Sil a Ne o, An onio Reinaldo e al.
A icle
Mul ic i e ia analysis o inno a ion ecosys ems and he
impac o human capi al and in es men s on B azilian
indus ies
Adminis a i e Sciences
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Sugges ed Ci a ion: Sil a Ne o, An onio Reinaldo e al. (2024) : Mul ic i e ia analysis o inno a ion
ecosys ems and he impac o human capi al and in es men s on B azilian indus ies,
Adminis a i e Sciences, ISSN 2076-3387, MDPI, Basel, Vol. 14, Iss. 10, pp. 1-20,
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Ci a ion: Sil a Ne o, An onio
Reinaldo, Miguel Gus a o Gomes da
Sil a, Fe nando Hen ique Taques,
Thiago Pole o, Thyago Celso
Ca alcan e Nepomuceno, Vic o
Diogho Heue de Ca alho, and
Madson B uno da Sil a Mon e. 2024.
Mul ic i e ia Analysis o Inno a ion
Ecosys ems and he Impac o Human
Capi al and In es men s on B azilian
Indus ies. Adminis a i e Sciences 14:
241. h ps://doi.o g/10.3390/
admsci14100241
Recei ed: 20 July 2024
Re ised: 12 Sep embe 2024
Accep ed: 26 Sep embe 2024
Published: 29 Sep embe 2024
Copy igh : © 2024 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
adminis a i e
sciences
A icle
Mul ic i e ia Analysis o Inno a ion Ecosys ems and he Impac
o Human Capi al and In es men s on B azilian Indus ies
An onio Reinaldo Sil a Ne o 1,*, Miguel Gus a o Gomes da Sil a 1, Fe nando Hen ique Taques 1,2 ,
Thiago Pole o 3, Thyago Celso Ca alcan e Nepomuceno 4, Vic o Diogho Heue de Ca alho 5
and Madson B uno da Sil a Mon e 6
1Pos -G adua e P og am in P oduc ion Enginee ing, Fede al Uni e si y o Pe nambuco, Campus Ag es e,
Ca ua u 55014-900, B azil; [email p o ec ed] (M.G.G.d.S.); [email p o ec ed] (F.H.T.)
2Facul ad de Ciencias Económicas y Emp esa iales, Uni e sidad Au ónoma de Mad id, 28049 Mad id, Spain
3Depa men o Business Adminis a ion, Fede al Uni e si y o Pa á, Belém 66075-110, B azil;
[email p o ec ed]
4Depa men o S a is ics, Fede al Uni e si y o Pe nambuco, Reci e 50740-560, B azil;
[email p o ec ed]
5Technologies Axis, Campus do Se ão, Fede al Uni e si y o Alagoas, Delmi o Gou eia 57480-000, B azil;
ic o [email p o ec ed]
6Facul y o Economics, Adminis a ion and Accoun ing, Fede al Uni e si y o Alagoas, Maceió57072-900,
B azil; [email p o ec ed]
*Co espondence: [email p o ec ed]
Abs ac : Inno a ion is one o he main ac o s associa ed wi h indus ial g ow h, as i con ibu es o
inc eased p oduc i i y, sus ainabili y, and in e na ional compe i i eness. The e is a ce ain deg ee o
complexi y in measu ing inno a ion, since he e a e a ious me ics o his pu pose, and each sec o
o he economy handles i di e en ly. In B azil, he Indus ial Su ey o Technological Inno a ion
(PINTEC) was de eloped o cons uc sec o ial indica o s on inno a ion ac i i ies. Based on hese
da a, his pape in es iga es how en sec o s o he economy pe o med du ing wo his o ical se ies
(2011 o 2014 and 2014 o 2017) conside ing i e c i e ia linked o he inno a ion p ocess and he
impac o quali ied human capi al. The p oblem is analyzed in ligh o mul ic i e ia decision analysis
(MCDA), using p e e ence anking o ganiza ion me hods o en ichmen e alua ion (PROMETHEE
II) o p o ide a anking o B azilian indus ial sec o s. The esul s show how he sec o s ha e changed
o e he yea s, highligh ing ha inno a ion expendi u e p o ed c ucial in measu ing companies’
commi men o inno a ion, bu also show ha a highly quali ied wo k o ce eme ged as a leading
ac o . Fu he mo e, he esea ch p esen s which c i e ia ha e con ibu ed posi i ely and nega i ely
o each sec o , which can se e as d i e s o policy o mula ion o s eng hen he B azilian indus y.
Keywo ds: inno a ion; mul ic i e ia decision analysis (MCDA); PINTEC; quali ied human capi al;
PROMETHEE II
1. In oduc ion
Inno a ion has been he subjec o s udy o unde s anding he economic capaci y o
o ganiza ions and how he ac o s linked o i inc ease business compe i i eness (Schum-
pe e 1934;Po e 1991;Damanpou 1991;D ucke 1998;OECD and Eu os a 2005;Sil a
e al. 2023). Inno a ion is one o he al e na i es o imp o ing o ganiza ions’ compe i i e
posi ioning and p o i abili y (Mo ei a and de Va gas 2015;Guima ães e al. 2016). In he 21s
cen u y, he abili y o gene a e inno a ions ega ding echnologies and hei use, business
s a egies, and p ocesses is one o he p e equisi es o he success o companies (Boehm
e al. 2014). To his end, inno a ion can be a compe i i e ad an age o companies, whe he
h ough in oducing new p oduc s and se ices o imp o ing exis ing ones (Taques e al.
2021). In con as , Na ional and Regional Inno a ion Sys em ac o s should obse e he
en i onmen whe e hey a e inse ed, sea ching o laws and s a egic de elopmen policies
Adm. Sci. 2024,14, 241. h ps://doi.o g/10.3390/admsci14100241 h ps://www.mdpi.com/jou nal/admsci
Adm. Sci. 2024,14, 241 2 o 20
ha a o he implan a ion o new inno a i e en u es ha suppo hem in he ma ke
and he main enance o exis ing ones ha suppo hei g ow h (Mo ei a e al. 2024).
