The impact of academic technology: Do modes of involvement
matter? The Flemish Case
Callaert, Julie
KU Leuven – INCENTIM – ECOOM, Waaistraat 6 - bus 3536, 3000 Leuven, Belgium
Julie.Callaert@kuleuven.be
Du Plessis, Mariette
KU Leuven – ECOOM, Waaistraat 6 - bus 3536, 3000 Leuven, Belgium
Mariette.Duplessis@kuleuven.be
Van Looy, Bart
KU Leuven - Department of Management, Strategy and Innovation –INCENTIM – ECOOM,
Naamsestraat 69, 3000 Leuven, Belgium
Bart.Vanlooy@kuleuven.be
Debackere, Koenraad
KU Leuven - Department of Management, Strategy and Innovation –INCENTIM – ECOOM
Naamsestraat 69, 3000 Leuven, Belgium
Koenraad.Debackere@kuleuven.be
Keywords: academic patenting; patent value; university inventors
JEL classification: O31, O34
1
Abstract
Patent statistics that reflect university technology development have become increasingly relevant
as academia adopts entrepreneurial objectives while facing a trend towards more accountability. In
this contribution, we focus on the patent activity of Flemish universities (period 1991-2001). In
Flanders, university patenting has become explicitly incentivized through policy measures (1996)
and more recently even resource allocation schemes resulting in a notably high share of
universities in the overall patent portfolio of the regional innovation system. As a result, one might
expect inflationary effects on the level of academic patents, especially in terms of quality. In
addition, we analyze, whether the impact of academic patents depends on the mode of university
involvement (university-invented versus university-owned). Overall, we observe a considerable
increase in both types of academic patenting without any deterioration (over time) of citation rates.
Moreover, our findings indicate that university-owned patents receive more forward citations than
university-invented (firm-owned) patents. Combined, these findings signal that the increase of
academic patent activity – stimulated by policies granting ownership rights to universities – did not
coincide with a decrease in their value.
2
1. BACKGROUND AND RESEARCH OBJECTIVE
Patent indicators that reflect the contribution of universities to technology development have
become increasingly relevant for mapping and monitoring science-technology interactions within
innovation systems. As academic research is facing a trend toward more accountability, indicators
are used to assess the quality and quantity of academic activities. Whereas the monitoring of
educational and scientific activities has a long tradition, the assessment of ‘third mission’ activities,
including patent activities, have only recently become an explicit part of performance evaluation in
a number of countries. Traditional bibliometric indicators are complemented with, among other,
patent-related indicators (Butler, 2003). These evolutions require an understanding of the modes
under which academic involvement in patent activity becomes apparent. A considerable number of
empirical studies have analyzed the phenomenon of academic patenting by relying on data about
patents owned by universities, i.e. patents for which the academic institution acts as assignee. At the
same time, several studies have shown that university-owned patents do not reveal a complete
picture of university involvement in technology development: a considerable share of patents
invented by university researchers, are not owned by the university but - in most cases - by a firm
(for an overview: see Lissoni et al., 2008). The empirical evidence collected in this respect suggests
that academic patents, invented but not owned by universities, are not a peculiar feature of
European countries (Balconi et al., 2004; Iversen et al., 2007; Lissoni et al., 2008; Meyer, 2003;
Saragossi and van Pottelsberghe, 2003), but also exist in the USA (Fabrizio & DiMinin, 2008;
Thursby et al., 2009). However, the proportion of university-invented patents over total academic
patents is higher in Europe than in the USA (Lissoni et al., 2008). Balconi et al. (2004) e.g. found that
over 60% of Italian academic patents are owned by firms, which is almost three times the share
calculated for the USA (Lissoni et al., 2008).
3
Given that a considerable amount of university-invented patents are not owned by universities, it
becomes relevant to assess whether and to what extent both types of university patents display
different characteristics. Indeed, while both types of technology exploitation trajectories are
different in terms of whether or not a partnering firm is involved – as owner of the technology –
less is known about whether both types of academic patents differ in terms of impact. A number of
studies investigated this question recently.
