OeconomiA

copernicana
Volume 11 Issue 4 December 2020
p-ISSN 2083-1277, e-ISSN 2353-1827
www.oeconomia.pl
ORIGINAL ARTICLE

Citation: Gorączkowska, J. (2020). Enterprise innovation in technology incubators and university

business incubators in the context of Polish industry. Oeconomia Copernicana, 11(4), 799–817.
doi: 10.24136/oc.2020.032

Contact: j.goraczkowska@wez.uz.zgora.pl; University of Zielona Góra, ul. Licealna 9, 65-417

Zielona Góra

Received: 07.07.2020; Revised: 29.10.2020; Accepted: 27.11.2020; Published online: 25.12.2020

Jadwiga Gorączkowska
University of Zielona Góra, Poland
orcid.org/0000-0001-6394-463X

Enterprise innovation in technology incubators and university

business incubators in the context of Polish industry

JEL Classification: 030; 032; 038

Keywords: technology business incubator; university business incubator; product innovations;

process innovations; R&D activities

Abstract

Research Background: The development of fledgling enterprises, especially those associated

with medium-high and high technology is not easy. They often need to develop from inception a
born global strategy, which is a great challenge at the beginning of a new business. Therefore,
there is a global phenomenon of incubation, which supports young enterprises in the early stages
of development. In Poland, the institutional dimension of incubation (especially for enterprises
associated with modern technologies) consists of technology incubators and university business
incubators. Yet, scientific research con-ducted in the area of entrepreneurship incubation gives
contradictory results - some assess their activity positively, others negatively.
Purpose of the article: Enterprises located in an incubator should allocate funds for R&D activi-
ties and create innovations to develop and gain market advantage. With this in mind, the purpose
of the article is to check whether technology incubators and university business incubators con-
tribute to an increase in the likelihood of conducting R&D activities and introducing product and
process innovations.
Methods: The study was conducted on a sample of 1058 industrial enterprises distributed across
2 Polish NUTS level 2 regions: Pomeranian and Kuyavian-Pomeranian Voivodships. It concerned
innovative activity that enterprises conducted in 2014–2016. Thanks to the use of probit modeling
determination was made for the probability of introducing new products and conducting R&D
works in entities that used the services of incubators in relation to those that did not belong to
them.
 Oeconomia Copernicana, 11(4), 799–817

Findings & Value added: Econometric modeling revealed that in the studied regions incubators
contribute to an increase in the introduction of product innovations by enterprises and in conduct-
ing R&D activities. Support for the process of implementing innovation occurred significantly
more often only in the case where technology incubators were involved. At the same time, it was
noticed that only academic incubators increased the chances of introducing product innovations
on a global scale. This means that tenants of technology incubators are more innovative than
entities outside them, but their innovations in terms of the level of novelty do not differ from
innovations implemented in entities outside incubators. The conducted study indicated that the
transfer of systemic solutions related to stimulating innovation from developed countries to catch-
ing-up countries may be successful. This is a guideline for local authorities to create incubators
that allow for an increase in the level of innovation of the incubated enterprises.

Introduction

In the modern world, implementation of innovation brings measurable ben-

efits to enterprises. Creating new solutions, such as new products and pro-
cesses, requires not only research and development, but also the building of
a network of connections between enterprises and research centers, and
between enterprises themselves. At the same time, it would be difficult for
enterprises to create innovations without state involvement. This is due to
specific features of innovation, such as difficulties in raising capital for
innovative projects from commercial banks or the spread of knowledge
created in one enterprise to another due to the openness of the economy
(Etzkowitz & Leydesdorff, 2000, pp. 109–123)
The economic conditions for creating innovative solutions can be diffi-
cult even for entities with an established position on the market, and the
development of young enterprises, especially those associated with medi-
um-high and high manufacturing techniques, is also not easy. Due to the
uniqueness of the products offered and the small audience, they often need
to develop from inception a born global strategy (Dzikowski, 2018, pp.
281–294; Stayton & Mangematin, 2019, pp. 1163–1187; Blackburne &
Buckley, 2019, pp. 32–50). At the beginning of a new business, this is a big
challenge. In response to this situation, the development of the phenome-
non of incubation arose, i.e., support for young enterprises in the early
stages of their activity at both the global and then the Polish levels.
In Poland, the institutional dimension of incubation, especially for en-
terprises associated with modern technologies, consists of technology busi-
ness incubators and university business incubators. The purpose of this
study is to check whether these institutions contribute to increasing the
likelihood of conducting R&D and to implementing product and process
innovations. The research hypothesis posits the claim that incubators will
contribute to the conducting of innovative activity in the entities engaged in
research. The presented research hypothesis seems to be obvious, as stimu-

