XXI. MEZINÁRODNÍ KOLOKVIUM O REGIONÁLNÍCH VĚDÁCH. SBORNÍK
PŘÍSPĚVKŮ.
21ST
INTERNATIONAL COLLOQUIUM ON REGIONAL SCIENCES.
CONFERENCE PROCEEDINGS
Place: Kurdějov (Czech Republic)
June 13-15, 2018
Publisher: Masarykova univerzita, Brno
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Viktorie KLÍMOVÁ
Vladimír ŽÍTEK
(Masarykova univerzita / Masaryk University, Czech Republic)
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o regionálních vědách. Sborník příspěvků. Brno: Masarykova univerzita, 2018. s. 1–5.
ISBN 978-80-210-8969-3.
AUTHOR, A. Title of paper. In Klímová, V., Žítek, V. (eds.) 21st
International Colloquium
on Regional Sciences. Conference Proceedings. Brno: Masarykova univerzita, 2018. pp. 1–
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ISBN 978-80-210-8969-3
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DOI: 10.5817/CZ.MUNI.P210-8970-2018-14
FACTORS INFLUENCING SPIN-OFF ACTIVITIES AT
UNIVERSITIES: EMPIRICAL EVIDENCE FROM THE
UNITED KINGDOM
Faktory ovlivňující spin-off aktivity na univerzitách: Případová studie
z Velké Británie
SAMUEL AMPONSAH ODEI
JAN STEJSKAL
Ústav ekonomických věd Institute of Economic Sciences
Fakulta ekonomicko-správní Faculty of Economics and Administration
Univerzita Pardubice University of Pardubice
 Studentská 95, 532 10 Pardubice, Czech Republic
E-mail: samuelamponsah.odei@upce.cz, jan.stejskal@upce.cz
Annotation
This paper intends to develop the understanding of the various factors that contributes to university knowledge
transfers and spinoff activities. Using data from the HESA-BCI survey and the Structural Equation Model (SEM)
we analysed the various determinants that influence spin off activities of universities in the United Kingdom. The
empirical results demonstrate that (1) incentive support provided to academics influences their spin off activities
positively; (2) incubation support in the form of science parks, entrepreneurial support, venture capital has a
positive influence on universities spin off activities; (3) the governance of universities’ spin off activities doesn’t
necessary contribute to academic spin off activities. Practical implications are also offered to universities
management, academics and industries on best strategies to support their spin off activities.
Keywords
spin offs, universities, knowledge transfer
Anotace
Tento příspěvek má za cíl analyzovat vybrané faktory, které přispívají k transferu znalostí z univerzit a ovlivňují
spin-off aktivity. K analýze byla využita data z průzkumu HESA-BCI a vytvořeny modely strukturálních rovnic
(SEM). Zkoumány byly různé determinanty, které ovlivňují spin-off aktivity univerzit ve Spojeném království.
Empirické výsledky ukazují, že (1) stimulační podpora poskytovaná akademickým pracovníkům má pozitivní vliv
na jejich spin-off aktivity; (2) inkubační podpora ve formě nabídky využití vědeckých parků, poskytnutí veřejné
podpory v podobě např. rizikového kapitálu má pozitivní vliv na spin-off aktivity univerzit; (3) řízení spin-off
aktivit univerzitami nezbytně nepřispívá ke zvýšení produkce vědeckých výsledků v rámci akademických spin-off
aktivit. Příspěvek poskytuje praktické implikace, které mohou být v praxi aplikovány managementem univerzit,
akademickými pracovníky a být případně využito v rámci strategického zacílení na spin-off aktivity v celých
průmyslových odvětvích.