Despi e he ele ance discussed in he li e a u e, common p oblems hinde he in-
no a ion p ocess, such as he lack o quali ied human capi al (pe sonnel) and high cos s
(Jacoski e al. 2014). Resea ch in o inno a ion o he business sec o is essen ial due o i s
signi icance and apid dynamics (Becheikh e al. 2006;Zanello e al. 2016). So, new s udies
a e necessa y o unde s and he impac s o hese ad ancemen s. In addi ion, he ac i i ies
linked o he inno a ion p ocess a e a c i ical ac o in inno a ion pe o mance (San os
e al. 2012). Despi e he ex ensi e li e a u e on inno a ion and i s impac on indus ial
g ow h conside ing he knowledge-gene a ing o ganiza ion pa adigm, he e is s ill a gap
in unde s anding he bes p ac ices o inno a ion ha a e e ec i e in di e en economic
and sec o al con ex s (Sa a o a e al. 2023).
S udies p esen a ious inno a ion indica o s and e en use he PINTEC da abase o
s udy he B azilian inno a ion ecosys em, al hough hey a e limi ed o speci ic opics. In
his con ex , we can ci e he posi i e s a is ical ela ionships ound be ween inno a ion
pe o mance and knowledge-in ensi e business se ices (San os 2019); be ween ob aining
coope a ion wi h o eign pa ne s and he adop ion o eco-inno a ion (da Sil a Rabêlo
and Melo 2019); and be ween he incidence o o ganiza ional inno a ion and he deg ee
o echnological in ensi y o indus y sec o s (de Oli ei a 2023). Al hough hese s udies
p o ide in e es ing insigh s in o he subjec , he e is a lack o a sys ema ic and compa a-
i e app oach o how speci ic inno a ion p ac ices can be adap ed and implemen ed o
pe o mance in di e se sec o s.
B azilian companies we e desc ibed conside ing he analysis model o p e ious e -
sions o PINTEC (Kannebley e al. 2005). I was possible o cha ac e ize he companies
as hose ha inno a ed by de eloping new p ocesses and by in oducing new p oduc s
o he ma ke . In his con ex , hey ound ha a ha ime, he main de e minan s o
cha ac e izing inno a i e companies we e in e -indus y di e ences, o eign capi al o igin,
i m size, and expo ing o ien a ion.
I is in e es ing o no e ha , e en a e almos wo decades, inno a ion in he B azilian
indus ial sec o is s ill concen a ed on he acquisi ion o equipmen and inno a ions
ha al eady exis on he global ma ke . Mo eo e , he e is a dependence on go e nmen
suppo and he e is no con inui y in he e o s made by B azilian i ms o inno a e
(Calia i e al. 2021;Ci ani e al. 2021). In o he wo ds, i is necessa y o unde s and he
cha ac e is ics o each sec o , aking in o accoun he speci ici ies o he o ganiza ions,
in o de o diagnose he ba ie s and d aw up speci ic s a egies ha boos inno a ion
and consequen ly he compe i i eness o he B azilian indus y a a wo ld le el, which is
co obo a ed by (de Mo aes Sil a e al. 2023).
Teixei a (2007) s a es ha he uel o he inno a ion p ocess in companies is quali ied
human capi al. When a company has quali ied employees, i inc eases he po en ial o
de eloping inno a ion so ha imp o ing he quali y o goods and se ices becomes possible
(D ucke 1998;Teixei a 2007). Resea che s a e key playe s in inno a ion sys ems h ough
he ans e o knowledge (E zkowi z 1998) and skilled labo (B own 2016). In p ac ical
e ms, in oducing new p oduc s and se ices and o he inno a ion p ocesses a e also
d i en by his p o essional quali ica ion and knowledge exchange (Sil a e al. 2023). This
dynamic c ea es inno a i e oppo uni ies o mee ma ke needs (Mo ei a e al. 2024).
On he o he hand, expendi u es on inno a ion a e o en di ec ed owa d esea ch and
de elopmen (R&D) ac i i ies, which o m he basis o inno a ion. The e o e, issues ela ing
o in es men in inno a ion a e ano he signi ican ac o o be in es iga ed. In he s udies
conduc ed by Lazza o i e al. (2015) and San os e al. (2012), in es men s in esou ces ha
can gene a e inno a ion ha e been shown o impac companies’ pe o mance.
Inno a ion is one o he al e na i es o imp o ing o ganiza ions’ compe i i e posi-
ioning and p o i abili y (Mo ei a and de Va gas 2015;Guima ães e al. 2016). In B azil,
one o he po en ial de e minan s o indus ial g ow h is in es men in inno a ion (A uda
e al. 2006;Fische e al. 2009;Con ede ação Nacional da Indús ia 2010;Spinosa e al.
Adm. Sci. 2024,14, 241 3 o 20
2021). Howe e , despi e he impo ance o inno a ion o g ow h and business posi ioning,
he B azilian indus ial sec o epo ed a 2.55% dec ease in he 2009–2011 inno a ion a e
compa ed o ha o he p e ious iennium (Ins i u o de Pésquisa Economica Aplicada
2013). This indica o assesses he a io be ween he numbe o companies ha inno a ed a
leas once and he o al numbe o companies su eyed du ing he pe iod in ques ion.
Thus, his wo k seeks o measu e which sec o o B azilian indus y and se ices has
he bes esul s, conside ing decision c i e ia such as he alue o expendi u e on inno a ion
by companies and he numbe o employees wi h highe educa ion (unde g adua e) and
specializa ion a he mas e ’s le el. These analyses ocused on wo his o ical se ies co e ing
he h ee-yea pe iods om 2011 o 2014 and om 2014 o 2017 based on compa isons
be ween hem. To his end, he wo k uses da a om he his o ical se ies ex ac ed om he
Indus ial Su ey o Technological Inno a ion (Pesquisa Indus ial de Ino ação Tecnológica,
PINTEC) published by he B azilian Ins i u e o Geog aphy and S a is ics (Ins i u o B asilei o
de Geog a ia e Es a ís ica, IBGE). Fo his analysis, he ollowing indica o s we e used, also
called c i e ia: (i) expendi u e by companies on inno a ion; (ii) pe cen age o employees
wi h pos g adua e deg ees (mas e s); (iii) pe cen age o employees wi h unde g adua e
deg ees; (i ) ne e enue; and ( ) pe cen age o new and subs an ially imp o ed p oduc s
in o al domes ic sales.
