The challenge of measuring innovation types: A systematic literature review

S undziene, Alina; Pilinkiene, Vaida; Vilkas, Man as; G ybauskas, And ius;
Lukauskas, Man as
A icle
The challenge o measu ing inno a ion ypes: A sys ema ic
li e a u e e iew
Jou nal o Inno a ion & Knowledge (JIK)
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: S undziene, Alina; Pilinkiene, Vaida; Vilkas, Man as; G ybauskas, And ius;
Lukauskas, Man as (2024) : The challenge o measu ing inno a ion ypes: A sys ema ic li e a u e
e iew, Jou nal o Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 9, Iss. 4,
pp. 1-18,
h ps://doi.o g/10.1016/j.jik.2024.100620
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/327522
S anda d-Nu zungsbedingungen:
Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen
Zwecken und zum P i a geb auch gespeiche und kopie we den.
Sie dü en die Dokumen e nich ü ö en liche ode komme zielle
Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich
machen, e eiben ode ande wei ig nu zen.
So e n die Ve asse die Dokumen e un e Open-Con en -Lizenzen
(insbesonde e CC-Lizenzen) zu Ve ügung ges ell haben soll en,
gel en abweichend on diesen Nu zungsbedingungen die in de do
genann en Lizenz gewäh en Nu zungs ech e.
Te ms o use:
Documen s in EconS o may be sa ed and copied o you pe sonal
and schola ly pu poses.
You a e no o copy documen s o public o comme cial pu poses, o
exhibi he documen s publicly, o make hem publicly a ailable on he
in e ne , o o dis ibu e o o he wise use he documen s in public.
I he documen s ha e been made a ailable unde an Open Con en
Licence (especially C ea i e Commons Licences), you may exe cise
u he usage igh s as speci ied in he indica ed licence.
h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0/
The challenge o measu ing inno a ion ypes: A sys ema ic
li e a u e e iew
Alina S undziene
a,*
, Vaida Pilinkiene
a
, Man as Vilkas
a
, And ius G ybauskas
a
,
Man as Lukauskas
b
a
Kaunas Uni e si y o Technology, School o Economics and Business, Kaunas, Li huania
b
Kaunas Uni e si y o Technology, Facul y o Ma hema ics and Na u al Sciences, Depa men o Applied Ma hema ics, Kaunas, Li huania
ARTICLE INFO
JEL classi ica ion:
O30
O31
M21
Keywo ds:
Inno a ion
Types o inno a ion
Inno a ion measu emen
Inno a ion indica o s
Sys ema ic e iew
ABSTRACT
Measu ing inno a ion has long posed a signi ican challenge and has been he subjec o ex ensi e scien i ic
esea ch. Va ious de ini ions and measu es o inno a ion exis , and each measu emen app oach aces limi a-
ions. This esea ch aims o conduc a sys ema ic li e a u e e iew o expose he endencies in measu ing a ious
ypes o inno a ion, he eby e ealing di e en app oaches, challenges, and limi a ions. This pape sys emises
and g oups indica o s, highligh ing simila i ies and di e ences in measu ing a ious inno a ion ypes. The
sys ema ic li e a u e e iew includes 172 pape s om he WoS Co e Collec ion and Scopus da abases, p esen ing
inno a ion indica o s ac oss nine ypes o inno a ion: p oduc , p ocess, se ice, echnological, managemen (o
o ganiza ional, adminis a i e), business model, supply chain, g een (o en i onmen al, eco), and open inno-
a ion. The analysis e eals ha esea che s o en employ a b oad ange o indica o s, many o which a e no
e en closely aligned wi h speci ic inno a ion ypes. Acco dingly, his pape o e s ecommenda ions o selec ing
indica o s ailo ed o inno a ion ype.
In oduc ion
The e is b oad consensus ha inno a ion con ibu es o economic
and p oduc i i y g ow h in coun ies. I is also a c ucial ac o enabling
companies o emain compe i i e and achie e sus ainable compe i i e
ad an ages. Howe e , measu ing inno a ion has long posed a signi i-
can challenge and has been he ocus o ex ensi e scien i ic esea ch
(Hong e al., 2012; Ramme & Es-Sadki, 2022; Salaza & Holb ook,
2004).
Inno a ion e e s o ‘ he in oduc ion o a new p oduc , se ice, o
p ocess o he ex e nal ma ke o he in oduc ion o a new de ice,
sys em, p og am, o p ac ice in one o mo e in e nal uni s’ (Walke
e al., 2015). Newness o no el y is a co e ea u e o inno a ions.
Schumpe e iden i ied ypes o inno a ion by p oposing ha inno a ions
in ol e he in oduc ion o new p oduc s, new me hods o p oduc ion,
new ma ke s, new sou ces o supply, and new ma ke s uc u es o
o ganisa ional o ms. Consequen ly, he li e a u e includes nume ous
e alua ions o p oduc inno a ion (Galindo & M´
endez, 2014; Ma ko ic
& Baghe zadeh, 2018; Yildiz e al., 2024), p ocess inno a ion (An onioli
e al., 2021; Hussen & Çokgezen, 2020; Pålsson & Hells ¨
om, 2023),
ma ke ing inno a ion (Abu Rumman e al., 2019; Aiello, 2013), and
o ganisa ional inno a ion (J. Cheng e al., 2024; Walke e al., 2015).
Some o hese ypes o inno a ion a e combined and esea ched unde
he umb ella o echnological inno a ion assessmen (Yi e al., 2021;
Zhang, 2022). The scien i ic li e a u e u he explo es inno a ion
e alua ions ela ed o o he ypes o inno a ion, such as se ice inno-
a ion (Aas & Pede sen, 2011; Ki sios & G igo oudis, 2020; Yang e al.,
2018), g een o eco-inno a ion (Ga cía-G ane o e al., 2018; Ghise i &
Pon oni, 2015; Kie e e al., 2017), open inno a ion (Al-Belushi e al.,
2018), supply chain inno a ion (Abdallah e al., 2021; Ojha e al.,
2016).
Measu ing di e en ypes o inno a ion is challenging due o a ied
heo e ical amewo ks, measu es, and sou ces o in o ma ion on inno-
a ion guiding measu emen . The inpu –p ocess–ou pu –ou come
(IPOO) model is he dominan amewo k used in inno a ion measu e-
men (OECD, 2018), acili a ing inno a ion measu emen h ough he
s ages o he inno a ion p ocess (Go in & Mi chell, 2010).
Inpu -o ien ed me ics assess he esou ces dedica ed o inno a ion.
These me ics include R&D spending, he numbe o pe sonnel engaged
in inno a ion- ela ed ac i i ies, and echnological in es men s.
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (A. S undziene).
Con en s lis s a ailable a ScienceDi ec
Jou nal o Inno a ion & Knowledge
jou nal homepage: www.else ie .com/loca e/jik
h ps://doi.o g/10.1016/j.jik.2024.100620
Recei ed 5 Augus 2024; Accep ed 29 Oc obe 2024
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
A ailable online 17 No embe 2024
2444-569X/© 2024 The Au ho s. Published by Else ie España, S.L.U. on behal o Jou nal o Inno a ion & Knowledge. This is an open access a icle unde he CC
BY-NC-ND license (
h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/ ).
Ou pu -o ien ed me ics e alua e he esul s and p o ide angible e i-
dence o inno a ion e o s. These me ics include pa en ilings, new
p oduc s and se ices, and inno a ion e iciency. Ac i i y- ela ed me -
ics measu e he ange and dep h o ac i i ies speci ically aimed a
ini ia ing and achie ing inno a ion. Ou come o impac measu es cap-
u e he b oade e ec s o inno a ion on i m pe o mance, such as
changes in p oduc i i y, compe i i eness, and ma ke posi ion.
While his amewo k is use ul and guides inno a ion measu emen ,
i su e s om o e simpli ica ion o inno a ion p ocesses, a ocus on
angible me ics, a limi ed pe spec i e on ou pu s, and neglec o
ex e nal collabo a ion. Fi s , he IPOO model ep esen s inno a ion as a
linea sequence—inpu , p ocess, and ou pu —whe eas inno a ion is
o en non-linea , i e a i e, and in ol es eedback loops. Fu he mo e, i
ends o o e look b oade en i onmen al, o ganisa ional, and cul u al
ac o s in luencing inno a ion, such as ma ke dynamics, compe i ion,
and egula o y changes, con ibu ing o o e simpli ica ion o inno a ion
p ocesses. Second, while he model ocuses on quan i iable me ics such
as R&D expendi u e and he numbe o pa en s o p oduc s launched, i
neglec s in angible aspec s such as c ea i i y, o ganisa ional cul u e,
and knowledge c ea ion, ailing o cap u e lea ning, expe imen a ion,
and adap a ion p ocesses c ucial in inno a ion. Thi d, he IPOO model
emphasises immedia e ou pu s, such as new p oduc s o pa en s, while
igno ing long- e m impac s such as sus ained compe i i e ad an age,
ma ke dis up ion, o ecosys em de elopmen . This app oach may ocus
on p io i ising easily measu able ou comes, such as pa en numbe s,
o e mo e meaning ul inno a ions ha a e ha de o quan i y, such as
business model inno a ions o cus ome expe ience imp o emen s.
Finally, as companies inc easingly adop open inno a ion pa adigms,
he IPOO model’s assump ion ha inno a ion p ocesses occu p ima ily
wi hin o ganisa ional bounda ies does no accoun o he ole o
ex e nal collabo a ions, pa ne ships, o ne wo ks (e.g., open inno a-
ion, co-c ea ion wi h cus ome s) (Chesb ough & Boge s, 2014). This
heo e ical amewo k hus guides he selec ion o measu es, bu he
na u e o he measu es can also in luence he esul .
A mb us e e al. (2008) no ed ha di e en ypes o inno a ion
measu es yield di e en esul s. They p oposed ha inno a ion can be
measu ed by agg ega e measu es, use- o change- ype measu es,
ex en -o -use- ype measu es, and measu es ela ed o inno a ion ea-
u es. Fo example, o measu e o ganisa ional (i.e., adminis a i e)
inno a ion, such as a hyb id wo k model wi h bo h on-si e and emo e
wo k modes, an agg ega e measu e would ques ion whe he a i m’s
new o imp o ed o ganisa ional s uc u es, policies, o p ocedu es
signi ican ly di e om p e ious o ganisa ional s uc u es and ha e
been in oduced du ing he las yea . Al hough he hyb id wo k model is
no di ec ly measu ed, i alls unde he ca ego y o new o imp o ed
o ganisa ional s uc u es, policies, o p ocedu es, allowing such ques-
ions o cap u e he in oduc ion o hyb id wo k and o he o ganisa-
ional inno a ions. A use- o change- ype measu e would ask whe he
he o ganisa ion in oduced a hyb id wo k model, p oducing a dicho -
omous measu e. Fu he , he ex en o use o he hyb id wo k model
wi hin he o ganisa ion can be examined h ough a Like - ype o dinal
measu e, indica ing he ex en o used po en ial o o ganisa ional
inno a ion. Finally, one may ope a ionalise hyb id wo k in o cons i u-
i e dimensions and p obe o each dimension o mul iple mani es
i ems cons i u ing each dimension. All o hese app oaches yield
di e en esul s (A mb us e e al., 2008). Such examples e eal ha
inno a ion measu emen can be conduc ed a a ying le els o g anu-
la i y. The mul iple mani es indica o s-based app oach p o ides he
mos de ailed insigh and p esupposes su eys as da a sou ces. Howe e ,
su eys a e only one o se e al sou ces o inno a ion measu emen da a.
