Important and Perkmann, 2011; Giuliani et al., 2010), and

Important field of studies concerns to the analysis of
personal motives and characteristics of scientists who are taking part in
technology transfer activities. The set of factors that influence the success
of scientists` entrepreneurial efforts is very large. According to Giuliani and
colleagues (2010) these factors can be divided into three groups: individual,
organizational and institutional. All are comparably important for achieving
ultimate success. And the reason that some research institutions are more effective
in technology transfer is considering the impact of these groups of factors.

a. Individual

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Some academics study the individual reasons and interests
which spur scientists into different forms of technology transfer. Individual
characteristics significantly affect participation of scientists in technology
transfer (Gregoire and Shepherd, 2012; Tartari and Breschi, 2012). Klofsten and
Jones-Evans (2000), O’Shea and colleagues (2005) point out that age and sex of
scientists as well as their main field of research are significant factors.
Male scientists are much more inclined to participate in academic-industry
collaboration (Azagra-Caro, 2007; Boardman, 2008; Giuliani et al., 2010;
Goktepe-Hulten, 2010; Link et al, 2007). The impact of age factor on
commercialization engagement is vague, even when it comes to work experience:
some academics found a positive correlation (Bordman and Ponomariov, 2009;
Haeussler and Colyvas, 2011; Link et al, 2007), some academics – negative
(Beckers and Bodas Freitas, 2008; D’Este and Patel , 2007; D’Este and Perkmann,
2011; Giuliani et al., 2010), and some academics didn’t find any correlation at
all (Boardman and Ponomariov, 2009; Gulbrandsen and Smeby, 2005; Renault,
2006). One of the main arguments that Bercovitz and Feldman (2008) made for
explaining the negative impact of age factor is that elder scientists who were
trained in the days when academic-industry partnership was less relevant or
even undesirable, can have professional background which is inevitably
unrelated to cooperation with industry. At the same time seniority is considered
as a factor that positively affects technology transfer process by many
academics (Boardman, 2008, 2009; Boardman and Corley, 2008; Bozeman and
Gaughan, 2007; D’Este and Perkmann, 2011; Haeussler and Colyvas, 2011; Link et
al., 2007; Ponomariov, 2008). Taking into account that personal contacts play a
big role in academic-industry collaboration, scientists with greater experience
tend to have larger networks of contacts which give them more opportunities to
be successful in searching for potential partners in industry (Giuliani et al.,
2010; Haeussler and Colyv, 2011; Landry et al., 2006). Prior experience of
collaboration with industry affects the attitude of scientists to industry (Van
Dierdonck et al., 1990), as well as their behavior during technology transfer
process (D’Este and Patel, 2007). The results of study by Bekkers and Bodas
Freitas (2008) consider that scientists with prior successful experience in
commercialization tend to be more involved in further academic-industry

Another group of individual characteristics that
predetermine scientists’ participation in commercialization is coherent to
scientists’ success and quality. The scientific productivity of researchers in
general positively correlates with scientists’ engagement in technology
transfer process (Bekkers and Bodas Freitas, 2008; Gulbrandsen and Smeby, 2005;
Haeussler and Colyvas, 2011; Louis et al., 1989). Moreover, the ability of
scientists to get funding for conducting researches is also positively related
to academic-industry collaboration. Many studies state that the amount of the
state funding obtained is conjugated with the amount of fund raised from
private sector (Boardman, 2009; Boardman and Ponomariov, 2009; Bozeman and
Gaughan, 2007; Lee and Bozeman, 2005; Link et al., 2007). The ability to get
state funding can point to an overall expertise in raising funds and,
accordingly, higher chances of being involved in joint projects with industry.
Individual characteristics of scientists correspond with the activities in
which they participate. As technology transfer process supposes the need of
taking certain risks and focusing on the applicability of the technology to
reach the expected results of commercialization in the most efficient way
(Olmos-Peñuela et al., 2017; Wilkesmann and Wilkesmann, 2011). However,
scientists tend to concentrate on researching unknown fields of science and
promoting the scientific environment. Many of the researches are devoted to
specific narrow fields of science that give no guarantees of gaining any profit
(B?k, 2016; Masis et al., 2009). Apparently, it can be concluded that these two
groups of personal characteristics contradict to each other and make technology
transfer process harder. On contrary, Anderson and colleagues (2015) argues
that these two groups of personal characteristics have common features and
technology transfer process only benefits from combining them. This may be due
to the fact that the commercialization process of research activities is
already part of the typical task of scientists in many countries (Lee and
Rhoads, 2004). Such studies can be used by government agencies to motivate
scientists to engage more actively in business (Sinell et al., 2015).

