Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
University´s Commercialization
Landscape: linking industry, license
agreement and licensee
Evita Milana1, Jason Li-Ying 2
1
2
Technical University of Denmark, [email protected]
Technical University of Denmark, [email protected]
The purpose of this paper is to shed a new light and provide new empirical evidence in research
commercialization literature by reviewing contracts of technology commercialization
agreements and by mapping the landscape of commercial technology transfer in Denmark. We
explore the tendencies and patterns as well as the geographical horizon of licensed technologies.
Our analysis of technology licensing landscape has showed stable increase in university´s
commercialization activities in the period from 2000-2015. To take a step further, we extend the
classical research of patenting activity to the commercialization activity. We find that most of
university´s patents are sold and not licensed; most of the licensees are incumbent firms,
however, the amount of commercialization contracts signed with academic spin-outs are not
lagging far behind in the total numbers. Geographically, there is a clear pattern that most of the
technologies are sold to Danish companies within Denmark indicating that university´s main
contribution is primarily for regional and national markets, especially around the capital area.
Based on that, we make conclusions and suggestions for university managers and policy
makers.
1. Introduction
As the policy interest and expectations from university-based technology development and commercialization continues
to grow and evolve all over the globe, the academic exploration of technology commercialization avenues grows with
it. Universities and other public research institutions in Denmark have to ensure that “research results produced by
means of public funds are utilised for the benefit of Danish society through commercial exploitation” (Act No. 347 of 2
June 1999 on inventions at public research institutions). Thus, Danish universities are obliged to consider
commercialization activities to bring their inventions to the market where buying and selling of products and services
take place.The goal as for universities as policies everywhere on the globe is the same: to transform the university´s
research into commercially viable innovations that enrich the market and sustain regional economy. The motivation to
transform university´s research into commercially viable innovations that enrich the market and sustain regional
economy has been demonstrated by the evidence that successful commercialization of research has been an important
source for wealth creation (Etzkowitz,H., 1998; Shane,S., 2004; Braunerhjelm et al. 2010; Mueller 2006), new jobs
creation (Audretsch and Lehmann 2005; Link and Welsh, 2013; Veugelers and Del Rey, 2014), and additional income
of resources for funding further research (Guldbrandsen and Smeby, 2005; Bozeman and Gaughan, 2007).
However, as noted by Gisling, V. et al (2011), we still have too little knowledge about the extent to which different
industries contribute to differences in technology transfer processes. Especially, we lack knowledge in this aspect about
transfer patterns through commercialization of university inventions. Our paper undertakes this topic and examines how
the nature of technologies, firms, and industries affect commercialization of university-generated technologies and
choice of commercialization channel – a commercial venture type that in-licenses a particular technology. One of our
purposes is to find out what is the profile of a firm that makes a decision to commercialize university innovations and
how it is connected to particular industry.
Within the body of technology transfer literature there are papers that look at different determinants contributing to the
commercialization of university inventions (Nerkar and Shane, 2007; Markman et.al., 2009; Barbolla and Corredera,
2009; Lee, 2000), barriers for commercialization (Siegel et al, 2004; Bruneel et al, 2010) and what are different transfer
1
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
channels (Cohen et.al, 1998; Cohen et al., 2000; Shane, 2000; Colyvas et al., 2000). However, we know little about the
licensees and their industries, their size and commercialization routes. Are there differences in licensing1 channels and
conditions if the licensee is a large firm or a small firm, an incumbent or a spin-out? This paper aims at answering these
questions by focusing on patent commercialization flow by exploring such factors as licensee venture types, contract
agreement forms, industries of licensee firms, and their geographical reach. In brief, we aim to cluster licensing
tendencies by these factors.
Moreover, our research motivation lies in the method of many researchers who estimate the success of technology
transfer and commercialization based on patent data, namely, the increase in patenting. A bunch of studies confirm that
since the Bay-Dohl Act in 1980 in the US and similar regulations in Europe around 2000, patenting has increased
dramatically (Mowery et al, 2001; Mowery and Ziedonis, 2002; Shane, 2004; Baldini, 2006). However, in our opinion,
this doesn’t mean that university’s research has reached the market or to what extent it has reached the market and been
commercialized. Commercialization will not be the case for all the patents that universities possess. Unfortunately, a
large amount of university patents in Europe as well as in the US still lie in the shelves of universities, because they
haven’t found their licensee and commercial potential. Of course, patents are internationally recognized as a measure of
research output and quality. However, our study is interested not to measure the total number of patents, but only
explore those patents that have been, first, granted to the university and, secondly, recognized as commercializable from
industry´s (licensees´) perspective. Thus, only contracted patents are subject of our research. This limitation is done in
purpose to exclude biased interpretation of commercial and entrepreneurial activity on the campus and to avoid
misleading conclusions.
