Mas e in Economics: Empi ical Applica ions and Policies
Uni e si y o he Basque Coun y UPV/EHU
Mas e Thesis
Technology ans e s om uni e si ies and inno a ion
Mi ian Oiz Chueca
Supe ised by Ja ie Ga deazabal Ma ías
July 22nd, 2024
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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Table o con en s
1. INTRODUCTION …………………………………………………………… 4
2. LITERATURE REVIEW ……………………………………………………. 5
3. DATA DESCRIPTION ……………………………………………………… 6
3.1. Va iable de ini ion ……………….…………………...…………….…… 7
3.2. Desc ip i e analysis ………………………..…………………….……… 9
4. METHODOLOGY …………………………………………...……………... 10
5. RESULTS …………………………………………………………………... 12
5.1. E ec o collabo a ion wi h uni e si ies ……………….……………… 12
5.2. Compa ison wi h he e ec o collabo a ion wi h o he companies ……. 20
5.3. Compa ison wi h he e ec o collabo a ion wi h any ype o
o ganiza ion ……………………………………………………………. 21
6. CONCLUSIONS …………………………………………….……………... 22
7. REFERENCES ……………………………………………………….…….. 24
8. APPENDIX ..………………………………………………………………. 26
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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Abs ac
This s udy uses causal in e ence me hods o assess he impac o uni e si y esea ch and
de elopmen (R&D) ans e s on i m inno a ion, u ilizing he Spanish su ey (PITEC)
spanning he pe iod om 2003 o 2016. In pa icula , mul i a ia e Nea es Neighbo
Ma ching (NNM) me hod is employed o he es ima ion o he A e age T ea men E ec
on he T ea ed (ATET). The indings indica e ha uni e si y collabo a ion has a mos ly
posi i e impac on a ange o inno a ion ou comes, including p ocess inno a ion, p oduc
inno a ion, and pa en egis a ion, bu i mainly no signi ican . These indings lend
suppo o he p oposi ion ha uni e si y R&D ans e s a e an impo an ac o in
s imula ing i m inno a ion. Finally, he esea ch acknowledges he limi a ions o i s
me hodology and sugges s a enues o u u e esea ch.
Key wo ds: R&D ans e s, inno a ion, uni e si ies
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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1. INTRODUCTION
In he con empo a y business en i onmen , cha ac e ized by apid change and in ense
compe i ion, he capaci y o inno a e is o pa amoun impo ance o i ms seeking o
succeed and gain a compe i i e ad an age. Uni e si ies, wi h hei subs an ial in ellec ual
capi al and pionee ing esea ch, se e as a impo an condui o ins illing an en i onmen
conduci e o inno a ion. In ligh o his, he e has been a no able inc ease in he numbe
o uni e si y-indus y collabo a ions, wi h i ms p oac i ely engaging wi h uni e si ies
in o de o gain access o hei expe ise and knowledge esou ces.
This esea ch explo es he complex in e ela ionship be ween uni e si y R&D
collabo a ion wi h i ms and his las ones’ inno a ion. This s udy speci ically examines
he impac o uni e si y collabo a ion on a i m's inno a i e pe o mance, encompassing
p ocess inno a ion, p oduc inno a ion, and pa en egis a ion. The analysis employs
da a om he Spanish su ey, PITEC (Panel de Inno ación Tecnológica, Panel o
Technological Inno a ion), which co e s R&D ans o ma ion in companies om 2003
o 2016. The su ey ga he s comp ehensi e da a on a ange o inno a ion- ela ed opics,
including uni e si y-indus y collabo a ion, inno a ion ou comes, and i m
cha ac e is ics, o be used o he esea ch analysis. The me hodology employed combines
mul i a ia e nea es neighbo ma ching, wi h accoun s o obse ed con ounding, and
di e ence-in-di e ence, which accoun s o ime in a ian unobse ed con ounding.
This esea ch is d i en by he esea ch ques ion: does he ans e o esea ch and
de elopmen (R&D) om uni e si ies o i ms lead o inc eased inno a ion in hose
i ms? By analyzing da a om he PITEC su ey and employing a obus me hodology,
his s udy aims o answe his ques ion and con ibu e o he unde s anding o he ole ha
his uni e si y ans e s plays in d i ing inno a ion in i ms. The analysis will commence
wi h a e iew o he ex an li e a u e, ollowed by a comp ehensi e accoun o he
a ailable da a and he me hodology o be employed. Subsequen ly, he indings will be
p esen ed, and some conclusions will be d awn.
