganiza ional pe o mance
goals (Reibenspiess e al., 2022). This can be sol ed h ough a holis ic
app oach, wi h employee capabili y building being cen al o
o ganiza ions’ leade ship p ac ices. O ganiza ions mus adop new
leade ship amewo ks o cul i a e employees’ digi al capabili ies and
os e a digi ally o ien ed wo k o ce (Gyame ah e al., 2025; Kane e al.,
2017; Kohli & Mel ille, 2019; Nakpodia e al., 2023; Opland e al.,
2022). This is especially impo an in he in o ma ion echnology (IT)
indus y, whe e digi iza ion is in oduced as a c i ical pa hway o sus-
ainabili y (B occa do e al., 2023). While esea ch on digi al inno a ion
has ecen ly begun o a ac u he in e es wi hin he se ice sec o
(A ´
anega e al., 2023; Liu e al., 2023; Xie e al., 2022), p e ious s udies
ha e la gely o e looked employee- ele an elemen s, such as leade -
ship, which can enhance digi al inno a ion and sus ainabili y pe o -
mance h ough capabili y building (Beni ez e al., 2022; Casalegno e al.,
2023; Opland e al., 2022).
Leade ship in he IT indus y is pa amoun o os e ing a wo k o ce
capable o accomplishing sus ainabili y pe o mance goals, which can
be done by encou aging isk- aking beha io s and de eloping u u e-
ocused ini ia i es, quali ies inhe en in en ep eneu ial leade ship.
* Co esponding au ho : School o Managemen , RMIT Uni e si y, Melbou ne, Aus alia, Tel: +61 3 9925 0243
E-mail add esses: [email p o ec ed] (U.F. Sahibzada), [email p o ec ed] (N.A. Janjua), [email p o ec ed] (L. A sha i), onlyshakil@
gmail.com (M. Shakil).
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.2025.100723
Recei ed 19 Sep embe 2024; Accep ed 5 May 2025
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
A ailable online 20 May 2025
2444-569X/© 2025 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/ ).
Eme ging esea ch has indica ed ha en ep eneu ial leade ship can
enhance g ow h and pe o mance unde challenging and ad e se con-
di ions (A ´
anega e al., 2023) and iden i y oppo uni ies in demanding,
ola ile, and compe i i e en i onmen s (A ´
anega e al., 2023). Recen
s udies ha e also sugges ed ha o ganiza ions, pa icula ly hose wi hin
he IT sec o , ace a g owing demand o en ep eneu ial leade ship,
necessi a ing mo e esea ch ocused on se ice-o ien ed indus ies
(Islam e al., 2024; Ma e al., 2024; Razzaque e al., 2024). This gap in
he li e a u e equi es u he in es iga ion, sugges ing ha in eg a ing
en ep eneu ial leade ship amewo ks could en ich ou unde s anding
o digi al inno a ion s a egies in IT con ex s.
The e ec s o en ep eneu ial leade ship on digi al inno a ion in he
IT sec o a e complex and in luenced by ac o s ha can ei he
s eng hen o weaken his ela ionship. To explo e hese e ec s, we
applied D ucke ’s p oduc i i y heo y, which highligh s he impo ance
o employees’ digi al li e acy and adap abili y in d i ing o ganiza ional
inno a ion (Nguyen e al., 2023; Shehzadi e al., 2021; Shujaha e al.,
2021). I posi s ha digi al wo ke s, wi h adequa e suppo o enhance
hei digi al skills, play an essen ial ole in os e ing digi al inno a ion
by e ec i ely in eg a ing echnological and human esou ces (Beni ez
e al., 2022). In he IT indus y, digi ally o ien ed employees a e i al o
in e ac wi h s akeholde s and ad ance inno a ion (Renko e al., 2009).
While p io esea ch has examined digi al o ien a ion and digi al
capabili y sepa a ely (Fe ei a e al., 2024; P oksch e al., 2024; Wang
e al., 2024), his s udy in es iga es how hese ac o s media e he link
be ween en ep eneu ial leade ship and digi al inno a ion, add essing
an o e looked a ea in IT-sec o esea ch (Hoang e al., 2024; Ib ahim
e al., 2024). This dual media ion model aims o en ich
sus ainabili y- ocused leade ship insigh s and p o ide a ounda ion o
u u e esea ch.
Mo eo e , p io esea ch has o e ed agmen ed insigh s in o he
ac o s de e mining sus ainabili y and has no adop ed a comp ehensi e
app oach o es ablishing a cohe en amewo k o a aining bo h digi al
inno a ion and sus ainabili y pe o mance (Chaudhu i e al., 2024;
Rahmani e al., 2024). This gap limi s esea ch insigh s in o he complex
in e play be ween di e se aspec s o digi al o ien a ion and hei e ec s
on sus ainabili y ou comes. Thus, s udying how en ep eneu ial lead-
e ship in luences wo ke s’ digi al o ien a ion and digi al capabili y can
imp o e he IT indus y’s digi al inno a ion and sus ainabili y pe o -
mance. To add ess hese gaps and p o ide an in eg a ed o e iew o
inno a ion and sus ainabili y pe o mance, we explo e leade ship
p ac ices ha cul i a e employees’ capabili ies in digi al inno a ion and
sus ainabili y. This s udy p oposes h ee p ima y esea ch ques ions:
•RQ1: How does en ep eneu ial leade ship in luence digi al
inno a ion?
•RQ2: To wha ex en do employee digi al o ien a ion and digi al
capabili y media e he ela ionship be ween en ep eneu ial lead-
e ship and digi al inno a ion?
•RQ3: How does digi al inno a ion con ibu e o o ganiza ional sus-
ainabili y pe o mance?
This s udy’s signi icance lies in ho oughly examining p e iously
unexplo ed connec ions wi hin he sus ainabili y li e a u e by imple-
men ing a media ing model ha inco po a es employee ac o s o
enhance digi al inno a ion. Such an app oach deepens ou unde -
s anding o how IT i ms, pa icula ly hose in he IT indus y, can boos
employee digi al o ien a ion and capabili y by le e aging en ep e-
neu ial leade ship o achie e highe le els o digi al inno a ion and
sus ainabili y pe o mance. This s udy igo ously examines he unique
leade ship and managemen challenges in he IT indus y, main aining
an analy ical iewpoin ha dis inguishes IT om he indus ial sec o .
Fu he mo e, i makes a aluable con ibu ion by conduc ing an
exhaus i e analysis o he c i ical associa ion, u ilizing a media ing
model in wo s udies, and employing a esea ch design wi h a ime-
lagged app oach o p oduce b oadly applicable esul s.
