Al a ez-Salaza , Jubal Ra ael; Be nal-Pé ez, Ped o Ma ín
A icle
Quali a i e compa a i e analysis o he pe sonal ai s o
manage s, scien is s, and inno a o s in co po a e science
Jou nal o Inno a ion & Knowledge (JIK)
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: Al a ez-Salaza , Jubal Ra ael; Be nal-Pé ez, Ped o Ma ín (2025) : Quali a i e
compa a i e analysis o he pe sonal ai s o manage s, scien is s, and inno a o s in co po a e
science, Jou nal o Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 10, Iss.
1, pp. 1-14,
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Quali a i e compa a i e analysis o he pe sonal ai s o manage s,
scien is s, and inno a o s in co po a e science
Jubal Ra ael Al a ez-Salaza
*
, Ped o Ma ín Be nal-P´
e ez
Pon i ical Ca holic Uni e si y o Pe u, A enida Uni e si a ia 1801. San Miguel, Lima, Lima, 15088, Pe u
ARTICLE INFO
JEL:
L21
M12
O31
O32
Keywo ds:
Co po a e science
T ans o ma ional leade ship
Open inno a ion
Knowledge app op ia ion
sQCA
Eme ging economy
ABSTRACT
This s udy examined he pe sonal ai s ha con ibu e o he success o co po a e science p ojec s in Pe u by
ocusing on he oles o CEOs, scien is s, and inno a o s. Al hough Pe u has seen economic p og ess in ecen
decades, in eg a ing scien i ic esea ch in o business s a egies equi es imp o emen , e lec ing a common end
in eme ging economies. Th ough a uzzy se quali a i e compa a i e analysis ( sQCA) and a sample o 56 pa -
icipan s, he con igu a ions o pe sonal cha ac e is ics ha con ibu e o he success o such p ojec s we e
iden i ied. The esul s indica e ha success depends no on a single a ibu e bu on a combina ion o a ious
capabili ies. This s udy emphasizes he impo ance o adap abili y and collabo a ion among key ac o s and
sugges s a managemen app oach ha blends echnical skills wi h in e pe sonal compe encies. The p ac ical
implica ions o his s udy emphasize he need o align co po a e leade ship wi h scien i ic and ma ke dynamics,
os e empa hy and eamwo k, and le e age ex e nal ne wo ks o enhance inno a ion. S a egies mus be
adap ed o he speci ici ies o eme ging economies whe e science, echnology, and inno a ion sys ems a e s ill
de eloping.
In oduc ion
Co po a e science in ol es conduc ing scien i ic esea ch unded by
companies o gene a e knowledge ha acili a es he in oduc ion o
new p oduc s in o he ma ke o he implemen a ion o p ocesses ha
imp o e business e iciency (Zah a e al., 2018). Academic li e a u e has
poin ed ou ha success in hese p ojec s equi es he pa icipa ion o
en ep eneu s wi h a long- e m ision (Sime h & Cince a, 2016), sup-
po ed by scien is s who p io i ize p ac ical applica ion o e scien i ic
cu iosi y (A ms ong & G een, 2022) and inno a o s capable o
ex ac ing alue om exis ing knowledge (Moon & Acquaah, 2020).
Howe e , i is impo an o no e ha co po a e science is no jus abou
indi idual capabili ies. I also equi es a sui able en i onmen ha a-
o s i (Pisano, 2010). This unde sco es he complexi y o he ield and
he need o conside ex e nal ac o s ha can signi ican ly in luence he
success o co po a e scien i ic p ojec s.
In he con ex o co po a e science, CEOs, scien is s, and inno a o s
a e key ac o s who b ing dis inc i e, complemen a y compe encies o
each phase o he inno a ion p ocess. Th ough ans o ma ional lead-
e ship (Bass, 1999), CEOs c ea e an o ganiza ional en i onmen ha
aligns indi idual goals wi h hose o he o ganiza ion, acili a ing
echnology adop ion and s a egic decision-making in cons an ly
changing en i onmen s (Chen e al., 2014; Zu aik & Kelly, 2019). Sci-
en is s play a undamen al ole in gene a ing and ans e ing knowl-
edge, suppo ed by he concep o open inno a ion, which allows
knowledge o low wi hin and ou side an o ganiza ion, s eng hening
s a egic alliances ha op imize esul s (O onica e al., 2020; S´
a e al.,
2023). Finally, inno a o s, as ‘ ansla o s’ o science, acili a e he
ans o ma ion o scien i ic knowledge in o comme cial applica ions,
in eg a ing his knowledge in o he company and adap ing i o he
ma ke , in line wi h knowledge app op ia ion heo y (Boehm & Hogan,
2013; Hislop, 2003).
De eloped coun ies a o in es men in scien i ic esea ch o
main ain hei g ow h and compe i i eness (Alsebai e al., 2022).
Al hough Pe u expe ienced signi ican economic p og ess in he i s wo
decades o he 21s cen u y (Rod iguez e al., 2024), he in eg a ion o
scien i ic esea ch in o business ac i i ies is limi ed (Sagas i, 2021). This
is e lec ed in mul iple aspec s such as a signi ican gap in esea ch and
de elopmen (R&D) in es men (Tu po-Gebe a e al., 2021), limi ed
in e ac ion be ween academia and business (Bo da-Ri e a &
O ega-Pa edes, 2021), ine ec i e public policies o p omo e scien i ic
esea ch (Quispe e al., 2023), echnological dependence on companies
* Co esponding au ho .
E-mail add esses: [email p o ec ed] (J.R. Al a ez-Salaza ), [email p o ec ed] (P.M. Be nal-P´
e ez).
Con en s lis s a ailable a ScienceDi ec
Jou nal o Inno a ion & Knowledge
jou nal homepage: www.else ie .com/loca e/jik
h ps://doi.o g/10.1016/j.jik.2025.100652
Recei ed 7 Oc obe 2024; Accep ed 2 Janua y 2025
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
2
(Ricalde-Chahua & Libaque-Saenz, 2023), and esis ance o change and
adop ion o new echnologies by companies (Seclen-Luna &
Al a ez-Salaza , 2021). These aspec s, in addi ion o he p edominance
o ex ac i e indus ies, do no gene a e a a o able en i onmen o
co po a e science (Lus , 2016).
Howe e , some Pe u ian companies ha e success ully de eloped
co po a e science p ojec s. Fo example, s a ups such as Quan um
Talen and Labo a o ia inno a e in educa ion and aining in digi al
echnologies, he eby s eng hening human capi al in he coun y (IDB
Lab, 2021). Simila ly, es ablished companies such as AGP, a p oduce o
lamina ed glass wi h global each, in es in co po a e science p ojec s
and collabo a e wi h academic ins i u ions, bene i ing om public
p og ams (PRODUCE, 2021). In addi ion, 74 o he companies ha e
bene i ed om ax incen i es o esea ch, which has allowed hem o
implemen success ul co po a e science p ojec s in Pe u (CONCYTEC,
2022).
Despi e he li e a u e on co po a e science iden i ying a ious ac o s
ha acili a e he in eg a ion o scien i ic esea ch in o business, he e is
limi ed explo a ion in o how he speci ic pe sonal ai s o key co po a e
science ac o s—CEOs, scien is s, and inno a o s—con ibu e o success
in eme ging economies such as Pe u. This gap in he li e a u e mo i a ed
he p esen s udy, which add essed he ollowing esea ch ques ions:
•Wha pe sonal cha ac e is ics o CEOs, scien is s, and inno a o s
con ibu e o he success o co po a e science p ojec s in eme ging
economies, such as Pe u?
•How a e hese pe sonal cha ac e is ics con igu ed in di e en com-
bina ions o os e an en i onmen a o able o co po a e science in
con ex s wi h limi ed R&D in as uc u e and policy suppo ?