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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2. LITERATURE REVIEW
The con e gence o academic esea ch and indus ial inno a ion ep esen s a
signi ican d i e o economic g ow h. This e iew examines he impac o uni e si y
esea ch and de elopmen (R&D) ans e s on i m inno a ion. This s udy examines he
ole o uni e si ies as ca alys s, acili a ing he ans o ma ion o knowledge in o cu ing-
edge p oduc s and p ocesses.
Se e al s udies suppo a posi i e associa ion be ween uni e si y echnology ans e
and i m inno a ion. Ga cía-Vega & Vicen e-Chi i ella (2020) demons a e a signi ican
ise in inno a i eness o i ms acqui ing R&D om uni e si ies. Ca boni & Medda
(2021) ein o ces his link, highligh ing he e ec i eness o uni e si y R&D in p omo ing
p oduc inno a ion. Fu he mo e, Li & Tan (2020) ind a posi i e spillo e e ec om
uni e si y R&D ac i i ies on i m inno a ion wi hin he same geog aphic loca ion.
The e ec i eness o uni e si y R&D ans e s depends on a ious ac o s. Bellucci &
Pennacchio (2015) emphasize he impo ance o a uni e si y's en ep eneu ial spi i and
he quali y o i s esea ch. Fi ms wi h open sea ch s a egies and a ocus on adical
inno a ion bene i mo e om uni e si y knowledge (Bellucci &
Pennacchio, 2015). Addi ionally, Ga cía-Vega & Vicen e-Chi i ella (2024) sugges ha
a i m's abso p i e capaci y, i s abili y o unde s and and u ilize ex e nal
knowledge, plays a c i ical ole in le e aging uni e si y R&D e ec i ely.
Uni e si y R&D ans e s can also gene a e posi i e ex e nali ies beyond di ec
knowledge acquisi ion. Ga cía-Vega & Vicen e-Chi i ella (2020) ind ha hese ans e s
enhance i ms' in e nal R&D capabili ies, po en ially c ea ing a i uous cycle o
inno a ion. Simila ly, Acos a e al. (2009) highligh he ole o uni e si y g adua es as a
sou ce o knowledge spillo e s, con ibu ing o new business o ma ion in high-
echnology sec o s.
Collabo a ion ne wo ks u he in luence he bene i s i ms de i e om uni e si y
R&D. Bolí a -Ramos (2017) inds ha i ms collabo a ing wi h uni e si ies in na ional
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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o egional ne wo ks show a s onge pa en ing p opensi y compa ed o hose wi hou
such collabo a ions. Howe e , Becke e al. (2023) sugges ha uni e si y spillo e s can
be limi ed, wi h some e idence o posi i e e ec s on pa en ing and new- o- ma ke
inno a ion in speci ic ci cums ances.
While uni e si y R&D ans e s o e signi ican ad an ages, challenges emain.
Kanama & Nishikawa (2015) iden i y a ious obs acles in inno a ion ac i i ies, such as
inancial and echnological limi a ions, ha d i e i ms o seek uni e si y
knowledge. Howe e , access o uni e si y knowledge may no always ansla e in o
p o i able inno a ion.
In conclusion, a g owing body o esea ch suppo s he posi i e impac o uni e si y
R&D ans e s on i m inno a ion. The e ec i eness o hese ans e s depends on ac o s
such as he i m's abso p i e capaci y, he uni e si y's esea ch en i onmen , and he
na u e o collabo a ion ne wo ks. Fu he esea ch is needed o explo e he mechanisms
unde lying uni e si y R&D spillo e s and iden i y s a egies o maximize hei bene i s
o i ms.
3. DATA DESCRIPTION
This sec ion p esen s a desc ip ion o he da abase used, he a iables employed o
he analysis, and he new a iables ha ha e been gene a ed om he exis ing ones. I
will conclude wi h a b ie desc ip i e analysis o he sample. In o de o asce ain he
in luence o collabo a ion wi h uni e si ies on o ganiza ional inno a ion, he p esen
s udy u ilizes an exis ing da abase om a Spanish su ey, namely PITEC, conduc ed
be ween 2003 and 2016.
The PITEC (Panel de Inno ación Tecnológica, Panel o Technological Inno a ion)
p ojec has he objec i e o ep esen ing he si ua ion and e olu ion o inno a i e
companies in Spain, as well as he de ec ion o oppo uni ies and needs in his ield. The
p ojec commenced in 2003 wi h he collabo a ion o he FECYT (Fundación Española
pa a la Ciencia y la Tecnología, Spanish Founda ion o Science and Technology) and
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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he Co ec Founda ion, wi h he inpu o a g oup o esea che s om a ious uni e si ies.