Inno a ions a e measu ed using su eys, s a is ical da a, pa en da a,
and da a collec ed using online algo i hms, wi h each sou ce in luencing
esul s h ough unique s eng hs and weaknesses. Su eys a e aluable
o collec ing bo h quali a i e and quan i a i e in o ma ion di ec ly
om s akeholde s such as companies, employees, cus ome s, o indus y
expe s. S a is ical da a encompasses a b oad ange o quan i a i e
in o ma ion ha can be analysed o de i e insigh s in o a company’s
inno a ions; common sou ces include inancial epo s, R&D spending
de ails, e enue om new p oduc s, and o he inno a ion- ela ed
inancial me ics. Pa en da abases se e as a ich sou ce o in o ma-
ion on a company’s echnological inno a ion, allowing a ious inno-
a ion aspec s o be analysed based on he numbe o pa en s iled and
g an ed as well as hei impac h ough ci a ions. Pa en s e lec he
di e si y o echnological a eas co e ed, indica ing inno a ion b ead h,
while pa en analysis e eals pa en ac i i y ac oss di e en coun ies,
sugges ing he scale and global each o inno a ion e o s. Finally, web
mining in ol es ex ac ing and analysing la ge da ase s om websi es,
social media pla o ms, and o he online sou ces. The same ype o
inno a ion can be measu ed using mul iple da a sou ces. Fo example,
p oduc inno a ions can be measu ed using su ey da a (E angelis a
e al., 2001; Rou inen, 2002), company epo s, pa en in o ma ion, and
web sc aping and p ocessing o company websi e da a (Kinne & Lenz,
2021). Each app oach has unique s eng hs and weaknesses (Ramme &
Es-Sadki, 2022). Howe e , he ou come o measu emen pa ly depends
on he da a used (H´
e oux-Vaillancou e al., 2020).
In summa y, measu ing inno a ion is challenging due o he heo-
e ical amewo ks ha guide measu emen , he a ious ypes o mea-
su es, and he sou ces o in o ma ion on inno a ion. The di e si y o
op ions in oduces high complexi y o inno a ion measu emen e o s.
Consequen ly, he esul s o esea ch ha adop idiosync a ic ap-
p oaches o inno a ion measu emen , g ounded in a speci ic se o
measu es, in o ma ion sou ces, and heo e ical amewo ks, a e o en
di icul o compa e. This esea ch aims o conduc a sys ema ic li e a-
u e e iew o e eal ends in he measu emen o a ious ypes o
inno a ion, as well as o unco e di e en app oaches, challenges, and
limi a ions. This pape seeks o sys emise and g oup indica o s o
highligh simila i ies and di e ences in measu ing di e en ypes o
inno a ion, con ibu ing o exis ing heo y and p ac ice in se e al ways.
Fi s , inno a ion is commonly di ided in o ypes such as p oduc ,
p ocess, echnological, and o ganisa ional inno a ion. Exis ing classi i-
ca ions a y among esea che s and ields, c ea ing a agmen ed un-
de s anding. By examining hese classi ica ions and iden i ying links
be ween hem, as sugges ed by Ko and Lu (2010), his esea ch p o ides
a sys ema ic analysis o he simila i ies and di e ences in measu ing
hese dimensions. Th ough he syn hesis and ca ego isa ion o inno a-
ion indica o s, his s udy adds dep h o he academic discou se on
inno a ion me ics.
Second, despi e he sho comings no ed abo e, he majo i y o i m-
le el inno a ion esea ch elies on he inpu –p ocess–ou pu –ou come
model. Due o he model’s comp ehensi eness, schola s end o use
single- ype measu es ela ed o inpu , ou pu , ac i i ies, o ou comes o
cap u e he ex en o a pa icula ype o inno a ion wi hin a company.
This s udy con ibu es o he ongoing discou se by demons a ing ha ,
as esea ch e ol es, inno a ion measu es become inc easingly di icul
o classi y s ic ly in o inpu o ou pu ca ego ies. The esea ch p esen s
a unique classi ica ion o inno a ion indica o s, o e ing a h ee-le el
agg ega ion sys em (majo , mode a e, mino ) ha enhances he cla i y
and applicabili y o inno a ion measu es ac oss a ious ypes o
inno a ion.
Thi d, he s udy summa ises dispa a e app oaches o measu ing
inno a ion by de eloping a classi ica ion sys em ha applies o nine
ypes o inno a ion (p oduc , p ocess, se ice, e c.). I also highligh s he
need o a s anda dised and alida ed sys em o inno a ion indica o s,
add essing a gap in he academic li e a u e whe e p e ious measu es
we e o en agmen ed and lacked su icien alida ion. This wo k can
hus se e as a ounda ion o u he heo e ical de elopmen and
empi ical alida ion.
Fou h, his esea ch p o ides a amewo k o p ac i ione s o assess
inno a ion mo e accu a ely by iden i ying speci ic indica o s o each
ype o inno a ion. I aids companies in aligning inno a ion e o s wi h
s a egic goals and enhancing decision-making. By sys emising and
classi ying indica o s, his esea ch p o ides o ganisa ions wi h
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
2
p ac ical guidelines o applying ele an me ics o e alua e inno a ion
ac oss di e en a eas.
The pape is s uc u ed as ollows. Sec ion 2 desc ibes he me hod-
ology employed o he analysis o pape s. Sec ion 3 p esen s an o e -
iew and compa ison o indica o s used o measu e nine ypes o
inno a ion (i.e., p oduc , p ocess, se ice, echnological, managemen ,
business model, supply chain, g een, and open). Sec ion 4 desc ibes he
da a sou ces esea che s use o ge in o ma ion abou company inno-
a ion. Sec ion 5 discusses limi a ions in cu en inno a ion measu e-
men p ac ices and sugges s di ec ions o u u e esea ch. Sec ion 6
p o ides a discussion o issues ela ed o inno a ion measu emen and
p esen s ecommenda ions on selec ing inno a ion indica o s. The
pape ends wi h he main conclusions de i ed om his esea ch.
Me hodology
The pape s o he sys ema ic li e a u e analysis we e selec ed om
he WoS Co e Collec ion and Scopus da abases, he leading and mos
epu able global ci a ion da abases. These da abases con ain high-
quali y jou nals, ensu ing he eliabili y o he esul s p esen ed in he
pape s. Since he objec i e o his esea ch is he measu emen o a
company’s inno a ion, pape s om hese da abases a e selec ed based
on he ollowing c i e ia:
•Keywo ds in he pape s’ i les, keywo ds, and abs ac s: (inno a ion
o inno a i e o inno a i eness) and (es ima ion o e alua ion o
measu emen ) and (indica o o measu e o a iable) and (company
o i m o en e p ise o co po a e);
•Documen ype: limi ed o A icles o Re iew A icles;
•Ca ego y: limi ed o Managemen , Business, Economics, Social Sci-
ences, o Mul idisciplina y Sciences;
•Publica ion da e: since 2010;
•Language: English.
The lis o he a icles used in his s udy was c ea ed on Ma ch 21,
2024. The pape selec ion p ocess is p esen ed in he P e e ed
Repo ing I ems o Sys ema ic Re iews and Me a-Analyses low dia-
g am (Page e al., 2021) in Fig. 1.
1557 a icles a e iden i ied in he WoS Co e Collec ion and 1815
a icles in he Scopus da abase. A e agg ega ing hese lis s o pape s
and elimina ing duplica es, a o al o 2619 pape s we e ob ained.
Fu he analysis is based on examining he abs ac s and keywo ds o
hese pape s, acco ding o he ollowing eligibili y c i e ia o iden i y
co e pape s o comp ehensi e analysis:
•Al hough he p ima y lis o pape s o med includes he keywo ds
il e ing he pape s ocused on companies’ inno a ion measu emen ,
a signi ican numbe o pape s s ill measu e inno a ion a he
egional, coun y, o ci y le el. Since he indica o s o inno a ion
measu emen a he mezzo o mac o le els di e , only pape s
ocused on inno a ion a he company le el a e deemed eligible.
•Nume ous pape s men ion ‘inno a ion’ in hei abs ac in a ious
con ex s (e.g., inno a i e me hod) o use he e m in agmen ed
ways wi hou aiming o measu e i . Mo eo e , ‘inno a ion’ is no
included among he keywo ds o he pape . These pape s a e also
excluded om u he analysis.
•Many pape s analyse company inno a ion in gene al ( he e is no
indica ion o a speci ic ype o inno a ion). Such pape s a e ou side
he scope o his esea ch and a e also excluded om u he analysis.
The analysis o such pape s will be he objec i e o ou u u e
esea ch. This esea ch is limi ed o he analysis o pape s ha
indica e he ype o inno a ion, such as p oduc inno a ion, p ocess
inno a ion, o g een inno a ion.
A e sc eening pape s based on hese c i e ia, he ollowing inno-
a ion ypes a e iden i ied: echnological, p oduc , se ice, o ganisa-
ional, managemen , adminis a i e, p ocess, ma ke ing, packaging,
employee, wo k beha iou , g een, en i onmen al, eco-inno a ion,
open, supply chain, consume , capi al, digi al, inancial, sus ainable,
business model, social, use , and knowledge. Howe e , se e al inno a-
ion ypes a e in es iga ed in a ew pape s, necessi a ing e ision o he
analysis o hei measu emen and explaining why such ypes o
Fig. 1. Flow diag am o he pape selec ion p ocess o he sys ema ic e iew.
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
3
inno a ion a e excluded om u he analysis. Thus, he u he
esea ch is limi ed o he analysis o nine ypes o inno a ion:
•P oduc inno a ion (22 pape s);
•P ocess inno a ion (18 pape s);
•Se ice inno a ion (14 pape s);
•Technological inno a ion (29 pape s);
•Managemen , o ganisa ional, o adminis a i e inno a ion (13
pape s);
•Business model inno a ion (se en pape s);
•Supply chain inno a ion ( i e pape s);
•G een, en i onmen al, o eco-inno a ion (51 pape s);
•Open inno a ion (13 pape s).
In o al, 172 a icles we e de e mined ele an o he comp ehen-
si e e iew. The analysis seeks o iden i y indica o s used o measu e
speci ic inno a ion ypes and he da a sou ces mos commonly used in
esea ch.
Gi en he di e si y o indica o s used in a ious esea ch, i is
necessa y o adop a ce ain sys em o hem. Acco dingly, his esea ch
classi ies indica o s a h ee le els o agg ega ion:
•Mino : indica o s a e p esen ed using main keywo ds om su ey
ques ions o seconda y da a sou ces. The lis o hese indica o s,
along wi h e e ences, is p esen ed in Appendix A.
•Mode a e: indica o s ( hei keywo ds) a e classi ied in o 16 ca e-
go ies based on he aspec s hey e eal, p esen ed in Sec ion 3 and
Appendix A.
•Majo : 16 ca ego ies a e g ouped in o ou clus e s, as desc ibed
below.
Conside ing he a ie y o indica o s used o measu e inno a ion, he
ollowing 16 ca ego ies o indica o s a e used in he analysis o
mode a e-le el agg ega ion:
•Ma e ials: indica o s ha conside a ious aspec s o ma e ials used
o make p oduc s, such as ecyclable, eusable, non-pollu ing/ oxic,
o emanu ac u ed ma e ials, inno a i e componen s, pa s, p od-
uc s, o less ma e ial.
•Na u al esou ces: indica o s ha obse e he esou ces equi ed o
make a p oduc o p o ide a se ice, such as he consump ion o
wa e , elec ici y, coal, oil, and enewable ene gy.
•Technology: indica o s ela ed o he company’s echnology, such as
g een, cleane echnology.
•Finance: g ouping a ious company inancial indica o s, such as in-
es men , e enue, cos , and p o i abili y.
•Pe sonnel: s a - ela ed indica o s, such as pe sonnel aining, R&D
pe sonnel, quali y, and p oduc i i y.
•P ocess: a ious indica o s ela ed o p oduc ion o deli e y, such as
p oduc de elopmen ime, capabili y, and imp o ed ways o pe -
o ming asks.
•Managemen : o ganisa ional aspec s o he company, such as s a egy,
policies and p ac ices, managemen sys ems, condi ions o o gan-
isa ional ac i i ies, ce i ica ion, audi s, and moni o ing and con ol
sys ems.
•P oduc : indica o s ela ed o he company’s ou pu , namely p oduc s
such as new p oduc s o imp o ed p oduc s.
•Se ice: indica o s ela ed o he company’s ou pu , namely se ices
such as new se ices o imp o ed se ices.
•Pa en : indica o s ela ed o ou pu , sepa a ed due o popula i y in
inno a ion esea ch.
•Ma ke : ma ke - ela ed indica o s, such as ma ke sha e, compe i-
ion, demand, g een ma ke s, and new ma ke s.