The con ibu ion o his s udy lies in i s adop ion o an analy ical amewo k based
on a mul ic i e ia analysis ha p o ides a de ailed assessmen o he dynamic changes
in sec o al pe o mance in he con ex o inno a ion. By p esen ing he impo ance o
digi al compe ence and leade ship in digi al ans o ma ion as undamen al ca alys s o
inno a ion, his s udy emphasizes he need o new unding policies o science, echnology,
and inno a ion ha enhance he educa ional quali ica ions o he wo k o ce o os e he
compe i i eness o economic sec o s. This s udy o e s aluable insigh s o policymake s
and indus ial s akeholde s, aiming o p omo e sus ainable indus ial g ow h h ough
s a egic in es men s in inno a ion and o ganiza ional esul s. In addi ion, his a icle
aims o in es iga e which sec o s o he B azilian indus y pe o med bes based on he
es ablished c i e ia o aid go e nmen bodies in o ming public policies o encou age hese
sec o s. This esea ch aims o p o ide esea che s, p ac i ione s, and en ep eneu s wi h a
summa y analysis based on ankings and inno a ion p ospec s.
This wo k is di ided in o ou sec ions. In addi ion o his in oduc ion, Sec ion 2
p esen s he me hod o analyzing he da a used o ob ain and explo e he esul s. Sec ion 3
examines he esul s o he mul ic i e ia models, while Sec ion 4discusses he indings and
limi a ions o he esea ch. Finally, he las sec ion p esen s he inal conside a ions.
2. Ma e ials and Me hods
2.1. Da a
PINTEC is an inno a ion su ey ha p o ides in o ma ion on sec o al, egional, and
na ional indica o s o B azilian companies’ inno a ion ac i i ies. This s udy used PINTEC
da a published in 2014 and 2017, he las yea s o he B azilian Ins i u e o Geog aphy and
S a is ics (IBGE 2024) su eys. Al hough he da a used we e published in hese wo yea s,
hey e e o wo his o ical se ies, he i s co e ing 2011 o 2014 and he second om 2014
o 2017.
Using a mul ic i e ia classi ica ion me hodology, his s udy seeks o assess which o
B azil’s indus ial and se ice sec o s pe o m bes based on c i e ia linked o inno a ion.
In his sense, i is c ucial o measu e he inno a ion po en ial o indus y and se ice
sec o s, gi en ha be e use o labo and inancial expendi u e on inno a ion can lead
o be e e enues and mo e inno a i e o subs an ially imp o ed p oduc s. To his end,
10 o hese sec o s o he na ional economy we e selec ed o measu e hei pe o mance:
ex ac i e indus ies, manu ac u e o ood p oduc s, manu ac u e o clo hing and acces-
so ies, manu ac u e o chemical p oduc s, manu ac u e o ubbe and plas ic p oduc s,
manu ac u e o machine y, equipmen , and elec ical ma e ials, manu ac u e o machine y
Adm. Sci. 2024,14, 241 4 o 20
and equipmen , elec ici y and gas, cus om so wa e de elopmen , and de elopmen o
cus omizable so wa e.
The sec o s we e chosen acco ding o hei p esence and impo ance in he B azilian
economy. Fo his pu pose, he sec o s wi h he highes sha e o agg ega e g oss domes ic
p oduc (GDP) om 2011 o 2017 we e adop ed. When ou lining he me hodological ame-
wo k o assessing inno a i e pe o mance in he a ious sec o s o he B azilian economy,
i e key indica o s we e selec ed ha co e di e en dimensions o he inno a ion p ocess.
2.2. E alua ion S uc u e o he PROMETHEE II Me hod
Behzadian e al. (2010), sugges ha mul ic i e ia decision-making me hods a e o en
used when analyzing many al e na i es based on con lic ing c i e ia. Roy (1996) a icula es
ha mul ic i e ia me hods add ess speci ic p oblems such as choice (P.
α
), so ing (P.
β
), and
o de ing (o anking, P.γ).
Making a simplis ic summa y o he mul ic i e ia analy ical p ocess, i looks o
ad an ages and disad an ages and hen compa es hem un il i becomes clea which is he
bes al e na i e, which is he one ha makes he bes use o he c i e ia conside ed, o , i
no he mos iable, which is he scena io ha comes closes o he op imum (De Ca alho
e al. 2022;Liu and Liu 2024).
Mul ic i e ia decision analysis (MCDA) is widely used in he li e a u e and can be
conduc ed using a ious p e e ence anking o ganiza ion me hods o en ichmen e al-
ua ion (PROMETHEE). Ka asakal e al. (2022) e alua ed wo classi ica ion app oaches
wi h PROMETHEE o de e mine weigh s and h eshold alues inspi ed by da a en el-
opmen analysis (DEA). Guney e al. (2020) applied he PROMETHEE me hod o assess
co po a e go e nance quali y in U.S. companies. Husin e al. (2024) conduc ed a s udy on
he physicochemical p ope ies o d ugs o enal cance ea men . Using a mul ic i e ia
decision-making app oach, he au ho s employ PROMETHEE II o classi y he a ge d ugs
o he s udy. Mi e al. (2024) assessed he isk o disas e o educa ional in as uc u e in
moun ainous egions using he PROMETHEE-II me hod. Ano he con ibu ion is made
by Wang e al. (2024), who analyze ba ie s o adop ing esilience in he ood supply
chain indus y.
De Ca alho e al. (2018) employed he PROMETHEE II me hod o e alua e he
ela i e impo ance o ac o s ela ed o in o ma ion echnology ou sou cing conside -
ing a g oup o companies in a B azilian me opoli an egion. Sil a e al. (2023) also
applied PROMETHEE II o e alua e he impo ance o ac o s ela ed o in o ma ion ech-
nology ou sou cing, which is conside ed a echnological inno a ion hub in a B azilian
ci y.
De Ca alho e al. (2020)
used PROMETHEE I and II o assess he c ea i e–inno a i e
po en ial o B azilian ci ies, c ea ing a anking o he nine capi als o he No heas Region.
In he con ex o he esea ch epo ed in his a icle, an ou anking model om he
PROMETHEE amily was de eloped using Visual PROMETHEE so wa e ( e sion 1.4.0),
which is eely accessible. This model’s selec ion elies on he non-compensa o y cha ac e -
is ics be ween he adop ed c i e ia and he possibili y o analyzing each c i e ion in i s own
uni s, elimina ing scale e ec s.
The PROMETHEE II me hod, selec ed o applica ion in his s udy, wo ks wi h o de -
ing p oblems (P.