Howe e , his ceased o be ca ied ou in 2016.
The da a om his pe iod o e s mo e han 460 a iables de i ed om app oxima ely
12,000 companies su eyed om 2003 onwa d, acili a ing he cons uc ion o ime se ies
ha can be used o s udy he e olu ion and impac o inno a ion in he business sec o , as
well as o iden i y he di e se inno a ion s a egies employed by companies in ques ion.
As i is a ixed panel, an annual obse a ion is collec ed om each i m, which ensu es
ha he da a ob ained a e o high quali y and eliabili y. The panel o companies is
selec ed om he na ional su eys ca ied ou by he INE (Ins i u o Nacional de
Es adís ica, Na ional S a is ics Ins i u e) in he inno a ion sec o : "Su ey on
Technological Inno a ion in Companies" and "S a is ics on R&D ac i i ies".
3.1. Va iable de ini ion
As p e iously s a ed, he da abase comp ises a mul i ude o a iables measu ing
di e se quali ies, om which we ha e iden i ied hose pe inen o ou in es iga ion. The
p ima y a iable o in e es , which will se e as he basis o in e ence, is he ans e o
esea ch and de elopmen (R&D) unds om uni e si ies o i ms. They appea as
'Pu chase o R&D se ices in Spain/uni e si ies' and 'Pu chase o R&D se ices
ab oad/uni e si ies'. They ep esen he p opo ion o ex e nal R&D expendi u e in he
i m, along wi h he pu chase o se ices in o he en i ies, which we will la e addi ionally
analyze. F om hese, he main ea men a iable o he s udy has been c ea ed, which
akes alue o 1 i he i m has ecei ed ans e s om uni e si ies and 0 i i has no .
Fu he mo e, as in Ga cía-Vega and Vicen e-Chi i ella (2020), we ha e de ined a
class o i ms ha ha e been called "s a e s". This denomina ion is accompanied by he
yea in which he company collabo a es wi h a uni e si y o he i s ime ( i s ime i
ecei es ans e s). In his way, as many s a e a iables ha e been gene a ed as he e a e
yea s in he da abase, wi h a dummy ca ego y and a alue o 1 i he company is a s a e
ha yea and 0 o he wise. In able 1 he s a e coun o each yea can be seen. The
numbe o s a e s o each yea o he sample is sp ead o e he yea s, wi h all yea s
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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ha ing igu es in he app oxima e ange o be ween 400 and 800, excep yea 2014, wi h
mo e han 1800, and 2015 wi h 203 i ms.
Table 1 S a e s
( i s ime ecei ing ans e s)
Yea
Numbe o s a e s
2004
591
2005
884
2006
503
2007
631
2008
547
2009
516
2010
511
2011
468
2012
409
2013
426
2014
1826
2015
203
2016
575
Sou ce: Own elabo a ion wi h PITEC da a
The a iables employed as ea men a e he ‘s a e s’ ones discussed in he p eceding
pa ag aphs, wi h 2006 being he example yea : he p e- ea men pe iod is de ined as
spanning 2003 o 2005, while he pos - ea men pe iod, du ing which he e ec s o
ea men can be obse ed, is de ined as spanning 2006 o 2016. The ea ed g oup is
de ined as he i ms which commenced collabo a ion wi h uni e si ies in 2006, while he
con ol g oup is de ined as he i ms ha nei he collabo a ed wi h uni e si ies no any
o he o he en i ies.
As o he dependen a iables, di e en ou comes ha e been aken as indica o s o
he deg ee o inno a ion o inno a i e capaci y o he i ms. These a e whe he o no he
company has had a p ocess inno a ion in he p e ious wo yea s, whe he o no i has
had a p oduc inno a ion in he p e ious wo yea s, whe he o no i has had a pa en
applica ion and he numbe o pa en s egis e ed. The impac o collabo a ion be ween
companies and uni e si ies on he ou has been in es iga ed o e he cou se o he
ollowing yea s.
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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In closing, se e al con ol a iables ha e been selec ed o use as co a ia es in he
es ima ion o e ec s. These include he numbe o employees o he i m, he amoun o
physical capi al, he amoun o ex e nal esea ch and de elopmen expendi u e, he
amoun o in e nal esea ch and de elopmen expendi u e, he p esence o absence o
expo s, and inally, whe he he i m belongs o a business g oup.
