Dzhunushalie a, Gulna a; Teube , Ramona
A icle
Roles o inno a ion in achie ing he Sus ainable
De elopmen Goals: A bibliome ic analysis
Jou nal o Inno a ion & Knowledge (JIK)
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: Dzhunushalie a, Gulna a; Teube , Ramona (2024) : Roles o inno a ion in
achie ing he Sus ainable De elopmen Goals: A bibliome ic analysis, Jou nal o Inno a ion &
Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 9, Iss. 2, pp. 1-13,
h ps://doi.o g/10.1016/j.jik.2024.100472
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Roles o inno a ion in achie ing he Sus ainable De elopmen Goals: A
bibliome ic analysis
Gulna a Dzhunushalie a
a,
*, Ramona Teube
b,1
a
The Ins i u e o Public Policy and Adminis a ion, Uni e si y o Cen al Asia, 720060 Bishkek, he Ky gyz Republic
b
Facul y o Ag icul u al Sciences, Nu i ional Sciences and En i onmen al Managemen , Ins i u e o Ag icul u al Policy and Ma ke Resea ch, Jus us Liebig Uni e -
si y, Giessen, Ge many
ARTICLE INFO
A icle His o y:
Recei ed 9 July 2023
Accep ed 8 Ma ch 2024
A ailable online 21 Ma ch 2024
ABSTRACT
As we app oach he midpoin o he Agenda 2030 p og amme, scien is s a e inc easingly elian on inno a-
i e solu ions o help b ing us close o achie ing he Sus ainable De elopmen Goals (SDGs). This s udy aims
o analyse he in ellec ual s uc u e o academic li e a u e on he SDGs, Inno a ion, and Science, Technology
and Inno a ion (STI).
Using a da abase o 544 English-language publica ions om Scopus and Web o Science published be ween
2015 and 2023, we employ a h ee-p onged app oach comp ising bibliome ic analyses, SDG mapping and
ex -mining echniques. Ou findings indica e ha inno a ions in one clus e defined in he analysis display
economic, social and en i onmen al dimensions. Fu he mo e, he unde lying oles o inno a ion in he li e -
a u e a e ound o ela e o p omo ing sus ainable de elopmen , d i ing economic g ow h, enhancing en e -
p ise pe o mance and s eng hening policies. Wi hin he sample li e a u e, all 17 goals we e iden ified by
he SDG Mappe . Among he 5Ps (People, Plane , P ospe i y, Peace and Pa ne ships), he e was a clea p e-
ponde ance o a icles on P ospe i y. The ex mining o i les and abs ac s indica es ha he e m “s i”is
less commonly associa ed wi h he SGDs han “inno a ion”. Howe e , he e is some e idence ha he e m
“inno a ion”is used in i les and abs ac s o a ac a b oade audience. Ou s udy highligh s esea ch gaps
and iden ifies oppo uni ies o u u e s udies.
© 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:
Inno a ion
SDGs
STI
Bibliome ic analysis
Sys ema ic li e a u e e iew
VOS iewe
JEL Classifica ion:
O3
In oduc ion
Inno a ion has eme ged as a c i ical d i e o sus ainable de elop-
men , wi h he Uni ed Na ions Sus ainable De elopmen Goals
(SDGs) p o iding a comp ehensi e amewo k o add ess he a ious
dimensions (People, Plane , P ospe i y, Pa ne ship and Peace) o
global challenges. As we a e al eady a he midpoin o he Agenda
2030 p og amme, wi h he global communi y s i ing o accele a e
p og ess owa ds achie ing he SDGs, an unde s anding o he ole o
inno a ion has become o pa amoun impo ance. P og ess owa ds
some SDGs lags se iously behind, especially in low-income coun ies,
whe e he e ec s o he COVID-19 pandemic and subsequen c ises
ha e been pa icula ly se e e. Despi e hese challenges, he SDGs a e
s ill achie able, and none o hei a ge s a e una ainable (Sachs e
al., 2023).
Gi en he uni e sal and in e connec ed na u e o he SDGs, any
inno a ions di ec ed owa ds hei a ainmen mus mee mul iple
equi emen s. Ou s udy aims o explo e his c ucial aspec o he
ela ionship be ween inno a ion and he SDGs. Scho and S einmuel-
le (2018) ha e a gued ha he complex na u e o SDGs equi es
ans o ma ional solu ions ha go beyond inno a ion alone; he e-
o e, i would seem ha a combina ion o Science, Technology and
Inno a ion (STI) is wa an ed.
STI is becoming inc easingly ele an in a emp s o achie e he
SDGs (Walsh e al., 2020), p ima ily due o he apid pace o echno-
logical p og ess (Managi e al., 2021) and dis up i e echnologies
such as a ificial in elligence (AI) (Di Vaio e al., 2020). Inno a ions
can subs an ially impac he cos s associa ed wi h making p og ess,
o e ing oppo uni ies o de elop new solu ions, app oaches and
en i onmen al ac ions ha can con ibu e o sus ainable de elop-
men (Ma ini Go igli e al., 2022). Thus, inno a ion and pa ne ship
play a c ucial ole in ackling he complex and in e connec ed chal-
lenges o sus ainable de elopmen (Oli ei a-Dua e e al., 2021).
O e all, wo s eams o li e a u e a e highly ele an o ou
esea ch: s udies explo ing he ole o inno a ion in achie ing he
* Co esponding au ho .
E-mail add ess: gulna a.djunushalie a@ucen alasia.o g (G. Dzhunushalie a).
1
Cen e o In e na ional De elopmen and En i onmen al Resea ch, D-35392 Gies-
sen, Ge many.
h ps://doi.o g/10.1016/j.jik.2024.100472
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) 100472
Jou nal o Inno a ion
&Knowledge
h ps://www.jou nals.else ie .com/jou nal-o -inno a ion-and-knowledge
SDGs, and exis ing li e a u e e iews and bibliome ic analyses o he
ela ionship be ween inno a ion and he SDGs.
