Qu ainah, Majdi Anwa ; Ayadi, Imen
A icle
The impac o digi al in eg a ion on co po a e
sus ainabili y: Emissions educ ion, en i onmen al
inno a ion, and esou ce e iciency in he Eu opean
Jou nal o Inno a ion & Knowledge (JIK)
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Sugges ed Ci a ion: Qu ainah, Majdi Anwa ; Ayadi, Imen (2024) : The impac o digi al in eg a ion on
co po a e sus ainabili y: Emissions educ ion, en i onmen al inno a ion, and esou ce e iciency in
he Eu opean, Jou nal o Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 9,
Iss. 3, pp. 1-14,
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The impac o digi al in eg a ion on co po a e sus ainabili y: Emissions
educ ion, en i onmen al inno a ion, and esou ce e ficiency in he
Eu opean
Majdi Anwa Qu ainah
a,
*, Imen Ayadi
b
a
College o Business Adminis a ion, Kuwai Uni e si y, Kuwai
b
Facul y o Economic Sciences and Managemen , Uni e si y o S ax, Tunisia
ARTICLE INFO
A icle His o y:
Recei ed 10 Sep embe 2023
Accep ed 23 July 2024
A ailable online 6 Augus 2024
ABSTRACT
This s udy examines he impac o digi al in eg a ion on he en i onmen al sus ainabili y o Eu opean com-
panies om 2016 o 2022, ocusing on emissions educ ion, en i onmen al inno a ion, and esou ce e fi-
ciency. Using a wo-s age sys em gene alized me hod o momen s (GMM) model and quan ile eg ession
wi h ins umen al a iables on panel da a, we in es iga e how digi al echnologies influence co po a e sus-
ainabili y p ac ices. Desc ip i e s a is ics e eal significan a ia ion in digi al echnology adop ion and en i-
onmen al pe o mance among he 22 Eu opean coun ies s udied. Pea son’s co ela ion ma ix and a iance
infla ion ac o analyses confi m he absence o mul icollinea i y among he a iables. The empi ical esul s
om he wo-s age GMM model demons a e ha digi al in eg a ion posi i ely a ec s emissions educ ion,
en i onmen al inno a ion, and esou ce e ficiency. These findings a e consis en ac oss di e en quan iles,
indica ing ha digi al in eg a ion benefi s companies ega dless o hei ini ial sus ainabili y le els. Howe e ,
he impac is mo e p onounced o companies wi h lowe ini ial pe o mance. The Hansen es alida es he
ins umen s used, and he absence o second-o de se ial co ela ion suppo s he obus ness o ou GMM
model es ima ions. The posi i e ela ionship be ween pas and cu en sus ainabili y pe o mance unde -
sco es he dynamic na u e o co po a e en i onmen al p ac ices. Ou s udy highligh s he c ucial ole o digi-
al in eg a ion in p omo ing sus ainable business p ac ices and o e s significan implica ions o
policymake s and business manage s. Companies a e encou aged o assess hei digi al en i onmen al oo -
p in s, in es in sus ainable echnologies, and adop g een inno a ions. Policymake s should suppo he
de elopmen o digi al indus ies and acili a e hei in eg a ion in o adi ional sec o s o enhance o e all
sus ainabili y. The findings con ibu e o unde s anding how digi al ans o ma ion can d i e en i onmen al
sus ainabili y, p o iding a ounda ion o u u e esea ch on he in e sec ion o digi al echnologies and co -
po a e sus ainabili y p ac ices.
© 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/)
Keywo ds:
Digi al in eg a ion
Co po a e sus ainabili y
Eu opean con ex
GMM
IV-QRPD eg ession
JEL classifica ion:
O00
O32
Q56
D83
In oduc ion
Big da a, a ificial in elligence, and cloud compu ing a e examples
o digi al echnology d i ing socie y and he economy in o he digi al
e a, along wi h he swi ad ancemen o in o ma ion echnology (Ji
e al., 2023). “Indus y 4.0”desc ibes his ou h indus ial e olu ion,
defined by a s eady ansi ion o digi al echnology ia ne wo ks con-
nec ing di e en kinds o goods, alue chains, and business models.
The usion o highly in elligen , ne wo ked, and sel -su ficien physi-
cal and digi al echnologies such as he In e ne o Things (IoT),
obo ics, au onomous ehicles, and 3D p in ing opens up new
oppo uni ies o inno a ion, expansion o comme cial ac i i ies, and
de elopmen o an in o ma ion socie y in he e a o Indus y 4.0
(Gembali e al., 2022;Ma»kowska e al., 2021). The ph ase “in o ma-
ion socie y”o igina ed in he 1970s wi h Al in To fle , a dis in-
guished Ame ican sociologis and u u is , and his well-known
echnological wa e heo y (To fle , 1980).
The COVID-19 epidemic, ade dispu es, and geopoli ical un es
ha e c ea ed a mo e complex and demanding economic clima e.
Imp o ing an o ganiza ion’s sus ainabili y has cons an ly eme ged as
he mos e ec i e way o deal wi h he uns able ou side wo ld (Ji e
al., 2023). Academics ypically use “sus ainable de elopmen ”o
“sus ainabili y” o e e o he coexis ence o he ecological en i on-
men and economic p og ess. Specifically, co po a e sus ainable
de elopmen (SD) is defined as a mul i ace ed concep encompassing
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (M.A. Qu ainah).
h ps://doi.o g/10.1016/j.jik.2024.100525
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/)
Jou nal o Inno a ion & Knowledge 9 (2024) 100525
Jou nal o Inno a ion
&Knowledge
h ps://www.jou nals.else ie .com/jou nal-o -inno a ion-and-knowledge
social, economic, and en i onmen al de elopmen and as a business
app oach ha aims o mee cu en needs wi hou impeding u u e
g ow h, conside ing ecological and na u al esou ce- ela ed conce ns
(Klimek, 2020). Socie y 4.0 and Economy 4.0 a e c i ical a eas o Eu o-
pean Union (EU) de elopmen (Kwilinski e al., 2023). The EU’s“Digi-
al Eu ope P og am,” o ins ance, aims o es ablish a sophis ica ed,
in elligen , wen y-fi s -cen u y economy ha should make Eu ope
he mos p oduc i e, in en i e, and “g een”economic powe in he
wo ld (Misu aca e al., 2012).
The cons an accele a ion o echnical ad ancemen s is a neces-
sa y componen o he digi al ans o ma ion o Eu opean na ions.
Howe e , he s a egy o digi ize he Eu opean economy needs mo e
han oaming es ic ions and ee wi eless in e ne access o e e y-
one. The digi iza ion o he Eu opean economy, which includes
manu ac u ing au oma ion and obo iza ion, c ea es p e iously
unhea d-o economic p ospec s. Fu he mo e, e en go e nmen s
unde s and ha ha ing digi al s a egies is c ucial. Fo ins ance, he
EU p esen ed i s digi al s a egy in Feb ua y 2020, s a ing ha
“e e yone is expe iencing he digi al ans o ma ion in hei li e”and
emphasizing ha a digi al s a egy will benefi e e y Eu opean, EU
business, and e en he en i e globe (Eu opean Commission, 2020b).
Go e nmen s and media ou le s wo ldwide now p io i ize emis-
sion educ ions because hey a e essen ial o p o ec he en i on-
men . The e is inc easing global p essu e o subs an ially educe
ca bon emissions om indus ial ene gy use, specifically ocusing on
hea ily emi ing en e p ises in coun ies such as China and he
Uni ed S a es (Ka lila e al., 2023). Gi en ha domes ic and in e na-
ional policies and legisla ion con inually emphasize educing emis-
sions, business owne s mus conside how o help comba clima e
change.
Humans ace eno mous issues ha need ac ion om all pa ies,
including businesses, go e nmen s, and he gene al public. In he
ace o clima e change and esou ce sho age, a new g ow h pa a-
digm ha gua an ees SD is equi ed. Acco ding o he Wo ld Com-
mission on En i onmen and De elopmen , SD can sa is y p esen
needs wi hou endange ing subsequen gene a ions. The main
ocuses o SD a e he p ese a ion o he en i onmen , economic
g ow h, and social inclusion (Ma inakis & Whi e, 2022).