Therefore, not neglecting the worth of previous studies that apply patent data, we apply a new method to analyze
commercialization of university inventions by exploring commercialization contracts. In that way, we wish to stress the
importance of careful examination of data and cautiousness when drawing conclusions on technology transfer and
commercialization.
This paper will contribute to the technology transfer literature with empirical evidence by investigating technology
commercialization in the largest technical university that owns and commercializes the most IPs in Denmark, namely,
the Technical University of Denmark (DTU). We identify the relevant commercialization patterns at the technical
university between 2000 and 2015 in order to present a comprehensive picture regarding the commercialization of DTU
technologies and explore patterns of the interplay among various contingent factors. The results can provide managers
at universities similar to DTU with useful insights for decision making, provide a useful analysis material for policy, as
well as academia with inspiring inputs for further research on potential causal relationships among the contingencies
and technology commercialization outcomes. Understanding the patterns and different commercialization paths for
industry fields can help to draw more precise and targeted policies towards commercialization and entrepreneurship at
universities.
2. Literature overview
Technology transfer of academic research through patenting and licensing of inventions and academic entrepreneurship
has attracted a lot of attention within innovation and entrepreneurship literature (Rothaermel et al, 2007; Phan and
Siegel, 2006; Markman et al, 2008; Perkmann et al, 2013). Technology transfer, however, can have different channels,
and technology commercialization is one of many and accounts only for less than 10%, as concluded by Agrawal &
Hendeson (2002) as they explored knowledge flow from MIT to industry. Also Cohen et al. (2002) found that firms
value more collaboration with academia through other channels (e.g. in the form of consulting, contract research or joint
research) than licensing of academic patents.
Despite that, the scope of this paper is to explore particularly the technology commercialization as one of the channels
of technology transfer to the market.
Notwithstanding that there are studies on technology transfer that mark some differences in transfer processes in
different industries (Bekkers and Bodas Freitas, 2008; Valentin and Jensen, 2007) and indicate on diverse licensing
strategies (Markman et el., 2009) concluding that licensing is not equally effective across all technologies (Levin et al.,
1987), we lack a comprehensive understanding of this issue and correlations between licensee venture type, licensee´s
industry and location. In summary, the findings of these different studies do not capacitate one to determine whether
there are visible differences in habits tested by industries/sectors how university inventions reach the market. Industry
differences in commercialization patterns appear to be important not only for differences in commercialization contract
types, but also for differences in licensee type. Therefore, this paper will reveal some of the interesting aspects of
linking industry sectors with contracts and licensees.
Another relevant study to which this paper refers is the paper of Nicola Baldini (2006) on Danish universities´ patenting
activity form 1982-2003. Because his study mainly focuses on policy and institutional aspects it is a good source for
understanding the institutional settings and how the Danish Bayh-Dole act was developed and introduced in 2000 by
Danish universities. At the same time, the study of Baldini covers only three years after the new law, and, as he
acknowledges himself, there is too little evidence to predict how patenting and commercialization developed after 2003.
1
In this study, licensing is presented as a process of commercialization that can take different forms: patent licensing,
patent sale and option agreement licensing.
2
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Our paper picks up that gap and brings new evidence. Thus, this is an evidence-based paper that contributes to the
broader literature on university technology transfer by adding a novel approach for exploring technology transfer from
university to the market – analysis of contracts and licensees to explore the flow of university patents into the market.
3. Data and method
Using a unique data from the invention disclosure database from DTU with inventions disclosed between 2000 and
2015, we estimate commercialization activities at university level and observe the dynamics between different forms of
in-licensing companies. Hence, the primary data of this paper consists of 147 recorded commercialization contracts at
DTU in the period between 2000 – 2015. This dataset includes all the contracts that commercialize and transfer any
kind of technology that is propriety of the university. These contracts transfer codified knowledge on inventions that is
commercially useful through systemized codifying form, namely, patenting. Patents are the actual transfer object of
these contracts, however, they are not per se the unit of our analysis. The concept of technology transfer, thus, is a
license agreement that grants licensee the access to the licensor´s patents (Wang et.al, 2015). In contrast to other
studies, we base our study on data on contracts that commercialize patents and licensees that in-license inventions from
universities. This is a new way and method to discover new angles on technology commercialization. Besides, this is
very new data that hasn’t been explored before and gives new insights in what happens within commercialization. The
reason why we have taken this perspective of exploring contracts lies in the evidence that technology commercialization
contracts more precisely describe the commitment of a firm to conduct a market transaction with university. Of course,
each contract is an individual and unique case dependent on negotiations between a university and a firm, but we can
find general patterns and trends also on aggregated level of given contracts.
