Database Management Systems Ramakrishnan (Raghu Ramakrishnan)

1.2 CHAPTER STRUCTURE

The core elements of this chapter are as follows:

• Introduction
• Policy Conditions: Innovation and Entrepreneurship

◦ The Triple Helix
◦ Entrepreneurial Ecosystems
• Policy Outcomes and Impacts
• Future Trends
◦ Gig Economy
◦ Internet of Things
◦ Convergent Technology Spaces
◦ Crowdfunding
• Chapter Summary
• Case Study – Renishaw Diagnostics Ltd
• Revision Questions
• Further Reading and Resources
• Appendices 1.1 and 1.2
• References
• Glossary of Terms

1.3 INTRODUCTION

The global economy has seen significant changes
since the banking crisis in 2008 and this has shaped

the direction of many economies and societies over
the last decade. Economies have gone through large-
scale austerity programmes to reduce government
deficits. This has resulted in higher levels of
unemployment, less disposable personal income and
recession. National government efforts have been
focused on the implementation of austerity
programmes, and some have also put in place stimulus
initiatives designed to encourage growth and recovery.
Job creation is at the core of policy initiatives to
reduce unemployment levels and to generate new
sources of economic growth. As part of such
economic recovery efforts, governments have also
focused on growing the numbers of entrepreneurs and
new venture creation in their economies. Investment
in research and development (R&D) through publicly
funded sources combined with private-sector
investment is now seen as critical to maintaining
ongoing economic growth and stability. This
investment in public science and research excellence
is viewed as vital if economies are to sustain
economic activities and flourish in the twenty-first
century. This means that governments are now taking
a more targeted approach to such investment in public
science. Mission-orientated public research is
focusing on grand challenges such as climate change.
Different terms such as knowledge or smart
economies have been used to describe economies
where activity is centred on services, knowledge and
highly trained and talented workers, as well as in
developing young and embryonic sectors such as
biotechnology and artificial intelligence (AI). The
creation of new ventures and encouraging
entrepreneurship are vital for economies to grow and
create wealth. For this to happen, national
governments need to consider having favourable

economic and social conditions that enable those
considering technology entrepreneurship to do so.
Therefore, national policies help create environmental
conditions that support technology entrepreneurship
and provide potential investors with confidence in
terms of their investments. For technology
entrepreneurs in economies where there are ongoing
investments in technologies, R&D is critical if their
new ventures are to succeed in competitive
international markets. This now has even greater
importance as national economies recover from
Covid-19.

1.4 POLICY CONDITIONS:
INNOVATION AND
ENTREPRENEURSHIP

Innovation and entrepreneurship activities in an
economy have positive economic benefits, particularly
in employment, taxation revenue, economic output
and further investment in infrastructure. We are
experiencing a more rapid pace of scientific
development, further advances in information and
communication technologies (ICT) and a more
effective transition of research to the marketplace
(Cunningham, 2008). This is evident in significant
public and private investment in new technologies
such as Artificial Intelligence (AI). These and other
changes have influenced the nature of innovation and
entrepreneurship policies that national governments
adopt, as technology entrepreneurs are vital
contributors to wealth creation in economies (see Park
and Leydesdorff, 2010). Many policies adopted by
national governments have moved from industrial
policies through to science and now innovation
policies, which incorporate innovation and technology

entrepreneurship as well as other forms of
entrepreneurship. Dahlstrand and Stevenson (2007, p.
17) argue the need for holistic entrepreneurship policy
and that this “requires combination of
entrepreneurship, SME, innovation, science and
technology, education/ university and regional policies
… For example SME policies are often developed to
help existing small firms, while entrepreneurship
policies focus on individuals and their capacity (e.g.,
skills and motivation).”

1.4.1 The Triple Helix

One of the underpinning policy paradigms that have
informed national innovation and entrepreneurship
policies has been the triple helix approach
(Leydesdorff, 2000). This attempts to understand the
relationship and interaction between
universities/public research organisations (PROs),
industry and government and innovation (Godin,
2006). The dynamic interactions between these actors
represent the true nature of innovation systems
(Piekarski and Torkomian, 2005). Moreover, in this
approach the university is seen as an influencer and
actor in contributing to innovation and
entrepreneurship. So what are the roles of universities,
industry and government in the triple helix?

Universities: Universities have three core missions:
teaching, research and what is now termed
“technology and knowledge transfer” (see Chapter 3).
At the heart of university activities is scientific and
research excellence. These areas of excellence can be
complemented by technology and knowledge transfer
activities, which seek to take scientific discoveries
from research that is commercialised by industry.
Within universities technology transfer offices (TTOs)

play a key role in supporting the commercialisation of
research. Moreover, many universities have become
entrepreneurial universities, which Subotzky (1999)
describes as “characterised by closer university-
business partnerships, by greater faculty responsibility
for accessing external sources of funding, and by a
managerial ethos in institutional governance,
leadership and planning”. For universities to become
entrepreneurial universities, Guerrero et al. (2014, p.
43) maintain that “university authorities need to
recognise their core role at this time as not only
building but also enforcing the university
entrepreneurship ecosystem that nurtures
entrepreneurial potential (incentives, new learning
tools, role models) as well as stimulating skills,
competences and tools that are most useful, creating
entrepreneurial mindsets that drive innovation (not
only inside universities but also within the existent
firms) and becoming entrepreneurial organisations”.
Entrepreneurial universities do create an economic
impact in all their core missions (see Guerrero et al.,
2015) and do influence high-technology
entrepreneurship (Cunningham and Menter, 2020).
Universities are at the forefront of new technological
and scientific developments. Technological
entrepreneurs benefit from entrepreneurial universities
through access to talent, as well as research that can
be commercialised or incorporated into their product
or service. University-based technology entrepreneurs
can avail themselves of university-based supports to
create a new technology venture (see Dolan et al.,
2019). The intellectual and human capital generated
by universities can have a direct and indirect impact
on technology entrepreneurs. Etzkowitz and
Leydesdorff (1997) best sum this up as follows: “The
development of academic research capacities carries

within itself the seeds of future economic and social
development in the form of human capital, tacit
knowledge and intellectual property.”

Industry: Within the triple helix paradigm, industry
can benefit from university engagement through
exploiting research, hiring new talent and having
access to international research networks. Moreover,
industry can shape the research fields that national
governments prioritise that are aligned with their near-
or long-term business needs. In some economies,
governments have gone through a research
prioritisation exercise designed to align research with
industry needs so that they can compete more
effectively in international markets. For example, the
UK Government’s Industrial Strategy1 outlined
national priorities to support business. Similarly, the
Irish Government as a small, open economy has also
undertaken a research prioritisation exercise (DBEI,
2018).