Theo e ical lens and hypo hesis de elopmen
Knowledge wo ke p oduc i i y heo y
Acco ding o D ucke ’s heo y o p oduc i i y (D ucke , 1999;
Sahibzada e al., 2022; Shujaha e al., 2020), digi al wo ke s, a ype o
knowledge wo ke s whose job is o inno a e, need o ganiza ional sup-
po encompassing en ep eneu ial leade ship, digi al o ien a ion, and
digi al capabili y. D ucke (1999, p. 94) a gued ha he abili y o
knowledge-in ensi e i ms o su i e depends on hei compe i i e
ad an age in making knowledge wo ke s mo e p oduc i e. Digi al
wo ke s a e compe en pe sonnel capable o lea ning as wi hin a i m
(Shahzadi e al., 2021). Knowledge wo ke s ace complex assignmen s
and edious and diso de ly jobs (Bosch-Sij sema e al., 2009); hei
p oduc i i y e e s o hei e iciency in c ea ing in ellec and
knowledge-based inno a i e ou pu s such as so wa e solu ions
(D ucke , 1999; Shujaha e al., 2020). D ucke ’s p oduc i i y heo y
also emphasizes ha leade s should ake he ini ia i e in o ganiza ions
o c ea e digi al esou ces and p omo e hei use h ough lea ning p o-
g ams (A sha i & Hadian Nasab, 2020; Fa idian, 2023).
En ep eneu ial leade ship and digi al inno a ion
En ep eneu ial leade ship is he leade ship p ac ice o exe ing in-
luence on o ganiza ions by ac i ely c ea ing alue o s akeholde s
(Al-Sha i e al., 2023). This objec i e is achie ed by using a dis inc i e
combina ion o inno a ion and esou ces o ha ness o wa d-looking
oppo uni ies (Hoang e al., 2023; Kas elli e al., 2024). En ep e-
neu ial leade ship inno a i ely ans o ms exis ing ansac ion se s in o
en ep eneu ial ac ions, hus pa ing he way o u u e- ocused p og ess
and de elopmen (Hoang e al., 2023). P e ious s udies ha e p oposed
ha en ep eneu ial leade ship is an e ec i e leade ship s yle in un-
p edic able and challenging en i onmen s, iden i ying oppo uni ies
and os e ing inno a ion in o ganiza ions (Razzaque e al., 2024). Along
wi h he p inciples o D ucke ’s p oduc i i y heo y, en ep eneu ial
leade s a e expec ed o p omo e digi al inno a ion in he IT indus y by
acili a ing he gene a ion o new ideas, aking ad an age o en ep e-
neu ial oppo uni ies in he wo kplace, and ans o ming hem in o
inno a i e digi al p oduc s. Addi ionally, hese leade s se e as ole
models by exhibi ing en ep eneu ial beha io s (Shujaha e al., 2021).
Cu en ends in en ep eneu ial leade ship and inno a ion ha e led
o he p oli e a ion o s udies ha only ocus on inno a ion pe o mance
(Al-Sha i e al., 2023; Hoang e al., 2023), adap i e inno a ion (Lin &
Yi, 2023), and open inno a ion (Fa idian, 2023). Addi ionally, many
solely examine he link be ween en ep eneu ial leade ship and em-
ployees’ inno a i e beha io (Abualoush e al., 2022; Maliba i &
Bajaba, 2022). Despi e he inc easing ocus on how en ep eneu ial
leade ship os e s inno a ion, s udies explo ing i s ela ionship wi h
digi al inno a ion, especially wi hin he IT indus y, emain sca ce
(Razzaque e al., 2024). The e o e, we p opose he ollowing hypo hesis:
H1: En ep eneu ial leade ship posi i ely a ec s digi al inno a ion.
En ep eneu ial leade ship, employee digi al o ien a ion, and digi al
inno a ion
Digi al o ien a ion e e s o employee beha io s ha acili a e he
adop ion o digi al echnologies (Wang e al., 2024). Digi ally o ien ed
employees end o ha e a g ea e p opensi y o lea n and e ec i ely
u ilize cu ing-edge echnologies, such as he In e ne o Things (IoT),
big da a, a i icial in elligence (AI), and blockchain (Wang e al., 2024).
D ucke ’s p oduc i i y heo y highligh s he idea ha an o ganiza ion’s
inno a ion is closely linked o i s employees’ digi al li e acy and com o
wi h echnology (Shehzadi e al., 2021; Shujaha e al., 2021). These
cha ac e is ics a e nu u ed only wi hin an en i onmen in which em-
ployees eel sa e, a e encou aged o ake isks, and emb ace
u u e- ocused oppo uni ies (Kinde mann e al., 2024). En ep eneu ial
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
2
leade ship es ablishes an en i onmen conduci e o g ow h and de el-
opmen , emphasizing he signi icance o digi al echnology in le e aging
po en ial oppo uni ies (Hoang e al., 2024). Resea ch has shown ha
when leade s p omo e inno a ion and digi al echnology, employees a e
mo e likely o acqui e digi al abili ies and become digi ally o ien ed
(Fa han e al., 2024; Gilli e al., 2024). Howe e , ew s udies ha e
examined he ela ionship be ween en ep eneu ial leade ship and em-
ployees’ digi al o ien a ion. Gaining a deepe unde s anding o how
en ep eneu ial leade ship can e ec i ely p omo e employees’ digi al
o ien a ion in he IT se ice indus y will open new a enues o p ac-
i ione s. D ucke ’s p oduc i i y heo y, which asse s ha leade s mus
ake he ini ia i e wi hin o ganiza ions o es ablish digi al esou ces and
acili a e hei u iliza ion h ough comp ehensi e lea ning p og ams,
suppo s his associa ion (Fa idian, 2023).
P e ious s udies ha e demons a ed ha o ganiza ional digi al
o ien a ion ensu es inno a ion ac oss a ious sec o s. Speci ically,
esea ch indica es ha digi al o ien a ion posi i ely in luences inno a-
ion pe o mance in high- ech small- and medium-sized en e p ises
(SMEs) in India (Ranjan, 2024), modi ies inno a ion ou pu s in i ms in
China (Wang e al., 2024), and a ec s inno a ion pe o mance in he
hospi ali y indus y in he Uni ed A ab Emi a es (Tajeddini e al., 2024).
P e ious s udies ha e also no adequa ely explo ed he ex en o which
employees’ digi al o ien a ion con ibu es o digi al inno a ion. This
o e sigh sugges s ha he e is a need o u he in es iga ion in o how
employees’ digi al capabili ies and engagemen can in luence an o ga-
niza ion’s capaci y o inno a e in he digi al landscape, pa icula ly
wi hin he IT indus y. Unde s anding his ela ionship is essen ial o
de eloping s a egies ha le e age digi al wo k o ce skills and d i e
success ul inno a ion ini ia i es. This s udy add esses schola s’ ongoing
demands o elucida e he media ing mechanisms h ough which en e-
p eneu ial leade ship in luences inno a ion in he se ice (IT) sec o , as
highligh ed in he li e a u e e iew (Hoang e al., 2024; Ib ahim e al.,
2024).
The e o e, we p opose he ollowing hypo heses:
H2: En ep eneu ial leade ship posi i ely a ec s employee digi al
o ien a ion.
H2a: Digi al o ien a ion posi i ely a ec s digi al inno a ion.