Henderson et al. (1998) explored the increase in US academic patenting that took place between
1965 and 1990. They found that, before the introduction of the Bayh-Dole act until about the mideighties, academic patents were more highly cited and cited by more diverse patents than a random
sample of all patents. After that, however, this difference in terms of impact disappeared. In other
words, the steep increase in volume and share of academic patenting was much higher than the
increase in impact of these patents. The authors attribute this to shifts in university patenting
behavior. Mowery & Ziedonis (2002) from their part argue that the increase was largely due to the
entry of inexperienced university technology transfer offices which might also partially explain a
decrease in impact.
Sapsalis et al. (2006) analyzed a sample of Belgian academic patents (EPO) and observed that the
value distributions of academically owned and academically invented patents (owned by firms) are
very similar (highly skewed). In addition, the authors observe that, conditional on being cited,
academic patents are cited more than corporate patents (respectively, 7.1 and 5.9 citations).
The same conclusion was drawn in a recent study by Veugelers et al. (2012) who studied the
creation and impact of academic patents for OECD countries, by means of an analysis of
cross
country citation patterns between academic and corporate patents. Although a smaller share of
university patents was cited (compared to company patents), the study reveals that, in terms of
impact (average number of citations received, conditional on being cited), university patents are
4
cited more than company patents; especially for some technological domains like Polymers,
Measurement and control, Chemicals, and Machinery.
Czarnitzki et al. (2011) analyzed German EPO patents. They compared university-invented patents1
(which they refer to as academic patents) to a control group of ‘non-academic’ patents (on which no
university inventor appears). Higher opposition rates are considered as a proxy for the more
applied nature of the patented invention, indicating that it is closer to market applications. The
authors find that opposition rates are related to patent impact (measured by forward citations) and
that academic patents (university-invented) are cited more than non-academic patents. In terms of
ownership, Czarnitzki et al. (2011) observe that university-invented patents with firm applicants
do not significantly differ from firm patents (in terms of opposition). Conversely, academic patents
assigned to universities display a lower opposition rate than firm patents and firm-owned
university-invented patents. The authors suggest that this is due to the fact that university-owned
inventions are further away from market applications than corporate patents. Given their
fundamental and complex nature, the technological content takes a longer time to diffuse (see also
Sampat et al., 2003). Therefore, university-owned patents would be less threatening to potential
competitors and less likely to face oppositions.
Thursby et al. (2009) analyzed a sample of US university-invented patents and found that,
university-invented patents assigned to firms are less basic2 than those assigned to universities.
Crespi et al. (2010), in their analysis of a sample of European university patents conclude that there
is little evidence in support of the contention that university-owned patents would be more
valuable than university-invented patents owned by firms. Sterzi (2013) performed a similar study,
analyzing the value of UK academic patents by distinguishing between university-owned and
1
In Germany, the professor’s privilege allowed professors to patent their inventions until 2002 privately without
university involvement.
2
But note that the authors’ measure of basicness (higher number of backward citations, spread over a larger range
of fields) is debatable.
5
university-invented patents. During the first 3 years, university-invented (corporate-owned)
patents receive more citations than university-owned patents. This difference however erodes
when considering longer time frames.
In line with these studies, we examine whether and to what extent Flemish academic patents
display a different impact depending on the ownership of the inventions. Belgium, and especially
the Flemish region, is of specific interest due to the relative high proportion of university-owned
patents. This is primarily incited by institutional regulations, aimed explicitly at stimulating the
‘entrepreneurial’ role of universities (see Debackere & Veugelers, 2005). When the governance of
Belgian universities became a regional responsibility at the beginning of the 1990s, a set of
regulations have been approved (1993, 1996), stipulating that all IP from university researchers
would belong by default to the university3. In addition, university patenting in Flanders is actively
incentivized by dedicated resource allocation schemes (Debackere & Glänzel, 2004). Since 2004,
each Flemish university receives funding from the IOF (Industrial Research Fund) for financing
follow-up research that is aimed at transferring academic research towards market exploitation.
The amount of financial support received for these activities partly depends on indicators reflecting
patent applications and grants (as well as indicators reflecting involvement in spin off creation)
obtained by universities. Rounded, the IOF funding comprises about 2,5% of research funding (and
1,5% of total funding) for Flemish universities. As a result of these regulations, Flemish universities
have been increasingly involved in the valorization and patenting of research results: over the
period 1991 – 2008, when the share of university-owned patents in Flanders has increased from
3
Notice that universities are free to transfer these rights to third parties, including industry, as long as a fair
compensation is implied. It is left to the discretion of the universities to define and implement relevant guidelines
in this respect.
