The Impact of Cooperation on Firms’ Innovation Propensity in Emerging Economies

Abstract

The importance of collaboration has been one of the main issues in innovation studies. Despite many different findings on collaboration and its impact on innovation performance, the impact of different types of collaboration on different types of innovation is still inconclusive. The purpose of this research is to investigate the effects of openness on the
performance of the innovation process in a leading emerging economy. Cooperation with partners and their effects on innovation propensity unveil that process, marketing and organisational innovations are determinants of product and service innovation, thus confirming that the various innovation types are intertwined and mutually supporting each other. From a geographical perspective, cooperating with external parties from the same country plays a dominant role in determining the innovation outcome. Cooperating with consultants and private labs on the other hand seems to negatively affect innovation performance. Surprisingly, the role of foreign cooperation remains ambiguous as results were
not statistically significant.

Full text

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
1 Ege University Science and Technology Centre, 35100 Bornova, Izmir-Turkey. Phone : +90 232 343 4400. email: serdal.temel@ege.edu.tr.
2 Centre de Recherche Public Henri Tudor, 29 Avenue J.F. Kennedy, 1855 Luxembourg, Luxembourg.
3 Department of Industrial Engineering and Management, Lappeenranta University of Technology, P.O. Box 20, FIN-53851 Lappeenranta,
Finland.
Received November, 13 2012 / Accepted Jan 16, 2013
The Impact of Cooperation on Firms’ Innovation Propensity in Emerging
Economies
Serdal Temel1, Anne-Laure Mention2, Marko Torkkeli3
Abstract
The importance of collaboration has been one of the main issues in innovation studies. Despite many different ndings
on collaboration and its impact on innovation performance, the impact of different types of collaboration on different
types of innovation is still inconclusive. The purpose of this research is to investigate the effects of openness on the
performance of the innovation process in a leading emerging economy. Cooperation with partners and their effects
on innovation propensity unveil that process, marketing and organisational innovations are determinants of product
and service innovation, thus conrming that the various innovation types are intertwined and mutually supporting each
other. From a geographical perspective, cooperating with external parties from the same country plays a dominant role
in determining the innovation outcome. Cooperating with consultants and private labs on the other hand seems to
negatively affect innovation performance. Surprisingly, the role of foreign cooperation remains ambiguous as results were
not statistically signicant.
Keywords: open innovation, performance, cooperation, emerging and transition economies.
(6)1072 temel

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
retical background of innovation collaboration is developed
and 7 hypotheses on collaboration based strategy are for-
mulated. Section 4 describes our research methods and
data collection. The hypotheses are tested through logistic
regression analysis and discussed in section 5. Finally, nd-
ings are presented in section 6, which also discusses their
managerial implications together with recommendations for
policy makers.
Framework conditions for Innovation and Collabo-
ration in Turkey
Most of the developing countries had protectionist policies
until 1980’s and during those periods these policies did not
create any meaningful reason for the rms to focus more
on R&D and innovation and collaboration (Mookherjee and
Ray, 1991; Kabiraj and Yang, 2001). Thereafter gradually, many
developing countries shifted from protectionist period to
competitive environment in order to enhance competitive-
ness of their rms and country accordingly. Turkey is not an
exception to this shift.
Since the liberalization of its economy in the early 1980s,
Turkey has put signicant emphasis on innovation and col-
laboration for innovation, mostly with universities, with the
objective of enhancing the competitiveness of the small
and medium-sized enterprises (SMEs) (Pamukcu, 2003; Ce-
tindamar and Ulusoy, 2008). After the liberalization of the
economy, Turkish rms have faced increasing international
competition, which made innovation and university-industry
collaboration more important (Pamukcu, 2003), and sev-
eral public institutions, including The Directorship for Small
and Medium-Sized Enterprises (KOSGEB), Directorship for
Technology and Innovation Assessment (TEYDEB) and Tech-
nology Development Foundation of Turkey (TTGV), were
established in mid-1990s to facilitate innovation (Beba and
Saatcioglu, 2009; Turkoglu and Celikkaya, 2011).