b. Organizational

The most important factor on the organizational level for a
scientist to participate in commercialization activities is the quality of the
research institution or the faculty of scientists. In general, the quality of
the research institution on the organizational level negatively affects
scientists` participation in commercialization activities (D’Este and Patel,
2007; Ponomariov, 2008; Ponomariov and Boardman, 2008). Partly, the study of
Azagra-Caro and colleagues (2006) accompanies previous findings considering
that the age of the research institution has a negative impact on faculty’s
support of scientists’ collaboration with industry. According to Perkmann and
colleagues (2013) such findings can be explained by the fact that scientists
from the research institution with low quality on organizational level and,
accordingly, with lack of internal resources for conducting researches strive
to get funding for further researches through academic-industry collaboration.
At the same time scientists’ participation in technology transfer process is
positively affected by the quality of the research institution from the
perspective of the quality of conducted researches (Di Gregorio and Shane,
2003; Mans?eld, 1995; O’Shea et al., 2005; Owen-Smith and Powell, 2001; Sine et
al., 2003).

Organizational context is propitious to reduce the effect
of individual characteristics on technology transfer activities. Louis and
colleagues (1989) stated that the impact of standards on organizational level
hardly regulates individual characteristics. Recently some studies confirmed
this finding: scientists tend to be engaged in commercialization activities, if
their colleagues value such activities, and vice versa (Haeussler and Colyvas
,2011; Bercovitz and Feldman, 2008; Stuart and Ding, 2006). Also the chances
that an individual is prone to establish a collaboration with
firms/entrepreneurs are higher if the individual has an experience of working
in a group that actively cooperates in the commercial sector (Kuhn and
Galloway, 2015). Scientists’ association with technology transfer offices
within research institutions positively affects their engagement in
commercialization (Bozeman and Gaughan, 2007; Markman et al., 2005; Phan and
Siegel, 2006).

c. Institutional

The third group of factors refer to institutional context.
The country context factor is very crucial when it comes to the regulation of
policies and the dissemination of resources in new solutions and areas of
research (Azagra-Caro et al., 2006). Perkmann and colleagues (2013) define two
components of institutional context that affects scientists in their
commercialization activities: association of a scientist to a particular
scientific discipline and the impact of specific national rules and government
policies. Both of these factors determine participation of scientists in
technology transfer as they define the rules and regulations that apply to
scientists, either because they are official public policies or because they
determine the rules of informal behavior within the research institutions in
which scientists work (Kochenkova et al., 2016; Crane, 1972).

Association to a specific scientific discipline is an
important factor that informs about interactions with industry (Bekkers and
Bodas Freitas, 2008; Martinelli et al., 2008). Applied fields of science make
cooperation or participation in commercialization more possible (Bekkers and
Bodas Freitas, 2008; Boardman, 2008, 2009; Bozeman and Gaughan, 2007; Lee and
Bozeman, 2005; Lee, 1996; Ponomariov, 2008). The selection of technology
transfer channel by the scientist is depended on the field of scientific
discipline the scientist is associated with. For example, Beckers and Bodas
Freitas (2008) defined that patenting and licensing, scientific products and
contract research are the channels mostly used in biomedical and chemical
engineering. Scientists associated with material field of science prefer
patenting and licensing while computer scientists tend to avoid such technology
transfer channels (Walsh and Huang, 2014; Nelson, 2016).