I is challenging o dis inguish be ween he di ec and indi ec
e ec s o in o ma ion and communica ion echnology (ICT) due o
he g ow h o digi aliza ion in en e p ises, homes, and he financial
sec o . Globaliza ion unques ionably influences digi al echnology
adop ion (Ska e & Ribe io So iano, 2021) and how ICT a ec s he
en i onmen (Danish e al., 2018). The scien ific communi y has, in
u n, aken an in e es in his issue, and he e is a significan amoun
o ecen wo k on his no el app oach o p oblem-sol ing. Fo
ins ance, Ahmed e al. (2021) find ha globaliza ion and ICT a o
CO
2
emissions, e en hough expansion and u baniza ion ha m di e -
en laye s o he biosphe e. Vi ual p ac ices, goods, and se ices ha
sa e on ene gy and emissions a e eplacing con en ional p ac ices,
goods, and se ices. T a el and he esul ing emissions a e lowe
hanks o e-comme ce, e-banking, i ual mee ings, and online edu-
ca ion (Adeleye e al., 2021). The impac o obo iza ion, digi iza ion,
and inno a ion on wo kplace p oduc i i y and employmen has also
ecei ed new esea ch a en ion (Balles a e al., 2021). Se e al s ud-
ies p o ide e idence o manu ac u ing p ocess ad ancemen s ha
esul in mo e e ficien wo k eams and mo e e ficien use o esou -
ces (Al-Omoush e al., 2020;Bai e al., 2021;Kliman e al., 2021). Dig-
i al ans o ma ion a all le els also ensu es sus ainable p oduc ion,
consump ion, and business con inui y in any scena io, including pan-
demics.
S udying how he digi al e olu ion a ec s he en i onmen is s ill
in i s ea ly s ages. Fo example, Chen and Hao in es iga e how boa d
s uc u e enhances en i onmen al pe o mance in digi al ans o -
ma ion (Chen & Hao, 2022). Ano he s udy finds ha new ene gy-
e ficien echnologies can educe ca bon dioxide p oduc ion (Cheng
e al., 2021). In addi ion, esea ch shows ha digi izing nondecom-
posable was e subs an ially inc eases was e educ ion (up o 65 %),
acco ding o Ku niawan (2022). Ne e heless, fi m-le el empi ical
esea ch finds scan suppo o he no ion ha digi al pa adigms
imp o e en i onmen al pe o mance. The lack o in-dep h esea ch
in o he co ela ion be ween digi al ans o ma ion and g een sus-
ainabili y hinde s a comp ehensi e unde s anding o he challenges
businesses ace in he digi al age. Fu he mo e, comp ehensi ely
examining he in icacies o he in e dependence be ween digi al
echnology and pollu ion has he po en ial o acili a e s a egies
aimed a enhancing en i onmen al pe o mance (Wang e al., 2022).
Fou ecen s udies a e based on a ious su ey esul s om
China. Li e al. (2020) measu e en i onmen al pe o mance ia
dec eases in ai pollu an s, was ewa e , and solid was e, as well as
imp o emen s in fi m en i onmen al s a us (Li e al., 2023). Th ee
c i e ia assess en i onmen al s a us: whe he he business measu es
i s impac on he en i onmen , whe he p omo ing en i onmen al
sus ainabili y is one o he company’s key aims, and whe he employ-
ees suppo en i onmen al p o ec ion (EP) measu es (Li, 2022;Zhou
& Liu, 2023). In a poll, we use he ollowing s a emen o gauge EP:
“Ou business elimina es was e (ai , wa e , and solid) emissions, he
consump ion o poisonous and haza dous ma e ials, and he e-
quency o en i onmen al mishaps and ene gy use.”
This empi ical esea ch sheds ligh on and assesses how digi al
in eg a ion influences Eu opean businesses’a emp s o educe hei
emissions. This s udy also e eals he ela ionship be ween digi al
in eg a ion and en i onmen al inno a ion in Eu opean companies.
Finally, he s udy un eils how digi al in eg a ion influences esou ce
e ficiency.
This s udy answe s h ee esea ch ques ions. Fi s , how does digi-
al in eg a ion con ibu e o emissions educ ion in Eu opean compa-
nies? Second, wha is he ela ionship be ween digi al in eg a ion
and en i onmen al inno a ion in Eu opean companies? Thi d, how
does digi iza ion a ec Eu opean companies’ esou ces?
This s udy uses a Thomson Reu e s sample o an a e age o 1,738
ESG (en i onmen al, social, and go e nance)-lis ed Eu opean compa-
nies om 2017 o 2022. In addi ion, we use a sophis ica ed gene al-
ized me hod o momen s (GMM) wi h a dynamic panel model ha
simul aneously conside s unobse ed he e ogenei y, se ial co ela-
ion, endogenei y p oblems, and e e se causali y (Win oki e al.,
2012). We use Powell’s (2016) IV-QRPD panel da a model wi h non-
addi i e fixed e ec s, allowing us o es ima e quan ile-specific
e ec s; his desc ibes he influence o explana o y a iables on he
cen al endency and he ails o he condi ional ou come dis ibu-
ion.
A e con olling o sec o and ime e ec s, he esul s indica e
ha digi al in eg a ion significan ly impac s emissions educ ion,
en i onmen al inno a ion, and co po a e esou ce e ficiency. The
heo e ical con ibu ions o hese posi i e impac s b ing new pe -
spec i es ega ding how digi al echnologies may p omo e co po a e
sus ainabili y and en i onmen al esponsibili y na ionally. These
findings may be ele an in guiding public policies, business s a e-
gies, and u u e esea ch o os e a mo e sus ainable economy.
The con e gence o digi al ans o ma ion and ESG p ac ices
p esen s an in iguing a ea o esea ch. Howe e , ou s udy aims o
add ess significan gaps in he li e a u e. While digi al ans o ma ion
is ad ancing apidly, i s di ec impac on co po a e sus ainabili y
emains inadequa ely explo ed, pa icula ly wi hin nonfinancial
Eu opean companies and unde he umb ella o ESG c i e ia. Exis ing
s udies o en o e look he specific con ibu ions and challenges aced
by sec o s ou side o finance, which play pi o al oles in sus ainabil-
i y e o s. This neglec limi s ou unde s anding o how digi al in e-
g a ion influences sus ainabili y p ac ices ac oss di e se sec o s and
o e looks sec o -specific dynamics c ucial o e ec i e policy and
business s a egy o mula ion. The exis ing esea ch me hodologies’
empo al dynamics and endogenei y conce ns pose subs an ial
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
2
challenges. Many s udies ail o accoun o hese ac o s adequa ely,
po en ially skewing causal in e ences abou he e ec s o digi al ech-
nologies on sus ainabili y ou comes. Ou s udy aims o mi iga e hese
me hodological gaps by u ilizing obus panel da a spanning 6 yea s
and employing ad anced econome ic echniques like he sys em
gene alized me hod o momen s (SGMM) and ins umen al a iable
quan ile eg ession panel da a (IV-QRPD). These me hods enable us
o explo e he ela ionships and cap u e he a ying impac s o digi al
in eg a ion on ESG pe o mance ac oss di e en quan iles o sus ain-
abili y, he eby con ibu ing me hodological ad ancemen s o he
field. Ul ima ely, ou esea ch seeks o deepen heo e ical insigh s
and p o ide ac ionable insigh s o policymake s and businesses
s i ing o in eg a e digi al echnologies e ec i ely in o sus ainable
p ac ices ac oss Eu ope.
The esea ch on he ela ionship be ween digi al in eg a ion and
ESG pe o mance p o ides heo e ical insigh s in o how digi al ech-
nologies can d i e sus ainable business p ac ices. We con ibu e o
he li e a u e by demons a ing ha digi al ans o ma ion is a ech-
nological ad ancemen and a significan enable o co po a e sus ain-
abili y.
