The Characteristics of Knowledge-Intensive Entrepreneurship in Greek High-Technology Sectors

Abstract

The present paper focuses on the Greek knowledge-based firms. Assuming that Knowledge-Based Entrepreneurship (KBE) is a high-potential entrepreneurship, we study different factors which shape this type of entrepreneurship as it may represent a new source of development for the Greek economy. We are interested in the educational attainment of founders and employees, the main areas of expertise of founders, and the factors influencing the creation of new ventures. We also explore the sources of knowledge for the exploration of new business opportunities and the importance of networking in different firm operations. Therefore, this research focuses on both the founder and the founding team as well as on the overall operations of the firms. Analysis is based on a structured questionnaire circulated to a representative sample of new firms that have been established between 2000 and 2010 and belong to various high-technology sectors. The examined sectors have been classified into three groups: (1) high-technology manufacturing, (2) medium-high-technology manufacturing, and (3) high-technology knowledge-intensive services. To understand the exploitation differences on sources of knowledge and the networking among the founders, depending on their educational background, we performed analysis of variance. Finally, we explore how these characteristics affect the performance of firms which in turn can generate economic growth, especially in the crisis period. Regarding the KBE perspective in exploring innovativeness and growth of newly established Greek firms, we derive useful conclusions for both the management of firms as well as for the public policies to promote innovation and entrepreneurship in general.

Full text

The Characteristics of Knowledge-
Intensive Entrepreneurship in Greek
High-Technology Sectors
Nikos Kanellos
Department of Business Administration, University of the Aegean, Chios,
Greece
Abstract
The abstract is published online only. If you did not include a short abstract
for the online version when you submitted the manuscript, the first paragraph
or the first 10 lines of the chapter will be displayed here. If possible, please
provide us with an informative abstract.
The present paper focuses on the Greek knowledge-based firms. Assuming
that Knowledge-Based Entrepreneurship (KBE) is a high-potential
entrepreneurship, we study different factors which shape this type of
entrepreneurship as it may represent a new source of development for the
Greek economy. We are interested in the educational attainment of founders
and employees, the main areas of expertise of founders, and the factors
influencing the creation of new ventures. We also explore the sources of
knowledge for the exploration of new business opportunities and the
importance of networking in different firm operations. Therefore, this
research focuses on both the founder and the founding team as well as on the
overall operations of the firms. Analysis is based on a structured
questionnaire circulated to a representative sample of new firms that have
been established between 2000 and 2010 and belong to various high-
technology sectors. The examined sectors have been classified into three
groups: (1) high-technology manufacturing, (2) medium-high-technology
manufacturing, and (3) high-technology knowledge-intensive services. To
understand the exploitation differences on sources of knowledge and the
networking among the founders, depending on their educational background,
we performed analysis of variance. Finally, we explore how these
characteristics affect the performance of firms which in turn can generate
1✉
1

economic growth, especially in the crisis period. Regarding the KBE
perspective in exploring innovativeness and growth of newly established
Greek firms, we derive useful conclusions for both the management of firms
as well as for the public policies to promote innovation and entrepreneurship
in general.
AQ1
Keywords
Knowledge-based entrepreneurship
Innovation
High-technology sectors
Greece
Entrepreneurial Marketing
Introduction
Knowledge-Based Entrepreneurship (KBE) is a socio-economic phenomenon
characterized as important for driving innovation, economic growth, and
development (Akuhwa et al. 2015; Groen 2005). The characteristic of this kind
of entrepreneurship is based in the high potential for technology enchantment
and upgrade. Moreover, KBE works as an effective mechanism for transforming
knowledge into innovation and, thus, to new economic activity (Carlsson et al.
2007). Many academics dispute better the term “Knowledge-Based
Entrepreneurship” and the “Innovative Entrepreneurship.” That is because it
develops and diffuses the product innovations or process innovations (Akuhwa
et al. 2015; Radosevic et al. 2010). Additionally, KBE, having a unique form, is
embedded in diverse sectors—including the traditional and high-technology
sectors, manufacturing and services, existing and new industries. They are new,
innovative, and high knowledge intensity firms, which are involved in a process
that translates knowledge into innovation (OECD, 2005).
AQ2
This paper examines the basic aspects of KBE, meaning knowledge intensity
and innovative performance. More specifically, it investigates the link between
the educational background of the founders withand the sources of knowledge
of firms for exploring business opportunities as well asand the role of networks
in different firm operations will lead in business success (Dimitrios and Sakas
2019a, b, c). We hypothesize that when a firm has at least one founder with a
very high educational level then it is connected to specific sources of

knowledge like in-house Research and Development (R&D), marketing,
universities and research institutes, scientific journals and research
programs (Drucker, 1985). The educational background of founders also affects
the networking in different firm operations (Fagerberg, 2006). The main
facilitators of networking are quite different between the founders who have
completed only elementary or secondary education with those who have PhD or
Master’s degree.
AQ3
Defining Knowledge-Based Entrepreneurship
Entrepreneurship is based on the exploitation of knowledge and opportunities.
KBE is a special form of entrepreneurship with links to the so-called knowledge
economy, which is characterized by the crucial role of information and
communication technologies (ICT), the high proportion of knowledge-intensive
activities, the growing ratio of intangible to tangible assets on corporate balance
sheets, and the increased expenditures on R&D (Stam and Garnsey 2008; Foray
2004). Entrepreneurship is defined as the process where new added value
products and services, while necessitatingrequire devotion, effort, and time in
participating in knowledge-intensive economic activities, while taking social,
economic, and psychological risks, and taking as reward the financial and
personal satisfaction and independence (Hisrich et al. 2005; Bosma 2010; Witt
and Zellner 2019). This definition is based on three key characteristics of
entrepreneurship. First, the process of creation and the process of creating new
products or services that have value for both the entrepreneur himself and for
the consumers (Dimitrios et al. 2015a; 2017a). Second, the time and effort
required to create something new, which must also be
functional (Kanellos, 2013; Zahra and George, 2002). The total time and effort
are appreciated only by those involved in the business process. Finally, the third
important aspect of entrepreneurship that stands out from the above definition is
to assess the risks involved in obtaining the expected benefits (Keins, 2006;
Cohen and Levinthsl, 1990). ToFor studying the phenomenon of KBE it is
important to take into account mainly the first of three key aspects of
entrepreneurship (Jones et al., 2013).
AQ4
AQ5
AQ6
AQ7