As for the impact of government policies, most studies
focus on EU countries such as Great Britain, Spain, Sweden and Germany, and The
USA with paying almost none attention to other geographical locations (Perkmann
et al., 2013). The impact of changes in government policies like the adoption
of the Bayh-Dole Act in the United States or relevant legislation in European
countries is well researched and considered as positive (Mowery and Sampat,
2005; Powers and McDougall, 2005; Sampat et al., 2003; Weckowska et al., 2015;
Kochenkova et al., 2016). Different studies that researched the institutional
antecedents of engagement of scientists in technology transfer in different
countries showed no significant difference comparing institutional context in
Germany and the USA (Grimpe and Fier, 2010), Germany and Great Britain
(Haeussler and Colyvas, 2011), and Ireland and Sweden (Klofsten and
Jones-Evans, 2000). Growing engagement of scientists in technology transfer
activities goes with its roots to academic career system in the United States
which incentivizes scientists to allocate industry resources to pursue a career
(Lee, 1998; Goldfarb and Henrekson, 2003; Balsmeier and Pellens, 2016).
National systems where funding is distributed on a less competitive basis and
discretionary endowed to research institutions exert less institutional
pressure on scientists (Henrekson and Rosenberg, 2001; Haeussler and Colyvas,
2011; Bonaccorsi and Cicero, 2016). Bozeman and Gaughan (2007) found that the
level of public funding of a particular area of research or a research group
could seriously affect the willingness of researchers to create a spin-off.

2.3. Commercialization channels

In academic literature “technology transfer” as a term
refers to the process when an intellectual property from academic or public
research gets commercialized through its licensing to a for-profit body (Friedman
and Silberman, 2003). Landry and colleagues (2006) defined three main forms of
technology transfer, namely the training of a skilled labor force, conferences
and scientific publications, and the commercialization of knowledge and common
algorithms for commercializing research activities which are consulting
activities, cooperative academic-industry researches, patenting, and creation
of spin-off companies.

For the past two decades some studies were conducted
focusing on different sides of technology transfer between research bodies and
firms/entrepreneurs. The results of these studies were distinct in terms of
defining the significance of different ways of transferring knowledge and
technology from research bodies to firms/entrepreneurs. Some of them identify
publications and patents as the most valuable input to industrial innovation (Cohen
et al., 2002; McMillan et al., 2000; Narin et al., 1997). Another group of
academics consider contracted and collaborative research activities as a much
more substantial form of technology transfer (Monjon and Waelbroeck, 2003;
Meyer-Krahmer and Schmoch, 1998; Kingsley et al., 1996). Furthermore, informal
communication between research bodies and industry is also considered as a
standard form of technology transfer (Cohen et al., 2002; Meyer-Krahmer and
Schmoch, 1998). Also the employment of specialists from research bodies by
firms/entrepreneurs counts as a powerful tool for improving commercialization
process (Gubeli and Doloreux, 2005; Zucker et al., 2002).

Academic literature defines two models that shape the
relationship between science and technology. The first model assumes that a
scientific research results in technology transfer through a spill-over of
science into technology and positively affects innovation and commercialization
process (Freeman, 2010; Mans?eld, 1995). On contrary the second model considers
that the relationship between science and technology is bilateral, when
scientific progress partially stems from feedback from technology transfer
process. In this model scientific progress is regarded not as an exogenic
closed-loop system but rather as an internally generated one through feedback
from technology transfer process (Murray, 2002; Nelson, 1995).