To answe his ques ion, a desc ip i e scoping s udy was conduc ed
(C eswell & C eswell, 2018) using a uzzy se quali a i e compa a i e
analysis ( sQCA) o iden i y he necessa y cha ac e is ics ha con ibu e
o p ojec success (Ragin, 2023). We wo ked wi h 56 scien is s and
manage s in ol ed in co po a e science p ojec s in Pe u. Using sQCA,
his s udy makes an inno a i e con ibu ion by examining he con igu-
a ions o pe sonal ai s in he con ex in which co po a e science
p ojec s ace unique challenges.
This s udy d aws on ans o ma ional leade ship heo y (Bass, 1999),
open inno a ion heo y (Chesb ough, 2003), and knowledge app op i-
a ion heo y (Nonaka, 1994). T ans o ma ional leade ship explains how
CEOs align indi idual and o ganiza ional in e es s, open inno a ion
highligh s in e nal and ex e nal collabo a ion wi h scien is s o co po-
a e science success, and knowledge app op ia ion desc ibes how in-
no a o s ans o m knowledge in o comme cial applica ions. By
p o iding empi ical e idence on how he speci ic pe sonal ai s o
CEOs, scien is s, and inno a o s in luence co po a e science success in
eme ging economies, his s udy o e s new heo e ical con ibu ions o
ans o ma ional leade ship, open inno a ion, and knowledge app o-
p ia ion heo ies unde condi ions o sys emic limi a ions.
Ou indings e eal ha co po a e science elies on adap abili y and
collabo a ion among key ac o s. The e is no single o mula o success
bu , a he , mul iple e ec i e combina ions o pe sonal cha ac e is ics.
Li e a u e e iew
Co po a e science
Co po a e science is a business s a egy ha seeks o gene a e sci-
en i ic knowledge o d i e business de elopmen o imp o e an o ga-
niza ion’s ope a ional e iciency (Zah a e al., 2018). Unlike science o
academic pu poses, co po a e science p io i izes p oduc i i y and eco-
nomic bene i gene a ion (Vi ale, 2017), ocusing on c ea ing alue o a
company and i s s akeholde s by applying knowledge o os e inno a-
ion (Bolí a -Ramos, 2023).
The co po a e science p ocess in eg a es manage ial decision-
making, he de ini ion o ope a ional ac i i ies, and he o maliza ion
o in e -o ganiza ional ag eemen s (Clay on e al., 2018). This p ocess is
di ided in o ou s ages: (i) in es men , in which esou ces a e alloca ed
and p ojec s a e selec ed; (ii) disco e y, in which esea ch ac i i ies a e
conduc ed; (iii) ans e , in which indings a e ans o med in o com-
me cial applica ions; and (i ) app op ia ion, in which ma ke able
p oduc s o p ocess imp o emen s a e gene a ed (Zah a e al., 2018).
The ou comes o co po a e science ange om knowledge gene a ion
and scien i ic publica ions (Yang e al., 2023) o he c ea ion o
ma ke able p oduc s (Zah a e al., 2018) h ough in e ac ions wi h
esea ch en i ies (Jong & Sla o a, 2014), echnology licensing (Yan
e al., 2023; K iege e al., 2024), and he adop ion o new echnologies
o educe cos s (Chen e al., 2024). These in e connec ed elemen s
maximize inno a ion and sus ainabili y, allowing hem o emain
compe i i e and adap able in cons an ly e ol ing ma ke s. Conse-
quen ly, a co po a e science p ojec is deemed success ul when i no
only gene a es o in eg a es scien i ic knowledge bu also ansla es ha
knowledge in o angible alue o he o ganiza ion.
To unde s and how he key ac o s in co po a e science con ibu e o
i s success, his s udy d aws on h ee undamen al heo ies: ans-
o ma ional leade ship (Bass, 1999), open inno a ion (Chesb ough,
2003), and knowledge app op ia ion (Nonaka, 1994). These heo ies
o e complemen a y pe spec i es on o ganiza ional leade ship,
esea ch collabo a ion, and he in eg a ion o knowledge in o com-
me cial applica ions, all o which a e essen ial o he co po a e science
p ocess.
Key ac o s in co po a e science
Th ee key playe s in co po a e science ha e been iden i ied: CEOs,
scien is s, and inno a o s. Each ac o b ings a dis inc heo e ical
pe spec i e ha de ines hei oles and con ibu ions o he p ocess.
Al a ez-Salaza and Be nal-P´
e ez (2023) iden i ied each ac o ’s main
cha ac e is ics.
T ans o ma ional leade ship and he CEO’s ole in co po a e science
T ans o ma ional leade ship heo y posi s ha leade s p omo e
o ganiza ional change by aligning he in e es s o o ganiza ional mem-
be s wi h b oade objec i es (Bass 1999). In doing so, hey c ea e a
conduci e en i onmen o co po a e science. This ype o leade ship
in luences he adop ion o new echnologies and p oduc inno a ion,
os e ing a mo e agile and adap able en i onmen ha enables com-
panies o e ec i ely ace echnological and compe i i e challenges (Y.
Chen e al., 2014; Zu aik & Kelly, 2019). The c ea i e dimension o
CEOs’ leade ship is c ucial o inno a ion e ec i eness in high- ech
i ms (Mak i & Scandu a 2010).
In he con ex o co po a e science, nine aspec s ha di e en ia e
CEOs in ol ed in co po a e science s and ou . Fi s , he CEO’s s a egic
ision allows scien i ic esea ch o align wi h co po a e s a egy, acili-
a ing adap a ion o en i onmen al changes. This ision, coupled wi h
leade ship skills, s eng hens companies’ esponsi eness and c ea es a
a o able posi ion o co po a e science by mo i a ing eams o exploi
new ideas and app oaches (F iedman e al., 2016). In addi ion, a CEO’s
abili y o an icipa e u u e ends con ibu es o o ganiza ional lexi-
bili y and esponsi eness (Su e al., 2023). Ano he essen ial aspec is
ma ke unde s anding, which enables i ms o make s a egic decisions
and explo e new oppo uni ies (Rao e al., 2024).
Commi men o co po a e science is ano he c ucial CEO a ibu e, as
i os e s an en i onmen conduci e o inno a ion by welcoming new
ideas om he eam (Rao e al., 2024). This commi men ansla es in o
a cul u e o inno a ion ha imp o es business pe o mance and he
abili y o adap o new challenges (Luo e al., 2024). In addi ion,
openness o new echnologies gi es companies a compe i i e ad an age
in echnological de elopmen (Rosie , 2022). Bes p ac ices indica e
ha CEOs commi ed o inno a ion inc ease hei in es men in esea ch
and suppo inno a i e ini ia i es (Loukil e al., 2020).
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
3
Knowledge o scien i ic p ocesses is also men ioned as an essen ial
CEO cha ac e is ic, as i os e s cu iosi y and a long- e m ision o he
company. CEOs wi h STEM backg ounds can be e e alua e and
manage eal op ions in esea ch p ojec s (Alde man e al., 2022),
esul ing in mo e ema kable o iginali y and alue o inno a ion (Song
e al., 2023).
Gene a ing p o essional ne wo ks is c i ical o he success o
co po a e science ini ia i es. CEOs who ac i ely pa icipa e in echnol-
ogy communi ies and s a -ups acili a e knowledge in eg a ion and
encou age in es men in esea ch (Faleye e al., 2014). Finally, CEOs’
en ep eneu ial capaci y complemen s hese cha ac e is ics, mani es ing
in hei abili y o iden i y oppo uni ies and gene a e new ideas. Ac-
co ding o Keil e al. (2017), he CEO’s en ep eneu ial o ien a ion can
inc ease i m alue, os e ing a cul u e o inno a ion and imp o ing
ma ke pe o mance (Luo e al., 2024).