R&D activities of large corporates support the
development of a sector or cluster of activities within
an economy. For example, Galway, a city in the west
of Ireland, is the fourth sub-critical location in the
world for manufacturing of medical devices and an
international cluster has developed over the last
decade in medical technologies (see Cunningham et
al., 2015; Evers and Giblin, 2017; Giblin and Ryan,
2012). Local third-level institutions have supported
the growth of this sector in the western region of
Ireland through new programmes, establishment of
international research programmes and recruitment of
faculty. Also industry, through its interaction with
national and local governments, puts pressure on these
bodies to ensure that they create environmental –
economic, social and educational – conditions to

enhance a firm’s competitive positioning in
international markets. For example, in the UK, the
British Chamber of Commerce represents over 75,000
businesses across over 53 local chambers and runs
campaigns on issues of importance and relevance to
UK businesses such as Brexit and digital capabilities.
For technology entrepreneurs and new business
creations, creating such an environment is vital to
their growth and survival.

Another role that industry plays is as co-investor in
research within universities and PROs. Increasingly,
funding agencies are requiring research projects to
have industry partners and some require financial
investment along with in-kind support. An example of
such a scheme is the Knowledge Transfer Partnership
in the UK (Innovate UK, 2015), where an industrial
partner collaborates with researchers and a graduate to
support its business growth and development (Jones
and Coates, 2020).

Government: National governments, in terms of
their economic and social policies, create the
environmental conditions that make it attractive for
new venture creation, for entrepreneurs and for
supporting services, such as venture capitalists, to
invest capital in the most efficient way possible.
Mowery et al. (2004) argue that this is pivotal in
supporting innovation and entrepreneurship, and
Etzkowitz (2002) suggests that the role of government
is expanding not only in relation to macro factors, but
increasingly to encompass the micro conditions of
innovation. Corporate and personal taxation, levels of
government administration, house prices, provision of
suitable office locations, public investment in
education, access to transport linkages and a myriad
of other macro and micro factors create these general
environmental conditions.

The education system contributes to the
development of human capital and talent within an
economy. One policy area that contributes to the
development of technology entrepreneurship is
educational policy, with national curriculums usually
set by national governments. For example, the
Organisation for Economic Co-operation and
Development (OECD) conducts analyses of school
systems, collating data from 72 countries through the
Programme for International Student Assessment
(PISA). The 2015 PISA survey ranked Singapore as
number one in its evaluation of school systems. To
ensure an adequate supply of human capital and
talent, governments are investing more national
resources in STEM skills (in science, technology,
engineering and maths) that support technology
entrepreneurship. For example, in the UK the House
of Commons Public Accounts Committee (2019)
noted the challenges facing its economy as follows:
“STEM skills are crucial for the UK’s productivity,
and a shortage of STEM skills in the workforce is one
of our key economic problems. The future workforce
relies on many more children and young people being
encouraged to take STEM subjects and enter STEM
careers.”

Another role that governments play within the
triple helix is via public investment in research –
through public research laboratories and higher
education institutions. This public funding supports
infrastructure, basic and applied research and human
capital and talent development. In 2019, France
launched multi-annual, multi-research agency
research programmes to support publicly funded
research and early career researchers and scientists
(Casassus, 2019). For governments, the level of
entrepreneurship and new business creation is one of

the measures of economic vibrancy. The World Bank
(2013) notes: “Entrepreneurial activity is a pillar of
economic growth. For evidence of the economic
power of entrepreneurship, we need look no further
than the United States, where young firms have been
shown to be a more important source of net job
creation than incumbent firms.” Data from the World
Bank in 2016 found there were 144,883 new limited
company formations in Hong Kong SAR, China;
246,623 in Australia; 109,974 in Chile; 93,714 in
India; 96,155 in South Korea; 13,590 in Finland; and
663,616 in the UK.

1.4.2 Entrepreneurial Ecosystems

Another perspective that is growing among policy-
makers and industrialists is the concept of
entrepreneurial ecosystems in order to create the
optimal policy and environmental conditions for
technology entrepreneurship to flourish. Audretsch et
al. (2019, p. 313) note “the rise of ‘entrepreneurial
ecosystems’ as organised attempts to establish
environments that are conducive to increasing the
success for newly established ventures”. According to
Spigel (2017), entrepreneurial ecosystems are
“combinations of social, political, economic, and
cultural elements within a region that support the
development and growth of innovative startups and
encourage nascent entrepreneurs and other actors to
take the risks of starting, funding, and otherwise
assisting high-risk ventures”. Entrepreneurial
ecosystem elements are configured with respect to
systemic and framework conditions (Stam, 2015).
Systemic conditions consist of networks, leadership,
finance, talent, knowledge and support
services/intermediaries. Formal institutions, culture,

physical infrastructure and demand constitute the
framework conditions of entrepreneurial ecosystems.
According to Isenberg (2011), an entrepreneurial
system consist of six domains that interact, namely
policy, finance, culture, supports, human capital and
markets.

In relation to policy, the government’s roles is
providing supportive incentives, institutions and
regulatory environments that support
entrepreneurship. Silicon Valley in the United States,
Oxford in the UK and Waterloo in Canada have been
cited as examples of supportive and effective
entrepreneurial ecosystems (see Stam and Spigel,
2016; Spigel, 2017; Mason and Brown, 2014). Such
entrepreneurial ecosystems emerge in geographical
locations that have some particular distinctive assets,
where there are established firms, multinational
companies (MNCs) or subsidiaries, that have
production and R&D activities and that are embedded
in the local environment (see Mason and Brown,
2014). Cantner et al. (2020) posits a dynamic model
of entrepreneurial ecosystems that encompasses
entrepreneurship and intrapreneurship. At the micro
level – that is, the individual level – scientists in
principal investigator roles have to manage the
governance of entrepreneurial ecosystems with other
stakeholders in order to realise economic and societal
impacts (see Cunningham et al., 2019; see also Case
Box 1.1). For policy-makers, whatever perspective
they take there is a need for their policy interventions
and instruments to align with the actual needs of
technology entrepreneurship and their environment
(see Brown and Mason, 2014).

CASE BOX 1.1 REALISING
ENTREPRENEURIAL ECOSYSTEM IMPACT:
A PRINCIPAL INVESTIGATOR
ENTREPRENEURIAL ECOSYSTEM
GOVERNANCE FRAMEWORK

Cunningham, J.A., Menter, M. and Wirsching, K. (2019)
Entrepreneurial ecosystem governance: A principal investigator-
centered governance framework. Small Business Economics,
52(2): 545–562.

1.5 POLICY OUTCOMES AND IMPACTS

One of the greatest challenges for governments and
policy-makers is to evaluate whether their policy
interventions support technology entrepreneurship.

Many public and private organisations are involved in
the collection and analysis of data on
entrepreneurship, technology entrepreneurship and
factors that create the conditions for such activity to
grow. This data is used for international comparative
purposes to assess the policy effectiveness and
environmental conditions for entrepreneurship and
innovation that contribute to technology
entrepreneurship activities and outcomes. National
governments use this comparative data to evaluate
their national performance across a number of
dimensions. International comparison studies
highlight the difference between countries in relation
to entrepreneurship and technology entrepreneurship.
New venture creation is viewed as a measure of the
entrepreneurial vibrancy in an economy. For example,
it highlights the patterns of new venture creations
across major economies (see Figure 1.1).