After 1994, consecutive Turkish governments launched pro-
grams, introduced incentives and founded organizations to
support and encourage rms (mostly SMEs) to perform
better regarding innovation (Yaniktepe and Cavus, 2011).
These institutions are designed to help and guide rms in
developing their own innovation projects, providing nan-
cial support through various programs. The ultimate aim of
these support programs is to enhance the rms’ innovative
capacity trough innovation projects and collaboration with
external organizations such as universities, research centres
and other service providers.
Although, compared to most European countries, Turkey
implemented support programs relatively late; however the
development of its innovation infrastructures has been ex-
traordinary. This is reected by the rate of R&D-oriented
Introduction
The Schumpeterian mode (Schumpeter, 1942) of the in-
dividual entrepreneur, which embraces sequentially the 3
stages of invention (i.e. research leading to the generation
of new ideas), innovation that involves the development of
these new ideas into marketable products and nally, the
diffusion process across the market, has been challenged
by new models emphasizing the interactive nature of the
innovation process. According to those models, turning an
idea into a potentially successful product or service requires
the cooperation between multiple players, usually coming
from various disciplinary horizons. Along these lines, innova-
tions have been acknowledged to result from interactions
between individuals, teams, groups located both and outside
the boundaries of the rm, as already strongly emphasized in
the third generation of innovation model (Rothwell, 1992).
Despite the growing awareness of these open, networked
and interactive features of the innovation process, there is
so far little empirical evidence on the impact of opening up
the innovation process on performance, either considered
in economic terms or adopting a broader approach to per-
formance, which encompasses nancial and non nancial cri-
teria, and thus this represents a critical area of interest for
innovation management.
Lichtenthaler (2011) further posits that prior research has
only touched upon the impact assessment of the openness
feature of the innovation process on performance, especially
from a quantitative perspective. This observation echoes the
ndings of Dahlander and Gann (2010), whose recent sys-
tematic literature review indicates that large-scale quantita-
tive studies remain scarce, with some notable exceptions
such as Laursen and Salter (2006) and Van de Vrande et al.
(2009), and Mention and Asikainen (2012) in service econo-
mies. Furthermore, most of prior studies have focused on
developed economies (e.g. Tether, 2005) and neglected tran-
sition and developing economies.
This empirical study precisely aims to investigate the effects
of openness on the innovation process and on its perfor-
mance in a leading emerging economy. More specically, it
rst investigates how cooperation affects innovation pro-
pensity, measured as the introduction of novelties, either in
the forms of goods or services. Then, it further delineates
the inuence of the geographical location of the cooperating
partner, as well as the type of partner on the innovative per-
formance. Finally, it considers how cooperating affects the
degree of novelty of the innovation introduced.
The article has the following structure. After this introduc-
tory section, the article presents the framework conditions
for innovation and collaboration taking into consideration
the specic Turkish context. In the third section, the theo-

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
mental shocks, improve economic performance and likeli-
hood of survival, gain access to complementary resources,
learn new skills, absorb technology, have control over re-
lation with other companies, keep abreast with competi-
tors and improve efciency. Moreover, access to technology
bases through inter-rm co-operation or alliance has been
demonstrated to help companies to redene and reposition
themselves in the market in terms of technology.
Co-operation for innovation is also often motivated by the
willingness to gain access to new or foreign markets and
to share the risks and costs associated with R&D and in-
novation activities. Critical factors for successful co-oper-
ation agreements have been identied in strategic alliance
literature and include trust, communication, matching of
resources, organizational structures and processes (George
and Farris, 1999). Besides the adequacy of this matching, the
ability of rms to keep and maintain the skills balance is an-
other key success factor (Hanna et al., 2008). The potential
of rms to generate innovations is dependent on the prior
accumulation of knowledge they have absorbed (Fiol, 1996),
in line with the concept of “absorptive capacity” introduced
by Cohen and Levinthal (1989).