H2b: Digi al o ien a ion media es he ela ionships be ween en e-
p eneu ial leade ship and digi al inno a ion.
En ep eneu ial leade ship, employee digi al capabili y, and digi al
inno a ion
Digi al capabili y, which e e s o employees’ skills, expe ience, and
knowledge in managing digi al echnology o c ea e new p oduc s, is
essen ial o digi al ans o ma ion (Kans & Campos, 2024). The abili y
o u ilize digi al echnologies is demons a ed h ough employees’ dig-
i al capabili ies, expe ise, and echnical knowledge (Alexand o & Bas-
owi, 2024). This a gumen aises he c ucial issue o cul i a ing digi al
capabili ies, pa icula ly in he IT indus y. P e ious s udies ha e shown
ha en ep eneu ial leade s can acili a e he ad ancemen o em-
ployees’ digi al skills by o e ing oppo uni ies o lea ning and g ow h
(Maliba i & Bajaba, 2022; Yada e al., 2024). En ep eneu ial leade s
can iden i y he speci ic digi al capabili ies and knowledge employees
need o achie e s a egic o ganiza ional objec i es (Hoang e al., 2024).
P e ious li e a u e has shown ha leade ship is a c ucial ac o in
de eloping he digi al capabili y equi ed o p omo e inno a ion in
SMEs (Aghazadeh e al., 2024). Howe e , esea ch on he connec ion
be ween en ep eneu ial leade ship and digi al capabili y in he se ice
(IT) indus y emains limi ed. This associa ion is alida ed by D ucke ’s
p oduc i i y heo y, which sugges s ha leade s can p omo e he
lea ning and communica ion o digi al wo ke s by e ec i ely u ilizing
digi al pla o ms such as collabo a ion ools and AI (Beni ez e al., 2022;
Wu e al., 2021).
Fu he mo e, exis ing li e a u e highligh s a signi ican gap in un-
de s anding he media ing ac o s ha connec leade ship o digi al
inno a ion (Bas idas e al., 2023). P e ious s udies ha e examined
a ious media ing ac o s o assess he ela ionship be ween leade ship
and inno a ion. Fu he mo e, di e en media ing ac o s ha e been
p oposed o es ablish a connec ion be ween en ep eneu ial leade ship
and inno a ion, including inno a ion s a egy and knowledge acquisi-
ion (Hoang e al., 2023), inno a ion capabili y (Al-Sha i e al., 2023),
eam c ea i i y and sel -e icacy (Baghe i e al., 2022), and se ice
inno a ion (Ge aneh Kebede e al., 2024). Howe e , empi ical e idence
on he media ing ole o digi al capabili y in he ela ionship be ween
en ep eneu ial leade ship and digi al inno a ion is lacking. Addi ion-
ally, p io esea ch has p edominan ly neglec ed employee-d i en ele-
men s explaining he ela ionship be ween en ep eneu ial leade ship
and digi al inno a ion in he IT sec o (Beni ez e al., 2022; Opland e al.,
2022; S aub e al., 2023). Fu he mo e, he ole o digi al capabili y as a
media o has ecei ed limi ed a en ion in p e ious s udies (P oksch
e al., 2024). Thus, his s udy es s he hypo hesis ha digi al capabili y
media es he ela ionship be ween en ep eneu ial leade ship and dig-
i al inno a ion in he con ex o Chinese IT i ms:
H3: En ep eneu ial leade ship posi i ely a ec s employee digi al
capabili y.
H3a: Employee digi al capabili y posi i ely a ec s digi al
inno a ion.
H3b: Employee digi al capabili y media es he ela ionship be ween
en ep eneu ial leade ship and digi al inno a ion.
Digi al inno a ion and sus ainabili y pe o mance
Digi al inno a ion is he in en ion o ma ke o e ings, business
p ocesses, o business models using digi al echnology (Felice i e al.,
2024). I has he po en ial o ans o m business ope a ions h ough
p ocess op imiza ion, cos educ ion, and he de elopmen o new
p oduc s and se ices (Han e al., 2023). The pu sui o inno a ion is
ela ed o wha can and should be imp o ed, which a ec s he acqui-
si ion and di ec ion o oppo uni ies ha p omo e sus ainabili y pe -
o mance (Shah e al., 2024). Acco ding o D ucke ’s p oduc i i y
heo y, digi al inno a ion is essen ial o gene a ing new ideas by
decisi ely capi alizing on en ep eneu ial oppo uni ies wi hin he
wo kplace. This s a egic app oach ans o ms hese oppo uni ies in o
inno a i e digi al p oduc s, he eby signi ican ly imp o ing sus ain-
abili y pe o mance (Felice i e al., 2024).
Sus ainabili y pe o mance ensu es he e icien use o na u al e-
sou ces wi hou jeopa dizing u u e economic p ospec s and ha ming
socie y and he en i onmen . I inco po a es en i onmen al in eg i y,
social equali y, and economic p ospe i y in o a i m’s ope a ions
(Nicolo’ e al., 2024; Siddik e al., 2024). P e ious esea ch has shown
ha inno a ion signi ican ly a ec s sus ainabili y pe o mance in SMEs
(Mokbel Al Koliby e al., 2024). Jum’a e al. (2024) acknowledged ha
sus ainabili y pe o mance depends on an o ganiza ion’s inno a ion in
Jo danian manu ac u ing companies. Khin and Ho (2018) con ended
ha a ious inno a ion- ela ed ac o s may in luence he in e play be-
ween a company’s sus ainable digi al business pe o mance and inno-
a ion. Despi e many s udies on digi al inno a ion, he impac o digi al
inno a ion on he sus ainabili y pe o mance o IT i ms emains
unde - esea ched. Add essing his gap is c i ical o a aining a
comp ehensi e unde s anding o he di ec in luence o digi al inno a-
ion on he sus ainabili y pe o mance o echnology i ms, he eby
acili a ing he enhancemen o sus ainable p ac ices wi hin he in-
dus y. Building on insigh s om p e ious li e a u e and he p inciples
o D ucke ’s p oduc i i y heo y, ou s udy shi s he ocus owa d
digi al inno a ion and es s he ollowing hypo hesis:
H4: Digi al inno a ion posi i ely a ec s sus ainabili y pe o mance.
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
3
Me hodology
Sample
So wa e echnology companies we e included in ou sample because
hey exhibi dis inc cha ac e is ics ele an o ou s udy. En ep e-
neu ial leade ship is c ucial in IT i ms, gi en hei dynamic en i on-
men s ha demand inno a i e leade ship s yles (Dona e & S´
anchez de
Pablo, 2015). Addi ionally, knowledge wo ke s in high- ech i ms
display a digi al o ien a ion ha is essen ial o adop ing and op imizing
digi al esou ces. Thei digi al capabili ies, which a e cha ac e ized by
echnical p o iciency, a e necessa y o d i e digi al inno a ion and
sus ain compe i i e ad an age (Yahya & Goh, 2002).