S udies wi hin he fi s s eam o li e a u e ha e ocused on he
a ious aspec s o en i onmen al sus ainabili y. Khan e al. (2022)
obse e ha g een inno a ion mode a es he co ela ion be ween a
company’sfinancial pe o mance and i s p og ess owa ds en i on-
men al and social SDGs. Meanwhile, Ullah e al. (2021) emphasise he
need o go e nmen suppo o small and medium-sized en e -
p ises in adop ing g een inno a ion. Wei e al. (2023) and Zhou e al.
(2020) explo e he p omo ion o g een inno a ion in sus ainable sup-
ply chains, while Wang e al. (2022) highligh he ole o g een
knowledge managemen in s eng hening o ganisa ions.
Ci cula Economy (CE) p ac ices ha e also been discussed in ela-
ion o he SDGs. Sch oede e al. (2019) highligh he di ec con ibu-
ions o CE p ac ices o SDGs 6−8, 12 and 15, while Dan as e al.
(2021) sugges ha combining CE wi h Indus y 4.0 echnologies
could enhance hese con ibu ions.
The li e a u e also examines he ole o en i onmen al policies
(Wang e al., 2022), ene gy inno a ion (Baloch e al., 2022) and ech-
nological inno a ion (Anwa e al., 2022) in educing emissions and
p omo ing ca bon mi iga ion. STI can lead o lowe le els o pollu-
ion, inc eased p oduc i i y and compe i i eness, and he sus ainable
use o na u al esou ces (Ma ínez & Po eda, 2021).
A he o ganisa ional le el, s udies ha e conside ed he ole o
publicly unded incuba o s o STI-based s a ups (Su ana e al.,
2020), communi y-led ini ia i es (Hen ey e al., 2023), and mul i-
s akeholde pa ne ships o med h ough collabo a i e inno a ions
(Ma iani e al., 2022) o c ea e an enabling en i onmen o sus ain-
able de elopmen . Calab ese e al. (2021) emphasise he media ing
ole o se ice and ugal inno a ions in fi ms’con ibu ions o he
SDGs. D illing down o he communi y le el, Imaz and Eizagi e
(2020) discuss how fi ms in a social solida i y economy can con ib-
u e o he sus ainable de elopmen agenda h ough esponsible
inno a ion. Meanwhile, Ala con Fe a i e al. (2021) and Noguei a e
al. (2022) highligh he ole o inno a ions such as ci izen science,
social s a egies and in en ionally sus ainable communi ies in
add essing he SDGs, pa icula ly in u al se ings.
The second s eam o li e a u e includes e iews and bibliome ic
analyses ha explo e he ela ionship be ween he SDGs and he
business sec o (Azma e al., 2023;Pizzi e al., 2020), AI echnology
(Di Vaio e al., 2020), echnological inno a ions (Tha o n e al., 2021),
inno a i e aspec s o he wa e −ene gy− ood nexus (Co ea-Po cel
e al., 2021), eco-inno a ion (Fa ma & Haleem, 2023;Pe eg ina e al.,
2023), social inno a ion (Eichle & Schwa z, 2019;Meye , 2022),
heal h and well-being (Sweileh, 2020), educa ion (P ie o-Jim
enez e
al., 2021), esponsible inno a ion (Di Vaio e al., 2022) and ugal
inno a ion (Albe , 2022).
Building on hese p io wo ks, ou s udy di e s, howe e , om
exis ing esea ch in wo ways. Fi s , he s udies ci ed abo e ocus p i-
ma ily on he con ibu ions made by specific inno a ions o achie ing
he SDGs. Howe e , i is also impo an o unde s and which inno a-
ions domina e he exis ing li e a u e. Hence, we adop a holis ic
app oach ha conside s inno a ion mo e b oadly, and gain a mo e
comp ehensi e pe spec i e by s udying inno a ion and STI in ela-
ion o he SDGs. To achie e his, we add ess he ollowing esea ch
ques ions (RQs):
RQ1: Wha is he in ellec ual s uc u e o he field o s udy?
RQ2: Which SDGs can be ound in he li e a u e on inno a ion, STI
and SDGs?
RQ3: How is he ole o inno a ion in ela ion o he SDGs p e-
sen ed in he exis ing li e a u e?
The second way in which ou s udy is dis inc om exis ing
esea ch can be seen in ou me hodological app oach, which com-
bines he use o h ee sepa a e echniques o add ess he RQs. Mo e
specifically, we use co-occu ence analysis o iden i y c i ical hemes
and gene a e a isualisa ion o he in ellec ual s uc u e using VOS-
iewe , in esponse o RQ1. Fo RQ2, we use he SDG Mappe ool o
iden i y ele an SDG goals and a ge s wi hin he i les, abs ac s
and keywo ds. Finally, we add ess RQ3 by defining he ole o inno a-
ion in he ques o achie e he SDGs using a ex -mining echnique.
Ou s udy con ibu es o he li e a u e in se e al ways. Fi s , we
p o ide an o e iew o cu en knowledge and new insigh s in o he
in ellec ual s uc u e o he ela ionship be ween inno a ion, STI and
SDGs. Second, ou esea ch acks and emphasises he links be ween
inno a ion and specific SDGs. Thi d, while ce ain p io bibliome ic
s udies ela e o he SDGs (Meschede, 2020;P ie o-Jim
enez e al.,
2021;Sweileh, 2020), none ha e used mapping o ex -mining ech-
niques; ou s udy demons a es he use ulness o hese echniques in
add essing his opic. Finally, by adop ing he 5Ps (People, Plane ,
P ospe i y, Peace and Pa ne ships) amewo k, he p esen s udy
aims o o e an unde s anding o he SDGs beyond he adi ional
h ee-pilla app oach.
Scope and bounda y o he e iew
Inno a ion and STI
The concep o inno a ion has been defined in a ious ways,
encompassing en i onmen al (Ullah e al., 2021), social (Ma ini Go i-
gli e al., 2022), echnological and ins i u ional inno a ions (Anwa e
al., 2022;Liu e al., 2022). While using a b oad defini ion o inno a-
ion can pose challenges in measu ing and moni o ing, i allows a
comp ehensi e unde s anding o he concep , which is pa icula ly
aluable o in e disciplina y s udies.