Inter-rm cooperation also embraces co-opetition (Branden-
burger and Nalebuff, 1996), which refers to the simultaneous
practices of cooperation and competition practices. Besides
the pooling of resources and the quest for synergistic effects
(Das and Teng, 2000; Huang et al., 2009), co-opetition may
also occur in the context of standard setting or when rms
aim at jointly achieving a dominant design, which in turn fos-
ters other innovations.
Cooperation with universities, research centres and the like
has also been extensively studied, leading to mixed conclu-
sions. On the one hand, cooperation with university and re-
search centres have been identied as critical partners for
the development of more radical or new-to-the-market in-
novations (Kaufmann and Tödtling, 2001; Becker and Dietz,
2004). Some scholars have also concluded that cooperating
with research institutions positively inuence the so-called
intermediary outputs of the innovation process, such as pat-
ents (e.g. Miotti and Sachwald, 2003). Lööf and Broström
(2008) nd that collaboration with university positively in-
uences innovative performance of Swedish manufacturing
rms and Aschhoff and Schmidt (2006) also evidence posi-
tive impact of university collaboration on the probability
of developing new product at German rms. In the case
of Dutch rms, Belderbos et al. (2004) nd that R&D col-
laboration with universities increases the growth of sales
attributable to market novelties. On the other hand, some
have argued that the knowledge developed by these part-
ners is less likely to be applicable in the short term, and that
they are frequently slow to react (Tether, 2002) and may not
companies, which gradually grew from around 1% to 1.4%
in 1995, and public R&D support funds increased substan-
tially, to 2.1% in 1997 and 2.5 % in 2000 (Taymaz, 2009).
The main objective of those support programs is to enhance
innovativeness of companies either alone or together with
research centres.
Notwithstanding most Turkish SMEs are still labour-inten-
sive and produce low value-added products, their focus on
innovation (Cetindamar and Ulusoy, 2008) and cooperation
is increasing. Turkey is one of the fastest growing economies
when it comes to R&D and innovation, and the number of
rms that has the potential to collaborate with external
partners is increasing continually, which is why the Turkish
situation provides us with an opportunity to examine the
early effects of innovation-based strategy and external co-
operation on rm performance.
Theoretical background and Hypotheses
Literature on the rationales for cooperation in innovation
activities abounds and usually distinguishes inter-rm coop-
eration, intra-rm, intra-country cooperation and coopera-
tion with research institutions. Inter-rm cooperation has
been demonstrated to support rms in their achievement
of three complementary goals. First, it contributes to the
creation of a critical mass of resources that enhance rms’
capacity to handle more complex and more demanding ven-
tures. Mairesse and Mohnen (2001) conrm the positive
relationship between R&D spending and innovation perfor-
mance using the French CIS 2. Similarly, the share of R&D
resources for in-house R&D and the number of R&D staff
have been demonstrated as the main factors of innovation
performance in most studies (e.g. Griliches, 1990; Crépon
et al., 1998); therefore these items have become important
variables in the explanation of innovation performance. This
critical mass of resources may be a consequence of a com-
bination of similar resource bases, through resource pooling
or may be derived from the bundling of unique repositories
of skills, expertise and knowledge of individual rms. Sec-
ond, it enables rms to rely on counterpart’s resources and
achieve higher levels of agility and exibility in the distribu-
tion of tasks both within and across different yet common
projects. Finally, through their partners’ networks, rms can
indirectly extend their own pool of potential resources and
partners.
There are different numbers of researches which have em-
phasised the impact of external R&D cooperation on rm’s
innovation performance (e.g. Lööf and Heshmati, 2002; Mi-
otti and Sachwald, 2003; Cincera et al., 2003; Belderbos et
al., 2004; Lööf and Broström, 2008; Aschhoff and Schmidt,
2006). The benets of co-operation have been extensively
studied and summarized by Ahuja (2000): endure environ-

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
tion with partners located abroad.
Hypothesis 9: Collaboration with suppliers has a positive im-
pact on rm’s innovation propensity.
