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ENTREPRENEURSHIP:
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STARTSTART-UP
ACTIVITY
INTERNAL
IMPACTS
EXTERNAL
IMPACTS
Human Capital
INDICATORS OF ACADEMIC ENTREPRENEURSHIP:
Monitoring determinants, start-up activity and wealth creation
Universidad Miguel Hernández de Elche
José María Gómez-Gras
Jesús Tadeo Pastor-Ciurana
Domingo Galiana-Lapera
Ignacio Mira-Solves
Antonio José Verdú-Jover
With the collaboration of GlobalStart partners: Universiteit Twente; Universidad de Salamanca;
Katholieke Universiteit Leuven Research & Development; University of Warwick; Finance Wales
PLC; Vysoké učení technické v Brnĕ (Brno University of Technology); Universitas TaruensisUnversity of Tartu.
INDEX
INTRODUCTION ................................................................................................ 5
1. WHY MONITOR ACADEMIC ENTREPRENEURSHIP? .............................................. 8
1.1 The role of the academic entrepreneurship ...................................................... 9
1.1.1. The driving forces to foster academic entrepreneurship ................................. 10
1.1.2. Development and implementation of policies and strategies to foster academic
entrepreneurship .............................................................................................. 10
1.2. University and global start-ups ..................................................................... 13
1.2.1. The university as a source of global start-ups............................................... 15
1.2.2. The current challenges of academic global start-ups...................................... 15
1.3. Indicators as units of strategic information................................................... 19
1.3.1. Features of suitable indicators of academic entrepreneurship.......................... 22
2. METHODOLOGICAL ISSUES ........................................................................... 24
2.1. Goals and theoretical framework................................................................... 25
2.2. Methodology.................................................................................................. 28
2.2.1. Literature review...................................................................................... 28
2.2.2. Exploration of existing indicators ................................................................ 29
2.2.3. Delphi survey .......................................................................................... 30
3. FINDINGS ................................................................................................... 33
3.1. University determinants. A literature review ................................................. 34
3
3.2. Indicators used in benchmarking surveys...................................................... 51
3.2.1. OECD: survey on the patenting and licensing activities of pros ........................52
3.2.2. The AUTM licensing survey ........................................................................57
3.2.3. HEFCE: higher education-business interaction survey (HE-BCI) .......................64
3.2.4. UNICO survey: university commercialisation activities ...................................69
3.2.5. Proton Europe survey................................................................................74
3.2.6. APRU: technology transfer and wealth creation (T2WC) survey .......................81
3.2.7 GlobalStart project: benchmarking survey ....................................................87
3.2.8. Summary checklist of benchmarking survey indicators...................................93
3.3. Delphi survey results ..................................................................................... 98
4. SET OF INDICATORS .................................................................................. 103
4.1. Overview ..................................................................................................... 104
4.3. Remarks and recommendations of use ........................................................ 107
Policies & strategies indicators........................................................................... 109
Stock of technology indicators ........................................................................... 110
Resources & initiatives indicators ....................................................................... 114
Human capital indicators .................................................................................. 118
Start-up activity indicators................................................................................ 121
Internal impact indicators ................................................................................. 125
External impact indicators................................................................................. 129
5. FINAL REMARKS ........................................................................................ 139
REFERENCES ................................................................................................. 141
4
Introduction
INTRODUCTION
In a knowledge economy, science is exerting a more important and direct influence on
innovation, especially in fast-growing new industries. The intensity and quality of this
relationship plays an increasing role determining returns on investment in research, in terms of
competitiveness, growth, job creation and quality of life. They also determine the ability of
countries to attract or retain increasingly mobile qualified labour (OECD 2002).
Industry-science relationships are undergoing fundamental changes prompted by globalisation
and other factors as part of an overall trend towards accelerated development of a market of
knowledge. In the recent period, policy attention in most countries has tended to focus
increasingly on the role of industry-science relationships in fostering entrepreneurship in fastgrowing new industries (OECD 2002).
In Europe, an ambitious strategy to become “the most competitive and dynamic knowledgebased economy in the world” was defined in the Lisbon European Council of 2000, emphasizing
the need for the creation of an environment conducive to starting up and developing innovative
businesses and, especially small and medium sized enterprises. One of the most visible
transformations is the emergence of broad alliances between universities and firms, and
growing activity in the realm of commercialisation of research results through licensing of
intellectual property and, particularly, the interest in the creation of spin-off companies (OECD
2002). The Lisbon Council and the communication of the European Commission "Innovation in a
Knowledge-driven Economy” highlight the relevance of spin-offs in the European Innovation
Policy, which will have a strategic role in the 7th EU Research Framework over the period 2007
to 2013.
Traditionally considered as an important source of new technology, universities are increasing in
recent years the use of the creation of new firms as vehicle to exploit research results, mainly
stimulated by changed societal external expectations for economic development and internal
pressures to generate new sources of income, becoming a key element of the innovation system
both as a human and technology capital provider and a seed-bed of new firms.
5
Introduction
Despite the interest in academic entrepreneurship, governments (OECD, 2002) and universities
(Wright, 2004; HEFCE, 2004), in some aspects, lack specific information and tools to monitor
academic entrepreneurship, evaluate their efficiency, analyse trends and learn from each other
in the search for good policy practices. Policy makers are greatly interested in revenues from
publicly funded intellectual property rights. Because many countries have recently enacted
reforms to encourage technology transfer and invested in academic entrepreneurship
infrastructure, policy makers would like to know when these new technology transfer initiatives
will become self-sufficient. In addition, being able to anticipate the financial returns to a given
intellectual property portfolio would be very useful for both universities and governments
(OECD, 2003).
Moreover, academic entrepreneurship activity should not be solely evaluated via economic
returns to the university but should be considered by wider social and economic benefits such as
the diffusion of knowledge or the contribution to employment. Thereby, the implemented
systems in universities for the measurement and evaluation of the entrepreneurship’s
institutional support and its impacts should contemplate the different views and expectations of
every involved stakeholder. From the point of view of universities, a performance measurement
system of academic entrepreneurship can support them in the development of tasks such as:
Analysis of captured data for the development of university policies, strategies and
initiatives related to academic entrepreneurship.
Short, medium and long-term planning: target setting, monitoring of trends and analysis of
results.
Dialogue, development of joint initiatives, and benchmarking with external stakeholders:
policy makers, funding institutions, universities, chambers of commerce, local development
agencies, etc.
This publication has been produced in the framework of the GlobalStart Project (2003-2006),
which is part of the Pilot Action of Excellence on Innovative Start-ups (PAXIS) of the European
Commission. The main objective of the project is encourage and support the creation of globalstart-ups in academic environments through the development, validation and diffusion of
6
Introduction
methodologies, instruments and tools for assisting new global entrepreneurs and university
structures of business creation support such as technology transfer offices and spin-off
programmes. The consortium of the project, which involves eight partners (seven universities
and a regional development agency) of different European regions, aware of the need of
monitoring academic entrepreneurship, resolved to take actions to fulfil the detected needs
related to the monitoring of academic entrepreneurship, and particularly, in the topic of
international entrepreneurship.
This study intends to provide stakeholders on academic entrepreneurship with a whole view
concerning the issues involved in the measurement of entrepreneurship process, in order to
make them to reflect about the aspects that should be considered for evaluation according to
their scopes. Stakeholders can find in this publication an analysis of current efforts on behalf of
institutions and researchers to measure academic entrepreneurship performance. Concretely: a
checklist of internal resources and capabilities of universities that are correlate with the start-up
activity (derived from a literature review), and a comprehensive checklist of indicators used for
measuring them (derived from a review of benchmarking surveys on technology transfer and a
Delphi survey among experts on entrepreneurship).
Finally, this publication includes a proposal of a set of indicators in order to be used as an
orientation tool for those entrepreneurial universities interested in the development or
improvement of data capture and performance measurement systems. Concretely, indicators
are grouped into seven subsets which shape the framework for monitoring academic
entrepreneurship. Four of these dimensions comprise indicators for the measurement of “inputs”
implied in the entrepreneurial process: policies and strategies, stock of technology, resources
and initiatives and human capital. The indicators for the measurement of “outputs” of the
university entrepreneurial process are included in three subsets, which comprise start-up
activity, and internal and external impacts, as measures of wealth creation.
7
1. WHY MONITOR ACADEMIC
ENTREPRENEURSHIP?
8
Why monitor academic entrepreneurship?
1.1 THE ROLE OF THE ACADEMIC ENTREPRENEURSHIP
New technology-based firms are a key feature of the modern knowledge economy, contributing
to the development of regional high tech clusters and the transformation of investments in basic
science into economic growth, employment and competitive advantage (Schumpeter, 1934;
Drucker, 1985; Teece, 1981; Griliches, 1990; Roberts, 1991; Autio, 1994, 1997, OECD, 2003).
According to Oakey (1995), the two major sources of new technology-based firms are wellestablished industrial firms (corporate spin-offs) and universities (academic spin-offs), which
have been traditionally considered as an important source of new technology (Jaffe, 1989;
Rosenberg and Nelson, 1996; Mowery et al., 2001), Mainly stimulated by changed external
expectations for economic development and internal pressures to generate new sources of
income (figure 1.1.1.), universities are increasing in the recent years the use of new companies’
creation as vehicle to exploit university inventions (DiGregorio and Shane, 2003; Feldman et al.,
2003).
3RD MISSION
(ENTREPRENEURSHIP)
Development
Driving forces
POLICIES
AND INSTITUTIONAL
STRATEGIES
EXPECTATIONS
INTERNAL / EXTERNAL
IMPACTS
Implementation
Figure 1.1.1. General steps in the development of an entrepreneurial university.
9
Why monitor academic entrepreneurship?
1.1.1. The driving forces to foster academic entrepreneurship
Following changes in government control (OECD, 2002), universities to an increasing extent
have to argue for their economic role and demonstrate their societal impact in order to obtain
public funding. This shift is arguably arising from both the internal development of the
university and external influences on academic structures and in some cases from the
increasing predominance of innovative clusters at the regional level.
Although education and research have traditionally been the university's main missions, this has
gradually changed with the emergence of new perspectives on the role of the university in the
system of knowledge production. According to Fairweather (1990), academic institutions can by
appearing to respond to social needs and economic development enhance their public image,
which in turn can lead to accountability for funding, taking a more direct role as actors in
regional and national economic development (Martin and Etzkowitz, 2001). Furthermore, this 3rd
university's mission, involving academic entrepreneurship, opens the possibility for many higher
education institutions to get a broader source of funding from non-governmental or public
organisations.
Hence, universities are becoming key elements of the innovation system contributing to
economic development both by interaction with existing industry and by other types of
commercialisation of knowledge, like the establishment of new firms (Rasmussen, in press).
1.1.2. Development and implementation of policies and strategies to foster academic
entrepreneurship
The entrepreneurial universities have the ability to generate a focused strategic direction, both
in formulating academic goals and in translating knowledge produced within the university into
economic and social utility (Clark, 1998). Nevertheless, polices and strategies developed and
implemented by universities are influenced by a range of internal and external factors, leading
10
Why monitor academic entrepreneurship?
to take particular approaches and affecting in this manner academic entrepreneurship
performance.
For instance, DeGroof and Roberts (2004), taking the case of Belgium, identified four
archetypes of academic spin-off policies in environments outside of high tech clusters and where
technology transfer and entrepreneurship infrastructures had been weak. Examining policies in
terms of the extent to which they engaged in origination, concept testing and start-up phase
activities, the four archetypes identified affecting growth potential of ventures were: an absence
of proactive spin-off policy; minimalist support and selectivity; intermediate support and
selectivity; and high support and selectivity. However, they note that high selectivity and high
support spin-off policies represent an ideal to achieve rather than an immediate accessible
policy since such a policy require considerable resources which individual academic institutions
seldom have access to in these environments.
Other study (Clarysse et al., 2004) identified three board types of spin-off incubator models that
have proven their efficiency: the low selective model; the supportive model; and the incubator
model. The first model supports the creation of self-employment oriented spin-offs. These
companies are predominantly service oriented. The second model stimulates the creation of
economic profitability oriented spin-offs. These spin-offs might be growth oriented, but usually
start with some kind of service or consulting model to limit the time to breakeven. This is
different for the third type, where financial gain from an eventual exit is paramount.
In summary, the different environments where a university is involved might influence its level
of commitment towards academic entrepreneurship in terms of formal institutional policies.
Developing formal policies may send a signal, but the levels of new venture formation appear
correlated with various configurations, different transfer strategies and other internal variables,
processes
and
university
resources,
including
the
individual
behaviour
of
potential
entrepreneurs.
11
Why monitor academic entrepreneurship?
In this landscape of supporting academic entrepreneurship, many single mechanisms could be
important, but there is a need for a complete system, a good interplay between the different
initiatives and policies, and an effective internal management to succeed. A holistic evaluation
of entrepreneurship should help to fulfil these internal needs of universities, providing strategic
information for decision-making processes. Furthermore, its role and contribution to the society
also should be evaluated form the point of view of external stakeholders that are providing
institutional support, since this formal support contributes to the business creation.
12
Why monitor academic entrepreneurship?
1.2. UNIVERSITY AND GLOBAL START-UPS
The process of supporting the creation of academic new ventures is a dynamic and complex task
that requires an on-going adaptation to the changes of the needs of nascent academic
entrepreneurs and new firms. In this sense, the phenomenon of globalisation is a clear example
of how changes in terms of commercialisation are affecting the current needs of many new spinoffs, and therefore how the support offered to them on behalf of universities should be adapted.
The modern business world is characterized by globalisation, which could be defined as the
international connectivity of markets and the interdependence of national economies. This
connectivity means a firm's competitors, suppliers, and customers are to be found throughout
the world.
According to Acts (2001), most observers agree that three forces drive the globalisations of
business. The first is the explosive growth in low-cost technology connecting people and
locations. Better information processing and communications technology creates a greater
awareness of international economic opportunities. It also lets companies divide their production
processes more.
A second driving force behind the globalisation of business is the steady dismantling of the
world trade barriers. Free-trade agreements have generated a more wide-open playing field for
innovative firms. This makes sense because financial success for an innovator often hinges
critically on the size of his market.
A third force motivating the globalisation of business is the widespread economic restructuring
and liberalization that followed the fall of socialism in Russia and Eastern Europe. These hitherto
closed areas are becoming new markets and magnets for investment, opening further
opportunities for growth and investment.
13
Why monitor academic entrepreneurship?
In this dynamic world of global entrepreneurial discovery, two features stand out. The first is
the widespread effort to innovate and bring innovations to the global marketplace. The second
is the wider and deeper competitive pressure forcing firms to scan the globe for more efficient
ways to do business. As a result, the landscape of competition changes, and the
internationalisation of value chain activities of companies occurs, that is, they increase their
involvement in international business activities.
The traditional theories and models of firms’ internationalisation suggested that the process
occurred gradually. Perhaps, the most popular is the Uppsala model (eg, Johanson and Vahlne,
1977). This model portrays internationalisation as an incremental process that depends on the
firm’s experimental knowledge of foreign markets. Nevertheless, further studies showed a rapid
internationalisation pattern of some new ventures that contrasted the traditional “stage-models”
(Johansson and Wiedersheim, 1975; Bilkey and Tesar, 1977; Johansson and Vahlne, 1977) of
firms’ internationalisation.
These international new ventures have been examined and classified under several names:
global start-ups (e.g, Mamis, 1989;Ray, 1989; Oviatt and McDougall, 1994; born global firms
(e.g., Rennie, 1993; Knight and Cavusgil, 1996; Knight, 1997), global high-technology firms
(e.g., Roberts and Senturia, 1996). Although these names have been treated as synonymous,
for instance global start-ups and born global firms (e.g, Blomstermo and Sharma, 2002;
Harveston, 2000; Moen, 2002), according to Oviatt and McDougall (1994) the global start-up is
the most radical manifestation of the international new ventures, defining them “as new firms
that derive significant competitive advantage from extensive co-ordination along multiple
organisational activities, the location of which is geographically unlimited”. Such firms do not
only respond to globalising market but also proactively act upon opportunities to acquire
resources and sell outputs wherever in the world they have the greatest value.
14
Why monitor academic entrepreneurship?
1.2.1 The university as a source of global start-ups
According to Waakee & Van der Sijde (2002), universities are an important source of potential
global start-ups. This statement is consistent with the argument that the presence of global
start-ups is more common in high tech sectors (see for instance Lindqvist, 1991; Roberts &
Senturia, 1996; Lindell & Karagozolou, 1997 Harveston, 2000; Saarenketo & Aijo, 2000), where
technologies
involved
in
university
research
activities
are
found
(biotechnology,
nanotechnology, etc). Thus, universities are a source of global business opportunities and
ventures with unique intangible assets, which are more able to internationalize quickly and
successfully (Oviatt & McDougall, 1995), although the challenges of these academic global startups are in likely different from those with non-academic origins.
1.2.2. The current challenges of academic global start-ups
Setting up global activities while still being in the start-up phase remains a very complex task.
After all, global start-ups, do not only have to deal with the usual problems associated with the
launching of a new venture, such as accumulating resources, building reputation, finding
partners and attracting customers. Madsen and Servais (1997) point out that the factors
influencing the propensity to form a global start-up as well as its further performance are
grouped into three levels (figure 1.2.1).
15
Why monitor academic entrepreneurship?
ENTREPRENEUR LEVEL:
ORGANISATION LEVEL:
•Global entrepreneurial orientation (global vision)
•Knowledge/technology intensity
•International experience (skills)
•Innovativeness of the technology
•International networks
•Imitability and legal protection
•Managerial capabilities
•Competitive advantages/firm strategy
•Resources employed/needed
Propensity
GLOBAL
START-UP
Further
Performance
ENVIRONMENT LEVEL:
•Industry profits and sales growth
•Domestic market (limited, saturation)
•Foreign markets (intensity of competition, profitability)
•Economies of scale
•Restrictive government policies
•Institutional environment
Figure 1.2.1. Factors influencing propensity to create a global start-up and its further performance.
Source: adapted from Madsen and Servais (1997).
In this sense, universities must play and important role helping academic entrepreneurs to
overcome these needs, as well as creating an international entrepreneurial culture for the
development of potential global start-ups in the academic environment. The main current needs
of academic global start-ups and the support offered by universities to fulfil them are related to:
Lack of commitment towards internationalisation.
Globalisation is also inevitable since in many technological sectors the necessary resources and
potential partners are scarcely available and scattered around the globe as well. Global or cross-
16
Why monitor academic entrepreneurship?
border opportunities are created because technological innovations facilitate international
activities and reduce its costs to a great extent.
A number of authors have therefore suggested that creating a global vision is also very
important for entrepreneurs who want or need to set up global activities (McDougall et al.,
1994; Cavusgil and Knight, 1997; Harveston, 2000). If such a global vision is lacking,
entrepreneurs either might not be able to recognise international opportunities or not be willing
to exploit these opportunities when recognised. Since academic entrepreneurs have little or no
management experience, they usually have not learned to identify (business/market)
international opportunities and act upon them. In this sense, the cognitive processes of the
entrepreneur seem to have an important effect on the international capabilities of the firm
(Barlett & Goshal, 1989; Kobrin, 1994).
Lack of managerial experience and international skills
Many founders of high tech ventures do not have any or fairly little entrepreneurial or business
experience. These entrepreneurs often have a background in the research –based academic
environment (Cooper, 1971; Roberts and Wainer, 1966; Schrage, 1965; Wainer and Rubin,
1969). These scientist or research technical entrepreneurs have been described as individuals
whose primary occupation, prior or concurrent to playing a role in the global start-up, was that
of a clinician, researcher or teacher affiliated with a university, research institute or hospital
(Samson and Gurdon, 1990). Setting up international activities requires knowledge of
international markets and an international network that, usually, has not yet been established at
this early stage in the firm’s development.
Lack of resources for the internationalisation
Academic global start-ups also have to deal with an enormous lack of resources, such as time,
money and credibility. Although this problem is inherent to most newly established ventures, it
is possibly even perceived stronger by high tech global start-ups. In order to reach all major
17
Why monitor academic entrepreneurship?
markets of their sector, high tech start-ups would have to cope with variations in the cultural,
legal, scientific and technological environments in different countries. High tech ventures are
highly specialised and operate in niche markets. For some start-ups in certain emerging sectors
globalisation is inevitable, and offers interesting opportunities. It is inevitable because high R&D
expenditure can often not be compensated by sales in the domestic market alone; finding
foreign customers is therefore essential. This means that the domestic market is usually small
or even non-existent (Roberts, 1991; McDougall and Oviatt, 1996; Burgel et al., 1999; Wakkee
et.al., 2001).
Further, the required investments in R&D are often considerable, while product life cycles are
relatively short. Furthermore, initiating global activities often means extensive travelling abroad
to obtain information about specific markets (Harveston, 2000). Such travels take up not only
financial resources, but also time. Often the entrepreneur cannot dedicate sufficient time to this,
as he has to take care of other issues. Furthermore, academic entrepreneurs, although typically
part of an extensive academic network, often have not yet built a business network that
provides them with access to or information about resources, markets, partners or customers.