6
3% to 9%4. As universities have become increasingly involved in patenting activities, the question
arises whether this growth also influences the quality or impact of academic patents.
2. DATA & METHODOLOGY
We analyze Flemish academic patents, evaluating whether university-owned patents differ from
university-invented patents in terms of impact. Patent data are extracted from the PATSTAT
database (October 2011 edition) and imply all Flemish universities: University of Leuven (KU
Leuven), University of Ghent (UG), University of Antwerp (UA), University of Hasselt (UH) and
University of Brussels (VUB). For each of these universities, university-owned and universityinvented patents have been identified. EPO and USPTO granted patents are considered, with
application years between 1991 and 2001. The cut-off point at application year 2001 allows for a
comparable forward citation window of 10 years for calculating indicators based on forward
citations. We considered only grants to ensure a consistent approach for both EPO and USPTO
patents5.
2.1. Dependent variables: impact and generality
Two forward-looking measures of patent value are considered as dependent variables. First,
forward patent citations are counted. This measure is commonly used to assess the value or the
importance of the invention. Ample empirical evidence has revealed a strong and robust relation
between forward patent citations and other measures of patent quality, like oppositions, renewal
data, monetary value, and firm creation (Sapsalis & van Pottelsberghe, 2007; Lanjouw &
Schankerman, 1997, 1999; Shane, 2001; Harhoff & Reitzig, 2004; Harhoff et al., 2003). A 10-year
forward citation window was used for calculating forward citations. We opted for this ‘long’
window to accommodate for potential longer citation lags for university-owned patents (cf. Sterzi,
4
See Flemish Indicator Book 2011 (http://www.ecoom.be/indicatorenboek)
For EPO information on applications is also available, while this is not the case for USPTO (at least not for the
considered time period).
5
7
2013)6. Besides this fixed time window, no further restrictions were placed on the citing patents (in
terms of patent system).
A complementary measure related to patent value is ‘generality’. Generality captures the extent to
which the patented technology serves as prior art for a broader range of technology fields
(Trajtenberg et al., 1997; Hall et al., 2005; Jaffe & Trajtenberg, 2003; Dahlin and Behrens, 2005;
Fleming et al., 2007). If a patent is cited by subsequent patents that belong to a wider range of
fields, the generality of that patent is considered higher. If most citations are concentrated in one or
a few fields, generality is low (close to zero). Generality is calculated as 1- the Herfindahl index of
technological classes (3-digit IPC) of all citing patents7. While forward citations are indicative of the
impact of a patent, a high generality score suggests that the patent presumably has a widespread
impact, in that it influences subsequent innovations in a variety of fields.
Throughout the literature, it has been argued that academic patents (on average) represent more
basic, fundamental developments, of a more embryonic nature (Czarnitzki et al., 2009; Thursby et
al., 2009; Feller & Feldman, 2010). As indicated by Czarnitzki et al. (2009), this assumption is often
made in the literature and in policy discussions, e.g. on the financing of science (Mansfield, 1995),
on economic growth (Adams, 1990; Caballero & Jaffe, 1993; Stokes, 1997). Firms from their side
focus on research and development that result in more immediate market returns. Moreover, it has
been argued that fundamental / basic research can have broader applications - and therefore
higher social value - than more application-oriented private science (Agrawal & Henderson, 2002).
These arguments suggest that university-owned patents may be more general than firm-owned
patents.
6
Notice that similar analysis which considered only a 5-year citation window have been performed and revealed
similar results as the ones reported in section 3.
7
The Herfindahl-index for concentration is calculated as the sum of the squared shares of IPC3 domain
occurrences among the citing patents. No restrictions were placed in terms of patent authority of the citing
patents.