In summa y, a CEO’s ans o ma ional leade ship and s a egic
ision no only c ea e a conduci e en i onmen o co po a e science
bu also lay he g oundwo k o o he key ac o s, such as scien is s, o
d i e knowledge gene a ion and collabo a ion wi hin he o ganiza ion.
Based on hese insigh s, we p opose he ollowing su iciency
hypo hesis:
H
1
: The combina ion o s a egic ision (s a V), commi men o
inno a ion (engage), knowledge o he scien i ic p ocess (sciP o),
p o essional ne wo ks (p oNe ), en ep eneu ial ai s (en eT), sci-
en i ic ocus (sciFoc), echnological expe ience ( echEx), sus ainable
mo i a ions (mo i ), and isk- aking abili y ( iskTk) in he CEO is
su icien o achie e success in co po a e science p ojec s.
This su iciency hypo hesis is sui able in his con ex because he
cha ac e is ics ou lined con ibu e o c ea ing a a o able en i onmen
o co po a e science success wi hou asse ing ha hese a e he only
cha ac e is ics ha could lead o such success.
Open inno a ion and he scien is ’s ole in co po a e science
The heo e ical implica ions o open inno a ion heo y highligh
how collabo a ion wi h in e nal and ex e nal scien is s acili a es com-
panies in gene a ing help ul knowledge o hei s a egies (O onica
e al., 2020). This low o knowledge, ci cula ing wi hin and ou side he
o ganiza ion, os e s he c ea ion o s a egic alliances ha enhance
co po a e science ou comes (S´
a e al., 2023). Resea ch on open inno-
a ion has shown ha in eg a ing scien is s in o he inno a ion p ocess
es ablishes a solid esea ch agenda ha op imizes he o ganiza ional
impac (Randhawa e al., 2016). Fu he mo e, inco po a ing scien is s
in o business s a egies allows companies o be e le e age ex e nal
knowledge, he eby inc easing hei compe i i eness and sus ainabili y
(Chesb ough & Appleya d, 2007).
The en i onmen os e ed by a CEO’s ans o ma ional leade ship
enables scien is s o wo k in a se ing ha alues collabo a ion and
knowledge gene a ion (Jiang & Chen 2018). This suppo i e en i on-
men is essen ial o scien is s o con ibu e e ec i ely o co po a e
science success h ough open inno a ion, whe e he low o in e nal and
ex e nal knowledge is ha nessed o he o ganiza ion’s bene i (Huang
e al., 2022).
In his con ex , co po a e scien is s possess i al cha ac e is ics o a
disco e y p ocess ha is o ien ed owa d business goals. Fi s , hei
alignmen wi h o ganiza ional objec i es d i es scien i ic p oduc i i y.
Fo example, co po a e models ha e been le e aged in he biomedical
ield o os e eamwo k (Valan ine e al., 2014). Business s a egy mus
align wi h co po a e science o o e come challenges and maximize
comme cializa ion bene i s (Zah a e al., 2018). This alignmen en-
hances business inno a ion and sus ainabili y, ein o cing he posi i e
impac o co po a e science on o ganiza ional de elopmen .
Second, co po a e scien is s seek a balance be ween a p ojec ’s sho -
and long- e m goals, he eby con ibu ing o he success o co po a e
science (Wasowicz, 2021). This balance p omo es sho - e m alue
c ea ion and long- e m sus ainable o ganiza ional g ow h and
inno a ion.
The hi d ele an cha ac e is ic is scien is s’ abili y o seek p ac ical
applica ions ha ansla e esea ch esul s in o success ul p oduc s,
p ocesses, and se ices, he eby con ibu ing o business inno a ion
(He e a, 2020). Scien is s mus apply undamen al business s a egy
concep s, de ine alue p oposi ions, and es ablish s a egic collabo a-
ions (Nguyen & Nguyen, 2020).
Finally, co po a e scien is s mus balance he cos and e iciency o
co po a e science p ojec s. This is achie ed by assessing he p o i abili y
and easibili y o p ojec s using pe o mance indica o s and isk
assessmen me hods such as discoun ed cash lows, Mon e Ca lo simu-
la ions, and decision ee analysis (Se iko e al., 2020).
Based on hese insigh s om open inno a ion heo y, we p opose he
ollowing su iciency hypo hesis:
H
2
: The combina ion o o ganiza ional alignmen (o gAln), special-
iza ion (specia), managemen skills (manSci), and empo al
balancing capaci y (dualTe) in scien is s is su icien o con ibu e o
he success o co po a e science p ojec s.
Scien is s’ con ibu ions es ablish a obus ounda ion o knowledge
wi hin he o ganiza ion, p o iding he g oundwo k ha inno a o s
le e age o ans o m disco e ies in o ma ke able applica ions and
comme cial success.
Knowledge app op ia ion and he inno a o ’s ole in co po a e science
Knowledge app op ia ion heo y explains how inno a o s ans o m
knowledge in o inno a ion. Collabo a ions be ween science and busi-
ness allow inno a o s o app op ia e and apply his knowledge in a
company (Boehm & Hogan, 2013). Fu he mo e, app op ia ion is no
only an indi idual p ocess bu also equi es social in eg a ion wi hin he
o ganiza ion o os e inno a ion (Rome o-Rod íguez e al., 2020). This
in eg a ion p ocess acili a es he gene a ion o new ideas based on
science, ans o ming hem in o comme cial applica ions ha d i e
o ganiza ional g ow h (Hislop, 2003; Wang & Chen, 2010).
The ole o inno a o s in ansla ing scien i ic knowledge in o com-
me cial applica ions aligns wi h he s a egic isions es ablished by he
CEO (Teece, 2006). This alignmen allows inno a o s o ailo hei e -
o s o o ganiza ional p io i ies and p omo e inno a ion in p oduc s
and se ices ha e lec he g ow h and compe i i eness goals ou lined
by o ganiza ional leade ship (Hensmans, 2022).
In his con ex , inno a o s can be dis inguished on he basis o se en
key cha ac e is ics. The i s is hei abili y o coo dina e wi h scien is s,
elying on s uc u ed and uns uc u ed s a egies ha acili a e he
in eg a ion o he knowledge and skills needed o inno a ion (Isae a
e al., 2024).
Ano he salien ea u e is empa hy and alignmen wi h scien is s,
which s eng hen collabo a ion. Empa hy imp o es he unde s anding
and connec ion be ween eam membe s and posi i ely con ibu es o
pe o mance (Keus e s e al., 2024). Alignmen ensu es ha wo k ob-
jec i es and me hods a e synch onized and mee challenges cohe en ly
(Keus e s e al., 2024).
In addi ion, inno a o s a e dis inguished by hei knowledge o he
ma ke , which in luences companies’ scien i ic esea ch agendas, p o-
ides in o ma ion on cus ome needs and ends, and guides he di ec-
ion o esea ch (Zah a e al., 2018). This knowledge allows companies
o adap hei scien i ic s a egies o de elop p oduc s and se ices ha
espond o ac ual demand, he eby inc easing he likelihood o com-
me cial success (Diaz Ruiz, 2022).
In summa y, inno a o s ac as ansla o s be ween scien i ic dis-
co e ies and comme cial applica ions by applying hei specialized
knowledge and in e disciplina y skills o con e echnical concep s in o
iable p oduc s. This in ol es engaging in en ions beyond he echnical
easibili y o comme cializa ion (Vekinis, 2023). They mus also un-
de s and in ellec ual p ope y issues and egula ions o p o ec hei
inno a ion and secu e a compe i i e ad an age (Van No man & Eisen-
ko , 2017).