3.2. Desc ip i e analysis
P io o es ima ing he e ec s in ques ion, a b ie desc ip i e analysis was conduc ed
o gain a comp ehensi e unde s anding o he sample. The da a a e p esen ed in Table 2,
which shows he numbe o obse a ions, he mean, and he s anda d de ia ion o he
ull sample, as well as o he obse a ions o i ms ha ha e ecei ed uni e si y ans e s
and hose ha ha e no , sepa a ely.
Table 2 Desc ip i e s a is ics
Full sample
Wi h uni e si y ans e s
Wi hou uni e si y ans e s
Obs.
Mean
S d. de .
Obs.
Mean
S d. de .
Obs.
Mean
S d. de .
T ea men Va i a b l e
T ans e s om
uni e si ies
171.511
0,261
0,439
44.812
1
0
126.699
0
0
Ou come a iables
P ocess inno a ion
135.798
0,467
0,498
9.110
0,704
0,457
126.688
0,451
0,498
P oduc inno a ion
135.799
0,464
0,498
9.110
0,744
0,437
126.689
0,445
0,497
Pa en s
135.797
0,101
0,301
9.109
0,311
0,463
126.688
0,086
0,281
Numbe o pa en s
125.717
0,487
5,938
8.325
2,238
14,385
117.392
0,363
4,781
Con ol a iables
Employmen
135.810
333,624
1.527,846
9.111
393,854
1.337,530
126.699
329,296
1.540,540
Physical in es men
135.810
4,507
12,970
9.111
10,807
17,271
126.699
4,055
12,482
Resea che s in R&D
135.810
6,765
18,684
9.111
23,904
23,773
126.699
5,533
17,634
In e nal R&D
135.810
39,609
43,815
9.111
66,055
26,574
126.699
37,708
44,195
Expo s
171.511
0,628
0,483
44.812
0,937
0,243
126.699
0,519
0,500
G oup
135.724
0,411
0,492
9.088
0,503
0,500
126.636
0,405
0,491
Sou ce: Own elabo a ion wi h PITEC da a
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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Figu e 2 shows he e ec s in a imeline ashion, and al hough as no ed abo e mos o
hem a e posi i e, hey a e no as obus o ep esen a i e as migh be expec ed a i s .
Figu e 2 Impac o ea men on p oduc inno a ion
Sou ce: Own elabo a ion wi h PITEC da a
A simila pa e n eme ges wi h espec o he p obabili y o iling a pa en when
ini ia ing collabo a ion wi h uni e si ies. This ou come unde sco es ha , excep o a ew
yea s in he 2006 coho and owa ds he end o 2015 and 2016, he p obabili y o iling
a pa en is highe when s a ing o collabo a e wi h uni e si ies. The nume ical e ec s a e
p esen ed in Table 5. I is in his ou come ha he e ec s a e mos signi ican , and hus i
can be s a ed ha , wi h ega d o inno a ion, he mos no able e ec obse ed in he
-.12
-.08
-.04
0
.04
.08
.12
Impac
2011 2012 2013 2014 2015 2016
Da e
Impac es ima e
95% con idence in e al
Da a om 2011-2016
Impac on P oduc Inno a ion o 2011 s a e s
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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analysis is he inc ease in he p opo ion o hose who ha e egis e ed pa en s wi h espec
o hose who ha e no egis e ed any. Fu he mo e, as illus a ed in Figu e 3, mos e ec s
a e posi i e, wi h alues exceeding ze o.
Table 5 Change in he p obabili y o egis e ing a pa en
Impac in yea
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
S a e
o
2006
.0011
(.0152)
.0243
(.0178)
.0209
(.0205)
-.0124
(.0206)
.0080
(.0216)
-.0170
(.0210)
-.0163
(.0218)
.0070
(.0227)
-.0180
(.0241)
.0015
(.0238)
-.0115
(.0235)
2007
.0322**
(.0156)
.0373**
(.0182)
.0269
(.0197)
.0247
(.0211)
.0244
(.0216)
.0251
(.0219)
.0359
(.0223)
.0242
(.0237)
.0478**
(.0240)
.0308
(.0234)
2008
.0499***
(.0169)
.0281
(.0185)
.0401*
(.0209)
.0291
(.0218)
.0328
(.0221)
.0634***
(.0226)
.0361
(0238)
.0471*
(.0241)
.0304
(.0247)
2009
.0082
(.0165)
.0283
(.0196)
.0204
(.0216)
.0438**
(.0221)
.0589**
(.0240)
.0467*
(.0254)
.0319
(.0254)
.0299
(.0252)
2010
-.0048
(.0173)
-.0181
(.0195)
.0084
(.0202)
.0254
(.0233)
.0202
(.0241)
.0210
(.0239)
.0301
(.0237)
2011
.0065
(.0183)
.0136
(.0205)
.0458**
(.0227)
.0289
(.0237)
.0146
(.0246)
.0099
(.0261)
2012
.0264
(.0194)
.0383*
(.0213)
.0247
(.0236)
.0093
(.0251)
-.0073
(.0258)
2013
.0514**
(.0199)
.0402*
(.0212)
.0195
(.0228)
.0010
(.0249)
2014
.0210
(.0218)
.0243
(.0225)
.0133
(.0114)
2015
.0171
(.0203)
-.0153
(.0219)
2016
-.0224
(.0246)
∗ Signi ican a 10%; ∗∗ Signi ican a 5%; ∗∗∗ signi ican a 1%.