•Coope a ion: indica o s e lec ing he company’s ac i i ies wi h
coun e pa ies, such as supplie s and o he s akeholde s.
•Pollu ion: indica o s ela ed o pollu ion caused by p oduc p oduc-
ion, such as indus ial was e ecycling, ca bon emissions, and
sewage discha ge.
•Regula ions: i g oups indica o s ela ed o go e nmen al egula ions,
such as go e nmen suppo , incen i es, subsidies, and en i on-
men al axes.
•Dummy: ou pu - ela ed ca ego y dis inguishing inno a ion measu ed
di ec ly using a dummy a iable (e.g., adop ed o no adop ed).
•O dinal: ou pu - ela ed ca ego y dis inguishing inno a ion measu ed
di ec ly using an o dinal a iable (e.g., based on he numbe o
ealised company imp o emen s o inno a ions).
These 16 ca ego ies can be g ouped in o ou clus e s:
•Di ec indica o s ocus on whe he a ce ain inno a ion has aken
place, measu ed as a bina y o o dinal a iable;
•Ou pu indica o s ep esen p oduc s, se ices, and pa en s;
•In e nal indica o s co e ma e ial and non-ma e ial esou ces and
p ocesses equi ed o achie e he ou pu (i.e., ma e ials, na u al e-
sou ces, echnology, inance, pe sonnel, p ocesses, and
managemen );
•Ex e nal indica o s encompass ex e nal p ocesses and s akeholde s
in ol ed in o wi h he po en ial o impac he c ea ion o he ou pu
(i.e., ma ke , coope a ion, pollu ion, and egula ions).
The ela ionship be ween ca ego ies and clus e s is p esen ed in
Fig. 2.
Measu emen o di e en ypes o inno a ion
This chap e p esen s indica o s used o measu e he nine ypes o
inno a ion men ioned in he Me hodology sec ion.
P oduc inno a ion
P oduc inno a ion has been de ined and ope a ionalised in a ious
ways in he li e a u e. Some esea che s de ine i as de eloping and
in oducing new p oduc s (Ma ko ic & Baghe zadeh, 2018), while
o he s desc ibe i as imp o ing exis ing ou comes o con inually c ea ing
new p oduc lines. Chupina e al. (2023) de ine i as a p oduc wi h
supe io echnical cha ac e is ics and consume p ope ies, o ien ed o
mee bo h cu en and u u e needs a a high le el. P oduc inno a ion
gi es i ms a compe i i e ad an age, wi h a be e ma ke posi ion, by
in oducing highe -quali y o cos -sa ing p oduc s, which helps i ms ill
demand gaps (Galindo & M´
endez, 2014) and expand ma ke sha e
(Lesko a -Spacapan & Bas ic, 2007).
Measu ing p oduc inno a ion equi es e alua ing he in oduc ion
and impac o new o signi ican ly imp o ed goods o se ices. This
assessmen ypically elies on adi ional inpu -o ien ed indica o s, such
as R&D me ics. Some s udies employ indica o s such as o al u no e
sales, emphasising e enue gene a ed om inno a i e p oduc s. O he s
ocus on indica o s ha measu e p oduc inno a ion capaci y. P e-
dominan ly, p oduc ion inno a ion is measu ed as a dummy a iable in
su ey-based s udies. Addi ionally, a signi ican po ion o esea ch in-
co po a es measu es speci ically ela ed o new p oduc s, p o iding a
comp ehensi e iew o he inno a ion p ocess and i s esul s. The
summa y o p oduc inno a ion indica o s is p o ided in Fig. 3 and
Appendix A.
P ocess inno a ion
P ocess inno a ion in ol es new p oduc ion me hods, including
comme cially handling goods o se ices. I changes manu ac u ing
p ocesses wi hou al e ing p oduc s uc u e (A aoui e al., 2023).
Lugo oi e al. (2022) no ice ha , while p ocess inno a ion di e s in
na u e om p oduc inno a ion, esea che s equen ly ail o
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
4

dis inguish be ween he wo. This o e sigh dis ega ds he ac ha he
knowledge necessa y o enabling p ocess inno a ions is o en mo e
complex and aci . Gi en ha p ocess inno a ions can ha e c oss- unc-
ional impac s, hei de elopmen equi es inpu om he a ious
unc ions wi hin an o ganisa ion whose ope a ions will be a ec ed by
he new echnology.
Resea ch on p ocess inno a ion p ima ily uses ou pu measu es,
whe e mos s udies di ec ly ask i i ms ha e in oduced any p ocess
inno a ions, wi h esul s analysed as a bina y a iable (see Appendix A).
Consequen ly, much o he esea ch elies on subjec i e measu es o
p ocess inno a i eness. Howe e , sligh a ia ions exis in he ques ion
o mula ion. In mos s udies (Al uza a, 2017; An onioli e al., 2021;
Ayll´
on & Radicic, 2019), he dummy a iable akes a alue o 1 i a i m
con i med ha ing in oduced a leas one p ocess inno a ion (usually
wi hin he p e ious 3 yea s), and 0 o he wise. O he s udies (A i e al.,
2020; Iandolo & Fe agina, 2021; Ren´
e Win jes, 2019) ex end he
ques ion o include no only he in oduc ion bu also imp o emen s o
he p ocesses (e.g., ‘Has his i m in oduced a new o signi ican ly
imp o ed p ocess du ing he las h ee yea s?’). Howe e , hese may
lack cla i y in de ining p ocess inno a ion, leading o a ied in-
e p e a ions by esponden s.
A aoui e al. (2023) speci y he ques ion as: ‘Has you company
Fig. 2. Ca ego ies and clus e s o inno a ion indica o s.
Fig. 3. Clus e s and ca ego ies o indica o s used o measu e p oduc inno a ion.
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
5
in oduced any signi ican new o imp o ed ea u es o you
manu ac u ing o p oduc ion p ocesses o goods o se ices?’. Ba els-
man e al. (2019) de ine p ocess inno a ions as he implemen a ion o
new o signi ican ly imp o ed p oduc ion p ocesses, dis ibu ion
me hods, o suppo ac i i ies o he i m’s goods o se ices. O he
esea ch ocuses on he new me hod o p oduc ion (e.g., ‘i he i m
in oduced a new me hod o p oduc ion he p e ious yea ’ (Aslam e al.,
2023)) o p oduc s o se ices (Hussen & Çokgezen, 2020). Simila ly,
Aghazada and Ashy o (2022) ollow he guidelines o he OSLO
Manual, asking i he company in oduced any new o signi ican ly
imp o ed me hods o p oducing o supplying p oduc s o se ices
wi hin he las 3 yea s. Oudgou (2021) uses an e en mo e comp ehen-
si e o mula ion om he Wo ld Bank’s Business En e p ise Su ey
(WBES), asking: ‘Has his es ablishmen in oduced any new o signi i-
can ly imp o ed p ocess (including me hods o manu ac u ing p oduc s
o o e ing se ices, logis ics, deli e y, o dis ibu ion me hods o in-
pu s, p oduc s, o se ices, o suppo ing ac i i ies o p ocesses)’.
Pålsson and Hells ¨
om (2023) analyse p ocess inno a ion wi hin
packaging inno a ion, de ining i as he in oduc ion o new me hods o
p oducing packaging. This p ocess can be b oken down in o h ee
sub-p ocesses: iden i ying inno a ions in packaging manu ac u ing
p ocesses, implemen ing new packaging manu ac u ing p ocesses, and
con inuous imp o emen . These sub-p ocesses a e a ed on a 4-poin
scale based on he ex en o which hey mee a ious equi emen s,
anging om bad p ac ice h ough medioc e p ac ice and good p ac ice
o bes p ac ice. Shi i e al. (2015) also coun he numbe o inno a ions
and also use an o dinal a iable ( om 0 o 4) o measu e p ocess
inno a ion.
The s udy by Lugo oi e al. (2022) is he only esea ch u ilising
subjec i e measu es, analysing pha maceu ical i ms’ inno a i e ou pu
h ough manu ac u ing p ocess pa en s. Sys ema ised in o ma ion
ega ding p ocess inno a ion measu emen is p o ided in Fig. 4 and
Appendix A.
Se ice inno a ion
Due o he a ious o ms o inno a ion, he e is no exac de ini ion o
se ice inno a ion, which may a y ac oss he in es iga ed sec o s.
Inno a ion in se ices is mo e mul idimensional han inno a ion in
manu ac u ing. Jong e al. (2003) a gue ha p oduc and p ocess in-
no a ions usually coincide due o he simul anei y o se ices, meaning
se ice inno a ion may encompass bo h p oduc and p ocess inno a ion.
Aas and Pede sen (2011) u he a gue ha nea ly all inno a ion ac-
i i ies in se ice i ms can be b oadly conside ed se ice inno a ions
and ha all inno a ion ypes epo ed in he Communi y Inno a ion
Su ey (CIS) (i.e., p oduc , p ocess, o ganisa ional, and ma ke ing
inno a ion) may quali y as se ice inno a ions in se ice indus ies.
Howe e , o i ms in he manu ac u ing indus y, only new se ices,
new logis ics, deli e y o dis ibu ion me hods, and new p oduc
placemen o sales channels can be conside ed se ice inno a ions (Aas
& Pede sen, 2011). Public se ice inno a ion, ocusing p ima ily on
social wel a e, is de ined as he c ea ion and implemen a ion o new
p ocesses, p oduc s, se ices, and deli e y me hods, o hei discon i-
nui y, in ol ing he pa icipa ion o o ganisa ions, supplie s, and clien s
(Co ona-T e i˜
no, 2023).
Go sch and Hipp (2012) a gue ha all se ice inno a ions can be
p o ec ed wi h adema ks, making adema ks a measu e o se ice
(and o he ypes o ) inno a ion. Howe e , mos esea che s u ilise a se
o indica o s o measu e se ice inno a ion. Yang e al. (2018) p opose a
ou -dimensional model consis ing o a new se ice deli e y sys em,
new clien in e ace, new se ice concep , and echnology choice,
measu ed ac oss 15 c i e ia ( ou c i e ia o each dimension, excep o
echnology selec ion, which has h ee dimensions). O he esea ch
(Yang e al., 2010) analyses se en indica o s o e alua e inno a ion
sou ces. Two o hese a e in e nal quan i a i e indica o s: he pe cen -
age o R&D unds ela i e o he i m’s sales and he pe cen age o
employees wi h a leas a bachelo ’s deg ee, ep esen ing wo k o ce
quali y. Ex e nal inno a ion sou ces (s a egic alliances, supplie s, cus-
ome s, consul ancy i ms, and compe i o s) a e sco ed om 0 o 1 based
on he equency wi h which i ms in e ac wi h ex e nal esou ces, wi h
1 as he highes sco e. Ki sios and G igo oudis (2020) analyse 24 inno-
a ion d i e s, ca ego ised in o six main g oups: en e p ise beha iou
o se ice inno a ion, idea gene a ion sou ces o he p o ided se ice,
ac ions o de eloping he p o ided se ice, o ganisa ional s uc u e
impac , en e p ise esou ce alloca ion impac , and ma ke impac .
Pan iluk and Szyma´
nska (2017) o e a se o 12 measu es o
measu ing inno a i eness, including i e measu es o inno a ion ac-
ions and se en o assessing he inno a i e ac ions aken. Measu emen
o en e p ise in ol emen in inno a i e ac i i ies includes o mula ing
de elopmen s a egies ha inco po a e inno a ions, expendi u e on
R&D, designa ed budge s o inno a ions, inancial esou ces o
aining ecalcula ed pe employee annually, and he es ablishmen o
uni s esponsible o he collec ion o ma ke in o ma ion. The assess-
men o he e ec s o inno a i e ac i i ies includes highe employee
p oduc i i y, lowe se ice p o ision cos s, ade name o adema k
egis a ions, inc eased se ice sale e enues, he limi a ion o ou ism
seasonali y, and inc eased ou is isi s in a gi en a ea annually.