800
 Oeconomia Copernicana, 11(4), 799–817

lating innovation activity is one of the goals of incubators. However, the

need to verify the hypothesis results from the ambiguous research on their
effectiveness in catching-up countries, including Poland. Research con-
ducted in the Czech Republic showed that enterprises operating in incuba-
tors achieved lower results than those located outside them (Dvoulety et al.,
2018, pp. 543–563). In studies conducted in Brazil, it was noted that incu-
bators do not achieve the assumed results and do not contribute effectively
to local and regional development (Silva & Da Chunha, 2018, pp. 298–
313). Some doubts also appeared in the research conducted in China. It
turns out that, compared to public incubators, private incubators have
a better effect on the economy (Hong et al., 2017, pp. 569–582). In Poland,
the activity of incubators is subsidized mainly from public funds, therefore
doubts may arise as to their functioning.
Moreover, it may seem that entrepreneurs in academic business incuba-
tors, due to the closer access to knowledge resources, may be characterized
by greater innovation activity than tenants of technological incubators.
A similar thesis with regard to the creation of product innovations was put
forward in research conducted in the Sao Paulo region in Brazil. It was
negatively verified in the course of the analyzes (Fernanades et al., 2017,
pp. 153–170). It remains an open question how this situation will look in
Poland in relation to not only product innovations, but also process innova-
tions and R&D.
The analysis is based on the cohort of 1058 enterprises located across 2
polish NUTS level 2 regions: Pomeranian and Kuyavian-Pomeranian voi-
vodeships. These regions are adjacent to each other and are characterized
by an average level of innovation in Poland. On the Polish scale, they are
characterized by an average level of innovation, which will not distort the
results of analyzes by too large or too small deviations from the national
level of innovation. As the research method probit modeling was used,
which enables determination of the probability of the occurrence of the
studied innovative phenomena.
The article is divided into five parts. The first reviews the literature re-
lated to the topic of incubators. The second presents the basic methodologi-
cal assumptions of the analyses. The third presents the results of the study,
and the fourth confronts them with the results of other scientists. The fifth
part presents the most important conclusions related to the conducted anal-
yses and also indicates the limitations that impacted on the research work.

801
 Oeconomia Copernicana, 11(4), 799–817

Literature review and empirical research gap indication

The incubation phenomenon contributes to the stimulation of entrepreneur-

ship (Cavallo et al., 2020, pp. 239–262) and brings measurable benefits to
the economy (Lamine et al., 2018, pp. 1121–1141). Well-developed incu-
bators have the ability to remove resource gaps or business knowledge gaps
(Yusubova et al., 2019, pp. 803–818). They lead to the development of
enterprises as well as new products (Breznitz & Zhang, 2019, pp. 885–
873). Therefore, it seems important that the range of services that incuba-
tors provide should be as wide as possible (Kee et al., 2019, pp. 43–59;
Lasrado et al., 2016, pp. 205–219; Stokan et al., 2015, pp. 317–327). Only
the proper matching of services to the needs of incubated entities will pro-
mote their real development (Kapinga et al., 2018, pp. 1–14, Reyani et al.,
2018, pp. 569–573; Vanderstraeten et al., 2016, pp. 45–64). Otherwise,
incubators may not fulfill their functions and may not improve regional
development (Hong et al., 2017, pp. 569–582). However, extending the
protective umbrella too far over the incubated enterprises can cause them to
perform worse than enterprises outside the incubator (Lukes et al., 2019,
pp. 25–34). Incubators in themselves do not ensure the success of start-ups
(Mas-Verdu et al., 2015, pp. 793–796), but they have the opportunity to
provide services that will provide assistance for the future development of
the entities (Sousa et al., 2018, pp. 823–834).
Nevertheless, determining the success factors of incubators is not an
easy task, because incubation of new ventures is a very flexible process
aimed at achieving various goals (Franco et al. 2018, pp. 239–262). A posi-
tive perception of the incubator's work translates into the effectiveness of
entrepreneurs and vice versa — i.e., the effectiveness of entrepreneurs has
a positive effect on the functioning of the incubators (Martinez et al., 2018,
pp. 1–15). For this reason, incubator managers should ensure a good image
of the incubator and its brand (Lucic et al., 2018, pp. 1–11).
The location of companies in incubators may be conducive to establish-
ing cooperation in the area of new solutions (Wu et al., 2020; Apa et al.,
2017, pp. 198–221). This is especially important for small entities that are
just beginning to grow, because it allows the risk associated with creating
innovation to be spread over many entities (Zouaghi et al., 2018, pp. 92–
104). Creating conditions in which entrepreneurs have the opportunity to
build networks increases the chances of establishing contact with other
companies in the future (Breznitz et al., 2018, pp. 343–367). Networks of
connections can be formed not only between incubated enterprises, but also
outside them, which may facilitate the attraction of venture capital (van
Rijnsoever, 2020, pp. 1–15). Enabling entrepreneurs to enter the network