The subsequen sec ions o his pape a e s uc u ed as ollows:
The fi s sec ion p esen s an in oduc ion, and he second sec ion
p esen s he heo e ical amewo k. The hi d sec ion de elops he
hypo heses. The ou h sec ion discusses he esul s and co espond-
ing discussions. Finally, we conclude by add essing he implica ions
o his esea ch o esea che s, manage s, and policymake s.
Theo e ical amewo k
The e ec s o in eg a ing digi al echnology in o company sus ain-
abili y s a egies a e mul i ace ed and encompass many in e depen-
den in e ac ions. To gain a holis ic and in-dep h unde s anding, we
app oach di e en aspec s o digi al in eg a ion and en i onmen al
sus ainabili y by combining di e en heo ies. The esou ce-based
iew (RBV) heo y ocuses on companies’in e nal esou ces; he
echnological inno a ion heo y ocuses on adop ing new echnolo-
gies; and he ins i u ional heo y analyzes ins i u ional p essu es.
S akeholde heo y conside s s akeholde expec a ions, while g een
IT and sus ainable business heo ies ocus specifically on he en i on-
men al p ac ices o digi al businesses.
Resou ce-based iew
Fo a long ime, one o he mos significan concep ual ame-
wo ks in academics has been he RBV. This app oach asse s ha
companies’unique, ha d- o- ep oduce esou ces and skills o m he
basis o hei compe i i e ad an age and excess e u ns, hus explain-
ing he dispa i ies in pe o mance among di e en o ganiza ions
(Ba ney, 2000). Resou ces and new compe encies a e equi ed o
build a las ing compe i i e edge in he digi al age (Liu e al., 2011).
Due o a as -paced clima e whe e gaining and main aining a sus-
ained compe i i e edge, e en o limi ed pe iods, has become mo e
challenging, fi ms oday ace ising unp edic abili y and complexi y.
Emb acing he ongoing indus ial e olu ion, p ima ily digi al, and
adjus ing o echnological imp o emen s is one o he g ea es di fi-
cul ies acing o ganiza ions oday. This is pa icula ly ue o compa-
nies ha did no s a digi ally o globally bu a e eage o expand
in e na ionally o cap u e a la ge ma ke . Digi al ans o ma ion is a
c ucial and economical s a egy o hese companies o ob ain a com-
pe i i e edge. Expanding in o new o e seas ma ke s h ough digi al
expo s o e-comme ce is one o he mos e ficien ways o accom-
plish his goal (Kehinde e al., 2022;Pe gelo a e al., 2019).
Abu Hasan e al. (2022) find ha companies can use angible and
in angible esou ces o c ea e a compe i i e edge. On he o he hand,
he li e a u e on s a egic managemen is no ye clea abou he
ex en o which en e p ise esou ces and alen s con ibu e o
compe i i e ad an ages h ough he in eg a ion o digi al echnology.
Resea che s claim ha he capabili y o inno a ion and in eg a ed
echnology inc easingly influences he iabili y o small- and
medium-sized fi ms (Abu Hasan e al., 2022). Acco ding o he RBV, a
fi m’s esou ces can imp o e pe o mance and sus ainabili y. These
include indi idual ac ics, co po a e esou ces, and pa icula in e nal
cha ac e is ics (Locke e al., 2009).
Many esea che s claim ha he influence o digi al ad ances on
eco- iendly p ac ices emains unce ain (Di
o
asi-Ko
acs & Nagy,
2023). On he one hand, he p oli e a ion o ICT ools and digi al ech-
nologies, along wi h hei capabili y and pe o mance g ow h, aises
ene gy demand. A he same ime, he significan en i onmen al
damage caused by elec onic was e d aws a en ion o he ad e se
e ec s o echnology li e cycles (Chen e al., 2020). Con e sely, using
digi al echnology and subsequen ly enhancing he p oduc i i y o
businesses and indus ial p ocesses may enable us o educe ou
ene gy consump ion, was e, pollu ion, and wo kload (Li e al., 2023).
Addi ionally, IT acili a es he coo dina ion o p oduc design and
manu ac u ing, enhancing he impac o en i onmen al p ac ices
(Gimenez e al., 2015). Co po a e social esponsibili y (CSR) epo ing
is a highly complex p ocess equi ing s o ing, p ocessing, and analyz-
ing la ge amoun s o da a. This is an a ea whe e digi al echnologies
can make significan p og ess. Quan i a i e and quali a i e da a can
help e alua e company pe o mance, and he sus ainabili y pe spec-
i e adds a laye o complexi y ha necessi a es cu ing-edge ech-
nology (Lind o s, 2021). Acco ding o B occa do e al. (2023),
ad ancing digi al echnologies helps en i onmen al managemen
me hods become mo e success ul.
The implica ions o digi al ans o ma ion on en i onmen al pe -
o mance a e cu ilinea (Li e al., 2023). A ebound e ec can happen
when handling da a, which nega i ely impac s he en i onmen (by
using mo e ene gy, con ibu ing o e-was e, e c.). Ini ially, EP
inc eases in he ea ly s ages o digi al ans o ma ion (by using ech-
nologies o op imize and manage esou ce use). Acco ding o he
RBV, a fi m’s pe o mance and compe i i e ad an age a e signifi-
can ly influenced by i s capabili ies and esou ces. Businesses can
gain and main ain compe i i e ad an age by using esou ces ha a e
aluable, a e, inimi abili y, and non-subs i u able (VRIN). Digi al
in eg a ion can be seen as a s a egic ool ha imp o es a company’s
en i onmen al managemen capaci ies. By in es ing in digi al ech-
nologies, businesses can c ea e dis inc i e capabili ies o esou ce
e ficiency, ca bon educ ion, and en i onmen al inno a ion. This is
consis en wi h he RBV’s ocus on u ilizing in e nal esou ces o
a ain highe pe o mance le els.
Technological inno a ion heo ies
In oducing new echnology signals a shi in economic sys ems.
Al hough digi iza ion is a as -e ol ing sec o o na ional conce n,
pa icula ly ega ding long- e m economic iabili y, i has benefi s
and d awbacks. The sea ch o a iables a ec ing economic g ow h
in he socioeconomic sec o has changed as esea ch ends in he
business sec o ha e e ol ed. Along wi h socie al ad ancemen , is-
ing indus ializa ion, en i onmen al de e io a ion, and o he inde-
penden a iables, he business sec o is as changing (Xu e al.,
2022). Fo example, Maiu o a e al. (2022) examine he en i onmen-
al e ec s o digi aliza ion in wo Ge man ci ies. They asse ha digi-
aliza ion is e olu iona y in educing municipal solid was e and
g eenhouse gas emissions, conse ing aw ma e ials, c ea ing jobs,
and imp o ing ene gy and machine y e ficiency. Al hough exis ing
esea ch indica es ha using con en ional ossil uels is di ec ly
ela ed o inc eased emissions (Abbasian Fe eidouni & Kawa, 2019),
financial inno a ion and digi iza ion suppo he p oduc ion and use
o enewable ene gy, he eby lowe ing emissions (Maiu o a e al.,
2022).
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
3
Se e al s udies in he mos ecen li e a u e find e idence ha
digi aliza ion influences en i onmen al quali y. Fo ins ance, empi i-
cal esea ch shows ha digi aliza ion imp o es en i onmen al qual-
i y by educing ca bon, g eenhouse gas, and o he pollu ion
emissions (Xu e al., 2022). Digi aliza ion also imp o es echnical
inno a ion, which in u n inc eases ene gy e ficiency, educes he
demand o ene gy ( ossil uels), and, as a esul , educes emissions
and o he pollu ion. Addi ionally, digi aliza ion suppo s g een glob-
aliza ion, ene gy e ficiency, g een expo alues, and a educ ion in
pollu ing businesses, acco ding o Xu e al. (2022).