Resea ch design
We conduc ed wo pa allel s udies o empi ically assess he p oposed
hypo heses, as shown in Figu e 1. S udy 1 was conduc ed o empi ically
es he model, u ilizing a ime-lagged esea ch design wi h a sample o
pe sonnel om he IT indus y in China. This me hodology p o ided a
solid analy ical ounda ion o ou s udy o add ess he mul idimen-
sional na u e o links be ween en ep eneu ial leade ship, digi al
o ien a ion, digi al capabili y, and digi al inno a ion in S udy 1. Sub-
sequen ly, S udy 2 was unde aken wi h he dual pu pose o illing a
c ucial esea ch gap by iden i ying p edic o s o sus ainabili y pe o -
mance and alida ing he esul s o he i s s udy, he eby ein o cing
con idence in he a ained esul s (Quade e al., 2020). P io esea ch on
leade ship also p oposed using wo amewo ks o mo e obus indings
(Quade e al., 2020; Rasheed e al., 2023).
S udy 1
S udy 1 empi ically es ed he model by u ilizing a ime-lagged s udy
design. Using he P oli ic da a collec ion se ice, a web-based ques-
ionnai e was de eloped o ga he in o ma ion om IT p o essionals in
h ee p og essi e IT ci ies in China: Shenzhen, Xi’an, and Beijing. The
da a collec ion o S udy 1 was conduc ed be ween Oc obe 2023 and
Decembe 2023. The p esen s udy was execu ed in h ee dis inc pha-
ses, wi h a 2-week in e al be ween each phase. P e ious s udies on
leade ship ha e indica ed ha a 2-week in e al should be obse ed
du ing successi e da a-ga he ing phases (Quade e al., 2020; Rasheed
e al., 2023).
A (T1), da a we e ga he ed om 327 con ibu o s ega ding hei
supe iso ’s en ep eneu ial leade ship (EL) app oaches. Two weeks
la e , a (T2), 327 pa icipan s we e asked o p o ide in o ma ion on
hei digi al o ien a ion (DO) and digi al capabili ies (DC), in which 317
pa icipan s esponded o he ques ionnai e. Two weeks a e he T2
wa e, he emaining pa icipan s we e asked o a e digi al inno a ion,
and he da a we e ga he ed du ing he T2 phase. A T3, only 308 pa -
icipan s esponded. Following he iden i ica ion o mul i a ia e ou -
lie s, nine esponses we e elimina ed, lea ing 299 alid esponses o
subsequen analyses.
Demog aphic p o ile o S udy 1
As unique iden i ie s, he P oli ic iden i ie s o he esponden s we e
used o link and consolida e he in o ma ion hey p o ided in he h ee
phases. O he 299 pa icipan s, 62.4% we e male and 37.5% we e e-
male. Fu he mo e, he analysis e ealed ha 35.6% o he pa icipan s
we e aged 30 o 39 yea s, whe eas 24.8% we e aged 20 o 29 yea s.
S udy 2
A ime-lagged echnique and analysis we e applied o he ull model.
We collec ed da a o S udy 2 om pe sonnel in he Chinese IT indus y
using he P oli ic da a collec ing ool. The second in es iga ion was
conduc ed in wo phases, wi h a 1-mon h in e al. Fo a mo e comp e-
hensi e analysis, i is ad isable o conduc a ollow-up s udy wi h a 1-
mon h gap (Rasheed e al., 2023). P e ious s udies in es iga ing lead-
e ship ha e also implemen ed a 1-mon h in e al be ween successi e
ounds o da a ga he ing (Khan e al., 2021; Rasheed e al., 2020).
Du ing he ini ial phase o da a ga he ing (T1), da a we e ob ained om
378 pa icipan s ega ding me ics o en ep eneu ial leade ship, dig-
i al o ien a ion, and digi al capabili ies. Da a o S udy 2 we e collec ed
om Janua y 2024 o Ma ch 2024. The esponden s’ demog aphic da a,
including loca ion, age, educa ional backg ound, sexual o ien a ion, and
o e all expe ise in he IT sec o , we e collec ed du ing he T1 su ey.
We eques ed ha he 378 pa icipan s in he T1 wa e p o ided da a
abou digi al inno a ion and sus ainabili y pe o mance. The T2 su ey
included a o al o 359 esponden s. Among he en i e pa icipan pool,
341 indi iduals submi ed esponses ha me he c i e ia o analysis.
A e excluding 18 esponses as mul i a ia e ou lie s, 341 esponses
we e included in he inal analysis.
Figu e 1. Theo e ical amewo k.
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
4
Demog aphic p o ile o S udy 2
As unique iden i ie s, he esponden s’ P oli ic iden i ie s we e used
o co espond wi h and compile he in o ma ion hey p o ided in he
wo phases. O he 341 su ey pa icipan s 36.7% we e emale and
63.3% we e male. Addi ionally, 25.8% o he esponden s we e aged 20
o 29 yea s, while 35.2% we e aged 30 o 39 yea s. Fu he mo e, 47.6%
had a mas e ’s deg ee, while 38.4% had 11 o 15 yea s o expe ience in
IT o ganiza ions.
Measu es
This s udy employed 28 measu ing i ems. Sligh modi ica ions we e
made o he wo ding o he sec ions o adhe e o IT s anda ds (La i e al.,
2020). The su ey employed a 5-poin Like - ype scale, wi h 1 indi-
ca ing s ong disag eemen and 5 indica ing s ong ag eemen . The
s udy applied a scale de eloped by Renko e al. (2015) o assess en e-
p eneu ial leade ship. Fo ins ance, one o he i ems was, “My manage
o en comes up wi h adical imp o emen ideas o he p o-
duc s/se ices we a e selling.” The 4-i em digi al o ien a ion measu e
was de i ed om Zhou e al. (2005) and Ga ignon and Xue eb (1997),
wi h one o he i ems being “I always look ou o oppo uni ies o use
digi al echnology in ou inno a ion.” The 5-i em digi al capabili ies
measu e was adop ed om Zhou and Wu (2010), wi h one o he i ems
being “I am de eloping inno a i e p oduc s/se ices/p ocesses using
digi al echnology.” The 6-i em digi al inno a ion scale was al e ed om
Paladino (2007), wi h one o he i ems being “I ake p ide in deli e ing
digi al solu ions ha su pass he quali y o e ed by ou compe i o s as
pa o my con ibu ion o he company’s success.” Finally, i e sus-
ainabili y pe o mance i ems we e adop ed om Gelha d and Von Del
(2016), wi h one o he i ems being “We de elop new se ices o
imp o e exis ing se ices ha a e ega ded as sus ainable o socie y and
he en i onmen .”