Manoha e al. (2021, 2023) summa ise se ice inno a ion measu es,
no ing ha esea che s employ di e se, dynamic measu emen scales
based on a ious app oaches. This a ia ion in app oach unde sco es he
need o a scale o pe cei ed se ice inno a ion, ollowing he syn hesis
app oach. Manoha e al. (2021) de eloped and es ed a scale con aining
se en majo ypologies measu ing se ice inno a ion, including bo h
echnological inno a ion (co e p oduc , pe iphe al p oduc , co e p o-
cess, and pe iphe al p ocess inno a ion) and non- echnological inno-
a ion (o ganisa ion, s a egic, and ma ke ing inno a ion) componen s.
La e , Manoha e al. (2023) de eloped a 22-i em scale, INNOSERV,
wi h he same se en majo ypologies measu ing se ice inno a ion.
Unlike p oduc s, se ices a e less s anda dised, and adi ional R&D
app oaches a e less applicable o se ice inno a ions. The e o e, he
ocus is shi ing owa d ac ual capabili ies and compe encies ha allow
i ms o sou ce ideas and con e hem in o ma ke able se ice
Fig. 4. Clus e s and ca ego ies o indica o s used o measu e p ocess inno a ion.
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
6
p oposi ions (Janssen e al., 2016). Janssen e al. (2016) p o ide a se o
dynamic se ice inno a ion capabili ies in ou cons uc s: sensing use
needs and ( echnological) op ions (six i ems), concep ualising ( ou
i ems), cop oducing and o ches a ing (3 i ems), and scaling and
s e ching (5 i ems). Babaei and Aghdassi (2022) add ha dynamic
se ice inno a ion capabili ies (DSICs) and o ganisa ional se ice
inno a ion compe encies (OSICs) a e c i ical ac o s in se ice inno a-
ion quali y. They p opose a amewo k based on he ma u i y model
concep o measu e se ice inno a ion pe o mance and con inuously
imp o e se ice inno a ion quali y. Using a speci ic ques ionnai e
consis ing o 34 ques ions, ou ypes o i m pe o mance in se ice
inno a ion can be ecognised: incapable, s uggling, unca ed, and
exhaus i e.
In Co ona-T e i˜
no’s (2023) esea ch, inno a i eness is measu ed
h ough he INDICO index (inno a ion, di usion, co- alue), adap ed
om echnology i ms. This index conside s a me ic o se en ela ed
inno a ion pa ame e s conce ning capaci ies and esul s, including he
inno a ion selec ed, adap a ions and eplicas (possible ou comes), im-
pac s on public and/o use alues ( esou ces and in e es s), knowledge
dep h equi ed o he inno a ion’s c ea ion, implemen a ion and de-
li e y, design capabili ies (R&D), co- alue (collabo a ion (en ailmen )
as co-c ea ion and co-p oduc ion (including i s deli e y)), and educa-
ional deg ees a he inno a ion’s beginning as well as aining du ing
he inno a ion’s c ea ion. The summa y o se ice inno a ion indica o s
is p o ided in Fig. 5 and Appendix A.
Technological inno a ion
Technological inno a ion is usually de ined as he de elopmen o
new p oduc s and p ocesses o as subs an ial echnological imp o e-
men s in exis ing p oduc s and p ocesses. I p esen s po en ial p o i
oppo uni ies o en ep eneu s o g asp he ma ke ; o gain mo e
p o i s, en e p ises need o eo ganise p oduc ion condi ions and ac o s
and es ablish a new sys em o p oduc ion and ope a ion ha enhances
e iciency and educes cos s (Chen & Zhao, 2012). The signi icance o
echnological inno a ion is closely associa ed wi h a ious aspec s o
i m pe o mance and compe i i eness. Resea ch has shown ha ech-
nological inno a ion impac s i m compe i i eness (Aldian o e al.,
2021; Cha zoglou & Cha zoudes, 2018), sus ainable g ow h (B and˜
ao
San ana e al., 2015; Lee & Lee, 2021; Li & Yang, 2022), i m g ow h (Lin
e al., 2020; Ma ínez-Alonso e al., 2020), and business s a egies
(Ve bano & C ema, 2016). I is also closely linked o bo h p ocess and
p oduc inno a ions (Geldes e al., 2017; Wu & Liu, 2016).
Mos pape s p edominan ly ocus on e alua ing echnological inno-
a ion, while only a ew ha e examined measu emen dimensions
h ough he lens o echnological inno a ion e iciency ( ou pape s) o
echnological inno a ion capabili ies ( wo pape s). Measu ing echno-
logical inno a ion is complex and cu en ly lacks a uni e sally accep ed
amewo k. Some esea ch elies on indi ec indica o s such as R&D
expendi u e and pa en da a (Chen e al., 2024, 2021; Gu e al., 2018;
Lee & Lee, 2021; Ve bano & C ema, 2016; Zhang, 2015) while o he s
u ilise di ec indica o s such as inno a ion coun s and company-based
su eys (C uz-C´
aza es e al., 2013; Lee & You, 2016; Ve bano &
C ema, 2016; Yi e al., 2021; Zhang, 2015).
Technological inno a ions a e achie ed h ough a long and complex
p ocess in ol ing phases such as sea ching, selec ing, implemen ing,
and cap u ing alue (C uz-C´
aza es e al., 2013). Al hough measu ing
echnological inno a ions is well-es ablished in he li e a u e, empi ical
e idence emains limi ed. Va ious s udies ha e applied echnological
inno a ion measu emen a he i m le el, wi h no able analyses con-
duc ed in coun ies such as China, Japan, and Spain. These s udies o en
di e ge in hei me hodologies: some include inpu s and ou pu s beyond
he echnological inno a ion p ocess (Zhang, 2022), while o he s asso-
cia e echnological inno a ion wi h di ec inpu indica o s and e alua e
he inal ou pu adi ionally, such as h ough pa en s o new p oduc
de elopmen . The summa y o echnological inno a ion indica o s is
p o ided in Fig. 6 and Appendix A.
Managemen inno a ion
This subsec ion a ibu es pape s ha s udy managemen inno a ion,
manage ial inno a ion, o ganisa ional inno a ion, and adminis a i e
inno a ion. Damanpou (2014) de ines managemen inno a ion as ‘ he
de elopmen and use o new app oaches o pe o ming he wo k o
managemen , new o ganisa ional s a egy and s uc u e, and new p o-
cesses ha p oduce changes in he o ganisa ion’s manage ial p ocedu es
and adminis a i e sys ems’. The Oslo Manual sugges s ha adminis-
a ion and managemen inno a ion a e pa o business p ocess inno-
a ion (Oslo Manual, 2018).
Managemen inno a ion is measu ed by assessing inpu s and ou pu s
associa ed wi h such inno a ion. Inpu - ela ed measu es o managemen
inno a ion include measu es such as in es men , esou ces o ganisa ion
o managemen inno a ion (Huang e al., 2015), pe cen age o man-
agemen s a , pe cen age o echnical s a , pe cen age o sales s a ,
managemen inpu a io, and R&D inpu a io (Cheng e al., 2024).
Managemen inno a ion is also measu ed by e alua ing employees,
including s a egic and beha iou al inno a i eness o all le els o
manage s (Ghosh & S i as a a, 2022), he ex en o c ea i i y, openness
o change, u u e o ien a ion, isk- aking, and p oac i eness (Raj &
S i as a a, 2016). Ou pu - ela ed indica o s include egula ly enewed
ules and p ocedu es, egula changes o he employees’ asks and
unc ions, he egula implemen a ion o new managemen sys ems,
changes in policy compensa ion, egula es uc u ing o in a- and
in e -depa men al communica ion s uc u es, and con inuous al e -
a ions o o ganisa ional s uc u e (Hassi, 2019). Heyden e al. (2018)
measu e managemen inno a ion by looking o indica ions o changes
in how o ganisa ions a ange communica ion and align and ha ness
e o om hei membe s, changes in ou ines ha go e n he wo k o
manage s, and changes in wha manage s do as pa o hei job on a
day- o-day basis. Gio opoulos e al. (2017) ack he numbe o im-
p o emen s o inno a ions ealised in he i m’s unc ions du ing he
las 3 yea s. Finally, Li e al. (2014) e alua e managemen inno a ion
Fig. 5. Clus e s and ca ego ies o indica o s used o measu e se ice inno a ion.
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
7
based on he ex en o employee de elopmen and sa e y, ope a ions
e ec i eness, he ma ke , and he inancial and social in luence o he
o ganisa ion. Schola s (Ghosh & S i as a a, 2022; Gio opoulos e al.,
2017; Hassi, 2019; Li e al., 2014; Raj & S i as a a, 2016) p ima ily ely
on su eys o measu e managemen inno a ion. Heyden e al. (2018)
combined epo s om an HR consul ing i m ha conduc s pe o -
mance e alua ions o manage s wi h companies’ a chi al sou ces o
measu e he ex en o managemen inno a ion as a unc ion o keywo ds
ela ed o changes in communica ion s uc u es, o ganisa ional ou ines,
and manage s’ day- o-day ac i i ies.
While schola s sugges ha managemen inno a ion, manage ial
inno a ion, o ganisa ional inno a ion, and adminis a i e inno a ion
ha e conside able o e lap (Damanpou , 2014; Henao-Ga cía & Ca dona
Mon oya, 2023; Walke e al., 2015), his analysis e eals a s a k
di e gence in he measu emen o o ganisa ional and managemen
(including manage ial and adminis a i e) inno a ion. Au ho s
measu ing o ganisa ional inno a ion (Cheng e al., 2024; Ghosh & S i-
as a a, 2022; Raj & S i as a a, 2016) end o ocus on measu es o
o ganisa ional inno a ion capaci y o company inno a i eness.
Con e sely, au ho s concen a ing on measu ing managemen inno a-
ion ocus on manage s’ e o s o in oduce new s uc u es, p ocesses,
sys ems, p og ams, o p ac ices wi hin an o ganisa ion o i s uni s
(Walke e al., 2015). Howe e , measu es a y ex ensi ely wi hin hese
wo ca ego ies, unde sco ing he need o con e gence, as i may a ec
compa abili y and hinde he accumula ion o e idence ega ding he
an eceden s and e ec s o managemen inno a ion. The summa y o
managemen inno a ion indica o s is p o ided in Fig. 7 and Appendix A.
Business model inno a ion
Business models a e s uc u al empla es o how i ms un and
de elop hei businesses on holis ic and sys emic le els (Clauss, 2017).
This s udy d aws on Foss and Saebi’s de ini ion o business model
inno a ion as ‘designed, no el, and non i ial changes o he key ele-
men s o a i m’s business model and/o he a chi ec u e linking hese
elemen s’, unde s anding business model inno a ion in e ms o no el y
and scope (Foss & Saebi, 2017).
Business model inno a ion is measu ed by measu ing he ou pu s
associa ed wi h such inno a ion. Se e al s a egies a e associa ed wi h
he measu emen o business model inno a ion. Fi s , schola s measu e
business model inno a ion di ec ly by p obing o changes o he busi-
ness model o pa s o he business model (Bouwman e al., 2019; Liu
e al., 2024). Measu es include a ious ypes o business model change,
such as changing he en i e business model, changing only some com-
ponen s o he business model, changing he p oduc o se ice o e ing
be o e changing he business model, changing he business model be o e
changing he p oduc o se ice o e ing, making simul aneous changes
o he business model and p oduc o se ice o e ing, and ying ou
new business models in p ac ice be o e making inal changes (Bouwman
e al., 2019).
The second measu emen app oach o business model inno a ion
assumes ha i can be agg ega ed in o h ee dimensions: alue c ea ion,
alue p oposi ion, o alue cap u e (B eie e al., 2021; Clauss, 2017;
Spie h & Schneide , 2016). Acco dingly, schola s di ec ly measu e he
change in alue c ea ion (B eie e al., 2021), change in alue p oposi-
ion (B eie e al., 2021; Ciampi e al., 2021; Niyawanon , 2023), and
change in alue cap u e (B eie e al., 2021) o gain insigh s in o he
scope and ex en o business model inno a ion.