γ
) and has wo essen ial phases: one dedica ed o cons uc ing ou anking
ela ions and he o he dedica ed o explo ing hese ela ions (B ans and Vincke 1985a,
1985b). The ela ed p ocedu e can be explained in he ollowing s eps (Behzadian e al.
2010;B ans and Vincke 1985b;De Ca alho e al. 2018):
S ep 1: De e mina ion o de ia ion based on pai wise compa isons:
dj(a,b)=gj(a)−gj(b)(1)
whe e dj(a,b) is he di e ence be ween al e na i es aand b o each c i e ion.
S ep 2: Applica ion o p e e ence unc ion:
Pj(a,b)=Fjdj(a,b)j=1, · · · ,k(2)
Adm. Sci. 2024,14, 241 5 o 20
Pj(a,b) is he p e e ence o al e na i e aconce ning al e na i e b o each c i e ion as a
unc ion o dj(a,b).
S ep 3: Calcula ion o a global p e e ence index:
∀a,b∈Aπ(a,b)=∑k
j=1Pj(a,b)wj(3)
whe e
π
(a,b) o ao e b( om 0 o 1) is he weigh ed sum o P
j
(a,b) o each c i e ion, and
wjis he weigh associa ed wi h he j h c i e ion.
S ep 4: Calcula ion o he inpu and ou pu lows:
Φ+(a)=1
n−1∑b∈Aπ(a,b)(4)
Φ−(a)=1
n−1∑b∈Aπ(b,a)(5)
whe e Φ+(a) is he posi i e low and Φ−(a) is he nega i e low o each al e na i e.
S ep 5: Calcula ion o he ne low:
Φ(a)=Φ+(a)−Φ−(a)(6)
whe e Φ(a) is he ne low o each al e na i e.
This esea ch applied he usual c i e ion de ined h ough (7) in S ep 2:
P(x)0∀dj(a,b)≤0
1∀dj(a,b)>0(7)
The ollowing sen ences de ine he bina y ela ions P e e ences (P) and Indi e ences
(I) in PROMETHEE II:
aPb i Φ(a)>Φ(b)(8)
aIb i Φ(a)=Φ(b)(9)
A he end o his p ocess, a comple e p eo de is c ea ed using he ne low, deli e ing
he anking o he al e na i es.
2.3. Applica ion o he PROMETHEE II Me hod in Inno a ion Ecosys ems
In e ms o inpu da a, he i s inpu selec ed was expendi u e on inno a ion, as his
is undamen al da a o cap u ing companies’ inancial commi men o inno a ion. The
second and hi d inpu s a e he p opo ion o employees wi h ad anced deg ees, in his
case, hose wi h mas e ’s and unde g adua e deg ees. S udies indica e ha companies
wi h highly quali ied p o essionals ha e a g ea e p opensi y o inno a e, as ad anced
educa ion is co ela ed wi h he abili y o abso b knowledge and c ea i i y.
In his sense, ne e enue was selec ed because i is an essen ial inancial indica o
o e ing a global pe spec i e on companies’ economic pe o mance. Finally, o ound o he
model, he pe cen age sha e o new p oduc s in domes ic sales in oduces a mo e de ailed
analysis o he pe cen age sha e anges, en iching he e alua ion and p o iding a mo e
e ined unde s anding o inno a i e pe o mance. Table 1summa izes hese indica o s
e alua ed wi h he same deg ee o impo ance, whe e h ee co espond o he inpu s o
eed he model and s imula e he p ocess s udied, and wo indica o s make up he ou pu s.
These indica o s help ou line an o e iew o he impac o inno a ion on ope a ions
and he ma ke , p o iding in e es ing insigh s by always conside ing a s anda d se o
ac o s associa ed wi h inno a ion, and enabling an unde s anding amed wi hin he same
compa ison ule. Dziallas and Blind (2019) and Taques e al. (2021) p esen a su ey o
indica o s o use in inno a ion assessmen s. Bo h conside inno a ion om a sec o al
pe spec i e and conside compa abili y wi h equi alen me ics.
Adm. Sci. 2024,14, 241 6 o 20
Table 1. Desc ip ion o model indica o s.
Indica o Desc ip ion
Objec i es
P ocess
Spending by companies
on inno a ion (BRL)
Spending on inno a i e ac i i ies
includes in e nal esea ch and
de elopmen (R&D) ac i i ies and
ex e nal R&D p ocu emen , as well as
o he ac i i ies.
Maximize Inpu
Pos g adua e (%)
Pe cen age o wo ke s wi h
pos g adua e deg ees in he wo k o ce
by sec o
as a p opo ion o he o e all numbe o
wo ke s employed.
Maximize Inpu
G adua ion (%)
Pe cen age o wo ke s in he wo k o ce
wi h a bachelo ’s deg ee by sec o as a
p opo ion o he o e all numbe o
wo ke s employed.
Maximize Inpu
Ne e enue (BRL) Ne e enue om sales o p oduc s in
each sec o . Maximize Ou pu
Pe cen age sha e o new
o subs an ially imp o ed
p oduc s in o al
domes ic sales (%)
Re e s o he p opo ion o a company’s
domes ic sales a ibu ed o new o
subs an ially imp o ed p oduc s.
Maximize Ou pu
Fu he mo e, he PINTEC su ey co e s companies ac oss all indus ies and sec o s
wi hou dis inc ion. This ein o ces he no ion ha indica o s, bo h om he inno a ion
pe spec i e and he inancial pe spec i e, can be collec ed o any o ganiza ion and, conse-
quen ly, any indus y. Finally, we chose accoun ing me ics ha can b oadly apply o bo h
manu ac u ing and se ice companies. This con as s wi h me ics like o al asse s, pa en s,
adema ks, machine y, and equipmen , among o he s, whose empi ical e idence shows
signi ican di e ences be ween indus ies.
To seek a be e e alua ion based on a compa ison, wo models we e c ea ed: one
comp ising he h ee yea s o he i s ime-lapse and he second con aining he h ee yea s
immedia ely a e wa d, cha ac e izing he ollowing his o ical se ies (see Table 2).
Table 2. Es ablishing he ime-lapse images o he models.
Inpu s
(Yea s)
Ou pu s
(Yea s)
Model 1 2011
Adm. Sci. 2024, 14, x FOR PEER REVIEW 6 o 22
Table 1. Desc ip ion o model indica o s.