18
Why monitor academic entrepreneurship?
1.3. INDICATORS AS UNITS OF STRATEGIC INFORMATION
Several studies indicate that formation of university spin-off companies is likely to generate
more revenue than licensing (Gregory and Sheahen, 1991; Bray and Lee, 2000; Rogers et al.,
2001). Rasmussen et al. (in press) suggest that there are three main reasons for a university to
focus on creating new firms rather than collaborating with existing ones.
First, companies that are created out of activities at the university will most often start out as
partners who acknowledge the university's competence, financial situation, and special longterm mission. The companies may thus become important future contractors.
Second, collaboration with existing industry can be highly influenced by the general economic
cycle. In economically rough periods, attempts at creating new firms could be made relatively
easier and receive public attention and support. Most countries would also be highly interested
in universities contributing to new economic activity and jobs, particularly if the alternative is to
enter a negative ‘lock-in’ relationship with existing industry, where the universities cease to be a
source of more radically new knowledge and innovations.
The third reason is the visibility of spin-off firms. The impact of collaborative interaction with
existing industry in terms of job creation or innovative new products is difficult to measure. The
establishment of new firms might be a more visible output of university activity and may be
used in the university struggle for public funding.
Although nowadays the main core of interest has been moved from the accumulation of
information towards its selection and processing, governments (OECD, 2002) and universities
(Wright, 2004) lack specific information and tools to monitor academic entrepreneurship,
evaluate their efficiency, analyse trends and learn from each other in the search for good policy
practices.
19
Why monitor academic entrepreneurship?
For instance, the Higher Education Funding Council for England, which conducts yearly a
technology transfer survey among UK universities, indicates in the 2004 survey report that
many institutions still find difficult to return financial and numeric data, specially when are
request to detail on their spin-off companies. The OECD (2003) also indicates that many
universities do not yet monitor the formation of spin-offs or start-ups, despite their political and
potential economic importance. Rasmussen et al. (in press) point out that to visualize the
contribution to economic development in one of the current challenges of universities.
These kind of evidences point out a growing interest in arrange a quality and strategic potential
data through the implementation of data capture systems on which both decision-makers and
implicated in the university can have a thorough knowledge and a concise diagnostic of the
reality of the institution regarding to academic entrepreneurship. Despite this interest, certain
issues regarding to the monitoring of the academic entrepreneurship could be difficult to carry
out. In this sense, Lockett et al. (2004) indicate that the number of spin-offs created are fairly
clear objective measures for universities, although setting objectives in terms of the wealth
creation from spin-offs in particular is perhaps less straightforward.
In this sense, extensive research literature (e.g., Taylor and Massy, 1996; Dolence and Norris,
1999) highlights the strategic perspective of indicators as essential elements for the dialogue
inside higher education institutions and these with their environment and the society in general.
Indicators of entrepreneurship can have different roles inside a university (figure 1.3.1). They
can provide universities with an accurate diagnosis of the academic entrepreneurship process,
which can lead to the development or re-definition of university policies and strategies to foster
new venture formation, supporting the design and implementation of specific initiatives through
the setting of targets, evaluate these initiatives in order to identify problems, and take
corrective actions to prevent non desirable impacts.
20
Why monitor academic entrepreneurship?
Formation of policies
Corrective actions
Implementation of initiatives
Problem identification
Evaluation of initiatives
Figure. 1.3.1. Frequent roles of indicators of academic entrepreneurship.
The monitoring of academic entrepreneurship process longitudinally and punctually over time
has a number of stakeholders both inside and outside the university (figure 1.3.2). We can
distinguish between internal stakeholders (namely, the university board members, managers of
spin-off programmes or other university units involved in academic entrepreneurship, and the
personnel working in these programmes and units) and external stakeholders, with whom
university holds relationships in terms of institutional dialogue, joint initiatives to promote
academic entrepreneurship, or even benchmarking with peers.
University board and others responsible for delivering entrepreneurship support services might
use entrepreneurship data to check on their own performance and to seek out scope for
improvement. University executive board can use entrepreneurship data to check that their
organizations are delivering services and deriving results in line with institutional strategies and
policies, to set long, medium and short-term targets, analyse effects of interventions, and to act
as a basis for performance rewards. Non-executive board members such as spin-off programme
managers can use entrepreneurship data to set operative targets and to hold university board
to account.
21
Why monitor academic entrepreneurship?
INTERNAL STAKEHOLDERS
EXTERNAL STAKEHOLDERS
University board
Dialogue
Government:
Medium/long-term planning
•Policy makers
Evaluation of results
•Funding Institutions
Managers of SO programmes
Short-term planning
Joint
initiatives
Evaluation of results
Personnel of SO programmes
•Business Innovation Centres
•Chambers of Commerce
•Local Development Agencies
•Industry/Business Associations
Benchmarking
•Other universities
•Venture capital
•Etc.
Figure 1.3.2. Stakeholders for a set of indicators of entrepreneurship and their relationships.
In sum, a set of indicators, common at the system, can be a useful tool for the management of
entrepreneurship in universities. Without it, some methodological gaps can be appear in the
process of evaluating the institutional performance as well as in the decision-making process
addressed to influence on it.
1.3.1. Features of suitable indicators of academic entrepreneurship
In a general context, indicators can be considered as relevant when they are showing something
interesting about the analysed issue, the institution or some elements of the production system,
the system as a whole, or when they are usefulness to decision-making. But an information unit
only has a strategic character when it affects, in a significant mode, in the processes of change,
adaptation and institutional improvement.
22
Why monitor academic entrepreneurship?
For the purpose of this study, we define the concept of indicator of academic entrepreneurship
as “a unit of strategic information about institutional performance related to entrepreneurship,
as well as about relevant factors influencing it”. We assume that suitable and strategic set of
indicators for entrepreneurial universities needs to fulfil the following criteria:
-
To
include
indicators
focused
on
relevant
aspects
of
the
academic
entrepreneurship process. They must inform about the obtained results of the university
in the fulfilment of its functions regarding to academic entrepreneurship, measuring the
added value, as well as inform about inputs, organisational features, resources and working
processes that are leading to obtain the expected results. Also, indicators must be based on
data from objective and reliable sources and available on an on-going basis.
-
To be useful for different purposes and audiences. The set must include indicators that
allow trend analysis and comparison with other jurisdictions. It’s not sufficient offering
information about the institutional performance. It’s necessary to take into account referents
to make a contrast. Criteria are needed to know whether information gathered shows if the
institution is now better or worse that was in the past, if it is better or worse in comparison
with other similar institutions, or if it has achieved its proposed goals. Furthermore, the set
must include indicators of interest for external stakeholders, like policy-makers and funding
institutions, to allow the dialogue with them.
-
Adequate levels of breakdown. The indicators must allow obtaining data with the most
precision as possible in order to generate the needed knowledge of fundamental correlations
cause-effect with strategic incidence in the decision–making processes.
23
Why monitor academic entrepreneurship?
2. METHODOLOGICAL ISSUES
24
Methodological issues
2.1. GOALS AND THEORETICAL FRAMEWORK
The main goals of this study are to make a review of the topics regarding the monitoring of the
academic entrepreneurship and to propose a set of indicators useful for universities as a
orientation tool for developing or improving their performance measurement systems.
Specifically, including in this set both driver indicators to monitor the internal determinants and
outputs indicators to monitor the start-up activity and wealth creation. To achieve them, the
four interim goals are:
•
Analyse the internal characteristics of universities in order to establish cause-effect
relationships, that is, correlations among these characteristics and the start-up activity.
•
Develop
and
propose
a
framework
model
for
monitoring
entrepreneurship
in
universities.
•
Identify and develop suitable indicators according to the selected criteria, with an
especial attention to those related to the international entrepreneurship.
•
Draw
up
and
propose
a
set
of
indicators
for
monitoring
university
internal
characteristics, start-up activity and wealth creation.
One theory within the entrepreneurship literature that has received considerable attention in
recent years is the resource-based view of the firm (Connor, 1991). The resource-based view
(RBV) is built upon the theory that an organisation's success is largely determined by the
resources it owns and controls.
Penrose (1959) characterises organisations as “a pool of resources”. She explained the
development and growth of organisations by looking at their internal resources, and how firms
utilize them and the resources acquired externally in way to ensure maximum profit. Essential
in Penrose’s theory is the idea that there are always stocks of unexploited productive services,
resources and specialised knowledge in a company conducive to economic growth and
expansion. The desire to grow in addition to the pursuit of profits is a prerequisite for the theory
of growth.
25
Methodological issues
Resources and capabilities are defined in various ways in literature. For instance, Grant (1991)
argues that: "while resources are the source of a firm’s capabilities, capabilities are the main
source of its competitive advantage". Implicit here is the notion that resources alone are not
sufficient to generate such advantages. The literature argues that firm resources, considered to
be strategic (Amit and Schoemaker, 1993 and Michalisin et al., 1997), can be important factors
of sustainable competitive advantage and superior firm performance only if they posses certain
special characteristics (Barney, 1991), and the company management must transform resources
into capability that can generate certain dividends in order to gain competitive advantages
(Chandler & Hanks 1994). To create competence is in other words not just a matter of collecting
a bunch of resources. Competence development involves complex patterns of coordination
among human beings and among human beings and other resources. Perfecting such
coordination requires learning through repetition. Capabilities can however not simply be bought
but developed gradually (Teece, Pisano & Shuen 1997), and in a strategic context this will mean
to get involved in long-term or direction-oriented competence development.
Although the resource-based view of the firm was largely developed from studies of the forprofit sector, its application in higher education is useful for sharpening the understanding of
organizational phenomenon (Powers and McDougall, 2004), such as entrepreneurial activity that
occurs there. From the point of view of the RBV, universities can be conceptualised as being in a
competitive environment with their peer institutions, competing for research funds, star faculty,
and for top-quality students, at least among institutions seeking to advance their reputations for
excellence. The competition for these financial and human capital resources has become
especially sharp in light of more institutions seeking limited public funds, cannibalising each
other's top faculty, and increasingly relying on merit aid to attract the brightest students. Public
universities also must compete more for a reduced pool of state funds. Thus, while higher
education may eschew characterizing itself as being part of a "market" or in competition like
for-profit firms, the reality is that the environment has become increasingly competitive and
market-like (Zemsky et al., 1997).
26
Methodological issues
Thus, certain resource and capabilities may provide a university with technology transfer
performance advantages. The use of the RBV at the institutional level research in universities
has revealed some insights on factors related to the academic entrepreneurship performance.
From the review of research identifying important resources and capabilities, we have identified
and proposed seven dimensions to monitor academic entrepreneurship: four input dimensions,
corresponding to the internal resources and capabilities (policies and strategies; stock of
technology;
resources
and
initiatives,
human
capital)
and
three
output
dimensions,
corresponding to start-up activity and internal and external wealth creation (figure 2.1.1).
Stock of
Stock of
Technology
Technology
Policies
Policies
&
&
Strategies
Strategies
Resources &
Resources &
Initiatives
Initiatives
START-UP
START
START-UP
ACTIVITY
ACTIVITY
Human Capital
Human Capital
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
Fig. 2.1.1. Framework proposed for monitoring academic entrepreneurship.
For the purpose of this study, the basic notions of the RBV are elaborate by re-defining generic
groups of resources and capabilities in terms of key monitoring areas.
27
Methodological issues
2.2. METHODOLOGY
The below figure shows the methodology followed to achieve the expected goal:
Existing indicators
and their characteristics
Benchmarking
indicators
PROPOSED
SET OF
INDICATORS
Literature
review
Determination of key
resources and capabilities to
monitor
Delphi survey
Indicators proposed
by experts
Figure 2.2.1. Followed methodology for the development of the set of indicators.
2.2.1. Literature review
The specific goal of the literature review is to identify the resources and capabilities of
universities that have a correlation and/or are influencing significantly the start-up activity rates
and the subsequently wealth creation. The knowledge of these cause-effect relationships is
fundamental to develop suitable indicators. For this purpose, we identified among the research
literature on academic entrepreneurship the empirical articles that analyse these relationships.
In this sense, we have noticed that the number of empirical studies focused on this topic of
technology transfer still remains limited. The main resources and capabilities are showed in a
checklist, as well as discussions for each one.
28
Methodological issues
2.2.2 Exploration of existing indicators
In
order
to
identify
and
analyse
indicators
currently
used
for
monitoring
academic
entrepreneurship, we have selected and analysed the most representative benchmarking
surveys on technology transfer that are being carried out in different regions of the world. By
reviewing
these
surveys
and
indicators
we
have
identified
the
used
methods
of
operationalisation of resources, capabilities, start-up activity and wealth creation.
The criteria to select these surveys were that they were carried out by organisations of
recognised prestige on the topic of technology transfer or entrepreneurship, including
information about the performance of universities on academic entrepreneurship, involving a
sufficient number of
universities, and/or carrying out on a regular basis. Thus, the
organisations and its analysed surveys have been the following:
•
Organisation for Economic Co-operation and Development (OECD): Survey on the
patenting and licensing activities of public research organisations.
•
Association of University Technology Managers (AUTM): The AUTM licensing survey.
•
University Companies Association (UNICO): University commercialisation activities
survey.
•
Higher Education Funding Council for England (HEFCE): Higher education-business
interaction survey (HE-BCI).
•
Proton Network: Proton Europe Survey.
•
Association of Pacific Rim Universities (APRU): Technology transfer and wealth creation
(T2WC) survey.
•
GlobalStart Project: benchmarking survey.
The indicators identified in each survey and its descriptions are showed, as well as a table
summarizing all indicators identified.
29
Methodological issues
2.2.3. Delphi survey
The operationalisation or measurement of these resources and capabilities must be adapted to
the specific environment of universities. In this sense, the Delphi methodology is a proper
approach.
In overview, Delphi is a method to structure a group communication process, which is effective
in order to let a group of individuals analyse a problem (Linston, 1975). It consists in the
selection of a group of experts who are asked about their opinions about a specific problem or
issue (in our case what indicators are suitable, and their features, for the monitoring of the
entrepreneurship in universities). Therefore while the traditional usage of the Delphi technique
is as a forecasting tool, a closely adapted approach could enjoy the benefits of being able to
generate opinion and move towards consensus on any issue that requires the input of
geographically
disperse
experts.
Kaynak
and
Macauley
(1984)
claim
that
the
Delphi
methodology is not a decision making tool, but rather a tool of analysis and as such the aim is
not to achieve a definitive answer, but instead to aid in the development of possible solutions,
based on the Delphi results.
According to the objectives, criteria for selection of key experts were identified. The experts
have to fulfil the following requisites: professional experience in entrepreneurship support
activities (managers or staff managing or controlling support activities of a spin- off/ business
creation programme); or, professional experience as lecturer or researcher in entrepreneurship
field or business administration. The profile of the Delphi survey is showed in the following
table:
30
Methodological issues
Table 2.2.1. Technical data of the Delphi survey.
Technical team
University Miguel Hernández
No. of experts
10 , from universities of : Twente, Tartu, Leuven, Salamanca, Warwick and Miguel Hernández
Rounds: 2
Date
Kind
Response rate
Results
November 03
Open-ended
questions
100%
65 proposals of indicators
January 04
Multi-item
questions
60%
41 proposed indicators
st
1
round
2nd round
For the purpose of this study, the Delphi survey was designed to be developed in two
anonymous rounds of expert estimations. The following figure shows the steps followed applying
Delphi method:
GlobalStart
GlobalStart
Research
questions
Proposed
indicators
Technical team
Technical team
Panel
Panelof
ofexperts
experts
Selection of experts
Design and send out
1st questionnaire
1st round
Answers 1st
questionnaire
Analysis of answers
Design and send out
2nd questionnaire
2nd round
Answers 2nd
questionnaire
Analysis of answers
Fig 2.2.2. Delphi survey design and development.
31
Methodological issues
A total of 10 experts participated in the Delphi survey, from the European universities of
Twente, Tartu, Leuven, Salamanca, Warwick and Miguel Hernández. For the first round, a
general questionnaire using open-ended questions (in order to glean as much information in the
exploratory stage as possible) was designed, which asked panel members to identify the issues
relating to the question under consideration. Clear instructions were given to experts about the
purpose of the indicators, and instructions to fill out the questionnaire. Questionnaires were sent
to experts using e-mail and gathered ten days after. This first round generated a overall of 65
proposals of indicators. These proposals derived from respondents were grouped where
appropriate to screen duplicate indicators, obtaining a overall of 41 indicators.
For round two, the list of proposed indicators were recorded alongside the total score (sum of all
respondents gave to each indicator) and sent back for re-consideration by the respondent.
Hence, this second questionnaire incorporated statements, in this case the proposed indicators,
and closed questions regarding to the suitability, measurability, revision period and scale of
these proposed indicators. Questionnaires were sent out using email, and were responded by six
experts (60 per cent response rate).
With these questions, we attempted to operationalise the criteria to select useful indicators.
Thus, criteria related to the question suitability were: the indicator is focused on relevant
aspects of the entrepreneurship process in institutions, the indicator measures conditions where
there is active public interest, the indicator is useful for different contexts, purposes and
audiences, and the indicator is easily understood by a wide variety of audiences. Criteria related
to the question measurability were: the indicator is based on data from objective and reliable
sources. Criteria related to the question period and scales were: the indicator requires available
data on an on-going basis to allow trend analysis and comparison with other jurisdictions. And
the indicator is used with the adequate level of breakdown.
32
Findings: literature review
3. FINDINGS
33
3.1. UNIVERSITY DETERMINANTS. A LITERATURE REVIEW
The majority of existing research on the performance of university technology transfer has
emphasized in the licensing activities rather in academic entrepreneurship. Nevertheless, in
recent years the number of research focused on determining cause-effect relationships among
internal characteristic of universities and their start-up activities is increasing, that is, the
university determinants that are affecting the start-up birth rates. The knowledge of these
relationships is fundamental for the developing of “input” indicators of the academic
entrepreneurship process.
We present a checklist summarizing the main studied resources and capabilities and their
correlations with start-up activity (table 3.1.1), as well as comments and implications for each
detected resource/capability.
34
Table 3.1.1. Correlations between internal resources/capabilities and start-up activity.
Resource/capability
Correlation with start-up activity
Di Gregorio and Shane (2003) found that more eminent universities have greater start-up activity than
Intellectual eminence
other universities.
/faculty quality
Powers and McDougall (2004) found a strong predictive nature of faculty quality in both the number of
start-ups formed and the number of IPO (initial public offering) licenses.
Patent importance
Powers and McDougall (2004) did not prove patent importance to be predictive of number of start-ups.
Total research
Lockett et al. (2004) found total research income to be consistently significant in the creation of university
income/expenditures
spin-offs.
Expenditure on IP
Lockett et al. (2004) found expenditure on IP protection to be consistently significant in the creation of
protection
university spin-offs that attract external equity finance.
Di Gregorio and Shane (2003) found that venture capital availability had no significant effect on start-up
Formal venture capital activity.
available at the
Zucker et al. (1998) found venture capital availability did not significantly influence start-up activity in
university's
biotechnology.
geographical area
Powers and McDougall (2004) found evidence that universities located in areas with more abundant venture
capital investment formed a greater number of start-ups.
Capability to access to
Lockett et al. (2004) found that external relational capabilities of the university relating to obtaining finance
external finance
were no significant in any of the models analysed.
Industry funding of
university
research/revenues
35
Licensing/technology
Powers and McDougall (2004) found industry R&D revenues, was positively predictive of both the number
of start-ups formed and the number of IPO licenses.
Di Gregorio and Shane (2003) fail to find adequate support for the argument that industry funding of
university research makes start-up activity more likely.
Di Gregorio and Shane (2003) found that low inventors’ share of royalties and a willingness to make equity
36
transfer policies and
investments in start-up companies increase start-up activity.
strategies
Lockett et al. (2004) found incentives and rewards were no significant in any of the models analysed.
Markman et al. (2005) found that licensing for cash strategy of technology transfer offices is the least
related to new venture emergence, licensing for equity strategy was positively related to new venture
formation and licensing for sponsored research was negatively related to new venture formation.
TTO archetype
Markman et al. (2005) found that the for-profit technology transfer office structure is positively related to
the transfer of new technology via new venture formation.
Di Gregorio and Shane (2003) found that the effects of university-affiliated incubators are insignificant.
University-affiliated
Markman et al. (2005) found that the technology transfer office structures non-correlated with venture
incubators
creation (traditional university and non-profit structures) were positively correlated with the presence of a
business incubator.
University venture
Di Gregorio and Shane (2003) found that the effects of university venture capital funds are insignificant.
capital funds
Powers and McDougall (2004) found age of the technology transfer office as a significant predictor of startExperience/age of
TTO
ups formed.
Lockett et al. (2004) found that the importance of experience (measured as age of the technology transfer
office) is only significant with respect to EIUSOs (spin-offs that attracted external investments) and not
with university spin-offs.
Di Gregorio and Shane (2003) found that the number of staff in the technology transfer office (as control
Number of TTO staff
variable) is significant.