Finally, he hi d measu emen app oach ope a ionalises hese h ee
business model dimensions and consecu i ely measu es he changes
wi hin hese dimensions (Clauss, 2017). To measu e he scope and
ex en o change in he alue c ea ion dimension, schola s measu e he
ex en o change in compe encies and esou ces (Clauss, 2017; Hock--
Doepgen e al., 2021; Mülle e al., 2018; Spie h & Schneide , 2016),
echnology o equipmen (Clauss, 2017; Hock-Doepgen e al., 2021;
Mülle e al., 2018; Spie h & Schneide , 2016), p ocesses and s uc u es
(Ciampi e al., 2021; Clauss, 2017; Hock-Doepgen e al., 2021; Spie h &
Schneide , 2016), and pa ne ships (Ciampi e al., 2021; Clauss, 2017;
Hock-Doepgen e al., 2021; Liu e al., 2024; Mülle e al., 2018; Niya-
wanon , 2023; Spie h & Schneide , 2016). To measu e he scope and
ex en o change in he alue p oposi ion, esea che s p obe o changes
in cus ome s and ma ke s (Ciampi e al., 2021; Clauss, 2017;
Fig. 6. Clus e s and ca ego ies o indica o s used o measu e echnological inno a ion.
Fig. 7. Clus e s and ca ego ies o indica o s used o measu e managemen inno a ion.
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
8
main ocus o each ype o inno a ion and he clus e s o inno a ion
indica o s ha bes e lec i .
We sugges using he main clus e (o clus e s) o inno a ion in-
dica o s ha bes ep esen ha ype o inno a ion, a oiding he in-
clusion o indica o s ha may ep esen o he ypes o inno a ion.
Pa en s se e as p oo o inno a ion and can be used as an inno a ion
indica o in each case bu should be di ec ly ela ed o ha ype o
inno a ion. Tha is, p oduc pa en s can se e as inno a ion indica o s o
p oduc inno a ion bu no o o he ypes o inno a ion. Since no p ocess
o inno a ion can occu wi hou people, pe sonnel- ela ed indica o s
should be ca e ully selec ed o e lec a ce ain ype o inno a ion.
While a ious ypes o inno a ion a e indeed in e ela ed, sepa a ing
hem o a oid indica o duplica ion is challenging. Fo example, in-
dica o s e lec ing echnologies a e no only ela ed o echnological
inno a ions bu can also be ela ed o p ocesses, supply chains, and
o he ypes o inno a ion. Technology inno a ion also o en leads o he
c ea ion o new p oduc s o se ices. Howe e , esea che s should ag ee
on common indica o s o measu ing di e en ypes o inno a ion o
a oid con usion and acili a e he compa ison o esea ch esul s.
Thus, sugges ed indica o s o inno a ion measu emen a e based on
he p ima y ocus and di e ences o each ype o inno a ion. Fo
example, p oduc inno a ion ocuses on physical goods ha can be
manu ac u ed, while se ice inno a ion emphasises in angible se ices
ha p o ide alue o cus ome s. Managemen inno a ion in ol es in-
e nal o ganisa ional ans o ma ions, whe eas business model inno a-
ion conside s ex e nal indica o s, such as he alue a business o e s o
i s cus ome s. Supply chain inno a ion can be analysed h ough in-
dica o s o coope a ion wi h supplie s, manu ac u e s, dis ibu o s, and
cus ome s, while open inno a ion can be measu ed using indica o s o
coope a ion wi h uni e si ies, s a -ups, associa ions, and companies
beyond supplie s, manu ac u e s, dis ibu o s, and cus ome s.
Conclusions
This pape p esen s a sys ema ic li e a u e e iew summa ising
inno a ion indica o s acco ding o nine ypes o inno a ion: p oduc ,
p ocess, se ice, echnological, managemen (o o ganisa ional,
adminis a i e), business model, supply chain, g een (o en i onmen al,
eco), and open inno a ion. The s udy indica es ha g een inno a ion,
also known as en i onmen al o eco-inno a ion, has eme ged as he
mos ex ensi ely esea ched a ea in ecen yea s. The inc easing olume
o esea ch in his ield e lec s g owing global awa eness and conce n
o e clima e change and he u gen need o solu ions o mi iga e i s
e ec s. G een inno a ion encompasses a b oad ange o ac i i ies,
including he de elopmen o new echnologies, p ocesses, and p oduc s
ha minimise en i onmen al impac , hus in e sec ing wi h many o he
ypes o inno a ion.
Su eys, including bo h p ima y and es ablished su eys, a e he
mos commonly used me hod, accoun ing o 58 % o all inno a ion
measu emen e o s. Es ablished su eys, such as he Communi y
Inno a ion Su ey (CIS), a e especially p ominen in measu ing p oduc
and p ocess inno a ions. Meanwhile, echnological and g een in-
no a ions ely mo e hea ily on s a is ical da a. S a is ical da a, such as
inancial epo s, indus y s a is ics, and pa en da a, a e used in 30.3 %
o cases. Howe e , he e is limi ed use o big da a sou ces, such as
company websi es and social media, o measu e inno a ions. Machine
lea ning me hods applied o company websi es a e used in only 0.5 % o
s udies.
This s udy demons a es ha de ini ions a e a signi ican challenge
in measu ing inno a ion. Fi s , schola s de ine each ype o inno a ion
in a ious ways. Second, de ini ions o e lap due o he in e ela ed
na u e o di e en inno a ion ypes. Consequen ly, con usion a ises o e
selec ing app op ia e indica o s o measu ing di e en ypes o
inno a ion.
The s udy e eals ha no pa icula indica o s a e exclusi e o spe-
ci ic ypes o inno a ion. Ins ead, esea che s employ a wide ange o
indica o s, many o which a e no closely ied o a pa icula ype o
inno a ion. Mos inno a ion measu emen s ocus on inancial and
pe sonnel- ela ed indica o s ac oss di e en ypes o inno a ion. This
b oad app oach can limi he abili y o cap u e he speci ic na u e o
ce ain inno a ions, leading o inaccu a e assessmen s.
Acco dingly, his pape p esen s ecommenda ions o selec ing
inno a ion indica o s based on hei ype. I includes a lis o clus e s o
inno a ion indica o s sugges ed o analysing di e en ypes o inno-
a ion, based on he p ima y ocus and di e ences o each inno a ion
ype o a oid o e lap. Howe e , u he in es iga ion in o he use ulness
o a ious indica o s and hei capaci y o e lec speci ic ypes o
inno a ion would be e y use ul and ele an . Fu u e esea ch should
ocus on e ining inno a ion measu emen by in es iga ing he ele-
ance and p ecision o di e en indica o s, de eloping s anda dised
sys ems, and inco po a ing mo e de ailed measu emen me hods. The
lack o s anda dised sys ems o selec ing and using inno a ion in-
dica o s unde sco es he need o an es ablished amewo k o help e-
sea che s selec mo e app op ia e indica o s and imp o e he p ecision
o inno a ion e alua ions.
Funding
This p ojec has ecei ed unding om he Resea ch Council o
Li huania (LMTLT), ag eemen No S-MIP-23–54.
CRediT au ho ship con ibu ion s a emen
Alina S undziene: W i ing – e iew & edi ing, W i ing – o iginal
d a , Visualiza ion, Supe ision, So wa e, Me hodology, Fo mal anal-
ysis, Da a cu a ion, Concep ualiza ion. Vaida Pilinkiene: W i ing –
e iew & edi ing, W i ing – o iginal d a , P ojec adminis a ion,
In es iga ion, Funding acquisi ion, Fo mal analysis. Man as Vilkas:
W i ing – e iew & edi ing, W i ing – o iginal d a , Resou ces, In es-
iga ion, Fo mal analysis. And ius G ybauskas: W i ing – e iew &
edi ing, W i ing – o iginal d a , Valida ion, Resou ces, Me hodology,
In es iga ion, Fo mal analysis. Man as Lukauskas: W i ing – e iew &
edi ing, W i ing – o iginal d a , Visualiza ion, Valida ion, So wa e,
Resou ces, Fo mal analysis.
Decla a ion o compe ing in e es
The au ho s ha e no con lic o in e es , inancial o o he wise.
Supplemen a y ma e ials
Supplemen a y ma e ial associa ed wi h his a icle can be ound, in
he online e sion, a doi:10.1016/j.jik.2024.100620.
Re e ences
Aas, T. H., & Pede sen, P. E. (2011). The impac o se ice inno a ion on i m-le el
inancial pe o mance. The Se ice Indus ies Jou nal, 31(13), 2071–2090. h ps://
doi.o g/10.1080/02642069.2010.503883
Abdallah, A. B., Al a , N. A., & Alhya i, S. (2021). The e ec o supply chain quali y
managemen on supply chain pe o mance: The indi ec oles o supply chain agili y
and inno a ion. In e na ional Jou nal o Physical Dis ibu ion & Logis ics Managemen ,
51(7), 785–812. h ps://doi.o g/10.1108/IJPDLM-01-2020-0011
Abu Rumman, A., Al-Abbadi, L., & Abu-Rumman, A. (2019). O ganiza ional Memo y,
Knowledge Managemen , Ma ke ing Inno a ion and Cos O Quali y: Empi ical
E ec s F om Cons uc ion Indus y In Jo dan. Academy o En ep eneu ship Jou nal,
25, 1528–2686.
A ab Alam, M., Rooney, D., & Taylo , M. (2022). Measu ing In e -Fi m Openness in
Inno a ion Ecosys ems. Jou nal o Business Resea ch, 138, 436–456. h ps://doi.o g/
10.1016/j.jbus es.2021.08.069
Aghazada, E., & Ashy o , G. (2022). Role o ins i u ions in he co up ion and i m
inno a ion nexus: E idence om o me So ie Union coun ies. Pos -Communis
Economies, 34(6), 779–806. h ps://doi.o g/10.1080/14631377.2021.2006495
Ahmed, R. R., Akba , W., Aijaz, M., Channa , Z. A., Ahmed, F., & Pa ma , V. (2023). The
ole o g een inno a ion on en i onmen al and o ganiza ional pe o mance:
Mode a ion o human esou ce p ac ices and managemen commi men . Heliyon, 9
(1), A icle e12679. h ps://doi.o g/10.1016/j.heliyon.2022.e12679
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
15

Aiello, F. (2013). The e ec i eness o R&D suppo in I aly. Some e idence om
ma ching me hods. Risk Go e nance and Con ol: Financial Ma ke s and Ins i u ions, 3
(4), 7–15. h ps://doi.o g/10.22495/ gc 3i4a 1
Al-Belushi, K. I. A., S ead, S. M., G ay, T., & Bu gess, J. G. (2018). Measu emen o open
inno a ion in he ma ine bio echnology sec o in Oman. Ma ine Policy, 98, 164–173.
h ps://doi.o g/10.1016/j.ma pol.2018.03.004
Aldian o, L., Tjak aa madja, J. H., La so, D., P imiana, I., & Anggadwi a, G. (2021).
A Technological Inno a i eness Measu emen F amewo k: A Case S udy o
Technology Based Indonesian Companies. Gadjah Mada In e na ional Jou nal o
Business, 23(1), 91–112. h ps://doi.o g/10.22146/gamaijb.33105
Al uza a, A. (2017). A e he e di e ences in pe sis ence ac oss di e en inno a ion
measu es? Inno a ion, 19(3), 353–371. h ps://doi.o g/10.1080/
14479338.2017.1331911
Amo es-Sal ad´
o, J., Ma in-de Cas o, G., & Na as-L´
opez, J. E. (2015). The impo ance o
he complemen a i y be ween en i onmen al managemen sys ems and
en i onmen al inno a ion capabili ies: A i m le el app oach o en i onmen al and
business pe o mance bene i s. Technological Fo ecas ing and Social Change, 96,
288–297. h ps://doi.o g/10.1016/j. ech o e.2015.04.004
An onioli, D., Gioldasis, G., & Musolesi, A. (2021). Es ima ing a non-neu al p oduc ion
unc ion. Ox o d Economic Pape s, 73(2), 856–878. h ps://doi.o g/10.1093/oep/
gpaa021
A aoui, N., Le Bas, C., Ve nie , M.-F., & Vo, L.-C. (2023). Inno a ion S a egies and
Implemen a ion o Va ious Ci cula Economy P ac ices: Findings om an Empi ical
S udy in F ance. Jou nal o Inno a ion Economics & Managemen , N◦, 42(3), 149–183.
h ps://doi.o g/10.3917/jie.p 1.0141
A lbjø n, J. S., de Haas, H., & Munksgaa d, K. B. (2011). Explo ing supply chain
inno a ion. Logis ics Resea ch, 3(1), 3–18. h ps://doi.o g/10.1007/s12159-010-
0044-3
A mb us e , H., Bik al i, A., Kinkel, S., & Lay, G. (2008). O ganiza ional inno a ion: The
challenge o measu ing non- echnical inno a ion in la ge-scale su eys.