Indica o Desc ip ion Objec i es P ocess
Spending by companies on
inno a ion (BRL)
Spending on inno a i e ac i i ies
includes in e nal esea ch and
de elopmen (R&D) ac i i ies and
ex e nal R&D p ocu emen , as well
as o he ac i i ies.
Maximize Inpu
Pos g adua e (%)
Pe cen age o wo ke s wi h
pos g adua e deg ees in he
wo k o ce by sec o
as a p opo ion o he o e all numbe
o wo ke s employed.
Maximize Inpu
G adua ion (%)
Pe cen age o
wo ke s in he
wo k o ce wi h a bachelo ’s deg ee
by sec o as a p opo ion o he
o e all numbe o wo ke s
employed.
Maximize Inpu
Ne e enue (BRL) Ne e enue om sales o p oduc s
in each sec o . Maximize Ou pu
Pe cen age sha e o new o
subs an ially imp o ed
p oduc s in o al domes ic sales
(%)
Re e s o he p opo ion o a
company’s domes ic sales a ibu ed
o new o subs an ially imp o ed
p oduc s.
Maximize Ou pu
These indica o s help ou line an o e iew o he impac o inno a ion on ope a ions
and he ma ke , p o iding in e es ing insigh s by always conside ing a s anda d se o
ac o s associa ed wi h inno a ion, and enabling an unde s anding amed wi hin he
same compa ison ule. Dziallas and Blind (2019) and Taques e al. (2021) p esen a su ey
o indica o s o use in inno a ion assessmen s. Bo h conside inno a ion om a sec o al
pe spec i e and conside compa abili y wi h equi alen me ics.
Fu he mo e, he PINTEC su ey co e s companies ac oss all indus ies and sec o s
wi hou dis inc ion. This ein o ces he no ion ha indica o s, bo h om he inno a ion
pe spec i e and he inancial pe spec i e, can be collec ed o any o ganiza ion and,
consequen ly, any indus y. Finally, we chose accoun ing me ics ha can b oadly apply
o bo h manu ac u ing and se ice companies. This con as s wi h me ics like o al asse s,
pa en s, adema ks, machine y, and equipmen , among o he s, whose empi ical e idence
shows signi ican di e ences be ween indus ies.
To seek a be e e alua ion based on a compa ison, wo models we e c ea ed: one
comp ising he h ee yea s o he i s ime-lapse and he second con aining he h ee yea s
immedia ely a e wa d, cha ac e izing he ollowing his o ical se ies (see Table 2).
Table 2. Es ablishing he ime-lapse images o he models.
Inpu s
(Yea s) Ou pu s
(Yea s)
Model 1 2011 2014
Model 2 2014 2017
As shown in Table 2, he inpu da a we e collec ed in p e ious yea s compa ed o he
ou pu da a because i akes a ce ain amoun o ime o he in es men s in he mos
a ied scena ios o be p ocessed, and only hen can he esul s be achie ed. As his
2014
Model 2 2014
Adm. Sci. 2024, 14, x FOR PEER REVIEW 6 o 22
Table 1. Desc ip ion o model indica o s.
Indica o Desc ip ion Objec i es P ocess
Spending by companies on
inno a ion (BRL)
Spending on inno a i e ac i i ies
includes in e nal esea ch and
de elopmen (R&D) ac i i ies and
ex e nal R&D p ocu emen , as well
as o he ac i i ies.
Maximize Inpu
Pos g adua e (%)
Pe cen age o wo ke s wi h
pos g adua e deg ees in he
wo k o ce by sec o
as a p opo ion o he o e all numbe
o wo ke s employed.
Maximize Inpu
G adua ion (%)
Pe cen age o
wo ke s in he
wo k o ce wi h a bachelo ’s deg ee
by sec o as a p opo ion o he
o e all numbe o wo ke s
employed.
Maximize Inpu
Ne e enue (BRL) Ne e enue om sales o p oduc s
in each sec o . Maximize Ou pu
Pe cen age sha e o new o
subs an ially imp o ed
p oduc s in o al domes ic sales
(%)
Re e s o he p opo ion o a
company’s domes ic sales a ibu ed
o new o subs an ially imp o ed
p oduc s.
Maximize Ou pu
These indica o s help ou line an o e iew o he impac o inno a ion on ope a ions
and he ma ke , p o iding in e es ing insigh s by always conside ing a s anda d se o
ac o s associa ed wi h inno a ion, and enabling an unde s anding amed wi hin he
same compa ison ule. Dziallas and Blind (2019) and Taques e al. (2021) p esen a su ey
o indica o s o use in inno a ion assessmen s. Bo h conside inno a ion om a sec o al
pe spec i e and conside compa abili y wi h equi alen me ics.
Fu he mo e, he PINTEC su ey co e s companies ac oss all indus ies and sec o s
wi hou dis inc ion. This ein o ces he no ion ha indica o s, bo h om he inno a ion
pe spec i e and he inancial pe spec i e, can be collec ed o any o ganiza ion and,
consequen ly, any indus y. Finally, we chose accoun ing me ics ha can b oadly apply
o bo h manu ac u ing and se ice companies. This con as s wi h me ics like o al asse s,
pa en s, adema ks, machine y, and equipmen , among o he s, whose empi ical e idence
shows signi ican di e ences be ween indus ies.
To seek a be e e alua ion based on a compa ison, wo models we e c ea ed: one
comp ising he h ee yea s o he i s ime-lapse and he second con aining he h ee yea s
immedia ely a e wa d, cha ac e izing he ollowing his o ical se ies (see Table 2).
Table 2. Es ablishing he ime-lapse images o he models.
Inpu s
(Yea s) Ou pu s
(Yea s)
Model 1 2011 2014
Model 2 2014 2017
As shown in Table 2, he inpu da a we e collec ed in p e ious yea s compa ed o he
ou pu da a because i akes a ce ain amoun o ime o he in es men s in he mos
a ied scena ios o be p ocessed, and only hen can he esul s be achie ed. As his
2017
As shown in Table 2, he inpu da a we e collec ed in p e ious yea s compa ed o he
ou pu da a because i akes a ce ain amoun o ime o he in es men s in he mos a ied
scena ios o be p ocessed, and only hen can he esul s be achie ed. As his p oblem makes
i impossible o ob ain esul s ins an ly, he cu en s udy decided o use he da a desc ibed
in Table 2.