The in e dependence o sus ainable de elopmen goals (SDGs) is
e iden . Sus ainable p ac ices use syne gies ha lessen he e ec s o
clima e change. Fo ins ance, low-ca bon ene gy sys ems can ack
and p edic clima e and biodi e si y changes o e ime wi h highly
e ec i e enewable ene gy in eg a ion, hanks o digi aliza ion and
a ificial in elligence. Addi ionally, clima e esea ch elies on mul i-
spa ial- empo al clima ic da a o unde s and clima e a iabili y and
u u e p ojec ions. Fo ecas ing has changed due o he digi aliza ion
o his o ical clima e da a and he a ailabili y o eal- ime clima e
da a. This has also gi en ise o a amewo k o unde s anding cli-
ma e e en s and hei implica ions o biodi e si y. Also, he IoT has
d ama ically imp o ed eal- ime, ex ensi e da a analysis and da a-
collec ion echniques, which could make implemen a ion easie .
Mul i-spa ial- empo al clima ic da a a e a s a ing poin in clima e
esea ch o analyzing wea he condi ions and p ojec ions. Digi izing
his o ical and cu en clima e da a has al e ed ex eme wea he p e-
dic ion and he c ea ion o p e en ion and adap a ion s a egies
(Mu ugesan, 2008). Wi hou a doub , digi izing collec ion-based
esea ch hus acili a es he compila ion and e alua ion o biological
baselines o es ima ing he e ec s o clima e change, changes in land
use (physical and biological quali ies o land), land co e (human use
o land), in asi e species, and consequences o human ac i i y on
species di e si y (Hed ick e al., 2020).
Ins i u ional heo y
Acco ding o ins i u ional heo y, an o ganiza ion mus adhe e o
socie al no ms, ules, and expec a ions o become legi ima e and
endu e in i s su oundings. This heo y s ongly emphasizes how
ex e nal ac o s—such as legal equi emen s and social no ms—
shape o ganiza ional beha io . The ins i u ional heo y o o ganiza-
ions places ins i u ions a he cen e o examining he o ma ion and
ope a ion o o ganiza ions. O ganiza ions, in his pe spec i e, a e
egional ins an ia ions o la ge ins i u ions. Ins i u ions shape o ga-
niza ional o ms, design elemen s, accep ed belie s, egula ions, and
con en ions. Following es ablished ules gi es an o ganiza ion legi i-
macy, educes unce ain y, and makes i s ac ions and ope a ions
mo e unde s andable (Be hod, 2016).
Acco ding o ecen li e a u e, ins i u ional amewo ks suppo a
na ional and in e na ional o ganiza ions’s uc u e. They in oduce
social conduc , mo al s anda ds, and con en ions ha p oduce
impo an ules (Bi ek ine e al., 2018). Ins i u ional heo y explains
o ganiza ional beha io , pa icula ly conduc ha is en i onmen ally
iendly. This beha io includes business me hods o conse ing
ene gy, en i onmen al managemen , and ecological esponsi eness
(Qian e al., 2015). Acco ding o ins i u ional heo y, he ins i u ional
en i onmen s in which a co po a ion ope a es significan ly a ec i s
pe o mance (bo h in e ms o economic and en i onmen al ac o s).
Fi ms unc ion like open sys ems, whe e in e ac ions wi h he en i-
onmen , which comp ises laws and no ms, no ma i e iews, and
social alues, happen egula ly (La i e al., 2020). Businesses end o
con o m o ins i u ional se ings o be e fi in o he en i onmen
because hey seek he legi imacy o con o ming o socie al and egu-
la o y egimes (Colwell & Joshi, 2013). We go in o de ail on how busi-
nesses emb ace digi al echnologies o inc ease en i onmen al
sus ainabili y because o ins i u ional p essu es. Go e nmen s,
consume s, in es o s, and o he s akeholde s a e pu ing mo e and
mo e p essu e on businesses o ac esponsibly owa d he en i on-
men . By in eg a ing digi ally, businesses can be e ulfill hese
demands and adhe e o en i onmen al egula ions.
S akeholde heo y
S akeholde heo y s a es ha companies s eng hen hei ies o
s akeholde s o ensu e sus ainable pe o mance and compe i i e
ad an ages (Abdullah e al., 2016). In addi ion, s akeholde heo y
pos ula es ha s akeholde engagemen inc eases pe o mance while
educing en i onmen al unce ain y and cos s. Se e al au ho s claim
ha educing en i onmen al unce ain ies can help o ganiza ions
be e manage hei p oduc s and se ices, hi e and e ain quali y
people, imp o e hei epu a ions, os e g ea e consume loyal y,
main ain compe i i e ad an ages, and minimize isk (Zailani e al.,
2019). Fu he mo e, imp o ed En i onmen al Managemen Accoun -
ing (EMA) p ac ices can dec ease en i onmen al unce ain y, enhanc-
ing how o ganiza ions use angible and in angible esou ces o
sa egua d he en i onmen and economic pe o mance (Ho e e al.,
2012).
G een IT and sus ainable business models
Business model inno a ion (BMI) has been well-known in ecen
co po a e p ac ice and esea ch (Bianchini e al., 2023). Acco ding o
se e al s udies, a BMI shi can lead o (E ans e al., 2017) and help
inco po a e sus ainabili y in business de elopmen (Schal egge e
al., 2012). Sus ainable business model inno a ion (SBMI) is o ficially
pa o BMI, and i is ob ious how BMI con ibu es o he g ow h o
sus ainable consump ion and p oduc ion (SCP) (Geissdoe e e al.,
2018).
E en hough con en ional inno a ion ac i i ies significan ly ha m
he en i onmen bu p oduce apid ma e ial ad ancemen , esea ch-
e s and businesses a e becoming mo e in e es ed in g een inno a-
ion, especially wi h he ad en o new echnologies and ma e ials.
G een echnology inno a ion (GTI), howe e , was no a ho opic o
schola s un il 2007, p ima ily because o he un es a he Uni ed
Na ions Clima e Change Con e ence ha yea and he U.S. go e n-
men ’s d ama ic signing o he Bali Road Map a he end o he con e -
ence (Halle e al., 2024). Since 2008, indus ialized and de eloping
na ions ha e s ongly emphasized achie ing emissions neu ali y,
and de eloping g een, low-ca bon echnologies is now a common
conce n o comba ing clima e change and global wa ming (Zhou e
al., 2023).
In con as , Shi and Lai find ha ich coun ies a e mo e in e es ed
in GTI han de eloping ones based on he g ow h a e o o e all pub-
lica ions (Shiu & Yang, 2017). Second, GTI is a wo ldwide phenome-
non, and in ecen yea s, esea ch on GTI in eme ging economies has
d as ically g own. The Chinese go e nmen ’s announcemen a he
15 h In e na ional Clima e Change Con e ence, held in Copenhagen
in 2009, ega ding i s inc eased global esponsibili y o low-ca bon
economic de elopmen and i s commi men o he Uni ed Na ions
o i s emission educ ion a ge s, is one possible explana ion. China
is a ed among he wo ld’s op na ions ega ding g een echnical
inno a ion ela ing o he en i onmen compa ed o o he na ions
and a eas (Zhou e al., 2023).
Hypo heses de elopmen
Since he 1990s, en i onmen al and social issues ha e become
inc easingly impo an o all en e p ises a bo h ope a ing and s a-
egic le els. Fu he , COP 23— he Con e ence o Pa ies o he Uni ed
Na ions F amewo k Con en ion on Clima e Change—emphasizes he
u gen need o con ol hei business impac ac oss he en i e p o-
duc ion alue chain (Uni ed Na ions, 2017). Sus ainabili y pilla s
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
4
mus in eg a e wi h a company’s s a egy, planning, and o ganiza-
ional cul u e. Sus ainabili y should, he e o e, be embedded in he
o ganiza ion, bo h a a s a egic and an ope a ing le el, in line wi h a
holis ic and pe asi e goal o maximizing benefi s and imp o ing
financial pe o mance.