802
 Oeconomia Copernicana, 11(4), 799–817

brings better results than providing physical infrastructure for companies

located in incubators (Fernanades et al., 2017, pp. 153–170).
University business incubators are one of the possibilities for stimulat-
ing entrepreneurship among researchers, students and graduates (Guerrero
et al., 2020). Nevertheless, to enhance these effects, it is necessary to create
entire entrepreneurship-related curricula so that entrepreneurial ecosystems
can be created (Allahar & Sookram, 2019, pp. 15–25; Baskaran et al.,
2019, pp. 385–400; Stevenson, 2017, pp. 140–144). Such ecosystems, apart
from elements of education, are made up of incubators and partnership
agreements between universities and external partners who are interested in
the commercialization of knowledge (Guerrero & Urbano, 2016, pp. 551–
563).
Creating university business incubators as a tool through which
knowledge can be commercialized brings favorable results (Ng et al., 2019,
pp. 465–485). The more so that the Central Statistical Office data indicate
that enterprises with no connections with universities do not recognize
them as a source of innovation (Krawczyk, 2013, pp. 5–18). Incubators can
therefore be a link between business and universities (Bras & Preto, 2019,
pp. 147–155). The commercialization of knowledge generated at the uni-
versity has another positive aspect, i.e., thanks to which it is possible to
develop practical solutions that have been developed from public funds
(Pohulak-Żołędowska, 2013, pp. 37–52). This means that basic research
that has been financed from public funds goes into the market in Poland as
applied research on a commercial basis. The effectiveness of incubators at
universities with a rich tradition of knowledge commercialization may look
slightly different. On the one hand research conducted in Israel and Aus-
tralia showed that universities played an important role in the creation of
new products by incubatees (Rubin et al., 2015, pp. 11–24). On the other
hand Kolympiris and Klein (2017, pp. 145–170) indicated, that after the
establishment of university business incubators, the quality of university
innovations decreased.
The aforementioned literature on incubators raises issues related to the
factors responsible for their success or discusses the processes of
knowledge transfer that occur in incubators. The issues discussed are treat-
ed both from the side of positive impact on incubated enterprises and also
indicate some limitations in the process. The positive assessment of the
functioning of incubators related mainly to research conducted in countries
such as Canada (Breznitz & Zhang, 2019, pp. 885–873), the USA (Lasrado
et al., 2016, pp. 205–219), Australia and Israel (Rubin et al., 2015, pp. 11–
24). In countries with a slightly lower level of development, e.g. Italy
(Cavallo et al., 2020, pp. 239–262; Lukes et al., 2019, pp. 25–34), Spain

803
 Oeconomia Copernicana, 11(4), 799–817

(Mas-Verdu et al., 2015, pp. 793–796) and a lower level of development,

e.g. Brazil (Vanderstraeten et al., 2016, pp. 45–64; Silva & Da Chunha,
2018, pp. 298–313), the results are not clear. Some of them confirm the
effectiveness of the operation of incubators, others indicate problems in
their functioning. In this context, it was particularly intriguing that in the
Czech Republic, a country similar to Poland in terms of economic devel-
opment and historical experience, incubator tenants were less productive
than enterprises outside incubators (Dvoulety et al., 2018, pp. 543–563).
For this reason, there is a gap in the literature related to the assessment of
the functioning of incubators in catching-up countries, especially in Central
and Eastern European countries, among which Poland belongs. It is reason-
able to check how these institutions function in Poland. The conducted
analyzes will allow to determine whether entities in incubators are more
innovative than outside them. In addition, their functioning will be assessed
not only in relation to the introduction of product innovations that appeared
in the previously discussed study (e.g. Fernanades et al., 2017, pp. 153–
170), but will be extended to process innovations and R&D activities. The
analyzes will take into account the level of novelty of implemented innova-
tions, which was not the case in previous studies.

Research methodology

The research on the impact of technology incubators and academic entre-

preneurship incubators on innovation activity was designed on the basis of
international standards for measuring innovation activity contained in the
Oslo Methodology (OECD/Eurostat, 2005, pp. 47–49). The dependent var-
iables were:
− product innovations;
− process innovations together with their types, i.e., new production
methods, new production-related systems and new systems supporting
the operations of enterprises;
− expenditure on research and development.
In the case of product and process innovations, the scale of implemented
novelties was also taken into account. They referred to (OECD/Eurostat,
2005, pp. 57-58):
− new products/process for the enterprise itself which implements them,
− new products/process for the market in which the enterprise operates;
− new products/process for the country of origin;
− new products/process on a global scale.

804
 Oeconomia Copernicana, 11(4), 799–817

The independent variables were technology business incubators and

university business incubators.
The study was conducted in 2017 and covered the years 2014–2016.
The three-year research period is also a standard in the study of innovative
activity (cf. Eurostat survey).
Primary data was used to perform the analysis. It was collected using
the survey form. This was constructed in such a way that respondents gave
an affirmative answer in the event of the occurrence of the analyzed phe-
nomenon in their enterprise. For example, one of the questions was "Did
the enterprise in 2014–16 incur expenditure on research and develop-
ment?". Respondents answered with either a yes or a no. Then, the answers
were assigned the value 1 (when the analyzed type of innovative activity
occurred in the enterprise or when the services of incubators were used in
the entity) or 0 (when the analyzed type of innovative activity did not occur
in the enterprise or when the services of the incubators were not used in the
entity).
Dichotomous variables allow the use of probability theory in the analy-
sis. In this case, one of three methods can be used: a linear probability
model, a logit model or a probit model. The linear probability model can be
easily estimated using multiple regression methods. Its use, however, is
inadvisable, because the values of such a function may be negative or
greater than one, and in the case of this study these values have no interpre-
tative sense (Long, 1997, pp. 38–40). In this situation, it is better to use
probit or logit models. Both models are very similar. The main difference
between the models is that in the probit model the probability value of the F
distribution function of the standard normal distribution is probable, while
the logit model uses logistic distribution (Maddala, 1992, pp. 327–328).
Estimation of the parameters of models with a dichotomous variable is
carried out using the maximum likelihood method. It gives the highest
probability of obtaining the values observed in the sample (Aldrich & Nel-
son, 1984, pp. 49–54). In the study, the maximization of the likelihood
function was performed using techniques used for non-linear estimation.
Models were estimated in Staistica software using the quasi-Newton meth-
od.
The model calculations were made at the significance level α = 0.01, α =
0.05 and α = 0.1. The statistical significance of the models is determined on
the basis of Wald's chi-square statistics, and the verification of the signifi-
cance of parameters using Student's t-statistics, based on asymptotic stand-
ard errors of assessment.
The estimated models are in the form of a linear function. A positive
sign next to a directional coefficient means that the probability of occur-