To build he mul ic i e ia model, i is necessa y o es ablish he objec i e (maximize o
minimize) o each c i e ion, and in his sense, he maximize di ec ion was adop ed o all
he c i e ia. In o he wo ds, inc easing he alues o all he c i e ia adop ed in his s udy
means mo ing owa ds achie ing be e esul s in e ms o inno a ion.
3. Resul s and Discussion
This sec ion discusses he da a and esul s o he assessmen o B azilian inno a ion
sys ems. Sec ion 3.1 epo s a comp ehensi e explo a ion o desc ip i e s a is ics, which
Adm. Sci. 2024,14, 241 7 o 20
se e as a undamen al aspec in unde s anding he b ead h o his s udy. Mo ing o wa d
o Sec ion 3.2, he mul ic i e ia analysis is de eloped using PROMETHEE II. Based on a
ne low amewo k, his me hodology acili a es he anking o sec o s by sub ac ing
ou lows om in lows, as desc ibed in Equa ion (6). This p ocess elucida es and highligh s
sec o al pe o mances om 2011 o 2014, epo ing no able indings such as he exempla y
pe o mance o chemical p oduc manu ac u ing. In Sec ion 3.3, he esea ch implica ions
a e discussed, sc u inizing sec o al dynamics o e ime while conside ing unique sec o
cha ac e is ics and he nuanced impac s o inno a ion in es men .
3.1. Desc ip i e S a is ics
This pu sui aimed o os e a comp ehensi e unde s anding o he s udied scena io,
he eby acili a ing he iden i ica ion o pa e ns, conduc ing in e g oup compa isons, and
enabling assessmen s o da a dispe sion. A comp ehensi e p esen a ion o hese desc ip i e
s a is ics can be ound in Table 3.
Table 3. Desc ip i e s a is ics o Model 1 a iables.
Inno a ion
Spending in
2011 (BRL)
Pos g adua e
% in 2011
G adua ion
% in 2011
Ne Re enue
in 2014
% o Subs an ially
Imp o ed
P oduc s in To al
Sales in 2014
Max 7,814,360.57 23.81 58
525,606,581.00
57
Q3 2,188,277.02 11.02 52
186,762,263.82
34
A e age
2,266,535.66 9.09 43
150,243,708.98
27
Median 1,793,904.56 6.25 41
112,821,141.50
25
Q1 667,002.92 5.37 35 53,669,513.00 16
Min 310,073.74 0.32 28 12,719,474.00 7
In his i s model, which co e s he ime se ies om 2011 o 2014, he clo hing and
accesso ies sec o had he lowes employmen o employees wi h unde g adua e and
pos g adua e deg ees in 2011. This may indica e ha his sec o has low sala ies and low
p oduc ion complexi y.
The ood p oduc s manu ac u ing sec o has he highes alues o he indica o s
ela ing o expendi u e by companies on inno a ion in 2011 and ne e enue in 2014.
These igu es may be di ec ly ela ed, bu mo e de ailed analysis is needed o con i m
his ela ionship.
The cus om so wa e de elopmen sec o is p ojec ed o ha e he lowes alues in
he indica o s o expendi u es made by companies in inno a ion” and in ne e enue. In
o he wo ds, e en hough his line o business has in es ed less inancially han o he lines
o business in inno a ion issues, i has s ill achie ed mo e han 50% o new o imp o ed
i ems in o al in e nal sales. This phenomenon may be linked o possible pas in es men s,
which made he b anch in es less because i al eady has a solid base o achie e hese le els
o inno a ion.
Box plo g aphs in Figu e 1we e gene a ed o aid in isualizing and analyzing he
desc ip i e da a, delinea ing he alues co esponding o he u ilized c i e ia. These g aphs
a e sys ema ically a anged o align wi h he sequence o indica o s ou lined in Table 3.
No ably, he ini ial plo pe ains o he expendi u es on inno a ion in 2011, as depic ed
in Figu e 1a. Mos o he da a a e concen a ed below he a e age, wi h a ew ou lie s
abo e i . Two ou lie s in he ood and chemical p oduc s manu ac u ing sec o s may ha e
inc eased he a e age alue. The da a se seems o ha e a posi i e asymme ic dis ibu ion,
whe e he highe alues a e mo e dispe sed han he lowe alues.
Adm. Sci. 2024,14, 241 8 o 20
Figu e 1. Box plo s o Model 1 a iables.
The box plo (Figu e 1b) shows ha he pe cen age o employees wi h pos g adua e
deg ees is concen a ed in a mode a e ange, wi h one ou lie , which in his case co esponds
o he elec ici y and gas sec o . In his scena io, i can be in e ed ha he e is a g ea e
concen a ion o da a abo e he a e age bu wi h a s ong endency owa d he e ogenei y.
The box plo (Figu e 1c), which shows he pe cen age o wo ke s wi h a deg ee, shows
ha mos o he da a a e g ouped in a mode a e ange, wi h a easonable dispe sion
a ound he a e age. The p esence o ou lie s indica es some a iabili y in he da a, bu he
dis ibu ion gene ally appea s ela i ely concen a ed and uni o m.
The box plo o ne e enue (Figu e 1d) shows only one ou lie , which in his case
e e s o he ood manu ac u ing sec o . Howe e , he da a dis ibu ion sugges s posi i e
asymme y since he median is below he mean, and he no able di e ence be ween Q3
and Q1 indica es signi ican a iabili y. The lowes alue iden i ied in he da a is BRL
12,719,474.00, and he highes is BRL 525,606,581.00, indica ing he p esence o ou lie s a
bo h ex emes.
The box plo (Figu e 1e) in e p e a ion o he enhanced p oduc sha e ange da a
sugges s ha mos alues a e concen a ed in a mode a e ange. Howe e , he p esence o
ou lie s, especially on he uppe side, highligh s signi ican a iabili y in he da a. Highe
alues in luence he a e age, indica ing a posi i e asymme y in he dis ibu ion.
Table 4shows he desc ip i e s a is ics o Model 2, which co e s he ange o agg e-
ga ed da a om 2014 o 2017.
Adm. Sci. 2024,14, 241 15 o 20
This scena io is obse ed in some sec o s ac oss he h ee-yea pe iods. In he man-
u ac u e o ood p oduc s, he nega i e signal o he pe cen age o g adua es in he i s
h ee-yea pe iod u ned posi i e in he second, demons a ing g ea e ele ance o he in-
dica o .