Techno a ion, 28(10), 644–657. h ps://doi.o g/10.1016/j.
echno a ion.2008.03.003
Asiaei, K., O’Conno , N. G., Ba ani, O., & Joshi, M. (2023). G een in ellec ual capi al and
ambidex ous g een inno a ion: The impac on en i onmen al pe o mance. Business
S a egy and he En i onmen , 32(1), 369–386. h ps://doi.o g/10.1002/bse.3136
Aslam, M., Sha i, I., Ahmed, J., de Ma in, M. S. G., Flo es, E. S., Gu i´
e ez, M. A. R., e al.
(2023). Impac o Inno a ion-O ien ed Human Resou ce on Small and Medium
En e p ises’ Pe o mance. Sus ainabili y, 15(7), 6273. h ps://doi.o g/10.3390/
su15076273
Ayll´
on, S., & Radicic, D. (2019). P oduc inno a ion, p ocess inno a ion and expo
p opensi y: Pe sis ence, complemen a i ies and eedback e ec s in Spanish i ms.
Applied Economics, 51(33), 3650–3664. h ps://doi.o g/10.1080/
00036846.2019.1584376
Babaei, M., & Aghdassi, M. (2022). Measu ing he dimensions o quali y in se ice
inno a ion: A dynamic capabili y and o ganisa ional compe ency pe spec i e. To al
Quali y Managemen & Business Excellence, 33(3–4), 434–466. h ps://doi.o g/
10.1080/14783363.2020.1861933
Bae, Y., & Chang, H. (2012). E iciency and e ec i eness be ween open and closed
inno a ion: Empi ical e idence in Sou h Ko ean manu ac u e s. Technology Analysis
& S a egic Managemen , 24(10), 967–980. h ps://doi.o g/10.1080/
09537325.2012.724164
Bai, R., & Lin, B. (2024). G een inance and g een inno a ion: Theo e ical analysis based
on game heo y and empi ical e idence om China. In e na ional Re iew o Economics
& Finance, 89, 760–774. h ps://doi.o g/10.1016/j.i e .2023.07.046
Ba ge-Gil, A. (2013). Open S a egies and Inno a ion Pe o mance. Indus y & Inno a ion,
20(7), 585–610. h ps://doi.o g/10.1080/13662716.2013.849455
Ba elsman, E. J., Falk, M., Hags en, E., & Polde , M. (2019). P oduc i i y, echnological
inno a ions and b oadband connec i i y: Fi m-le el e idence o en Eu opean
coun ies. Eu asian Business Re iew, 9(1), 25–48. h ps://doi.o g/10.1007/s40821-
018-0113-0
Biscione, A., Ca uso, R., & de Felice, A. (2021). En i onmen al inno a ion in Eu opean
ansi ion coun ies. Applied Economics, 53(5), 521–535. h ps://doi.o g/10.1080/
00036846.2020.1808185
B and˜
ao San ana, N., Rebela o, D. A. D. N., P´
e ico, A. E., Mo alles, H. F., & Leal Filho, W.
(2015). Technological inno a ion o sus ainable de elopmen : An analysis o
di e en ypes o impac s o coun ies in he BRICS and G7 g oups. In e na ional
Jou nal o Sus ainable De elopmen & Wo ld Ecology, 22(5), 425–436. h ps://doi.o g/
10.1080/13504509.2015.1069766
B eie , M., Kallmuenze , A., Clauss, T., Gas , J., K aus, S., & Tibe ius, V. (2021). The ole
o business model inno a ion in he hospi ali y indus y du ing he COVID-19 c isis.
In e na ional Jou nal o Hospi ali y Managemen , 92, 102723. h ps://doi.o g/
10.1016/j.ijhm.2020.102723
Calab ese, G. G., Fala igna, G., & Ippoli i, R. (2024). Inno a ion policy and co po a e
inance: The I alian au omo i e supply chain and i s ansi ion o Indus y 4.0.
Jou nal o Policy Modeling, 46(2), 336–353. h ps://doi.o g/10.1016/j.
jpolmod.2024.01.007
Chan, F. T. S., Nayak, A., Raj, R., Chong, A. Y.-L., & Manoj, T. (2014). An inno a i e
supply chain pe o mance measu emen sys em inco po a ing Resea ch and
De elopmen (R&D) and ma ke ing policy. Compu e s & Indus ial Enginee ing, 69,
64–70. h ps://doi.o g/10.1016/j.cie.2013.12.015
Cha zoglou, P., & Cha zoudes, D. (2018). The ole o inno a ion in building compe i i e
ad an ages: An empi ical in es iga ion. Eu opean Jou nal o Inno a ion Managemen ,
21(1), 44–69. h ps://doi.o g/10.1108/EJIM-02-2017-0015
Chen, S., Feng, Y., Lin, C., Liao, Z., & Mei, X. (2021). Resea ch on he Technology
Inno a ion E iciency o China’s Lis ed New Ene gy Vehicle En e p ises.
Ma hema ical P oblems in Enginee ing, 2021, 1–9. h ps://doi.o g/10.1155/2021/
6613602
Chen, X., & Zhao, S. (2012). Resea ch on he e alua ion model o Chinese en e p ises’
echnological inno a ion sys em. Chinese Managemen S udies, 6(1), 65–77. h ps://
doi.o g/10.1108/17506141211213735
Cheng, C. C. J., & Huizingh, E. K. R. E. (2014). When Is Open Inno a ion Bene icial? The
Role o S a egic O ien a ion. Jou nal o P oduc Inno a ion Managemen , 31(6),
1235–1253. h ps://doi.o g/10.1111/jpim.12148
Cheng, J., Wang, M., Wu, L., & Li, X. (2024). Assessing he high-quali y de elopmen
s a egy o mine al esou ce en e p ises. Chinese Managemen S udies, 18(3),
802–817. h ps://doi.o g/10.1108/CMS-10-2022-0366
Chesb ough, H. (2003). The Logic o Open Inno a ion. Cali o nia Managemen Re iew, 45
(3), 33–58. h ps://doi.o g/10.1177/000812560304500301
Chupina, Z., Chu sin, A., Boginsky, A., & K aso , I. (2023). Sus ainable Economic
De elopmen o En e p ises: A Me hodology Based on he Toolki . Sus ainabili y, 15,
12682. h ps://doi.o g/10.3390/su151712682
Ciampi, F., Demi, S., Mag ini, A., Ma zi, G., & Papa, A. (2021). Explo ing he impac o
big da a analy ics capabili ies on business model inno a ion: The media ing ole o
en ep eneu ial o ien a ion. Jou nal o Business Resea ch, 123, 1–13. h ps://doi.o g/
10.1016/j.jbus es.2020.09.023
Ci e a, X., & Muzi, S. (2020). Measu ing inno a ion using i m-le el su eys: E idence
om de eloping coun ies✰. Resea ch Policy, 49(3), A icle 103912. h ps://doi.o g/
10.1016/j. espol.2019.103912
Clauss, T. (2017). Measu ing business model inno a ion: Concep ualiza ion, scale
de elopmen , and p oo o pe o mance. R&D Managemen , 47(3), 385–403. h ps://
doi.o g/10.1111/ adm.12186
Chen, J., Li, Q., Zhang, P., & Wang, X. (2024). Does Technological Inno a ion E iciency
Imp o e he G ow h o New Ene gy En e p ises? E idence om Lis ed Companies in
China. Sus ainabili y, 16(4), 1573. h ps://doi.o g/10.3390/su16041573
Bouwman, H., Nikou, S., & de Reu e , M. (2019). Digi aliza ion, business models, and
SMEs: How do business model inno a ion p ac ices imp o e pe o mance o
digi alizing SMEs? Telecommunica ions Policy, 43(9), 101828. h ps://doi.o g/
10.1016/j. elpol.2019.101828
Bellan uono, N., Pon andol o, P., & Scozzi, B. (2021). Measu ing he Openness o
Inno a ion. Sus ainabili y, 13(4), 2205. h ps://doi.o g/10.3390/su13042205
A i , M., Hasan, M., Sha ique Joyo, A., Gan, C., & Abidin, S. (2020). Fo mal Finance
Usage and Inno a i e SMEs: E idence om ASEAN Coun ies. Jou nal o Risk and
Financial Managemen , 13(10), 222. h ps://doi.o g/10.3390/j m13100222
Chesb ough, H., & Boge s, M. (2014). Explica ing Open Inno a ion: Cla i ying an
Eme ging Pa adigm o Unde s anding Inno a ion. In H. Chesb ough,
W.. Vanha e beke, & J. Wes (Eds.), Open Inno a ion: New F on ie s and
Applica ionsOpen Inno a ion: New F on ie s and Applica ions (pp. 3–28). Ox o d:
Ox o d Uni e si y P ess.
Co ona-T e i˜
no, L. (2023). Public se ice inno a ion o igh co up ion: Me ics and
policy in Mexico 2019–2022. Jou nal o Inno a ion and En ep eneu ship, 12(1), 1–19.
h ps://doi.o g/10.1186/s13731-023-00347-3
Cos a, J., Ne es, A. R., & Reis, J. (2021). Two Sides o he Same Coin. Uni e si y-Indus y
Collabo a ion and Open Inno a ion as Enhance s o Fi m Pe o mance. Sus ainabili y,
13(7), 3866. h ps://doi.o g/10.3390/su13073866
C uz-C´
aza es, C., Bayona-S´
aez, C., & Ga cía-Ma co, T. (2013). You can’ manage igh
wha you can’ measu e well: Technological inno a ion e iciency. Resea ch Policy,
42(6–7), 1239–1250. h ps://doi.o g/10.1016/j. espol.2013.03.012
Damanpou , F. (2014). Foo no es o Resea ch on Managemen Inno a ion. O ganiza ion
S udies, 35(9), 1265–1285. h ps://doi.o g/10.1177/0170840614539312
Dang, C. N., Wipulanusa , W., Nuaklong, P., & Wi chayangkoon, B. (2024). Assessing
g een inno a ion p ac ices in cons uc ion i ms: A de eloping-coun y pe spec i e.
Enginee ing, Cons uc ion and A chi ec u al Managemen . h ps://doi.o g/10.1108/
ECAM-08-2023-0788. ahead-o -p in .
Elmawazini, K., Chki , I., M ad, F., & Rjiba, H. (2022). Does g een echnology inno a ion
ma e o he cos o equi y capi al? Resea ch in In e na ional Business and Finance, 62,
101735. h ps://doi.o g/10.1016/j. iba .2022.101735
E angelis a, R., Iamma ino, S., Mas os e ano, V., & Sil ani, A. (2001). Measu ing he
egional dimension o inno a ion. Lessons om he I alian Inno a ion Su ey.
Techno a ion, 21(11), 733–745. h ps://doi.o g/10.1016/S0166-4972(00)00084-5
Foss, N. J., & Saebi, T. (2017). Fi een Yea s o Resea ch on Business Model Inno a ion.