8
2.2. Independent variable: University-owned versus university-invented patents
University-owned patents have been identified as patents with a Flemish university as (co)applicant. An exhaustive identification of university applicants has been achieved by relying on
sector allocation and name harmonization algorithms, developed at KU Leuven – ECOOM (Eurostat,
2011). Table 1 shows the proportional evolution of Flemish patents by applicant types (firms,
universities, government / non-profit agencies and individuals). With an average share of 6.56%
university patents, Flanders displays a high proportion of academically owned patents (compared
to an average of 1,24% in EU-15: see Veugelers et al., 2012). Moreover, a growth in university
patenting is apparent over the considered period, and becomes especially pronounced from 1996
onwards after the introduction of above mentioned Flemish decrees, stipulating the role of
universities in terms of valorisation (Debackere & Veugelers, 2005).
--- Insert table 1 --From a methodological perspective, identifying ‘university-invented’ patents in an exhaustive
manner is not straightforward, as patent databases lack information on the institutional affiliation
of inventors. Several alternatives to identify university inventors have been advanced. E.g. for
Germany, Czarnitzki et al. (2009, 2011) and identified academic inventors by searching inventor
names containing “Prof. Dr.” and variations of it. For other countries, where the use of professional
titles on official documents is less common, identifying academic inventors implied a matching of
inventor names with university personnel directories (see Lissoni et al., 2006). The identification of
university-invented patents was based on a name matching between personnel lists of Flemish
universities (for the years 1990-2000) and patent inventor names (all inventor names appearing on
EPO and USPTO granted patents with application years between 1991 and 2001). The matching
was performed on surnames of the university personnel and the patent inventors. A first inspection
of identified matching pairs served at eliminating certain mismatches / false hits. After this step,
9
1.152 USPTO and 382 EPO patents remained that possibly involved academic inventors. For all of
these potential matches, contact details of the involved university researcher were retrieved in
order to contact the researcher in question directly (via email or phone) to confirm involvement as
an inventor. In the final database, only confirmed matches were retained. In other words: 100%
precision was prioritized over recall for identifying university-invented patents. Figure 1 provides a
schematic overview of the procedure followed to identify university-invented patents.
--- Insert figure 1 --For this Flemish population of identified academic patents, about 70% are university-invented.
Table 2 shows the breakdown by technology domain (with full counts for patents allocated to more
than 1 domain). A chi square test (Pearson = 55.184***) reveals that Physics and Electricity are to a
larger extent university-owned whereas Chemistry and Performing operations, Transporting are
less university-owned. Due to the very low patent volumes in domains D (Textiles, Paper), E (Fixed
constructions) and F (Mechanical engineering; Lighting; Heating; Weapons; Blasting), these
domains were eliminated from the analyses in the remainder of the study, hence all analyses on the
level of technology domain are based on a total of 710 observations8.
--- Insert table 2 --Table 3 presents the breakdown by patent system: no significant difference between the
proportions of university-owned versus university-invented patents is observed for EPO versus
USPTO grants. The table does reveal that the number of USPTO granted patents is almost 4 times
higher than the number of EPO granted patents in the same period. This is due to a combination of
at least two causes. First, more patents are filed at the USPTO than at EPO9. This is at least partly
8
The analyses with originality and/or generality will be based on fewer observations: patents without any
backward and/or forward citations respectively have no originality and/or generality score.
9
Detailed figures for Flanders can be found in the Flemish Indicator Book (ECOOM, 2011)
10
due to the lower cost of procedure at USPTO, compared to EPO (van Pottelsberghe & François,
2009). Second, the grant rate at USPTO is higher than the grant rate at EPO (OECD, 2004, p.145).
--- Insert table 3 --As can be seen in table 4, 92% of the identified university-invented patents are owned by a firm. For
university-owned patents, 19% is co-owned with a non-profit or governmental institute, 8% is coowned with a company and 6% is co-owned with an individual. Within the analysis, patents coowned by academia are considered as university owned. In terms of academic patents not owned
by universities, we focus on industry-owned academic patents, as the numbers for other types of
assignees do not allow for meaningful multivariate analysis.
--- Insert table 4 --2.3. Covariates and control variables
Throughout the analyses, we control for several patent characteristics, including application year,
technological domain on IPC 1-digit level and patent system (EPO / USPTO: accounting for
differences in citation practices between systems).