805
 Oeconomia Copernicana, 11(4), 799–817

rence of the type of innovative activity being examined (e.g., creation of

product innovation) is greater in the group of entities that used the services
of the analyzed incubator. In the case of a negative sign, the situation is
opposite — the probability is higher in entities that did not cooperate with
incubators.
In the Results section only models that met the requirements of statisti-
cal significance were presented. The value of the probability of occurrence
of individual types of innovative activity was also estimated, so that it was
visible how big the difference in innovation between incubator tenants and
entities outside incubators was.

Results

In total, the survey was completed by 1058 industrial enterprises, whose

activities are classified in Section C Polish Classification of Business Ac-
tivity (Polska Klasyfikacja Działalności). 666 enterprises came from the
Pomeranian voivodeship, and 392 from the Kuyavian-Pomeranian voivode-
ship (Table 1). Nearly half of the surveyed entities were micro and 1/3
small enterprises. Medium-sized enterprises accounted for less than 20% of
the surveyed enterprises, and large ones 4%.
Among the surveyed enterprises, only a small number used the services
of technology incubators and academic entrepreneurship incubators (Table
2). In the Pomeranian voivodship there were 12 and 10 entities, respective-
ly, whereas in the Kuyavian-Pomeranian voivodeship there were 8 and 7.
When considering the impact of technology business incubators on the
analyzed types of innovative activity, it is noted that they affected activities
positively (Table 3). The incubators contributed most to the implementation
of new production processes. It can be concluded that the introduction of
new processes to enterprises that used incubator services is almost certain,
as p1 = 0.95. In the opposite case, i.e., in enterprises that did not cooperate
with incubators, the level of p2 = 0.61. Analyzing the types of process in-
novations more closely, a significant impact of incubators on the imple-
mentation of new production methods and production-related systems is
also noticeable. In the first case, the probability of their introduction in-
creases more than 1.5 times from p2 = 0.43 (in enterprises not using incuba-
tor services) to p1 = 0.70 (among participants of incubators), and in the
second more than 3 times, with p2 = 0.21 to p1 = 0.65. Incubators did not
have a significant impact on the implementation of new support systems.
Due to the activity of technology, business incubators in the surveyed enti-
ties, the probability of introducing new products to the market was p1 =

806
 Oeconomia Copernicana, 11(4), 799–817

0.85 and was 1.5 times higher than in entities that did not cooperate with
them. The probability of incurring expenditure on R&D in the group of
entities using the services of incubators was p1 = 0.75 and was over 2.5
times higher than in the opposite case of enterprises not using the services.
Incubators were characterized by a large and positive impact on innovation
activity. Unfortunately, models that illustrated their impact on the degree of
novelty of the analyzed products and processes did not meet the conditions
of statistical significance.
University business incubators contributed less to the implementation of
innovations than technological incubators (demonstrated by fewer models
meeting the conditions of statistical significance being estimated), but their
impact was positive (Table 4). University incubators have contributed most
to the launch of new products. In relation to entities not using incubator
services, the probability increased by 1.5 times from p2 = 0.58 to p1 = 0.88.
At this stage of consideration, it should be emphasized that in the study of
the impact of university incubators on the degree of novelty of implement-
ed product innovations, one model meeting the conditions of statistical
significance was estimated. Namely, among the recipients of incubators,
innovations on a global scale were more often implemented. On the one
hand, this is a positive phenomenon, because the probability increased 5
times, on the other, it remained low, p1 = 0.24. This means that every fourth
enterprise has implemented novelty on such a large scale. Nevertheless, this
is the beginning from which the development of innovative academic en-
trepreneurship can begin.
Among the process innovations, university incubators only affected the
implementation of production-related systems. Entities that used their ser-
vices implemented this type of innovation almost three times more often.
The probability of its implementation was p1 = 0.59.
In entities using the services of university business incubators, the prob-
ability of incurring expenditure on R&D increased. It amounted to p1 =
0.53 in this group and was almost 2 times higher than in the opposite case.