Da a analysis and esul s
The da a we e examined using se e al me hods o e i y he hy-
po heses. We employed a missing- alue examina ion, mul i ac o iden-
i ica ion o ou lie s, assessmen o he no mal da a dis ibu ion,
s a is ical analysis o a iance, and co ela ion analyses o da a il e ing
(Hai J e al., 2020). We also conduc ed a ho ough e alua ion o
iden i y IT specialis s wi h a leas 1 yea o ull- ime employmen . These
wo s udies used iden ical c i e ia o da a e alua ion (Rasheed e al.,
2023). We chose PLS-SEM o e CB-SEM because i sui s he complex
ela ionships be ween he la en cons uc s and explo a ion o heo e -
ical le els (Hai e al., 2017). This app oach has been ex ensi ely used in
heo y alida ion and es ing and is app op ia e o in es iga ing
mul i ace ed associa ions (Fo nell & La cke , 1981). PLS-SEM equi es a
wo old analysis: measu emen model calcula ion (ou e model) and
s uc u al model (inne model) analysis (Ringle e al., 2018). The mea-
su emen model speci ica ion ensu ed ha hese s uc u es had app o-
p ia e poin e loadings, con e gen alidi y, composi e eliabili y, and
disc iminan alidi y when ex ended o he s uc u al model. S uc u al
model assessmen equi es measu ing pa h coe icien s and e alua ing
hei consequences.
Common me hod bias and mul i-collinea i y
To mi iga e he isk o bias, his in es iga ion adhe ed o well-
de ined p ocedu es (Podsako e al., 2003). P elimina y es ing was
conduc ed while p epa ing he ques ionnai e. I aimed o iden i y as-
pec s o he su ey’s layou and i ems ha equi ed e inemen o educe
he pa icipan s’ wo kload. Addi ionally, he su ey was c ea ed o
clea ly dis inguish be ween he dependen and independen a iables.
The i ems we e andomized o ensu e an unbiased app oach owa d he
speci ic esponses. The e o e, e e y possible wo ding and a angemen
o he pa ame e s ha may ha e induced a p iming ou come was
ci cum en ed. Nex , Ha man’s es was conduc ed o assess single a -
iables. The analysis yielded no ob ious conce ns because a single i em
accoun ed o 41% o he disc epancy in he sample, which is well below
he minimum equi emen o 50%. The e o e, he e was no need o
conside common me hod bias (Volbe da e al., 2012). In addi ion, a
ho ough examina ion was conduc ed o analyze he associa ions be-
ween he cons uc s. The esul s show ha he ela ionships a e ela-
i ely weak, wi h alues abo e 0.90 (Low y & Gaskin, 2014). Finally,
a iance in la ion ac o s (VIFs) we e used o inspec bo h he axial and
ho izon al collinea i y among each cons uc (Kock, 2015). Acco ding o
Kock (2015), one way o e alua e he po en ial bias o commonly used
me hods in esea ch in ol ing he compu a ional modeling o s uc u al
equa ions is o conduc a collinea i y es . VIFs we e employed o
de e mine whe he he model was a ec ed by common me hod bias. The
model was conside ed unbiased i VIFs we e 3.30 o lowe . A e con-
duc ing a comp ehensi e collinea i y es , he esul s indica ed a
maximum VIF below 3.30 ( ange, 2.103–2.915), and he sample u ilized
in his s udy did no exhibi any issues associa ed wi h common me hod
bias.
Assessmen esul s o S udy 1
Measu emen model assessmen o S udy 1
Ali e al. (2018) sugges ed using a model i index o assess da a. The
es ima ion model in S udy 1 demons a ed a sa is ac o y i wi h he
ollowing s a is ics:
χ
2 =689.821, d =302, and
χ
2/d =3.359. The GFI
had a alue o 0.984, he AGFI was 0.891, he NFI 0.836, he CFI 0.973,
he IFI 0.907, he RMSR 0.037, and he RMSEA 0.072. The GFI and AGFI
alues should exceed 0.8, as sugges ed by Hu and Ben le (1999). The
measu emen model used in his in es iga ion was belie ed o i
(Baumga ne & Hombu g, 1996). The in es iga ion began by assessing
he in e nal eliabili y o he S udy 1 model using composi e eliabili y
(CR) and C onbach’s alpha indica o s.
Using ou e loading analysis, a e age a iance ex ac ed (AVE), and
Fo nell–La cke , his s udy addi ionally assessed he model’s disc imi-
nan and con e gen alidi y (Hai e al., 2017). To assess he in e nal
eliabili y o he s udy, C onbach’s alpha and CR should be abo e he
minimum h eshold o 0.6, as indica ed by Nunnally (1978). Table 1 lis s
he alues ha de e mine in e nal cohe ence. The AVE sco es we e
e alua ed o assess con e gen alidi y. These indings sugges ha each
AVE alue exceeds he minimum pe missible alue o 0.5. In addi ion,
pe iphe al loadings we e assessed o de e mine he eliabili y o he
Table 1
I em loadings, eliabili y, and con e gen alidi y.
ΛАCR AVE
0.906 0.928 0.682
EL1 0.860
EL2 0.873
EL3 0.829
EL4 0.829
EL5 0.795
EL6 0.766
0.833 0.889 0.667
DO1 0.781
DO2 0.777
DO3 0.864
DO4 0.840
0.777 0.871 0.692
DC1 0.810
DC2 0.863
DC3 0.821
0.825 0.872 0.533
DI1 0.767
DI2 0.781
DI3 0.616
DI4 0.706
DI5 0.741
DI6 0.759
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
5
indica o s. Values exceeding 0.6 we e deemed sui able o addi ional
da a analysis, as pe he me hods ou lined by Hai e al. (2017). A his
poin , ou i ems we e omi ed om conside a ion because hei ac o
loadings ailed o mee he ecommended h eshold o 0.6. A e e i-
ying he con e gen alidi y, we e alua ed he disc iminan alidi y
acco ding o he me hodology ou lined by Hai e al. (2017). This
ensu ed ha he co ela ion be ween i ems comp ising he same
cons uc was g ea e han ha be ween i ems comp ising o he con-
s uc s. Following Hai e al. (2017), he disc iminan alidi y was
assessed using he he e o ai –mono ai a ios (HTMT). All HTMT s a-
is ics we e below 0.85. S udy 1 passed es ing o disc iminan alidi y
(Tables 1 and 2).
S uc u al model assessmen o S udy 1
The examina ion o he s uc u al model es cons i u ed he second
phase. These hypo heses we e examined sequen ially. The di ec e ec
o T1-EL on T2-DI was also in es iga ed. A e examining he causal
connec ions among T1-EL, T2-DO, and T2-DC, S udy 1 examined he
in luence o T2-DO and T2-DC on T3-DI. To asce ain he signi icance o
he es ima ed mean e o s and di ec pa hs, 5,000 boo s ap esamples
we e used (Ringle, 2005). The esul s p esen ed in Table 4 indica e a
s a is ically signi ican ela ionship be ween T1-EL and T3-DI (β =
0.255, =0.830, p =0.406); hus, H1 is suppo ed. Fu he mo e, he
s a is ical analysis demons a es ha T1-EL exhibi s a subs an ial in-
luence on T2-DO (β =0.568, =12.425, p <0.000) and T2-DC (β =
0.617, =14,166, p <0.000). Thus, hypo heses H2 and H3 a e sup-
po ed. T2-DO (β =0.358, =5,480, p <0.000) and T2-DC (β =0.466,
=7,255, p <0.000) a e ound o ha e a signi ican e ec on T3-DI, as
con i med in S udy 1. Thus, H2a and H3a a e suppo ed (see Table 3).