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
4
Based on knowledge app op ia ion heo y, we p opose he ollowing
su iciency hypo hesis o he ole o inno a o s in co po a e science:
H
3
: The combina ion o bidi ec ional coo dina ion (biCoo ), oppo -
uni y ocus (oppFoc), ma ke o ien a ion (ma kO ), esea ch agenda
alignmen ( esAgn), knowledge ans o ma ion (knT an), in e nal
coo dina ion (in Coo), and empa hy (empa h) in inno a o s is su -
icien o con ibu e o he success o co po a e science p ojec s.
The su iciency o his con igu a ion lies in how hese cha ac e is ics
enable inno a o s o adap knowledge o ma ke needs, acili a e
collabo a ion be ween science and business, and espond o o ganiza-
ional demands wi hou assuming ha his is he only possible
con igu a ion.
In summa y, h oughou he co po a e science p ocess, as desc ibed
by Zah a e al. (2018), ans o ma ional leade ship heo y (Bass, 1999),
open inno a ion heo y (Chesb ough, 2003), and knowledge app op i-
a ion heo y (Nonaka, 1994) p o ide a cohesi e amewo k o unde -
s anding how each key ac o con ibu es o co po a e science success.
T ans o ma ional leade ship heo y illus a es how, h ough s a egic
ision and c ea i e leade ship, CEOs es ablish an en i onmen ha en-
ables knowledge disco e y, ans e , and app op ia ion, ul ima ely
leading o echnological ad ancemen s and os e ing p oduc and p o-
cess inno a ion (F iedman e al., 2016; Su e al., 2023). Open inno a ion
heo y emphasizes he ole o scien is s in gene a ing and in eg a ing
in e nal and ex e nal knowledge, he eby acili a ing collabo a ions ha
s eng hen he co po a e science p ocess and op imize o ganiza ional
ou comes (Randhawa e al., 2016; S´
a e al., 2023). Finally, knowledge
app op ia ion heo y highligh s he ole o inno a o s as essen ial
ansla o s who b idge scien i ic knowledge wi h comme cial applica-
ions, ans o ming disco e ies in o iable ma ke solu ions
(Rome o-Rod íguez e al., 2020; Wang & Chen, 2010). Each ac o ’s
con ibu ion, in e linked wi h o he s, o ms a dynamic and in e de-
penden sys em in which leade ship, knowledge gene a ion, and
knowledge applica ion p opel co po a e science o wa d.
Me hodology
Design
The sQCA me hod was employed o iden i y con igu a ions o pe -
sonal cha ac e is ics o CEOs, scien is s, and inno a o s ha con ibu e
o he success o co po a e science in an eme ging coun y wi h an un-
a o able esea ch en i onmen . The sQCA me hod was selec ed
because i can handle he mul idimensionali y and unce ain y inhe en
in he s udy da a (Pa laˇ
cko ´
a e al., 2023).
The sQCA app oach is an app op ia e me hodology o analyzing
complex a ibu e con igu a ions, as i allows he explo a ion o speci ic
combina ions o ac o s—in his case, he cha ac e is ics o key
ac o s— ha a e su icien o achie e success in co po a e science a he
han iden i ying isola ed indi idual ac o s. This is essen ial in s udies
such as he p esen one, in which mul iple combina ions o cha ac e -
is ics can lead o success, some hing ha adi ional eg ession and SEM
me hods do no adequa ely add ess (Khedhaou ia & Thu ik, 2017).
Unlike eg ession o SEM, sQCA allows o he analysis o mul i-
causali y and asymme y, meaning ha di e en combina ions o con-
di ions can lead o he same ou come, a phenomenon known as
equi inali y (Ding, 2022). This con igu a ional app oach is essen ial o
unde s anding how di e en se s o pe sonal cha ac e is ics can
con e ge in achie ing success, p o iding a comp ehensi e pe spec i e
o mul iple causali y, in which each combina ion ep esen s a unique
“causal ecipe” o he desi ed ou come (Kopplin, 2023).
Addi ionally, sQCA is pa icula ly sui able o s udies wi h small
sample sizes. Gi en ha he sample size in his s udy was 56 cases,
sQCA allowed o p ecise analysis wi hou he ex ensi e sample size
equi emen s o me hods such as eg ession o SEM, which equi e
la ge sample sizes o ensu e s a is ical eliabili y (Tho, 2018).
Finally, sQCA acili a es he analysis o complex in e ac ions among
mul iple condi ions, hus cap u ing speci ic con igu a ions unique o
co po a e science in eme ging economies. This capabili y o handle
nonlinea and con igu a ional in e ac ions makes i a obus me hod o
his s udy, in which combina ions e lec ing he complexi y o indi idual
cha ac e is ics and hei alignmen wi h o ganiza ional goals a e
explo ed (Alsebai e al., 2022).
This me hodological app oach has been widely alida ed in he
li e a u e, highligh ing i s abili y o e eal complex causal con igu a-
ions in o ganiza ional con ex s (e.g., Khedhaou ia & Thu ik, 2017;
Lepp¨
anen e al., 2023; an de Valk e al., 2016; Ve gne & Depey e,
2016). We an icipa e ha his will allow us o iden i y he combina ions
o pe sonal cha ac e is ics ha a e necessa y and su icien o he
success o co po a e science p ojec s in an eme ging coun y’s business
en i onmen .
Da a
Fo he analysis, in o ma ion was used om companies ha ha e
bene i ed om esea ch and inno a ion incen i e p og ams in Pe u,
speci ically he Na ional Inno a ion P og am o Compe i i eness and
P oduc i i y (PNICP) and he Na ional Inno a ion P og am o Fishe ies
and Aquacul u e (PNIPA). Da a on companies ha bene i ed om Law
No. 30,309, which o e s ax deduc ions o hose de eloping R&D p o-
jec s, we e also included. A sample ame o 174 p ojec s inanced o e
he las i e yea s was cons uc ed om hese da abases.
Gi en he sca ci y o companies in ol ed in co po a e science p o-
jec s in Pe u, a pu posi e sampling app oach was essen ial o ensu e he
inclusion o ele an cases. This app oach ocused on iden i ying key
ac o s, p ima ily scien is s and manage s, engaged in p ojec s deemed
success ul acco ding o he success c i e ia de ined by public science
unding p og ams in Pe u. This pu posi e sample, which comp ised 93
po en ial pa icipan s, was selec ed o ep esen companies ha ha e
demons a ed alignmen wi h go e nmen policies and inancial in-
cen i es o science-based ini ia i es, ollowing simila p ac ices in
sQCA s udies wi h small samples and cons ained con ex s. Fi y-six
esponses o he ques ionnai e we e ecei ed, ep esen ing a esponse
a e o 60.2%. The ques ionnai e was adminis e ed be ween Feb ua y
and July 2024.
While a ge ed, he sampling s a egy may p esen limi a ions in
e ms o ep esen a i eness as i p edominan ly includes companies wi h
expe ience in accessing public unding o ax incen i es. Consequen ly,
he s udy may no ully ep esen all i ms wi h a po en ial in e es in
co po a e science, pa icula ly hose ha lack esou ces o alignmen
wi h go e nmen -suppo ed p og ams. This ocus on publicly unded o
incen i ized i ms could in oduce selec ion bias, po en ially limi ing
he gene alizabili y o he esul s o companies wi h less access o hese
esou ces.
To mi iga e non- esponse bias, se e al measu es we e implemen ed
o encou age pa icipa ion and educe he po en ial o bias, including
pe iodic eminde s and pe sonalized communica ions. Wi h a 60.2%
esponse a e, e o s we e made o maximize engagemen ; howe e , we
ecognize ha he limi ed esponse may s ill in oduce pa ial esponse
bias. Howe e , sQCA is obus in se ings wi h limi ed esponses
because o i s emphasis on da a quali y o e quan i y, allowing o he
ex ac ion o meaning ul causal con igu a ions, e en wi h incomple e
da a (Pie aszek & Sk zypczak-Pie aszek, 2014). In sQCA, da a quali y
is mo e c i ical han quan i y (Hao e al., 2021; Kolossa & Kopp, 2018).