Discussion

Undoubtedly, in the surveyed enterprises, incubators contributed to stimu-

lating innovative activity. The importance of incubators in implementing
innovative solutions has been confirmed by research conducted in Italy
(Sedita et al., 2019, pp. 439–454) and in Brazil (Mansano & Pereira, 2016,
pp. 23–32), where enterprises associated with the incubator implemented
more product innovations. In the case of university incubators, this result

807
 Oeconomia Copernicana, 11(4), 799–817

was confirmed in Australian (Breznitz & Zhang, 2019, pp. 885–873) and
Brazilian (Marques et al., 2019, pp. 153–169) studies. This shows that de-
spite the doubts related to the functioning of incubators that arose during
the literature review, incubators are a good tool to support the creation of
product innovations in developing and developed countries.
At the same time, it is noticeable that technology business incubators
were characterized by greater efficiency than university business incuba-
tors. For the former, more models meeting the conditions of statistical sig-
nificance were estimated, and except creating product innovations the
probability of the occurrence of the analyzed innovative phenomena was
higher. This is surprising, because the proximity of the university should
provide incubatees greater access to knowledge resources. It is difficult to
give an unambiguous reason for this condition, however, Italian studies
indicate that providing too friendly an environment for incubated entities
may reduce their effectiveness (Lukes et al., 2019, pp. 25–34). In the case
of the studied region, it may turn out that the university community protects
entities in the incubator to a greater extent than in the case of technological
incubators, therefore they do not have to be as innovative as entities in
technological incubators. However, explicit confirmation of this thesis re-
quires additional analysis.
At this stage, it should be emphasized that university business incuba-
tors have contributed to the implementation of innovations worldwide. This
means that entities residing in incubators most likely use the potential of
the close vicinity of the university. This is a very positive phenomenon,
because while innovations are implemented in the Polish industry, they are
at a low level (Sachpazidu-Wójcicka, 2017, pp. 287–299). The number of
entities that used university business incubators' services in the scale of the
regions studied was small, but this phenomenon is the beginning from
which a more intensive development of the region may begin.
Entities located in technology business incubators more often imple-
mented process innovations than entities situated outside of them. This
concerned new production and production-related systems. In the case of
university incubators, the impact was noticed only for production-related
systems. This phenomenon may be associated with the implementation of
product innovations, because one of the factors that forces enterprises in
incubators to implement new processes is the need to improve the product
and increase production (Adelowo et al., 2015, pp. 72–89).
In the surveyed enterprises, incubators contributed to the expenditure on
R&D. This is a positive phenomenon, because R&D is one of the most
important variables influencing patenting by incubatees (Lofsten, 2015, pp.
1–32).

808
 Oeconomia Copernicana, 11(4), 799–817

A small number of enterprises that used the services of technology busi-

ness incubators and university business incubators might suggest that the
impact of these institutions on the economy of the regions is small. Howev-
er, statistical analysis provides evidence to note their significant impact. It
turns out that incubator tenants are more innovative than companies located
outside of them.

Conclusions

The analysis of the impact of technology business incubators and university

business incubators has confirmed their systemic, positive impact on the
innovation of the surveyed entities. Both types of incubators contributed to
expenditure on R&D, creation of new products and implementation of new
processes. The research hypothesis has been confirmed and the aim of the
study achieved. Nevertheless, it should be emphasized that the analyzes
showed a weak relationship between enterprises — tenants of technology
incubators, and the degree of novelty of the implemented product and pro-
cess innovations. In the case of university business incubators, a positive
correlation was noticed for new product worldwide. Taking into account
the fact that incubators should significantly increase the level of incubeet-
ies' innovation, it can be assumed that university incubators filled this gap,
while technological incubators did not.
At the same time, the research has some limitations. On the one hand, it
can be concluded that incubators positively influenced the innovation activ-
ity of incubeeties, on the other hand, it is difficult to quantify exactly the
influence of the incubators' contribution to the development of participants.
Therefore, research should be deepened and the functioning of the incuba-
tors themselves and their tenant entities should be assessed. There should
be an examination of the availability and nature of services provided by
these institutions and an assessment of how entrepreneurs evaluate them. In
addition, the study is limited to analyzing two regions in Poland. It is,
therefore, difficult to generalize from them to the entire population — all
the more so because in the economy some incubators are more effective,
others less (M'Chirgui et al., 2018, pp. 1142–11).
Despite the denoted limitations, the conducted analyzes filled the re-
search gap indicated at the beginning of the paper. From the point of view
of enriching the literature, it was indicated that in Poland, a country located
in Central and Eastern Europe, incubators contribute to increasing the level
of innovation of tenant companies. The study shows that transferring of
system solutions related to stimulating innovation (including incubators)

809
 Oeconomia Copernicana, 11(4), 799–817

from developed countries to catching up countries may be successful. The

strength of the study was that this thesis was confirmed using econometric
modeling. Although only a few companies have used the services of incu-
bators, the impact on such companies is high. If only simple statistical
analyses had been made, this fact would not be visible. From the perspec-
tive of practical implications, the analysis carried out gives a signal to local
government authorities. It indicates that the phenomenon of incubation
allows the development of enterprises by creating new products and im-
plementing new processes. Considering the fact that in the period under
consideration only a small number of entities used the services of incuba-
tors, one should consider how to increase their number. This could have
a positive impact on the development of the region.