Klíčová slova
spin-off, univerzity, transfer znalostí
JEL classification: O30, O31, O33
1. Introduction
Universities contribute to regional development through demand sided knowledge and absorptive capacity
development through new business formation (spin offs), graduate startups and graduate placements (Kempton et
al., 2013). The academic setting has undergone several structural revolutions that have transformed the roles of
universities in the economy. The first of this kind of revolution took place way back in the 1930s (Etzkowitz &
Viale, 2010). The first academic revolution was the era where universities embraced research as a university
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function simultaneously to their traditional mission of teaching (Etzkowitz, 2003) but this did not lead academics
to collaborate with universities. It was the second and third academic revolutions that took place in the 1980s
(Etzkowitz & Viale, 2010) that metamorphosed and paved way for the direct engagement of universities in the
economy, and the emergence of entrepreneurial scientists and entrepreneurial universities (Etzkowitz, 2001).
Entrepreneurial universities combine their academic goals of teaching and research and decipher knowledge
produced within the university domain into economic and social usefulness (Clark, 1998). The surfacing of the
entrepreneurial university concept has given universities dual responsibilities, first is to create new knowledge and
secondly to take measures appropriate to facilitate the transfer of technology and knowledge spillovers (Audretsch,
2014). The entrepreneurial path taken by universities has emphasized new roles and expectations of university in
socioeconomic development and cooperation between external stakeholders such as industries and governments
(Sam & van der Sijde, 2014).
Many universities have buttressed their entrepreneur drive by setting up specialized supporting structures such as
technology transfer offices (TTOs), incubators and science parks within or in close proximity to their campuses
(Clarysse et al., 2005). Spinoffs generally emanate from institutions conducting noteworthy discovery research
activities such as universities (Odei, 2017) or other public research institutions (Hájek & Stejskal, 2016).The main
distinguishing feature of spin offs as a means of university-industry collaboration is the direct engagement of
faculty who double as the academic inventors who are mostly affiliated with universities (Bigliardi et al., 2013).
Academic spin offs are the bridges that connect industries with academia. Spin offs facilitates the transfer of
knowledge and technology from the academic setting into new companies (Nicolaou & Birley, 2003).
Spinoffs are considered as a medium to expedite the transfer and dissemination of university research outcomes,
and contributing mainly to the economy and also diffusing technologies to firms (Rasmussen & Wright, 2015).
However, the overconcentration on patenting and spin-off activities may “obscure the presence of other types of
university– industry interactions that have a much less visible economic pay-offs, but can be equally as (or even
more) important both in terms of their frequency and economic impact” (D’Este & Patel, 2007; Geuna & Muscio,
2009). Spinoffs also have minimal impact on community and regional economic development because they are
mostly small in nature and takes longer time to mature (Degroof & Roberts, 2004) and compete with other hightech
companies (Ensley & Hmieleski, 2005).
The rest of this paper is structured in the following manner. The next section describes the theoretical background.
In the methodology section the research methods and sources of data are explained. The results and analysis
section elaborates on the empirical results. The conclusions and implications section conclude this paper by
summarizing the most important findings, discussing several implications for policy-makers, industries and
universities as a whole.
2. Determinants of spinoff activities
The burgeoning literatures on university spinoff activities have demonstrated that spinoff firms are not established
accidentally, but they require conceited efforts and initiatives. The establishment of academic spin offs is a
multidimensional phenomenon, often determined by a numerous factors such as institutional factors and support
mechanisms, individual, social and legal framework (Bruton, Ahlstrom, & Li, 2010; Stenholm, Acs, & Wuebker,
2013). The institutional factors clearly influences academic spin off creation, this is evidenced by the uneven
distribution of spin offs among universities (O'Shea et al., 2005). Some universities are well known to be
associated with spinoffs while others struggle to even establish one.