Thus, 56 cases we e deemed sui able o he objec i es o his s udy.
In conclusion, while sQCA and he quali y o he collec ed da a
suppo he alidi y o he indings, i is impo an o in e p e he esul s
wi h an unde s anding o he po en ial ep esen a ional limi a ions
s emming om he sample design and pa ial esponse.
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
5
Va iables and measu emen
The a iables we e based on he esul s o he explo a o y quali a i e
esea ch de eloped by ´
Al a ez-Salaza and Be nal-P´
e ez (2023). We
highligh a se o a iables (pe sonal cha ac e is ics) ha could de e -
mine he success o co po a e science in Pe u. Based on his and aking
he concep ual amewo k as a e e ence, de ini ions we e p oposed o
he a iables analyzed. Table 1 p esen s he p oposed de ini ions o
CEOs, scien is s, and inno a o s.
All o hese cha ac e is ics beha e as la en a iables and a e e-
lec ed in speci ic beha io s. Conside ing he concep ual amewo k, an
ins umen was p oposed o collec beha io s ha demons a e he
p esence o hese la en a iables (Sa s ed e al., 2017) and o iden i y
he exis ence o ou comes in co po a e science (Zah a e al., 2018).
Gi en he sample size, applying ac o analysis was impossible; he e-
o e, we used PLS-SEM (Al a ez-Salaza & Seclen-Luna, 2023). The in-
s umen consis ed o 76 obse able a iables measu ed using a
i e-poin Like scale. Resea che s and manage s a ed hei le el o
ag eemen wi h s a emen s e lec ing desi ed pe sonal cha ac e is ics
(20 la en a iables) and condi ions e lec ing co po a e science success
(one la en a iable). Following he guidelines o Hai e al. (2017), he
ins umen was e alua ed, disca ding i e obse able a iables and
ensu ing ha eliabili y and alidi y c i e ia we e me o measu ing
la en a iables in all cases. Appendix A p esen s he assessmen o he
alidi y and eliabili y o he ins umen .
P ocedu e
Da a on he pe sonal cha ac e is ics o co po a e science ac o s and
he esul s o co po a e science p ojec s we e ob ained om PLS-SEM
applica ion es ima es and s anda dized alues, wi h mean ze o and
s anda d de ia ion one. These da a we e calib a ed ollowing he
guidelines p oposed by Dus¸a (2018). Ragin (2023) indica ed ha cali-
b a ion accu acy is essen ial o analysis alidi y. Thus, he 10 h
pe cen ile was used as he exclusion c i e ion, making i possible o
iden i y cases wi h low membe ship in each se . This app oach is ele-
an o e ec i ely disc imina ing cases a he lowe ex emes o he
dis ibu ion (Schneide & Wagemann, 2012). The c osso e poin was
se sligh ly below he 50 h pe cen ile o a oid ambiguous alues close o
0.5, which could hinde he in e p e a ion o he esul s (Dus¸a, 2018).
This adjus men ensu ed ha cases close o he c osso e poin we e
classi ied mo e clea ly, he eby educing he unce ain y associa ed wi h
in e media e membe ship alues. The median is a common e e ence
poin in calib a ion because i ep esen s a cen al alue in he dis i-
bu ion and allows o balanced calib a ion (Schneide & Wagemann,
2012). Finally, he 90 h pe cen ile was aken as he inclusion poin , a
h eshold used o iden i y cases wi h high membe ship in he se , ha is,
hose ha ul ima ely ul illed he condi ion. Selec ion o he 90 h
pe cen ile ensu ed ha only he mos ep esen a i e cases o he phe-
nomenon unde s udy we e classi ied as ull membe s o he se , which
inc eased he p ecision and signi icance o he esul s ob ained
(Schneide & Wagemann, 2012).
Calib a ed da a iden i ied he cha ac e is ics necessa y o success ul
co po a e science. The ool used o his analysis was he QCA package in
R (Dus¸a, 2024). Fea u es su icien o co po a e science success we e
e alua ed using he same package in R. This analysis iden i ied speci ic
combina ions o ea u es ha gua an eed he ou come and p o ided
insigh in o possible causal con igu a ions (Ragin, 2023).
The u h able is a cen al componen o sQCA. I shows all possible
combina ions o condi ions and he numbe o cases co esponding o
each combina ion, he eby acili a ing he iden i ica ion o obus causal
con igu a ions (Rihoux & Ragin, 2009). Following s anda d me hodo-
logical ecommenda ions, an inclusion h eshold o 0.8 was se o
de e mine which combina ions we e su icien o he ou come (Ragin,
2023).
In addi ion, a Boolean logic-based minimiza ion was pe o med o
simpli y he combina ions o he ea u es, which allowed he iden i i-
ca ion o he essen ial con igu a ions ha explain he ou come (Ragin,
2014). Thus, complex, in e media e, and pa simonious solu ions we e
iden i ied, p o iding a comp ehensi e iew o he causal con igu a ions
(Schneide & Wagemann, 2012).
Finally, obus ness es s we e conduc ed o alida e he esul s,
including sensi i i y analysis a di e en consis ency h esholds. Despi e
some inhe en limi a ions o he sQCA me hod, he esul s a e alid and
eliable, p o iding insigh in o he causal con igu a ions in Pe u’s
co po a e science.
Resul s
Sample desc ip ion
The s udy sample was cha ac e ized by a p eponde ance o scien is s
(80.4%) o e manage s (19.6%). The e was a highe ep esen a ion in
enginee ing and echnology ields (46.4%), ollowed by social sciences
Table 1
De ini ion o a iables.
Ac o Fea u e De ini ion
CEO S a egic ision Abili y o lead inno a ion aligned wi h
co po a e s a egy, aking ad an age o
ma ke oppo uni ies and adap ing o
changes.
Engagemen Encou ages inno a ion and ac i ely suppo s
echnological de elopmen in he company.
Scien i ic p ocess
knowledge
Unde s anding he scien i ic p ocess, i s
con inuous upda ing, and i s abili y o iden i y
inno a i e oppo uni ies.
P o essional
ne wo ks
Abili y o use p o essional ne wo ks o os e
collabo a ion and access esou ces.
En ep eneu ial ai Abili y o inno a e, see beyond day- o-day
ope a ions, and seize oppo uni ies ha
eme ge om co po a e science.
Scien i ic ocus Focus on science and esea ch o inno a ion.
Technological
expe ise
Expe ience and knowledge in echnological
a eas, applying inno a i e s a egies in he
company’s de elopmen .
Mo i a ions Focus on sus ainabili y and long- e m impac .
Risk- aking Abili y o make isky decisions based on
knowledge, acing challenges in a calcula ed
manne .
Scien is O ganiza ional
alignmen
The deg ee o which hey align hei esea ch
wi h o ganiza ional objec i es and s a egies.
Specializa ion Le el o expe ise and abili y o p o ide
inno a i e, high- alue solu ions.
Managing scien is Abili y o manage p ojec s and communica e
indings.
Dual empo ali y Abili y o balance p ojec s wi h immedia e
esul s and long- e m bene i s.
Inno a o Bi-di ec ional
coo dina ion
Abili y o communica e and collabo a e wi h
R&D, manage s, and business leade s.
Oppo uni y ocus P oac i ely iden i ying ma ke p oblems and
solu ions and seeking new oppo uni ies om
co po a e science.
Ma ke -o ien ed Abili y o de elop p oduc s wi h ma ke
po en ial, an icipa ing and esponding o hei
needs.
Resea ch agenda
o ien a ion
O ien a ion owa d esea ch p ojec s aligned
wi h he business, aking isks o sa is y he
ma ke .