During the process of interaction both research
institutions and firms/entrepreneurs use different approaches to advance
technology transfer. Firms/entrepreneurs use coauthoring with scientists from
research institutions (Cockburn and Henderson, 1998; Liebeskind et al., 1996), employment
of research personnel from research institutions (Dasgupta and David, 1994), and
close geographical location to research bodies (Zucker et al., 1998) to enhance
technological advance and maximize financial returns. At the same time research
institutions contribute to technology transfer process through engaging its
scientists in academic-industry partnership in the form of cooperation with
firms/entrepreneurs, contract researches and consulting (Perkmann et al., 2013),
and through creating academic spin-offs (Murray, 2004; Stuart and Ding, 2006;
Stuart et al., 2007). On organizational level research institutions can
stimulate commercialization by patenting and licensing their scientists`
inventions though technology transfer offices (Bercovitz and Feldman, 2006;
Debackere and Veugelers, 2005), fostering academic spin-offs (Phan et al., 2005),
and investing in start-ups (Feldman et al., 2002). Some studies (Klofsten and Jones-Evans,
2000; Gulbrandsen and Smeby, 2005; Bozeman and Gaughan, 2007; D’Este and Perkmann,
2011; Grimpe and Fier, 2010; Haeussler and Colyvas, 2011) show the difference
in engagement of scientists in different commercialization activities in
different countries (Appendix 1).

Another big issue in academic literature is a difference
between incentives which stimulate researchers in academic and technology
transfer field. Merton (1957) ?rst emphasized that there are different incentive
systems between `the institutions of science and technology`. From scientific
point of view, the freedom to choose the line of research, the possibility to
get acknowledgment in academic community through publishing of peer-reviewed
publications and the system of remuneration based on priority are the main
incentives for scientists in research institutions.  On contrary, technology transfer stimulates
scientists to protect their inventions and ideas with the use of intellectual
property protection mechanism (patents, trademarks, etc.) in order to propel
commercialization process and obtain financial gain (Dasgupta and David, 1994).
`The institution of science` is targeted on the accruement of open knowledge
bank, whilst `the institution of technology` is aimed to generate revenue
streams that come up from possessing private knowledge. The Bayh-Dole Act of
1980 (Mowery et al., 2001) as well as similar policies in Asia and Europe
(Wright et al., 2007; Wright et al, 2008; Kodama, 2008) enacted the process of
alignment of these two systems when research bodies started to foster
commercialization process through patenting the results of their researches and
intensifying academic-industry cooperation.

A collaboration of research institutions with industry
representatives is one of the most valuable forms of innovation process (van de
Vrande et al., 2009; Bianchi et al., 2011) which allows research institutions
ad firms/entrepreneurs to use each other’s cohesive skills and thus likely
contribute to cost savings and improved research results. The goal of
firms/entrepreneurs in collaborating with research institutions during
innovation process is not only to amplify their own research and development
efforts (Veugelers and Cassiman, 2005), but also to carry out innovative
research crucial for innovation in the long term and for obtaining relevant
knowledge for private benefit (Bruneel et al., 2010). Concurrently research
institutions which are interested in establishing successful and fast-growing
research companies and acquiring non-public funding for researches are also
interested in fruitful and deep-rooted research collaboration (Etzkowitz et al.,

Even though research institutions and firms/entrepreneurs
tend to increase a mutual collaboration, they are up against difficulties of
struggling to collaborate coming from fundamentally different institutional
cultures (Bjerregaard, 2010) and   intermittently   con?icting  
goals (Gilsing et al., 2011).  Usually
institutional culture in research institutions focuses on scientific
performance not related to financial results or market assessment as a main
goal (Dasgupta and David, 1994). The free and decent liaison of research
results is crucial for their goal of dispersing and disclosing knowledge. For
firms/entrepreneurs the protection of their intellectual property is important
for the purpose of reaching their main goal of gaining financial benefits. Such
differences in institutional cultures, goals and approaches between research
institutions and firms/entrepreneurs end in strong tension between counterparts
of collaboration and lead to results of collaboration going below expectations
(Burnside and Witkin, 2008; Bruneel et al., 2010). Also research collaboration
poses a problem of potential exploitation of its actors by their counterparts.
Scientists in research institutions consider that funding from
firms/entrepreneurs affects their research in a negative way as it ties up
their research freedom. Conversely, firms/entrepreneurs construe the
willingness of research institutions to hold exclusive rights for intellectual
property as a barrier for research collaboration. In order to pull off the
research collaboration process both counterparts have to concede and be
sensitive to these major differences and to build mutual trust as it is vital
for lessening such differences (Mora-Valentin et al., 2004).