References

Adelowo, C. M., Ilori, M. O., Siyanbola, W. O., & Oluwale, B. A. (2015). Techno-
logical learning mechanisms in Nigeria's technology incubation centre. African
Journal of Economic and Management Studies, 6(1). doi: 10.1108/AJEMS-10-
2014-0071.
Aldrich, J. H., & Nelson, F. D. (1984). Linear probability, logit, and probit models.
Quantitative Applications in the Social Sciences, 45.
Allahar, H., & Sookram, R. (2019). A university business school as an entrepre-
neurial ecosystem hub. Technology Innovation Management Review, 9(11). doi:
10.22215/timreview/1280.
Apa, R., Grandinetti, R., & Sedita, S. R. (2017). The social and business dimen-
sions of a networked business incubator: the case of H-Farm. Journal of Small
Business and Enterprise Development, 24(2). doi: 10.1108/JSBED-07-2016-
0103.
Baskaran, A., Chandran, V. G. R., & Ng, B. K. (2019). Inclusive entrepreneurship,
innovation and sustainable growth: role of business incubators, academia and
social enterprises in Asia. Science Technology and Society, 24(3). doi: 10.1177/
0971721819873178.
Blackburne, G. D., & Buckley, P. J. (2019). The international business incubator as
a foreign market entry mode. Long Range Planning, 52(1). doi: 10.1016/j.
lrp.2017.10.005.
Breznitz, S. M., & Zhang, Q. T. (2019). Fostering the growth of student start-ups
from university accelerators: an entrepreneurial ecosystem perspective. Indus-
trial and Corporate Change, 28(4). doi: 10.1093/icc/dtz033.
Breznitz, S. M., Clayton, P. A., Defazio, D., & Isett, K. R. (2018). Have you been
served? The impact of university entrepreneurial support on start-ups' network
formation. Journal of Technology Transfer, 43(2). doi: 10.1007/s10961-017-
9565-0.

810
 Oeconomia Copernicana, 11(4), 799–817

Bras, G. R., & Preto, M. T. (2019). The geographical distribution of Portuguese

business incubators: an empirical approach. Economics and Business Letters,
8(3). doi: 10.17811/ebl.8.3.2019.147-155.
Dzikowski, P. (2018). A bibliometric analysis of born global firms. Journal of
Business Research, 85. doi: 10.1016/j.jbusres.2017.12.054.
Dvoulety, O., Longo, M. C., Blazkova, I., Lukes, M., & Andera, M. (2018). Are
publicly funded Czech incubators effective? The comparison of performance of
supported and non-supported firms. European Journal of Innovation Manage-
ment, 21(4). doi: 10.1108/EJIM-02-2018-0043.
Cavallo, A., Ghezzi, A., Colombelli, A., & Casali G.L. (2020). Agglomeration
dynamics of innovative start-ups in Italy beyond the industrial district era. In-
ternational Entrepreneurship and Management Journal, 16. Advance online
publication. doi: 10.1007/s11365-018-0521-8.
Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: from Na-
tional Systems and “Mode 2” to a Triple Helix of university–industry–
government relations. Research Policy, 29(2). doi: 10.1016/S0048-7333(99)
00055-4.
Fernandes, C. C., Oliveira, M. D., Sbragia, R., & Borini, F. M. (2017). Strategic
assets in technology-based incubators in Brazil. European Journal of Innova-
tion Management, 20(1). doi: 10.1007/10.1108/EJIM-04-2016-0043.
Franco, M., Haase, H., & Correia, S. (2018). Exploring factors in the success of
creative incubators: a cultural entrepreneurship perspective. Journal of the
Knowledge Economy, 9(1). doi: 10.1007/s13132-015-0338-4.
Guerrero, M., & Urbano, D. (2016). Entrepreneurial universities: emerging models
in the new social and economic landscape. Small Business Economics, 47(3).
doi: 10.1007/s11187-016-97554.
Guerrero, M., Urbano, D., & Gajón, E. (2020). Entrepreneurial university ecosys-
tems and graduates' career patterns: do entrepreneurship education programmes
and university business incubators matter? Journal of Management Develop-
ment. Advance online publication. doi: 10.1108/JMD-10-2019-0439.
Hong, J., Chen, M., Zhu, Y.H., & Song, G. (2017). Technology business incuba-
tors and regional economic convergence in China. Technology Analysis & Stra-
tegic Management, 29(6). doi: 10.1080/09537325.2016.1216096.
Kapinga, A. F., Suero Montero, C., Mwandosya, G. I., & Mbise, E. R. (2018).
Exploring the contribution of business and technology incubators to women en-
trepreneurs’ business development in Dar es Salaam, Tanzania. Journal of
Global Entrepreneurship Research, 8(23). doi: 10.1186/s40497-018-0111-9.
Kee, D. M. H., Yusoff, Y. M., & Khin, S. (2019). The role of support on start-up
success: a PLS-SEM approach. Asian Academy of Management Journal, 24(1).
doi: 10.21315/aamj2019.24.s1.4.
Kolympiris, C., & Klein, P.G. (2017). The effects of academic incubators on uni-
versity innovation. Strategic Enterprenuarship Journal, 11(2). doi: 10.1002/sej.
1242.