Hypothesis 10: Collaboration with competitors has a posi-
tive impact on rm’s innovation propensity.
Data and method
Sample and data collection
The empirical work is based on the Community Innovation
Survey (CIS). The CIS is conducted by the Turkish Statistical
Institute (TSI) and it is only available data source from the
TSI that collects data in terms of the size of enterprises
surveyed at country level and which is comprehensive in
terms of the range of questionnaire items (e.g. innovation
expenditures such as training expenditures or acquisition
of external knowledge, importance of information sources
and co-operation for innovation activities, factors hamper-
ing innovations and protection methods – patents but also
trademarks, copyrights, design patterns and secrecy – for
innovations).
The data covers all manufacturing sectors including small
and large enterprises and the sampling excluded rms which
have fewer than 10 employees over the period between
2006 and 2008. The survey has been conducted at enterpris-
es’ place by using face to face meeting and questions were
answered by top level managers. A total of 5.863 companies
responded to the survey. The average rm size has 247 em-
ployees, whereas the median size is 49 and standard devia-
tion is 1073. Overall, 16% of rms are part of an enterprise
group. According to the respondents, the main markets for
their products and services was the local/regional market
(56% of respondents), followed by national market (50%),
and then to a lesser extent European countries (roughly
30%) and all other countries (27%) (Mention et al., 2013).
The descriptive statistics indicate that slightly more than 8%
of rms do cooperate to develop novelties, and that the
main cooperation partner is located in the country (7.8%),
followed by European partners (4%), US partners (1%), Chi-
nese and Indian partners (less than 1%) and the rest of the
world (1.1%), whatever type of partner is considered (Men-
tion et al., 2013).
Measurement of variables
In the survey, cooperation is dened as the “active participa-
tion with other enterprises or non-commercial institutions
on innovation activities”. Both partners do not need to gain
a commercial benet. The denition excludes pure contract-
ing out of work where there is no “active co-operation.”
Cooperation partners include rms belonging to the same
group; suppliers (Suppliers _ANY) of equipment, materials,
meet the needs of some industries, such as services indus-
tries (e.g. Tether, 2008). Dasgupta and David (1994) state that
researchers in research centres and universities focus on
academic results and they mostly ignore commercial results,
leading to a negative impact on university cooperation. Pavitt
(2003) focuses on the fact that the response time from uni-
versities may be slighter longer than what the business sec-
tor expects. According to Temel et al., (2013) cooperation
with university doesn’t bring expected benet immediately
and their ndings prove that it takes a certain threshold of
university collaboration intensity to reach a better perfor-
mance.
Despite the growing body of literature on “open innovation”
(Chesbrough, 2003), and the effects of opening up the in-
novation process on innovative and business performance,
large-scale studies concentrating on qualifying and quantify-
ing the impact of the openness nature of the innovation pro-
cess remain scarce. This observation is further exacerbated
when emerging economies are considered. Nevertheless,
most prior studies focusing on manufacturing industries in
developed economies tend to support a positive effect of
cooperation on innovation performance, though to various
forms and extents according to the type of partner or the
cooperation intensity (e.g. Monjon and Waelbroeck, 2003;
Tether, 2005; Tether and Tajar, 2008), our expectations natu-
rally follow the same lines and we adopt an “a priori positive
bias” of the effect of opening up the innovation process.
In sum, based on the arguments above we developed 10 hy-
potheses.
Hypothesis 1: Cooperation with different partners has posi-
tive and signicant impact on the propensity to develop and
commercialise novel products.
Hypothesis 2: Internal R&D which can be conducted either
occasional or on a continuous basis has signicant and posi-
tive impact on rm’s innovation performance.
Hypothesis 3: Conducting simultaneously various types of
innovations, namely process and organisational innovations,
positively inuences innovation propensity.
Hypothesis 4: The rm which has a marketing organization is
more likely to introduce novelties
Hypothesis 5: There is a positive and signicant correlation
between size and innovation propensity.
Hypothesis 6: Collaboration with externally partners such
as customers has a positive impact on rm’s innovation pro-
pensity.