Jou nal o Managemen , 43(1), 200–227. h ps://doi.o g/10.1177/
0149206316675927
Galindo, M.-´
A., & M´
endez, M. T. (2014). En ep eneu ship, economic g ow h, and
inno a ion: A e eedback e ec s a wo k? Jou nal o Business Resea ch, 67(5),
825–829. h ps://doi.o g/10.1016/j.jbus es.2013.11.052
Ga cía-G ane o, E. M., Pied a-Mu˜
noz, L., & Galdeano-G´
omez, E. (2018). Eco-inno a ion
measu emen : A e iew o i m pe o mance indica o s. Jou nal o Cleane
P oduc ion, 191, 304–317. h ps://doi.o g/10.1016/j.jclep o.2018.04.215
Ga cía-G ane o, E. M., Pied a-Mu˜
noz, L., & Galdeano-G´
omez, E. (2020). Measu ing eco-
inno a ion dimensions: The ole o en i onmen al co po a e cul u e and comme cial
o ien a ion. Resea ch Policy, 49(8), 104028. h ps://doi.o g/10.1016/j.
espol.2020.104028
Ga cía-Pozo, A., S´
anchez-Olle o, J. L., & Ons-Cappa, M. (2018). Impac o in oducing
eco-inno a ion measu es on p oduc i i y in anspo sec o companies. In e na ional
Jou nal o Sus ainable T anspo a ion, 12(8), 561–571. h ps://doi.o g/10.1080/
15568318.2017.1414340
Geldes, C., Felzensz ein, C., & Palacios-Fenech, J. (2017). Technological and non-
echnological inno a ions, pe o mance and p opensi y o inno a e ac oss indus ies:
The case o an eme ging economy. Indus ial Ma ke ing Managemen , 61, 55–66.
h ps://doi.o g/10.1016/j.indma man.2016.10.010
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
16
Ghise i, C., & Pon oni, F. (2015). In es iga ing policy and R&D e ec s on en i onmen al
inno a ion: A me a-analysis. Ecological Economics, 118, 57–66. h ps://doi.o g/
10.1016/j.ecolecon.2015.07.009
Ghosh, S., & S i as a a, B. K. (2022). The unc ioning o dynamic capabili ies: Explaining
he ole o o ganiza ional inno a i eness and cul u e. Eu opean Jou nal o Inno a ion
Managemen , 25(4), 948–974. h ps://doi.o g/10.1108/EJIM-06-2020-0241
Gio opoulos, I., Kon olaimou, A., Ko a, E., & Tsakanikas, A. (2017). Wha d i es ICT
adop ion by SMEs? E idence om a la ge-scale su ey in G eece. Jou nal o Business
Resea ch, 81, 60–69. h ps://doi.o g/10.1016/j.jbus es.2017.08.007
Go in, K., & Mi chell, R. (2010). Inno a ion Managemen : S a egy and Implemen a ion
Using he Pen a hlon F amewo k (2nd Edi ion). Basings oke: Palg a e Macmillan.
h ps://doi.o g/10.1007/978-1-137-04752-6
Go sch, M., & Hipp, C. (2012). Measu emen o inno a ion ac i i ies in he knowledge-
in ensi e se ices indus y: A adema k app oach. The Se ice Indus ies Jou nal, 32
(13), 2167–2184. h ps://doi.o g/10.1080/02642069.2011.574275
Gu, W., Saa y, T. L., & Wei, L. (2018). E alua ing and Op imizing Technological
Inno a ion E iciency o Indus ial En e p ises Based on Bo h Da a and Judgmen s.
In e na ional Jou nal o In o ma ion Technology & Decision Making, 17(01), 9–43.
h ps://doi.o g/10.1142/S0219622017500390
Hagedoo n, J., & Clood , M. (2003). Measu ing inno a i e pe o mance: Is he e an
ad an age in using mul iple indica o s? Resea ch Policy, 32(8), 1365–1379. h ps://
doi.o g/10.1016/S0048-7333(02)00137-3
Hassi, A. (2019). Empowe ing leade ship and managemen inno a ion in he hospi ali y
indus y con ex . In e na ional Jou nal o Con empo a y Hospi ali y Managemen , 31
(4), 1785–1800. h ps://doi.o g/10.1108/IJCHM-01-2018-0003
Henao-Ga cía, E. A., & Ca dona Mon oya, R. A. (2023). Managemen inno a ion and i s
ela ion o inno a ion ou comes and i m pe o mance: A sys ema ic li e a u e
e iew and u u e esea ch agenda. Eu opean Jou nal o Inno a ion Managemen ,
ahead-o -p in . h ps://doi.o g/10.1108/EJIM-10-2022-0564
H´
e oux-Vaillancou , M., Beaud y, C., & Rie sch, C. (2020). Using web con en analysis
o c ea e inno a ion indica o s—Wha do we eally measu e? Quan i a i e Science
S udies, 1(4), 1601–1637. h ps://doi.o g/10.1162/qss_a_00086
Heyden, M. L. M., Sidhu, J. S., & Volbe da, H. W. (2018). The Conjoin In luence o Top
and Middle Managemen Cha ac e is ics on Managemen Inno a ion. Jou nal o
Managemen , 44(4), 1505–1529. h ps://doi.o g/10.1177/0149206315614373
Hock-Doepgen, M., Clauss, T., K aus, S., & Cheng, C.-F. (2021). Knowledge managemen
capabili ies and o ganiza ional isk- aking o business model inno a ion in SMEs.
Jou nal o Business Resea ch, 130, 683–697. h ps://doi.o g/10.1016/j.
jbus es.2019.12.001
Hong, S., Oxley, L., & McCann, P. (2012). A su ey o he inno a ion su eys. Jou nal o
economic su eys, 26(3), 420–444. h ps://doi.o g/10.1111/j.1467-
6419.2012.00724.x
Huang, P.-Y., Wu, T.-S., Chen, L.-J., Sai o, R., Yu, C.-L., Huang, C.-Y., e al. (2015). An
empi ical esea ch on managemen inno a ion o high- echnology manu ac u e s.
Ad ances in Mechanical Enginee ing, 7(7). h ps://doi.o g/10.1177/
1687814015593679
Hussen, M. S., & Çokgezen, M. (2020). Analysis o Fac o s A ec ing Fi m Inno a ion: An
Empi ical In es iga ion o E hiopian Fi ms. Jou nal o A ican Business, 21(2),
169–192. h ps://doi.o g/10.1080/15228916.2019.1625020
Iandolo, S., & Fe agina, A. (2021). In e na ional ac i i ies and inno a ion: E idence
om I aly wi h a special eg esso app oach. The Wo ld Economy, 44(11),
3300–3325. h ps://doi.o g/10.1111/ wec.13153
Idd is, F. (2016). Measu emen o inno a ion capabili y in supply chain: An explo a o y
s udy. In e na ional Jou nal o Inno a ion Science, 8(4), 331–349. h ps://doi.o g/
10.1108/IJIS-07-2016-0015
Janssen, M. J., Cas aldi, C., & Alexie , A. (2016). Dynamic capabili ies o se ice
inno a ion: Concep ualiza ion and measu emen . R&D Managemen , 46(4), 797–811.
h ps://doi.o g/10.1111/ adm.12147
Jiang, T., Ji, P., Shi, Y., Ye, Z., & Jin, Q. (2021). E iciency assessmen o g een
echnology inno a ion o enewable ene gy en e p ises in China: A dynamic da a
en elopmen analysis conside ing undesi able ou pu . Clean Technologies and
En i onmen al Policy, 23(5), 1509–1519. h ps://doi.o g/10.1007/s10098-021-
02044-9
Jong, J. P. J., B uins, A., Dol sma, W., & Meijaa d, J. (2003). Inno a ion in Se ice Fi ms
Explo ed: Wha , How and Why? S a egic S udy B, 2003.
Kie e , C. P., Ca illo-He mosilla, J., Del Río, P., & Calleal a Ba oso, F. J. (2017).
Di e si y o eco-inno a ions: A quan i a i e app oach. Jou nal o Cleane P oduc ion,
166, 1494–1506. h ps://doi.o g/10.1016/j.jclep o.2017.07.241
Kinne, J., & Lenz, D. (2021). P edic ing inno a i e i ms using web mining and deep
lea ning. PLOS ONE, 16(4), A icle e0249071. h ps://doi.o g/10.1371/jou nal.
pone.0249071
Ki sios, F. C., & G igo oudis, E. (2020). E alua ing se ice inno a ion and business
pe o mance in ou ism: A mul ic i e ia decision analysis app oach. Managemen
Decision, 58(11), 2429–2453. h ps://doi.o g/10.1108/MD-09-2019-1326
Ko, H., & Lu, H. (2010). Measu ing inno a ion compe encies o in eg a ed se ices in
he communica ions indus y. Jou nal o Se ice Managemen , 21(2), 162–190.
h ps://doi.o g/10.1108/09564231011039277
Lee, C.-J., & You, Y.-Y. (2016). E ec s o Co po a e Technological Inno a ion Ac i i ies
on Technological and Managemen Pe o mance - Focusing on Go e nmen
Suppo ed Con e gence Consul ing. Indian Jou nal o Science and Technology, 9(41).
h ps://doi.o g/10.17485/ijs /2016/ 9i41/103851
Lee, H., & Lee, K. (2021). The E ec s o Technology Inno a ion Ac i i y on CSR:
Emphasizing he Nonlinea and He e ogenous E ec s. Sus ainabili y, 13(19), 10893.
h ps://doi.o g/10.3390/su131910893
Lee, S. M., Lee, D., & Schniede jans, M. J. (2011). Supply chain inno a ion and
o ganiza ional pe o mance in he heal hca e indus y. In e na ional Jou nal o
Ope a ions & P oduc ion Managemen , 31(11), 1193–1214. h ps://doi.o g/10.1108/
01443571111178493
Lesko a -Spacapan, G., & Bas ic, M. (2007). Di e ences in o ganiza ions’ inno a ion
capabili y in ansi ion economy: In e nal aspec o he o ganiza ions’ s a egic
o ien a ion. Techno a ion, 27(9), 533–546. h ps://doi.o g/10.1016/j.
echno a ion.2007.05.012
Li, D., & Shen, W. (2022). Regional Happiness and Co po a e G een Inno a ion: A
Financing Cons ain s Pe spec i e. Sus ainabili y, 14(4), 2263. h ps://doi.o g/
10.3390/su14042263
Li, S., Li, X., Zhao, Q., Zhang, J., & Xue, H. (2022). An Analysis o he Dimensional
Cons uc s o G een Inno a ion in Manu ac u ing En e p ises: Scale De elopmen
and Empi ical Tes ing. Sus ainabili y, 14(24), 16919. h ps://doi.o g/10.3390/
su142416919
Li, T., Qi, E., & Huang, Y. (2014). G ey clus e ing e alua ion based on iangula
whi eniza ion weigh unc ion o en e p ise’s managemen inno a ion pe o mance.
G ey Sys ems: Theo y and Applica ion, 4(3), 436–446. h ps://doi.o g/10.1108/GS-
05-2014-0017
Li, X., & Yang, Y. (2022). Does G een Finance Con ibu e o Co po a e Technological
Inno a ion? The Mode a ing Role o Co po a e Social Responsibili y. Sus ainabili y,
14(9), 5648. h ps://doi.o g/10.3390/su14095648
Lima Rua, O., Musiello-Ne o, F., & A ias-Oli a, M. (2023). Linking open inno a ion and
compe i i e ad an age: The oles o co po a e isk managemen and o ganisa ional
s a egy. Bal ic Jou nal o Managemen , 18(1), 104–121. h ps://doi.o g/10.1108/
BJM-08-2021-0309
Lin, Y.-C., Chen, C.-L., Chao, C.-F., Chen, W.-H., & Pandia, H. (2020). The S udy o
E alua ion Index o G ow h E alua ion o Science and Technological Inno a ion
Mic o-En e p ises. Sus ainabili y, 12(15), 6233. h ps://doi.o g/10.3390/
su12156233
Liu, L., Cui, L., Han, Q., & Zhang, C. (2024). The impac o digi al capabili ies and
dynamic capabili ies on business model inno a ion: The mode a ing e ec o
o ganiza ional ine ia. Humani ies and Social Sciences Communica ions, 11(1), 10.