Fo elec ici y and gas, he pe cen age o g adua es swi ched om posi i e o nega i e
be ween he pe iods. In cus om so wa e de elopmen , he p opo ion o pos g adua es
e e sed om posi i e o nega i e be ween he h ee-yea pe iods.
In he manu ac u e o machine y and equipmen , he p opo ion o g adua es changed
om posi i e o nega i e, while he di ec ion o ne e enue was he opposi e be ween
he in e als. In he manu ac u e o elec ical ma e ials, he p opo ion o g adua es and
pos g adua es changed om nega i e o posi i e, whe eas he di ec ion o ne e enue
was he opposi e.
In cus omizable so wa e de elopmen , all i e indica o s e e sed hei signals, wi h
he pe cen age o g adua es and he pe cen age sha e o new o subs an ially imp o ed
p oduc s in o al domes ic sales changing om nega i e o posi i e.
The e o e, he esul s o he me hod allow o an e alua ion o how indica o s ela ed
o he ele ance o human capi al and inno a ion can a ec he inancial pe spec i e. When
p io i izing he con ex o a sec o , i becomes clea ha i is no s a ic, as i is in luenced by
changes in bo h he in e nal and ex e nal en i onmen s. Moni o ing o e ime allows o
no only unde s anding possible sho - and medium- e m s a egy adap a ions bu also
assessing each sec o ’s p io i ies o e ime by iden i ying he mos app op ia e me ics.
I is also impo an o men ion ha B azil has a concen a ion o sec o s h oughou i s
e i o y. This concen a ion is no uni o m, so i is only na u al ha ce ain sec o s s udied
in his s udy a e loca ed in speci ic s a es, which means ha he bene i s o de elopmen
e ec s hey b ing a e na u ally no sp ead ac oss he en i e na ional e i o y, as is he
demand ha he sec o s lack, such as he a ailabili y o skilled labo , especially hose wi h
unde g adua e and pos g adua e deg ees, which a e di e en in ce ain B azilian egions
o s a es.
By analyzing he si ua ion and dynamics o he budge s o he Minis y o Science,
Technology, and Inno a ions and he alloca ion o esou ces om he Na ional Fund o
Scien i ic and Technological De elopmen , i is e iden ha B azil is s uggling o ace
he challenges o he 21s cen u y and in e na ional compe i i eness among he leading
de eloped na ions. The coun y’s unding bases and science, echnology, and inno a ion
models a e in c isis (Ta a es 2024). The e is a econcen a ion o in es men s in science,
echnology, and inno a ion in al eady de eloped egions o he coun y based on he execu-
ion o no eimbu sable esou ces om he Na ional Fund o Scien i ic and Technological
De elopmen . The p e ious s a egy o alloca ing 30% o he esou ces o egions such as
he No h and No heas Regions is no longe su icien o mi iga e egional asymme ies
(McManus e al. 2022).
This concen a ion is no uni o m, esul ing in he localiza ion o ce ain sec o s
analyzed in his s udy in speci ic s a es. This implies ha hei bene i s and de elopmen al
e ec s a e no e enly dis ibu ed ac oss he na ional e i o y. This dispa i y mani es s
i sel , o example, in he demand o sec o s lacking in a eas such as he a ailabili y o
quali ied labo , pa icula ly hose wi h highe educa ion and pos g adua e deg ees, which
a y be ween di e en egions o s a es in B azil. The unding bases o science, echnology,
and inno a ion conce ning he needs o he na ional knowledge p oduc ion sys em a e
cu en ly limi ed (McManus e al. 2023).
Based on he esul s o his s udy, o achie e a high le el o inno a ion, a obus ecosys-
em is necessa y, including a well-es ablished esea ch and de elopmen in as uc u e,
policies o incen i ize inno a ion, a quali y educa ion sys em ha ains highly quali ied
p o essionals, and a egula o y en i onmen ha acili a es he c ea ion and g ow h o new
businesses (Be nd e al. 2024). Howe e , one o he main in e nal ba ie s companies ace
is he lack o digi al compe encies among leade s (Ca alho e al. 2023). Manage s do no
unde s and eme ging echnologies o how hey can be s a egically applied o imp o e
Adm. Sci. 2024,14, 241 16 o 20
p ocesses, p oduc s, and se ices (Kowalski e al. 2024). Addi ionally, companies ace
di icul ies a ac ing and e aining alen due o high demand and a sho age o quali ied
p o essionals.
Al hough his esea ch p esen s a no el con ibu ion h ough he PROMETHEE II
me hod o inno a ion in B azil, a ac o ha limi s compa abili y wi h o he s udies using
he same me hod, he e is con e gence wi h indings ha demons a e he impo ance o
inno a ion indica o s in explaining he inancial pe o mance o o ganiza ions.
The e is a weal h o empi ical e idence in he li e a u e ha explo es his ela ionship.
Speci ically, wi h da a on he numbe o g adua es, mas e ’s deg ee holde s, o PhDs wi hin
a company, o hei espec i e p opo ions, he con ibu ions o Guo e al. (2012), Han and
Bae (2014), de Oli ei a e al. (2018), San os e al. (2018), and Dankwah e al. (2024) can be
highligh ed. This same body o esea ch also u ilizes R&D in es men indica o s o simila
me ics ha demons a e he inno a i e e o s o companies.
As wi h he e idence om his esea ch, bo h spending on inno a ion and employee
educa ion a e shown o be app op ia e indica o s o es ing his ela ionship. Despi e di -
e ences in me hodology, s udying his ela ionship emains ele an . Simila ly, he sec o al
o indus y pe spec i e can e eal di e ences in he ela ionship be ween inno a ion and
inancial pe o mance, as sugges ed by he s udies o Kos opoulos e al. (2011), Gök and
Peke (2017), Chouaibi (2021), and Lu and Chesb ough (2022).
Finally, i is wo h no ing ha his s udy was ca ied ou using a low numbe o e alu-
a ion c i e ia, which can ce ainly be expanded in u u e s udies and applied o s a is ical
es s. The explo a o y na u e o his s udy has no been eplica ed in any ecen esea ch in
he li e a u e, and he model p oposed he e is also a amewo k o u u e analysis.