One of the challenges that technology
entrepreneurs face along with other categories of
entrepreneurship is access to finance during venture
creation. Technology entrepreneurs typically seek
venture capital funding to support the initial stages of
their new venture creation. OECD data highlights
venture capital investment patterns and differences
between countries (see Figure 1.2).

Technology entrepreneurship in Europe is lagging
behind other major world economies (see Figure 1.3),
as Van Roy and Nepelski (2017, p. 3) note: “Europe’s
weak innovation performance is rooted in its
specialisation in low and medium-tech sectors. High-
tech entrepreneurship is one of the vehicles through
which scientific results are converted into economic
benefits. However, current policy support does not
seem to recognise the transformative role of high-tech

entrepreneurship.” In essence, this suggests a policy
gap in supporting technology entrepreneurship.

Figure 1.1 OECD new enterprise creations
Source: OECD.Stat (2019) Accessed 25 July 2019
https://stats.oecd.org/index.aspx?queryid=74181.
Note: OECD venture capital investment data for other countries is
available to access via the companion website:
www.macmillanihe.com/companion/Evers-Technology-
Entrepreneurship-2e
Countries available are Australia, Austria, Belgium, Canada,
Switzerland, Czech Republic, Germany, Denmark, Spain,
Estonia, Finland, France, Greece, Hungary, Ireland, Israel, Italy,
Lithuania, Luxzembourg, Latvia, Netherlands, Norway, Poland,
Portugal, Romania, Slovak Republic and Slovenia.

Figure 1.2 OECD venture capital investment 2019

OECD.Stat (2019) Accessed 25 July
https://stats.oecd.org/index.aspx?queryid=74181.

Note: OECD new enterprise creations data relating to Iceland,
New Zealand and Russia has been removed from this graph for
accessibility purposes. Please find the unabridged graph
available to access via the companion website:
ww.macmillanihe.com/companion/Evers-Technology-
Entrepreneurship-2e

Figure 1.3 High technology in Europe
Source: Van Roy, V. and Nepelski, D. (2017) Determinant of high-
tech entrepreneurship in Europe, Joint Research Centre, JRC
Scientific and Policy Reports – EUR 28299 EN;
doi:10.2791.96153. ©EU Commission.

The policy challenge is best summed up by
Lundström et al. (2008, p. 24): “One of the challenges
for Governments is to determine what actions or
combination of actions will most appropriately
address the salient direct and indirect barriers to
achieving higher levels of entrepreneurship and/or
innovation, given their idiosyncratic set of country
contextual and structural circumstances.” From a
political perspective, maintaining a high level of
tailored policy support for technology
entrepreneurship can be difficult for governments to
justify to citizens when there are cut-backs to other

government-funded services such as social welfare,
health, policing and education. Moreover, technology
entrepreneurship requires even more specific policy
instruments and incentives as this type of
entrepreneurship is more affected by economic
conditions, and needs funding and a regulatory
environment that is progressive (see Van Roy and
Nepelski, 2017, p. 3).

Given the importance of innovation and
entrepreneurship to the European Union (EU), each
year the Innovation Union Scoreboard is published,
which details the innovation leaders, followers,
moderate innovators and modest innovators in Europe
(see Table 1.1 for the 2019 Innovation Union
Scoreboard). The Innovation Union Scoreboard uses a
range of indicators in a national economy in relation
to research and innovation performance for the 28
member states, as well as comparing the EU 28 with
other major economies (see Appendix 1.1 for full
range of indicators). Innovation indicators are
presented per member state as well as an analysis of
their strengths and weaknesses (see Appendix 1.2 for
a country profile of Sweden). The Innovation Union
Scoreboard 2019 reveals Sweden as the leading
innovation performer. In looking at future
performances, the European Innovation Scorecard
(2019, p. 38) concluded: “In summary, the analysis
suggest that EU performance will continue to increase
for most indicators, leading to an overall EU
innovation performance compared to 2011 from 109
in 2018 to 11 in two years’ time.”

Figure 1.4 European Innovation Scorecard 2019 global
performance
Source: European Union (2019) European Innovation Scoreboard
2019, © European Union 2019, p. 6.

Table 1.1 Summary Innovation Union Scoreboard 2019

Innovation Leaders: Sweden, Finland, the Netherlands
Strong Followers: Austria, Belgium, Estonia, France, Germany,
Ireland and Luxembourg

Moderate Innovators: Croatia, Cyprus, Czechia, Greece,
Hungary, Italy, Latvia, Lithuania, Malta, Poland, Portugal,
Slovakia, Slovenia and Spain
Modest Innovators: Bulgaria and Romania

Source: European Union (2019) European Innovation Scoreboard
2019, © European Union 2019.

The European Commission has also undertaken
further analysis as part of the European Innovation
Scorecard in relation to the EU 28’s performance
against other major economies. Applying the same
measurements as outlined in Appendix 1.1 to these
economies, this analysis reveals that the EU is ahead
of the United States and China in terms of innovation
performance. The European Innovation Scorecard

(2019, p. 6) concludes that “At the global level, the
EU continues to lag behind South Korea, Canada,
Australia, Japan, but compared to last year, it has
overtaken the United States. Relative to Japan and
South Korea, the EU has been falling behind, and the
performance gap is expected to further increase in the
coming years.”

Such analysis has focused on high-growth small to
medium enterprises (SMEs), new venture creation,
conditions for business R&D, knowledge-intensive
services (KIS) and economic competitiveness. Some
interesting data from the Innovation Union
Competitiveness Report 2011 is emerging about new
business creation. In essence, there is a steady pattern
of new business creation across the EU, but lower
than the US figures that have higher numbers of new
venture creations in the high-tech sector (see Figure
1.2).

1.6 FUTURE TRENDS

As we can see from previous sections, creating the
appropriate economic conditions and policy initiatives
to encourage technology entrepreneurship is vital. The
global economic crisis that began in 2008 has
fundamentally challenged old business models and
paradigms and has opened up new opportunities for
technology entrepreneurs. There are many trends that
we could look at here, but we have decided to focus
on four that we believe will influence technology
entrepreneurship. These future trends are enabled by
open innovation models of innovation and
collaboration and have gained momentum in many
sectors.

1.6.1 Gig Economy

The rise of the gig economy has created opportunities
for workers and those seeking entrepreneurial
opportunities or self-employment without the
associated entrepreneurial risk. It provides flexibility
for individual workers in relation to their participation
and reward from that participation in the gig economy.
Gig platforms provide opportunities for easy
participation for workers, suppliers and customers.
Some examples include private home rental platform
onefinestay, construction equipment rental
marketplace Tool Locker, same-day tradesperson
platform TaskRabbit, delivery network Dolly and tech
support company HelloTech. The OECD (2017, p. 2)
notes “some evidence suggesting that the gig
economy may sometimes decrease entrepreneurial
activity, in particular when gig economy platforms act
as a substitute for low quality entrepreneurship rather
than as a complement to high-quality
entrepreneurship”. For technology entrepreneurs the
gig economy provides significant opportunities to
scale their new venture quickly using appropriate
technologies and business models. GEM (2019)
describes the growth as follows: “The rise of the gig
and sharing economy worldwide led 27 GEM teams to
include questions on this topic in their 2018 survey.
The highest rate of involvement in such activities by
far is in the Republic of Korea (over 20 per cent of the
adult population).” In the UK, the Department for
Business, Energy and Industrial Strategy (2018, pp. 5–
6) reported that over 2.8 million had worked in the gig
economy, and that they were younger and had similar
educational attainment to the general population of the
UK. Moreover, it found that the highest subsector
within the gig economy was courier services and that
individual earning from the gig economy was low,
with mean income estimated as £5,634.