Hypothesis 7: Collaborating with externally partners like,
universities has positive and signicant effects on propensity
to innovate.
Hypothesis 8: For the rms in emerging economies, having
cooperation partners within the country has positive inu-
ence on the innovation propensity compared to coopera-

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
intertwined, occur simultaneously, while supporting different
strategic goals, we also include dummy variables related to
the introduction of process (Process_Innovation), market-
ing (Marketing_Innovation) and organisational innovations
(Organizational_Innovation). Across all multivariate analyses,
innovation (INNO) is modelled as a dependent variable and
equals one when the rm declares having introduced a new
product (i.e. good or service). Logistic regression analysis
is applied as it is often used to investigate the relationship
between discrete responses and a set of explanatory vari-
ables (e.g. Cox and Snell, 1989; Agresti, 1990; Collett 1991;
Hosmer and Lemeshow, 2000; Stokes et al., 2000).
Results and discussion
The rst regression, which uses the variable COOP as an
aggregate variable, clearly indicates that cooperation has a
positive and signicant inuence on the propensity to de-
velop and commercialise novelties (Table 1). The value of
the odds ratio conrms that cooperating strongly affects
the probability to innovate, giving rms which set up coop-
eration agreements an advantage of almost 2.5 over rms
which opt for a closed innovation process. This nding pro-
vides support for Hypothesis 1. Results also provide support
for Hypothesis 2 which indicates that doing intramural R&D,
either on a continuous or on an occasional basis signicantly
and positively impacts innovation performance. Comparing
the odds ratios, rms that do R&D on a permanent basis
are much more likely to innovate than rms which conduct
R&D on an occasional basis. This is perfectly consistent with
the extant literature on absorptive capacity (Cohen and
Levinthal, 1989) and the need to maintain internal R&D ca-
pabilities in order to integrate external knowledge into the
internal innovation process. Interestingly, rms that declared
components or software; customers (Customers _ANY) or
clients; competitors (Competitors _ANY); universities and
higher education institutions (Universities _ANY); consult-
ants (Consultants _ANY), commercial labs or private R&D
institutes and nally, government bodies or public research
institutes (Government _ANY).
Partners for innovation activities may be located inside
the country (Cooperation _COUNT) or reside beyond
boundaries, namely in other European countries (Coopera-
tion _EU), United States (Cooperation _US), China (Coop-
eration _CHI) or India, and all other countries (Coopera-
tion _REST). Cooperation is rst modelled as an aggregated
variable taking the value of 1 if the rm cooperates, with
any partner, located in any of the listed geographical areas.
Then, we further delineate the type of cooperation partner
in order to explore its impact on the propensity to innovate
(measured as the introduction of new product, either goods
or services) and then on the degree of novelty of the in-
novation.