From the data base of the university we could track back all the contracts that the university has signed with its
collaborators. This contract data base, however, is broader than pure commercialization evidence, because it includes
also co-ownership contracts with companies, individuals and other public research institutions that express willingness
to in-license university’s inventions.
We explicitly extracted contracts that witness a market transaction between the Technical University and another party
as to be sure that we explore the commercialization of university patents. As noted by Perkamnn et. al (2013),
university-industry collaboration is a broad concept and commercialization forms just a small part of these intentions.
Therefore, we are cautious that we conduct a proper analysis of exactly this marginal activity of university-industry
collaboration.
There are all together 205 records on contract part in our data set. Out of those, 147 are commercialization contracts and
55 co-ownership contracts. Co-ownership agreements indicate that university collaborates with a bunch of other firms
besides those mentioned in commercialization contracts. Hence, our case is aligned with Perkmann´s (2013) findings
and we see a potential of those co-ownership agreements to be followed up as commercialization agreements. Yet, for
the purpose of this paper we explore explicitly commercialization contracts.
We could identify 112 different organizations that have signed contracts on commercialization of university´s
inventions whether by licensing, sales or option agreements. Out of these, 110 are commercial ventures, i.e., firms, and
two are other universities. The only two Options agreements that the university signed with individuals we excluded
from analysis as both contracts have run out and no further action was followed up; in addition, individuals are not
market players that develop and commercialize particular invention (for this purpose they would need to establish a
company).
The contracts in the database cover the period of 15 years, from 2000-2015 taking as the starting point the date on
which the contract was signed. Database, thus, contains both contracts that already have run out and that are still active.
Methodologically, we apply descriptive statistics to track patterns and cluster the data.
4. Commercialization patterns: what, how and where?
Commercialization of research is a process in which scientific research results serve as important input in
entrepreneurial activities, within existing businesses as well as in new ventures. Despite findings of Valentin and Jensen
(2007) who examined the effects of the Danish policy change towards university IP ownership in contrast to Swedish
profesor´s privilege and found a significant reduction in contributions from Danish academic inventors, we come to the
conclusion that since introduction of the Danish Bay-Dohl Act in 2000 the overall commercialization activity within
DTU has increased, with only a marginal drop in 2012 (see, Figure 3).
4.1. Contract types
In this paper we aim to highlight the contract or agreement aspect of technology commercialization as an alternative
perspective to account for technology commercialization. There are two constructs that are used in literature referring to
the technology transfer settlement, namely, agreement or a contract. We rather use the construct ´contract´ to highlight
the legal enforcement and market transaction characteristics of this settlement between two parties, although, both
constructs have the same meaning.
3
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
A substantial body of previous research has examined the total number of patents, numbers of licensed patents and
numbers of academic spinouts a measurement instrument for technology transfer from university to industry. However,
patents per se, whether licensed or not, do not mirror the actual interaction density between a university and business
world for commercialization purposes. This can, further, lead to misleading conclusions about commercialization
activity. Therefore, in this paper we introduce commercialization contract perspective that expounds the
commercialization contract signing as a fact of commercial transaction between a university and a firm. The main
difference between contract perspective and patent or patent licensing perspective is that the former one refers to a
contract between a firm and a university at a given time meaning that one contract with one company may, actually,
contain more than one patent. It is not rarity that when a firm in-licenses a patent from a university it does so for several
patents at a time (there are different reasons for firms to do that). For example, in our data set the maximum of patents
that were transferred in one commercialization contract were seven patents at a time to one company. Thus, the actual
statistical data on contracts will display less interaction points between a university and industry than when accounting
for single patent licensing statistics. But, of course, the opposite can also be true, that one patent is licensed to more
than one firm. Hence, patents can still be a reference point, but in this study licensing and sale refers strictly to the
licensing or sale of patents. Figure 1 illustrates the difference between two approaches by exhibiting the total number
of patents commercialized, contracts signed and licensee firms participating.
Total number of patents, contracts
and licensees
252
147
Patents
Contracts
114
Licensees
Figure 1 Comparison of total numbers for patents, contracts and licensees
However, before underpinning the data we give a short explanation of what different contract agreement types contain.