Media ion analysis o S udy 1
As hypo hesized in H2b and H3b, his analysis e alua ed he ole o
T2-DO and T2-DC in S udy 1 o de e mine whe he hey media e he
co ela ion be ween T1-EL and T3-DI. The esul s indica e ha when he
media o s a e included in he p oposed model, he e is a s a is ically
signi ican and posi i e di ec e ec (β =0.25, =0.43, p =0.40). The
s udy indings u he indica e ha he indi ec e ec is s a is ically
signi ican o T2-DC (β =0.288, =5.941, p <.000) and T2-DO (β =
0.203, =5.489, p <.000), sugges ing pa ial media ion. S udy 1 shows
ha he in ol emen o T2-DC and T2-DO in luences he ela ionship
be ween T1-EL and T3-DI (see Table 4).
Assessmen esul s o S udy 2
Measu emen model assessmen o S udy 2
Simila ly, o S udy 2, he measu emen model demons a ed sa is-
ac o y i wi h he ollowing alues:
χ
2 =889.801, d =337,
χ
2/d =
3.829, GFI =0.927, AGFI =0.851, NFI =0.981, CFI =0.897, IFI =
0.891, RMSR =0.050, and RMSEA =0.082. The model is adequa e
when bo h he GFI and AGFI exceed 0.8 (Hu & Ben le , 1999). In gen-
e al, his s udy’s measu emen model was deemed sa is ac o y
(Baumga ne & Hombu g, 1996). The esea ch eam ini ially assessed
he in e nal eliabili y o S udy 2 using C onbach’s alpha and CR me -
ics. Fu he mo e, he con e gen and disc iminan alidi y o he model
was e alua ed by examining he pe iphe al loadings, AVE, and Fo -
nell–La cke measu es (Hai e al., 2017). To de e mine in e nal
consis ency, C onbach’s alpha and CR alues mus su pass he lowes
accep able h eshold o 0.6 (Nunnally, 1978). The esul s p esen ed in
Table 3 demons a e in e nal consis ency. Con e gen alidi y was
assessed by analyzing he AVE sco es. The indings demons a e ha
each AVE alue exceeds he minimum pe missible alue o 0.5, as
es ablished by Hai e al. (2017). In addi ion, pe iphe al loadings we e
assessed o de e mine he dependabili y o he indica o s. Values
exceeding 0.6 we e deemed sui able o subsequen da a analysis in
adhe ence o he guidelines o Hai e al. (2017). In his phase, each
ac o was excluded because i s ac o loadings exceeded he ecom-
mended h eshold o 0.6. S udy 2 examined disc iminan alidi y
ollowing he con i ma ion o con e gen alidi y o asce ain whe he
he co ela ion be ween cons uc s was mo e p onounced han ha be-
ween cons uc s (Hai e al. 2017). A e analyzing he he e o-
ai –mono ai a ios (HTMT), i was ound ha e e y s a is ic ell
below 0.85, which is consis en wi h he guidelines p oposed by Hai
e al. (2017). S udy 2 passes he disc iminan alidi y es (see Tables 5
and 6).
S uc u al model assessmen o S udy 2
The s uc u al assessmen o he model en ailed a sequen ial me h-
odological analysis o all hypo heses. In S udy 2, he e ec s o T1-EL on
T2-DI we e examined, ollowed by he e ec s o T1-DO and T1-DC on
T2-DI. Mo eo e , we assessed he in luence o T2-DI on T2-SP. To assess
he signi icance o he di ec pa hs and ob ain s anda d e o s and
con idence in e als, 5,000 boo s ap esamples we e used (Ringle,
2005). T1-EL subs an ially in luences T2-(DI), as e idenced by he s a-
is ical esul s shown in Table 6 (β =0.244, =3.256, p =0.001). The
indings o S udy 2 suppo he alidi y o H1. Fu he mo e, he esul s
demons a e ha T1-EL g ea ly in luences T1-DO (β =0.905, =51.918,
p <0.000) and T1-DC (β =0.914, =52.155, p <0.000). Thus, H2 and
H3 a e e i ied. In S udy 2, he esul s con i m ha T1-DO (β =0.164,
=2.580, p <0.000) and T1-DC (β =0.560, =9.432, p <0.000) ha e a
signi ican e ec on T2-DI. Thus, H2a and H3a a e suppo ed. The esul s
o S udy 2 con i m he subs an ial e ec o T2-DI on T2-SP (β =0.814,
=18.402, p <0.000). The e o e, H4 is ully suppo ed. (See Table 7).
Media ion analysis o S udy 2
As hypo hesized by H2b and H3b, S udy 2 e alua ed T1-DO and T1-
DC o de e mine whe he hey media e he ela ionship be ween T1-EL
and T2-DI. The esul s indica e ha inco po a ing he media o in o he
model leads o a signi ican posi i e di ec e ec (β =.24, =0.90, p =
0.00). A signi ican indi ec e ec is obse ed o T1-DC (β =0.417, =
8.311, p <.000) and T1-DI (β =0.121, =2.584, p <0.010). Thus, he
esul s sugges pa ial media ion in S udy 2, which implies ha he e ec
o T1-EL on T2- DI in S udy 2 is pa ially media ed h ough T1-DC and
T1-DO (see Table 8).
Assessing p edic i e ele ance using PLS p edic
The success o he model in explaining he a iabili y obse ed in he
sample is suppo ed by he R2 alues p esen ed be o e. The p edic i e
ele ance assessmen o he model de eloped o sus ainabili y pe o -
mance was conduc ed using PLS-P edic (Shmueli e al., 2016). T aining
samples, which comp ise a subse o he da a se u ilized o model
Table 2
Disc iminan alidi y (HTMT).
DC DI DO EL
DC
DI 0.827
DO 0.751 0.772
EL 0.733 0.489 0.646
No e: All HTMT alues a e <0.85.
Table 3
Resul s om SEM.
Hypo heses Rela ionships Sample
mean
S anda d
de ia ion
T
s a is ics
P
alues
H1 EL ->DI 0.255 0.067 0.830 0.406
H2 EL ->DO 0.568 0.046 12.425 0.000
H2a DO ->DI 0.358 0.065 5.480 0.000
H3 EL ->DC 0.617 0.043 14.166 0.000
H3a DC ->DI 0.466 0.064 7.255 0.000
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
6
es ima ion, and holdou samples, which con ain he esidual po ion o
he da a se no employed o pa ame e es ima ion, a e a he co e o
his me hodology (Hai J e al., 2020; Shmueli e al., 2016). Holdou
samples we e used in PLS p edic ion o make case- o i em-le el p e-
dic ions. PLS p edic ion can assess model accu acy and p edic no el
case ou comes (Shmueli e al., 2016). Following he guidelines by Hai
J e al. (2020) and Shmueli e al. (2016) ega ding he p edic i e
impo ance o ou model, we ini ia ed he PLS p edic ion me hod using
10 olds (k =10). Each old o he aining sample was ca e ully
inspec ed o ensu e compliance wi h he minimum sample size e-
qui emen s speci ied by Kock and Hadaya (2018). The calcula ions we e
pe o med using he G* Powe so wa e. The analysis examined he
Q
2
-P edic alues gene a ed by he PLS-SEM model.