Lockett et al. (2004) found the number of staff in the technology transfer office to be significant in some
partial models analysed.
Business development
capabilities
Lockett et al. (2004) found business development capabilities significant, being the level of significance
greater for the number spin-offs that attracted external investments than the number of university spinoffs that didn’t attract external investments.
Findings: indicators used in benchmarking surveys
Universities’ intellectual eminence /faculty quality
A critical human capital resource for the development of technological advances is access to
people with expert knowledge and talent. University faculty (academic staff) are a primary
source of this expertise. Research results show that more eminent universities have greater
birth rates of start-ups than other universities. Given this evidence, then, a university that has
built a high-quality faculty, something that takes considerable time, effort, and resources
(hence, it is a likely source of competitive advantage) will likely be more successful in their
technology transfer efforts than will a university with a faculty of lesser quality (Powers and
McDougall, 2004).
Although the precise mechanism through which this effect operates is not entirely clear, this
evidence is consistent with the arguments that leading researchers found companies to earn
rents on their intellectual capital (Zucker et al., 1998), and that gathering the necessary
resources to found a company to exploit uncertain new technology is easier when the
university’s status enhances the entrepreneur’s credibility. Since investors use signals, such as
institutional reputation or prestige, to help assess the commercial potential of university
technologies, inventors from more prestigious universities may be better able to obtain the
necessary capital to start their own firms (Di Gregorio and Shane, 2005).
Moreover, a significant relationship between the reputation of university scientists and various
measures of firm performance has been identified. Previous research on the value of university
researchers provides evidence of this fact. Deeds et al. (1998), for example, found that
university scientists' talent was a significant predictor of IPO (initial public offering) performance
of biotechnology companies. Zucker et al. (1998) found a significant relationship between the
reputation of university scientists and the number of products in development or on the market
as well as the employee size of the company. Finkle (1998) found that biotechnology companies
in which the CEO was a former university professor performed better than firms where the CEO
was not a former professor.
37
Findings: literature review
Venture capital availability
Research on formal venture capital effects is not conclusive. Di Gregorio and Shane (2003)
suggest that venture capitalists may be late stage investors in university technology, and other
sources of funds, such as business angels, government agencies, and universities themselves
(through equity investment in their own start-ups), may be more important in the early stages,
and thus may be catalysts for new firm formation and economic development. They also
suggest that capital markets distribute venture capital efficiently over geographic space; and
the availability of local venture capital is not a constraint on TTO (technology transfer office)
start-up activity.
Powers and McDougall (2004) point out that the variability in venture capital investment
strategy and the enormous fluctuation in venture disbursements in recent years can be
explained by the argument that venture capital effects are more complex than have been
investigated up until this point. Thus, it appears that further research into venture capital and
university technology transfer remains a robust area of inquiry.
Access to external finance
Universities’ working relationships with external organizations may also be crucial to the
successful implementation of strategies for spin off creation. Networking allows entrepreneurs to
enlarge their knowledge of opportunities, to gain access to critical resources such as finance
(Manigart et al., 1996). External networks with the financial and commercial sector may be
especially important for the development of spin offs given the traditionally non-commercial
environment of universities. Di Gregorio and Shane (2003) argue that proximity to local venture
capital firms provides an important means to overcoming capital market barriers to the
development of technology-based spin-outs; proximity also lowers monitoring costs and helps
development of networks of contacts. However, their empirical evidence did not support this
conjecture. They suggest that this finding may indicate that venture capital firms distribute
38
Findings: indicators used in benchmarking surveys
finance efficiently over geographic space and may only become more involved in spin offs at a
later stage.
Therefore, technology transfer offices need to focus on their ability to access early stage
external finance. The sources of external equity finance available to a spin off are a venture
capitalist, business angel or industrial partner. The availability of seed funding can help the
commercialisation process in a number of ways: financing access to managerial skills, by
securing or enhancing intellectual property; by supporting additional R&D; construction of a
prototype; preparation of a business plan; covering legal costs; etc. In effect, this seed money
is intended to facilitate the spin offs in getting themselves “investor ready” for next stage equity
financing. An ability to access resources, capabilities and expertise that can be provided by
external sources of finance leads to comparatively faster professionalization of a new venture
into a growing business (Hellmann and Puri, 2001).
In addition to providing finance, Lockett et al. (2004) points out that business angels may be
able to take on the role of surrogate entrepreneur, that is providing close commercial
managerial involvement in helping the business to develop to become ready for the next stage
of financial input (Franklin et al., 2001). This may be especially important during the earlier
stages of development where managerial inputs are required but the firm does not have the
revenue stream to support significant salary costs. Through their networks of contacts, both
venture capital firms and industrial partners can provide links to potential suppliers and
customers, as well as advice and monitoring (Florida and Kenney, 1988). The formation of a
joint venture between the university and an established firm, in particular, can be a mechanism
for gaining access to resources, exchanging information, developing inter-organizational
commitments and establishing legitimacy. Joint venture spin offs may be adept in providing a
clear route to market by building on their stock of social capital derived from long-standing
relationships established through previous business transactions (Vohora et al., 2003).
39
Findings: literature review
Patent importance
Patent importance did not prove to be predictive. Powers and McDougall (2004) found that the
importance of a university's patent portfolio does not propel either of our performance
measures, suggesting that numerous other forces may inhibit an otherwise highly innovative
technology. However, Powers and McDougall (2004) claim caution because of their study
examined only one patent measure. Results could have been very different since they chose to
examine the impact of patent citations among other patent-related measure. In addition, the
study examined only two measures of university entrepreneurship, and these measures may not
be as impacted by the quality or importance of a university's patent portfolio as might such
measures as the number of licenses or licensing income received. Additionally, it may be that
the lag time they chose was not long enough to detect an effect that is in fact present.
Powers and McDougall (2004) argue that the patent strategy of a university may vary
tremendously. For example, some universities may merely pursue a numbers game, while other
universities may concentrate on patenting technologies applicable to a specific industry, such as
optics, biotechnology, or petroleum. As TTOs begin to explore mechanisms of technology
transfer
beyond
traditional
licensing
and
royalties,
additional
research
examining
the
relationship between varying performance outcomes and different attributes of the university's
patent portfolio is merited.
IP protection expenditure
Lockett et al. (2004) research on IP (intellectual property) expenditure in universities shows a
significant correlation with start-up activity, especially in the process of creating spin-offs that
attract external equity finance. Researchers point out that this may well highlight the
importance of IP for any external equity provider (IP is clean, well defined and protected before
trying to raise external equity finance).
40
Findings: indicators used in benchmarking surveys
Industry funding of university research
Industry funding of university research have been used by researches as a measure of their
commercial orientation. Di Gregorio and Shane (2003) found positive the percentage of total
sponsored research funding that is derived from industry sources, but not significant, with startup activity. However, in an alternative specification in which commercial orientation was
measured by the dollar amount of industry funding, the coefficient for industry funding was
positive and significant. Powers and McDougall (2004) found industry R&D revenues positively
predictive of both the number of start-ups formed and the number of IPO licenses suggesting
that industry-sponsored research does stimulate business growth.
Di Gregorio and Shane (2003) suggest that one reason why the commercial orientation of a
university does not predict its start-up rate could be countervailing effects of commercial
orientation. Although a commercial research orientation might generate a pool of university
inventions that are more appropriate for new firm formation than is generated from a
governmental research orientation, the funding structure necessary to generate university
inventions might mitigate the benefits of this better pool of inventions. Because private firms
might be very likely to license commercially valuable inventions that are generated from
research that they fund, any increase in the pool of commercially valuable inventions that a
commercial orientation creates may be siphoned off by greater invention licensing by the
private sector providers of research funds. As a result, there is no net effect on the TTO start-up
rate of the university’s commercial orientation.
Powers and McDougall (2004) suggest that it is likely that industry R&D activity helps to
stimulate a culture of entrepreneurship within the university. Faculty engaged in industrysponsored entrepreneurial activity share their experiences with or involve other faculty in their
funded research. As a result, the culture may be altered because culture is a reflection of the
shared experiences of the members of the organization. Furthermore, the investment by
industry into numerous university research centers likely fosters an entrepreneurial spirit within
the university itself, and builds industry/university linkages that may form the basis for further
41
Findings: literature review
collaborative endeavours. Also, the slack resources that would likely be associated with higher
levels of industry R&D have some additional implications. Specifically, slack resources provide
universities with greater flexibility to choose the more risky time and personnel intensive startup route to commercialisation rather than the traditional large firm path. Furthermore, doing so
appears to result in greater rewards, in this case, more successful licensing to firms that IPO.
Presence of affiliated incubator
According to Di Gregorio and Shane (2003), one reason why the presence of incubators has an
insignificant effect on start-up rates may be that potential entrepreneurs do not consider the
use of incubators when making the start-up decision. Consequently, the existence of incubators
merely shifts the location of start-ups (to incubators from outside) rather than increasing the
amount of them. Although they can conclude that having access to an incubator does not
influence the rate of TTO start-up activity; their analysis cannot determine if university-affiliated
incubators influence the success of start-ups.
In this sense, Grimaldi and Grandi (2005) identified two business incubator models. Model 1 lies
in the capacity to reduce start-up costs for small entrepreneurial initiatives, targeting local
markets, more anchored to the old economy, looking for local visibility and local contacts with
public and private institutions, requiring small amounts of capital to start up and valuing the
provision of logistical assets. Model 2 lies in their ability to accelerate the start-up process of
highly promising entrepreneurial initiatives, attractive in terms of size of investments, fast and
aggressive, looking for high-value services (access to advanced technology, market, managerial
knowledge and competencies and day-to-day operational support). Model 2 also provides their
tenants with synergies created through supporting strategic technological and commercial
partnerships between new ventures and incubators’ networks of partners.
42
Findings: indicators used in benchmarking surveys
University venture capital funds
Di Gregorio and Shane (2003) found that university venture capital funds have an insignificant
effect on start-up rates. This finding suggest that may be university entrepreneurs develop
adequate ties to external venture capitalists to provide the investors with information about
them through technical due diligence or other activity. As a result, academic entrepreneurs can
obtain adequate amounts of external venture capital. Therefore, university venture capital
merely substitutes for, rather than adds to, external venture capital in its effect on start-up
activity. Although we cannot be sure why these policies have no effect on start-up rates, Di
Gregorio and Shane (2003) point out that university officials, researchers, and policy makers
will find the evidence in support of some policies and not in support of others useful in
developing explanations for and procedures toward the management of university technology
transfer and TTO start-up activity.
Licensing/technology transfer policies and strategies
Some university policies appear to influence start-up activity. Di Gregorio and Shane (2005)
found that two sets of university licensing policies—policies regarding the distribution of
royalties to inventors and whether or not the university is permitted to take an equity stake in
licensees— appear to influence start-up activity. Lower royalty rates may be an incentive to
start a venture to exploit a technology rather than license it. In contrast, the ability for
academics to take significant equity stakes in spin offs may be a greater incentive for them to
create spin offs (Lockett, et al, 2003). For spin offs to develop commercially may require the
attraction of external equity finance. To do so may require the presence of commercially
experienced managers, who in turn are likely to require appropriate incentives. Markman et al.
(2005) found that licensing in exchange for sponsored research is negatively related to new
venture formation, and licensing for cash—the transfer strategy of choice among 72% of TTOs
they studied—is least related to new venture creation, a disconcerting finding given that the
universities in which they operate have overwhelmingly invested in incubators to accelerate new
venture creation.
43
Findings: literature review
Markman et al. (2005) points out that these findings suggest that universities most interested in
generating short-term cash flows from their IP licensing strategies are least positioned to create
long-term wealth through venture creation. Although many universities have invested significant
resources in incubators and have expressed an interest in new business start-ups and economic
development, most of them have not linked this to their technology transfer strategy choices to
the mission of their TTOs.
Organizations require incentives and rewards to encourage people to perform particular
productive activities (Holmstrom, 1979; Jensen, 1993). For most universities, commercialization
of research requires radical changes in the way they have traditionally exploited scientific
discoveries (Etzkowitz, 1998). The institutional incentive and reward mechanisms that operate
within universities can preserve and reinforce existing cultures, organizational norms, policies
and procedures. There may be a need to modify procedures to align rewards with
commercialization goals, taking into account the characteristics, actions and motives of key
stakeholders. Siegel et al (2002) revealed palpable differences in these areas that can
potentially impede technology transfer. The norms, standards and values of academic scientists
reflect an organizational culture that values creativity, innovation, and especially, the
individual’s contribution to advances in knowledge or basic research. The primary motivation for
university scientists is recognition within the scientific community. Promotion is almost always
based upon an assessment of researchers’ contributions to the progress of science measured by
refereed publications.
Universities typically do not reward activities such as commercialising research and creating new
spin-offs, in their promotion and tenure decisions (Siegel et al, 2003). The performance
evaluation process and publishing-orientation of researchers thus act as barriers to these
activities (Ndonzuau et al, 2002). US universities benefit from the clarity of the Bayh-Dole Act,
which reduces the conflict of interest and puts the onus on the university commercially to
exploit inventions that result from scientific research. Lockett, Wright and Franklin (2003)
conjecture that in the UK environment an important and overlooked impediment to the
44
Findings: indicators used in benchmarking surveys
commercialisation of university IP is the unavailability of sufficient incentives and rewards for
university staff to spend time on spinouts.
TTO archetype
Markman et al. (2005) found that for-profit TTO structures and licensing in exchange for equity
are most positively related to new venture formation and traditional and non-profit TTO
structures are unrelated to new ventures even though they are correlated with the presence of
a university business incubator. These three archetypes vary by the degree of autonomy
granted at the institutional level to pursue technology commercialisation opportunities.
According to Markman et al. (2005), a “traditional” TTO is organized as an integral department
within a university's administrative structure, usually reporting to the Office of the Provost or
Vice President for Research. Such TTOs are tightly supervised by an assistant or vice president
of the university and is generally funded by the research office. Personnel are normally
untenured university staff with the primary role of pursuing conventional licensing opportunities
for royalty income. The direct, and often strong, oversight by a university administration limits
the autonomy of TTO management in matters of decision-making, licensing strategies, and
incentive systems.
“Non-profit research foundation” TTOs function as independent non-profit units or part of
separately constituted research foundations outside the university's administrative structure.
Such research foundations have their own Board of Directors, which is frequently chaired by the
university president. Private universities and many large multisystem state universities create
non-profit research foundations to grant greater autonomy to faculty to conduct research and
license new technology. In addition, many universities use this structure as it provides stronger
legal protection against lawsuits stemming from licensing disputes, IP infringements, and even
future product or service liabilities stemming from the university's licensed technology. TTOs
under this structure enjoy a separate budget from their affiliated universities, greater autonomy
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Findings: literature review
in choosing licensing strategies, and the ability to hold equity in start-up companies created to
exploit their licensed technologies.
“For-profit private extension” TTOs generally are created as separate private for-profit private
venture extensions. The for-profit private extension is focused on economic development and
creating start up companies. Private extensions also have an independent CEO and a Board,
with personnel who have substantial experience in such areas as IP law, managing companies,
and venture capitalism. Private venture extensions are most aggressive at creating start-ups
and raising capital. For-profit TTOs enjoy the greatest autonomy in terms of licensing strategies
and compensation systems
Business development capabilities
Lockett et al. (2004) examined the extent to which the university had developed relevant
capabilities to spin-out companies since a strategy of commercialising technology through spin
offs places a number of additional requirements on the routines/capabilities possessed by
universities, beyond those skills required for licensing. They found that university’s business
development capabilities were an important determinant of spin-off activity, highlighting the
importance of both resource inputs and skills in the creation of spin-offs. Also, the results
relating to business development capabilities indicated that the level of significance is greater
for the external equity investments in spin-offs than the creation of spin-offs. These findings
provide an important additional novel insight by identifying that it is not so much the number of
TTO staff that is important but their expertise.
By routines/capabilities they mean some form of ability to perform a productive activity
(Eisenhardt and Martin, 2000). These routines/capabilities are likely to be unequally distributed
across universities and are as yet rather embryonic for the vast majority of institutions. These
routines/capabilities involve processes for assessing intellectual property rights (IPR), processes
for spinning-out companies, and skills embodied in university staff in terms of both managing
the commercialisation process and specific technical and marketing skills. First, whether
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Findings: indicators used in benchmarking surveys
technology is exploited through licensing or spin-out, universities may employ clear processes
for conducting IP evaluation and due diligence to ensure intellectual property rights (IPR) are
identified and fully evaluated before commercialization can commence (Vohora et al, 2004).
Unless new IP is shown to be exempt from potential infringements of existing patent rights and
there is exclusive ‘freedom to operate’, the commercial exploitation process cannot proceed
without great difficulties. If it is not possible to secure a patent there are likely to be major
problems in marketing and generating rents from the technology.
Second, there is also a strong requirement for clear policies, processes and routines for creating
and developing spin offs. The creation of a legal entity is relatively straightforward. However,
the creation of a spin off that includes legally protected IP, and the managerial and marketing
skills, premises and financial resources to enable it to develop, is more complex. These routines
take time to develop and their development is also dependent on individual university contexts
(Teece et al, 1997).
Third, the development of these routines/capabilities relies heavily upon the experience and
expertise of TTO personnel. Clear processes and organizational routines in themselves do not
enable the technology transfer process to function productively. There is a requirement for
individuals to develop and implement these routines. The availability of skilled TTO staff to
manage the commercialisation process is thus vital to the creation of spin offs. The quality of
the TTO staff is important in terms of their marketing, technical, negotiating skills. More
developed routines and capabilities may be associated with the selection of inventions with
greater commercialisation prospects. In addition, these skills may bring a greater ability to
prepare the invention to a state where it is ready to attract external finance. Universities may
thus develop different strategies towards the development of spin offs depending on the extent
to which they are selective in terms of offering assistance to potential spin offs (Clarysse et al,
2003). Universities with greater business development capabilities may be able to focus
attention on those spin offs, which they perceive are going to make the greatest return.
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Findings: literature review
Experience/ age of the TTO
TTOs represent an important resource to university research faculty. Professionals who work in
university TTOs must understand both the culture and function of the academic research
enterprise as well as that of the industry sector, using their expertise to put together licensing
deals. Given that faculty typically know relatively little about the business of technology
commercialisation but usually have a high degree of psychological ownership for their
inventions, TTO professionals are key players in the commercialisation of a technology, often in
their role as arbiters between the higher education and industry cultures.
Following passage of the Bayh–Dole Act in 1980, there began a dramatic increase in the
establishment of TTOs and in turn, university-licensing activity. AUTM surveys report that
approximately 20 universities had TTOs in 1980. That number had grown to 200 by 1990, and
by the turn of the century, nearly every major university had a TTO (Colyvas et al., 2002).
The learning curve for new TTO personnel is steep as they may be unfamiliar with the faculty
and industrial networks important for finding licensees (Thursby and Thursby, 2002). Thus,
institutions with older TTOs would be expected to have developed superior skill sets for
managing the commercialisation enterprise, and hence, also predicted to enjoy higher
performance levels based on this organizational resource. The technology transfer literature
suggests that institutions with older offices often outperform those with newer offices, perhaps
due to the longer time period needed to develop the resource of specific skill sets useful to
facilitating technology transfer (Matkin, 1990; Roberts and Malone, 1996).
As TTO offices gain experience, they are more willing to consider equity in start-up companies.
Bray and Lee (2000) found that universities that took equity had older TTOs, leading them to
conclude that an established TTO is more likely to consider taking equity than would a young
TTO with pressure from the university to become self-supporting. The younger TTOs focused
primarily on royalty income, but as the TTO gained experience, its personnel were more willing
to consider equity. Bray and Lee's results were consistent with Feldman et al.'s (2002) study
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Findings: indicators used in benchmarking surveys
examining the conditions under which universities adopt equity-based transfer mechanisms.
They found a positive relationship between the age of the TTO and the university's use of equity
as a percentage of intellectual property transactions.
In summary, an experienced TTO is an important organizational resource to universities
engaged in all forms of technology transfer. The greater willingness of older TTOs to accept an
equity arrangement would be especially important in the formation of start-ups, as the use of
equity would most likely be used in start-up deals.
Number of TTO staff
Lockett et al. (2004) found significant the number of staff in the TTO in the partial models
excluding experience and/or capabilities but was found to be insignificant when these variables
were included. This is consistent with Di Gregorio and Shane (2003) who found only intermittent
support for the number of TTO staff as a control variable.
These findings provide an important additional novel insight by identifying that it is not so much
the number of TTO staff that is important but their expertise. These findings may suggest that
universities need to think of the experience and skills of their staff if they are to create spin-offs
that attract external equity finance.
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Findings: literature review
Remarks on the literature review
This literature review has allowed us to deepen into the knowledge of cause-effect relationships
between university resources and capabilities and start-up activity. Some of these relationships
appear to be well recognised by most researchers, such as the faculty quality, the experience of
TTOs, or policies regarding to spin-off creation. Nevertheless, others remain unclear, for
instance, the presence of venture capital or the industry funding of university research.