The propensities for universities to spin off firms to utilize their academic research depend on the availability of
support infrastructure and strategies. These instruments include science parks, laboratories, incubation facilities,
technology transfer offices (TTO), venture capital, and any other infrastructure which promotes the creation of
firms (Lockett and Wright, 2005, Fini et al. 2009; Salvador, 2011). University science parks foster spin off
establishment (Vinig & Van Rijsbergen, 2010). These innovation hubs encourage and manage knowledge and
technology flow between universities and innovation-based firms. According to Wright et al. (2007), incubators
have expansively become a pivotal instrument employed by universities since the 1990s to promote the
establishment of spinoffs. Start-up incubators are public financed to links industries and academia regionally and
locally (Hackett and Dilts, 2004). Technology transfer offices (TTO) and incubators represent the most
important supportive instruments (Bergek & Norrman, 2008) in spin offs creation. TTO act as the mediating
agency responsible to identify the prospects of spinning out companies thus relieving academics of the time and
resources to carry out such a daunting task. TTOs carry out the due diligence and the viability to commercialize
an IP (Lockett et al, 2005). These tasks carried out by TTOs leads to the unremitting interaction with industry
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(Siegel et al., 2003). The incubation services provided by university science parks intensify the frequency of
spinning out new firms as well as dampening start-up costs (Caldera and Debande, 2010).
Therefore we propose that
H1: Universities that have supporting infrastructure will generate more spin off firms.
Research funding also plays a critical role in universities spinoff activities. Without ample access to finance,
universities cannot carry out quality research that will have commercial value (Sørheim et al, 2011). Numerous
studies have shown that the amount of research funding has a positive influence on university spin off activities
(Lockett et al., 2004; Lockett & Wright, 2005; Van Looy et al, 2011; Rasmussen et al, 2014). Financial resources
contribute crucially to the establishment or revamping of new spin off firms, funds are needed to come up with
business plans or conduct market research (Vohora et al., 2004). Three types of funding are crucial to spin offs
development; they are research funding which has the goal of financing the development of innovation and
technologies (Geuna, 2001). Governments the world over are providing these funding schemes to universities and
other research organizations because of the spillover effects of such knowledge and its contribution to economic
growth (Audretsch & Keilbach, 2008).
Additionally after the quality research has been carried out and assessed to possess some commercial value,
universities will require investment funding to kick start the idea of commercial production. This investment
funding will be used to establish the premises of the prospective company, pay the scientist and academics involves
in the idea and product development etc. (Smith & Ho, 2006). Finally, incubator funding will also be required to
provide the needed infrastructure needed to sustain the newly established spinoff firm. Establishing science parks
to accommodate spinoffs requires huge investment that universities may not be capable of financing (Chan & Lau,
2005). This therefore requires support from governments and business that might be potential beneficiaries. Many
European countries such as the UK, Germany, and Spain where universities are known to collaborate with
universities have this financial support (venture capital and business angels) critical for the establishment of new
spin offs (Gras et al, 2008). A study by Lockett and Wright (2005) concluded that the number of spinoff firms
established by UK universities was positively associated with R&D funding. We therefore propose that,
H2: The availability of research funding supports universities spin off support infrastructure
Institutional support mechanisms such as incentives also play a central role in universities spinoff activities (Fini
et al, 2009; D’este & Perkmann, 2011). Offering financial incentives to faculty members will motivate them to
contribute to academic spin offs formation. Providing academic researchers with incentives to augment their
research activities and technology transfer activities will make them committed to the university where students
and the academic community can continue to enjoy their services. In the UK, government provides financial and
political incentive arrangements to boost entrepreneurship (Smith & Ho, 2006). A study by Link and Siegel (2005)
has demonstrated that universities that provide astronomical percentages of royalty disbursements to their staffs
positively impact the effectiveness of university technology transfer undertakings. We therefore hypothesize that
H3: Incentives support provided to faculty supports their spin off activities
To add to the above-mentioned factors, it is envisaged that the number of people that govern the spin off process
from its initiation states to when it becomes fully operational matters a lot. Governance of Knowledge Transfer
(KT) activities was mainly spearheaded faculty members without the involvement of their institutions (Geuna &
Muscio, 2009). But this has been institutionalized in many parts of the world with universities taking charge of
establishing TTOs to regulate this venture (O’Gorman et al, 2008). The governance structure must be constituted
in such a manner that it must involve experts from the industrialist, academics, legal experts, financial experts
among others. Effective governance arrangements in extremely uncertain environment encourage experiments and
adaptation capable of unearthing the true value of the spinoff (Chesbrough, 2003). Therefore we hypothesis that
H4: Effective governance contributes to university knowledge transfer support activities
The main aim of this paper therefore is to examine the various factors that contribute to universities knowledge
transfer activities. The United Kingdom was selected for this study because it’s been one of the countries in Europe
where government has devoted lots of resources to promote spin off activities, industry-science collaboration
(Mustar & Wright, 2010; Guerrero et al., 2015). Almost all public universities in the UK have established spin off
companies to commercialize their research outcome (Soetanto & Jack, 2016). Outcomes of this paper can serve
as a guide to universities elsewhere aiming to start research commercialization. This paper also intends to
contribute to the burgeoning literature on university-industry collaboration.