1.6.2 Internet of Things

The Internet of Things (IoT) is embedding sensor
technology in devices that can then be connected. As
Saarikko et al. (2017) note, “Connected devices and
products offer new possibilities for everything from
preemptive maintenance to new services and business
models. The IoT is not a homogenous concept or
paradigm, but rather a buffet of possibilities from
which each actor can peruse and assemble an
approach that is right for their strategic interests and
business requirements.” McKinsey (2015) estimates
the potential economic impact of IoT by 2025 to be
$11.1 trillion in nine settings – homes, offices,
factories, retail environments, worksites, human,
outside, cities and vehicles; and the type of market
opportunities will focus on business models and
transforming business processes. Some of the
challenges facing EU technology entrepreneurs in
exploiting IoT centre on knowledge and getting ideas
to the market. IoT also opens up opportunities for the
creation of unicorns – ventures with a market
valuation of greater than $1 billion (see Cunningham
and Whalley, 2020), with IT technologies contributing
to entrepreneurial and innovative unicorns (see Skog
et al., 2016). According to CB Insights (2019),
European unicorns accounted for 11 per cent of global
unicorns and these include such firms as data centre
operator Global Switch, used-car platform Auto1
Group and prosthetics manufacturer Ottobock
Healthcare. IoT provides many market opportunities
for technology entrepreneurs.

1.6.3 Convergent Technology Spaces

With rapid advances in many scientific fields, as
established companies collaborate and co-invest in

R&D outside their traditional areas of activity,
supported by public research and infrastructure, they
are presented with new market opportunities.
Governments are prioritising public research through
public research programmes that are designed to
support cross-sector collaborations. This might be, for
example, an energy company and an ICT company
collaborating to bring to the market new devices that
monitor energy consumption. It might be a medical
device company collaborating with a software
company and other healthcare stakeholders and
insurers in developing services that monitor patient
health and dynamically based insurance products
based on data monitoring. In essence, different
companies from different sectors converge on a
common problem, seek ways to address it and develop
an appropriate business model that shares the risk,
cost and returns. In April 2013, then US President
Obama launched the BRAIN Initiative (Brain
Research through Advancing Innovative
Neurotechnologies), which is a focused large-scale
basic research effort on understanding the human
mind, which will present new opportunities to treat
and prevent diseases such as Alzheimer’s,
schizophrenia, autism and epilepsy. Obama (2013)
outlined it as follows: “Imagine if someone with a
prosthetic limb can now play the piano or throw a
baseball as well as anybody else, because the wiring
from the brain to that prosthetic is direct and triggered
by what’s already happening in the patient’s mind.
What if computers could respond to our thoughts or
our language barriers could come tumbling down? Or
if millions of Americans were suddenly finding new
jobs in these fields – jobs we haven’t even dreamt up
yet – because we chose to invest in this project?” Such
an initiative opens up significant technology-

convergent opportunities and opportunities for
technology entrepreneurs working in this field.
Another example, IBM’s Smarter Cities Challenge,
seeks to use existing and new data in ways that
improve city life and contribute to the growth of
cities. This has meant that IBM increased its service
offerings in public safety, energy and water, planning,
environment, health and public administration, and
has opened up more opportunities for new services
and collaborations.

1.6.4 Crowdfunding

One of the ongoing barriers to technology
entrepreneurship is access to finance. For technology
companies, access to early seed, high-risk capital can
be even more difficult and has become even more
challenging to secure in order to scale their
businesses. This has led to the development of
different investment models where, in essence,
investors come together in an organised manner to
provide financial support to early-stage companies,
social entrepreneurs and other categories of
entrepreneurs. Specific funds have been set up around
this crowdsourcing concept. Online crowdfunding
platforms such as crowdcube.com, kickstarter.com
and syndicateroom.com enable technology
entrepreneurs to pitch their venture ideas to investors
through a crowdfunding model, and such platforms
have different value propositions for entrepreneurs
and investors.

1.7 CHAPTER SUMMARY

We began the chapter by considering the role of
government, industry and universities as part of the
triple helix and entrepreneurial ecosystem approaches
to supporting technology entrepreneurship. While
there is a paucity of specific data focusing on
technology entrepreneurship, our review of policy
outcomes and impacts among EU member states and
international comparisons shows the performance
differences and patterns of entrepreneurship and
innovation that contribute to technology
entrepreneurship. The chapter concluded with a
review of four future trends that will impact on
technology entrepreneurs – gig economy, the Internet
of Things, convergent technology spaces and
crowdfunding. Case Study 1.1 offers an example of a
start-up that benefited from the tripe helix approach.

CASE STUDY 1.1 RENISHAW
DIAGNOSTICS LTD

Case written by Dr Grace Walsh, Whitaker Institute, NUI
Galway.

Inception

In May 2007, Scotland’s Strathclyde University launched D3
Technologies Ltd to develop diagnostic tests and examinations
that indicate a genetic predisposition to disease faster than
existing technologies. D3 Technologies was formed by
academics Ewen Smith, Duncan Graham and Karen Faulds,
from the university’s chemistry department, and life sciences
entrepreneur Jim Reid. The firm’s goal was “to exploit certain
patents related to Surface Enhanced Raman Spectroscopy
(SERS) and to develop SERS for molecular diagnostics and
trace detection” (www.renishaw.com, 1). The funding for this
new venture was obtained from Renishaw PLC, a UK-based
developer of high-tech measurement systems and a FTSE-250
firm. In addition to providing finance, Renishaw collaborated

with Strathclyde researchers on developing and
commercialising the diagnostic tools (www.scotsman.com). The
investment deal, one of the Glasgow-based institution’s biggest
ever spin-out deals, occurred in the form of £1.85 million in
monetary assistance and also instrumentation support with a
combined value of £5 million over five years, for which
Renishaw received a 75 per cent stake in the spin-out. Part of
the investment was also used by D3 Technologies to purchase
the business and assets of the analytical business unit (ABU)
operated by Mesophotonics Ltd, a spin-out company of the
University of Southampton, for £850,000. Renishaw, already a
leading supplier of Raman instrumentation, has a vested
interest in the progression of Raman spectroscopy and its
application in new and developing markets
(www.renishaw.com, 1).