Se e al ypes o inno a ion ha e ecen ly eme ged as p omising
d i e s o achie ing he SDGs, including collabo a i e inno a ions
(Ma iani e al., 2022), eco- iendly inno a ions (Miao e al., 2023), co-
inno a ion (Adomako & Nguyen, 2022;Fielke e al., 2018) and
esponsible inno a ion (Imaz & Eizagi e, 2020;Ranabahu, 2020).
The COVID-19 pandemic has inc eased inno a ion in, o example,
he biopha maceu ical sec o , con ibu ing o sus ainabili y (Pi~
nei o-
Chousa e al., 2022). The concep o “inno abili y”has been p oposed
by De la Vega and De Paula (2020) as a s a egic app oach o compa-
nies seeking o achie e bo h compe i i eness and sus ainabili y.
To achie e sus ainabili y, significan changes a e needed in he
public’s hinking, beha iou , p oduc ion and consump ion. Scien ific
expe ise alone is no su ficien o de elop and implemen e ec i e
solu ions: in ellec ual capi al is also needed, including access o in o -
ma ion, knowledge and expe ience (Fa aji e al., 2022). Open inno a-
ion p inciples (Chau asia e al., 2020), social inno a ion and
dis up i e echnologies (Ciampi e al., 2020) ha e all helped o accel-
e a e he sha ing o knowledge.
STI dis inguishes i sel om inno a ion in i s inclusion o he
e ms “science”and “ echnology”, hus posi ioning i sel as he d i -
ing o ce behind p og ess: science can ad ance knowledge by
imp o ing ou unde s anding h ough obse a ion, expe imen a ion,
and esea ch and de elopmen (R&D), leading o he c ea ion o ech-
niques and echnologies ha o e public benefi . Technology is he
p ac ical applica ion o scien ific knowledge o c ea e p oduc s and
se ices. While inno a ion can esul me ely om hinking “ou side
o he box”, echnological p og ess can only be achie ed h ough sci-
en ific disco e y and esea ch which in en and de elop echnology
(ESCAP, 2015). Technology links science wi h inno a ion.
The echnology gap is one o he p ima y causes o pe sis en
inequali y be ween na ions (Naud
e & Nagle , 2015), and he key di -
e ence be ween de eloped and de eloping coun ies lies in knowl-
edge le els. Elimina ing he knowledge gap, as sugges ed by Ozkaya
e al. (2021), can close bo h de elopmen and income gaps. To
add ess his issue, he Addis Ababa Ac ion Agenda acknowledges he
ole o STI in achie ing he SDGs and p o ides unding o suppo
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
2
p og ess o his end (Uni ed Na ions, 2015). Fu he mo e, he Tech-
nology Facili a ion Mechanism (TFM) and he engagemen o Uni ed
Na ions en i ies and o he s akeholde s acili a e he exchange o
in o ma ion, bes p ac ice, expe ience and policy ad ice (Uni ed
Na ions, 2020).
The 5Ps o Sus ainable De elopmen Goals
Rega ding he amewo ks used o unde s and he SDGs, p e ious
s udies ha e adi ionally ocused on h ee p incipal pilla s: social
inclusion, economic g ow h and en i onmen al p o ec ion. Howe e ,
ecen global challenges −such as he COVID-19 pandemic, mili a y
conflic s and ene gy and clima e shocks −ha e led o a b oade
unde s anding o sus ainable de elopmen . The 2030 Agenda in o-
duced wo addi ional componen s, Pa ne ship and Peace, (Dumpe &
Gue a a, 2020), hus expanding he amewo k o include fi e essen-
ial dimensions: People (SDGs 1−5), P ospe i y (SDGs 7−11), Plane
(SDG 6, SDGs 12−15), Peace (SDG 16), and Pa ne ship (SDG 17),
known as he 5Ps o he Sus ainable De elopmen Goals (Ki-moon,
2019).
To acili a e he moni o ing o p og ess owa ds he SDGs, an
inno a i e app oach was adop ed which esul ed in a se o indica-
o s o global go e nance. The In e -Agency and Expe G oup, in
collabo a ion wi h he S a is ical Commission, de eloped he Global
Indica o F amewo k (GIF) o he SDGs. The GIF comp ises 231
unique indica o s, some epea ed ac oss mul iple SDG a ge s (Uni ed
Na ions, 2022). This app oach o e s flexibili y and adap abili y as
me hodologies and da a sou ces e ol e and expand be ween 2015
and 2030, p o iding a obus basis o moni o ing p og ess owa ds
he SDGs.
Inno a ion- ela ed keywo ds in he SDGs
The SDGs do no explici ly define he ole ha inno a ion may
play in achie ing hem. Howe e , he specific ypes o inno a ion
ha may d i e he achie emen o each SDG a e no s a ed oo. To
be e unde s and he ela ionship be ween inno a ion, STI and he
SDGs, we conduc ed a de ailed analysis o he 17 SDG goals and he
169 a ge s ha unde pin hem, as ou lined in he GIF. To his end,
we iden ified he e ms linked o inno a ion and STI in he GIF, fi s
c ea ing a lis o all he e ms we encoun e ed and labelling hem as
inno a ion- ela ed keywo ds. We we e hen able o g oup hese key-
wo ds in o fi e b oad ca ego ies: knowledge, science, echnology,
inno a ion and in o ma ion and communica ion echnology (ICT).
Finally, we dis ibu ed he a ge s ha included he keywo ds in o
hese ca ego ies, which we hen aligned wi h he 5Ps, as shown in
Table 1, which is o med o fi e columns ep esen ing he fi e ca ego-
ies (Knowledge, Science, Technology, Inno a ion and ICT) and fi e
ows ep esen ing he 5Ps (People, P ospe i y, Plane , Pa ne ship
and Peace). We hus iden ified he a ge s o e ms ha we expec ed
o find in he sample da abase. F om his basis, i was hen possible
o compa e he expec ed and ac ual occu ences o inno a ion-
ela ed keywo ds in he li e a u e by examining he e ms, and he
equency wi h which hey appea ed, using he SDG mapping ool.