The PLS-SEM analysis exhibi s supe io pe o mance in indica o s o
ou p ima y a ge cons uc compa ed o he benchma k linea
eg ession model (LM), as e idenced by he Q
2
p edic alue o sus-
ainabili y pe o mance. This inding implies ha elying solely on he
median alues o he ma ke s in he aining sample educed he p e-
cision o ou analysis. Following his, we in es iga ed he a iabili y o
es ima ion e o s in he p edic i e amewo k ha we de eloped and
iden i ied an asymme ical dis ibu ion. Consequen ly, he acqui ed
mean a e age e o da a we e applied o he LM and PLS-SEM bench-
ma ks. The esul s p esen ed in Table 9 indica e ha he mean a e age
e o alues o all indica o s e alua ed using he PLS-SEM we e
signi ican ly lowe han hose ob ained using he LM. The p edic i e
capabili y o he model was mode a e.
Discussion
S a is ical analysis showed ha he e is a posi i e associa ion be-
ween en ep eneu ial leade ship and digi al inno a ion. I has been
p o en ha en ep eneu ial leade ship has a posi i e e ec on inno a-
ion pe o mance (Al-Sha i e al., 2023; Hoang e al., 2023), adap i e
inno a ion (Lin & Yi, 2023), and open inno a ion (Fa idian, 2023)
wi hin o ganiza ional con ex s. Hence, he esul s ob ained om S udies
1 and 2 align wi h hose o he exis ing body o esea ch. Addi ionally,
he indings indica e ha IT i m manage s who demons a e an en e-
p eneu ial leade ship s yle a e mo e inclined o enhance digi al inno-
a ion. Leade s use hei en ep eneu ial skills in compe i i e se ings o
a ain digi al inno a ion. This inding s eng hens con idence in he
signi ican impac o en ep eneu ial leade ship on digi al inno a ion in
he Chinese IT indus y.
We disco e ed ha he media ion analysis esul s o bo h in-
es iga ions we e simila . These indings indica e ha he e is pa ial
media ion o he dual pa hways. The esul s ob ained om bo h s udies
a e consis en wi h hose epo ed in he cu en li e a u e (Al-Sha i
e al., 2023; Hoang e al., 2023). Resea ch indica es ha employee
digi al o ien a ion is a signi ican p edic o o digi al inno a ion and ha
his co ela ion is s eng hened by en ep eneu ial leade ship suppo .
Ou esul s show ha digi ally o ien ed employees a e mo e ecep i e o
digi al echnologies. They quickly adop digi al ini ia i es wi h dedica-
ion, which enables hem o c ea e inno a i e p oduc s, se ices, and
solu ions. Such cogni i e abili ies and idea ion can only be os e ed by
en ep eneu ial leade s who gene a e no el concep s and in eg a e
inno a ion in o managemen p ac ices. Employees’ digi al o ien a ion
ex ends beyond digi al echnology (Meske & Junglas, 2021). I also
empowe s wo ke s o eel compe en in isk- aking, become
Table 4
Media ion analysis esul s.
To al e ec (T1-EL ->T3-DI) Di ec e ec s (T1-EL ->T3-DI) Indi ec e ec s o T1- EL on T3- DI
Coe icien P- alue Coe icien p- alue Coe icien SD T alue P- alues
0.43 0.00 0.25 0.40 H2b: T1-EL ->T2-DC ->T3-DI 0.288 0.048 5.941 0.000
H3b: T1 -EL ->T2- DO ->T3-DI 0.203 0.037 5.489 0.000
Table 5
I em loadings, eliabili y, and con e gen alidi y.
ΛАCR AVE
0.932 0.944 0.677
EL1 0.811
EL2 0.805
EL3 0.846
EL4 0.815
EL5 0.841
EL6 0.811
EL7 0.823
EL8 0.827
0.894 0.927 0.760
DO1 0.847
DO2 0.889
DO3 0.888
DO4 0.861
0.905 0.930 0.727
DC1 0.840
DC2 0.760
DC3 0.909
DC4 0.888
DC5 0.858
0.930 0.945 0.741
DI1 0.834
DI2 0.879
DI3 0.898
DI4 0.850
DI5 0.865
DI6 0.837
0.902 0.928 0.719
SP1 0.828
SP2 0.814
SP3 0.867
SP4 0.862
SP5 0.868
Table 6
Disc iminan alidi y (HTMT).
DC DI DO EL SP
DC
DI 0.813
DO 0.774 0.884
EL 0.579 0.673 0.809
SP 0.488 0.489 0.468 0.794
No e: All HTMT alues a e <0.85.
Table 7
Resul s om SEM.
Hypo heses Rela ionships Sample
mean
S anda d
de ia ion
T
s a is ics
P-
alues
H1 EL ->DI 0.244 0.074 3.256 0.001
H2 EL ->DO 0.905 0.017 51.918 0.000
H2a DO ->DI 0.164 0.065 2.580 0.010
H3 EL ->DC 0.914 0.018 52.155 0.000
H3a DC ->DI 0.560 0.060 9.432 0.000
H4 DI ->SP 0.814 0.044 18.402 0.000
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
7
sel -su icien , and engage wi h o he s. Following ou esea ch indings,
en ep eneu ial leade ship p o ides suppo o employees by os e ing a
cul u e ha encou ages hem o enhance hei digi al skills and knowl-
edge. I also p omo es a sense o collec i e owne ship and accoun abili y
owa d achie ing he o e a ching goal o digi al inno a ion.
The e idence suppo ing he media ing ole o digi al o ien a ion in
he ela ionship be ween en ep eneu ial leade ship and digi al inno-
a ion aligns wi h D ucke ’s p oduc i i y heo y. Acco ding o his
heo y, digi al wo ke s who ecei e assis ance om en ep eneu ial
leade s become digi ally o ien ed and engage in digi al inno a ion.
These indings sugges ha en ep eneu ial leade s who p io i ize digi-
al o ien a ion among employees and he iden i ica ion o oppo uni ies
in pu sui o e ol ing and u u e- ocused o ganiza ional goals no only
gene a e c ea i e ideas o add ess business challenges bu also guide he
inno a ion and oppo uni y ecogni ion p ocesses by encou aging em-
ployees o ake isks (Apa icio e al., 2023). Ou s udy sugges s ha
adop ing a digi al o ien a ion encou ages employees o p io i ize he
in eg a ion o digi al echnologies o mee he e ol ing digi al e-
qui emen s o businesses and consume s. This enables hem o p o ide
digi al solu ions wi h he po en ial o e olu ionize business models and
enhance consume expe ience and i m pe o mance. The e o e,
implemen ing digi al o ien a ion can enhance he connec ion be ween
en ep eneu ial leade ship and digi al inno a ion.