We additionally include the following variables, inspired by the existing literature on patent value:
-
Technological scope (number of IPC3 digit codes): Following Lerner (1994), the number of
technology domains assigned to a patent is included as a measure of patent scope.
-
Originality of the invention (breadth of technology fields cited in the backward citations10):
This measure was developed by Trajtenberg et al. (1997) and relies on backward citations
(patent references). It is calculated as 1- the Herfindahl index reflecting the concentration of
(front page) references included in the patent document across technology domains. The
10
For the calculation of originality, all backward cited patents are considered (i.e. without any restrictions in terms
of patent system, citation origin, citation type,…)
11
originality score is higher if the range of classes to which the patent makes citations is
higher. A score of 0 indicates that all citations to prior art stem from a single technology
domain, whereas a scores close to 1 indicates that backward citations are spread over a
broad range of domains. A patent is considered more ‘original’ if it cites prior art from many
rather than few technology classes. Notice that this indicator can only be calculated if the
patent document includes references.
-
Number of backward patent citations11: Backward citations of patents qualify the technical
novelty of a patent (Reitzig, 2003; Van Looy et al., 2007). They determine the legal
boundaries of an invention by citing related work, referring the extent of existing and
related patenting in a given technological area and hence to the potential profitability of
inventions (Czarnitziki et al., 2009).
-
Number of non-patent references: this indicator signals the importance of scientific
knowledge to qualify the novelty and scope of the patented invention (Van Looy et al.,
2007). More scientific references signal science proximity, which might indicate
technological activities of a more basic nature12.
3. ANALYSES AND RESULTS
In what follows, we present several models that allow evaluating the evolution of impact and
generality; and whether university-owned and university-invented patents differ in terms of impact
and generality. Table 5 presents the correlations between the variables under study. All indicators
related to scope (i.e. originality, number of IPC classes and generality) are significantly and
positively correlated. The correlation between application year on the one hand and backward and
11
All backward cited patents are considered (i.e. without any restrictions in terms of patent system, citation origin,
citation type,…)
12
Note that the validity of this indicator has been subject of discussion, based at least partly on the argument that
these citation links do not represent direct links between the scientific research and the patented invention (see
e.g. Meyer, 2000; Tijssen et al., 2000; Alcacer & Gittelman, 2006; Breschi & Lissoni, 2001; Van Looy et al., 2007).
12
forward citations on the other hand suggest that more recent patents cite more prior art and that
they receive more forward citations (over a fixed 10 year time window)13.
--- Insert table 5 --A negative binomial regression is used for analyzing differences in impact. The results in table 6a
indicate no decline of impact over time. Secondly, university-owned patents receive more forward
citations than university-invented patents. The significant interaction between ownership and
patent system stems from more outspoken differences for EPO patents, as can be seen in the
descriptive statistics reported in table 6b. As obtaining EPO patents implies more financial
resources than obtaining USPTO patents (van Pottelsberghe & François, 2009), this observation
might signal a ‘selection effect’ whereby EPO grants are more likely to be pursued for more valuable
inventions. For firms, financial considerations may be subordinate to strategic and market
concerns, resulting in less selectivity when filing for patents in different patent systems.
In terms of control variables, the main effect of patent system indicates that US patents receive
more citations than EP patents. This effect is at least partly due to the fact that US patents contain
more (backward) references, combined with the observation that – as further analysis of our
sample of patents reveals –US-to-US cited-citing pairs accounts for 87% of all observed citations.
The higher impact of the US patents in our sample can therefore at least partly be attributed to the
fact that they are cited more by US patents: i.e. their forward citing patents are the ones that contain
higher volumes of backward citations.
Technological scope and the number of non-patent references are negatively related to impact. In
previous studies, the relation of both variables with impact revealed mixed results (Sapsalis & van
Pottelsberghe, 2007). Whereas a positive relation between patent scope and impact was uncovered
Although the latter observation may seem surprising, further analyses will show that this relation between
application year and impact disappears when other variables are controlled for within more appropriate
multivariate models (cf. infra table 6a).
13
13
by Lerner (1994), Shane (2001), and Czarnitzki et al. (2011), this relation was challenged by other
studies (Harhoff et al., 2003; Harhoff & Reitzig, 2004; Guellec & van Pottelsberghe, 2002; Lanjouw &
Schankerman, 1997). For non-patent references, Harhoff and Reitzig (2004) and Czarnitzki et al.