We iden ified 31 (ou o 169) a ge s ha men ioned a leas one
inno a ion- ela ed e m. The e m “inno a ion”was i sel men ioned
in SDG 9 and a ge s 8.2, 8.3, 9.5 and 9.b. The e m “STI”was obse ed
in SDGs 17.6 and 17.8, and he e ms “ esea ch”and “science”we e
epea edly men ioned, wi h 14 and 9 occu ences espec i ely. How-
e e , he mos equen ly used e m was “ echnology”(including
ICT), which appea ed 33 imes. Technology was ound o be ele an
ac oss ou dimensions (People, P ospe i y, Plane and Pa ne ship).
Howe e , i is impo an o no e ha echnology alone canno
achie e sus ainable de elopmen , due o he possibili y o ebound
e ec s (Gio annini & Rou e, 2017). The Uni ed Na ions ecognises
he c ucial ole played by echnology bu , a he same ime, highligh s
he need o i o be in eg a ed wi h science and inno a ion o
achie e he SDGs (Sachs e al., 2022).
Me hods and ma e ials
Bibliome ic analyses a e commonly employed in sus ainabili y-
ela ed e iews due o hei comp ehensi e and sys ema ic app oach
(Azma e al., 2023;Co
es e al., 2021;Meye , 2022). In ou me hod-
ology, we combined he P e e ed Repo ing I ems o Sys ema ic
Re iews and Me a-Analyses (PRISMA) guidelines (Page e al., 2021)
wi h he flow plan p oposed by Zupic and
Ca e (2015). Ou flow
plan comp ised fi e main s ages: (1) esea ch design, (2) compila ion
o bibliome ic da a (in eg a ing he PRISMA 2020 flow diag am), (3)
analysis, (4) isualisa ion and (5) in e p e a ion.
To co e he ele an li e a u e comp ehensi ely, we conduc ed a
sea ch using he ISI Web o Science (WOS) and Scopus da abases
Table 1
Dis ibu ion o inno a ion- ela ed SDG goals and a ge s by 5Ps.
Knowledge Science Technology Inno a ion ICT
People
SDG 2.3 SDG 1.4 SDG 4.4
SDG 2.a ag icul u al esea ch, echnology SDG 4.b
SDG 3.b medical esea ch SDG 6.a ecycling, euse echnology SDG 5.b
P ospe i y
SDG 7.1 SDG 7.b SDG 9 SDG 8.10
SDG 7.a clean ene gy esea ch echnology SDG 8.2 SDG 9.c
SDG 9.2 SDG 9.4 SDG 9.a SDG 8.3
SDG 9.5/9.b scien ific esea ch, echnology, inno a ion
Plane
SDG 12.a scien ific and echnological capaci y
SDG 14.3 SDG 12.5
SDG 14.4
SDG 14.a scien ific knowledge, esea ch, echnology
Pa ne ship
SDG 17.7
SDG 17.6 STI and enhance knowledge-sha ing h ough a global echnology acili a ion mechanism
SDG 17.8 echnology bank and science, echnology and inno a ion capaci y-building mechanism, ICT
SDG 17.16 sha e knowledge, expe ise, echnology
Peace
SDG 16.10
Sou ce: P epa ed by he au ho s based on sc eening o he Global Indica o F amewo k
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
3
(A a inda aj & Chinna, 2022;Fa ma & Haleem, 2023;Id ees e al.,
2023).
Inclusion and exclusion c i e ia
To ensu e he ep oducibili y o ou esul s, we es ablished p ecise
inclusion and exclusion c i e ia and pe o med a comp ehensi e
sea ch o keywo ds, i les and abs ac s ac oss bo h da abases. Ou
p elimina y e iew e ealed ha au ho s equen ly men ion he
SDGs and inno a ion in hei abs ac s o appeal o a wide audience.
To na ow ou sea ch, we ocused pa icula ly on a icle i les, as ou
p elimina y e iew showed ha au ho s gene ally include he e m
“inno a ion*”in hei i le i inno a ion is a co e aspec o hei s udy.
We fi s used he sea ch que y: i le, abs ac , keywo ds = (“sdg*”OR
“sus ainable de elopmen goal*”) AND i le = “inno a ion*”. This
que y iden ified 1374 eco ds (Scopus n= 826; WOS n= 548) (Fig. 1).
We hen conduc ed a second que y: i le, abs ac , keywo ds = “sdg*”
OR “sus ainable de elopmen goal*”AND “science, echnology, and
inno a ion”, which yielded 91 eco ds (Scopus n= 60; WOS n= 31).
O e all, ou ini ial sea ch gene a ed 1465 esul s.
We applied he ollowing fil e s: (a) Documen ype: A icles, (b)
Language: English, (c) Publica ion yea s: 2015−2023, and cleaned he
da a o emo e duplica e en ies and add ess any missed keywo ds,
i les o abs ac s. Following hese p ocedu es, 571 ele an eco ds
emained.
We applied u he exclusion c i e ia −(a) SLRs and (b) bibliome -
ic analyses − o na ow he selec ion du ing he sc eening p ocess.
Following a con en analysis o i les and abs ac s, 15 SLRs and 12
bibliome ic analyses we e excluded, esul ing in a o al o 544 s ud-
ies emaining o u he analysis (Fig. 1). F om his sample, i can be
seen ha he numbe o publica ions has g own exponen ially o e
he pe iod in ques ion, om only wo in 2015 o 185 as o 11 No em-
be 2023.
Bibliome ic analysis and isualisa ions
The analysis in his s udy was pe o med using VOS iewe so -
wa e e sion 1.6.19, a ool designed o c ea e and isualise co-occu -
ence ne wo ks. We u ilised wo ypes o isualisa ion: ne wo k
isualisa ion and clus e densi y isualisa ion; bo h used only he
keywo ds o each a icle in ou sample − hose chosen by he
au ho s and hose gene a ed au oma ically by he Keywo d Tool.