Licensing as a general term is often used to refer to commercialization of patents. However, licensing contract is a
concept that describes the transaction between a university and a firm in which a patent is transferred to the firm for an
exchange of some benefit (contract conditions) for university, mainly in form of a licensing fee. Further, a sales contract
is another type of contract that prescribes patent transfer from university to a firm and in which the firm gains full rights
over the patent under the contract. While, within the database of university contracts, co-ownership contracts can´t be
counted as commercialization transactions per se, because the nature of these contracts is to settle the general rules and
shares of patent ownership between two or more parties (in our data sample, this contract type is usually signed
between two research institutions or their employees, co-founders). Of course, these patents can afterwards be licensed
and commercialized; often that is one of the co-owners that in-licenses or buys out the patent in order to commercialize
it. Because of this reason, we exclude those co-ownership agreements that are not followed by commercialization
contract (be it licensing or sale) from our data set. To be more precise, if the co-owned patent got commercialized, it
will be refered in the database as licensed or sold and, thus, counted in our data set among commercialized patents. For
example, our data contains a company that from a co-ownership contract´s date took eight years to sign a sales contract
on that same invention with the university. So, our intention is not to neglect the importance of co-ownership patenting
as they pose entrepreneurial potential for the future, yet they don’t serve the purposes of this paper and are, thus,
excluded from our data set for further analysis. In result, data set contains 147 commercialization contracts with
established firms (exceptionally, two universities are also counted under this category) and 55 co-ownership contracts.
4
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Contract types
Option
6%
License
40%
Salg
54%
Figure 2 Distribution of commercialization contracts per contract type
Our data set contains also Option contract agreements that prescribe university´s rights over the patent, yet, providing
an option or opportunity for the licensee to negotiate (or withdraw) the contracting conditions. As noted by an employee
of DTU´s technology transfer office, the maximum length of an option license is up to 12 months, the average being
around 6 months. Thus, the total number of contracts that the university has signed with companies contain contracts
that are still active as well as contracts that have expired and are marked as inactive in the database.
Total number of Contracts per contract type (per year)
40
35
Number
30
25
20
15
10
5
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
year
Licensing
Sale
Co-ownership
Total
Figure 3 Yearly dynamics of signed contracts
Figure 3 confirms what we already mentioned above: patenting and sale of patents at the university has been increasing
and so does patent out-licensing by taking different forms. There is a clear evidence of increasing co-ownership type of
license contracts; however, this is not increasing at the expense of other contract types as also licensing and sales
contracts have increased steady after 2012. The period between 2009 when we see a decrease in the total number of
signed contracts and 2012 when slope goes up again reflects the global financial crisis that hit rather hard also
Denmark´s economy. In sum, there is a growing tendency for sales contracts.
5
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
4.2. Licensee venture types
Licensee venture types characterize a firm that has signed a commercialization contract with university by its role in the
market. We refer to spinouts as newly established ventures that are spinning out from university research and involve
almost always also academics. Incumbents, in turn, are well established firms that are active in the market for 3 or more
years. These two are venture or firm types. However, as mentioned before, among licensees there are also two
universities and two individuals that have had a commercialization contract with the university, but the individuals will
be excluded from the further analysis as they are not classified as ventures or organizations.
With secondary data from public register of companies (CVR and Orbis database) we describe and categorize the
organizational factors of in-licensing firms. Thus, we are able to analyze licensees for such parameters like firm size,
venture type, sector, and geographical location.
From knowledge of previous studies we might expect that most patents are licensed to incumbent companies. However,
accounting for the total number of firms that in-licensed patents from DTU, we see that, actually, almost half of the
licensees are spin-outs, with incumbents more signing sales contracts and spinouts, on the other hand, more licensing
contracts. Because some firms have repeated transaction with the university, one firm can have more than one contract
meaning that it has in-licensed more than one technology (at different points in time) from the university. Thus, in
result, we have more licensing contracts than the number of licensees.
Number of contracts per licensee types
Licensing
Sales
Option
55
37
23
23
6
0
Incumbents
0
Spin-outs
0
3
Others
Figure 4 Distribution of different contract types
Therefore, we agree with findings of Astebro and Bazzazian (2010) that in absolute terms the number of university
spin-outs is growing, however we can´t agree to their generalization that licensing to incumbents strongly dominates
over licensing to spin-outs.
Figure 4 summarizes the total number of contracts and how the contract types are distributed between incumbents, spinouts and other organisational forms. As we see, the interest of incumbent firms to buy patents from universities
overwhelms licensing and option agreements, whereas the opposite is true for spinouts – they are more licensing than
buying university inventions. This can be explained by the limited financial resources and insecure future of new firms
while developing embryonic technologies, because patents are expensive business.
Among licensee venture types dominate two types: spinouts and incumbent firms. Other universities as licensees
account only for less than 2%. Interestingly, the number of spin-outs and incumbent firms that have in-licensed DTU´s
invention is rather close to eaqual, incumbent venture type taking a little bit over in the total number. However, looking
on the area of greater Copenhagen 60% are spinouts and only 40% are incumbents. The more we move away from the
university, the more decreases the number of spinouts and increases the number of incumbent licensees. The licensees
from abroad change the picture completely as incumbents make up 90% of these licensees. Thus, this pattern is an
evidence of strong localization of codified and patented knowledge.
Altogether, we identified 147 commercialization contracts with 113 firms. This means that some firms have had
repeated transactions with the university over time. Those are incumbents twice as many as spin-outs that have had
repeated transaction, 11 firms. Most of them having two contracts; and only one large company has signed a contract
with the university 9 times at different points in time.