We also investigate the role of the location of the partner in
order to unveil if and to what extent this inuences the out-
come of the innovation process. All dependent variables re-
lated to cooperation (COOP_Type of partner and COOP_
geographical region) are binary, with values equalling when
one when the rm does cooperate with this type of partner
or with any type of partner located in this geographical area,
respectively. We also include other variables, such as size
(expressed in natural log), the ownership to a group and
the fact that the rm declares conducting in-house R&D ac-
tivities on a permanent (R&D_ Continuous) or on an occa-
sional (R&D_ Occasional) basis. Since literature has empha-
sized that the different forms of innovation are frequently
Table 1 – Role of cooperation on innovation propensity - ** p<0.01; *p<0.05
DEP=INNO Parameter Esti-
mated
Standard
Error Khi2 Pr> khi2 Odds
Intercept -2.5247 0.1353 348.3294 <.0001
Group -0.078 0.121 0.4162 0.5188 0.925
lnsize -0.0121 0.0322 0.1415 0.7068 0.988
R&D_Continuous ** 2.5474 0.1632 243.7552 <.0001 12.774
R&D_Occasional ** 1.7629 0.1406 157.1237 <.0001 5.829
Process_Innovation** 1.9385 0.0952 414.592 <.0001 6.949
Marketing_Innovation* 0.3268 0.1124 8.4493 0.0037 1.387
Organizational_Innova-
tion** 1.1664 0.1047 124.197 <.0001 3.211
COOP 0.8951 0.1551 33.3193 <.0001 2.448
Percent Concordant 87.5

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
partner for cooperation activities, conclusions can be drawn
only for customers or clients and for universities and higher
education institutions as results are statistically signicant
only for these 2 types of partners. Cooperating with cus-
tomers seems to give a clear competitive advantage when
it comes to introducing product or service innovation and
conrms prior research conducted in developed economies
(e.g. Monjon and Waelbroeck, 2003; Tether, 2005) and this
result supports Hypothesis 6. On the other hand, coopera-
tion with the science base is demonstrated to negatively and
substantively (considering that the odd ratio is much lower
than 1) inuence the propensity to introduce novelties. Neg-
ative and signicant effect of cooperating with universities
has been found, with odds ratio value of 0.536, suggesting
a strong disadvantage of cooperating with this kind of part-
ner for innovation activities. This result oddly suggests that
cooperating with universities, whether they are located in
the country or abroad actually deteriorates the innovation
performance of the rm. As such, it is certainly challenging,
and deserves further investigation in the context of the na-
tional innovation system as well as international academic
cooperation. In conclusion, this nding does not support
Hypothesis 7.
Adopting another angle to investigate the effects of coop-
eration, we merged the different partners according to their
geographical origin. The results regarding intramural R&D
having introduced both process and organisational innova-
tions are more likely to innovate than rms which do not
succeed with or get involved in these innovation types and
this is in parallel with Hypothesis 3. This nding supports the
view that the different innovation types are closely linked and
may be mutually supporting each other. Marketing organisa-
tion is also evidenced to be positively associated to product
innovation, as the result is statistically signicant at the 5%
level and this result supports our statement in Hypothesis
4. Surprisingly, despite being statistically non-signicant, size
seems to negatively affect innovation propensity. This nd-
ing may seem contradictory with prior evidence supporting
that larger rms are usually more likely to innovate.
As a second stage, the cooperation variable was disaggregat-
ed and we considered cooperation with each type of part-
ner separately. These results replicate the pattern regard-
ing the positive and signicant inuence of conducting R&D
activities either on a continuous or on an occasional basis
(Table 2). Similar ranges for the odds ratios also conrm the
magnitude of this inuence. Likewise, conducting in parallel
process, marketing and organisational innovations positively
impact the propensity to develop novelties and this also in
line in Hypothesis 4.
Process innovation clearly emerges as an enabler consider-
ing the value of the odds ratio. When focusing on the type of
Table 2 – Role of partner type on innovation propensity - ** p<0.01; *p<0.05
DEP=INNO Parameter Esti-
mated
Standard
Error Khi2 Pr> khi2 Odds
Intercept -2.5482 0.1361 350.7409 <.0001
Group -0.0651 0.1219 0.2854 0.5932 0.937
lnsize -0.0073 0.0323 0.0522 0.8193 0.993
R&D_ Continuous** 2.5948 0.1645 248.7145 <.0001 13.393
R&D_ Occasional** 1.7608 0.1409 156.0553 <.0001 5.817
Process _Innovation** 1.9723 0.0955 426.7989 <.0001 7.187
Marketing _Innovation* 0.3156 0.1131 7.7933 0.0052 1.371
Organizational _Innovation** 1.1564 0.1052 120.7364 <.0001 3.179
Group _ANY 0.4313 0.302 2.04 0.1532 1.539
Suppliers _ANY 0.0245 0.29 0.0072 0.9326 1.025
Customers _ANY* 0.9878 0.3485 8.0337 0.0046 2.685
Competitors _ANY 0.5143 0.3608 2.0312 0.1541 1.672
Consultants _ANY -0.4939 0.3243 2.3196 0.1277 0.61
Universities _ANY -0.6231 0.3775 2.7241 0.0998 0.536
Government _ANY 0.6491 0.4076 2.5366 0.1112 1.914
Percent Concordant 86.5

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
Conclusions
Despite huge interest in developing the collaboration as a
main accelerator for innovation propensity, few empirical
studies have been used to examine the impact of collabora-
tion on innovation propensity in emerging economies. In
this exploratory empirical study based on 5.863 CIS data
from Turkey, which is one of the fastest growing economies
last recent years we explored the effects of inter-rm, intra-
rm, intra-country cooperation and cooperation with re-
search actors. The ndings revealed that as long as Turkish
rms are involved in innovation activities either occasionally
or continuously, they have better innovation performance.