Other issue that remains unclear is that likely important relationships are still little analyzed in
the research literature, for instance, the relationships with the wealth creation in terms of
internal or external impacts. Some attempts have been carried out to measure wealth creation
generated by start-ups. In this sense, some researchers have operationalised wealth creation as
the number of IPO (initial public offering) licenses or spin-offs with external investments. Also,
is possible that micro-level factors could affect directly the university start-up activity, like the
factors influencing decision-making of potential entrepreneurs to start-up a business.
We must also point out that variations in cultural factors and external institutional conditions
can affect the start-up activity and produce variations between universities located in different
countries. In this sense, Chiesa (2000) indicates that it seems possible that there is European
model for spin-off companies’ creation, which is different from the American (and perhaps
Anglo-Saxon) one. Talking about the Italian model, he indicates that it seems to be
characterised by low risk levels, together with modest growth rates in part due to the perception
of the failures. The Italian model context and entrepreneurs seem to be less willing and ready to
accept failures, whereas in the US failures are seen less traumatic events and it is rather
common that entrepreneurs fail more than once before they start a really successfully business.
Also, the Italian model might be partly influenced by the greater stability offered by the
university system in terms of long-life employment, so that researchers might consider
entrepreneurship a good opportunity to achieve personal prestige and increase earnings and
satisfaction, but not as a forced way to have a job.
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Findings: indicators used in benchmarking surveys
3.2. INDICATORS USED IN BENCHMARKING SURVEYS
This section includes a checklist of indicators of academic entrepreneurship used in
benchmarking surveys related to technology transfer. We have selected and analysed the most
representative benchmarking surveys that are being carried out in different regions of the
world. In this sense, The OECD survey gathered data among universities of OECD countries, the
Proton survey gathered data among European universities, and the APRU survey gathered data
of universities of the Pacific Rim. The AUTM, UNICO and HEBI surveys are focused on mainly
national data, but we have included them because of their use as sources of data for research
on academic entrepreneurship.
For each survey analysed, indicators are grouped into the dimensions of the framework of our
study: policies and strategies; stock of technology; resources and initiatives; human capital;
start-up activity; internal impacts; and, external impacts. We have attempted to maintain the
specific nomenclature used in each survey, and, we also present the indicators’ definitions
based on key concepts or explanations included in the respective report.
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Findings: indicators used in benchmarking surveys
3.2.1. OECD: SURVEY ON THE PATENTING AND LICENSING ACTIVITIES OF
PROs
The Organisation for Economic Co-operation and Development (OECD) carried out this survey in
2001, and results were included and published in the report “Turning business into science:
patenting and licensing at public research organisations”, in 2003. The survey requested
universities (among other public research organisations) to respond questions about the
organisational structure of their TTOs, their intellectual property portfolio and their licensing
practices and income. Participating countries included: Belgium, Canada, Denmark, Germany,
Italy, Japan, Korea, the Netherlands, Norway, Spain, Switzerland, Russia and the United States.
Respondents were asked to choose either the most recent fiscal or calendar year for which they
had full records. All responses are then for the chosen definition and year. Most countries chose
2001 or 2000 as the “last year”.
Indicators of policies and strategies
TTO archetype
Universities were requested to indicate the archetype of the TTO among the following possible
responses: dedicated TTOs (on-site or off-site); administrative departments of the university whose
main mission is not intellectual property (IP) management; external (private or public) providers of IP
management services.
University’s intellectual property policy
Universities were requested to indicate the ownership/s of the intellectual property generated: the
institution; researcher or inventor at the institution; organisation or firm that funded the research; the
government; varies by type of contract with the research founder; or no formal policy. Also, universities
were requested to indicate if their intellectual property or licences generated by individual researchers
influence their recruitment, career advancement, bonuses, or salary.
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Findings: indicators used in benchmarking surveys
Indicators of resources and initiatives
Year of TTO establishment
Universities were requested to indicate the year of the establishment of the TTO.
Staff working at the TTO
Universities were requested to indicate the number of employees (full-time equivalents) currently
working at the TTO.
Activities of the TTO
Universities were requested to indicate the activities in which the TTO is involved: assessing the
patentability of inventions; applying for patents (or arranging for an outside expert to apply); arranging
licences for inventions developed by the institution; obtaining licences for researchers within the
institution (licensing-in); or negotiating research agreements between the percentage of the
institution’s IP managed by the TTO.
Methods to find licensees
Universities were requested to indicate what methods and their degree of success (low/mid/high) they
used in the last year to find licenses for the institution’s technology: advertising in magazines, journals
or on the Internet; informal contacts of researchers or inventors; informal contacts of the TTO;
technology brokers or consulting services; electronic marketplaces and auctions (for example, Internet
forums where IP and technology from multiple sources can be bought and sold); or other.
Indicators of stock of technology
Expenditures on research and development
Universities were requested to include the total amount of research and development expenditures,
which include core and institutional funding, grants and contracts.
Research expenditures funded by private firms
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Findings: indicators used in benchmarking surveys
Universities were requested to include the percentage of the total amount of research and development
expenditures funded by private firms (for example for contract research).
Intellectual property expenditures
Universities were requested to indicate the amount spend on the following intellectual property
activities: IP management (patent application and renewal fees, etc.); licensing and other costs to
transfer technology from the institution to other organisations or firms; licence fees and other
acquisition costs for technology used by the institution (licensing in).
New patent applications
Universities were requested to indicate the number of patents applied in the last year by the institution,
and
breakdown
it
by
following
fields:
health,
pharmaceuticals,
medical
(including
relevant
biotechnology); food, agro-industry, (including relevant agro-biotechnology; information technology,
electronics, instruments; production technology, new materials; energy, environment, transportation;
or other.
New patents granted
Universities were requested to include the number of technically unique patents granted to the
institution in the last year, and breakdown it by the following jurisdictions: home country; European
Patent Office; United States Patent and Trademark Office; Japan Patent Office; or other.
Active and technically unique patents
Universities were requested to include the number of the active and technically unique patents of the
university’s portfolio. For the purpose of the survey, currently active means that the patents are still the
property of the university (they have not expired, been allowed to lapse or been sold), and technically
unique patents means that multiple applications or grants for the same invention in different
jurisdictions should be counted as just one application or grant. For example, five patents for the same
invention in five patent jurisdictions would be counted as one technically unique patent.
Active and technically unique patents licensed
Universities were requested to indicate the number of patents of the current portfolio that have ever
been licensed, as well as the number of these patents that are currently earning licence income.
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Findings: indicators used in benchmarking surveys
Non-patent intellectual property actions undertaken
Universities were requested to include the number of the following non-patent actions undertaken in
the last year: invention disclosures; copyright registration for software and databases, education
materials or multimedia; industrial design registration; plant breeder’s rights application; nondisclosure, confidentiality; or other.
Licences executed
Universities were requested to include the total number of licenses executed in the last year, and
breakdown it by the following types of intellectual property: patented inventions (patent granted);
patent-pending inventions (in application phase); non-patented inventions (no application planned);
copyrighted materials; industrial designs; plant breeder’s rights; or other.
Exclusivity of licences executed
Universities were requested to include the number of licensed executed by the following types of
exclusivity: fully exclusive for the lifetime of the patent (single licensee); exclusivity limited to a
specified number of years; exclusivity limited to a specific territory; exclusivity limited to a specific field
or market type; other type of exclusivity; or non exclusive (the institution may license to other firms or
organisations).
Type and allocation of licensee companies
Universities were requested to breakdown the number of licences executed in the last year by small
firms (with fewer than 500 employees), large firms (with more than 500 employees) or universities or
research organisations, as well as by exclusivity according to these company types. Also, universities
were requested to breakdown the total number of licenses executed in the last year by the location of
the licensee company: domestic (including non-national firms located in the home country) or abroad
(including subsidiaries or domestic firms in other countries).
Requirements included in licences
Universities were requested to indicate approximately (all/some/none) how many of the licence
agreement include some of the following requirements: requirement to work the invention; requirement
to work the invention in the home country; right for licensee to delay publication of papers; reachthrough clauses for the institution (institution’s intellectual property rights extend to products or further
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Findings: indicators used in benchmarking surveys
inventions based on the licensed invention); licensor (owner) has right of first refusal for future
inventions by the licensee institution.
Licences earning income
Universities were requested to include the number of active licences (excluding trademarks) earning
incomes in the last year.
Gross income from intellectual property
Universities were requested to include the total amount of the gross income( not deducting IPR
management costs) from its intellectual property, including income from licence fees (licence issue
fees, annual payments, termination payments, end-user fees), running royalties from product sales
cashed-in equity, etc., and excluding trademarks.
Gross income distribution
Universities were requested to distribute the gross income (%) among the following stakeholders: TTO;
inventor; the research group or department where the inventor works; the central administration of the
institution; and/or other. Also, universities were requested to indicate the number of inventions
(protected by patents, copyright, know-how, etc.) that are responsible both of the 20 % of the gross
income and the 50% of the gross income.
Indicators of start-up activity
Spin-offs and start-ups established
Universities were requested to include the number of spin-offs and start-ups established in the last
year. For the purpose of the survey, spin-offs are defined a new firm founded by staff from the
institution to develop or commercialise an invention, and start-ups are defined as new firms to develop
or commercialise an invention developed by the institution, but not founded by staff from the
institution.
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Findings: indicators used in benchmarking surveys
3.2.2. THE AUTM LICENSING SURVEY
The Association of University Technology Managers (AUTM) carries out this survey in an annual
basis since more than a decade ago. The AUTM licensing survey provides quantitative
information on licensing activities from U.S. and Canadian universities, hospitals and research
institutions. This survey is one of the most cited in publications on technology transfer around
the globe, and researchers on academic entrepreneurship often use its data. The methodology
of the AUTM Licensing Survey is just now starting to be replicated in other leading innovation
economies throughout the world. The indicators included below have been gathered from the
“AUTM Fiscal Year 2002 Licensing Survey Summary”, published in 2003. In this edition, a total
of 156 U.S. universities (most of them were into the top 100 research universities) were
contacted, with a response rate of 61%.
Indicators of policies and strategies
The
“AUTM
Fiscal
Year
2002
Licensing
Survey
Summary”,
does
not
include
any
kind
of
quantitative/qualitative indicator about policies or strategies regarding to technology transfer or
academic entrepreneurship.
Indicators of resources and initiatives:
Maturity of technology transfer programme
Surveyed universities were asked about the first year when the institution devoted one-half of a
professional full time equivalent (FTE) to technology transfer. Professional FTE means a professional
position whose duties included support of technology transfer activities. This person may or may not
have been located in a formally established technology transfer office at that time.
Staffing in technology transfer
Universities were requested to include the number of FTEs, and breakdown it by licensing FTEs and
other FTEs. Licensing FTEs includes person(s) employed in the technology transfer office whose duties
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Findings: indicators used in benchmarking surveys
are specifically involved with the licensing and patenting processes as either full or fractional FTE
allocations. Licensing examples include licensee solicitation, technology valuation, marketing of
technology, license agreement drafting and negotiation, and start-up activity efforts. Other FTEs
includes person(s) employed in the technology transfer office as either full or fractional FTE allocations
whose duties and responsibilities are to provide professional, administrative, or staff support of
technology transfer activities that are not otherwise included in licensing FTE. Such duties might include
management, compliance reporting, license maintenance, negotiation of research agreements, contract
management, accounting, MTA activity, and general office activity. General secretarial/administrative
assistance to the technology transfer office had also to be included in this category.
Indicators of stock of technology
Total research expenditures
Universities were requested to include the expenditures (not new awards) made by the institution in the
last fiscal year in support of its research activities that are funded by all sources including the federal
government, local government, industry, foundations, voluntary health organizations, and other nonprofit organizations. Indirect costs had to be included.
Research expenditures from federal government sources
Universities were requested to include expenditures made in the last fiscal year by the institution in
support of its research activities that are funded by the federal government. Expenditures by state and
local governments should be excluded.
Research expenditures from industrial sources
Universities were requested to include expenditures made in the last fiscal year by the institution in
support of its research activities that are funded by for-profit corporations, but not expenditures
supported by other sources such as foundations and other non-profit organizations.
Total Research funding:
Universities were requested to include the total amount of research support committed (i.e., awarded)
to the institution in the last fiscal year (even if the funds are to be spent over several years) that was
related to license/ option agreements executed in the survey period or signed in a prior year for which
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Findings: indicators used in benchmarking surveys
the related research funding was not previously reported (e.g., research funding committed as a result
of a renewal of a research agreement that is related to a license/option agreement signed in a prior
year).
Invention disclosures
Universities were requested to include the number of disclosures, no matter how comprehensive, which
are made in the year requested and are counted by the institution.
Total U.S. patent applications filed
Universities were requested to include the total number of U.S. patent applications filed during the
reporting year, which include any filing made in the U.S.: provisional applications, provisional
applications that are converted to regular applications, new filings, CIPs, continuations, divisionals,
reissues, plant patents, applications for certificates of plant variety protection., and PCT applications (is
the first filing where the U.S. is designated), but not including those PCT applications that followed a
previous U.S. application. The survey report also includes: new U.S. patent applications filed per
invention disclosures received.
New U.S. patent applications filed
Is a subset of total U.S. patent applications filed. It does not include continuations, divisionals, or
reissues, and typically does not include CIPs. A provisional application filed in the surveyed fiscal year
had to be counted as new. If a provisional application is converted in the surveyed fiscal year to a
regular application, then that corresponding regular application filed in the requested fiscal year had not
to be counted as new. A PCT application counted in total U.S. patent applications filed where the PCT
application is a first filing where the U.S. is designated had to be counted as new.
U.S. patents issued
Universities were requested to include the number of U.S. patents issued or reissued to the institution
in the year requested, including certificates of plant variety protection issued by the United States
Department of Agriculture. The survey report also includes: patents issued as a percentage of total
patent applications, and patents issued as a percentage of new patent applications
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Findings: indicators used in benchmarking surveys
Legal fees expenditures
Universities were requested to include the amount spent in external legal fees for patents and/or
copyrights. These costs include patent and copyright prosecution, maintenance, and interference costs,
as well as minor litigation expenses that are included in everyday office expenditures (an example of a
minor litigation expense might be the cost of an initial letter to a potential infringer written by counsel).
Excluded from these fees is significant litigation expense (e.g., any individual litigation expense that
exceeds 5% of total legal fees expenditures. They also do not include direct payment of any of these
costs by licensees).
Legal fees reimbursements
Universities were requested to include legal fees reimbursements, the amount reimbursed by licensees
to the institution for legal fees expenditures.
Licenses/options executed
Universities were requested to count the number of license or option agreements that were executed in
the year indicated for all technologies. Each agreement, exclusive or non-exclusive, had to be counted
separately. Licenses to software or biological material end-users of $1,000 or more had to be counted
per license, or as 1 license, or 1/each for each major software or biological material product (at
manager's discretion) if the total number of end-user licenses would unreasonably skew the institution's
data. Licenses for technology protected under U.S. plant patents or plant variety protection certificates
had to be counted in a similar manner to software or biological material products as described above, at
manager’s discretion. Material transfer agreements didn’t have to be counted as licenses/options in the
survey. For the purpose of the survey, a license agreement formalizes the transfer of technology
between two parties, where the owner of the technology (licensor) permits the other party (licensee) to
share the rights to use the technology. An option agreement grants the potential licensee a time period
during which it may evaluate the technology and negotiate the terms of a license agreement. An option
agreement is not constituted by an option clause in a research agreement that grants rights to future
inventions, until an actual invention has occurred that is subject to that option.
Exclusivity of the licenses and options executed
Surveyed universities reported on the exclusivity pattern of each license executed. The reporting of a
license as exclusive or non-exclusive should follow the terms of the license agreement. If a license is
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Findings: indicators used in benchmarking surveys
designated as exclusive in the license agreement, it had to be reported as an exclusive license to the
survey. Exclusive licenses include licenses that are designated as exclusive by field of use, territory, or
otherwise but excludes co-exclusive licenses, which were reported as non-exclusive licenses.
Active license/options
Universities were requested to include the cumulative number of licenses/options over all years that are
not terminated by the end of the fiscal year requested.
Size of licensee company
Surveyed universities had to include the size of the licensee companies: start-ups, small, or large
companies. As used in the survey, small companies are those companies that had 500 or fewer
employees at the time the license/option was signed, but, for the purposes of the survey, not including
start-up companies initiated by the institution. Start-up companies are companies that were dependent
upon licensing the institution's technology for initiation. Large companies are companies that had more
than 500 employees at the time the license/option was signed.
Licenses/options yielding income
Universities were requested to include the number of licenses/options that generated license income
received in the last fiscal year. Also, universities were requested to include the number of active
licenses generating more than $1 million in the last fiscal year.
Licenses/options yielding running royalties
Universities were requested to include the number of licenses/options that generated running royalties
in the year requested. For the purposes of this survey, running royalties are defined as royalties earned
on and tied to the sale of products. Excluded from this number are license issue fees, payments under
options, termination payments, and the amount of annual minimums not supported by sales. Also
excluded from this amount was cashed-in equity, which had to be reported separately.
Source of gross license income: running royalties, cashed-in equity and other sources
Universities were requested to include the amount of income from running royalties, cashed-in equity
and other sources. Cashed-in equity includes the amount received from cashing in equity holdings,
resulting in a cash transfer to the institution. The amount reported should be reduced by the cost basis,
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Findings: indicators used in benchmarking surveys
if any, at which the equity was acquired. Excluded from this amount is any type of analysis or process
whereby a value for the equity holdings is determined but a cash transaction does not take place
through the sale of these holdings. An internal sale (e.g., to the endowment) will constitute cashing-in
if the transaction results in cash being made available for internal distribution. Equity, for the purposes
of the survey, is defined as an institution acquiring an ownership interest in a company (e.g., stock or
the right to receive stock).
Research support linked to licenses
Universities were requested to include the amount paid to other institutions under inter-institutional
agreements. The survey subtracts it from the total license income of the institution to avoid doublecounting license income when the receiving institution reports it to the survey.
Indicators of start-up activity
Start-up companies formed
Surveyed institutions were requested to include the number of start-ups companies formed during the
last financial year. As used in the survey, start-up companies are defined as companies that were
dependent upon licensing the institution's technology for initiation.
Primary place of new start-up companies
Universities were requested to include the number of start-ups companies initiated in fiscal year
requested that had their primary place of business operating in their home state.
Start-up companies became non-operational
Surveyed institutions were requested to include the number of start-up companies, which became nonoperational in the last financial year. For the purpose of the survey, a non-operational start-up
company is one that no longer possesses sufficient financial resources and expends these resources to
make progress toward stated business goals.
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Findings: indicators used in benchmarking surveys
Operational start-up companies
Surveyed institutions were requested to include the number of start-up companies that were
operational the last day of the surveyed fiscal year, For the purpose of the survey, an operational startup company possesses sufficient financial resources and expends these resources to make progress
toward stated business goals. The company must also be diligent in its efforts to achieve these goals.
New start-up companies with institutional equity
Surveyed institutions were requested to include the number of start-up companies formed in the last
fiscal year in which the institution holds equity.
Indicators of external impact
Licensed technologies made available
Surveyed institutions were asked to include the number of licensed technologies made available in the
year requested. For the purpose of the survey, licensed technologies concept refers to licensed
technologies that became a product that was sold either to the public or to industry. It also refers to a
licensed technology that is a process that was put into has to be considered available if it is bundled
with other technologies when made available to the end-user.
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Findings: indicators used in benchmarking surveys
3.2.3. HEFCE: HIGHER EDUCATION-BUSINESS INTERACTION SURVEY (HEBCI)
Up to date, the Higher Education Funding Council for England (HEFCE) has carried out four
surveys of this kind, among higher education institutions, for assessing the volume and
development of higher education knowledge transfer, or rather exchange, between the United
Kingdom-higher education sector on the one hand and business and the wider community on
the other hand. The HE-BCI survey is carried out to provide data regarding the continuing
development of interactions, reliable and relevant information to support the continued public
funding of the third stream of higher education institutions’ activity, to give them good
benchmarking and management information, and to develop a source of indicators at the level
of the individual higher education institutions’, some of which will be useable to inform the
allocation of their continued funding.
The following indicators are extracted from the edition of the survey published on January 2005,
which gathered data from the academic year 2002-03.
Indicators of policies and strategies
Economic development priorities
Universities were requested to indicate what areas do they see the institution as whole making the
greatest contribution to economic development: access to education; research collaboration with
industry; meeting regional skills needs technology transfer: supporting SMEs; meeting national skills
needs; developing local partnerships; attracting non-local students to the region; graduate retention in
local region; support for community development; spin-off activity; attracting inward investment to
region; management development; and/or strategic analysis of regional economy.
Policies and strategies to support businesses
Universities were requested to respond several questions regarding to their support and relationships
with existing businesses: sectors they work with, and how those were determined; the type of partners/
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Findings: indicators used in benchmarking surveys
clients of their third stream strategic priorities; geographical areas of greatest priority in the university’s
institutional mission; the level of incentives for the staff to engage with industry and commerce; the
existence of an strategic plan for business support; the business and community representation on their
government body; the maximum number of days per year permitted to university staff (excluding
dedicated business and community staff) to provide business support services/activities; partnership
arrangements with local and regional bodies.