Un o una ely, he ways companies in e p e and implemen sus-
ainabili y p inciples and ansla e goals in o ac ions a e no homoge-
neous due o dissimila i y in indus y ea u es o in e nal ea u es,
such as size, age, o o ganiza ional s uc u e. Di e en ools should
suppo his implemen a ion, including p og ams o sus ainabili y
epo ing, moni o ing sys ems, specific digi al echnologies, business
p ocess eenginee ing, and sus ainable p oduc designs (B occa do e
al., 2023).
Afi m’s abili y o manage u gen en i onmen al and social chal-
lenges is c ucial o i s success because doing so is essen ial o gene -
a ing new alue (B e on, 2015). The li e a u e indica es ha
sus ainabili y has pa icula s a egic impo ance o businesses and
a ious s akeholde s (Nekhili e al., 2017); a comp ehensi e unde -
s anding o sus ainabili y is hus necessa y o balance economic
g ow h, en i onmen al p ese a ion, and social p o ec ion (Be gman
e al., 2018). Managing sus ainabili y e ec i ely is c ucial o main-
aining i s significance and p o iding alue o s akeholde s (Lee &
Raschke, 2020). Businesses hus spend mo e on sus ainabili y o a -
ious easons, including comme cial success, legi imacy, o in e nal
de elopmen (Mohapa a, 2023;Windolph e al., 2014). Ex e nal
ma ke p essu e, legal amewo ks, and s akeholde expec a ions
may also s eng hen a company’s commi men o sus ainabili y
(Tes a e al., 2016).
The benefi s o an inno a ion-spu ing digi al economy on a low-
ca bon ajec o y may ha e his o ically been o e s a ed. Acco ding o
one s udy, since China s a ed i s ca bon emission ading pilo p o-
g am, he digi al economy has conside ably assis ed he es ablish-
men o low-ca bon en e p ises (Zhang e al., 2022). Also, some
esea che s find ha he de elopmen le el o he digi al economy
(DLDE) has a a o able e ec on he educ ion o CO
2
emissions; hey
also use in e p o incial panel da a o find a no able impac on
egional di usion (Hao e al., 2022).
Jing Dong (JD) Company in China is an example o an e ec i e CER
u ilizing digi al economy echnologies. JD’s da a cen e employs
ene gy-sa ing echnology, including indi ec e apo a i e cooling and
equency con e sion. Economic managemen g adually educed he
da a cen e ’s a e age yea ly powe use, making i mo e en i onmen-
ally iendly. Addi ionally, JD G oup en e ed in o a business alliance
wi h Didi Taxi o p omo e ca -sha ing among employees, educing
CO
2
emissions by a ound 270,000 kg. JD uses ecyclable shipping
boxes and looks o g een models o p oduc packaging (Meng e al.,
2023). In addi ion, JD launched a digi al collec i e supply chain o
p omo e collabo a i e e o s among companies o achie e sus ain-
able g ow h.
S eamlining he u iliza ion o da a and in o ma ional asse s
wi hin he digi al economy may be a mo e e ec i e way o educe
he cos s o alloca ing human and ma e ial esou ces. Addi ionally,
s eamlining he u iliza ion o da a and in o ma ional asse s can os-
e inno a ion and con e gence o imp o e economic ansac ions’
e ficacy and be e manage ene gy esou ce consump ion. This signi -
ican ly lowe s ca bon emissions by c ea ing an open, sha ed, and
symbio ic ecology. This leads us o he ollowing:
Hypo hesis 1. Digi al in eg a ion inc eases emissions educ ion e o s.
Digi aliza ion is a significan economic and social change agen in
he EU (Ha, 2022). I s e ec s on he en i onmen appea h ough a -
ious mediums. Fo example, he enhanced collec ion and ecycling o
elec onic ash and he euse o ma e ials con ibu e o de eloping a
ci cula economy, all made possible by echnology (Eu opean Com-
mission, 2020a). Digi al solu ions can sol e se e al en i onmen al
challenges, including solid was e, e-was e, ood was e, and
ag icul u al was e. Addi ionally, se e al esea che s ha e s udied
hese sys ems (Hung e al., 2023). The e a e also nume ous ways in
which digi al echnologies may help o p omo e biodi e si y (Ha,
2022). Visualizing and dissemina ing biological da a, such as ICT, can
boos policy e ec i eness and public unde s anding.
Addi ionally, digi aliza ion can c ea e economic models ha aid in
hal ing biodi e si y decline (Ha & Thanh, 2022). O he significan
ou es exis , such as en i onmen al p ese a ion, sus ainable ag icul-
u e, and u ban sus ainabili y. Howe e , digi al echnologies can help
manage p oblems wi h ai and wa e pollu ion caused by hea y and
chemical indus ies. Digi al echnology can also help sol e en i on-
men al issues such as ai pollu ion, g eenhouse gas emissions, was e-
wa e ea men , and clima e change (Fe oz e al., 2021). Digi al
echnology in manu ac u ing can implemen g een ene gy, ene gy
sa ings, o enewable ene gy (Ha & Thanh, 2022).
Fu he mo e, companies can educe ope a ing cos s and imp o e
wo ke sa e y by in oducing cleane and mo e sus ainable p ocesses
(Zhang e al., 2017). Sus ainable p oduc ion can also educe esou ce
consump ion and deg ada ion (Roy & Singh, 2017). We can add ess
esou ce sho ages, a fic conges ion, and ai pollu ion by in oduc-
ing digi al echnologies such as big da a, cloud compu ing, and a ifi-
cial in elligence (Wu e al., 2021).
The li e a u e also s udies he connec ion be ween digi aliza ion
and “con en ional”inno a ion. ICTs and cloud compu ing in es -
men s a e acili a o s o inno a ion, acco ding o he OECD Digi al
Economy Ou look 2020. We p opose ha digi al in eg a ion os e s
inno a ion by p o iding fi ms wi h ad anced ools and capabili ies o
de elop g een echnologies. This aligns wi h he RBV’s ocus on using
unique capabili ies o d i e inno a ion and compe i i e ad an age.
Hence,
Hypo hesis 2. Digi al in eg a ion inc eases en i onmen al inno a ion.
Inc eased esou ce e ficiency in manu ac u ing en e p ises is in i-
ma ely linked o inc eased digi aliza ion o e ec i e business admin-
is a ion and es ablishing a con ol hub o p ese e and alloca e
esou ces (Vazhenina e al., 2023). Resou ces, capabili ies, and o ga-
niza ion a e he main elemen s influencing ope a ional e ec i eness
(Li & Jia, 2018). Aligned wi h he co e ene s o he esou ce-based
pe spec i e, he cul i a ion o compe i i e ad an ages necessi a es
p ocu ing esou ces ha a e aluable, a e, di ficul o eplica e, and
essen ial (Ba ney, 1991). Thus, in addi ion o land, capi al, and labo ,
digi al esou ces ha e become impo an o de eloping a digi al
economy. By enabling businesses o implemen in elligen p oduc-
ion, ope a ions, and managemen , hey can significan ly inc ease
p oduc i i y, alue, and compe i i eness (Chaudhu i e al., 2022).
The widesp ead in eg a ion o a ificial in elligence, cloud com-
pu ing, blockchain, and o he ecen echnologies in o adi ional
manu ac u ing p ocesses is also helping businesses op imize p o-
cesses, educe ope a ing expenses, boos p oduc ion e ficiency, c ea e
e ficien and adap able ope a ional amewo ks, and consolida e he
quali y o o ganiza ional planning, among o he hings (Mikale &
Pa eli, 2017). Also, he e ficien exchange o in e nal in o ma ion in a
digi al se ing mi iga es he p incipal−agen p oblem, which enhan-
ces he company’s in e nal con ols and capaci y o esou ce alloca-
ion (F ynas e al., 2018). Th ough digi al ans o ma ion, en e p ises
can es ablish a esh ope a ional pa adigm and o ganiza ional man-
agemen amewo k (Konopik e al., 2022).