This would suggest that sequence of innovation activities
does not really matter for innovation propensity as long as
companies are involved any innovation activities in Turkey,
whether they do it on a regular or irregular basis. With
regards to the type of innovation it is evidenced that any
type of innovation like process, organizational and marketing
has a positive impact on Turkish rms’ innovation propensity.
However, process and organizational innovation has strong-
er impact then marketing innovation. Still it is clear that all
type of innovation activities increase innovation skills of
Turkish rms. Our results conrmed that collaboration is an
important factor also for emerging economies for innova-
tion propensity. Surprisingly only collaboration with custom-
ers may bring value to the innovation propensity of Turkish
again hold, as well as the mutually reinforcing effects of the
different innovation types (i.e. marketing, organisational and
process). Statistically signicant results are obtained exclu-
sively for cooperation within the country, which is evidenced
to positively inuence the propensity to innovate and this is
in line with Hypothesis 8. Further delineating the coopera-
tion with the different types of partners located in Turkey,
positive and signicant effects could be demonstrated for
customers/clients and government bodies/public research
institutes, with odds ratios of 3.235 and 2.168 respectively.
Finding highlights that having external collaboration with all
partners doesn’t increase the likelihood to innovate in the
emerging economy under investigation. Collaboration with
suppliers and competitors is statistically not signicant.
A further step included tests on whether cooperation, what-
ever the partner under consideration and its geographical
location, had an impact on the degree of the novelty of the
innovation. Namely, we tested whether cooperation affect-
ed the propensity to introduce new-to-the-market versus
new-to-the rm innovations, as literature tends to suggest,
although empirical evidence is scarce and usually ambiguous
on this topic (e.g. Monjon and Waelbroeck, 2003; Mention,
2011). Results did not show any signicant relationship be-
tween any type of cooperation (either horizontal or vertical
cooperation forms) or the location of the partner and the
degree of novelty, thus deserving further investigation.
Table 3 – Role of geographical location of partners on innovation propensity - ** p<0.01; *p<0.05
DEP=INNO Parameter
Estimated
Standard
Error Khi2 Pr> khi2 Odds
Intercept -2.5118 0.1359 341.6912 <.0001
Group -0.0889 0.1217 0.5333 0.4652 0.915
lnsize -0.0145 0.0323 0.2003 0.6544 0.986
R&D _ Continuous ** 2.546 0.1637 241.8085 <.0001 12.756
R&D_ Occasional ** 1.7659 0.1409 157.1381 <.0001 5.847
Process_ Innovation** 1.9345 0.0953 411.7264 <.0001 6.921
Marketing_ Innovation 0.3129 0.113 7.6701 0.0056 1.367
Organizational_ Innovation** 1.1641 0.1049 123.1001 <.0001 3.203
Cooperation _EU 0.4595 0.3186 2.0802 0.1492 1.583
Cooperation _US -0.0235 0.5285 0.002 0.9645 0.977
Cooperation _COUNT** 0.7732 0.1822 18.0203 <.0001 2.167
Cooperation _REST 0.7795 0.5311 2.1538 0.1422 2.18
Cooperation _CHI -0.3147 0.688 0.2093 0.6473 0.73
Percent Concordant 87.8

61
ISSN: 0718-2724. (http://www.jotmi.org)
Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
Limitations and future research
This study focuses on a single country setting, which chal-
lenges the generalizability of the results. Nevertheless, due
to the lack of prior empirical research on the effect of open-
ness on innovation performance in emerging economies, this
paper provides relevant insights into this critical issue. Using
a longitudinal dataset would further allow capturing the dy-
namics of the innovation process and its effects on perfor-
mance, and would thus signicantly increase the relevance of
these ndings. Nevertheless, it should be mentioned that the
data related to cooperation covers the entire period 2006-
2008 while information on introduced novelties relates to
2008. Another interesting area for further development
includes the collection of information on innovation as an
object, as CIS is subject-oriented and thus focuses on the
innovative activities of the rm, irrespectively of the impor-
tance of these activities. In other terms, CIS does not inquire
whether one or several innovations have been introduced.