Incentives and rewards
Universities were requested to indicate (yes/no) whether the staff is rewarded by the institution for the
intellectual property which they generate.
Indicators of resources and initiatives
Age of the commercialisation department
Universities were requested to include the year when the commercialisation department was
established.
Institution’s staff employed in a dedicated business and community function
Universities were requested to include the number of staff (full time equivalents) in a dedicated
business and community function, breaking down it by: engaging with commercial partners; engaging
with public sector partners; engaging with social, community and cultural partners. Also, universities
were requested to include the headcount (as a percentage) of the institution’s academic and related
staff directly involved in providing services to the different types of clients/partners, as well as to
indicate their level of engagement.
Spin-off support offered
Universities were requested to indicate the provided support for spin offs through the following
mechanisms(either provided by the institution or in collaboration with a partner organisation): on
campus incubators; other incubators in the locality; science park accommodation; entrepreneurship
training; seed corn investment; venture capital; business advice.
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Findings: indicators used in benchmarking surveys
Indicators of stock of technology
Collaborative research income
Universities were requested to include the income from public sector funded collaborative research
grants involving business co-funding or formal collaboration, excluding income from any project that
does not involve direct business participation in the form of part sponsorship or direct collaboration.
R+D contracts
Universities were requested to include the number and income from contract R&D originating from
partners located in the same region, within the UK and from outside the UK, during the survey
reporting year. For the purpose of the survey, were excluded responsive mode grants for research
made by educational charitable bodies and public agencies, but focus on studies and projects
commissioned by the client body to underpin their own objectives. Contracts with devolved
administrations or regional government offices had to be included as regional unless the university is in
different region. Universities with substantial campuses in two regions had to consider both regions as
the home region, although if one campus is simply a teaching outpost lacking significant research
generation activity then that region had to be considered as outside the home region.
Universities were also requested to indicate the percentage of contracts with businesses by number and
value during de survey reporting year were with small and medium enterprises (SMEs, less than 250
employees and not part of bigger enterprise groupings), as well as contracts with business as a
proportion of total income.
Consultancy contracts
Universities were requested to include the number and value of incomes from consultancy contracts by:
SME, non-SME commercial business and non-commercial organisations.
Services related to facilities and equipment
Universities were requested to include the number of organisations involved (by SME, non-SME
commercial business and non-commercial organisations) in facilities and equipment related services as
well as the income generated, during the last year.
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Findings: indicators used in benchmarking surveys
Invention disclosures
Universities were requested to include the number of invention disclosures received during the last
financial year.
New patents filed
Universities were requested to include the number of patents filed during the last year.
Number of patents granted
Universities were requested to include the number of patents granted during the last year.
Cumulative portfolio of active patents
Universities were requested to include the number of active patents at the end of the year.
Licences granted
Universities were requested to include the number of licenses granted by type of licence (non-software
licences or software licenses) type of licensee (SME, non-SME commercial business and non-commercial
organisations), and location of licensee (UK based companies or companies based overseas).
IP income
Universities were requested to include the income from licences (including from copyrights, designs and
trademarks, and from the sale of shares in spin-off companies) by sector (SME, non-SME commercial
business, non-commercial organisations) and type of licensee (software and non-software licences).
Other university–business relationships
The survey includes other questions related to university–business interactions as courses for industry
staff and employment of students.
Indicators of start-up activity
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Findings: indicators used in benchmarking surveys
Spin-offs established
Universities were requested to include the number of spin-offs established during the last year and
breakdown it by: spin-offs with some university ownership, formal spin-offs, not university-owned, staff
start-ups, graduate start-ups. For the purpose of the survey, spin offs are enterprises, in which an
university or university employee/s possesses equity stakes, which have been created by the university
or its employees to enable the commercial exploitation of knowledge arising from academic research.
Other ‘start-up’ companies may be formed by university staff or students without the direct application
of university-owned intellectual property.
Four types of spin off or start up firms are defined: spin off companies established using university
intellectual property and in which there is some element of university ownership; spin off companies
into which the university has assigned or licensed intellectual property (IP), but in which it has no
equity; start-up companies involving current or former university staff as founders where the university
has no ownership nor an IP agreement (in this case the university staff must be connected to the
university immediately prior to formation of the company); graduate start-up companies that have
originated through the direct involvement off the university or through a dedicated graduate start-up
programme.
Active spin-offs
Universities were requested to include the number of spin-offs still active that have survived at least 3
years.
Indicators of internal and/or external impacts
Employment of active firms
Universities were requested to indicate an estimated total number of employees by: spin-offs with some
university ownership, formal spin-offs, not university-owned, staff start-ups, graduate start-ups.
Turnover of active firms
Universities were requested to indicate an estimated total value of the turnover by: spin-offs with some
university ownership, formal spin-offs, not university-owned, staff start-ups, graduate start-ups.
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Findings: indicators used in benchmarking surveys
3.2.4. UNICO SURVEY: UNIVERSITY COMMERCIALISATION ACTIVITIES
The University Companies Association (UNICO) conducts and publishes since 2001 in an annual
basis this survey on the commercialisation activities of United Kingdom universities. The survey
results provide information on trends in the commercialisation of academic research by UK
institutions. The report contains information on commercialisation in terms of invention
disclosures, patenting, licensing and the creation of new spinout companies.
The following indicators have been extracted from the two latest publications of the survey. The
survey published in 2003 gathered data from the financial year 2002-03, collecting data from
125 institutions (including 96 of the top 100 universities in terms of research expenditure), with
a response rate of 99%. The survey published in 2004 gathered data from the financial year
2002-03, collecting data from 75 institutions (including 25 of the top 30 universities by research
income).
Indicators of policies and strategies
Institutional incentives and rewards
Universities were requested to report how are distributed the rewards/revenues from commercialisation
between the inventor, the department and the institution.
Finance and impediments to spin-out success
An attitudinal survey on finance and impediment to spin-out success of was carried out. Institutions
were asked to identify the most important sources of finance for spinout firms during the last financial
year, as well as to indicate the factors impeding or promoting the creation and development of spinout
companies.
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Findings: indicators used in benchmarking surveys
Indicators of resources and initiatives
Initiation of university commercialisation activities
Surveyed universities were asked about the first year when the institution had at least 0.5 full time
equivalents (FTEs) dedicated to commercialisation activities. For the purpose of the survey, a person
with a professional position whose duties included the support of commercialisation activities at least
50% of the time. This person may or may not have been located in a formally established a
commercialisation office at that time.
Number of full time equivalents employed
Universities were requested to include the number of FTEs that were employed in their technology
transfer and commercialisation activities at the end of the reporting year. For the purpose of the
survey, all FTEs whose duties and responsibilities include licensing, patenting and spinout company
creation activities, as well as those providing related secretarial, contract management and other
administrative support. Universities were requested to breakdown the total number by FTEs employed
in commercialisation activities, FTEs employed primarily in licensing activities, and FTEs employed
primarily in spinout company development activities.
Valuation methods employed for spinout companies
Universities were requested to indicate the preferred method/s for determining the value of portfolio
companies. The survey results shows aggregate data including: no method, cost (less provision),
earning multiple, third party valuation, net assets, future cash flows and other.
Indicators of stock of technology
Number of new invention disclosures
Universities were requested to include the number of disclosures received in the financial year
requested, no matter how comprehensive. The survey results’ report shows aggregate data on the
average number of invention disclosures, using data of two financial years.
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Findings: indicators used in benchmarking surveys
New patent applications filed
Universities were requested to include the number of patent applications filed in the last financial year.
New patents issued
Universities were requested to include the number of patents issued during the last financial year, and
the number of patents issued to UK institutions. Also, the survey results’ report shows aggregate data
on the average number of new patents issued, using data of last two financial years.
IP protection expenditure
Universities were requested to include the amount of intellectual property (IP) protection expenditure.
For the purpose of the survey, IP protection expenditure covers costs incurred for legal fees, patent
costs, consultancy and specialist IP advice.
Number of licences/options/agreements) executed
Universities were requested to include the number of licences, options and/or agreements executed in
the reporting year. For the purpose of the survey, a licence is where the licensor (the institution) grants
rights to use the technology under licence in a defined field of use and territory. An option agreement
grants the potential licensee a time period during which it may evaluate the technology and negotiate
the terms of a licence agreement.
Destination of licences, options and agreements executed
Universities were requested to breakdown the number of licences executed in the reporting year by
type of licensee company: university spin-off companies, small and medium enterprises and large
companies.
Number of licences and options executed with equity
Universities were requested to include the number of licences and options executed with equity in the
reporting year (institution took shares in the company, the licence was granted to in lieu of royalties, or
as part payment of the licence being granted).
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Findings: indicators used in benchmarking surveys
Number of licences, options and agreements yielding income
Universities were requested to include the number of licences, options and/or agreements yielding
income in the requested year, and breakdown it by monetary ranges.
Total amount of licence income received
Universities were requested to include the total amount of licence income received in the reporting
year, which includes licence issue fees, payments under options, lump sum payments in consideration
of an assignment, annual minimums, running royalties, termination payments, the amount of equity
received when cashed-in. Does not include research funding, patent expense reimbursement, a
valuation of equity not cashed-in, trademark licensing royalties from university insignia or income
received in support of costs incurred under material transfer agreements. Licensing income excludes
software and biological material end user licences under £1,000.
Amount of income received from licences generating running royalties
Universities were requested to include the amount of income received from licences generating running
royalties in the reporting year. Also, the survey report includes the number of licences yielding income
per sales revenue.
Indicators of start-up activity
Number of spin-outs formed
Universities were requested to include the number of spin-outs formed in the reporting year. For the
purpose of the survey, spin-out are companies that were dependent upon licensing or assignment of
the institution’s technology for initiation. Also, universities were requested to breakdown this number by
the types of source of equity finance: venture capital, business angels, university challenge funds,
proof-of-concept funds, equity joint ventures with industrial partners and other external and internal
sources of finance.
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Findings: indicators used in benchmarking surveys
Number of spin-ins formed
Universities were requested to include the number of spin-ins formed in the reporting year. For the
purpose of the survey, ‘spin-ins’ are companies originating from the institution but based on technology
generated from outside.
Investments made into already existing spinout companies
Universities were requested to include the number and source of investment for existing spinout
companies during the last financial year: venture capital; business angels; university challenge funds;
proof-of-concept funds, etc; equity joint ventures with industrial partners; other external and internal
sources of finance; university.
Existing spin-outs institution holding shares
Universities were requested to include the number of existing spin-out companies with university equity
holdings at the end of the reporting year.
Indicators of internal impacts
Full Exits from spin-out companies
Universities were requested to include the number and the total value realised through full exits of spinout company investments in the reporting year, breaking it down by exists via: IPO (initial public
offering), share sale, MBO (management buy-out), or failure/liquidation.
Partial Exits from spin-out companies
Universities were requested to include the number and the total value realised through partial exits of
spin-out company investments in the reporting year, breaking it down by exists via: IPO, share sale, or
MBO.
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Findings: indicators used in benchmarking surveys
3.2.5. PROTON EUROPE SURVEY
Proton is a pan-european network of knowledge transfer offices, is funded by the European
Commission and is a part of the initiative Gate2Growth. One of the objectives of ProTon Europe
network is to help its members raise their performance through the exchange of knowledge and
good practice. In this sense, the network will set up and conduct an annual “Observatory” based
on survey results among national associations of transfer offices from Belgium, France,
Germany, Republic of Ireland, Italy, Spain and United Kingdom, as well as among new
participant associations.
Due to date a public report of the annual observatory has not been yet published, we present
indicators extracted from the survey form, which is of public access in the website of the Proton
Network.
Indicators of policies and strategies
Incentive regimes in knowledge transfer activities
Technology transfer offices (TTOs) were requested to allocate the percentage of licences net revenue to
the different players involved: inventors/individuals; institution department and/or faculty; research
group; or/ and other. Also, technology transfer offices were requested to indicate the types of rewards
and policies regarding to the academic staff-spin-offs: financial incentives for creating spin-outs; equity
policies
TTO archetype
Technology transfer offices were requested to indicate their relationships with the university: centralized
internal unit of the institution; departmental internal unit of the institution; non profit external firm or
organisation; profit external firm or organisation; sectorial firm or organisation (dedicated to specific
disciplines or sectors); or external firm or organisation wholly owned by the institution.
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Findings: indicators used in benchmarking surveys
TTO functions
Technology transfer offices were requested to indicate whether knowledge transfer is their main
function or has another: university research office; university CPD office; administrative and financial
issues; and/or other. Also, technology transfer offices were requested to respond another specific
questions about their current activities (management of contracts, management of project grants,
management of technical services, management of disclosures, management of patent applications,
etc).
Indicators of resources and initiatives
TTO creation
Technology transfer offices were requested to indicate the year when the university decided to create a
formal structure for knowledge transfer activities.
TTO staff
Technology transfer offices were requested to include the number of professional full time equivalents
(FTEs) employed in the office. For the purpose of the survey, "Professional TTO staff" means a
professional position whose duties include any management (liaison, marketing, negotiation, evaluation,
administration, monitoring, legal and business counselling, grants fund raising) for the support of
knowledge transfer activities 100% of the time. Also, technology transfer offices were requested to
breakdown it by approximate percentages of professional TTO staff dedicated to: research or
consultancy contracts; collaborative research grants; intellectual property (IP) protection; licensing;
spin-off development; TTO marketing; dedicated to other duties (e.g. financial management, training
processes), as well as to indicate the number of full time equivalents of clerical staff.
TTO budget
Technology transfer offices were requested to indicate the approximate annual TTO budget, including
staff and subcontracts, as well as to allocate percentages of this budget among: budget from recurrent
institutional budget (public general funding); budget from overheads/indirect costs on research
contracts; budget from licence revenue; budget from subsidies from regional/national government or
European funds; budget from others sources.
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Findings: indicators used in benchmarking surveys
Promotional activities expenditures
Technology transfer offices were requested to indicate the amount spent in promotional activities (fairs,
events, materials, publicity…) during the last financial year.
Initiatives to support spin-offs
Technology transfer offices were requested to indicate (yes/no) if the university have its own seed fund
and/or venture capital funds.
TTO networking
Technology transfer offices were requested to indicate the number of current subscriptions to
professional networking and representative organisations, in the home country, Europe and worldwide.
Training activities
Technology transfer offices were requested to indicate the number of training activities addressed to
TTO staff and developed in the last financial year. It includes not only classical training but also staff
exchanges, conferences, distance learning, etc.
Profile of clients/partners involved in knowledge transfer activities
Technology transfer offices were requested to indicate the number of public/private business clients or
partners, as well as the amount of revenues derived from them during the last financial year.
Also technology transfer offices were requested to indicate the number of internal clients (academics
involved in knowledge transfer activities), and the number of clients (public and private) operating:
regionally, nationally and internationally. Revenues during last financial year from private business
clients operating regionally was also requested.
Indicators of stock of technology
Recurrent institutional research grants
Technology transfer offices were requested to include the amount of recurrent institutional research
grants in the last financial year. For the purpose of the survey, ‘recurrent institutional research grants’
are institution own resources dedicated to research and development.
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Findings: indicators used in benchmarking surveys
IP expenditures
Technology transfer offices were requested to indicate the amount spent in external legal fees, patent
costs and specialist IP consultancy advice during the last financial year.
Institutional research revenues
Technology transfer offices were requested to include the approximate amount of research revenues in
the last financial year and breakdown it by source: regional government programmes, national
government programmes, European Community programmes; third party funded research and
consultancy contracts charities, donations; and other.
Research projects
Technology transfer offices were requested to include the number of projects granted, the income of
grants of these projects, the number of collaborative research proposals submitted for public funding
during the last financial year, and the number of active projects and their value generated.
Contracts and technical services
Technology transfer offices were requested to include: the number of R&D and consultancy contracts
negotiated by the TTO (with or without success); the number of contracts entered into during the last
financial year; the number of contracts active in portfolio and revenue generated during the last
financial year; and, the number and value of technical services carried out during last financial year.
Inventions/commercial disclosures
Technology transfer offices were requested to include the number of invention disclosures received
during the last financial year. For the purpose of the survey, “disclosure “ is a document that contains
all the information which is deemed necessary to evaluate the potential of an invention/result deriving
from the research activities so as to be able to decide its legal protection and/or active
commercialisation.
Priority patent applications filed
Technology transfer offices were requested to include the number of priority patent applications filed
during the last financial year. For the purpose of the survey ‘Priority patent applications’ are new patent
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Findings: indicators used in benchmarking surveys
applications that have been filed by the institution (plant breeders applications had also to be included),
and does not include continuations, divisional, or reissues, continuations in parts, etc.
Patents applied for extension
Technology transfer offices were requested to include the number of patents applied for extension
during the last financial year. For the purpose of the survey, ‘extension’ means a PCT application or a
patent application in another country than that where priority patent has been filed.
Patent portfolio
Technology transfer offices were requested to include the number of active patents at the end of the
last financial year.
Patents licensed yielding revenues
Technology transfer offices were requested to include the number of patents licensed yielding revenues
during the last financial year.
Licenses/options/assignments granted
Technology transfer offices were requested to include the number of licenses/options/assignments
granted during the last financial year. For the purpose of the survey, a license is where the licensor
grants rights to use the technology under licence in a defined field of use and territory. An option
agreement grants the potential licensee a time period during which it may evaluate the technology and
negotiate the terms of a license agreement. An assignment is a transfer of all the knowledge rights
included ownership. One contract may grant more than one license.
Active licences
Technology transfer offices were requested to include the number of active licenses during the last
financial year.
Licenses/options/assignments providing returns
Technology
transfer
offices
were
requested
to
include
the
licenses/options/assignments providing returns during the last financial year.
78
number
of
active
Findings: indicators used in benchmarking surveys
Revenue from license/options/assignments
Technology
transfer
offices
were
requested
to
include
the
amount
of
revenues
from
license/options/assignments contracts during the last financial year.
Indicators of human capital
Business plans
Technology transfer offices were requested to indicate the number of business plans presented to the
TTO during the last financial year.
Indicators of start-up activity
Spin-off companies formed
Technology transfer offices were requested to include the number of spin-offs formed in the last
financial year. For the purpose of the survey, “spin-off” company refers to a new company whose
formation was dependent on the use of intellectual property (including patents, copyright, design rights,
"know how", and utility model or similar) which was created and/or developed at a university
Spin-off companies with university equity holding
Technology transfer offices were requested to include the number of spin-offs formed in the last
financial year where the university has taken shares directly or through affiliated seed fund.
Value of university equity holding
Technology transfer offices were requested to include the value of spin-off equity taken by the
university, directly or through affiliated seed fund, during the last financial year.
Seed funds/venture capital invested
Technology transfer offices were requested to include an approximate value of seed funds/venture
capital invested by the institution in spin-off companies during the last financial year.
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Findings: indicators used in benchmarking surveys
Forms of finance used for spin-off companies
Technology transfer offices were requested to indicate what forms of finance were used for new spin-off
companies established in the last financial year: venture capital finance; business angel finance;
university managed funds or equivalent; personal investment by founders; government grants; other
funds.
Start-up companies formed
Technology transfer offices were requested to include the number of start-ups formed during the last
financial year. For the purpose of the survey, start-ups are companies formed by staff, students, or
graduates within 2 years of graduation that did not depend on licensing or assignment of intellectual
property generated by the institution. Also, TTOs were requested to include the number for start-ups
that received assistance from the office.
Location of spin-offs and start-ups
Technology transfer offices were requested to include the number of existing spin-offs/start-ups that
are located or having their primary place of business in the institution’s home region.
Portfolio value of current spin-off companies
Technology transfer offices were requested to include the estimated portfolio value of current spin-off
companies.
Indicators of internal impacts
Revenue from spin-off equity
Technology transfer offices were requested to include the value of revenues from spin-off equity (profit
or investment) during the last financial year.
Exits of spin-off company investments
Universities were requested to include the total value realised through exits of spin-out companies
during the last financial year, and breaking it down by exists via: merger o trade sale; IPO( initial public
offering)/stock market flotation; MBO (management buy-out); and, failure or liquidation.
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Findings: indicators used in benchmarking surveys
3.2.6. APRU: TECHNOLOGY TRANSFER AND WEALTH CREATION (T2WC)
SURVEY
Formed in 1997, the Association of Pacific Rim Universities (APRU) is a consortium of 36
research universities in the Pacific Rim. This survey was conducted in 2001 and published in
2002, collecting data form 22 universities (10 from North America, 9 from Asia, and 1 from
Australia, New Zealand and South America), with an average response rate of 76%. The
purpose of the survey looked at how universities transfer and apply new knowledge and
technologies generated by research. It involves a multi-university study on the scope, pattern,
trends and impact of technology transfer activities by universities along the Pacific Rim.
Indicators of policies and strategies
University policies on technology transfer objectives
Universities were requested to indicate the relative importance of the following technology transfer
objectives: number of inventions disclosed; amount of licensing income generated; number of
inventions commercialised; number of start-ups created, amount of associated sponsored research
grants generated; contributions to prestige of the university; contributions to local economic
development; service to researchers; transfer of technology to the public good; and/or other.