The ins i u ional-based iew (IBV) con ends ha a c i ical de e -
minan o an o ganiza ion’s size is i s capaci y o espond o changes
in he ex e nal ins i u ional en i onmen (Pa naik e al., 2022). No a-
bly, digi al ans o ma ion now in ol es en e p ises ups eam and
downs eam in he indus ial chain (Li, 2020), os e ing an ongoing
exchange wi h compe ing fi ms, online se ices, and go e nmen al
o ganiza ions o acqui e in o ma ion, echnology, and money (Teece,
2018). This occu s because he indus ial sys em con inuously
expands, and he di ision o labo is mo e specialized. Consequen ly,
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
5
digi al ans o ma ion allows businesses o no only mas e addi-
ional digi al esou ces bu also o es ablish close links wi h and
acqui e o he economic ac o s.
Businesses can use his knowledge o gain a compe i i e edge. Fo
example, web-based pla o ms enable businesses o combine mass
cus omiza ion and pe sonaliza ion seamlessly, achie ing dis inc ion
and cos educ ion simul aneously (Mou zis e al., 2014). Digi al
echnology can has en in o ma ion di usion and dissemina ion,
which benefi s business communica ion and lowe s sea ch cos s
(Malone e al., 1987). As a esul , o ganiza ions can be e assess hei
compe i i e posi ions and connec wi h mo e ups eam and down-
s eam fi ms. Also, businesses ha unde go digi al ans o ma ion
can be e alloca e hei in e nal and ex e nal esou ces and boos
ope a ions, managemen , and p oduc ion e ficiency, s eng hening
hei abili y o main ain hei co po a e sus ainabili y p og ams.
The e o e, we hypo hesize ha digi al in eg a ion, as a aluable
esou ce, enables fi ms o implemen mo e e ficien p ocesses and
echnologies, leading o educed emissions. This hypo hesis is
g ounded in he RBV’s emphasis on le e aging in e nal esou ces o
pe o mance imp o emen .
Hypo hesis 3. Digi al in eg a ion inc eases esou ce e ficiency.
Resea ch design and me hodology
Ou s udy ocuses on Eu opean ESG-lis ed companies be ween
2017 and 2022, co esponding o he g owing awa eness o digi al
ans o ma ion and ESG ini ia i es among policymake s wo ldwide.
This ime ame spans 6 yea s, p o iding aluable panel da a o
add ess po en ial endogenei y conce ns in ou model specifica ions.
Sample selec ion
We ollowed a s uc u ed me hodology o c ea e a ep esen a i e
Eu opean sample o companies. The selec ion p ocess ook place in
se e al s ages o gua an ee he obus ness and ep esen a i eness o
ou sample:
Ini ial popula ion: Ou ini ial s udy popula ion consis ed o 2575
companies lis ed on Eu opean s ock exchanges and included in he
Thomson Da as eam and ASSET4 da abases.
Sec o exclusions: The financial sec o , which includes financial
ins i u ions, insu ance companies, and eal es a e fi ms, was
excluded om ou sample due o i s dis inc ac i i ies and egula o y
en i onmen . This sec o di e s conside ably om he o he sec o s
in o ganiza ional and concep ual e ms, which could in oduce he -
e ogenei y in o ou analysis.
Da a comple eness: Companies wi h missing da a o dependen
o explana o y a iables du ing he sampling pe iod we e excluded
o ensu e a well-balanced panel. This s ep was c ucial o main aining
he in eg i y o he s a is ical analysis and a oid bias caused by
incomple e da a.
A e hese exclusions, ou final sample comp ises 1,738 nonfi-
nancial companies om 22 Eu opean coun ies, ep esen ing nine
sec o s: basic ma e ials, consume goods, consume se ices, oil and
gas, heal hca e, indus ial p oduc s, echnology, elecommunica ions,
and u ili ies. This comp ehensi e da a se co e s 6 yea s and includes
12,166 obse a ions.
Da a collec ion p ocess
The da a collec ion o ou s udy was based on h ee p ima y
sou ces:
Thomson da as eam: This da abase p o ided us wi h financial
and ma ke in o ma ion o he companies in ou sample. Da as eam
is enowned o i s ex ensi e co e age and eliabili y, which gua an-
ee he accu acy o he financial da a used in ou analysis.
Refini i Eikon da abase: This sou ce p o ides de ailed da a on
companies’ESG pe o mance. ASSET4 is ecognized o i s comp e-
hensi e ESG indica o s, enabling a p ecise assessmen o companies’
sus ainabili y p ac ices and digi al in eg a ion.
Eu opean Commission: We supplemen ed ou da ase wi h ele-
an policy and egula o y in o ma ion om he Eu opean Commis-
sion. This in o ma ion is c ucial o unde s anding he egula o y
amewo k influencing ESG p ac ices and he digi al ans o ma ions
o companies in Eu ope.
The da a has been sys ema ically ex ac ed and e ified o ensu e
consis ency and eliabili y. In eg a ing hese di e en sou ces has
esul ed in a comp ehensi e and obus da ase co e ing he finan-
cial, ESG, and egula o y aspec s o he companies in ou sample.
By ollowing his igo ous da a collec ion p ocess, we aim o p o-
ide an in-dep h and eliable analysis o he ela ionship be ween
digi al ans o ma ion and he ESG p ac ices o Eu opean nonfinancial
companies.
The measu emen o he a iables. The measu emen o a iables,
which encompasses he cha ac e is ics o a se o alues ha can be
nume ically quan ified, ollows a classical app oach. I in ol es a
dependen a iable along wi h independen and ins umen al a ia-
bles. Fu he mo e, we inco po a e con ol a iables o ensu e an
unbiased es ima ion o he pa ame e o in e es .
Dependen a iables: co po a e sus ainabili y
Co po a e sus ainabili y is he dependen a iable in ou econo-
me ic model and is measu ed using he en i onmen al pilla o he
Refini i ESG index. In es o s widely use his pilla o measu e co po-
a e beha io in en i onmen al, social, and go e nance con ex s (Issa
& Hanaysha, 2023;Konadu e al., 2022;Se a eim, 2015). The en i on-
men al pilla o he Refini i ESG Index is based on h ee ca ego ies:
esou ce use, emissions, and inno a ion.
We use h ee specific co po a e sus ainabili y indica o s: emis-
sions educ ion sco es, en i onmen al inno a ion sco es, and
esou ce e ficiency sco es, as explained in he Refini i ESG Index
(Refini i Eikon Da as eam, 2022):
Emissions sco e: This assesses a company’s willingness and abili y
o educe en i onmen al emissions as pa o i s manu ac u ing and
ope a ing ac i i ies (Issa & Hanaysha, 2023;Refini i Eikon
Da as eam, 2022).
En i onmen al inno a ion sco e: This e e s o inno a i e en i-
onmen al echnologies and p ocesses, o ecologically designed
goods, as well as he abili y o minimize en i onmen al cos s and dis-
ad an ages o consume s, he eby opening up new business oppo -
uni ies (Konadu e al., 2022;Refini i Eikon Da as eam, 2022).
Resou ce use sco e: This eflec s a company’s abili y o imp o e
he use o ma e ials, ene gy, wa e , and ecology h ough be e sup-
ply chain managemen (Refini i Eikon Da as eam, 2022;Se a eim,
2015).
These comp ehensi e sus ainabili y indica o s p o ide aluable
in o ma ion on he en i onmen al p ac ices and e ficiency o he
companies we e alua e. These measu es a e essen ial o unde s and-
ing how companies in eg a e SD in o hei ac i i ies and hei en i-
onmen al impac . The de ailed assessmen o hese a iables
enables a nuanced analysis o companies’sus ainabili y pe o mance
and i s de e minan s.
Explana o y a iables: in eg a ion o digi al echnology. Digi al
in eg a ion is a complex phenomenon wi h a ious dimensions, mak-
ing i challenging o accu a ely es ablish p ecise pa ame e s o mea-
su e i s dynamics and changes.