In he ne wo k isualisa ion, keywo ds a e depic ed as labels
accompanied by ci cles, whe e he size o he ci cle co esponds o
he weigh o he keywo d. The weigh o a keywo d eflec s i s
impo ance and is calcula ed h ough a ious me ics, including link
weigh , o al link s eng h weigh and occu ence weigh . The sco e
a ibu e indica es any nume ical p ope ies o a keywo d (e.g. a e -
age publica ion yea sco e o a e age ci a ion sco e). The VOS iewe
echnique g oups closely linked keywo ds in o indi idual clus e s
Fig. 1. PRISMA flow diag am and me hods.Sou ces: Figu e c ea ed by he au ho s
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
4
which a e colou -coded. The colou o a ci cle is hus de e mined by
he clus e o which i belongs, and links be ween ci cles a e ep e-
sen ed as lines ( an Eck & Wal man, 2023).
Clus e densi y isualisa ion, in con as , ocuses on he occu -
ence and popula i y o keywo ds. Simila ly o ne wo k isualisa ion,
keywo ds a e ep esen ed as poin s, and he sa u a ion o he poin ’s
colou is de e mined by he numbe o keywo ds in i s neighbou -
hood and he weigh o he neighbou ing keywo ds.
Bo h isualisa ions o e a comp ehensi e and isually appealing
ep esen a ion o ne wo ks and clus e s, enabling a deepe unde -
s anding o he ela ionships be ween he e ms wi hin he sample
da abase and hei ela i e densi ies ( an Eck & Wal man, 2023).
SDG mapping
To answe RQ2, we u ilised a web pla o m called “Knowledge
Base o he Sus ainable De elopmen Goals”, which includes he
SDG Mappe ool. This pla o m se es as a knowledge hub o EU
policies, indica o s, and da a ela ed o he SDGs. The SDG Mappe
uses na u al language p ocessing (NLP) echniques o de ec he
SDGs men ioned in he uploaded bibliome ic eco ds (Eu opean
Commission, 2021). Once e e ences o he SDGs ha e been iden i-
fied, machine lea ning algo i hms a e hen applied o analyse he
da a in he sample da abase and es ablish connec ions be ween he
bibliome ic eco ds and he ele an SDGs. This p ocess u ilises ule-
based echniques o iden i y specific keywo ds o ph ases associa ed
wi h each SDG.
The esul s o he analysis a e p esen ed in a ious isualisa ions.
The ba cha s p o ide an o e iew o he SDGs iden ified and hei
ela i e impo ance in he ex , o e ing insigh s in o he equency
and p ominence o each SDG. The bubble cha s show he ele ance
o he SDG goals and a ge s wi hin he eco ds, illus a ing he dis i-
bu ion and in e connec edness o he SDGs. These isualisa ions
enable an unde s anding o he ep esen a ion and impo ance o di -
e en SDGs wi hin he analysed bibliome ic eco ds, and acili a e a
comp ehensi e mapping and analysis o SDG- ela ed knowledge.
Tex -mining echniques
The ex -mining ea u e o he VOS iewe acili a ed he gene a-
ion o a e m map ha elies on NLP algo i hms ( an Eck & Wal man,
2011). In con as o he ne wo k and clus e densi y isualisa ions,
he ex -mining echnique examines he i les and abs ac s o he
sample da abase. In he VOS iewe , a noun ph ase is defined as a
sequence o one o mo e consecu i e wo ds in which he las wo d is
a noun and any p eceding wo ds a e nouns o adjec i es. The wo-
dimensional map shows he placemen o e ms acco ding o hei
ela edness, wi h close p oximi y indica ing a s onge ela ionship.
This ool de e mines he ela edness o e ms based on hei co-
occu ence wi hin he eco ds.
Resul s
Wha is he in ellec ual s uc u e o he s udied field?
The clus e densi y isualisa ion
The co-occu ence analysis iden ified 2915 keywo ds wi hin he
sample da abase. We ocused on keywo ds ha occu ed a leas fi e
imes, in line wi h he de aul h eshold se in he VOS iewe . A he-
sau us file (n= 356 keywo ds) was p epa ed o me ge synonyms and
plu als and iden ified 220 keywo ds ha me he h eshold c i e ia.
Fig. 2 p o ides insigh s in o he densi y and in e connec edness o
he keywo ds wi hin he sample da abase, highligh ing he ela ion-
ships and pa e ns be ween hem.
In densi y isualisa ion, we ocus on colou sa u a ion and he dis-
ance be ween keywo ds. He e, he clus e s a e loca ed igh ly
a ound he main keywo ds due o he p ecision wi h which we
selec ed ou sample da abase. The keywo ds “sdgs”,“sus ainabili y”
and “sus ainable de elopmen ”a e ound in he ed clus e , while
“inno a ion”,“ echnology”and “g een inno a ion”a e in he blue
clus e . The keywo d “inno a ion”is closely ela ed o “sdgs”,“sus-
ainabili y”and “sus ainable de elopmen ”, as e idenced by he 76,
46 and 45 links espec i ely be ween hese wo ds. Fu he mo e, we
no iced ha keywo ds such as “sdgs”,“sus ainabili y”,“sus ainable
de elopmen ”,“inno a ion”,“impac ”,“co2 emissions”and “ echno-
logical inno a ion”exhibi high colou sa u a ion, indica ing hei
p ominence in e ms o he amoun o esea ch dedica ed o hem
wi hin he sample da abase. The keywo d “s i”is ound in he pu ple
clus e , which includes keywo ds such as “science”and “inno a ion
policy”.
As we migh expec , he e m “sdgs”had he highes occu ence
weigh −212 −among he keywo ds, indica ing ha i appea ed in
212 a icles wi hin he sample da abase. The weigh o he link a i-
bu e −signi ying he numbe o links he keywo d “sdgs”had wi h
o he keywo ds −was 211, indica ing ha i appea ed oge he wi h
di e en keywo ds in 211 a icles. The weigh o he o al link
s eng h a ibu e o “sdgs”, ep esen ing he cumula i e s eng h o
all he links his e m has wi h o he keywo ds, was 1153.