(2011) found no relation with patent value. Arts et al. (2013) report a positive relation (for
biotechnology patents), whereas Sterzi (2013) found a negative relation. Indeed, as indicated by
Sapsalis et al. (2006), analyzing and interpreting the impact of literature citations on the value of a
patent is not straightforward. Citations to the scientific literature indicate the relevance of scientific
knowledge for qualifying the underlying invention. This relevance might signal novelty and hence
be associated with higher levels of future value. This assumption is not confirmed in our analysis. At
the same time, it can be noted that all patents under study involve academic inventors, which
qualifies this study as less appropriate to contribute to an understanding of the relationship
between both variables.
In terms of the number of backward patent citations, the relation with impact appears more robust
in the literature (Czarnitzki et al., 2011; Sapsalis & van Pottelsberghe, 2007) and our findings
confirm these insights. Originality, or the scope of backward citations, is not related to impact.
--- Insert table 6a&b --For studying whether university-owned patents have a broader impact, i.e. whether they are cited
by a larger number of technological fields a GLM analysis was performed with generality as
dependent variable. The results in table 7a reveal no difference between university-owned and
university-invented patents. There is a main effect of the patent system, revealing that US patents
are more general than EPO patents14, as can also be seen in the descriptive statistics presented in
table 7b. The higher generality for US patents is in line with the observation that US patents receive
14
Note that, when including an interaction effect between patent system and ownership (as in the model for
impact), both the interaction term and the main effect of patent system become insignificant.
14
more citations (see also table 6a) implying an increased likelihood that these citations stem from a
wider range of technological domains. The variables related to technological scope (of the focal
patent as well as of the backward cited patents, i.e. originality) are positively related to generality.
Unlike for impact (see table 6a), our results show no domain-specificity for generality.
--- Insert table 7a&b --4. CONCLUSIONS AND DISCUSSION
As the volume of academic patents increases, concerns have been uttered about detrimental effects
in terms of quality and value (Mowery & Ziedonis, 2002; Lacetera, 2009; Czarnitzki, 2011). This
study examines the value of Flemish academic patents during a period of growing patent activity,
incited by policy measurements for stimulating a more entrepreneurial role of universities. We
distinguish between modes of involvement by comparing university-owned to university-invented
patents.
First of all, our findings show no decline in impact over time. Second, university-owned patents
receive more forward citations than university-invented (firm-owned) patents. As such, these
findings indicate that the increase of academic patent activity – stimulated by policies granting
ownership rights to universities – does not coincide with a decrease in ‘quality’. Rather, our findings
appear to be in line with previous studies that signal a higher impact of academic patents,
compared to firm-owned patents (e.g. Czarnitzki et al., 2009, 2011; Henderson et al. 1998; Sapsalis
et al., 2006).
Our findings further reveal that the higher impact of university-owned patents is more explicitly
present for EPO patents. As the costs of EPO patents are considerably higher than for USPTO
patents (van Pottelsberghe & François, 2009), it seems plausible to infer a selection effect:
universities might be more prone to pursue EPO patents for their more valuable inventions. Our
15
findings do not confirm any difference in terms of generality between both types of academic
patents. University-owned patents are as ‘general’ as university-invented patents.
While the Flemish innovation system displays an outspoken high proportion of university-owned
patents (compared to other European countries and the US), an even larger number of academic
patents are owned by industry (in line with figures from other countries/regions). This again
underscores that identifying university-invented patents remains crucial for creating a more
encompassing picture of university involvement in technological activities. These figures at the
same time suggest that stimulating universities to become more entrepreneurial does not
jeopardize the transfer of relevant knowledge to industrial partners.
In terms of future research, a further examination of the underlying rationale of the observed
relations seems worthwhile to pursue. Why and when are patents held by universities, rather than
transferred to industrial partners (which might include academic spin offs) and what are the
implications in terms of value creation (technical, scientific as well as commercial)? In addition, a
further development and routinizing of methodologies for identifying university-invented patents
on a larger scale (based on automated or semi-automated approaches) seems highly relevant given
the reported figures in this study. The resulting potential for extraction of comparative data that
cover a wider set of countries /regions allows for the analysis of national / regional differences and
the extent to which these differences are related to institutional and regulatory contexts. The
fragmented and mixed evidence that is currently available from empirical studies on the value of
academic and corporate patents, underscores the relevance of such more encompassing efforts.