Knowledge
ans o ma ion
Abili y o adap scien i ic knowledge o
p ac ical and ele an applica ions and
communica e i in he business en i onmen .
In e nal coo dina ion Abili y o ansla e esea ch in o
unde s andable concep s, os e ing
collabo a ion be ween science and business.
Empa hy Unde s anding and empa hy owa d
scien is s, acili a ing collabo a ion and join
explo a ion o esea ch opics.
Own elabo a ion based on Al a ez-Salaza and Be nal-P´
e ez (2023).
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
6
(35.7%) and na u al sciences. The pa icipan s’ deg ee o expe ience
a ied, wi h 35.7% ha ing mo e han 10 yea s o expe ience, sugges ing
a solid knowledge base and p ac ice in he ield.
Rega ding educa ion, 39.3% had a mas e ’s deg ee and 30.4% had a
doc o a e, indica ing high academic aining. Mos pa icipan s (82.1%)
had wo ked on one o i e p ojec s, sugges ing amilia i y wi h he
esea ch p ocess. The size o he p ojec s was di e se, wi h he majo i y
(39.3%) being less han US$10,000, e lec ing unding limi a ions in he
Pe u ian con ex .
Da a calib a ion
By se ing he exclusion h eshold a he 10 h pe cen ile, he c oss-
o e poin a he median, and he inclusion h eshold a he 90 h
pe cen ile, i was possible o co ec ly classi y he cases unde s udy and
iden i y hose wi h low, mode a e, and high membe ship o se e al key
cha ac e is ics (see Appendix B).
Calib a ion ensu es ha he da a accu a ely e lec he deg ee o
membe ship o each case, elimina ing ambigui ies and p o iding cla i y
in classi ica ion. This allows o eliable analysis ailo ed o di e en
da a dis ibu ions (Dus¸a, 2018). The iden i ica ion o cases wi h low,
mode a e, and high membe ship le els demons a ed he e ec i eness
o he calib a ion p ocess. As Schneide and Wagemann (2012) a gued,
he absence o cases wi h high membe ship in speci ic ea u es sugges s
ha hese a e no indi idual condi ions necessa y o success ul co po-
a e science bu may be in combina ion wi h su icien condi ions. The
p edominance o mode a e membe ship indica es g ea e complexi y
and di e si y in he ou es o success, unde sco ing he impo ance o
assessing mul iple cha ac e is ics o iden i y p ac ical causal
con igu a ions.
T u h ables
T u h ables o CEOs, scien is s, and inno a o s e eal a ious
combina ions o pe sonal cha ac e is ics and hei ela ionships wi h
success in co po a e science in Pe u (see Appendix C). Many combina-
ions had only one associa ed case, sugges ing limi ed ep esen a i e-
ness and high a iabili y in eme ging ecosys ems, possibly because o
he small sample size. Howe e , he analysis in his explo a o y s udy is
s ill in o ma i e (Schneide & Wagemann, 2012). Despi e he limi ed
numbe o cases pe combina ion, he con igu a ion p o ided essen ial
insigh in o co po a e science in eme ging sys ems.
On he o he hand, combina ions wi h high consis ency (incl. >0.80)
and low p opo ional educ ion o inconsis ency (PRI <0.75) sugges
ha ce ain se s o condi ions end o lead o success (Dus¸a, 2024). The
combina ion o all condi ions indica es ha mul iple simul aneous
cha ac e is ics could be su icien o he success o co po a e science
p ojec s in Pe u. Thus, he a iabili y in combina ions e lec s he di-
e si y o ac o cha ac e is ics in he Pe u ian ecosys em, and each
unique combina ion may me i addi ional a en ion.
Analyzing he u h ables allows us o iden i y he condi ions ha ,
when p esen oge he , c ea e an en i onmen conduci e o success.
They show ha he cha ac e is ics o CEOs (12 cases; incl. =0.87; PRI =
0.77), scien is s (16 cases; incl. =0.84; PRI =0.71), and inno a o s (20
cases; incl. =0.88; PRI =0.76) we e su icien o he success o
co po a e science in Pe u. The o al absence o hese condi ions also
highligh s ha hese p ojec s end o ail (CEOs, ou cases; scien is s, 14
cases; and inno a o s, eigh cases). Al hough many con igu a ions ha e
only one case (CEOs, 24; scien is s, i e; inno a o s, 14), his un-
de sco es he impo ance o explo ing and documen ing hese con igu-
a ions o be e unde s and he comple e pic u e. The ollowing sec ions
discuss he necessi y and su iciency o he con igu a ions iden i ied in
he empi ical da a.
Necessi y and su iciency analysis
The necessi y and su iciency analysis (Table 2) o CEOs, scien is s,
and inno a o s shows ha no indi idual condi ion achie es a necessi y
consis ency g ea e han 0.80 (Schneide & Wagemann, 2012), indi-
ca ing ha no cha ac e is ic is s ic ly necessa y o success ul co po a e
science (Ragin, 2014). Fo CEOs, knowledge o he scien i ic p ocess
(0.74) and scien i ic app oach (0.75) a e essen ial bu insu icien .
Specializa ion (0.78) and scien i ic p ojec managemen (0.69) p e-
sen ed high alues bu we e also no necessa y condi ions. Fo in-
no a o s, empa hy (0.83) comes closes o being necessa y bu is also
insu icien .
When applying a su iciency h eshold o a consis ency o 0.80, no
indi idual CEO cha ac e is ic eached his le el. S a egic ision,
commi men , p o essional ne wo ks, en ep eneu ship, and isk- aking
show su icien consis ency o 0.72, indica ing ha hese condi ions
can con ibu e o success in combina ion wi h o he s. Among scien is s,
o ganiza ional alignmen , specializa ion, scien i ic p ojec managemen ,
and empo al duali y showed alues close o he h eshold, wi h he
highes being 0.75 and 0.74. These condi ions may be pa o a su icien
causal con igu a ion (Ragin, 2014).
Se e al inno a o cha ac e is ics eached adequa e su iciency
le els. Bidi ec ional coo dina ion, oppo uni y o ien a ion, ma ke
o ien a ion, knowledge ans o ma ion, in e nal coo dina ion, and
empa hy showed su icien consis encies be ween 0.74 and 0.83. These
condi ions can con ibu e signi ican ly o success (Schneide & Wage-
mann, 2012).
As combina ions o condi ions can p o ide a mo e comple e pic u e
o success, a coun e ac ual analysis using pa simonious and in e me-
dia e solu ions is equi ed (Schneide & Wagemann, 2012). This
app oach iden i ies simpli ied and balanced causal con igu a ions,
p o iding a be e basis o unde s anding he unde lying dynamics and
designing s a egies o de eloping co po a e science in eme ging
con ex s.
Complex solu ions
In sQCA, iden i ying complex con igu a ions is undamen al o
unde s anding he mul iple pa hs ha can lead o success in di e en
con ex s. The ollowing sec ion p esen s he complex solu ions o CEOs,
scien is s, and inno a o s, highligh ing combina ions o su icien con-
di ions o co po a e science success in Pe u (see Appendix D). Robus
con igu a ions we e selec ed, elimina ing hose wi h ewe han h ee
cases, su icien consis ency o less han 0.80, and p opo ional incon-
sis ency educ ion o mo e han 0.75, as ecommended by Misangyi and
Acha ya (2014).