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3. Data and methodology
Data for the empirical analysis was from the Higher Education Business and Community Interaction Survey (HEBCI)
for the 2015/16 academic year. The HE-BCI Survey is compulsory for all higher education providers in
Wales and England. The HE-BCI Survey is the vehicle for evaluating the volume and direction of collaborations
between UK higher education providers and industries and the general community (Rae et al., 2012). The survey
also collects information on capacity and strategies of HE providers, and their financial data with regard to their
third stream activity concerned with the production, use, application and utilization of knowledge and other HE
provider capabilities outside academic environments.
The study subsequently used the Structural Equation Model (SEM) to develop a model to analyze and test the
hypothesis. The model was chosen because of its distribution-free assumption, the predictive focus and the
explanatory model development approach for understanding the determinants of university spinoff activities
(Kock & Hadaya, 2018). Path analysis in the SEM, allows for all coefficients of association in multiple regression
models to be estimated at once (Kock, 2011).
4. Results
This study carried out number of measurements to determine the reliability and internal consistency of the model.
These included composite reliability, convergent validity and discriminant validity. Construct reliability uses the
Cronbach’s alpha coefficient to estimate measurement errors and true composite weights. A Cronbach’s alpha
with the value of equal to or greater than 0.7 is acceptable (Hair et al., 2010). From table 1 and table 2 below all
the constructs demonstrated this. The model demonstrated that all the constructs were above the 0.7 threshold with
the only exception been the support variable. Again convergent validity is the extent to which the measurement
items together explain the construct they represent in the structural model (Hair et al., 2010). It can be assessed by
the Average Variance Extracted (AVEs) that should have minimum loading of 0.50, and through composite
reliability (CR) with acceptable minimum of 0.70 (Hair et al., 2010; Kock, 2014). All the variables in this model
have loadings higher than the 0.50 threshold.
Tab. 1: Construct Reliability Tests
PAT FUN SUP INCEN GOV
Composite reliability 0.954 0.839 0.772 1.000 1.000
Cronbach's alpha 0.927 0.742 0.556 1.000 1.000
AVE 0.873 0.569 0.530 1.000 1.000
Full collinearity VIFs 1.852 1.906 1.295 1.266 1.040
Source: Own processing
Note: PAT=patenting activities, FUN=research funding, SUP=knowledge support infrastructure, INCEN=incentives
schemes, GOV=governance systems in place, AVE= Average Variance Extracted, VIF= Variance Inflation Factor.