Development

The merging of D3 Technologies and the Mesophotonics ABU
has resulted in a combination of complementary products and
this, in addition to the investment and mentoring by Renishaw,
has given the company “the platform to develop new-
generation products that give the potential to revolutionise
medical and genetic testing”, according to Dr David McBeth,
Strathclyde’s Director of Research and Innovation
(www.scotsman.com). In January 2008, D3 Technologies was
awarded a Strathclyde Enterprise Award, an award aimed at
giving recognition to some of Scotland’s most inventive
businesses that have been supported by the university’s
enterprise network (www.renishaw.com, 2). Another honour
was bestowed on D3 Technologies in 2009 when the firm was
shortlisted for the Scottish Enterprise Life Sciences Award
(www.renishaw.com, 3). D3 Technologies’ university roots
remained strong throughout the development of the firm, with
the founding professors staying directors of the firm to the date
of writing (March 2013), and the firm’s strong R&D focus
continues to be a positive asset. In 2009 ITI Techmedia, part of
an organisation that supports economic growth through market-
driven R&D programmes, invested £7.9 million in a three-and-
a-half-year R&D programme, and D3 Technologies was one of
a small number of R&D providers (www.innovationuk.org). The
programme was funded with public finance, led by academics
from multiple UK universities and conducted in conjunction with
numerous industry partners, of which D3 Technologies was one
(IWJ editor, 2009). This highlights the strength of the triple helix
and the lack of barriers to information flow between industry,
academia and government organisations.

Realisation

In February 2010 the firm’s CEO, Professor Ewen Smith, stood
down to focus on a new portfolio of products for the firm, and
David Burns was appointed CEO. Shortly afterwards the
company’s name changed from D3 Technologies Ltd to
Renishaw Diagnostics Ltd (www.renishaw.com, 4). The
investments of the previous years paid off in February 2011
when Renishaw Diagnostics launched its first major product,
the RenDx™ research-use-only multiplex assay system, which
provided a marked improvement on existing screening methods
(www.renishaw.com, 5). Shortly afterwards, in May 2011, the
firm signed an exclusive licensing agreement for a patent on
nucleic acid sequence identification (SERS beacons) from the
University of Strathclyde, in a move that Professor Duncan
Graham called “another excellent example of technology
transfer”. According to Renishaw Diagnostics’ CEO, David
Burns, “the licensing of this patent will enhance our existing
patent portfolio and allow us to develop new format molecular
diagnostics assays in additional disease areas”. However, the
collaboration signalled more than a mere licensing deal: David
McBeth believed it signified a further strengthening of the
university’s relationship with Renishaw Diagnostics, and it was
his hope that the licence would underpin the company’s growth
and that this in turn would create more highly skilled jobs in the
West of Scotland. Furthermore, McBeth saw this as the
beginning of a long and symbiotic relationship, as he expected
that they would develop several other research and knowledge
exchange collaborations with Renishaw Diagnostics in the
future (www.renishaw.com, 6).

Relationship

A key component of the success of this venture stems from the
strong and overlapping relationship between the spin-out firm
and the University of Strathclyde. Not only did Renishaw
Diagnostics remain in contact with the university, but the firm’s
founding academics continued on as directors, in addition to
keeping their affiliation with the university. Furthermore, the
firm’s successes were recognised, supported and promoted by
governing bodies through both awards and funding. The
collaboration and alignment of the three resources of business,
academia and government for the goal of sustainable economic
success represents the triple helix of innovation. In recent
decades universities have been becoming increasingly involved
in the formation of firms resulting from academic research, and
this has cemented their role in the triple helix of innovation
alongside industry and government (Etzkowitz, 2003). In the
case of Renishaw Diagnostics, the supports of the triple helix
relationship allowed the firm to develop and grow its R&D
without the immediate pressure of returning a profit. Renishaw
Diagnostics had been almost four years in existence before its

first major product was launched, thus it needed this type of
environment for it to become a success. In 2016, Renishaw
made the decision to close its diagnostic unit with a loss of 33
jobs, and the BBC (2016) reported that this “followed ‘an
extensive’ review of the business. Renishaw said it had tried to
find a collaboration or acquisition partner for the diagnostic unit
but had not received any acceptable offers.”

CASE STUDY QUESTIONS

1. How did the triple helix influence and shape the development
of Renishaw Diagnostics?

2. Discuss how entrepreneurial ecosystems supported the
growth and development of Renishaw Diagnostics.

3. Discuss how convergent technology space opportunities,
crowdfunding, the Internet of Things or the gig economy could
have been applied to Renishaw Diagnostics to potentially
have made it more attractive to new collaborators or
acquirers.

CASE STUDY REFERENCES

BBC (2016) Engineering Firm Renishaw to Shut Glasgow Diagnostics
Unit. BBC News, 13 October. www.bbc.co.uk/news/uk-scotland-
scotland-business-37642473 (accessed 1 July 2019).

Etzkowitz, H. (2003) Innovation in Innovation: The Triple Helix of
University-Industry-Government Relations. Social Science
Information, 42(3): 293–337.

Innovation UK website, Accessed online on 13 March 2013 at
www.innovationuk.org/news/innovation-uk-vol4-1/0147-iti-
scotland.html.

IWJ editor (2009) News and Views. International Wound Journal, 6(4):
250–257. DOI: 10.1111/j.1742-481X.2009.00617.x.

Newsweaver website, Accessed online on 11 March 2013 at
www.archive.newsweaver.com/lifesciences/newsweaver.co.uk/lifesci
ences/e_article00100654364e4.html?x=b11,0,w.

Renishaw website, 1, Accessed online on 11 March 2013 at
www.renishaw.com/en/renishaw-invests-in-d3-technologies-limited-
8041.

Renishaw website, 2, Accessed online on 12 March 2013 at
www.renishaw.com/en/scottish-business-award-for-spectroscopy-
expert-9265.

Renishaw website, 3, Accessed online on 12 March 2013 at
www.renishaw.com/en/10571.aspx.

Renishaw website, 4, Accessed online on 12 March 2013 at
www.renishawdiagnostics.com/en/ground-breaking-molecular-
diagnostics-business-appoints-new-ceo-12539.

Renishaw website, 5, Accessed online on 13 March 2013 at
www.renishawdiagnostics.com/en/renishaw-diagnostics-enables-
customised-multiplex-assays-for-precious-research-samples – 14576.

Renishaw website, 6, Accessed online on 13 March 2013 at
www.renishawdiagnostics.com/en/renishaw-diagnostics-signs-
exclusive-licence-agreement-for-serrs-beacons-with-the-university-
of-strathclyde-14981.

Scotsman website, Accessed online on 11 March 2013 at
www.scotsman.com/business/industry/strathclyde-university-in-163-
5m-spin-out-deal-1-908461.

1.8 REVISION QUESTIONS

1. Discuss how innovation and entrepreneurship policy impacts
on technology entrepreneurs.

2. Outline the triple helix model and discuss the roles of the key
actors in this model.

3. Take an entrepreneurial ecosystem that you are familiar with
and map out the key elements. Discuss how resilient and
robust this entrepreneurship ecosystem is and how it
supports technology entrepreneurship.