Research and invention policies
Universities were requested to indicate (yes/no) if corporate sponsorship and joint R&D with industry is
encouraged centrally within the institution., and to indicate who owns the patent rights to technologies
developed by faculty, students and staff of the university in the course of their use of university
facilities: university; inventor/s; and/or other. Universities were also requested to indicate their current
split of net income (equity/ royalties) from patented (and un-patented) technologies among:
inventor/s; university; inventor’s department/school; technology transfer office; and/or other.
Start-up policies
Universities were requested to indicate the roles allowed to tenure track faculty related to start- up
companies: to serve on board of directors of a new start-up company to commercialise her/his
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Findings: indicators used in benchmarking surveys
invention; take no-pay leave to be involved in a new start-up to commercialise her/his invention;
engage in consulting for industry.
Universities were requested to indicate if they have a written policy statement on conflict of interest for
faculty member involvement with business/industry, as well as if they have an equity management
policy for start-up companies receiving technology licensing.
TTO archetype
Universities were requested to indicate the archetype of their technology transfer office (TTO) :an
internal office/department of the university; part of a foundation; a for-profit corporation; or a nonprofit corporation, as well as the structure between the TTO organisation and the office of the university
president.
Range of responsibilities for TTOs
Universities were requested to indicate the range of responsibilities of their TTO: technology transfer
trademark licensing, industry sponsored research, spin-off company formation, incubation, researcher
education (IP issues, working with industries, etc.) entrepreneurship, and/or other.
Indicators of resources and initiatives
Programme start date
Universities were requested to indicate the programme start date. It refers to the year in which at least
0,5 professional full time equivalent was devoted toward technology transfer activities.
Number of staff working at the TTO
Universities were requested to indicate the number of full time and/or part-time staff working at the
TTO.
Assistance provided to start-up companies
Universities were requested to indicate the current types of assistance provided by the university to
start-up
companies:
entrepreneurship
center
providing
entrepreneurship-related
education
and
outreach events, university can take equity in start-up companies, university-based incubator
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Findings: indicators used in benchmarking surveys
facility/services,
university-affiliated
research/science
park,
direct
investment
from
university
endowment fund in start-up companies "prototyping" fund, government commercialisation grants
advisement, aid in recruiting management team , facilitation of access to venture capital, mentoring
and business advisory services, business plan competition, other.
Indicators of stock of technology
Total sponsored research expenditures
Universities were requested to include the total expenditures made in the survey reporting years by the
institution in support of its sponsored research activities. Also, universities were requested to report the
indirect cost rate (as a % of total sponsored research expenditures.
Research expenditures: government sources
Universities were requested to include the % of the research expenditures made in the survey reporting
years by the institution in support of its research activities that were funded by all government sources,
including the federal government, state government or local municipal authorities.
Research expenditures: industrial sources
Universities were requested to include the % of the research expenditures made in the survey reporting
years by the institution in support of its research activities that are funded by for profit corporations,
but not expenditures supported by other sources such as foundations and other non-profit
organizations.
Research expenditures: foundation/endowment
Universities were requested to include the % of the research expenditures made in the survey reporting
years by the institution in support of its research activities that are funded by sources such as
foundations, endowment and other non-profit organizations.
Research expenditures as% of university's operating budget
Universities were requested to include the percentage of research expenditures related to the
university's operating budget in the survey reporting years.
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Findings: indicators used in benchmarking surveys
Research expenditures performed by school/department
Universities were requested to include the % of research expenditures performed by university
school/department: Physical Sciences, Engineering, Medicine (including nursing), Life Sciences and
Pharmacy , Agriculture, and others.
Invention disclosures
Universities were requested to include the number of invention disclosures, no matter how
comprehensive, that were made in the survey reporting years and were counted by the institution.
Patents applications filed
Universities were requested to include the number of patent applications in the survey reporting years
filed by the institution, and breakdown it, by patent applications filed in home country, in U.S. or other
countries. For the purpose of the survey patents applications filed includes any filing made, including
provisional applications, provisional applications that are converted to regular applications, new filings,
CIPs, continuations, divisionals, reissues, and plant patents. Applications for certificates of plant variety
had also to be included. For patents application filed in the U.S., certificates of plant variety protection
issued by the U.S.D.A. had also to be included.
Cumulative non-expired patents issued
Universities were requested to include the number of total non-expired patents issued as the end of the
survey-reporting year. Also, universities were requested to breakdown it by schools/departments:
Physical Sciences, Engineering, Medicine (including nursing), Life Sciences and Pharmacy, Agriculture,
and others, as well as by patents issued in home country, issued in the USA or issued in other
countries.
Licences/options executed
Universities were requested to include the number of licenses/options executed in the survey reporting
years, as well as the total cumulative number as of end of last fiscal year.
Licences/options executed with equity
Universities were requested to include the number of licenses/options executed with equity in the
survey reporting years, as well as the total cumulative number as of end of last fiscal year.
84
Findings: indicators used in benchmarking surveys
Exclusivity of licences/options
Universities were requested to breakdown the number of licenses/options executed in the survey
reporting years, as well as the total cumulative number as of end of latest fiscal year, by exclusive or
non-exclusive licences.
Types of recipient organizations of licences
Universities were requested to breakdown the number of licenses/options executed in the survey
reporting years, as well as the total cumulative number as of end of latest fiscal year, by exclusive type
of licensee companies: start-ups companies or existing companies.
Licenses yielding income
Universities were requested to include the number and amount of active licenses/options yielding
income in the survey reporting years, excluding income earned from licensing of trademarks, as well as
breakdown the total amount by income received and income paid to other institutions. For the purpose
of the survey, license income received includes: license issue fees, payments under options, annual
minimums, running royalties, termination payments, the amount of equity received when cashed-in,
and software and biological material end-user license fees equal to $1,000 or more, but not research
funding, patent expense reimbursement, a valuation of equity not cashed-in, software and biological
material end-user license fees less than $1,000, or trademark licensing royalties from university
insignia. License income also does not include income received in support of the cost to make and
transfer materials under material transfer agreements. License income paid to other institutions is a
subset of license income received and didn’t have tot be subtracted from the total.
Gross license income
Universities were requested to breakdown the gross licence income received in the last fiscal year, by
one-time royalty/fees, running royalties, cashed-in equity or other types. For the purpose of the survey,
one-time royalties/fees are defined as royalties earned on a one-time, up-front basis independent of the
actual sale of products. Included in this number are license issue fees and payments under options.
Excluded from this amount are termination payments and annual minimum payments not supported by
sales, which should be reported separately. Running royalties are defined as royalties earned on the
sale of products. Excluded from this number are license issue fees, payments under options,
termination payments, and the amount of annual minimums not supported by sales. Cashed-in equity
85
Findings: indicators used in benchmarking surveys
includes the amount received from cashing in equity holdings, resulting in a cash transfer to the
institution. The amount reported had to be reduced by the cost basis, if any, on which the equity was
acquired. Excluded from this amount is any type of analysis or process whereby a value for the equity
holdings is determined but a cash transaction does not take place through the sale of these holdings.
Research funding generated by licensing
Universities were requested to report whether any technology licensing over past 3 years generate new
sponsored research grants to university by recipient company, as well as the total amount of research
and development support committed to your institution (even if the funds are to be spent over several
years) that was related to license/option agreements executed by the institution.
Indicators of start-up activity
Start-ups formed
Universities were requested to include the number of start-ups companies, breaking it down by startups with or without technology licensing from the university.
Indicators of internal/external impacts
Number of jobs created
Universities were requested to include the number of jobs created by the start-ups with technology
licensing from the university and start-ups without technology licensing from the university.
External investment received
Universities were requested to indicate the total amount of external investment received by start-ups
with technology licensing from the university and start-ups without technology licensing from the
university.
Sales revenue generated
Universities were requested to indicate the total amount of sales revenues generated by start-ups with
technology licensing from the university and start-ups without technology licensing from the university.
86
Findings: indicators used in benchmarking surveys
3.2.7 GLOBALSTART PROJECT: BENCHMARKING SURVEY
The GlobalStart is a project funded by the Fifth Framework Programme of the European
Community, and is part of the European Commission's Pilot Action of Excellence in Innovative
Start-ups (PAXIS). In the framework of the project, a benchmarking exercise among the seven
participant universities was done in order to examine their spin-off creation performance and
processes, and more specifically global spin-off creation. Qualitative and quantitative indicators
were grouped into four different levels: spin-off support activities; other technology transfer;
capabilities of the university; and, regional context.
The following indicators are gathered from the draft report of the benchmarking exercise
(published in 2004). Although the report includes indicators as those for benchmarking the
regional contexts of each project partner, we just include indicators referred to internal
resources/capabilities of universities.
Indicators of policies
University’s core missions
Universities were requested to indicate the level of importance (crucial, very important, important or
less important) of the education, research and commercialisation of research results for them.
Technology transfer strategies
Universities were requested to indicate (yes/no) if technology transfer has an explicit objective in the
overall strategy of the university, as well as indicate (yes/no) the presence of a specific university policy
with regard to the management of university related intellectual property rights (IPR).
Indicators of resources and initiatives
87
Findings: indicators used in benchmarking surveys
Start of technology transfer activities
Universities were requested to include the year/s when they started technology transfer activities,
active IPR support and/or active spin-off support. Universities were also requested to indicate the year
of the technology transfer office (TTO) establishment, first year in which at least 0,5 full time equivalent
(FTE) was dedicated to IPR support, and first year in which at least 0,5 FTE was dedicated to spin-off
support.
TTO staff
Universities were requested to include the total number of professional staff currently working at the
TTO, and breakdown it by: staff for spin-off support; IPR support; contract research; and/or others. For
the purpose of the survey, Professional staff is the qualified TTO staff responsible for carrying out
technology transfer activities on behalf of the university, based on expert knowledge and / or working
experience.
TTO staff-professional background
Universities were requested to indicate the professional background of the TTO staff members involved
in spin-off support: Economics/Business Administration; Law; Engineering; Biomedical; and/or other.
The survey report includes the following indicators to normalise values relating to university size: total
TTO staff per 100 academic staff; spin-off staff per 100 academic staff; IPR staff per 100 academic
staff; contract research staff per 100 academic staff; total TTO staff per 100 professor; spin-off staff per
100 professor; IPR staff per 100 professor; contract research staff per 100 professor.
TTO staff-professional experience
Universities were requested to indicate the years of professional experience of TTO staff members
involved in spin-off support: years of professional experience, including business experience. The
survey report includes the averages of professional experience per member and business experience
per member of TTO staff.
TTO working budget
Universities were requested to indicate the value of the working budget of the last year. The survey
report includes values of working budget per TTO staff and working budget per 100 academic staff.
88
Findings: indicators used in benchmarking surveys
Capital/loans: spin-off support activities
Universities were requested to indicate of the university has their own seed capital funds for spin-offs
and its size, as well as to indicate the provider (TTO, other university unit; region) of support activities
related to capital and loans (providing capital, providing support to obtain capital, providing loans).
Infrastructure: spin-off support activities
Universities were requested to indicate the number of incubators, high tech incubators and science
parks in the region, the degree of involvement of the university with them, and the range of services
offered by incubators and science parks: office space; professional equipment; administrative support;
management support; and/or financial services.
Also, universities were requested to indicate the provider (TTO, other university unit; region) of support
activities related to infrastructure (providing access to university equipment and facilities, finding
infrastructure).
Networking: spin-off support activities
Universities were requested to indicate the number of networks in which the TTO (officers) participate
(regional, national and international level), as well as if the TTO or others in the university provide
access to industrial and entrepreneurial networks.
Awareness creation/pre-venture and venture support
Universities were requested to indicate the provider/s (TTO, other university unit; region) and the
activities related to awareness creation, pre-venture and venture support: awareness creation
activities;
training
activities
oriented
towards
stimulating
entrepreneurship;
identification
of
opportunities; market research and competitor analysis; development of business plan; formation of
management team; legal / tax consulting for the spin-off company; advice in the field of IPR for the
spin-off company; advice in the field of export and internationalisation; management support / interim
management; management training.
Indicators of stock of technology and TT activities
Scientific publications
Universities were requested to indicate the number of scientific publications during the last year.
89
Findings: indicators used in benchmarking surveys
Contract research revenue
Universities were requested to include the value of revenues from contract research during the last
year. The survey report includes revenue from contract research per academic staff, per professor, and
per staff involved in contract research.
Invention disclosures
Universities were requested to include the number of invention disclosures received during the last
year. Also, the survey report includes the following indicators: invention disclosures per 100 academic
staff; invention disclosures per 100 professor; invention disclosures per 100 academic staff involved.
Patents applications
Universities were requested to include the number of patent applications filed during the last year. Also,
the survey report includes the following indicators: patent applications per 100 academic staff; patent
applications per 100 professor; patent applications per 100 academic staff involved.
Patents granted
Universities were requested to include the number of patents granted during the last four years. Also,
the survey report includes the following indicators: patent granted per 100 academic staff; patent
granted per 100 professors; patent granted per 100 academic staff involved.
Licensing revenue
Universities were requested to include the value of revenues from licensing during the last year. Also,
the survey report includes the following indicators: license revenue per 100 academic staff; license
revenue per 100 professors; license revenue per 100 academic staff involved.
Valorisation method used for patents granted
Universities were requested to include the % of the patent portfolio valorised and used methods during
the last five years: % licensed to a company; % licensed to a spin-off; % transferred to a spin-off.
90
Findings: indicators used in benchmarking surveys
Indicators of start-up activity
Spin-off companies formed
Universities were requested to include the total number of spin-off companies formed during all years,
as well as the number of spin-off companies formed during last five years. Also, the survey report
includes: % of spin-offs formed during the last five years; number of spin-offs per 100 academic staff;
number of spin-offs per 100 professor; number of spin-offs per 100 academic staff involved; number of
spin-offs per TTO staff; number of spin-offs per TTO staff for spin-off support.
For the purpose of the survey, universities were requested to indicate their criteria/s used to define the
term spin-off, among: a newly established firm that exploits knowledge and research results, developed
within the university; at least one of the founders is a researcher, who was actively involved in the
development of the knowledge; active involvement of the university by contribution in-kind (intellectual
property) or investment in equity.
Spin-off distribution
Universities were requested to indicate the industry where the spin-offs formed during the last five
years are operating: food; pharmaceuticals and biotechnology; ICT; industrial products, machinery and
equipment; medical devices; consulting; others.
Spin-offs with global potential
Universities were requested to indicate the number of spin-offs formed during the last five year that
have a global potential.
Academic staff involved in spin-off activities
Universities were requested to indicate the % of academic staff involved in: spin-off activities; IPR
activities and contract research.
Spin-off failure
Universities were requested to indicate the number of spin-off formed that have ceased trading
(bankruptcy, settlement, etc.) over the last five years. The survey report also includes the % of failure.
91
Findings: indicators used in benchmarking surveys
Indicators of human capital
SCI-covered publications
Universities were requested to include the number of SCI (science citation index)-covered publications
of the university during the last year.
Business ideas and plans
Universities were requested to include the number of both business ideas and business plans presented
during the last year.
Indicators of internal/external impacts
Spin-off employment
Universities were requested to indicate the number of employees of spin-offs formed during the last five
years. The survey report includes the total number of employees and an average of employees per
spin-off.
Spin-off revenues
Universities were requested to breakdown the number of spin-offs formed during the last five years by
their approximate revenues (keur): < 250; 250-500; 501-1000; 1001-2500; >2500. The survey report
also includes an average of revenues per firm.
92
Findings: indicators used in benchmarking surveys
3.2.8. SUMMARY CHECKLIST OF BENCHMARKING SURVEY INDICATORS
The following tables show a summary of the indicators of academic entrepreneurship gathered
from the benchmarking surveys. These tables allow us to detect the most common indicators
according the dimensions of our proposed framework for monitoring academic entrepreneurship.
Table 3.2.1. Indicators of policies and strategies.
PROTON
OECD
AUTM
APRU
HEBI
UNICO
GS
AUTM
APRU
HEBI
UNICO
GS
University core missions
IP policy
TT strategies
TTO archetype
Incentives and rewards
Start-up policies
Table 3.2.2. Indicators of resources and initiatives.
PROTON
OECD
Age of TTO
TTO functions
TTO staff
Technical/
support
Level of educ./
experience
Specific duties
Support for start-ups
TTO budget
By activities
TTO networking
93
Findings: indicators used in benchmarking surveys
Staff training
Methods to evaluate
start-up projects
Table 3.2.3. Indicators of stock of technology.
PROTON
Total research
expenditures
Origin of funds
By school
Total research funding
Origin of funds
Research projects
Scientific publications
New invention
disclosures
New patents
applications/filed
By technical
field
Stock of active patents
By technical
field
Licensed/non
licensed
Yielding income
Licensee types
New patents
granted/issued
Jurisdictions
New non patent IP
actions
By type
Ratio of New Patent
Applications Filed to
Invention Disclosures
94
OECD
AUTM
APRU
HEBI
UNICO
GS
Findings: indicators used in benchmarking surveys
received
Patents Issued as % of
Total Patent Applications
Patents Issued % of New
Patent Applications
Non-patent IP actions
Table3.2.4. Indicators of technology transfer activity.
PROTON
OECD
AUTM
APRU
HEBI
UNICO
GS
Total IP income
Distribution by
stakeholders
IP expenditures
Legal fees
reimbursements
Number and amount of
R+D contracts
Consultancy contracts
Methods to find licensees
New licences negotiated
Type of IP
New licences executed
Type of IP
Research area
Exclusivity
Licence
requirements
Licensee types
National/oversea
s
With equity
Active licenses/options
Yielding Income
95
Findings: indicators used in benchmarking surveys
License income of active
licences
Source types
Licensee types
Amount of license income
paid to other institutions
Adjusted gross income
from licences
Profile of TTO clients
Internal/external
Geographical
distribution
Table 3.2.5. Indicators of start-up activity.
PROTON
New start-ups formed
University equity
holding
Equity finance
origin
Location
Amount of external
investment received
Active start-up
companies
University equity
holding
More than 3
years old
New equity
finance origin
Location
Industry
Global potential
Non-operational start-ups
96
OECD
AUTM
APRU
HEBI
UNICO
GS
Findings: indicators used in benchmarking surveys
Table 3.3.6. Indicators of human capital.
PROTON
OECD
AUTM
APRU
HEBI
UNICO
GS
Share of students
employed in enterprises
during their studies
Provision of courses for
business: number of
students
New business ideas/plans
SCI-covered publications
Table 3.2.7. Indicators of internal impacts.
PROTON
OECD
AUTM
APRU
HEBI
AUTM
APRU
HEBI
UNICO
GS
Value of new/total
venture capital
invested
Value of revenues
from start-up equity
Number/value of exits
from spin-offs
Table 3.2.8. Indicators of external impacts.
PROTON
OECD
UNICO
GS
Estimated turnover of
active firms
Estimated
employment of all
active firms
Product introductions
97
Findings: Delphi survey results
3.3. DELPHI SURVEY RESULTS
This section includes the results of the Delphi survey. Advantages of the applied methodology
are several. Delphi methodology has enabled us to elicit and refine a group rational judgement
on the issue of entrepreneurship evaluation, by structuring an effective group communication
process
to
deal
with
this
complex
issue.
Nevertheless,
this
methodology
has
some
disadvantages. In order to glean as much information in the exploratory stage as possible and
hold not induced opinions, we preferred the use in the first round of open-ended questions
against, for instance, of using screened indicators derived from literature or other sources. As
consequence, it could have generated a decrease of the level of information compiled, since
certain questions were not asked or focused on specific issues, as it could have been asking
about indicators for defined key areas of analysis.
Following tables show proposed indicators and the results of the second round survey, which
attempted to “bring close” opinions of experts about proposed indicators asking about
“suitability” of each indicator, and the features measurability, revision period and scale.
For the question suitability, respondents had the option of choosing among four possible
responses: “very good”, “not too bad” and “bad”. For the question measurability, respondents
had the option of choosing between two possible responses: “yes”, “no”. For the question
period, respondents had the option of choosing among three possible responses: “academic
year”, “calendar year” and an open-ended one “others”. For the question scale, respondents had
the option of choosing between two possible responses: “ranks” and “absolute values”.
Table 3.3.1. Proposed indicators within the area “Stock of technology”.
STOCK OF
TECHNOLOGY
N° of patent
applications
98
Suitability
VG
66%
NTB
33%
Measurability
DK
0%
Y
66%
N
0%
Period
DK
AY
CY
33%
50%
50%
Scale
DK
0%
R
AV
0% 100%
DK/
0%
Findings: Delphi survey results
Table 3.3.2. Proposed indicators within the area “Resources and initiatives”.