811
 Oeconomia Copernicana, 11(4), 799–817

Krawczyk, M. (2013). Sources of information for innovative activity of enterprises.

types, importance, measurement. Oeconomia Copernicana, 4(1). doi: 10.12775/
OeC.2013.001.
Lasrado, V. Sivo, S., Ford, C., O'Neal, T., & Garibay, I. (2016). Do graduated
university incubator firms benefit from their relationship with university incu-
bators? Journal of Technology Transfer, 41(2). doi: 10.1007/s10961-015-9412-
0.
Lamine, W., Mian, S., Fayolle, A., Wright, M., Klofsten, M., & Etzkowitz, H.
(2018). Technology business incubation mechanisms and sustainable regional
development. Journal of Technology Transfer, 43(5). doi: 10.1007/s10961-016-
9537-9.
Lofsten, H. (2015). Critical resource dimensions for development of patents—an
analysis of 131 new technology-based firms localised in incubators. Interna-
tional Journal of Innovation Management, 19(1). doi: 10.1142/S1363919615
500061.
Long J. S. (1997). Regression models for categorical and limited dependent varia-
bles. Newbury Park: Sage Publishing.
Lucic, A., Dabic, M., & Busic, S. (2018). Brand management practices in technol-
ogy parks and incubators - an exploratory study. In K. S. Soliman (Eds.). Inno-
vation management and education excellence throught vision 2020, Vols I-XI.
Milan: International Business Information Management Association.
Lukes, M., Longo, M. C., & Zouhar, J. (2019). Do business incubators really en-
hance entrepreneurial growth? Evidence from a large sample of innovative Ital-
ian start-ups. Technovation, 82(83). doi: 10.1016/j.technovation.2018.07.008.
Maddala, G. S. (1992). Introduction to econometrics. New York: Macmillan Pub-
lishing Company.
Mansano, F. H., & Pereira, M. F. (2016). Business incubators as support mecha-
nisms for the economic development: case of Maringa's technology incubator.
International Journal of Innovation, 4(1). doi: 10.5585/iji.v4i1.51.
Martinez, K. R. G., Fernandez-Laviada, A., & Crespo, A. H. (2018). Influence of
business incubators performance on entrepreneurial intentions and its anteced-
ents during the pre-incubation stage. Entrepreneurship Research Journal, 8(2).
doi: 10.1515/erj-2016-0095.
Marques, N. D., Sbragia, R., Oliveira, M. D., & Borini, F. (2019). Entrepreneur's
background and product innovation Evidences from technology-based incubat-
ed firms. Management Research - The Journal of The Iberoamerican Academy
of Management, 18(2). doi: 10.1108/MRJIAM-11-2018-087.
Mas-Verdu, F., Ribeiro-Soriano, D., & Roig-Tierno, N. (2015). Firm survival: the
role of incubators and business characteristics. Journal of Business Research,
68(4), doi: 10.1016/j.jbusres.2014.11.030.
M'Chirgui, Z., Lamine, W., Mian, S., & Fayolle, A. (2018). University technology
commercialization through new venture projects: an assessment of the French
regional incubator program. Journal of Technology Transfer, 43(5). doi:
10.1007/s10961-016-9535-y.

812
 Oeconomia Copernicana, 11(4), 799–817

Ng, B. K., Chen, S. H., Wong, C. Y., & Chandran, V. (2019). University incuba-
tion system for research commercialisation: the case of Taiwan and Malaysia.
Science Technology and Society, 24(3). doi: 10.1177/0971721819873184.
OECD/Eurostat (2005). Oslo manual: guidelines for collecting and interpreting
innovation data. The measurement of scientific, technological and innovation
activities. Paris, Luxembourg: OECD/ Eurostat. doi: 10.1787/9789264013100-
en.
Pohulak-Żołędowska, E. (2013). Property rights of scientific knowledge in terms
of creating innovation. Oeconomia Copernicana, 4(1). doi: 10.12775/OeC.2013
.003.
Reyani, S., Muralidharan, C., Selvi, R. P., & Sakthirama, V. (2018). The impact of
technology business incubators in entrepreneurial development of start-ups. In-
dian Journal of Economics and Development, 14(3). doi: 10.5958/2322-0430.
2018.00173.7.
van Rijnsoever, F. J. (2020). Meeting, mating, and intermediating: how incubators
can overcome weak network problems in entrepreneurial ecosystems. Research
Policy, 49(1). doi: 10.1016/j.respol.2019.103884.
Rubin, T. H., Aas, T. H., & Stead, A. (2015). Knowledge flow in technological
business incubators: evidence from Australia and Israel. Technovation, 41(42).
doi: 10.1016/j.technovation.2015.03.002.
Sachpazidu-Wójcicka, K. (2017). Innovation as a determinant of the competitive-
ness of Polish enterprises. Oeconomia Copernicana, 8(2). doi: 10.24136/oc.v
8i2.18.
Sedita, S. R., Apa, R., Bassetti, T., & Grandinetti, R. (2019). Incubation matters:
measuring the effect of business incubators on the innovation performance of
start-ups. R&D Management, 49(4). doi: 10.1111/radm.12321.
Silva, A. Q., & Da Cunha, J. C. (2018). Are technology business incubators ful-
filling their objectives? A study of the Tbi's performance located in Brazil. In-
ternational Journal of Innovation, 6(3). doi: 10.5585/iji.v6i3.313.
Stayton, J., & Mangematin, V. (2019). Seed accelerators and the speed of new
venture creation. Journal of Technology Transfer, 44(4). doi: 10.1007/s10961-
017-9646-0.
Stevenson, B. (2017). Oulu Edulab: university-managed, interdisciplinary Edtech
incubator program from Finland. In K. A. Aziz (Ed.). Proceedings of the 5th in-
ternational conference on innovation and entrepreneurship (ICIE 2017). Kuala
Lumpur.
Stokan, E., Thompson, L., & Mahu, R. J. (2015). Testing the differential effect of
business incubators on firm growth. Economic Development Quartley, 29(4),
doi: 10.1177/0891242415597065.
Sousa, J., Meneses, R., Ribeiro, H., & Alves, S. R. (2018). The symbiotic relation-
ship beetwen sturtups and incubator. In R. Veselica, G. Dukic, & K. Hammes
(Eds.). 36th international scientific conference in economic and social devel-
opment - "Building resilient society". Book Series: International Scientific Con-
ference on Economic and Social Development Zagreb.