4. From your assessment of the European Innovation
Scorecard, what are the implications for technology
entrepreneurs?

5. Discuss how future trends will impact on technology
entrepreneurs and new venture formations.

1.9 FURTHER READING AND
RESOURCES

• For detailed EU data on investments in

innovation, a good source is the Eurostat
PocketBook published annually on Science,
Technology and Innovation in Europe.

• Excellent data, reports and perspective are

available on the Global Entrepreneurship
Monitor website (www.gemconsortium.org/).

• To track unicorns, see CB Insights:

www.cbinsights.com/research-unicorn-
companies.

• For discussion of entrepreneurial universities,

see Guerrero, M., Urbano, D., Cunningham, J.
and Organ, D. (2014) Entrepreneurial
Universities in Two European Regions: A Case
Study Comparison. Journal of Technology
Transfer, 29(3): 415–434.

• For a comprehensive overview of business

failure, see Walsh, G.S. and Cunningham, J.A.
(2016) Business Failure and Entrepreneurship:
Emergence, Evolution and Future Research.
Foundations and Trends” in Entrepreneurship,
12(3): 163–285.

APPENDIX 1.1 EUROPEAN UNION
(2013) INNOVATION
UNION SCOREBOARD
INDICATOR

Indicator Definition Definition Most recent year for
numerator denominator which data are
Source Source available
Interpretation

1.1.1 New Number of Population 2017
doctorate graduates doctorate between and
per 1,000 graduates including 25 The indicator is a
population aged and 34 years measure of the
25–34 supply of new
Eurostat second-stage
tertiary graduates in
all fields of training
(ISCED 8). For most
countries, ISCED 8
captures PhD
graduates.

1.1.2 Percentage Number of Population 2018
population aged persons in age between and
25–34 having class with some including 25 This is a general
completed tertiary form of post- and 34 years indicator of the
education secondary supply of advanced

education Eurostat skills. It is not limited
Eurostat to science and
technical fields,
because the
adoption of
innovations in many
areas, in particular
in the service
sectors, depends on
a wide range of
skills. The indicator
focuses on a
younger age cohort
of the population,
aged 25–34, and
will therefore easily
and quickly reflect
changes in
educational policies
leading to more
tertiary graduates

1.1.3 Lifelong The target Total 2017
learning population for population of
lifelong learning the same Lifelong learning
1.2.1 International statistics refers age group, encompasses all
scientific co- to all persons in excluding purposeful learning
private those who activity, whether
households aged did not formal, non-formal
between 25 and answer the or informal,
64 years. The question undertaken on an
information concerning ongoing basis with
collected relates participation the aim of improving
to all education in (formal knowledge, skills
or training, and non- and competence.
whether or not formal) The intention or aim
relevant to the education to learn is the critical
respondent’s and training point that
current or distinguishes these
possible future Eurostat activities from non-
job. Data are learning activities,
collected through such as cultural or
the EU Labour sporting activities
Force Survey
(LFS)

Eurostat Total 2018
population
Number of
scientific

publications per publications with Eurostat International
million population at least one co- scientific co-
author based publications are a
abroad (where proxy for the quality
abroad is non- of scientific research
EU for the EU28) as collaboration
increases scientific
Scopusa productivity

1.2.2 Scientific Number of Total number 2016
publications among scientific of scientific
the top-10 per cent publications publications The indicator is a
most cited among the top- Scopusa measure for the
publications 10 per cent most efficiency of the
worldwide as cited publications research system, as
percentage of total worldwide highly cited
scientific publications are
publications of the Scopusa assumed to be of
country higher quality. There
could be a bias
towards small or
English-speaking
countries given the
coverage of Scopus’
publication data

1.2.3 Foreign Number of Total number 2017
doctorate students doctorate of doctorate
as a percentage of students from students The share of foreign
all doctorate foreign countries doctorate students
students Eurostat reflects the mobility
Eurostat of students as an
effective way of
diffusing knowledge.
Attracting high-
skilled foreign
doctorate students
will secure a
continuous supply of
researchers

1.3.1 Broadband Number of All 2018
penetration enterprises with enterprises
a maximum Realising Europe’s
contracted Eurostat, full e-potential
download speed Community depends on creating
of the fastest Survey of the conditions for
fixed internet ICT Usage electronic
connection of at and E- commerce and the
least 100 Mb/s Internet to flourish.

Eurostat, commerce in This indicator
Community Enterprises captures the relative
Survey of ICT use of this e-
Usage and E- potential by the
commerce in share of enterprises
Enterprises that have access to
fast broadband

1.3.2 Opportunity- This index is 2018
driven calculated as the
entrepreneurship ratio between the Data from GEM
(Motivational index) share of persons distinguish between
involved in two types of
improvement- entrepreneurship:
driven (1) improvement-
entrepreneurship driven
and the share of entrepreneurship
persons involved and (2) necessity-
in necessity- driven
driven entrepreneurship.
entrepreneurship The first includes
persons involved in
Global TEA (Total Early-
Entrepreneurship Stage
Monitor (GEM) Entrepreneurial
Activity) who (i)
Comment: claim to be driven
Three-year by opportunity as
averages have opposed to finding
been used no other option for
work; and (ii) who
indicate the main
driver for being
involved in this
opportunity is being
independent or
increasing their
income, rather than
just maintaining
their income; the
second includes
persons involved in
TEA who are
involved in
entrepreneurship
because they had
no other option for
work

Countries with high

2.1.1 R&D All R&D Gross relative prevalence
expenditure in the expenditures in domestic of improvement-
public sector the government product driven opportunity
(percentage of sector entrepreneurship
GDP) (GOVERD) and Eurostat appear to be
the higher primarily innovation-
education sector driven countries. In
(HERD) these countries,
Eurostat opportunities may
be expected to be
more abundant, and
individuals may
have more
alternatives to make
a living

GEM has
constructed the
Motivational index to
measure the relative
degree of
improvement-driven
entrepreneurship

2017

Research and
development (R&D)
expenditure
represents one of
the major drivers of
economic growth in
a knowledge-based
economy. As such,
trends in the R&D
expenditure
indicator provide
key indications of
the future
competitiveness and
wealth of the EU.
R&D spending is
essential for making
the transition to a
knowledge-based
economy as well as
for improving
production
technologies and
stimulating growth

2.1.2 Venture Venture capital Gross 2018
capital (percentage expenditures is domestic
of GDP) defined as product The amount of
private equity venture capital is a
being raised for Eurostat proxy for the relative
investment in dynamism of new
companies. business creation.
Management For enterprises
buyouts, using or developing
management new (risky)
buy-ins and technologies,
venture purchase venture capital is
of quoted shares often the only
are excluded. available means of
Venture capital financing their
includes early (expanding)
stage (seed + business
start-up) and
expansion and 2017
replacement
capital Invest The indicator
Europe captures the formal
Comment: creation of new
Three-year knowledge within
averages have firms. It is
been used particularly
important in the
2.2.1 R&D All R&D Gross science-based
expenditure in the expenditures in Domestic sectors
business sector the business Product (pharmaceuticals,
(percentage of sector (BERD) chemicals and some
GDP) Eurostat areas of electronics)
Eurostat where most new
knowledge is
2.2.2 Non-R&D Sum of total Total created in or near
innovation innovation turnover for R&D laboratories
expenditures expenditure for all
2016