Sou ce: Own elabo a ion wi h PITEC da a
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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Figu e 3 Impac o ea men on pa en egis a ion
Sou ce: Own elabo a ion wi h PITEC da a
Finally, he las ou come o be analyzed is he change in he numbe o pa en s iled
(Table 6). The es ima es ob ained exhibi a high a iabili y, and he e is no clea pa e n
o posi i e o nega i e e ec s wi h almos all es ima es being insigni ican ly di e en
om ze o, so no i m conclusions can be d awn abou hese e ec s. I can also be seen
ha he s anda d e o s a e conside ably la ge han he o he s, and all his could be ela ed
o he con inuous na u e o he ou come.
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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Table 6 Change in he numbe o egis e ed pa en s
Impac in yea
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
S a e
o
2006
.0438
(.0920)
.1165
(.2004)
-.4500
(.6423)
-.0622
(.3324)
.0164
(.4542)
-.2942
(.2816)
-.1071
(.4754)
.1195
(.4782)
.3030
(.5500)
-.1630
(.5754)
-.1946
(.6685)
2007
.1545
(.1819)
-1.163
(1.339)
.1819
(.2491)
.2150
(.3651)
-.0374
(.2029)
.0055
(.3950)
.0041
(.4108)
.1086
(.4862)
-.4652
(.8415)
-.6558
(.8689)
2008
-.6358
(.8092)
.2230
(.2658)
.1796
(.3966)
-.3360
(.3484)
.2267
(.5077)
-.1975
(.5495)
.3050
(.4998)
-.8837
(1.377)
-.8229
(1.328)
2009
.9361
(.9608)
1.128
(.9464)
.5410
(.9700)
1.040
(1.016)
1.091
(.9966)
.6151
(.9276)
-.9582
(1.569)
-1.029
(1.494)
2010
.0302
(.2256)
-.6533*
(.3855)
.0250
(.4572)
-.4365
(.3945)
-.2279
(.4886)
-.6273
(.5424)
-1.141
(.7150)
2011
-.7564
(.5721)
-.3828
(.3853)
-.3576
(.4088)
.2046
(.5254)
-1.997
(1.423)
-1.629
(1.636)
2012
.3527
(.4991)
.4364
(.4661)
.5516
(.5408)
-1.387
(1.594)
-1.483
(1.554)
2013
.2240
(.1956)
.5124*
(.2846)
-1.538
(1.601)
-1.046
(1.679)
2014
.6782
(.5710)
-.4408
(.9640)
-.3039
(.2792)
2015
-1.539
(.9540)
-2.17**
(1.012)
2016
-.7493
(.5091)
∗ Signi ican a 10%; ∗∗ Signi ican a 5%; ∗∗∗ signi ican a 1%.
Sou ce: Own elabo a ion wi h PITEC da a
G aphically, we also ind mo e i egula lines han in he g aphs o he o he esul s,
highligh ing a d op in he numbe o pa en s egis e ed in 2008, p obably ela ed o he
Spanish c isis o ha yea , which can be analyzed in he g aphs o se e al o he s a e s.
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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Figu e 4 Impac o ea men on numbe o pa en egis a ion
Sou ce: Own elabo a ion wi h PITEC da a
5.2. Compa ison wi h he e ec o collabo a ion wi h o he companies (p oduc
inno a ion)
Wi h he in en ion o ex ending he analysis ca ied ou and inding new
cha ac e is ics o he de e minan s o en ep eneu ial inno a ion, he ini ial a iables and
he ATET es ima es we e e o mula ed, bu conside ing ha he ea men was now
collabo a ion wi h o he i ms. In his way, he e ec on en ep eneu ial inno a ion can
be compa ed wi h he es ima es ob ained o collabo a ion wi h uni e si ies.