6
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Incumbents
Spinouts
Micro
9
36
Small
14
15
7
1
Large
10
0
Very large
18
0
Medium
Table 1 Total number of incumbents and spinouts per firm size
Licensee firms can be divided according to their size 2. Table 1 marks significant differences when refered to the size of
incumbents and spinouts. Almost all of the spinouts are micro or small, except one medium size. On the other hand,
almost half of all incumbents are large or very large firms having ten thousands of employees. Acs, Audretsch, and
Feldman (1994) found that university research has greater impacts for small firms than for large firms and that these
effects differ across industrial sectors. Because almost all spinouts are micro or small firms, therefore, we could assume
that contracts signed with spinouts and firms have greater impact than for large incumbent firms which probably have a
rich portfolio of other patents.
4.3. Technologies and industry sectors
There is some notion in the literature that patenting activity differs across industries and across firm sizes (Alkaersig,
2015). Therefore, we can assume that also licensing of these patents will have similar characteristics and show
differences across industries and firms that in-license patents. This paper aims to reveal a part of interesting relationship
between industries and commercialization patterns.
There are two ways to identify the industry: by technology (patent class or international patent coding) or by licensee
firm´s industry code. We follow the logic of identifying licensee industry as this data will more precisely indicate to
what industry in the market particular technology has contributed and what industry benefits from university´s research
output.
For purposes of international comparability we apply internationally recognized industry classification system
developed by European Union – NACE3 that derives from United Nations' International Standard Industrial
Classification of all Economic Activities (ISIC), yet is more detailed than ISIC (NACE Rev. 2 Introductory Guidelines).
NACE classification provides a framework to collect statistical data according to economic activity of firms in the
market and also allows the comparability of statistics acquired in different statistical domains. As most of the firms in
our sample are Danish firms they possess also an activity code according to Danish national classification system,
Dansk Branchekode 2007 (DB07) that is maintained by Statistics Denmark and has minor subdivision differences from
NACE rev. 2, but wouldn’t be possible find one for international companies and make international comparisons.
Therefore, we apply NACE classification of economic activities that is a well-established and systematic way of
collecting firm data.
Many other authors have used patent codes as the gateway to technology sector and industry. However, because we aim
to explore the economically active firms and market side of technology commercialization process, we focus on the
output of those firms, and this output is classified by NACE economic activity code. We assume that this will provide
us a better understanding of the role that patents play for firms in the market.
2
According to Statistics Denmark, micro firm has 1-10 employees, small: 20-49 employees, medium: 50-99 employees,
large: 100 – 250 employees, very large: 250+ employees
3
NACE in French means "Nomenclature générale des Activités économiques dans les Communautés Européennes" (Statistical
classification of economic activities in the European Communities). Source:
http://ec.europa.eu/eurostat/documents/1965800/1978839/NACEREV.2INTRODUCTORYGUIDELINESEN.pdf/f48c8a
50-feb1-4227-8fe0-935b58a0a332
7
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Spinouts
Incumbents
0% 2% 0%
2% 2%
C
3%
D
F
32%
G
23%
44%
J
K
52%
0%
0%
6%
M
7%
N
2%
2%
6%
12%
P
2% 3%
Q
Figure 5 Distribution of all spinouts and incumbents according to NACE classification
Figure 5 compares industry distribution among two licensee groups: spinouts and incumbents. There are two economic
sectors that dominate in both groups, namely manufacturing (C) and professional, scientific and technical activities (M).
Not surprisingly, most of the contracted spinouts are occupied with scientific activities, while incumbents with
manufacturing meaning that they continue along the activity lines we are used to expect from them. However, 32% of
spinouts are also active as manufactures. This is an exciting finding, because recalling Table 1, we know that spinouts
are micro or small companies, so available resources of these new firms are very limited and they mainly employ 1-10
people. A further study would be necessary to measure growth and survival of these new technology firms telling more
about their actual success and market impact.
A remarkable difference between spinouts and incumbents is that the third largest economic sector group among
incumbents is wholesale and retail trade (G), whereas it is represented only by 1 spinout. Sector D (electricity, gas,
steam and air conditioning supply) covers 3% of incumbents, but not a single spinout. This is unexpected result from
spinouts of a technical university who has strong emphasis on sustainability and green energies. The same pattern
applies for human health and social work activities (Q).
On the contrary, 6% of spinouts and only 2% of incumbents are representing information and communication (J) sector.
If this study would apply to all spinouts and start-ups of the university, then the cover of this sector would increase even
more. Yet, we limit our study to those firms that poses a patent from the university, and therefore, we find it rather
significant to see firms who have found ways to patent in this sector despite European unpatentability of IT software.