813
 Oeconomia Copernicana, 11(4), 799–817

Vanderstraeten, J., van Witteloostuijn, A., Matthyssens, P., & Andreassi, T. (2016).
Being flexible through customization - the impact of incubator focus and cus-
tomization strategies on incubatee survival and growth. Journal of Engineering
and Technology Management, 41. doi: 10.1016/j.jengtecman.2016.06.003.
Wu, W., Wang, H., & Tsai, F.-S. (2020). Incubator networks and new venture
performance: the roles of entrepreneurial orientation and environmental dyna-
mism. Journal of Small Business and Enterprise Development. Advance online
publication. doi: 10.1108/JSBED-10-2019-0325.
Yusubova, A., Andries, P., & Clarysse, B. (2019). The role of incubators in over-
coming technology ventures' resource gaps at different development stages.
R&D Management, 49(5). doi: 10.1111/radm.12378.
Zouaghi, F., Sanchez, M., & Martinez, M. G. (2018). Did the global financial crisis
impact firms' innovation performance? The role of internal and external
knowledge capabilities in high and low tech industries. Technological Fore-
casting and Sozial Change, 132. doi: 10.1016/j.techfore.2018.01.011.

814
Annex

Table 1. Structure of the surveyed industrial enterprises in the Pomeranian and Kuyavian-Pomeranian voivodeships in 2017

Micro Small Medium-sized Large

Voivodeships Quantity Quantity Quantity Quantity
Percentage Percentage Percentage Percentage
of companies of companies of companies of companies
Pomeranian 321 48% 210 31% 111 17% 24 4%
Kuyavian-Pomeranian 164 42% 130 33% 80 20% 18 5%
Sum 485 46% 340 32% 191 18% 42 4%

Table 2. Number of enterprises using the services of technology business incubators and university business incubators in the
surveyed voivodships in 2014–2016

Number of enterprises
Voivodhips technology business university business
incubators incubators
Pomeranian 12 10
Kuyavian-Pomeranian 8 7
Sum 20 17
Table 3. The influence of technology business incubators on innovation activity of industrial companies in Pomerania and
Kuyavian-Pomerania voivodeships in 2014–2016

Innovation Attributes Models p1 p2 σ t χ2 p

Expenditure on R&D y = 1 .22 x − 0 .54 0.75 0.29 0.31 3.98 17.52 0.000
Implementation of new products y = 0 ,85 x + 0 . 19 0.85 0.57 0.34 2.46 6.92 0.009
Implementation of new processes, including y = 1 .35 x + 0 .29 0.95 0.61 0.47 2.85 12.28 0.000
a) manufacturing methods y = 0 . 71 x − 0 . 18 0.70 0.43 0.30 2.39 6.01 0.014
b) production-related systems y = 1 . 19 x − 0 .80 0.65 0.21 0.29 4.08 17.44 0.000
c) support systems
Note:
p1 – probability of occurrence of the examined type of innovation activity in the group of enterprises that used the services of technology business incubators
p2 – probability of occurrence of the examined type of innovative activity in the group of enterprises that did not use the services of technology business
incubators
σ – asymptotic standard error of the independent variable parameter estimator (technology business incubator)
T – Student t-distribution value of the independent variable parameter estimator (technology business incubator)
χ2 – chi-square test value of the estimated model
p – p-value
Table 4. The influence of university business incubators on innovation activity of industrial companies in Pomerania and Kuyavian-
Pomerania voivodeships in 2014–2016

Innovation Attributes Models p1 p2 σ t χ2 p

Expenditure on R&D y = 0 .61 x − 0 .53 0.53 0.30 0.31 1.98 3.92 0.048
Implementation of new products y = 1 . 00 x + 0 . 19 0.88 0.58 0.40 2.50 7.59 0.005
New products on a global scale y = 0 .94 x − 1 .66 0.24 0.05 0.34 2.76 6.81 0.009
Implementation of new processes, including
a) manufacturing methods
b) production-related systems y = 1.02 x − 0.80 0.59 0.21 0.31 3.29 11.00 0.001
c) support systems
Note:
p1 – probability of occurrence of the examined type of innovation activity in the group of enterprises that used the services of university business incubators
p2 – probability of occurrence of the examined type of innovative activity in the group of enterprises that did not use the services of university business incubators
σ – asymptotic standard error of the independent variable parameter estimator (university business incubator)
t – Student t-distribution value of the independent variable parameter estimator (university business incubator)
χ2 – chi-square test value of the estimated model
p – p-value