RESOURCES &
INITIATIVES
Suitability
VG
NTB
Measurability
DK
Y
N
Period
DK
AY
CY
Scale
DK
R
AV
DK/
University financial
support
100%
0%
0%
83%
17%
0%
33%
66%
0%
17%
83%
0%
seed capital
invested
100%
0%
0%
83%
17%
0%
33%
66%
0%
17%
83%
0%
loans conceded
66%
17%
17%
50%
17%
33%
17%
50%
33%
17%
50%
33%
awards conceded
66%
17%
17%
50%
17%
33%
17%
50%
33%
17%
33%
50%
33%
0%
66%
33%
17%
50%
17%
50%
33%
33%
17%
50%
83%
17%
0% 100%
0%
0%
66%
33%
0%
17%
83%
0%
in pre-spin off
assistance
66%
17%
17%
50%
17%
33%
66%
17%
17%
17%
66%
17%
in spin off
assistance
66%
17%
17%
50%
17%
33%
66%
17%
17%
17%
66%
17%
in research
activities
66%
17%
17%
66%
17%
17%
66%
17%
17%
17%
66%
17%
in marketing and
communication
activities
50%
33%
17%
66%
17%
17%
66%
17%
17%
33%
50%
17%
N° of encouragement
activities
83%
17%
0% 100%
0%
0%
50%
33%
17%
0%
66%
33%
N° of entrepreneurship
training courses
83%
17%
0% 100%
0%
0%
50%
33%
17%
0%
66%
33%
TTO Working budget
% of regularly
paid micro loans
TTO staff (FTEs)
66%
17%
17%
66%
0%
33%
50%
50%
0%
33%
50%
17%
in pre-spin off
assistance
33%
33%
33%
33%
0%
66%
50%
17%
33%
17%
33%
50%
research
activities
33%
17%
50%
33%
0%
66%
33%
33%
33%
17%
33%
50%
in spin off
assistance
17%
33%
50%
33%
0%
66%
33%
17%
50%
0%
33%
66%
public/private
origin
0%
66%
33%
50%
0%
50%
50%
33%
17%
33%
33%
33%
In marketing and
communication
activities
0%
17%
83%
33%
33%
33%
50%
17%
33%
17%
33%
50%
No. of news in local and
national press
17%
66%
17%
33%
33%
33%
33%
33%
33%
0%
33%
66%
No. of requests for the
accommodation in TI
17%
50%
33%
17%
33%
50%
33%
0%
66%
0%
33%
66%
99
Findings: Delphi survey results
No. of published articles
improving innovation
awareness
0%
50%
50%
0%
17%
83%
0%
17%
83%
0%
0% 100%
No. of psychological
profile questionnaires
filled in
17%
50%
33%
33%
33%
33%
33%
17%
50%
0%
33%
66%
No. of companies
accepted to the
Technology Incubator
0%
50%
50%
33%
0%
66%
33%
33%
33%
17%
50%
33%
No. of articles
describing the best
practices
0%
50%
50%
0%
17%
83%
0%
17%
83%
0%
0% 100%
Table 3.3.3. Proposed indicators within the area “human capital”.
Suitability
HUMAN CAPITAL
VG
NTB
Measurability
DK
Y
N
Period
DK
AY
CY
Scale
DK
R
AV
DK/
No. of attendants in
training activities
83%
0%
17% 100%
0%
0%
83%
17%
0%
No. of business plans
drawn up
83%
0%
17%
83%
0%
17%
50%
33%
17%
0%
83%
17%
Amount of contract
research
66%
33%
0%
66%
0%
33%
33%
50%
17%
0%
83%
17%
No. of business ideas
66%
17%
17%
50%
17%
33%
50%
33%
17%
0%
83%
17%
No. of students enrolled
on business creation
subjects
66%
0%
33%
66%
0%
33%
50%
17%
33%
0%
66%
33%
No. of attendants in
encouragement
activities
50%
33%
17% 100%
0%
0%
66%
33%
0%
0% 100%
0%
No. of university staff
involved in new projects
50%
33%
17%
50%
17%
33%
50%
17%
33%
0%
66%
33%
No. of informal contacts
(requests for
information)
33%
17%
50%
50%
50%
0%
66%
17%
17%
0%
83%
17%
No of applicants for the
Enterprise Fellowship
Scheme
33%
0%
66%
33%
33%
33%
17%
33%
50%
0%
50%
50%
0%
50%
50%
33%
17%
50%
33%
33%
33%
0%
66%
33%
No. of staff employed by
contract research
100
0% 100%
0%
Findings: Delphi survey results
Table 3.3.4. Proposed indicators within the area “start up activity”.
START UP
ACTIVITY
Suitability
VG
NTB
Measurability
DK
Y
100%
0%
100%
0%
05
50%
50%
Average growth of No.
spin-offs
33%
No. of university staff
involved in new spinoffs
No. of spin-offs sent to
bankruptcy
No. of spin-offs formed
Global/ non
global
Assisted/not
assisted
0% 100%
N
Period
DK
AY
CY
Scale
DK
R
AV
DK/
0%
0%
50%
50%
0%
17%
83%
0%
83%
0%
17%
50%
50%
0%
17%
83%
0%
0%
33%
33%
33%
17%
33%
50%
17%
50%
33%
66%
0%
17%
33%
50%
17%
33%
50%
0%
50%
50%
83%
17%
0%
50%
17%
33%
50%
33%
17%
0%
83%
17%
50%
33%
17%
33%
33%
33%
33%
33%
33%
0%
66%
33%
101
4. SET OF INDICATORS
103
Set of indicators
4.1. OVERVIEW
The following proposed set of indicators is addressed to stakeholders on business creation inside
higher education institutions, in order to be an orientation tool for the development of their
tasks related to the monitoring academic entrepreneurship. Some of the uses of the set are
related to:
The development of university policies, strategies and initiatives related to academic
entrepreneurship through the analysis of the captured data.
The setting of targets, analysis of trends and benchmarking.
Short, medium and long-term planning of initiatives and milestones.
Dialogue and report of impacts to stakeholders outside university: policy makers, funding
institutions, other universities, chambers of commerce, local development agencies, etc.
For the development of this proposal of indicators, we have carried out a literature review on
resources and capabilities of universities that are correlated with start-up activity in order to
find cause–effect relationships. From this review, we have gathered and identified indicators for
the measurement of these resources and capabilities, the start-up activity and the wealth
creation by reviewing benchmarking surveys on technology transfer as well as the development
of a Delphi survey.
Concretely, the proposed indicators are grouped into seven subsets which shape the framework
for monitoring academic entrepreneurship. Four of these subsets include indicators for the
measurement of “inputs” implied in the entrepreneurial process: policies and strategies, stock of
technology, resources and initiatives and human capital. The indicators for the measurement of
“outputs” of the university entrepreneurial process are included in three subsets, which
comprise start-up activity, and internal and external impacts, as measures of wealth creation.
This framework and each subset are explained below.
104
Set of indicators
For a better comprehension, in each subset (excluding policies and strategies) the indicators are
grouped into three types: basic, recommended and global activity (concerning the measurement
of international entrepreneurship). In addition, normalised indicators regarding the size of the
university (by academic staff and research expenditures) are included, in order to allow
benchmarking exercises and take into account changes when medium and long-term planning
actions are undertaken. A glossary of terms and definitions is attached, as well as two examples
of questionnaires for the indicators based on data surveys.
Stock of
Stock of
TTechnology
echnology
Policies
Policies
&
&
Strategies
Strategies
Resources &
Resources &
Initiatives
Initiatives
Human Capital
Human Capital
START-UP
START
START-UP
ACTIVITY
ACTIVITY
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
Policies and strategies
According to the different universities policies on technology transfer developed by the
university, the start up activity can be encouraged or inhibited. Accordingly, this subset of
indicators monitors the perceptions of university stakeholders on the state of start-up policies,
as well as the strategies and their implementation in structures of support.
Stock of technology
The technological production is the main source of business opportunities for a university.
Thereby, it is necessary to gather information about the” business opportunities portfolio” as
well as monitor its characteristics and the trends over time. Analysis of the information gathered
with these indicators can provide the university with knowledge about their weakness and
105
Set of indicators
strengths in terms of technological production in order, for instance, to develop specific policies
and initiatives or to focus on more promising departments or technologies.
Resources and initiatives
Some institutional resources, and its optimal use, can affect the university capabilities for
supporting new start-ups. Institutional resources such as staff with experience in business
creation issues, or economical resources for the development of support initiatives (training,
counselling, etc.) are monitored with the indicators included in this subset.
Human capital
The potential entrepreneurs that universities possess are a key element determining their startup activity performance. Not only the number of potential entrepreneurs, but also their
characteristics can influence the access to external resources and the further performance of
new firms.
Start-up activity
This subset includes indicators to monitor the start-up activity performance of an university in
terms of new organisations created, university community involvement, and the characteristics
of the start-up portfolio. Indicators to measure and monitor efficiency of resources used to
support start-up activity are also included in this subset.
Internal impacts
One part of the wealth creation derived from university start-ups can be measured in terms of
impacts to the university. This subset includes indicators both for measuring and monitoring
internal impacts in economical-financial terms and job creation for university community.
External impacts
The other part of the wealth creation by university start-ups can be measured in terms of
impacts to the society. The university, as a social organisation, must measure the impact of
106
Set of indicators
their start-ups in terms of contribution to the economic and social development. Indicators such
as contribution to the local GDP or to the employment are included in this subset. These
indicators are also useful to dialogue with the society and its institutions in order to
communicate these impacts and acquire new external support for academic entrepreneurship.
4.3. REMARKS AND RECOMMENDATIONS OF USE
This proposed set of indicators is an orientation tool for the developing a performance
measurement system for monitoring academic entrepreneurship. Since many universities have
implemented their own performance measurement systems, the main usefulness for these
institutions is to serve as a basis for reviewing, redefining or improving existing ones.
This implies that universities, according to their characteristics, have to develop their own
performance measurement systems by focusing in their specific key areas, selecting and fitting
the indicators. The process of developing and implementing a performance measurement
system for monitoring academic entrepreneurship can be a complex task due to the
organisational characteristics of higher education institutions. Accordingly, we suggest that the
steps to follow for using this set of indicators are related to:
1. Review of the university strategy concerning the promotion and support of academic
entrepreneurship.
2. Identify the factors of the university that are influencing start-up activity rates, and
select those key factors that will be monitored.
3. Identify existing related targets of the university.
4. Review of the existing performance measurement systems and measures that are
included.
5. Select and adapt the indicators: definitions, key concepts, revision periods, etc.
6. Integration of indicators in the existing performance measurement system.
107
Set of indicators
Concerning the use of this set for benchmarking exercises, the use of a scale of measurement
that facilitates a correct interpretation of questions is crucial for achieving quality results.
Therefore, we suggest the adaptation of indicators to the reality of surveyed universities, ass
well as clear definitions regarding to key concepts.
108
Set of indicators
Stock of
Stock of
Technology
Technology
Policies
Policies
&
&
Strategies
Strategies
Resources
Resources&&
IInitiatives
nitiatives
Human Capital
Human Capital
START-UP
START
START-UP
ACTIVITY
ACTIVITY
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
POLICIES & STRATEGIES
INDICATORS
INDICATORS
Code
Pall
A. Basic
Perceptions of university community
Average score given by all university stakeholders on policies and
strategies to encourage and support start up activity.
Pubm
Perceptions of university board members
Average score given by the university board members on policies
and strategies to encourage and support start up activity.
Pstaff
Perceptions of staff involved in start up support
Average score given by the staff involved in supporting start-ups
on policies and strategies to encourage and support start up
activity.
Pacstaff
Perceptions of academic staff
Average score given by researchers/lecturers on policies and
strategies to encourage and support start up activity.
Punder
Perceptions of undergraduates
Average score given by students on policies and strategies to
encourage and support start up activity.
109
Set of indicators
Stock of
Stock of
Technology
Technology
Policies
Policies
&
&
Strategies
Strategies
Resources
Resources&&
Initiatives
Initiatives
START-UP
START
START-UP
ACTIVITY
ACTIVITY
Human Capital
Human Capital
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
STOCK OF TECHNOLOGY
INDICATORS
INDICATORS
Code
RDexp
A. Basic
R&D expenditures
Total amount of research expenditures made during the last year.
Nsp
New scientific publications
Number of scientific publications made during the last year.
Nid
New invention disclosures
Number of invention disclosures received during the last year.
Npa
New patent applications
Number of patent applications made during the last year.
Npg
New patents granted
Number of patents granted during the last year.
Npac
New patents actions
Number of patent applications and patents granted made during
the last year. It’s an integration of the indicators “Npa” and “Npg”.
PPort
Patent portfolio
Number of active patents at the end of the year.
110
Set of indicators
Code
Rdexp/S
B. Recommended
Research expenditures by school
Distribution of the total amount of research expenditures made in
the last year by school/department.
Pport/S
Patent portfolio by school
Distribution of the patent portfolio by school/department.
Code
Nipa
C. Global activity
New international patent applications
Number of patents for which international extensions were applied
for during the last year.
Nipg
New international patents granted
Number of patents for which international extensions were granted
during the last year.
Ipport
International patents’ portfolio
Number of active patents with international extensions granted, at
the end of the year.
NORMALISED INDICATORS
Code
Rdexp/as
A. Per academic staff
Research expenditures per academic staff
“Rdexp” value per 100 academic staff.
Nsp/as
New scientific publications per academic staff
“Nsp” value per 100 academic staff.
Nid/as
Invention disclosures per academic staff
“Nid” value per 100 academic staff.
111
Set of indicators
Npa/as
New patent applications per academic staff
“Npa” value per 100 academic staff.
Npg/as
New patents granted per academic staff
“Npg” value per 100 academic staff.
Npac/as
New patents actions per 100 academic staff
“Npac” value per 100 academic staff.
PPort/as
Patent portfolio per academic staff
“Pport” value per 100 academic staff.
Nipa/as
New international patent applications per academic staff
“Nipa” value per 100 academic staff.
Nipg/as
New international patents granted per academic staff
“Nipg” value per 100 academic staff.
Ipport/as
International patents’ portfolio per academic staff
“Ipport” value per 100 academic staff.
Code
Nps/RDexp
B. Per research expenditures
New scientific publications per research expenditures
“Nps” value per €10 million of research expenditures.
Nid/RDexp
Invention disclosures per research expenditures
“Nid” value per €10 million of research expenditures.
Npa/RDexp
New patent applications per research expenditures
“Npa” value per €10 million of research expenditures.
Npg/RDexp
New patents granted per research expenditures
“Npg” value per €10 million of research expenditures.
Npac/RDexp
New patents actions per research expenditures
“Npac” value per €10 million of research expenditures.
112
Set of indicators
PPort/RDexp
Patent portfolio per research expenditures
“Pport” value per €10 million of research expenditures.
Nipa/RDexp
New international patent applications per research
expenditures
“Nipa” value per €10 million of research expenditures.
Nipg/RDexp
New international patents granted per research expenditures
“Nipg” value per €10 million of research expenditures.
Ipport/RDex
p
International patents’ portfolio per research expenditures
“Ipport” value per €10 million of research expenditures.
113
Set of indicators
Stock of
Stock of
TTechnology
echnology
Policies
Policies
&
&
SStrategies
trategies
Resources
Resources&&
Initiatives
Initiatives
START-UP
START
START-UP
ACTIVITY
ACTIVITY
Human
apital
HumanCCapital
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
RESOURCES & INITIATIVES
INDICATORS
INDICATORS
Code
Wf
A. Basic
Work force
Number of FTEs dedicated to encourage and support start-up
activity, including technical and administrative staff, at the end
of the year.
Suex
Start-up experience
Number of technical FTEs dedicated to support start-ups with
more than 2 years of experience, at the end of the year.
Suexp
Start-up support expenditures
Total amount of university expenditures made to encourage and
support start-up activity, during the last year.
Code
Exp/d
B. Recommended
Expenditures distribution
Distribution of start-up support expenditures by type of primary
process:
Marketing activities
Training activities
Advice/mentoring activities
IPR-licensing activities
114
Set of indicators
Wf/d
Work force distribution:
Distribution of technical and administrative FTEs by type of
primary process:
Marketing activities management
Training activities management
Advice/mentoring activities
IPR-licensing activities
Otser
Offer of training services
Total number of encouragement-training credits offered: sum for
all courses, of number of credits x places offered.
Oamser
Offer of advice/mentoring services
Total number of advice/mentoring credits offered: Sum of
technical FTEs dedicated to advice/mentoring.
Seedav
Seed capital available
Amount of own or affiliated university seed capital.
Code
GSe
C. Global activity
Global start-up experience
Number of technical FTEs dedicated to support international new
ventures with more than 2 years of experience.
Otii
Offer of training services in international issues:
Total number of offered credits for training courses in
international issues: sum for all courses, of number of credits x
places offered.
NORMALISED INDICATORS
Code
Wf/as
A. Per academic staff
Work force per academic staff
“Wf” value per 100 academic staff.
115
Set of indicators
Suex/as
Start-up experience per academic staff
“Suex” value per 100 academic staff.
Suexp/as
Start-up support expenditures per academic staff
“Suexp” value per 100 academic staff.
Otser/as
Offer of training services per academic staff
“Otser”value per 100 academic staff.
Oamser/as
Offer of advice/mentoring services per academic staff
“Oamser” value per 100 academic staff.
Seedav/as
Seed capital available per academic staff
“Seedav” value per 100 academic staff.
GSe/as
Global start-up experience per academic staff
“Gse” value per 100 academic staff.
Otii/as
International encouragement training services per academic
staff
“Otii” value per 100 academic staff.
Code
Wf/RDexp
B. Per research expenditures
Work force per research expenditures
“Wf” value per €10 million of research expenditures.
Suex/RDexp
Start-up experience per research expenditures
Suex” value per €10 million of research expenditures.
Suexp/RDexp
Start-up support expenditures per research expenditures
“Suexp” value per €10 million of research expenditures.
Otser/RDexp
Offer of training services per research expenditures
“Otser”value per €10 million of research expenditures.
Oamser/RDexp
116
Offer of advice/mentoring services per research expenditures
Set of indicators
“Oamser” value per €10 million of research expenditures.
Seedav/RDexp
Seed capital available per research expenditures
“Seedav” value per €10 million of research expenditures.
GSe/RDexp
Global start-up experience per research expenditures
“Gse” value per €10 million of research expenditures.
Otii/RDexp
Offer of international training services per research
expenditures
“Otii” value per €10 million of research expenditures.
117
Set of indicators
Stock of
Stock of
TTechnology
echnology
Policies
Policies
&
&
SStrategies
trategies
Resources
Resources&&
Initiatives
Initiatives
START-UP
START
START-UP
ACTIVITY
ACTIVITY
Human
HumanCapital
Capital
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
HUMAN CAPITAL
INDICATORS
INDICATORS
Code
Facqual
A. Basic
Faculty quality
Number of citations that the university has received during the
last year.
SCIpub
SCI-covered publications
Number of SCI-covered publications during the last year.
RDind
R&D industry revenues
Total amount of revenues derived from the R&D funded by
industry sources.
Nbip
New business ideas/plans
Number of business ideas and plans presented during the last
year.
Epe
Enrolment of potential entrepreneurs
Number of potential entrepreneurs enrolled in the assistance
programme.
Code
II
118
B. Recommended
Index of intention
Set of indicators
Percentage of academic staff with intentions of start-up a
business.
Nbip/s
Business ideas/plans per school
Distribution of “Nbip” value by school/department.
Epe/s
Potential entrepreneurs per school
Distribution of “Epe” value by school/department.
Code
Nibip
C. Global activity
New international business ideas/plans
Number of business ideas and plans with international approaches
presented during the last year.
NORMALISED INDICATORS
Code
Facqual/as
A. Per academic staff
Faculty quality per academic staff
“Facqual” value per 100 academic staff.
SCIpub/as
SCI-covered publications per academic staff
“SCIpub” value per 100 academic staff.
RDind/as
R+D industry revenues per academic staff
“RDind” value per 100 academic staff.
Nbip/as
New business ideas/plans per academic staff
“Nbip” value per 100 academic staff.
Epe/as
Enrolment of potential entrepreneurs per academic staff
“Epe” value per 100 academic staff.
Nibip/as
New international business ideas/plans per academic staff
“Nibip” value per 100 academic staff.
119
Set of indicators
Code
Facqual/RDexp
B. Per research expenditures
Faculty quality per research expenditures
“Facqual” value per €10 million of research expenditures.
SCIpub/RDexp
SCI-covered publications per research expenditures
“SCIpub” value per €10 million of research expenditures.
Rdind/RDexp
R+D industry revenues per research expenditures
“RDind” value per €10 million of research expenditures.
Nbip/RDexp
New business ideas/plans per research expenditures
“Nbip” value per €10 million of research expenditures.
Epe/RDexp
Enrolment of potential entrepreneurs per research
expenditures
“Epe” value per €10 million of research expenditures.
Nibip/RDexp
New international business ideas/plans per research
expenditures
“Nibip” value per €10 million of research expenditures.
120
Set of indicators
Stock of
Stock of
Technology
Technology
Policies
Policies
&
&
Strategies
Strategies
Resources
Resources&&
Initiatives
Initiatives
START-UP
START-UP
ACTIVITY
ACTIVITY
Human Capital
Human Capital
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
START-UP ACTIVITY
INDICATORS
INDICATORS
Code
NSU
A. Basic
New start-ups
Number of start-ups formed during the last year.