Since he fi s sea ch que y was based on he e m “inno a ion*”,
we iden ified wo ds con aining his e m. Among he 220 keywo ds
men ioned mo e han fi e imes, 18 ha included “inno a ion*”
we e iden ified, wi h a o al o 469 occu ences. The ed clus e dis-
plays a highe equency (n= 10) o inno a ion keywo ds. Table 2
summa ises he in o ma ion ga he ed on inno a ion keywo ds, hei
occu ences and hei weigh wi hin he clus e s.
The keywo d “inno a ion”belongs o he blue clus e , wi h an
occu ence weigh o 138, a link weigh o 187 and a o al link
s eng h o 806. The mos significan keywo ds by o al link s eng h
weigh included “ echnological inno a ion”,“g een inno a ion”and
“eco-inno a ion”. The wo mos ecen keywo ds a e “financial inno-
a ion”(a e age publica ion yea sco e o 2022.8) and “g een inno a-
ion”(2022.3). The h ee mos ci ed keywo ds a e “inno a ion
policy”(a e age ci a ion sco e o 41.91), “ ugal inno a ion”(34.38)
and “ echnological inno a ion”(33.83). Thus, 86 % o he a icles
we e ela ed o hese 18 keywo ds, which can be conside ed he
main hemes o ou s udy.
The ne wo k isualisa ion
The ne wo k isualisa ion c ea ed in he VOS iewe p o ided u -
he insigh s in o he clus e ing o keywo ds wi hin he sample da a-
base. The VOS iewe o med fi e clus e s in he ne wo k
isualisa ion (Fig. 3). The sizes o he clus e s a ied conside ably,
wi h a subs an ial di e ence be ween he la ges , ed clus e (n= 72)
and he smalles , pu ple clus e (n= 25).
The ed clus e emphasises h ee opics d i en by “sdgs”. Fi s ly,
social aspec s a e shaping he “ u u e” h ough “social inno a ion”
and “social en ep eneu ship”, co po a e social esponsibili y (“cs ”),
“ esponsible inno a ion”and “ esponsible esea ch and inno a ion”.
The second opic encompasses he adop ion o “eco-inno a ion”,
“open inno a ion”and “ci cula economy”p inciples. Finally, he
hi d opic in ol es economic aspec s such as “pe o mance”,“man-
agemen ”,“sys ems”,“indus y”and “indus y 4.0”,“fi m”,“business
model inno a ion”,“ ugal inno a ion”and “p oduc inno a ion”,
and he “adop ion”o “sma ”and “digi al” ools o c ea e new “pe -
spec i es”.
The g een clus e ep esen s wo c ucial a eas in which inno a-
ion plays a significan ole. The fi s encompasses “ echnological
inno a ion”, d i ing “economic-g ow h”. The second highligh s he
ela ionship be ween “ enewable ene gy”,“co2 emissions”, and “con-
sump ion”pa e ns and he in e connec ions be ween hese ac o s,
known as he “nexus”.
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
5
The blue clus e includes a gene al discussion o “inno a ion”and
“ echnology”, alongside ela ed e ms such as “ &d”and “ic ”as nec-
essa y p e equisi es o de elopmen . Ano he heme in his clus e
is conce ned wi h g een aspec s, such as he g een economy, g een
finance, g een g ow h, g een inno a ion and g een echnology, all o
which aim o p omo e g ea e en i onmen al awa eness.
The keywo ds in he yellow clus e cen e on wo main opics:
educa ion and heal h. The educa ion aspec emphasises he
inco po a ion o sus ainable de elopmen “p inciples”in o
“highe educa ion”“cu icula” h ough inno a i e “me hodolo-
gies”and “leade ship”app oaches. The heal h opic examines
“heal h policy”,“challenges”and po en ial imp o emen s, pa icu-
la ly in “A ica”.
The pu ple clus e ocuses on p omo ing “ ansi ions”using “s i”
o ackle “clima e change”and “ ood secu i y”and achie e a mo e
“ esilien ” u u e h ough “policy”.
Fig. 2. The clus e densi y isualisa ion o he sample da abase on inno a ions, STI and he SDGs.Sou ces: Figu e c ea ed by he au ho s using VOS iewe 1.6.19
Table 2
Lis o inno a ion- ela ed keywo ds in he co-occu ence analysis.
# label clus e weigh
<Links>
weigh
<To al link s eng h>
Weigh
<Occu ences>
sco e
<A g. pub. yea >
sco e
<A g. ci a ions>
1 inno a ion Blue 187 806 138 2021.5 15.34
2 echnological inno a ion G een 146 641 69 2022.3 33.83
3 g een inno a ion Blue 129 427 59 2022.3 20.17
4 social inno a ion Red 87 175 39 2021.3 9.13
5 eco-inno a ion Red 100 215 30 2021.5 22.27
6 inno a ion policy Pu ple 64 130 22 2021.2 41.91
7 open inno a ion Red 50 86 15 2021.3 12.87
8 s i Pu ple 30 43 14 2021.5 9.00
9 ugal inno a ion Red 42 69 13 2019.5 34.38
10 sus ainable inno a ion Red 47 62 12 2021.3 17.25
11 inno a ion sys em Red 50 88 10 2021.7 9.00
12 p oduc inno a ion Red 41 80 10 2021.1 28.9
13 i ( esponsible inno a ion) Red 37 54 9 2021 11.78
14 i ( esponsible esea ch and inno a ion) Red 30 44 7 2019.7 22.57
15 business model inno a ion Red 25 43 7 2021.4 12.14
16 en i onmen al inno a ion Blue 22 28 5 2021.2 15.8
17 financial inno a ion G een 39 46 5 2022.8 21.8
18 g ass oo inno a ion Pu ple 22 23 5 2021.8 10.8
Sou ce: Da a we e iden ified h ough he VOS iewe 1.6.19.
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
6
Which specific SDGs a e de ec ed in he exis ing li e a u e on inno a ion,
STI and SDGs?