4.4. Geographical distance
“Geography, in the most fundamental sense, provides organization for the diverse
types of knowledge needed for new product commercialization.” (Feldman,
M.,1994, p.2)
Geographical distance from the university to the licensee can be important from two perspectives. First, it indicates the
role university´s research plays for regional economy. Second, it indicates the importance of geographic proximity
between licensor and licensee that can lead to innovative product development and production due to exchange of tacit
knowledge.
Ideally, according to geographic economic theories as well as policy postulates, academic research results should
directly benefit and enrich the regional economy of that university. In that situation, university´s input into regional
economy would justify all the expectations.
Numerous previous studies have focused on spatial proximity as the facilitator of the economic impact of university
knowledge production. Geographical localization of knowledge diffusion has been found in the US as well as in Europe
(Fischer and Varga, 2003; Jaffe and Trajtenberg, 1996; Hall, Jaffe and Trajtenberg, 2000).
For regional knowledge based economy the presence of university and its spillovers are an important precondition for
the development and innovation. A whole section of literature researches on geography of innovation by investigating
spatial differences in knowledge production. Jaffe et al. (1993) methodology has become the basis of the patent-based
8
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
geography of innovation literature. In their paper Jaffe et.al. were tracing the geographic localization of knowledge
spillovers by patent citations. They found that spillovers were geographically correlated and firms geographically close
to the inventor had higher probability of benefiting from knowledge spillovers than other firms.
S. Belenzon and M. Schankerman (2013) followed up this research line and by using Google maps measured the actual
geographic distance between the locations of licensors and licensees. They show that knowledge flows from patents
decline dramatically with distance up to around 100 miles and there is a strong evidence of a state border constraining
effect.
In a more recent paper Mowery and Ziedonis (2015) track the geographic incidences of knowledge flow from
universities by using two measures, licenses and patent citations. They found out that knowledge flows via license
contracts are more geographically localized than via nonmarket spillovers. This especially concerns licenses with
exclusive rights more than non-exclusive contracts.
Adams (2002) compared localization of academic and industrial spillovers and concluded that university spillovers are
more localized than industrial spillovers from R&D activities. This suggests that firms tend to look for research, advice
and personnel at local universities, whereas industrial collaboration takes place over a greater distance and occur
selectively. Additionally, spillovers are weaker and even more localized for new products (Adams, 2002).
Several cross-sectional studies have indicated the tendency of technology-intensive firms to locate near universities as
these firms often combine their production activity with research and development (Audretsch and Stephan, 1996;
Bania et al, 1993; Glasmeier, 1991; Goldstein, H., & Drucker, J.,2006). On the other hand, Audretsch and Stephan
(1996) examined locational links between companies and scientists in biotechnology sector and concluded that that
geographic proximity is important only for the transfer of informal knowledge between firms and universities, but not
for formal market mediated channels like licensing, because these are usually “carefully planned” face to face contacts
and for those meetings the actual location of the partner doesn’t influence formal meeting times.
Cross-continental
Incumbents
Europe
Spinouts
Other universities
Denmark
0
20
40
60
80
100
Figure 6 Total number of licensees per location and venture type
Our data (Figure 6) confirm the pattern for licensees of university inventions to locate in close proximity to those
universities
Additionally, there is an evidence in the literature that 93 percent of the world’s recent patent applications were filed by
inventors living in metropolitan areas with only 23 percent of the global population (J.Rothwell, 2012) and in the US 92
percent of patents are concentrated in just 100 metropolitanian areas with 59 percent of the population (J.Rothwell,
2013, p.1). This indicates the dominant role of metropolitan areas over more peripheral areas in terms of patenting and
innovating activity. Further, Rothwell found that patented inventions drive long-term regional growth, especially high
quality patents that are funded by governments. Thus, patents tend to concentrate in metropolitan areas and sustain
regional economic performance. Yet, we cannot assume that patents originating in one geographic location will also
spill over economic benefits for the same location, because a set of preconditions (the presence of a skilled labour force,
a business system providing complementary goods and services, financing and marketing assets) have to be met for
invention to be commercialized.
The university under our study is located not directly inside the capital of Denmark (Copenhagen), however, in the
greater metropolitan area around Copenhagen that settles approximately 20 % of Denmark´s population. Our findings
confirm the overall tendency for knowledge flow from university concentrates in large metropolitanian areas (Table 2).
Greater area of Copenhagen locates 2/3 of all licensees, and together with the territory of the rest of Denmark they
locate more than 80% of licensees.