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21
TABLES AND FIGURES
APPY
Firm
Government
Individual
University
1991
89.06%
3.22%
4.51%
2.79%
1992
91.58%
1.72%
5.15%
1.37%
1993
92.69%
1.49%
3.58%
2.09%
1994
92.19%
1.37%
4.66%
1.37%
1995
88.93%
2.64%
5.91%
2.52%
1996
87.66%
2.02%
5.10%
5.10%
1997
90.06%
0.70%
4.37%
4.47%
1998
84.76%
1.54%
6.25%
7.28%
1999
86.01%
1.47%
4.99%
7.20%
2000
86.20%
1.75%
4.74%
7.32%
2001
85.17%
2.54%
5.42%
7.12%
2002
84.59%
1.91%
6.55%
6.71%
2003
85.37%
1.41%
5.05%
8.09%
2004
85.30%
3.09%
3.94%
7.38%
2005
83.43%
2.94%
4.92%
8.64%
2006
85.77%
2.10%
4.26%
7.45%
2007
84.27%
2.90%
3.25%
9.40%
2008
85.58%
2.43%
2.83%
9.03%
Average
86.40%
2.11%
4.74%
6.56%
Table 1 – Sector shares in Flemish patent activity (EP applications)
IPC (1 digit)
A. HUMAN NECESSITIES
B. PERFORMING OPERATIONS;
TRANSPORTING
C. CHEMISTRY; METALLURGY
D. TEXTILES; PAPER
E. FIXED CONSTRUCTIONS
F. MECHANICAL ENGINEERING; LIGHTING;
HEATING; WEAPONS; BLASTING
G. PHYSICS
H. ELECTRICITY
TOTAL
Universityinvented
136 (74%)
59 (88%)
Universityowned
47 (26%)
8 (12%)
183 (100%)
67
(100%)
196
2
2
2
63
3
1
0
259 (100%)
5
(100%)
3
(100%)
2
(100%)
(76%)
(40%)
(67%)
(100%)
66 (58%)
38 (44%)
501 (70%)
(24%)
(60%)
(33%)
(0%)
48 (42%)
49 (56%)
219 (30%)
Total
114
87
720
(100%)
(100%)
(100%)
Table 2 – University-invented versus university-owned patents, broken down by field (Flanders,
application years 1991-2001)
22
University-invented University-owned Total
EPO grants
58 (62%)
35 (38%)
93 (100%)
USPTO grants 258 (68%)
119 (32%)
377 (100%)
Total
316 (67%)
154 (33%)
470 (100%)
Table 3 – University-invented versus university-owned patents: EPO vs USPTO (Flanders,
Application year 1991-2001)
SECTOR
% university-invented patents
COMPANY
92%
INDIVIDUAL
5%
GOV NON-PROFIT 3%
Table 4 – Sector breakdown university-invented patents
23
IMPACT (10Y
WINDOW)
APPL YEAR
GENERALITY
ORIGINALITY
# BW NON-PAT
REFERENCES
TECH SCOPE
# BW PATENT
REFERENCES
Pearson Corr
Sig. (2-tailed)
N
Pearson Corr
Sig. (2-tailed)
N
Pearson Corr
Sig. (2-tailed)
N
Pearson Corr
Sig. (2-tailed)
N
Pearson Corr
Sig. (2-tailed)
N
Pearson Corr
Sig. (2-tailed)
N
Pearson Corr
Sig. (2-tailed)
N
IMPACT
(10Y
WINDOW)
1
710
APPL
YEAR
GENERALITY ORIGINALITY
,154**
,000
710
,035
,402
577
-,118**
,004
599
1
,006
,888
577
1
-,034
,409
599
,379**
,000
544
1
710
577
599
# BW NONTECH
# BW
PAT
SCOPE
PATENT
REFERENCES
REFERENCES
,001
-,213**
,132**
,000
,980
,000
710
710
710
,043
,249
710
,082*
,049
577
,166**
,000
599
1
710
-,040
,290
710
,234**
,000
577
,376**
,000
599
,026
,496
710
1
710
,180**
,000
710
,040
,342
577
,192**
,000
599
,699**
,000
710
-,077*
,039
710
1
710
Table 5 – Correlations between model variables
24
Dep Var: IMPACT (10Y WINDOW1)
Source
Wald Chi-Square
df
Sig.