Tab. 2: Combined loadings and cross-loadings
PAT FUN SUP INCEN GOV
PAT1 0.929 -0.260 0.014 -0.005 -0.051
PAT2 0.913 0.158 -0.045 -0.027 0.056
PAT3 0.962 0.101 0.030 0.030 -0.005
FUN1 0.432 0.759 -0.107 -0.082 0.133
FUN2 -0.153 0.766 -0.004 0.041 -0.176
FUN3 0.006 0.847 0.066 0.068 -0.061
FUN4 -0.343 0.628 0.045 -0.042 0.136
SUP1 0.055 -0.096 0.709 -0.240 -0.105
SUP2 -0.219 0.330 0.698 -0.016 0.191
SUP3 0.147 -0.209 0.775 0.234 -0.075
INCEN -0.000 0.000 -0.000 1.000 -0.000
GOV -0.000 0.000 0.000 0.000 1.000
Source: Own processing
4.1 Structural model results
Figure 1 below represents the results for the hypothesis testing. It can be seen that the strongest factor that
influences university knowledge transfer activities that is supporting activities and infrastructures was incentive
support (β=0.31), this was closely followed by funding support schemes (β=0.29). The least determinant was the
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governance structure (β=-0.08) implying that it influenced spin off activities in a negative way. Again it can be
evidenced that all these support infrastructure and mechanisms positively influenced patents acquisition process
(β=0.24). Cohen (1988) has suggested that path coefficients can be indicative of the effect sizes users can ascertain
i.e. whether the effects are small, medium, or large. A value of 0.02 indicates a small effect, 0.15 indicates medium
effect and 0.35 large effects. Values below 0.02 mean that the effects are too weak to be considered relevant from
a practical point of view (Cohen, 1988). This means that this model’ constructs have almost a medium predictive
effects.
Fig. 1: Results of hypothesis testing
Source: Own processing
Tab. 3: Path Estimates and Hypotheses Testing
Hypothesis Regression weights P values Remarks
H1 SUP>PAT 0.24 0.001*** Supported
H2 FUN>SUP 0.29 0.001*** Supported
H3 INCEN>SUP 0.31 0.001*** Supported
H4 GOV>SUP -0.08 0.16 Rejected
Source: Own processing
Conclusion
The main objective of this paper is to examine the factors that influence university knowledge transfers activities
(spinoffs). The results of the empirical analysis has demonstrated that the availability of support infrastructure
such as science parks, incubators, incentives supports and research funding have more influence on university spin
off activities (patent acquisition). An essential determinant that influences universities spinoff activities is the
availability of support mechanism either on campus or the surroundings of the universities. This can be in the form
of TTOs, incubators and science parks. This supports H1. The study found out that support infrastructure
contributes to patent acquisition which was used to measure spin offs activity. It had a coefficient of (β=0.24).
This supports other research by Fini et al (2011) and Nosella & Grimaldi (2009) which all concluded that internal
support mechanisms for academics motivate them to start commercializing their research results.
Again H2 is also supported. This study found out that funding support from the public, EU, universities and other
sources significantly contributes to the support mechanism and infrastructure (β=0.29). This buttress Sternberg
(2014) and Soetanto & Van Geenhuizen (2015) claim that university’ access to venture capital funds boosts spin
off spawning. Universities that provide greater research funding have humongous propensity to generate spin off
companies, this is because the cost of spawning such spin offs are very exorbitant for individual faculty members.
So when universities provide this for them, it relieves them of the pain of meeting these financial demands.
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The study also supported H3. The study found a significant and a positive effect of incentive support has a
mediating effect on spinoff activities (β=0.31). This means that certain enticing rewards whether in cash or
material support can influence university faculty members to engage in spin off activities. The process of spin off
can be increased when there are incentives to support academic entrepreneurship (Iacobucci & Micozzi, 2015;
Rasmussen & Wright, 2015).
The H4 is not supported. The study found that the number of people that manage or govern spin off activities does
not necessary influence spin off activities. This is because there can be better governance mechanism but if they
refuse to come up with sweetener policies to entice faculty to commercialize, then their efforts will be insignificant.
Our results contradicts that of Lockett et al. (2004) and Lockett and Wright (2005), they rather found a significant
and positive effect of spin off governance or membership on the ability of universities to spin out new academic
firms.
From the forgoing discussion, this study strongly believe that universities can increase their knowledge transfer
activities and spin off creation when they are provided with the necessary support infrastructure, financial support
to carrying out commercial viable research, incentives to support and entice faculty members that intend to venture
into research commercialization as evidenced in the literature will increase their spin off activities. These support
mechanisms buttress and forms the basis of every universities’ spin off activities. This study can further be
replicated in other countries since it narrowly focused on the United Kingdom.
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Acknowledgment
This work was supported by grant provided by the scientific research project of the Czech Sciences Foundation
Grant No: 17-11795S.