9
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Firm location
Incumbents
Spin-outs
Other Universities
Total
Greater area of Copenhagen
31
44
1
76
Rest of Denmark
11
5
1
17
US
8
0
0
2
France
2
0
0
1
Norway
1
1
0
1
Sweden
1
1
0
1
Germany
1
0
0
2
Malaysia
1
0
0
1
Netherlands
1
0
0
2
Spain
1
0
0
1
Switzerland
1
0
0
8
59
51
2
Total
Table 2 Total number of licensees per location and venture type
112
In sum, Denmark accommodates 83% or totally 93 licensees out of which 49 are spinouts, 42 are
incumbents and 2 are other universities. The rest of Europe accommodates 8 incumbents and only 2
spinouts. Licensees coming over European borders account only for 9 incumbents and no spinouts.
Not surprisingly, from all spinouts having a commercialization contract with DTU almost 96% are located in a close
geographical proximity with university, in the greater area of Copenhagen, and many of these are located directly on the
campus (mainly within the science park). Thus, spinouts localize geographically closer to the university than do
incumbent licensees.
And because most of the technologies are sold to Danish companies, it shows that university´s main contribution is
primarily for regional and national market needs and main industries around the capital, and following the logic of Jeffe
et.al. (1993), also the knowledge spillovers of those patents will be rather spilled in the area around the capital (as most
licensors can be found in this area). Yet, this is a research question for another paper and will not be more explored
here.
10
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Picture 1 Greater area of Copenhagen and the location of the university (Source: http://susreg.eu/case-study-capitalregion-of-greater-copenhagen/ )
5. Conclusions
In contrast to the classical research on patent commercialization, this paper sheds a new light on commercialization by
broadening the scope of commercialization contract exploration and investigates in what ways and with what means
university research reaches the market through market transactions. This paper maps commercialization landscape and
finds some patterns in commercialization process. This is a new contribution with new evidence from a European
university to the technology transfer literature.
In result, this analysis draws a profile of a firm who is the potential client of the university´s inventions. Patent licensing
is almost equally distributed among incumbents and spinouts as licensees. From industry perspective, there are two
industries that dominate for both these venture types: manufacturing and professional, scientific and technical activities.
However, significant differences among licensees emerge when accounting for firm size. Namely, all spinouts are micro
or small firms, while almost half of the incumbents are large or very large companies. Geographically, greater
metropolitan area of Copenhagen locates 2/3 of all licensees, and together with the territory of the rest of Denmark they
locate more than 80% of all licensees. This indicates to the strong pattern of localization, this is especially evident for
spinouts who locate geographically closer to the university than do incumbent licensees.
We hope that this paper can help universities to see in which directions they should develop their technology transfer
strategies and which are directions or markets that still lack a clear use of university innovations. In order to increase
manufacturing among spinouts and, thus, increasing scalability and growth of new firms, governments and universities
should support the new technology ventures that explore patented inventions, especially at their early premanufacturing stage – prototyping that for some technologies can turn out to bee to expensive and time consuming.
One of the main implications for this paper is to draw attentions of different stakeholders when making management
decisions and researchers to be more cautious about making conclusions that are based on patent data as a tool to
explore commercialization implications at universities.
This paper is only a descriptive representation of some patterns and tendencies for commercialization of university
inventions, but more research should be done based on our findings. Future research should continue to explore
relationships between licensee innovation performance and firm characteristics, between licensees´ represented
industries and patent characteristics.
11
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
References
Act No. 347 of 2 June 1999 on inventions at public research institutions
Adams, J. D. (2002). Comparative localization of academic and industrial spillovers. Journal of Economic
Geography, 2(3), 253-278
Audretsch, D. and M. Feldman (1996). "R&D Spillovers and the Geography of Innovation and Production." The
American Economic Review 86(3): 630-640
Audretsch, D.B., Lehmann E.E. (2005). Does the knowledge spillover theory of entrepreneurship hold for regions?
Research Policy, 2005
Audretsch, D.B., Stephan, P.E. (1996) Company-scientist locational links: the case of biotechnology. The American
Economic Review, 86 (3), pp. 641–652
Baldini, N.(2006) The Act on inventions at public research institutions: Danish universities’ patenting activity.
Scientometrics, Vol. 69, No. 2, p.387–407
Belenzon, S. and Schankerman M., “Spreading the Word: Geography, Policy, and Knowledge Spillovers,” Review of
Economics and Statistics 95 (2013) 884–903
Bozeman,B., Gaughan,M.,2007.Impacts of grants and contracts on academic researchers’ interactions with industry.
Research Policy 36, p.694–707
Braunerhjelm, P.; Z. J. Acs, D. Audretsch, and B. Carlsson. 2010. The Missing Link: Knowledge Diffusion and
Entrepreneurship in Endogenous Growth. Small Business Economics, 34:105-125
Bruneel, J., P. D’Este, and A. Salter (2010). Investigating the factors that diminish the barriers to university–industry
collaboration. Research Policy 39(7), 858–868
Cohen, W. M., R. Florida, L. Randazzese, and J. Walsh (1998). Industry and the academy: uneasy partners in the cause
of technological advance. Challenges to research universities 171(200), 59
Etzkowitz, H., 1998. The norms of entrepreneurial science: cognitive effects of the new university–industry linkages.