Fo CEOs, 23 possible con igu a ions we e iden i ied. The minimized
complex solu ion o CEOs shows combina ions o su icien condi ions
o he success o co po a e science in Pe u. The iden i ied con igu a-
ions p esen he me ics o consis ency, PRI, co e age, and se e al cases
ha suppo hei ele ance. The combina ion o all condi ions (s a egic
ision, commi men , knowledge o he scien i ic p ocess, p o essional
ne wo ks, en ep eneu ial capaci y, scien i ic app oach, mo i a ion, and
isk- aking) showed high consis ency and adequa e co e age. This sug-
ges s ha a holis ic app oach in which he CEO leads inno a ion aligned
wi h co po a e s a egy, unde s ands he scien i ic p ocess, u ilizes
p o essional ne wo ks, and inno a es by aking in o med isks is e ec-
i e o he success o co po a e science.
Ano he con igu a ion wi h high consis ency includes he absence o
a s a egic ision and commi men bu wi h knowledge o he scien i ic
p ocess, p o essional ne wo ks, en ep eneu ship, echnological expe -
ise, and mo i a ion. This indica es ha in some con ex s, p o essional
ne wo ks and mo i a ion can compensa e o he need o a clea ision
and s a egic commi men . The hi d con igu a ion shows ha p o es-
sional ne wo ks, en ep eneu ial abili y, scien i ic ocus, echnological
expe ise, mo i a ion, and isk aking can compensa e o he absence o
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
7
s a egic ision and commi men . CEOs can o e come hei lack o
ision and commi men h ough a solid p o essional ne wo k and sci-
en i ic app oach. Finally, ano he con igu a ion wi h high consis ency
includes a scien i ic app oach wi hou a s a egic ision, commi men ,
p o essional ne wo ks, en ep eneu ship, echnological expe ise,
mo i a ion, o isk- aking. This highligh s ha in some con ex s, a solid
scien i ic app oach may be su icien , e en wi hou he mul iple condi-
ions gene ally associa ed wi h success.
The esul s o he scien is s’ analysis e ealed mul iple con igu a-
ions ha con ibu ed o he success o co po a e science, wi h 71% o
cases included in he epo ed con igu a ions. This allowed us o iden i y
he ends and pa e ns ha highligh ed he impo ance o a ious
condi ions in di e en combina ions. The combina ion o o ganiza ional
alignmen and science p ojec managemen s ands ou , wi h high con-
sis ency and adequa e co e age. This sugges s ha scien is s who align
hei esea ch wi h o ganiza ional goals and e ec i ely manage hei
p ojec s a e mo e likely o achie e success. O ganiza ional alignmen
acili a es he in eg a ion o science in o co po a e s a egy, imp o ing
esea ch impac , whe eas e ec i e p ojec managemen imp o es he
communica ion o indings and he applica ion o managemen
concep s.
Ano he ele an con igu a ion is he combina ion o o ganiza ional
alignmen and he absence o empo al duali y. This sugges s ha sci-
en is s who align hei esea ch wi h o ganiza ional goals bu do no
need o balance p ojec s wi h di e en ime ho izons may s ill be suc-
cess ul. The absence o empo al duali y may indica e a g ea e ocus on
sho - o long- e m p ojec s, allowing o mo e in-dep h esea ch
wi hou he p essu e o balance mul iple empo al p io i ies. Howe e ,
specializa ion combined wi h he absence o scien i ic p ojec manage-
men capabili y shows high consis ency and su icien co e age. This
indica es ha specializing in a speci ic a ea may be mo e bene icial han
managing mul iple p ojec s. Specializa ion allows o in-dep h knowl-
edge in a pa icula ield, leading o highe - alue inno a ions, which
sugges s ha p ojec managemen should all o ac o s o he han sci-
en is s. This acili a es a g ea e ocus on esea ch.
Ano he combina ion o specializa ion and empo al duali y man-
agemen sugges s ha scien is s who balance p ojec s wi h immedia e
esul s and long- e m bene i s may ha e an ad an age. Managing em-
po al duali y allows scien is s o in eg a e con inuous inno a ion wi h
sho - e m esul s while pu suing mo e p o ound esul s when dealing
wi h de elopmen s ha equi e mo e R&D e o . Finally, he
combina ion o a lack o specializa ion and he abili y o manage em-
po al duali y may be o se by a scien is ’s manage ial capabili ies. This
sugges s ha some scien is s can achie e success by e ec i ely man-
aging p ojec s wi hou he need o deep specializa ion and wi hou he
complexi y o balancing p ojec s wi h di e en ime ho izons. Thus,
e ec i e p ojec managemen may be essen ial o scien is s in mo e
gene al en i onmen s, allowing o apid adap a ion o di e se demands
and oppo uni ies.
The analysis e eals ha no single con igu a ion o scien i ic cha -
ac e is ics gua an ees success in co po a e science. The di e si y o
success ul combina ions sugges s ha mul iple ou es can lead o suc-
cess, depending on he con ex and s eng hs o he scien is s. These
con igu a ions unde sco e he impo ance o o ganiza ional alignmen ,
specializa ion, and p ojec managemen , sugges ing ha di e en s a-
egies may be equally alid.
The complex solu ion o inno a o s includes 79% o he cases,
indica ing be e ep esen a i eness han o CEOs and scien is s.
Se e al combina ions o condi ions ha e been iden i ied as de e minan s
o success in co po a e science. The i s con igu a ion highligh s he
impo ance o wo-way coo dina ion, o ien a ion on he esea ch
agenda, in e nal coo dina ion, empa hy, and a lack o ocus on oppo -
uni ies. This sugges s ha e icien communica ion and collabo a ion
among scien is s, manage s, and business leade s, aligned wi h o gani-
za ional goals and empa hy o scien is s, is c i ical o success, e en
wi hou p oac i i y ocused on ma ke oppo uni ies.
The second con igu a ion emphasizes oppo uni ies, esea ch agenda
o ien a ion, knowledge ans o ma ion, in e nal coo dina ion, and
empa hy. Inno a o s who iden i y ma ke p oblems and solu ions,
ansla e esea ch in o p ac ical applica ions, and e ec i ely collabo a e
wi h scien is s end o be success ul. Ano he ele an con igu a ion is a
combina ion o ma ke o ien a ion, esea ch agenda o ien a ion,
knowledge ans o ma ion, in e nal coo dina ion, and empa hy. De el-
oping p oduc s wi h ma ke po en ial and adap ing scien i ic knowledge
o ele an applica ions while collabo a ing in e nally and main aining
empa hy o scien is s is c i ical.
An addi ional con igu a ion shows ha empa hy is su icien o
success, e en wi hou oppo uni y ocus, ma ke o ien a ion, esea ch
agenda, knowledge ans o ma ion, o in e nal coo dina ion. This in-
dica es ha scien is s’ empa hy can compensa e o a lack o o he
condi ions. A inal con igu a ion, an al e na i e o he p e ious one,
combines a ocus on oppo uni ies, ma ke o ien a ion, and esea ch
Table 2
Need and su iciency analysis.
Ac o Fea u e Needs Analysis Su iciency Analysis
inclN RoN co N inclS PRI co S co U
CEO s a V 0.69 0.78 0.72 0.72 0.57 0.69 0.00
engage 0.72 0.77 0.72 0.72 0.56 0.72 0.01
sciP o 0.74 0.72 0.69 0.69 0.54 0.74 0.00
p oNe 0.67 0.79 0.72 0.72 0.54 0.67 0.00
en eT 0.74 0.76 0.72 0.72 0.55 0.74 0.02
sciFoc 0.75 0.74 0.71 0.71 0.56 0.75 0.01
echEx 0.71 0.72 0.68 0.68 0.50 0.71 0.00
mo i 0.70 0.77 0.71 0.71 0.55 0.70 0.00
iskTk 0.74 0.76 0.72 0.72 0.55 0.74 0.00
Scien is o gAln 0.70 0.82 0.76 0.76 0.62 0.70 0.01
specia 0.78 0.77 0.74 0.74 0.60 0.78 0.07
manSci 0.69 0.78 0.71 0.71 0.55 0.69 0.02
dualTe 0.68 0.81 0.74 0.74 0.59 0.68 0.01
Inno a o biCoo 0.75 0.79 0.75 0.75 0.59 0.75 0.02
oppFoc 0.73 0.73 0.69 0.69 0.50 0.73 0.00
ma kO 0.75 0.79 0.75 0.75 0.58 0.75 0.01
esAgn 0.77 0.79 0.76 0.76 0.60 0.77 0.00
knT an 0.74 0.82 0.77 0.77 0.62 0.74 0.01
in Coo 0.76 0.83 0.79 0.79 0.66 0.76 0.00
empa h 0.83 0.73 0.74 0.74 0.60 0.83 0.01
No e: inclN =consis ency o need; RoN = ele ance o need; co N =co e age o need; inclS =consis ency o su iciency; PRI =p opo ional educ ion o incon-
sis ency; co S =co e age o su iciency; co U =single co e age.