To unde s and he ela ionship be ween digi al ans o ma ion
and business sus ainabili y, we ely on he o ficial Eu opean da abase
o indica o s o he Digi al Economy and Socie y Index. One o hese
indica o s, “In eg a ion o Digi al Technology,”pe ains o using he
la es echnological ad ancemen s in business and e-comme ce. I
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
6
encompasses “business digi aliza ion”and ”e-comme ce,”as he
Eu opean Commission explains (Eu opean Commission, 2020a).
The business digi aliza ion ca ego y comp ises ou indica o s ha
measu e he pe cen age o companies u ilizing elec onic in o ma-
ion sha ing, social media pla o ms, big da a analy ics, and cloud sol-
u ions. The e-comme ce segmen includes h ee indica o s: he
pe cen age o companies engaged in online sales, he a io o e-com-
me ce e enue o o al company e enue, and he pe cen age o com-
panies conduc ing online sales in e na ionally.
By u ilizing hese indica o s, we gain aluable insigh s in o he
ex en o digi al echnology adop ion and i s impac on sus ainabili y.
Con ol a iables. We ca e ully accoun o a ious ac o s in ou
analysis. To add ess he influence o company size, we use he na u al
loga i hm o o al asse s a yea -end, ollowing p e ious s udies
(Ma sa e al., 2021;Ni ino e al., 2021). We measu e financial pe o -
mance ia e u n on asse s (ROA), he a io o ne income o o al
asse s, consis en wi h p e ious esea ch (Ma sa e al., 2021;Ni ino
e al., 2021). We measu e ma ke pe o mance wi h he ma ke - o-
book a io, as in Ma sa e al. (2021). Boa d size is he numbe o
di ec o s on he boa d, as in Ya am and Adapa (2021).
To measu e boa d independence, we ollow Ya am and Adapa
(2021) and conside he pe cen age o independen di ec o s on a
boa d. Addi ionally, we inco po a e wo dummy a iables—INDUS-
TRY DUMMY and Coun y DUMMY— o accoun o indus y and coun-
y di e ences, he eby enhancing he compa abili y o ou esul s.
Fu he mo e, we in oduce annual fixed e ec s (FE; YEAR DUMMY) o
cap u e empo al a ia ions in p oduc ion, eflec ing economic cycles
and mac oeconomic fluc ua ions (Nguyen e al., 2015).
By ca e ully accoun ing o hese a iables, we enhance he
s eng h and alidi y o ou analysis.
Ins umen al a iable. We e alua e each company’s en i onmen-
al managemen e ficiency; specifically, we ask whe he he company
holds he ISO 14000 ce ifica ion. This ce ifica ion signifies he adop-
ion o en i onmen al managemen sys ems (EMS) based on s and-
a ds es ablished by he In e na ional O ganiza ion o
S anda diza ion (ISO) (Aba & Bada , 2013;Delmas & Mon iel, 2008;
Eps ein & Roy, 1997). Among he ISO 14000 amily o no ms, ISO
14001 is he mos significan , ou lining EMS equi emen s ha
o ganiza ions can implemen o enhance hei en i onmen al pe o -
mance (Eps ein & Roy, 1997). The ISO 14000 amily also encompasses
o he elemen s such as en i onmen al audi ing, eco-labeling, and li e
cycle assessmen . To cap u e his ela ionship e ec i ely, we in o-
duce a bina y dummy a iable ha equals 1 i a company ob ains he
ISO 14000 ce ifica ion in a gi en yea and 0 o he wise (Refini i
Eikon Da as eam, 2022). This a iable se es as ou ins umen al
a iable in he analysis.
Model specifica ion
Re e se causali y and endogenei y issues a e inhe en in mos
s udies conce ning CSR (Aouadi, 2016;Habib & Bhuiyan, 2017). Fo
ins ance, aking ou case as an example, companies ha demons a e
excellence in sus ainabili y may choose o in eg a e digi al echnol-
ogy in o hei s a egic p ocesses o enhance hei en i onmen al
compliance. Igno ing his e e se causali y could in e e e wi h he
ac ual e ec o digi al in eg a ion on fi m sus ainabili y.
In esponse o hese pe inen conce ns, we conduc a se ies o
diagnos ic es s, namely he Woold idge es o au oco ela ion, he
B eusch-Pagan/Cook-Weisbe g es o he e oskedas ici y, and he
Woold idge es o s ic exogenei y (Woold idge, 2010). The esul s
do no ejec he Woold idge s ic exogenei y es , confi ming ha
u u e alues o ou digi al in eg a ion and con ol a iables co ela e
wi h he cu en yea ’sfi m sus ainabili y (Win oki e al., 2012). This
finding p ecludes using he adi ional o dina y leas squa es and
fixed e ec s es ima ion models. Following subsequen s udies (see
Gi od and Whi ing on 2017,Kos e and Pels e 2017), we employ a
wo-s ep SGMM es ima ion de eloped by Rellano and Bond (1991),
ollowing he model in Win oki e al. (2012).
Addi ionally, we employ he IV-QRPD panel da a model wi h
Powell’s (2016) nonaddi i e fixed e ec s, which exhibi s g ea e
obus ness agains ou lie s. Specifically, his model es ima es quan-
ile-specific e ec s, desc ibing he influence o explana o y a iables
on he cen e and he ails o he condi ional dis ibu ion o ou -
comes. We use he ins umen al a iable in he case o endogenei y.
Using he IV-QRPD model, we can be e unde s and he impac o
digi al in eg a ion on en i onmen al sus ainabili y, conside ing di -
e ences be ween companies and iden i ying specific e ec s a di e -
en le els o sus ainabili y dis ibu ion. This gi es us a mo e comple e
and nuanced iew o he ela ionship be ween digi al in eg a ion and
co po a e en i onmen al sus ainabili y. The e o e, we adop he ol-
lowing equa ion:
Yi; ¼a0þa1Yi; 1þa2Digi al Technologyi; þX
7
n¼3
anXn;i;
þXIndus y dummies þXCoun y dummies
þXYea dummies þɛi;
In he abo e equa ion, Y(i, ) deno es one o he h ee sus ainabili y
indica o s o each fi m, such as he emission educ ion sco e, en i-
onmen al inno a ion sco e, o esou ce u iliza ion sco e, o e each
yea . X ep esen s a ec o o con ol a iables, and ei is he e o
e m. The iand e e o indi idual fi ms in he sample and he
espec i e pe iods. Hence, Y_ (i, -1) cap u es he empo al depen-
dence o sus ainabili y o fi m i. The inclusion o his e m in ou
model is c ucial o ob aining consis en es ima es, as i helps o
add ess issues such as omi ed a iable bias, e e se causali y, and
dynamic endogenei y, which a e significan sou ces o endogenei y
(Win oki e al., 2012).
Empi ical esul s
This sec ion p esen s and analyzes he desc ip i e and empi ical
esul s o he s udy.
Desc ip i e s a is ics and Pea son’s co ela ion ma ix esul s
Table 1 depic s he main desc ip i e s a is ics o he a iables in
ou s udy. The a e age alue o Digi al Technology o he 22 Eu opean
coun ies in he sample is 43.161 %. The a e age Emission Reduc ion
alue is 50.67 %, he a e age En i onmen al Inno a ions alue is 28.06
%, and he a e age E ficien Use Resou ces alue is 47.66 %.
Acco ding o Mukhe jee e al. (1998), da a is usually dis ibu ed i
he skewness alue is close o 0 and he ku osis alue is less han 3.
Table 1 shows ha none o ou a iables ha e skewness close o 0 o
ku osis abo e 3, sugges ing ha he da a is no symme ically dis-
ibu ed and ha he e a e ex eme alues. Addi ionally, he mean
significan ly di e s om he median in many cases, implying ha
ou da a dis ibu ion is abno mal. Fu he mo e, we ollow he
app oach o Razali and Wah (2011) o confi m ou findings using he
Shapi o−Wilk no mali y es .