A ex file was p epa ed o iden i y he ele an SDG goals and a -
ge s wi hin he sample da abase o 544 bibliome ic eco ds, includ-
ing i les, abs ac s and keywo ds. The SDG Mappe de ec ed 122
SDG a ge s (ou o 169) in he sample da abase.
Table 3 shows he 24 a ge s wi h inno a ion- ela ed keywo ds
ha we e iden ified by he SDG Mappe ool. When we compa ed
hese o ou o iginal lis o 31 a ge s ha we expec ed o find wi hin
he sample da abase, we ound 18 ma ches (ma ked in bold). An
examina ion o he sum o occu ences shows ha esea che s a e
mos in e es ed in SDG 8.2 (n= 514 occu ences), SDG 9.5 (n= 452),
and SDG 7.2 (n= 353).
The ele ance o goals and a ge s is ep esen ed by bubbles in
Fig. 4. The size o he bubble is de e mined by he pe cen age o co -
esponding keywo ds de ec ed ( he a io o he numbe o keywo ds
ela ing o a single goal o he o al numbe o keywo ds). The o al
numbe o de ec ed keywo ds was 3656. Thus, SDG 8 (decen wo k
and economic g ow h) is he mos isible, wi h 1107 occu ences, ol-
lowed in second and hi d places by SDG 9 (indus y, inno a ion and
in as uc u e) and SDG 7 (a o dable and clean ene gy), wi h 567
and 534 occu ences espec i ely.
SDG 8.2 (di e si y, inno a e and upg ade o economic p oduc i -
i y) is ep esen ed by he la ges bubble, wi h “ echnolog inno ” he
mos de ec ed keywo d, appea ing 494 imes in he sample da abase.
The second mos popula keywo d was “ enew ene gi”, wi h 282
occu ences, ollowed by “econom g ow h”, which appea ed
167 imes. The op en keywo ds also include “g een echnolog”
(n= 122 occu ences), “s i”(n= 60) and “ &d”(n= 59).
Fig. 5 shows he SDGs de ec ed and hei dis ibu ion ac oss he
5Ps. The consolida ion o he SDGs in o he 5Ps suppo s e o s o
gauge p og ess and unde sco es he ac ha he SDGs a e no a col-
lec ion o isola ed goals bu , a he , closely in e connec ed.
The esul s o he SDG Mappe show ha he P ospe i y dimen-
sion, which includes SDG 7 (14.6 %), SDG 8 (30.3 %), SDG 9 (15.5 %),
SDG 10 ( educed inequali ies) (3.1 %) and SDG 11 (sus ainable ci ies
and economies) (3.1 %), accoun s o app oxima ely 67 % o all iden i-
fied keywo ds. Thus, he majo i y o he publica ions in ou da abase
we e de o ed o economic aspec s. The nex mos equen ly occu -
ing SDGs a e hose pe aining o he Plane dimension, including he
en i onmen al aspec s o SDG 6 (clean wa e and sani a ion) (1.1 %),
SDG 12 ( esponsible consump ion and p oduc ion)(5.1 %), SDG 13
(clima e ac ion) (7.1 %), SDG 14 (li e below wa e ) (0.2 %) and SDG 15
(li e on land) (5.3 %) which collec i ely accoun o 18.8 % o occu -
ences. The People dimension (11.8 %) anks hi d, encompassing
SDG 1 (no po e y) (1.8 %), SDG 2 (ze o hunge ) (3.1 %), SDG 3 (good
heal h and well-being) (4.9 %), SDG 4 (quali y educa ion) (1.6 %) and
SDG 5 (gende equali y) (0.4 %), which oge he add ess equi y and
jus ice wi hin public and p i a e communi ies and na ional en i ies.
SDG 17 (pa ne ship o he goals), ep esen ing he Pa ne ship
dimension, is c ucial in os e ing inno a ion bu was penul ima e in
he lis o mos equen ly ci ed SDGs, wi h 1.9 %. The Peace dimen-
sion (SDG 16 −peace, jus ice and s ong ins i u ions) is men ioned in
he ewes publica ions, accoun ing o only 0.9 % o men ions.
Role o inno a ion in achie ing he SDGs
The ex -mining echnique iden ified concep s, ha is, he mos
equen ly appea ing noun ph ases in i les and abs ac s. Noun
Fig. 3. Ne wo k isualisa ion o he sample da abase on inno a ions, STI and he SDGs.Sou ces: Figu e c ea ed by he au ho s using VOS iewe 1.6.19
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
7
ph ases ha appea ed a leas en imes we e, in acco dance wi h he
de aul posi ion, conside ed o mee he h eshold o inclusion. O
he se o 13,163 noun ph ases, 439 me his h eshold. A c ucial me -
ic in ex mining is he ele ance sco e, which anks wo ds based on
hei impo ance in abs ac s and i les. As migh be expec ed, he
mos commonly occu ing keywo ds we e “sdgs”(n= 919 occu -
ences) and “inno a ion”(n= 892), bu hese we e excluded as hey
o med pa o he ini ial sea ch que y. Mo eo e , hese e ms had
ele ance sco es o 0.02 and 0.21 espec i ely and, as a gued by Van
Eck and Al man (2023), excluding e ms wi h low ele ance sco es −
which a e o en gene ic e ms and con ibu e minimal in o ma ion −
enhances he use ulness o a map. Wi h hese wo e ms hidden, he
mapping was hen esco ed, esul ing in 437 equen ly occu ing
noun ph ases which we e selec ed o display on he map.
The VOS iewe ex -mining ne wo k o med fi e clus e s o a y-
ing sizes. The mos p ominen was a ed clus e con aining 200 i ems,
while he smalles was a pu ple clus e wi h only 10 i ems.
Fig. 6 p esen s a ne wo k o dis inc clus e s o in e connec ed
concep s p ecisely iden ified h ough co-occu ence equencies.