The asse ion ha employee digi al capabili ies in he IT sec o
media e he ela ionship be ween en ep eneu ial leade ship and digi al
inno a ion, as obse ed in bo h s udies, is consis en wi h p e ious
esea ch conduc ed in non-IT se ings (Bha dwaj e al., 2022; Khin & Ho,
2018; Maliba i & Bajaba, 2022). The unique cons uc o employee
digi al capabili ies dis inguishes his s udy’s indings om hose o
p e ious esea ch, which demons a e ha employees’ digi al capabil-
i ies play a pi o al ole in enabling companies o e olu ionize hei
inno a i e business models and, in u n, hei sus ainabili y pe o -
mance (Khin & Ho, 2018).
Addi ionally, his s udy con ibu es o he exis ing body o li e a u e
on sus ainabili y and digi al inno a ion by examining he impac o
employees’ digi al capabili ies on o ganiza ional digi al inno a ion
wi hin he con ex o he Chinese IT indus y. The success ul execu ion
o digi al inno a ion necessi a es acqui ing digi al echnology and
de eloping no el digi al solu ions, bo h o which equi e p o icien
expe ise om skilled p o essionals. D ucke ’s p oduc i i y heo y,
which posi s ha digi al wo ke s equi e leade ship suppo o enhance
hei digi al capabili ies, alida es his hypo hesis. The indings indica e
ha he con inuous suppo and guidance p o ided by en ep eneu ial
leade ship and employees’ abili y o ecognize oppo uni ies in a ola-
ile, unce ain, complex, and ambiguous (VUCA) en i onmen imp o e
hei digi al skills o e ec i ely na iga e he e ol ing challenges o he
con empo a y digi al landscape (Ochinanwa a e al., 2023). Conse-
quen ly, digi al wo ke s ha e an enhanced unde s anding o he po-
en ial bene i s and limi a ions o digi al echnology. This enhanced
unde s anding empowe s knowledge wo ke s o make well-in o med
and p uden decisions ega ding digi al inno a ion p ocesses. The sec-
ond s udy ocused on he esea ch ques ions. We p o ided an in eg a ed
o e iew o how i ms add ess sus ainabili y challenges h ough digi al
inno a ion. We inco po a ed an addi ional sus ainabili y pe o mance
a iable o assess he ex en o which digi al inno a ion can con ibu e
o a aining sus ainabili y pe o mance in IT i ms. Ou sec o selec ion
was in o med by he IT indus y’s c i ical ole in p o iding he digi al
echnologies equi ed o de ise o wa d-looking solu ions in he exis ing
digi ized economy. Ou indings con i med he exis ence o a posi i e
co ela ion be ween digi al inno a ion and sus ainabili y pe o mance.
These indings a e consis en wi h hose o p e ious s udies ha we e
conduc ed in non-IT se ings. P io s udies ha e demons a ed ha
inno a ion has a subs an ial in luence on sus ainabili y pe o mance
(B occa do e al., 2023; Opland e al., 2022). This inding highligh s he
necessi y o a holis ic app oach o di ec ing o ganiza ional esou ces
owa d achie ing sus ainabili y goals. Ou indings unde sco e he
impo ance o cul i a ing employee capabili ies h ough e ec i e lead-
e ship p ac ices o pa e he way owa d sus ainabili y h ough digi al
inno a ion. This inding sugges s ha o ganiza ions demons a ing
s ong leade ship commi men o adop ing digi al echnologies
(A ´
anega e al., 2023; Fa idian, 2023) and enhancing hei employees’
abili y o na iga e hese echnologies e ec i ely a e mo e likely o
gene a e inno a i e digi al solu ions o en i onmen al and social chal-
lenges, ul ima ely leading o imp o ed sus ainabili y pe o mance.
This s udy adop ed a comp ehensi e app oach ha builds on p e i-
ous esea ch, emphasizing how en ep eneu ial leade ship acili a es
au onomous decision-making and digi al compe ency, which a e c i ical
de e minan s o employee-d i en inno a ion (Felix e al., 2019; Huu,
2023). This app oach u he explo es he ole o en ep eneu ial lead-
e ship in os e ing inno a ion while acknowledging he necessi y o
digi al capabili ies o e ec i ely ansla e au onomy in o inno a i e
ou comes (Huu, 2023). The in e play be ween en ep eneu ial leade -
ship and digi al capabili ies no only d i es inno a i e wo k beha io
bu also aligns wi h sus ainabili y goals by p omo ing au onomous,
adap i e, and e icien p ac ices. This pe spec i e p o ides p ac ical
insigh s in o leade ship s a egies in he IT indus y, pa icula ly in
le e aging leade ship capabili ies o enhance sus ainabili y pe o mance
in he sec o (S aub e al., 2023).
Theo e ical con ibu ions
This s udy makes ou signi ican heo e ical con ibu ions. Fi s , i
inco po a es o ganiza ional and employee ac o s, including en ep e-
neu ial leade ship, digi al o ien a ion, digi al capabili ies, and digi al
inno a ion, wi hin a uni ied model o add ess an unde - esea ched and
c i ical elemen o o ganiza ional pe o mance: sus ainabili y pe o -
mance. This model aimed o cla i y how IT i ms can imp o e em-
ployees’ digi al o ien a ion and digi al capabili ies, he eby p omo ing
digi al inno a ion and a aining sus ainabili y pe o mance.
Second, his s udy ocused on employee ac o s o explo e he ca-
pabili ies equi ed o build a pa hway om inno a ion o sus ainabili y.
Human esou ces a e a c ucial elemen o digi al inno a ion in oday’s
knowledge-dependen and u u e- ocused economy; howe e , hey a e
Table 8
Media ion analysis esul s.
To al e ec (T1-EL ->T3-DI) Di ec e ec s (T1-EL->T3-DI) Indi ec e ec s o T1-EL on T3-DI
Coe icien P- alue Coe icien p- alue Coe icien SD T alue P- alues
0.90 0.00 0.24 0.00 H2b: T1-EL ->T2-DC ->T3-DI 0.417 0.051 8.311 0.000
H3b: T1-EL ->T2-DO ->T3-DI 0.121 0.048 2.584 0.010
Table 9
Assessmen o p edic i e ele ance o compe i i e ad an age.
PLS-SEM LM PLS-SEM-LM
I ems o he dependen a iable MAE Q2 P edic MAE MAE
SP1 0.817 0.228 0.801 –0.052
SP2 0.897 0.249 0.838 –0.034
SP3 0.702 0.316 0.688 –0.019
SP4 0.871 0.307 0.724 –0.027
SP5 0.773 0.218 0.750 –0.073
U.F. Sahibzada e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100723
8