As shown in Table 1, he assump ion o a no mal dis ibu ion o
he a iable mus be ejec ed. The e o e, ou a iables do no pe -
ec ly mee he assump ions o no mali y and he absence o ou lie s.
Be o e conduc ing mul i a ia e analyses, we examine he co ela-
ions be ween he independen a iables o ensu e no collinea i y
exis s. We use a bi a ia e co ela ion ma ix o es o he absence o
pe ec mul icollinea i y among he inpu a iables, as shown in
Table 2. Mul icollinea i y be ween wo a iables is “p oblema ic”
when he co ela ion coe ficien exceeds he c i ical alue o 0.8
(Guja a i & Po e , 2009). In ou case, he in e co ela ions be ween
he explana o y a iables ange om −0.1388 o 0.4900, below he
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
7
c i ical h eshold o 0.8. The e o e, he co ela ion ma ix indica es no
collinea i y among he explana o y a iables in ou model.
Fu he mo e, we employ he a iance infla ion ac o as a diag-
nos ic es o mul icollinea i y. As a ule o humb, Ma qua id
(1970) and Guja a i & Po e (2009) sugges ha a a iance infla ion
ac o g ea e han 10 indica es significan collinea i y. Acco ding o
Table 2, he e a e no issues wi h mul icollinea i y among he s udied
a iables.
Empi ical esul s o he wo-s age SGMM dynamic models and IV-QRPD
To analyze he ela ionship be ween digi al in eg a ion and co po-
a e sus ainabili y, including emissions educ ion, en i onmen al
inno a ion, and esou ce e ficiency, we employ a dynamic panel
model known as he wo-s age SGMM, ollowing he app oach in
A ellano and Bond (1991). This econome ic es ima ion me hod can
cap u e a ia ions among companies and o e ime while add essing
he endogenei y bias o he explana o y a iables. The endogenei y
bias a ises om digi al in eg a ion and specific company cha ac e is-
ics ha simul aneously influence sus ainabili y. By u ilizing he wo-
s age SGMM model, we mi iga e his bias and enhance he obus ness
o ou findings. Tables 3−5display he pa ame e es ima es and co -
esponding P- alues de i ed om he wo-s age SGMM model.
In he con ex o eg ession using he GMM me hod, we apply he
Hansen es o iden i y ins umen s and de e mine he alidi y o he
specified ins umen s, ollowing Roodman (2007). Addi ionally, we
employ he A ellano & Bond (1991) es o iden i y fi s - and second-
o de au oco ela ion (A ellano & Bo e , 1995;Blundell & Bond,
1998).
The P- alues om he Hansen es o he wo-s ep GMM model
a e 1.000 (Table 3), 0.881 (Table 4), and 0.998 (Table 5), indica ing
excellen quali y and alidi y o he ins umen al a iables in ou
es ima ions.
Consequen ly, he absence o second-o de se ial co ela ion in
he e o e m, as indica ed by he AR(2) alues, confi ms he alidi y
o he GMM model es ima ion o he h ee analyzed models (Rood-
man, 2009). The lagged dependen a iables also exhibi posi i e
coe ficien s wi h high significance ac oss all specifica ions,
demons a ing he dynamic na u e o he model’s specifica ion
(Dahe e al., 2015).
We obse e a significan co ela ion (a he 1 % le el) among he
pas alues o Emissions Reduc ion (Table 3), En i onmen al Inno a ion
(Table 4), Resou ce E ficiency (Table 5), and hei cu en alues o
he company. This esul is consis en wi h p io li e a u e, sugges -
ing ha cu en manage ial decisions and p ac ices a e s ongly influ-
enced by he company’s pas pe o mance le els (Ga cia-Cas o e al.,
2010). The e o e, pas sus ainabili y sco es (Y -1), such as emissions
educ ion, en i onmen al inno a ion, and esou ce e ficiency, play a
c ucial ole in cap u ing he dynamic ac o s ha a ec i .
On he o he hand, he esul s in Table 3 demons a e a a o able
and s a is ically significan associa ion a he 1 % le el o significance
o he digi al in eg a ion−emissions educ ion ela ionship, confi m-
ing hypo hesis 1. This sugges s ha digi al in eg a ion posi i ely
a ec s e o s o educe emissions. This posi i e co ela ion be ween
digi al in eg a ion and emissions educ ion sugges s ha adop ing
digi al echnologies helps companies implemen mo e en i onmen-
ally iendly p ac ices. By le e aging digi al solu ions, businesses can
op imize hei p ocesses, educe was e, and imp o e ene gy e fi-
ciency, esul ing in lowe emissions and a posi i e en i onmen al
impac .
Fu he mo e, o es hypo hesis 2, Table 4 e eals a significan and
a o able linkage, significan a he 1 % le el, be ween Digi al In eg a-
ion and En i onmen al Inno a ion. This sugges s ha digi al in eg a-
ion p omo es en i onmen al inno a ion, which in u n sugges s ha
companies adop ing digi al echnologies a e mo e likely o de elop
and implemen inno a i e and sus ainable p ac ices. Digi al ools can
acili a e esea ch, de elopmen , and implemen a ion o en i on-
men ally iendly echnologies and p ocesses, p omo ing con inuous
imp o emen in en i onmen al pe o mance.
Simila ly, he esul s in Table 5 show a a o able and s a is ically
significan ela ionship be ween Digi al In eg a ion and Resou ce E fi-
ciency, as an icipa ed in hypo hesis 3. The e o e, we accep hypo he-
sis 3, which p oposes ha digi al in eg a ion inc eases esou ce
e ficiency. By le e aging da a analy ics, a ificial in elligence, and
au oma ion, companies can op imize esou ce alloca ion, educe con-
sump ion, and minimize was e gene a ion, hus imp o ing o e all
esou ce e ficiency.
Table 1
. Desc ip i e s a is ics.
N Mean SD Min Q25 Median Q75 Max Skewness Ku osis S−W es
Digi al Technology 10423 43.1611 10.2469 21 35.3 40.5 54.2 83.3 0.47764 6.767 14.959***
Emission Reduc ion 10423 50.6710 31.1737 0 26 52.58 77.39 98.74 -0.1764 3.8611 14.174***
En i onmen al Inno a ions 10423 28.0676 31.7524 0 8.76 17.15 51.25 64.67 0.7175 2.1600 13.536***
E ficien Use Resou ces 10423 47.6661 32.6090 0 18.53 48.16 77.06 91.4633 -0.0268 7.7058 14.504***
Fi m Size 10423 6.2912 0.9290 0.9542 5.6722 6.2411 6.8722 9.8603 -.0388 4.9681 12.422***
ROA 10423 9.1892 7.7611 -1.96 2.95 10.66 18.14 26.0 17.3077 1196.107 22.635***
Ma ke -To-Book 10423 3.2110 2.9531 -1.32 1.08 1.99 3.69 8.99 -78.889 7403.712 22.842***
Boa d Size 10423 8.9726 3.7716 2 6 8 11 18 1.6052 11.4043 16.257***
Boa d Independence 10423 29.0287 14.5991 0 20 30 40 46.71 -0.1495 3.8601 10.269***
No e: S-W: Shapi o-Wilk es wi h Z-s a is ics. *** indica es significance a he 1 % le el.
Table 2
Co ela ion among all a iables (Pea son coe ficien s).
1 23456VIF
Digi al Technology 11 1.03
Fi m Size 2 -0.0043 1 1.37
ROA 3 -0.0051 0.0065 1 1.00
Ma ke -To-Book 4 0.0029 -0.0230** 0.0341*** 1 1.00
Boa d Size 5 -0.1388*** 0.4900*** 0.0041 -0.0128 1 1.36
Boa d Independence 6 0.0592*** 0.2559*** 0.0080 0.0050 0.1876*** 1 1.08
No e: ** and *** indica e significan ela ionships a he 5 % and 1 % le els.
M.A. Qu ainah and I. Ayadi Jou nal o Inno a ion & Knowledge 9 (2024) 100525
8