Each clus e , depic ed in a di e en colou , showcases a di e en
dimension o he ole o inno a ion as discussed in he li e a u e. We
labelled he ed clus e “P omo ing Sus ainable De elopmen ”:i
in ol es add essing issues in a way ha suppo s he plane , benefi s
socie y and ensu es long- e m economic iabili y. This clus e high-
ligh s he in e play be ween go e nmen , uni e si ies and indus y.
The inno a ion- ela ed keywo ds in his clus e a e simila o hose
in he ne wo k map (Table 2).
The g een clus e , “D i ing Economic G ow h”, in es iga es
“impac ”on “economic g ow h”and he use o “ enewable ene gy”
and “ echnological inno a ion” o achie e en i onmen al sus ainabil-
i y by educing “CO2 emissions”. This clus e emphasises le e aging
“g een inno a ion”,“eco-inno a ion”and “en i onmen al inno a-
ion” o d i e economic g ow h while educing en i onmen al
impac and add essing clima e change. When suppo ed by financial
inno a ion, aspec s such as “ enewable ene gy”and “ene gy inno a-
ion”play a significan ole in ensu ing long- e m sus ainabili y.
The blue clus e , “S eng hening policy”, is conce ned wi h poli-
cies and ini ia i es ha p omo e inno a ion and sus ainabili y wi hin
specific geog aphic egions. The clus e also includes “me hodology”,
“index”and “assessmen ”, which e e o he de elopmen and adop-
ion o he Agenda 2030 p og amme. The yellow clus e , “Enhancing
en e p ise pe o mance”, ocuses on sys ema ically examining da a
and e idence and u ilising “models”and “ heo ies” o unde s and
“indus y”and “fi m pe o mance”, while he pu ple clus e b ings
oge he a ious keywo ds ha we e no g ouped wi h o he clus-
e s.
Discussion
Ou esea ch has adop ed a comp ehensi e app oach o unde -
s anding he ole o inno a ion and STI in achie ing he SDGs. I p o-
ides a de ailed and nuanced unde s anding o he in ellec ual
s uc u e by ollowing a h ee-p onged app oach, using he SDG
Mappe , bibliome ic analyses and ex mining.
The co-occu ence analysis iden ified fi e clus e s, he la ges o
which ( he ed clus e ) is o ien ed a ound sus ainable de elopmen .
The incep ion o he Agenda 2030 p omp ed a su ge in he numbe o
schola ly pape s published on all dimensions o sus ainabili y, esul -
ing in a subs an ial body o li e a u e and significan con ibu ions o
he field (Khan, 2016;Scho & S einmuelle , 2018). The ed clus e
showcases he in e connec ions be ween he SDGs and en specific
ypes o inno a ion (Table 2), all o which suppo he h ee pilla s o
sus ainabili y (en i onmen al, social and economic). Specifically, eco-
inno a ion is conce ned wi h issues ha educe en i onmen al
impac and p o ec he plane (Albi a e al., 2023;Fa ma & Haleem,
2023). Social inno a ion and esponsible inno a ion, oge he wi h
es ablished me hods such as open and g ass oo s inno a ion, a e
di ec ed owa ds he social sphe e (Amba i, 2019;Panse a & Sa ka ,
2016). Finally, business model inno a ion, ugal inno a ion and
p oduc inno a ion suppo he economic pilla o sus ainabili y,
while business model inno a ion can con ibu e o sus ainabili y by
p omo ing local p oduc ion and inco po a ing eco- iendly p ac ices
Table 3
21 SDG a ge s selec ed by inno a ion- ela ed keywo ds.
5P Goal Ta ge Sum o occu ences Lis _o _keys
People SDG 1 1.4 4 p ope i igh
SDG 2 2.3 1 ag icul u p oduc i i y
SDG 2 2.4 15 sus ain ood p oduc sys em, sus ain ag icul u , ag oecolog, sus ain ood sys em
SDG 2 2.a 9 ag icul u esea ch
SDG 3 3.0 1 heal h esea ch inno
SDG 4 4.4 5 digi skill, echnolog skill, oca educ, new skill, e-lea n
SDG 4 4.a 1 school compu
SDG 5 5.b 1 ic women
P ospe i y SDG 7 7.1 15 mode n ene gi, a o d ene gi, mini-g id, elec gene a
SDG 7 7.2 353 clean ene gi, enew ene gi, g een ene gi, wind ene gi, sola ene gi, eco- iend ene gi, sola powe , wind u bin
SDG 7 7.a 5 clean ene gi echnolog, financ clean ene gi
SDG 8 8.2 514 echnolog inno , echnolog p og ess, inno g ow h, compe i inno , inno compe i , imp o p oduc i i y
SDG 8 8.3 169 en ep eneu ship, suppo smes, capi ma ke
SDG 8 8.10 7 mobil money se ic
SDG 9 9.0 19 digi ans o m, digi alis
SDG 9 9.2 16 sus ain indus i, manu ac u indus i, clean indus i, c ea i indus i, sus ain indus ialis
SDG 9 9.4 6 sus ain indus i p ocess, clean echnolog
SDG 9 9.5 452 inno in as uc u , inno indus i, indus i inno , indus i echnolog, esea ch de elop, &d, inno echnolog, g een
echnolog, os e inno , esea ch inno , inno esea ch, ne wo k esea ch, acili inno , scien i esea ch, scienc
echnolog inno , s i
SDG 9 9.b 1 de elop coun i echnolog
Plane SDG 12 12.5 70 ecycl, eus esou c, ci cula economi
SDG 13 13.2 37 clima chang polici, educ g eenhous gas emiss, educ ghg, emiss educ , educ emiss, ne ze o emiss, educ ca bon
emiss, emiss ade
Pa ne ship SDG 17 17.2 7 o fici de elop assis , oda
SDG 17 17.6 33 pa ne ship inno , sha e inno , sha e echnolog, echnolog ans e , collabo inno , pa ne ship esea ch, coope
esea ch
SDG 17 17.7 1 de elop coun i echnolog
Sou ce: he lis o keywo ds was iden ified h ough he SDG Mappe ool.
G. Dzhunushalie a and R. Teube Jou nal o Inno a ion & Knowledge 9 (2024) 100472
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