This indicator

(percentage of enterprises, enterprises measures non-R&D
turnover) excluding innovation
intramural and Eurostat, expenditure as a
extramural R&D Community percentage of total
expenditures Innovation turnover. Several of
Survey the components of
Eurostat, innovation
Community expenditure, such
Innovation as investment in
Survey equipment and
machinery and the
acquisition of
patents and
licences, measure
the diffusion of new
production
technology and
ideas

2.2.3 Enterprises Number of All 2018
providing training to enterprises that enterprises
develop or upgrade provided any ICT skills are
ICT skills of their type of training to Eurostat, particularly
personnel develop ICT Community important for
related skills of Survey of innovation in an
their personnel ICT Usage increasingly digital
and E- economy. The share
Eurostat, commerce in of enterprises
Community Enterprises providing training in
Survey of ICT that respect is a
Usage and E- proxy for the overall
commerce in skills development
Enterprises of employees

3.1.1 SMEs Number of small Total number 2016
introducing product and medium- of small and
or process sized enterprises medium- Technological
innovations (SMEs) who sized innovation, as
(percentage of introduced at enterprises measured by the
SMEs) least one product introduction of new
innovation or Eurostat, products (goods or
process Community services) and
innovation either Innovation processes, is a key
new to the Survey ingredient to
enterprise or new innovation in
to their market. A manufacturing
product activities. Higher
innovation is the shares of
market technological
introduction of a innovators should

new or reflect a higher level
significantly of innovation
improved good activities
or service with
respect to its
capabilities, user
friendliness,
components or
subsystems. A
process
innovation is the
implementation
of a new or
significantly
improved
production
process,
distribution
method, or
supporting
activity.

Eurostat,
Community
Innovation
Survey

3.1.2 SMEs Number of small Total number 2016
introducing and medium- of small and
marketing or sized enterprises medium- The Community
organisational (SMEs) who sized Innovation Survey
innovations introduced at enterprises mainly asks firms
(percentage of least one new about their
SMEs) organisational Eurostat, technological
innovation or Community innovation. Many
marketing Innovation firms, in particular in
innovation. An Survey the services sectors,
organisational innovate through
innovation is a other non-
new technological forms
organisational of innovation.
method in an Examples of these
enterprise’s are marketing and
business organisational
practices innovations. This
(including indicator captures
knowledge the extent to which
management), SMEs innovate
workplace through non-
organisation or

external relations technological
that has not been innovation
previously used
by the enterprise.
A marketing
innovation is the
implementation
of a new
marketing
concept or
strategy that
differs
significantly from
an enterprise’s
existing
marketing
methods and
which has not
been used
before.

Eurostat,
Community
Innovation
Survey

3.1.3 SMEs Number of small Total number 2016
innovating in-house and medium- of small and
(percentage of sized enterprises medium- This indicator
SMEs) (SMEs) with in- sized measures the
house innovation enterprises degree to which
activities. In- SMEs, that have
house innovating Eurostat, introduced any new
enterprises are Community or significantly
defined as Innovation improved products
enterprises Survey or production
which have processes, have
introduced innovated in-house.
product or The indicator is
process limited to SMEs,
innovations because almost all
either large firms innovate
themselves or in and because
co-operation with countries with an
other enterprises industrial structure
or organisations. weighted towards
larger firms tend to
Eurostat, do better
Community

Innovation
Survey

3.2.1 Innovative Number of small Total number 2016
SMEs collaborating and medium- of small and
with others sized enterprises medium- This indicator
(percentage of with innovation sized measures the
SMEs) co-operation enterprises degree to which
activities, i.e. SMEs are involved
those firms that Eurostat, in innovation co-
had any co- Community operation. Complex
operation Innovation innovations often
agreements on Survey depend on the
innovation ability to draw on
activities with diverse sources of
other enterprises information and
or institutions in knowledge, or to
the three years collaborate in the
of the survey development of an
period innovation. This
indicator measures
Eurostat the flow of
Community knowledge between
Innovation public research
Survey institutions and
firms, and between
firms and other
firms. The indicator
is limited to SMEs,
because almost all
large firms are
involved in
innovation
cooperation

3.2.2 Public-private Number of Total 2018
co-publications per public-private co- population
million population authored This indicator
research Eurostat captures public-
publications. The private research
definition of the linkages and active
“private sector” collaboration
excludes the activities between
private medical business sector
and health researchers and
sector. public sector
Publications are researchers
assigned to the resulting in
country in which academic
the business publications

companies or
other private
sector
organisations are
located

Scopusa

3.2.3 Private co- All R&D Gross 2016
funding of public expenditures in Domestic
R&D expenditures the government Product This indicator
(percentage of sector measures public-
GDP) (GOVERD) and Eurostat, private co-operation.
the higher OECD University and
3.3.1 PCT patent education sector government R&D
applications per (HERD) financed financed by the
billion GDP (in by the business business sector are
PPS) sector expected to
explicitly serve the
3.3.2 Trademarks Eurostat, OECD more short-term
applications per research needs of
billion GDP (in Number of patent Gross the business sector
PPS) applications filed Domestic
under the PCT, Product in 2016
at international Purchasing
phase, Power The capacity of
designating the Standard firms to develop
European Patent new products will
Office (EPO). Eurostat determine their
Patent counts competitive
are based on the advantage. One
priority date, the measure of the rate
inventor’s of new product
country of innovation is the
residence and number of patents.
fractional counts This indicator
measures the
OECD Gross number of PCT
Domestic patent applications
Number of Product in
trademark Purchasing 2018
applications Power
applied for at Standard Trademarks are an
EUIPO plus important innovation
number of Eurostat indicator, especially
trademark for the service
applications sector. The
applied for at Community
trademark gives its

WIPO (“yearly proprietor a uniform
Madrid right applicable in all
applications by Member States of
origin”) the European Union
through a single
European Union procedure which
Intellectual simplifies trademark
Property Office policies at European
(EUIPO), World level. It fulfils the
Intellectual three essential
Property Office functions of a
(WIPO) trademark: it
identifies the origin
Comment Two- of goods and
year averages services,
have been used guarantees
consistent quality
through evidence of
the company’s
commitment vis-à-
vis the consumer,
and it is a form of
communication, a
basis for publicity
and advertising

4.1.1 Employment Number of Total 2017
in knowledge- employed employment
intensive activities persons in Knowledge-
(percentage of total knowledge- Eurostat intensive activities
employment) intensive provide services
activities in directly to
business consumers, such as
industries. telecommunications,
Knowledge- and provide inputs
intensive to the innovative
activities are activities of other
defined, based firms in all sectors of
on EU Labour the economy
Force Survey
data, as all
NACE Rev.2
industries at 2-
digit level where
at least 33 per
cent of
employment has
a higher
education degree
(ISCED 5-8)