B param
2,492
1 ,114
-68,33
13,832
1 ,000
2,039
8,080
1 ,004
-,434
tech IPC1= PERFORMING OPERATIONS; TRANSPORTING
13,193
1 ,000
-,730
tech IPC1= CHEMISTRY; METALLURGY
12,250
1 ,000
-,522
,354
1 ,552
,093
(Intercept)
OWNERSHIP (1: university-invented; 2: university-owned)
tech IPC1= HUMAN NECESSITIES
tech IPC1= PHYSICS
tech IPC1= ELECTRICITY (reference category)
.
.
18,373
1 ,000
1,890
2,396
1 ,122
,034
,054
1 ,817
-,057
6,590
1 ,010
-,008
13,209
1 ,000
-,215
6,409
1 ,011
,017
11,770
1 ,001
-,997
.
PATENT SYSTEM (1: EPO; 2: USPTO)
APPL YEAR
ORIGINALITY
# BW NON-PAT REFERENCES
TECH SCOPE
# BW PATENT REFERENCES
PATENT SYSTEM * OWNERSHIP
Likelihood ratio Chi square (N=599)
1 The
.
126,879***
same analysis with a 5 year citation window reveals consistent results.
Table 6a – Impact of academic patents (Negative Binomial Regression)
Patent System
Ownership
Mean
Std. Dev.
EPO
University-invented
2,76
3,734
42
University-owned
7,03
11,238
32
University-invented
7,94
9,628
373
University-owned
10,70
14,348
152
University-invented
7,41
9,333
415
University-owned
10,07
13,900
184
USPTO
TOTAL
N
Table 6b – Descriptive statistics: Impact (10 year window) by ownership and patent system
25
Dep Var: Generality 10 year window1 (GLM)
Source
Type III Sum of
Squares
Corrected Model
df
Mean
Square
F
Sig.
B
Param
,491 12,352 ,000
---
1
,027
,690 ,407
6,541
,055
1
,055
1,397 ,238
tech IPC1= HUMAN NECESSITIES
,039
1
,039
,993 ,319
-,030
tech IPC1= PERFORMING OPERATIONS;
TRANSPORTING
,014
1
,014
,353 ,552
-,023
tech IPC1= CHEMISTRY; METALLURGY
,001
1
,001
,017 ,896
,004
tech IPC1= PHYSICS
,036
1
,036
,903 ,343
,029
tech IPC1= ELECTRICITY (reference
category)
.
.
.
PATENT SYSTEM (1: EPO; 2: USPTO)
,904
APPL YEAR
5,398a
11
Intercept
,027
OWNERSHIP (1: university-invented; 2:
university-owned)
.
.
1
,904 22,764 ,000
,152
,027
1
,027
2,361
1
# BW NON-PAT REFERENCES
,054
1
,054
1,371 ,242
,001
TECH SCOPE
,419
1
,419 10,549 ,001
,036
# BW PATENT REFERENCES
,145
1
,145
Error
21,135 532
,040
Total
186,061 544
ORIGINALITY
Corrected Total
.
,023
,692 ,406
-,003
2,361 59,423 ,000
,350
3,658 ,056
-,002
26,533 543
a. R Squared = .203 (Adjusted R Squared = .187)
1 The
same analysis with a 5 year citation window reveals consistent results.
Table 7a – Generality of academic patents (General Linear Model)
Patent System
Ownership
Mean
Std. Dev.
N
EPO
University-invented
,4308
,28093
24
University-owned
,4052
,25058
29
University-invented
,5616
,19865
146
University-owned
,5550
,21207
491
University-invented
,5443
,22392
369
University-owned
,5357
,21538
175
USPTO
TOTAL
Table 7b – Descriptive statistics: Generality by ownership and patent system
26
Figure 1 – Procedure for identification of university-invented patents
27