Along the lines of prior projects such as those conducted
by Pentikainen et al., (2002) in Finland, one could consider
building such database focusing on novelties although this is
a time-consuming and resource-intensive activity.
Avenues for further research include explaining some of the
challenging results, especially when it comes to foreign co-
operation when explored in an aggregated way. As Europe
is by far the largest trade partner for the country, it would
be relevant for policy makers and business leaders alike to
understand the impact of developing synergies in innova-
tion activities. Considering the critical role of innovation for
economic growth, further understanding how cooperation
affects performance so as to design effective and efcient
innovation systems, at all levels – national, regional and local,
with all related mechanisms and incentives should be of the
utmost priority and may require the development of dedi-
cated surveys in order to better capture the peculiarities of
the innovation process and its openness nature in emerging
economies.
Acknowledgements
The authors would like to thank Izmir Development Agency
(IZKA) for its support and assistance to access the CIS data.
The data was accessed during “Izmir Regional Innovation
Strategy” project.
This paper is an extended version of the article entitled “In-
novation and cooperation in emerging economies: two sides
of the same coin?” accepted at the International Conference
on Innovation and Entrepreneurship, Jordan, 2013.
rms and this nding suggests that Turkish rms should pay
accrued importance to their customers.
Astonishingly, and in contrast with previous studies (e.g.
Capon et al., 1990; Lee et al., 2001; Song et al., 2008), our
ndings reveal that collaboration with universities does not
really enhance innovation propensity. Several reasons may
explain this negative result. First, most of Turkish universities
are teaching intensive. Second, there are few well functioning
technology transfer ofces and third, the absorption capac-
ity of Turkish rms is very low. Another observation is the
negative relationship between size and innovation propen-
sity of the rm, although nothing can be concluded since the
relationship is not statistically signicant.
Policy recommendations
Based on the above analysis, policy recommendations for
policy makers are as follows. It is obvious that all type of in-
novation initiatives improve innovation propensity of rms.
Therefore it is important to urge rms to conduct innova-
tion projects. Secondly, external collaboration is important
factor and should be supported to extent rms’ collabora-
tion network via different mechanisms. Last but not least,
university-industry collaboration does not create expected
value in these types of countries, to the extent that our
results show a negative relationship between university co-
operation and innovation propensity. Therefore, new policies
and instruments should be developed to have better results
from this collaboration.
Managerial implications
The present article may help managers wishing to enhance
their company’s innovation propensity to take advantage of
collaboration with external partners in emerging economies.
However managers should keep in mind that the best part-
ner for their innovation propensity is their customer and it is
important to have well dened and long lasting collaboration
with them. On the other hand, collaboration with research
organization is not the best tool for innovation propensity
in emerging economies since this collaboration needs longer
period and rms in emerging economies cannot involve long
time frame project due to their nancial and technical re-
strictions. Therefore, managers should be very careful when
they are choosing their innovation partners and also make
sure that their rms ready for this collaboration. However,
collaborating with local partners is much more benecial
than international collaboration for their rms.

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Journal of Technology Management & Innovation © Universidad Alberto Hurtado, Facultad de Economía y Negocios.
J. Technol. Manag. Innov. 2013, Volume 8, Issue 1
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