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
Jou nal o Inno a ion & Knowledge 10 (2025) 100652
8
agenda o ien a ion wi h he absence o knowledge ans o ma ion and
in e nal coo dina ion bu wi h he p esence o empa hy. This sugges s
ha a p oac i e ocus on ma ke oppo uni ies aligned wi h esea ch
agenda o ien a ion and empa hy may be su icien o success wi hou
needing knowledge ans o ma ion o in e nal coo dina ion.
The analysis o complex solu ions e eals mul iple combina ions o
condi ions ha can lead o success in co po a e science. The di e si y o
success ul con igu a ions unde lines he impo ance o lexibili y,
adap abili y, and a combina ion o di e en capabili ies and ap-
p oaches. Howe e , analysis o he co e and pe iphe al con igu a ions is
necessa y o a deepe unde s anding. This app oach allows he iden i-
ica ion o simpli ied and balanced causal con igu a ions, p o iding a
be e basis o unde s anding he dynamics unde lying he de elop-
men o co po a e science in eme ging con ex s.
Cen al and pe iphe al condi ions
The analysis o he co e and pe iphe al condi ions in co po a e sci-
ence p ojec s allows us o iden i y he CEO cha ac e is ics ha lead o
success. Table 3 p esen s he esul s ob ained.
Analysis o he se en iden i ied solu ions highligh s he a ious
combina ions o condi ions o success in co po a e science. In Solu ion
1, he CEO’s scien i ic o ien a ion is cen al, while s a egic ision is
seconda y, sugges ing ha a ocus on science may be su icien o
p ojec success. Solu ion 2 emphasizes CEO in ol emen suppo ed by
s a egic ision and scien i ic knowledge as undamen al elemen s. So-
lu ion 3 emphasizes he impo ance o p o essional ne wo ks, echno-
logical expe ise, and isk- aking, whe eas s a egic ision and scien i ic
knowledge a e less ele an . In Solu ion 4, p o essional ne wo ks,
en ep eneu ship, and isk- aking a e cen al. Solu ion 5 emphasizes
p oac i e leade ship wi h a solid scien i ic and echnological base. So-
lu ion 6 combines he willingness o ake isks, a scien i ic app oach, and
an en ep eneu ial a i ude, highligh ing he CEO’s in ol emen .
Finally, Solu ion 7 shows ha p o essional ne wo ks, en ep eneu ial
skills, and echnological expe ise a e essen ial, while mo i a ion and
scien i ic knowledge a e seconda y.
In summa y, he e alua ion o Hypo hesis 1 indica es ha no all
p oposed condi ions a e simul aneously equi ed o achie e success in
co po a e science p ojec s. Ins ead, success can be achie ed h ough
a ious pa ial combina ions o su icien condi ions. CEO in ol emen ,
p o essional ne wo ks, en ep eneu ial ai s, echnological expe ise,
and isk aking eme ged as he mos impo an and ecu en ac o s
ac oss con igu a ions, whe eas mo i a ion appea ed o be a comple-
men a y bu no essen ial elemen . The e o e, his hypo hesis is pa ially
suppo ed, as di e en combina ions o some o he p oposed condi ions
a e su icien o success wi hou necessi a ing hei simul aneous
p esence.
Rega ding scien is s’ co e and pe iphe al condi ions (Table 4), he
solu ions e eal di e en combina ions o success in co po a e science.
In Solu ion 1, o ganiza ional alignmen and specializa ion a e cen al
condi ions, sugges ing ha success depends on he alignmen o esea ch
wi h o ganiza ional goals and a high le el o specializa ion. Solu ion 2
highligh s he cen ali y o specializa ion and he abili y o manage
empo al duali y. A he same ime, p ojec managemen is pe iphe al,
and o ganiza ional alignmen is i ele an , indica ing ha combining
specializa ion wi h he abili y o achie e bo h sho - and long- e m e-
sul s is c i ical. In Solu ion 3, o ganiza ional alignmen and he abili y o
manage empo al duali y a e su icien o success, ega dless o
specializa ion o p ojec managemen . Solu ion 4 emphasizes he
impo ance o o ganiza ional alignmen and managemen o empo al
duali y, complemen ed by p ojec managemen skills, wi h specializa-
ion being i ele an .
The e alua ion o H2 shows ha di e en con igu a ions o condi-
ions a e su icien o success in co po a e science p ojec s wi hou
equi ing he simul aneous p esence o all p oposed condi ions. O ga-
niza ional alignmen and empo al balancing capaci y ha e eme ged as
he mos impo an and ecu en condi ions, sugges ing ha success
la gely depends on aligning esea ch wi h o ganiza ional goals and
e ec i ely managing bo h sho - and long- e m objec i es. Specializa-
ion and managemen skills a e ele an in some con igu a ions bu a e
Table 3
Cen al and Pe iphe al Condi ions o CEOs.
Fea u e Solu ion 1 Solu ion 2 Solu ion 3 Solu ion 4 Solu ion 5 Solu ion 6 Solu ion 7
s a V ⨂•⨂•
engage ● ● ●
sciP o •⨂• • • •
p oNe ● ● ●
en eT ● ● ● ●
sciFoc ● ● ●
echEx ●●●
mo i • •
iskTk ● ● ●
Consis ency 0.816 0.803 0.814 0.842 0.846 0.835 0.822
PRI 0.547 0.665 0.477 0.722 0.728 0.706 0.695
Raw Co e age 0.431 0.51 0.298 0.477 0.522 0.525 0.519
Unique Co e age 0.022 0.034 0.004 0.005 0.012 0.009 0
O e all Solu ion Consis ency 0.825
O e all Solu ion Co e age 0.469
No e: (●) Indica es ha he condi ion is p esen and cen al o he con igu a ion; (•) Indica es ha he condi ion is p esen bu no cen al o he con igu a ion; (⨂)
Indica es ha he condi ion is absen and cen al o he con igu a ion; (⨂) Indica es ha he condi ion is lacking bu no cen al o he con igu a ion.
Table 4
Cen al and Pe iphe al Condi ions o Scien is s.
Va iable Solu ion 1 Solu ion 2 Solu ion 3 Solu ion 4
o gAln ●●
manSci ••
dualTe ● ● ●
specia ● ●
Consis ency 0.85 0.81 0.80 0.80
PRI 0.64 0.47 0.66 0.58
Raw Co e age 0.38 0.32 0.60 0.45
Unique Co e age 0.01 0.02 0.02 0.07
O e all Solu ion
Consis ency
0.82
O e all Solu ion Co e age 0.12
No e: (●) Indica es ha he condi ion is p esen and cen al o he con igu a ion;
(•) Indica es ha he condi ion is p esen bu no cen al o he con igu a ion;
(⨂) Indica es ha he condi ion is absen and cen al o he con igu a ion; (⨂)
Indica es ha he condi ion is lacking bu no cen al o he con igu a ion.
J.R. Al a ez-Salaza and P.M. Be nal-P´
e ez