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Due o he size o he esul s ables, one esul (in his case p oduc inno a ion) has
been selec ed and included in Appendix 1. The esul s o R&D ans e s wi h o he
en e p ises a e simila o hose o uni e si ies. Fo mos s a e s, he e ec on he
p obabili y o ha ing a p oduc inno a ion is posi i e when hey s a o pu chase esea ch
se ices om o he en e p ises, wi h hese igu es being e y signi ican o s a e s
en e p ises in ecen yea s. Figu e 5 shows ha he e ec s ollow a simila pa e n o
bo h ypes o collabo a ion and ha he ange o he es ima es and he con idence in e als
a e he same (collabo a ion wi h uni e si ies is he blue line and wi h companies he ed
line).
Figu e 5 Compa ison o p oduc inno a ion o s a e s o 2008 and 2009
Sou ce: Own elabo a ion wi h PITEC da a
5.3. Compa ison wi h he e ec o collabo a ion wi h any ype o o ganiza ion
(pa en egis a ion)
To comple e his ex ension o he s udy, a di e en ea men g oup was again
selec ed, consis ing o hose en e p ises ha s a ed o collabo a e wi h one o he
o ganiza ions o which he sample p o ides da a (g oup en e p ises, o he en e p ises,
uni e si ies, public adminis a ion o ganiza ions, p i a e non-p o i o ganiza ions and
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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in e na ional o ganiza ions). The con ol g oup includes all i ms ha ha e ne e
collabo a ed wi h anyone, and o show he compa ison o esul s, he ou come o pa en ing
has been chosen ( he able o es ima es can be ound in Appendix 2).
As expec ed, he e ec ound is also p edominan ly posi i e. I he indi idual
collabo a ions wi h uni e si ies and o he companies we e posi i e, we would expec an
e en la ge change in he p obabili y o iling a pa en . Howe e , he obse ed e ec is
no as signi ican as an icipa ed and canno be ex ended o he en i e popula ion (only o
some s a e s in he sample). This compa ison can also be seen in g aphical o m in Figu e
6, whe e collabo a ion wi h uni e si ies is ep esen ed by he blue line and join
collabo a ion by he g een line.
Figu e 6 Compa ison o pa en egis a ion o s a e s o 2009 and 2010
Sou ce: Own elabo a ion wi h PITEC da a
6. CONCLUSIONS
This s udy p o ides weak e idence in suppo o he p oposi ion ha uni e si y
collabo a ions os e inno a ion wi hin i ms. The indings illus a e ha he majo i y o
pa icipa ing o ganiza ions ha e expe ienced posi i e bu mos ly insigni ican impac s on
a ious inno a ion ou comes, including p ocess and p oduc inno a ion. These esul s a e
Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies
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no qui e in acco dance wi h exis ing esea ch which has iden i ied he impo an ole
played by he ans e o uni e si y esea ch and de elopmen o i ms in s imula ing
inno a ion.
I is impo an o acknowledge ha he indings o his s udy a e subjec o ce ain
limi a ions. The me hodology employed di e s om ha desc ibed in he o iginal pape s.
Fu he mo e, he s udy concen a es on he in luence o uni e si y collabo a ion, whe eas
o he ac o s, including he abili ies and expe ise o employees, business ac i i y,
inancial esou ces, and echnological in as uc u e, also exe a conside able in luence
on inno a ion.
Fu he esea ch should in es iga e hese mul i ace ed ac o s in g ea e dep h in o de
o gain a mo e comp ehensi e unde s anding o hei in e ac ion wi h uni e si y
collabo a ion and i s ul ima e impac on i m inno a ion. By in es iga ing he mode a ing
and media ing e ec s o hese a iables, esea che s can p o ide mo e de ailed
knowledge o he ci cums ances unde which uni e si y collabo a ions a e mos e ec i e
in d i ing inno a ion.
Despi e hese limi a ions, he indings o his s udy highligh he signi ican ole o
ins i u ional collabo a ion in s imula ing inno a ion wi hin i ms. By le e aging he
expe ise and esou ces o uni e si ies, i ms can enhance hei inno a i e capabili ies,
leading o he de elopmen o new p oduc s, p ocesses, and se ices ha d i e economic
g ow h and socie al well-being.
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Da asou ce
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