Eurostat

4.1.2 Employment Number of Total 2016
in fast-growing employees in employment
enterprises high-growth for This indicator
(percentage of total enterprises in 50 enterprises provides an
employment) per cent ‘most with 10 or indication of the
innovative’ more dynamism of fast-
industries22 employees growing firms in
innovative sectors
Eurostat Eurostat as compared with all
fast-growing
business activities.
It captures the
capacity of a
country to transform
rapidly its economy
to respond to new
needs and to take
advantage of
emerging demand

4.2.1 Exports of Value of medium Value of total 2018
medium and high and high-tech product
technology exports, in exports The indicator
products as a share national currency measures the
of total product and current Eurostat technological
exports prices, including (ComExt) for competitiveness of
exports of the MS, UN the EU, i.e. the
following SITC ComTrade ability to
Rev.3 products: for non-MS commercialise the
266, 267, 512, results of research
513, 525, 533, and development
54, 553, 554, (R&D) and
562, 57, 58, 591, innovation in
593, 597, 598, international
629, 653, 671, markets. It also
672, 679, 71, 72, reflects product
731, 733, 737, specialisation by
74, 751, 752, country. Creating,
759, 76, 77, 78, exploiting and
79, 812, 87, 88 commercialising
and 891 new technologies
are vital for the
Eurostat competitiveness of a
(ComExt) for country in the
Member States, modern economy.
UN ComTrade Medium and high
technology products

for non-EU are key drivers for
countries economic growth,
productivity and
4.2.2 Exports of Total value welfare, and are
Knowledgeintensive knowledge- of services generally a source
services exports as intensive exports of high value added
percentage of total services is Eurostat and well-paid
services exports defined as the employment
sum of credits in Total
EBOPS 2010 turnover for 2017
(Extended all
Balance of enterprises The indicator
Payments Eurostat, measures the
Services Community competitiveness of
Classification) Innovation the knowledge-
items SCI, SC2, Survey intensive services
SC3A, SF, SG, sector.
SH, SI, SJ and Competitiveness-
SK123 enhancing
measures and
Eurostat innovation
strategies can be
4.2.3 Sales of new- Sum of total mutually reinforcing
to-market and new- turnover of new for the growth of
to-firm innovations or significantly employment, export
as percentage of improved shares and turnover
turnover products, either at the firm level. It
new-to-the-firm reflects the ability of
or new-to-the- an economy,
market, for all notably resulting
enterprises from innovation, to
export services with
Eurostat, high levels of value
added, and
successfully take
part in knowledge-
intensive global
value chains

2016

This indicator
measures the
turnover of new or
significantly
improved products
and includes both
products which are
only new to the firm
and products which

Community are also new to the
Innovation market. The
Survey indicator thus
captures both the
creation of state-of-
the-art technologies
(new-to-market
products) and the
diffusion of these
technologies (new-
to-firm products)

a Data provided by Science-Metrix as part of a contract to
European Commission (DG Research and Innovation).

Source: European Union (2019) European Innovation Scorecard
2019, © European Union 2019, pp. 86–90.

APPENDIX 1.2 SWEDEN INNOVATION
UNION SCOREBOARD
INDICATIONS

Source: European Union (2019) Innovation Union Scoreboard
2019, © European Union 2019, p. 69.

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1.11 GLOSSARY OF TERMS

American US national strategy policy for innovation.
Strategy for
Innovation

Co-working Incubation locations for young sectors.
Incubation

Crowdfunding Mechanism to seek start-up funding.

Global Established in 1999 and now the world’s largest

Entrepreneurship assessment of entrepreneurial activities.

Monitor

High-Growth Privately own firms that have a high growth
Enterprises orientation.

Indicator These are specific measures of innovation and
Measures entrepreneurship activities that can be used for
comparison purposes.

Innovation Union Annual member state comparative assessment of

Scoreboard EU innovation capacities.

Innovation Union Launched by the EU in 2010, outlines the

Strategy strategy for the EU in relation to innovation.

Triple Helix A paradigm that explains the relationship
between universities, industry and government.

Universities Public or privately own organisations that have
three missions – teaching, research and
commercialisation.

1 www.gov.uk/government/topical-events/the-uks-industrial-strategy

TECHNOLOGY Chapter
2
ENTREPRENEURS

AND NEW

TECHNOLOGY

VENTURES

2.1 LEARNING OBJECTIVES

This chapter explores three areas with respect to technology
entrepreneurs and new technology ventures. We begin by
exploring the different definitions of entrepreneurship and
then examine how technology entrepreneurs are different
from other types of entrepreneurs. We then turn our focus to
examining the characteristics of technology entrepreneurs.
We present the common characteristics of entrepreneurs and
technology entrepreneurs to explore the commonalities and
differences. We conclude the chapter by outlining the
motivations and entrepreneurial intent of entrepreneurs and
technology entrepreneurs.

After reading this chapter, you will be able to:

1. Define entrepreneur and technology entrepreneur;

2. Understand the common characteristics of entrepreneurs
and technology entrepreneurs;

3. Describe and explain the motivations of technology
entrepreneurs; and

4. Understand the psychological characteristics of
entrepreneurship.

2.2 CHAPTER STRUCTURE

The core elements of this chapter are as follows:

• Introduction
• Defining the Entrepreneur and Technology

Entrepreneurs

• Technology Entrepreneurs’ Characteristics
• Motivations and Intentions
• Chapter Summary
• Case Study – Rovio Entertainment: The Angry Birds

Creators

• Revision Questions
• Further Reading and Resources
• References
• Glossary of Terms

2.3 INTRODUCTION

Becoming an entrepreneur is now considered a
socially acceptable career path in many societies.
Economies need entrepreneurs to support
economic activity and growth. For those
considering the entrepreneurial route, it is a
significant move where they have total
responsibility over their idea and bringing it to the
market. They also have to deal with fear and
uncertainty as to whether their idea will make it in
competitive marketplaces. Consideration must be

given to the level of risk and the capital they need
in order to realise their idea. This can involve
investing personal savings, appropriating financial
support from family and friends, as well as
availing themselves of any state supports to get
from idea stage to launching the product or service
into a marketplace. The entrepreneurial process
stretches the capabilities of entrepreneurs in terms
of skills, decision-making and business acumen.
For technology entrepreneurs the danger is having
an exclusive focus on the product or service,
without due consideration to whether it addresses a
real market problem with customers who would be
willing to pay for it. The excitement around the
technology can mean that technology
entrepreneurs often neglect robust market
validation (see Chapter 7) and do not develop an
appropriate business model to sell their product to
the key customer (see Chapter 6). In many cases
technology entrepreneurs can lack knowledge and
skills around strategy, marketing and finance, and
learn by doing as they bring their ideas through to
a viable product or service. The success of any
venture can depend on a variety of external factors
such as market and economic conditions, reaction
of competitors, regulations and other products and
services. The success of the venture can also be
shaped by the entrepreneur, as Baron (2004) notes:
“the decision they make, the strategies they
develop, the style of leadership they exercise …”

2.4 DEFINING THE ENTREPRENEUR
AND TECHNOLOGY
ENTREPRENEURS