Research Policy 27, 823–833
Etzkowitz, H., 1983. Entrepreneurial scientists and entrepreneurial universities in American academic science. Minerva,
21(2), pp.198–233
Feldman, M. P. (1994). The geography of innovation. Boston, MA: Kluwer Academic
Finn, V., Lund Jensen, R. Effects on academia-industry collaboration of extending university property rights.
Journal of Technology Transfer, Vol. 32, No. 3, 2007, p. 251-276
Gisling, V. Differences in technology transfer between science-based and development-based industries: Transfer
mechanisms and barriers. Technovation, 31 (2011), 638–647
Goldstein, H., & Drucker, J. (2006). The economic development impacts of universities on regions: Do size and
distance matter? Economic Development Quarterly, 20, 22-43
Gulbrandsen,M., Smeby, J.C. 2005. Industry funding and university professors’ research performance. Research Policy,
34 (2005), pp. 932–950
Hwang, V.W., 2013. The Rainforest Blueprint: How to Design Your Own Silicon Valley | Unleash an Ecosystem of
Innovation in Your Company, Organization, or Hometown 1 edition., Regenwald.
Jaffe, A.B., Trajtenberg, M. and Henderson, R. “Geographic Localization of Knowledge Spillovers as Evidenced by
Patent Citations,” The Quarterly Journal of Economics 108 (1993) 577–98)
12
Paper submitted to:
R&D Management Conference 2016 “From Science to Society: Innovation and Value Creation” 3-6 July 2016, Cambridge, UK
Link, A.N., Welsh, D.2013. From laboratory to market: On the propensity of young inventors to form a new business.
Small Business Economics (40): 1-7
Markman, G. D., P. T. Gianiodis, et al. (2009). "Supply-Side Innovation and Technology Commercialization." Journal
of Management Studies 46(4): 625-649
Mowery, D. C. and B. N. Sampat (2001). "Patenting and Licensing University Inventions: Lessons from the History of
the Research Corporation." Industrial and Corporate Change 10: 317-355
Mowery, D. C. and B. N. Sampat (2005). "The Bayh-Dole Act of 1980 and universityindustry technology transfer: A
model for other OECD governments." Journal of Technology Transfer 30: 115-127
Mowery, D. C. and A. Ziedonis (2001). "The Geographic Reach of Market and Nonmarket Channels of Technology
Transfer." N.B.E.R. working paper 8568
Mowery, D., 2005. The Bayh-Dole Act and high-technology entrepreneurship in US universities: chicken, egg, or
something else. University Entrepreneurship and Technology Transfer. Amsterdam: Elsevier, pp.39–68
Mustar, P., Wright, M. & Clarysse, B., 2008. University spin-off firms: Lessons from ten years of experience in Europe.
Science and Public Policy, 35(2), pp.67–80
Nerkar, A. & Shane, S., 2003. When do start-ups that exploit patented academic knowledge survive? International
Journal of Industrial Organization, 21(9), pp.1391–1410
O’Shea, R.P., Chugh, H. & Allen, T.J., 2007. Determinants and consequences of university spinoff activity: a
conceptual framework. The Journal of Technology Transfer, 33(6), pp.653–666
Phan, P.H., Siegel, D.S., 2006. The effectiveness of university technology transfer: lessons learned from qualitative and
quantitative research in the US and UK.Foundations and Trends in Entrepreneurship 2, 66–144
Rasmussen, E. & Wright, M., 2015. How can universities facilitate academic spin-offs? An entrepreneurial competency
perspective. The Journal of Technology Transfer, 40(5), 782–799
Rothwell, J., “Global Innovation: The Metropolitan Edition,” The Avenue blog at The New Republic, March 16, 2012
Shane, S.A., 2004. Academic Entrepreneurship:University Spinoffs and Wealth Creation. Edward Elgar, Cheltenham
Siegel, D.S., Waldman, D., Link, A., 2003. Assessing the impact of organizational practices on the relative productivity
of university technology transfer offices: an exploratory study. Research Policy 32, 27–48
Veugelers, R., & Del Rey, E., 2014. The contribution of universities to innovation, (regional) growth and employment.
EENEE Analytical Report No. 18
Wang, Y, Li-Ying, J, Chen, J & Lu, Z 2015, 'Technology licensing in China. Science and Public Policy, (42), 293-299
Welter, F., 2011. Contextualizing Entrepreneurship—Conceptual Challenges and Ways Forward. Entrepreneurship
Theory and Practice, 35(1), 165–184
13