SUPort
Start-up portfolio
Current number of active start-ups at the end of the year.
Facpart
Faculty participation
Number of academic staff involved in active start-ups, at the end
of the last year.
SUPort/s
Start-up portfolio per school
Distribution of “SUPort” value by school/department.
Surrate
Survival rate
Percentage of start-ups formed during the last five years
currently active.
Attbal
Annual technology transfer balance
Percentage of licences executed during the last year to new startups.
Code
B. Recommended
121
Set of indicators
SUI
Start-up activity index
Number of start-ups formed during the last three years per 100
academic staff.
EAI
Entrepreneurial activity index
Percentage of academic staff involved in start-ups that were
formed during the last three years.
Eqport
Portfolio of start-ups with equity
Current number of active start-ups with university equity holding
SUloc
Start-ups location
Distribution of “SUport” value by current location:
University infrastructures: incubator/science park
Local
Regional
National
Eqportval
Equity portfolio value
Value of the university equity in active start-ups at the end of the
last year.
SUexit
Start-up exits
Number of exits via: IPO, or MBO
EWf
Efficiency of work force
Number of staff (FTEs) per new start-up.
SUcost
Unit cost
Support expenditures per new start-up during the last year. Thus
is, “Suexp” value divided by “NSU” value.
Code
NpGS
C. Global activity
New potential GS
Number of potential global-start-ups formed during the last year.
PGSport
122
Potential GS portfolio
Set of indicators
Current number of active start-ups formed during the last three
years with global potential.
GSport
GS portfolio
Current number of active global start-ups at the end of the year.
NORMALISED INDICATORS
Code
NSU/as
A. Per academic staff
New start-ups per academic staff
“NSU” value per 100 academic staff.
SUPort/as
Start-up portfolio per academic staff
“SUport” value per 100 academic staff.
Facpart/as
Faculty participation per academic staff
“Facpart” value per 100 academic staff.
SUPort/s
Start-up portfolio per school and per academic staff
“SUport/s” values per 100 academic staff.
Eqport/as
Portfolio of start-ups with equity per academic staff
“Eqport” value per 100 academic staff.
Eqportval/as
Equity portfolio value per academic staff
“Eqportval” value per 100 academic staff.
SUexit/as
Start-up exits per academic staff
“SUexit” value per 100 academic staff.
NpGS/as
New potential GS per academic staff
“NpGS” value per 100 academic staff.
PGSport/as
Potential GS portfolio per academic staff
123
Set of indicators
“PGSport” value per 100 academic staff.
GSport/as
GS portfolio per academic staff
“GSport” value per 100 academic staff.
Code
NSU/RDexp
B. Per research expenditures
New start-ups per research expenditures
“NSU” value per €10 million of research expenditures
SUPort/RDexp
Start-up portfolio per research expenditures
“SUport” value per €10 million of research expenditures
Facpart/RDexp
Faculty participation per research expenditures
“Facpart” value per €10 million of research expenditures
SUPort/s/RDexp
Start-up portfolio per school and per research expenditures
“SUport” value per €10 million of research expenditures
Eqport/RDexp
Portfolio of start-ups with equity per research expenditures
“Eqport” value per €10 million of research expenditures.
Eqportval/RDexp
Equity portfolio value per research expenditures
“Eqportval” value per €10 million of research expenditures
SUexit/RDexp
Start-up exits per research expenditures
“SUexit” value per €10 million of research expenditures
NpGS/RDexp
New potential GS per research expenditures
“NpGS” value per €10 million of research expenditures
PGSport/RDexp
Potential GS portfolio per research expenditures
“PGSport” value per €10 million of research expenditures
Gsport/RDexp
GS portfolio per research expenditures
“GSport” value per €10 million of research expenditures
124
Set of indicators
Stock of
Stock of
TTechnology
echnology
Policies
Policies
&
&
SStrategies
trategies
Resources
Resources&&
Initiatives
Initiatives
START-UP
START
START-UP
ACTIVITY
ACTIVITY
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
Human
apital
HumanCCapital
INTERNAL IMPACT
INDICATORS
INDICATORS
Code
RevSU
A. Basic
Revenues from start-ups
Total amount of revenues from start-up portfolio during the
last year, including licence incomes, cashed-in equity, and
R&D funds from start-ups.
NUjob
New university-related jobs
Number of jobs (FTEs) created from the start-up portfolio
during the last year, involving undergraduates, graduates,
PhDs, and academic staff of the university.
UJobport
University-related job portfolio
Number of active jobs (FTEs) created from start-up portfolio
involving undergraduates, graduates, PhDs, and academic
staff of the university.
TTrevbal
Technology transfer revenues balance
Percentage of total university licence incomes generated by
start-up portfolio during the last year.
Code
RevSU/o
B. Recommended
Revenues distribution
Distribution of amount revenues from start-up portfolio
125
Set of indicators
during the last year, by origin:
Licences: tax fees and royalties
Equity holdings: cashed in equity
R+D funds from start-ups
ROExp
Return over expenditures
Percentage of expenditures related to revenues.
Code
RevGS
C. Global activity
Revenues from GS
Total amount of revenues from GS portfolio during the last
year, which includes revenues from:
Licences: tax fees and royalties
Equity holdings: cashed in equity
R+D funds from GS
NGSUjob
New university-related jobs in global start-ups
Number of jobs (FTEs) created from the GS portfolio during
the last year, involving undergraduates, graduates, PhDs, and
academic staff of the university.
GSUjobport
GS university–related job portfolio
Number of active jobs (FTEs) created from GS portfolio
involving undergraduates, graduates, PhDs, and academic
staff of the university.
NORMALISED INDICATORS
Code
RevSU/as
A. Per academic staff
Revenues from start-ups per academic staff
“RevSU” value per 100 academic staff.
NUjob/as
New university-related jobs per academic staff
“Njob” value per 100 academic staff.
126
Set of indicators
UJobport/as
University-related job portfolio per academic staff
“Jobport” value per 100 academic staff.
TTrevbal/as
Technology transfer revenues balance per academic staff
“TTrevbal” value per 100 academic staff.
RevSU/o/as
Revenues distribution per academic staff
“RevSU/o” values per 100 academic staff.
ROExp/as
Return over expenditures per academic staff
“NGSjob” value per 100 academic staff.
RevGS/as
Revenues from GS per academic staff
“RevGS” value per 100 academic staff.
NGSUjob/as
New GS university-related jobs per academic staff
“NGSjob” value per 100 academic staff.
GSUjobport/as
GS university-related job portfolio per academic staff
“GSjobport” value per 100 academic staff.
Code
RevSU/RDexp
B. Per research expenditures
Revenues from start-ups per research expenditures
“RevSU” value per €10 million of research expenditures.
NUjob/RDexp
New jobs creation per research expenditures
“Njob” value per €10 million of research expenditures.
UJobport/RDexp
Job portfolio per research expenditures
“Jobport” value per €10 million of research expenditures.
TTrevbal/RDexp
Technology transfer revenues balance per research
expenditures
“TTrevbal” value per €10 million of research expenditures.
RevSU/o/RDexp
Revenues distribution per research expenditures
“RevSU/o” values per €10 million of research expenditures.
127
Set of indicators
ROEexp/RDexp
Return over expenditures per research expenditures
“NGSjob” value per €10 million of research expenditures.
RevGS/RDexp
Revenues from GS per research expenditures
“RevSU/o” values per €10 million of research expenditures.
NGSjob/RDexp
New GS jobs creation per research expenditures
“NGSjob” value per €10 million of research expenditures.
GSjobport/RDexp
GS job portfolio per research expenditures
“GSjobport” value per €10 million of research expenditures.
128
Set of indicators
Stock of
Stock of
TTechnology
echnology
Policies
Policies
&
&
SStrategies
trategies
Resources
Resources&&
Initiatives
Initiatives
START-UP
START
START-UP
ACTIVITY
ACTIVITY
Human
apital
HumanCCapital
INTERNAL
INTERNAL
IMPACTS
IMPACTS
EXTERNAL
EXTERNAL
IMPACTS
IMPACTS
EXTERNAL IMPACT
INDICATORS
INDICATORS
Code
SUturn
A. Basic
Start-up portfolio turnover
Total amount of turnover from start-up portfolio generated
during the last year.
Njob
New job creation
Total number of jobs (FTEs) created by active start-ups during
the last year.
Jobport
Job portfolio
Total number of employees (FTEs) in start up portfolio at the
end of the year.
Npi
New product introductions
Number of new products/processes/services introduced to the
market by start-up portfolio during the last year.
Pport
Product portfolio
Number of innovative and active product/services introduced to
the market by start-up portfolio.
Code
B. Recommended
129
Set of indicators
GDPcont
Contribution to the GDP
Percentage of the local/regional GDP generated by start-up
portfolio during the last year.
Forinvest
Foreign investments
Total amount of foreign investments made to start-ups during
the last year.
Code
GSturn
C. Global activity
Global start-ups portfolio turnover
Total amount of turnover from global start-up portfolio
generated during the last year.
GSNjob
New GS job creation
Total number of jobs (FTEs) created by active global start-ups
during the last year.
GSJobport
Global start-ups job portfolio
Total number of employees (FTEs) in global start up portfolio at
the end of the year.
GSNpi
New global start-ups product introductions
Number of new products/processes/services introduced to the
market by global start-up portfolio during the last year.
GSPport
Global start-up product portfolio
Number of new product/services introduced to the market by
global start-up portfolio.
NORMALISED INDICATORS
Code
SUturn/as
A. Per academic staff
Start-up portfolio turnover per academic staff
“SUturn” value per 100 academic staff.
Njob/as
130
New job creation per academic staff
Set of indicators
“Njob” value per 100 academic staff.
Jobport/as
Job creation per academic staff
“Jobport” value per 100 academic staff.
Npi/as
New product introductions per academic staff
“Npi” value per 100 academic staff.
Pport/as
Product portfolio per academic staff
“Pport” value per 100 academic staff.
GDPcont/as
Contribution to the GDP per academic staff
“GDPcont” value per 100 academic staff.
Forinvest/as
Foreign investments per academic staff
“Forinvest” value per 100 academic staff.
GSturn/as
Global start-ups portfolio turnover per academic staff
“GSturn” value per 100 academic staff.
GSNjob/as
New GS job creation per academic staff
“SUturn” value per 100 academic staff.
GSJobport/as
Global start-ups job creation per academic staff
“GSJobport” value per 100 academic staff.
GSNpi/as
New global start-ups product introductions per academic
staff
“GSNpi” value per 100 academic staff.
GSPport/as
Global start-up Product portfolio per academic staff
“GSPport” value per 100 academic staff.
Code
SUturn/RDexp
B. Per research expenditures
Start-up portfolio turnover per research expenditures
“SUturn” value per €10 million of research expenditures.
131
Set of indicators
Njob/RDexp
New job creation per research expenditures
“SUturn” value per €10 million of research expenditures.
Jobport/RDexp
Job creation per research expenditures
“SUturn” value per €10 million of research expenditures.
Npi/RDexp
New product introductions per research expenditures
“SUturn” value per €10 million of research expenditures.
Pport/RDexp
Product portfolio per research expenditures
“SUturn” value per €10 million of research expenditures.
GDPcont/RDexp
Contribution to the GDP per research expenditures
“SUturn” value per €10 million of research expenditures.
Forinvest/RDexp
Foreign investments per research expenditures
“SUturn” value per €10 million of research expenditures.
GSturn/RDexp
Global start-ups portfolio turnover per research
expenditures
“SUturn” value per €10 million of research expenditures.
GSNjob/RDexp
New GS job creation per research expenditures
“SUturn” value per €10 million of research expenditures.
GSJobport/RDexp
Global start-ups job creation per research expenditures
“SUturn” value per €10 million of research expenditures.
GSNpi/RDexp
New global start-ups product introductions per research
expenditures
“SUturn” value per €10 million of research expenditures.
GSPport/RDexp
Global start-up product portfolio per research expenditures
“SUturn” value per €10 million of research expenditures.
132
Set of indicators
GLOSSARY
Academic staff: the number of FTEs responsible for all teaching and research activities at the university.
They include the professors, associate professors, lecturers, tutors, researchers and other similar figures
involved in those activities.
Active patents: technically unique patents that are still property of the university (they have not expired,
been allowed to lapse or been sold). A technically unique patent means that multiple grants for the same
invention in different jurisdictions should be counted as just one grant.
Active start-up company: a company that possesses sufficient financial resources and expends these
resources to make progress toward stated business goals. The company must also be diligent in its efforts
to achieve these goals.
Administrative staff: professional position in either full or fractional FTEs whose duties includes the
execution of activities to support, assist or maintain the primary processes, such as human resources,
financial management, purchasing, etc.
Assistance programme: a university organisational structure, involving one or more units, which manages
and carries out activities to encourage and support academic entrepreneurship.
Cashed-in equity: This includes the amount received from cashing in equity holdings, resulting in a cash
transfer to the institution.
Equity: is defined as a university acquiring an ownership interest in a start-up company.
Executed license: The signed grant of rights that does not amount to an assignment by the university to
the licensee in the form of a contract that permits the licensee to exploit IP according to the contractual
terms and conditions.
FTE: Full time equivalent.
133
Set of indicators
Invention disclosure: written notification to the university, no matter how comprehensive, reporting that
an invention has been made. An invention is new and useful process, device, substance, method, article of
manufacture, or composition of matter, or new or useful improvement upon one of these.
IPO: Initial public offering.
License incomes: includes license issue fees, payments under options, annual minimums, running
royalties, termination payments, and software and biological material end-user license fees.
License/option agreement: A license is where the university grants rights to use the technology under
license in a defined field of use and territory. An option agreement grants the potential licensee a time
period during which it may evaluate the technology and negotiate the terms of a license agreement.
License/option agreement with equity: executed licenses /options that include equity, where equity is
defined as an institution acquiring an ownership interest in a company.
License incomes: includes licence issue fees, payments under options, lump sum payments in
consideration of an assignment, annual minimums, running royalties, termination payments, the amount of
equity received when cashed-in. Does not include research funding, patent expense reimbursement, a
valuation of equity not cashed-in, trademark licensing royalties from university insignia or income received
in support of costs incurred under material transfer agreements.
MBO: management buy-out.
New product introductions: products or services available to the end-user that are derived from licensed
or assigned technologies to start-up companies.
Patent applications: it refers to the applications for technically unique patents that have been filed by the
university in the year requested; does not include continuations, divisional, or reissues, continuations in
parts, etc. Plant breeders applications may also be included, as well as applications for certificates of plant
variety protection. Technically unique patent means that multiple applications for the same invention in
different jurisdictions should be counted as just one application.
134
Set of indicators
Patents granted: technically unique patents issued to the university, including plant breeder’s rights. A
technically unique patent means that multiple grants for the same invention in different jurisdictions should
be counted as just one grant.
Primary processes: a set of activities to encourage and/or support academic entrepreneurship, which will
produce the targeted results. These activities can be included in the following groups:
Marketing activities: The direct activities (e.g., seminars, workshops, website, diffusion of brochures,
business plan competitions, etc.) and indirect activities (proactive evaluation of university technologies,
etc.), and its development and management (e.g., marketing and promotion plan, management of
entrepreneurs’ database, etc.) addressed to the university community in order to promote the academic
entrepreneurship and make known the university services to support nascent entrepreneurs and new
firms.
Training activities: courses and similar activities addressed to nascent entrepreneurs in order to
develop the needed skills in the process of feasibility evaluation, starting up, and management of the
new firm.
Advice/mentoring activities: activities related to the counselling of nascent entrepreneurs, on a
regular basis, for the development of the business plan and/or the development of the new firms, as
well as those activities related to the management of the access to resources (financial, office/lab
space, training, IPR, etc.).
IPR-licensing activities: activities related to the management of the university IPR that will be use by
the new firms (management of agreements on licenses, options, etc.).
R+D expenditures: expenditures made by the university in support of its research activities that are
funded both by government, industrial, and foundation/endowment sources.
Research expenditures: government sources: These include expenditures made by the university
in support of its research activities that are funded by all government sources, including the federal
government, state government or local municipal authorities.
Research expenditures: industrial sources: These include expenditures made by the university in
support of its research activities that are funded by for profit corporations, but not expenditures
supported by other sources such as foundations and other non-profit organizations.
135
Set of indicators
Research expenditures: foundation/endowment: These include expenditures made by the
university in support of its research activities that are funded by sources such as foundations,
endowment and other non-profit organizations.
Scientific publications: academic publications that report original empirical and theoretical work in the
sciences and social sciences, including: articles published in scientific journals; authored books; chapters in
books; working papers, conference papers.
SCI-covered publications. Publications in journals covered in the Science Citation Index.
Seed capital available: an own or affiliated university seed/risk fund. An affiliated seed capital means a
fund without direct university financial resources, but the university has an agreement to use for spin-off
creation.
Start-up support expenditures: total amount of expenditures made by the university in support of
primary processes (activities related to encourage and/or support academic entrepreneurship, e.g.,
marketing and entrepreneur relationships management, identification-evaluation of business opportunities,
support services for entrepreneurs/new firms), as well as maintenance processes (activities to support,
assist or maintain the primary processes). It doesn’t include expenditures in the building of infrastructures
(incubators, office space, etc) or directly financial support for nascent entrepreneurs or new firms (seed
capital, loans, etc.).
Technical staff: professional position in either full or fractional FTEs whose duties include the development,
management or execution of primary processes (activities related to encourage and/or support academic
entrepreneurship, e.g., marketing and entrepreneur relationship management, identification-evaluation of
business opportunities, support services for entrepreneurs/new firms). These persons may or may not have
been located in a formally established a commercialisation office at that time.
136
Set of indicators
SURVEY QUESTIONNAIRE MODELS
A. Example of “Policies & Strategies” questionnaire items.
University board member
Manager of unit involved in start-up activity support
Staff involved in start-up activity support
Researcher/lecturer
Student/former student
Other…
Academic Entrepreneur
Non academic entrepreneur
Please indicate, in your opinion, the level of the following issues related to the university policies
and strategies to encourage and support the start up activity:
I strongly
disagree
N/A
I strongly
agree
The current university policies related to
academic entrepreneurship are properly
explicit.
The current university policies are contributing
properly to encourage/support start up activity.
Explicitness of the current defined
strategies related to academic
entrepreneurship.
The university has an optimal support structure
to encourage/ support start-up activity.
The university exploits optimally the
external resources to encourage/
support start-up activity.
Targets in my unit/department related to
encourage/support start-up activity are
properly explicit.
137
Set of indicators
B. Example of questionnaire items to measure intentions among academic staff
(adapted from Shapero and Krueger model).
1. Have you ever seriously thought about create a business to exploit your research results?
No, never.
Yes, we expect do it in the next year.
Yes, we expect do it in the next three years.
Yes, we expect do it in the next five years.
2. In a scale from 0 to 100, how desirable is for you to start your own business to exploit
research results?
Strongly not
desirable
0
10
20
30
40
50
60
70
80
90
100
Strongly
desirable
3. In a scale from 0 to 100, how feasible do you consider to start a business for exploiting
research results?
Strongly not
feasible
138
0
10
20
30
40
50
60
70
80
90
100
Strongly
feasible
Final remarks
5. FINAL REMARKS
The main goal of this study has been to make a review of the state of the art about the
monitoring of the academic entrepreneurship, as well as provide stakeholders on this issue with
a checklist of indicators useful as an orientation guide for developing performance measurement
systems or improving existing ones. Logically, this is not a novelty, since most universities have
developed their own measurement scales. Nevertheless, the approach of this study offers the
possibility of bring a broad view of the state of current issues regarding academic
entrepreneurship performance in universities. We think that the main usefulness of this
publication relies on providing stakeholders with information about the currently issues that are
taken into account as fundamental on behalf of institutions and researchers on academic
entrepreneurship.
In addition of being a useful tool to develop or improve performance measurement systems,
this publication can support universities and institutions to recognise and pay attention to the
university key factors that could be influencing the start-up birth rates and the derived wealth
creation, and in consequence, develop, implement and monitor initiatives to improve these
factors and the final impacts. In this sense, the approach of the resource- based view of this
study have revealed some insights about the cause-effect relationships among the resources
and capabilities of universities as predictors of start-up activity and wealth creation. In this
sense, the study identifies four groups of resources and capabilities: internal policies and
strategies of universities, which can promote or inhibit entrepreneurship; the stock of
technology, which determines the emergence of business opportunities; the resources and
initiatives directly arranged for business creation support; and the human capital, regarding the
number of potential academic entrepreneurs and their characteristics.
Nevertheless, we must highlight that all universities have not necessarily to centralise their
attention to all resources and capabilities. It is necessary that each university develop their own
strategic plans that include strategic objectives related to academic entrepreneurship and
deliberate on what must be their priorities in order to distribute financial and other kind of
resources. Entrepreneurial universities must be aware that there are different ways to achieve
the expected results.
139
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