4. Conclusions
Th oughou his s udy, an e o was made o e alua e and unde s and inno a i e
pe o mance in he a ious sec o s o he B azilian economy using a mul ic i e ia app oach
based on he PROMETHEE II me hod.
F om hese esul s, i is possible o see which sec o s pe o med bes in each his o ical
se ies and which c i e ia made hem ise o all in he anking. These indings a e o
go e nmen bodies o o mula e incen i e policies, o example, o sec o s ha canno
exi he lowes posi ions, such as (i) clo hing and accesso ies manu ac u ing and (ii) ubbe
and plas ics manu ac u ing. These sec o s we e anked lowes in he anking lis s o bo h
models, and he nega i e c i e ion o hese sec o s was he numbe o employees wi h
unde g adua e and pos g adua e deg ees.
In o he wo ds, wi h hese indings, go e nmen bodies can encou age o mal educa-
ion o hese sec o s o b ing quali ied p o essionals in o he ma ke . In addi ion, inancial
incen i es, such as c edi access policies o inno a i e p ocesses, can be o mula ed.
Ano he impo an inding o his s udy is he sec o o ganiza ions. A he op o bo h
models, he e we e posi i e c i e ia, such as spending on inno a ion and he numbe o
quali ied employees wi h academic quali ica ions. F om his, i is possible o in e ha
hese speci ic c i e ia can in luence o ganiza ions’ pe o mance.
This s udy’s manage ial con ibu ion is ha i allows manage s o de elop a oadmap
o indus y sec o s’ digi al ansi ion aligned wi h business and managemen s a egies.
This amewo k p o ides a s uc u ed app oach o iden i ying and implemen ing eme ging
echnologies, p omo ing digi al in eg a ion a all le els o he o ganiza ion.
I is plausible o en ep eneu s o see hese indings as a way o imp o ing hei busi-
nesses and o ocus on hese speci ic c i e ia when seeking inno a ion in hei companies.
A his poin , we would like o poin ou ha u he s udies could in es iga e how he
beha io o hese ma ke s is shaped by he maximiza ion o his indica o in a mul ic i e ia
model. Acco ding o his s udy, businesses can in e ha imp o ed o inno a i e p oduc s
can a ec e enue o e ime.
F om a me hodological pe spec i e, one limi a ion is he impossibili y o iden i ying,
he p ac ical easons, why he c i e ia we e posi i e o nega i e o he economic sec o s
Adm. Sci. 2024,14, 241 17 o 20
selec ed o analysis. In o he wo ds, al hough he esul s show which c i e ia boos ed
o lowe ed he sec o ’s anking, i was no possible o de e mine he eal easons o i
eaching ha le el. Bu i is hoped ha his esul will encou age s udies o de elop his
unde s anding.
This wo k also limi s i sel o no assigning weigh s o he c i e ia, e en hough i is
known ha his can di ec ly impac lows and, consequen ly, he anking o sec o s. I is
sugges ed ha u he in es iga ions can assign hese weigh s o he c i e ia, such as he
Roc Weigh classi ica ion.
Rega ding da a cha ac e iza ion, his s udy only add esses wo speci ic pe iods (2011
o 2014 and 2014 o 2017) g ouped in o wo his o ical se ies, which sugges s ha i is
possible ha inno a i e p ocesses ha e no ye aken place, as he analysis does no e en
conside a decade. Simila ly, he expansion o bo h inno a ion indica o s and he inancial
pe spec i e can p o ide a b oade unde s anding o his phenomenon unde s udy.
Finally, using gene al da a om all egions o he coun y is also a limi a ion o
his s udy, lea ing aside he demog aphic, economic, and social conside a ions o many
B azilian loca ions.
In u u e wo k, i is sugges ed o s udy PINTEC mic oda a o de e mine whe he
he beha io s ou lined he e a e he same ac oss B azil’s egions and s a es. Wi h his
sample se , i is possible o access o e 200 answe ed ques ions ega ding he pe spec i e
o o ganiza ional inno a ion. Combined wi h he mic oda a om he Annual Indus ial
Su ey (PIA) and he Annual Se ices Su ey (PAS), bo h conduc ed by he IBGE, a ious
o he inancial pe o mance me ics can be ob ained, hus p o iding a deepe pe spec i e
on his ela ionship. In addi ion, mo e comp ehensi e s udies a e sugges ed, inco po a ing
ex e nal ac o s, he size o each company, and he business sec o .
Au ho Con ibu ions: Concep ualiza ion, A.R.S.N. and M.G.G.d.S.; me hodology, A.R.S.N., M.G.G.d.S.,
and T.C.C.N.; so wa e, A.R.S.N.; alida ion, F.H.T., T.C.C.N., T.P., V.D.H.d.C., and M.B.d.S.M.; o mal
analysis, A.R.S.N. and M.G.G.d.S.; in es iga ion, M.G.G.d.S.; esou ces, T.C.C.N.; da a cu a ion,
A.R.S.N. and M.G.G.d.S.; w i ing—o iginal d a p epa a ion, A.R.S.N., M.G.G.d.S., F.H.T., T.P., and
V.D.H.d.C.; w i ing— e iew and edi ing, T.P., V.D.H.d.C., and M.B.d.S.M.; isualiza ion, A.R.S.N.
and M.G.G.d.S.; supe ision, T.C.C.N. and F.H.T.; p ojec adminis a ion, F.H.T.; unding acquisi ion,
T.C.C.N. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding: This esea ch was suppo ed by he Pos g adua e De elopmen P og am (PDPG) S a egic
Pos doc o al o he B azilian go e nmen , wi h unding om he esea ch unding agency CAPES
(Coo dina ion o he Imp o emen o Highe Educa ion Pe sonnel Founda ion), esea ch unding
88887.799539/2022-00. Also by he esea ch p oduc i i y g an 309950/2022-8, unded by he Na ional
Council o Scien i ic and Technological De elopmen (CNPq), Financial Code 001, B azil.
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : The aw da a suppo ing he conclusions o his a icle will be made
a ailable by he au ho s upon eques .
Acknowledgmen s: Mic oso Copilo , G amma ly P o so wa e, and he Cu ie pla o m so wa e
we e used o some ansla ions and o e iew he p oduced ex . A e using hese ools, he au ho s
made he necessa y edi s, aking ull esponsibili y o he ex ual con en o his a icle.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
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