h ps://doi.o g/10.1057/s41599-024-02910-z
Lu, Q., & Chesb ough, H. (2022). Measu ing open inno a ion p ac ices h ough opic
modelling: Re isi ing hei impac on i m inancial pe o mance. Techno a ion, 114,
102434. h ps://doi.o g/10.1016/j. echno a ion.2021.102434
Lugo oi, I., And i sos, D. A., & Seno , C. (2022). No el y and scope o p ocess inno a ion:
The ole o ela ed and un ela ed manu ac u ing expe ience. P oduc ion and
Ope a ions Managemen , 31(10), 3877–3895. h ps://doi.o g/10.1111/poms.13793
Maldonado-Guzm´
an, G., Ga za-Reyes, J. A., & Pinz´
on-Cas o, Y. (2020). Eco-inno a ion
and he ci cula economy in he au omo i e indus y. Benchma king: An In e na ional
Jou nal, 28(2), 621–635. h ps://doi.o g/10.1108/BIJ-06-2020-0317
Manoha , S., Mi al, A., & Tandon, U. (2021). HEd-INNOSERV: Pe cei ed se ice
inno a ion scale o he highe educa ion sec o . Benchma king: An In e na ional
Jou nal, 28(3), 957–989. h ps://doi.o g/10.1108/BIJ-08-2020-0415
Manoha , S., Paul, J., S ong, C., & Mi al, A. (2023). INNOSERV: Gene alized scale o
pe cei ed se ice inno a ion. Jou nal o Business Resea ch, 160, 113723. h ps://doi.
o g/10.1016/j.jbus es.2023.113723
Ma ín-Vinuesa, L. M., Sca pellini, S., Po illo-Ta agona, P., & Mone a, J. M. (2020). The
Impac o Eco-Inno a ion on Pe o mance Th ough he Measu emen o Financial
Resou ces and G een Pa en s. O ganiza ion & En i onmen , 33(2), 285–310. h ps://
doi.o g/10.1177/1086026618819103
Ma ko ic, S., & Baghe zadeh, M. (2018). How does b ead h o ex e nal s akeholde co-
c ea ion in luence inno a ion pe o mance? Analyzing he media ing oles o
knowledge sha ing and p oduc inno a ion. Jou nal o Business Resea ch, 88,
173–186. h ps://doi.o g/10.1016/j.jbus es.2018.03.028
Ma ínez-Alonso, R., Ma ínez-Rome o, M. J., & Rojo Ramí ez, A. (2020). The impac o
echnological inno a ion e iciency on i m g ow h: The mode a ing ole o amily
in ol emen in managemen . Eu opean Jou nal o Inno a ion Managemen , 23,
134–155. h ps://doi.o g/10.1108/EJIM-09-2018-0210
Ma ullo, C., Ahn, J. M., Ma elli, I., & Di Minin, A. (2022). Open o inno a ion: An
imp o ed measu emen app oach using i em esponse heo y. Techno a ion, 109,
102338. h ps://doi.o g/10.1016/j. echno a ion.2021.102338
Ma Dahan, S., & Yuso , S. M. (2020). Re iew and p oposed eco-p ocess inno a ion
pe o mance amewo k. In e na ional Jou nal o Sus ainable Enginee ing, 13(2),
123–139. h ps://doi.o g/10.1080/19397038.2019.1644387
Mülle , J. M., Buliga, O., & Voig , K.-I. (2018). Fo une a o s he p epa ed: How SMEs
app oach business model inno a ions in Indus y 4.0. Technological Fo ecas ing and
Social Change, 132, 2–17. h ps://doi.o g/10.1016/j. ech o e.2017.12.019
Munodawa a, R. T., & Johl, S. K. (2022). Measu emen de elopmen o eco-inno a ion
capabili ies o Malaysian oil and gas i ms. In e na ional Jou nal o P oduc i i y and
Pe o mance Managemen , 71(8), 3443–3465. h ps://doi.o g/10.1108/IJPPM-07-
2020-0404
Niyawanon , N. (2023). The in luence o s a -up en ep eneu ship and dis up i e
business model on i m pe o mance. En ep eneu ial Business and Economics Re iew,
11(1), 57–76. h ps://doi.o g/10.15678/EBER.2023.110103
Ojha, D., Shockley, J., & Acha ya, C. (2016). Supply chain o ganiza ional in as uc u e
o p omo ing en ep eneu ial emphasis and inno a i eness: The ole o us and
lea ning. In e na ional Jou nal o P oduc ion Economics, 179, 212–227. h ps://doi.
o g/10.1016/j.ijpe.2016.06.011
Michelino, F., Lambe i, E., Camma ano, A., & Capu o, M. (2015). Open Inno a ion in
he Pha maceu ical Indus y: An Empi ical Analysis on Con ex Fea u es, In e nal
R&D, and Financial Pe o mances. IEEE T ansac ions on Enginee ing Managemen , 62
(3), 421–435. h ps://doi.o g/10.1109/TEM.2015.2437076
Michelino, F., Camma ano, A., Lambe i, E., & Capu o, M. (2014). Measu emen o open
inno a ion h ough in ellec ual capi al lows: F amewo k and applica ion.
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
17
In e na ional Jou nal o In elligen En e p ise, 2(2/3), 213-235. doi:10.1504/IJIE.20
14.066679.
Oslo Manual 2018. (2018). OECD. h ps://doi.o g/10.1787/9789264304604-en.
Oudgou, M. (2021). Financial and Non-Financial Obs acles o Inno a ion: Empi ical
E idence a he Fi m Le el in he MENA Region. Jou nal o Open Inno a ion:
Technology, Ma ke , and Complexi y, 7(1), 28. h ps://doi.o g/10.3390/
joi mc7010028
Page, M. J., McKenzie, J. E., Bossuy , P. M., Bou on, I., Ho mann, T. C., Mul ow, C. D.,
e al. (2021). The PRISMA 2020 s a emen : An upda ed guideline o epo ing
sys ema ic e iews. BMJ (Clinical esea ch ed.), n71. h ps://doi.o g/10.1136/bmj.
n71
Pålsson, H., & Hells ¨
om, D. (2023). Packaging inno a ion sco eca d. Packaging
Technology and Science, 36(11), 969–981. h ps://doi.o g/10.1002/p s.2769
Pan iluk, E., & Szyma´
nska, E. (2017). The measu emen o he inno a i eness o heal h
ou ism se ices using an adequacy ma ix i le o he a icle. En ep eneu ship and
Sus ainabili y Issues, 4(4), 400–420. h ps://doi.o g/10.9770/jesi.2017.4.4(1)
Raj, R., & S i as a a, K. B. L. (2016). Media ing ole o o ganiza ional lea ning on he
ela ionship be ween ma ke o ien a ion and inno a i eness. The Lea ning
O ganiza ion, 23(5), 370–384. h ps://doi.o g/10.1108/TLO-09-2013-0051
Ramme , C., & Es-Sadki, N. (2022). Using Big Da a o Gene a ing Fi m-Le el Inno a ion
Indica o s – A Li e a u e Re iew. SSRN Elec onic Jou nal. h ps://doi.o g/10.2139/
ss n.4072590
Ren´
e Win jes, H.H. (2019). P omo ing Inno a ion, Capabili ies and Impac o SMEs in
T adi ional Indus ies Calls o Va ie y in Inno a ion Suppo . In L’indus ia, i is a di
economia e poli ica indus iale.
Rashid, N., Jaba , J., Yahya, S., & Shami, S. (2014). Dynamic Eco Inno a ion P ac ices: A
Sys ema ic Re iew o S a e o he A and Fu u e Di ec ion o Eco Inno a ion S udy.
Asian Social Science, 11(1), 8–21. h ps://doi.o g/10.5539/ass. 11n1p8
Rou inen, P. (2002). Cha ac e is ics o p oduc and p ocess inno a o s: Some e idence
om he Finnish inno a ion su ey. Applied Economics Le e s, 9(9), 575–580.
h ps://doi.o g/10.1080/13504850110108102
Salaza , M., & Holb ook, A. (2004). A deba e on inno a ion su eys. Science and public
policy, 31(4), 254–266. h ps://doi.o g/10.3152/147154304781779976
Shi i, G., Sau ´
ee, L., & Abdi ahman, Z.-Z. (2015). B idge and edundan ies in ne wo ks:
The impac on inno a ion in ood SMEs. Eu opean Jou nal o Inno a ion Managemen ,
18(3), 355–379. h ps://doi.o g/10.1108/EJIM-04-2014-0049
Spie h, P., & Schneide , S. (2016). Business model inno a i eness: Designing a o ma i e
measu e o business model inno a ion. Jou nal o Business Economics, 86(6),
671–696. h ps://doi.o g/10.1007/s11573-015-0794-0
Su, Y., Chai, J., Lu, S., & Lin, Z. (2024). E alua ing G een Technology Inno a ion
Capabili y in In elligen Manu ac u ing En e p ises: A $Z$-Numbe -Based Model.
IEEE T ansac ions on Enginee ing Managemen , 71, 5391–5409. h ps://doi.o g/
10.1109/TEM.2024.3350357
Ve bano, C., & C ema, M. (2016). Linking echnology inno a ion s a egy, in ellec ual
capi al and echnology inno a ion pe o mance in manu ac u ing SMEs. Technology
Analysis & S a egic Managemen , 28(5), 524–540. h ps://doi.o g/10.1080/
09537325.2015.1117066
Walke , R. M., Chen, J., & A a ind, D. (2015). Managemen inno a ion and i m
pe o mance: An in eg a ion o esea ch indings. Eu opean Managemen Jou nal, 33
(5), 407–422. h ps://doi.o g/10.1016/j.emj.2015.07.001
Wang, C. (2022). G een Technology Inno a ion, Ene gy Consump ion S uc u e and
Sus ainable Imp o emen o En e p ise Pe o mance. Sus ainabili y, 14(16), 10168.
h ps://doi.o g/10.3390/su141610168
Wong, D. T. W., & Ngai, E. W. T. (2022). Supply chain inno a ion: Concep ualiza ion,
ins umen de elopmen , and in luence on supply chain pe o mance. Jou nal o
P oduc Inno a ion Managemen , 39(2), 132–159. h ps://doi.o g/10.1111/
jpim.12612
Wu, T., & Liu, X. (2016). An in e al ype-2 uzzy ANP app oach o e alua e en e p ise
echnological inno a ion abili y. Kybe ne es, 45(9), 1486–1500. h ps://doi.o g/
10.1108/K-01-2016-0011
Yang, Y., Guo, L., Zhong, Z., & Zhang, M. (2018). Selec ion o Technological Inno a ion
o Se ice-O ien a ed En e p ises. Sus ainabili y, 10(11), 3906. h ps://doi.o g/
10.3390/su10113906
Yi, K., Zhang, L., Mao, X., Li, Y., & Bao, J. (2021). E alua ing Technological Inno a ion o
Media Companies om he Pe spec i e o Technological Ecosys em. Wi eless
Communica ions and Mobile Compu ing, 2021, 4170619. h ps://doi.o g/10.1155/
2021/4170619
Yildiz, B., Çi˘
gdem, S
¸., Meidu ˙
e-Ka aliauskien˙
e, I., & ˇ
Cinˇ
cikai ˙
e, R. (2024). The Nexus O
Big Da a Analy ics, Knowledge Sha ing, And P oduc Inno a ion In Manu ac u ing.
Jou nal o Business Economics and Managemen , 25(1), 66–84. h ps://doi.o g/
10.3846/jbem.2024.20713
Yin, S., Zhang, N., & Li, B. (2020). Enhancing he compe i i eness o mul i-agen
coope a ion o g een manu ac u ing in China: An empi ical s udy o he measu e o
g een echnology inno a ion capabili ies and hei in luencing ac o s. Sus ainable
P oduc ion and Consump ion, 23, 63–76. h ps://doi.o g/10.1016/j.spc.2020.05.003
Zhang, H. (2015). E iciency o he supply chain collabo a i e echnological inno a ion
in China: An empi ical s udy based on DEA analysis. Jou nal o Indus ial Enginee ing
and Managemen , 8(5), 1623–1638. h ps://doi.o g/10.3926/jiem.1507
Zhang, Q. (2022). A Big Da a-D i en App oach o Analyze he In luencing Fac o s o
En e p ise’s Technological Inno a ion. Compu a ional In elligence and Neu oscience,
2022, 3785685. h ps://doi.o g/10.1155/2022/3785685
Yang, X., Chi, R., & Yang, Z. (2010). Fuzzy Suppo Vec o Machine Me hod o
E alua ing Inno a ion Sou ces in Se ice Fi ms. Jou nal o Con e gence In o ma ion
Technology, 5(7), 187–196. h ps://doi.o g/10.4156/jci . ol5.issue7.25
A. S undziene e al.
Jou nal o Inno a ion & Knowledge 9 (2024) 100620
18