In the context of this paper, we will adopt some basic characteristics for the
KBE, provided by Malerba and McKelvey (2010). KBE is linked to:
•New firms.
•Innovative firms.
•Firms which have a significant knowledge-intensive in their activities.
•Firms that exploit innovative opportunities not only in high-technology
sectors but in diverse sectors.
AQ8
The activity sectors of KBEs are not limited only to high-technology sectors but
also in traditional industries and sectors that are either existing or new. Their
business models depend on the knowledge required to exploit innovation
opportunities and the creation of value and growth at the enterprise level (Autio,
1997). Therefore, the definition of KBE connects firms with knowledge
economy, as a mechanism that turns knowledge into innovation (and further into
development) (Akuhwa et al. 2015). So, innovation can happen in any sector no
matter how “traditional” it may be. For example, von Tunzelmann and Yoruk
(2004) consider that the food industry is currently undergoing a transformation
from low-technology sector to medium-tech sector or even to high-technology
sector (Sexton and Smilor, 1986). For the purposes of this research we will
focus on firms operating in high-technology sectors, which are considered as the
pioneers sectors of the economy in terms of innovation.
Methodology
Sampling and Data Collection
During 2012 we administrated an extensive structured questionnaire to the
owners/founders of 1162 young Greek firms. The data for these firms were
compiled from two data sources: (1) Hellastat, a private financial and business
information services company and (2) Amadeus, a Pan-European financial
database.
The questionnaire was divided into four parts providing information on: (a) the
founder or the founding team, (b) information on the strategy of the firm, (c) the
innovation, and (d) growth of the firm. The questions designed are closed

questions based on a five-point ordinal Likert-type scale or closed-ended
questions. They are to be answered by one or two or more options or values.
The questionnaire was made accessible over the Internet, and respondents were
sent a direct link by e-mail (Madsen et al. 2004, Neergaard and Madsen 2003).
The criteria for firm selection in the original sample were the year of
establishment and the industry classification. Our sample consists of firms that
are new by definition, i.e. ventures that have been established between 2000 and
2010. Furthermore, the selected sample operates in the following sectors: (1)
high-technology manufacturing, (2) medium-high-technology manufacturing,
and (3) high-technology knowledge-intensive services.
AQ9
One of the criteria for the firm selection was the year of establishment. The
firms of our sample are new ventures that were established during the period
2000–2010. The majority of them (69%) were set up during the period 2000–
2006. In this time frame there was a strong momentum for the high-technology
sectors in Greece (ΙΟΒΕ 2008). Several firms also created amid the financial
crisis period, i.e. after 2008 (19%). There are no statistically significant
differences between sectors with respect to year of establishment.
Variables
As noted above, we are interested in examining how the educational background
of founders affects the sources of knowledge and the networking in different
firm operations. The required indicators are related to the knowledge of both the
founder and the company. Knowledge of founders is measured by two variables:
Educational attainment of founders: We measure educational attainment using
an ordinal variable which takes the following values: 1—Elementary/Secondary
education; 2—Bachelor degree; 3—PhD/Master. If there is a founding team,
then we derive the highest educational attainment at all members of each
founding team.
Main areas of expertise of founders: We measure the main areas of expertise for
each founder (i.e. technical/engineering knowledge, marketing, general
management, and other). The following set of variables measure the firm’s
knowledge and networking. Knowledge intensity is gauged by a Likert-type
scale (with one (1) being “Not important” and five (5) characterized as
“Extremely important”) that asks respondents to assess the role of specific
1

sources of knowledge for the exploration of new business opportunities
(Caloghirou and Protogerou, 2015).
The sources of knowledge are either internal (In-house R&D) or external
associated with the value chain (clients, suppliers, and competitors), the science
and research community (universities, research institutes, research programs,
and scientific journals), several open sources (exhibitions and conferences,
Internet), or collaborative R&D (strategic alliances).
Empirical Results
We will first examine the educational background of founders. However, since
most of the firms were set up by a founding team and not a founder, it is
appropriate to find the highest educational attainment of founder/s in each firm.
We also examine the main areas of founder expertise and the factors influencing
the firm creation. Furthermore, we investigate the educational level of human
capital. Then we will see the answers we got regarding the innovative
performance of firms. The questions to be dealt with are: (a) what percentages
of firms innovate? (b) Innovation derived from? (c) Innovation is new for
whom? We still try to see how the background of founders is related to the
sources of knowledge of firms and to networks which each firm develops. The
vast majority (93%) of firms are microenterprises and small firms. More
specifically, microenterprises (1–9 employees) account for 52% of the sample
and small firms (10–49 employees) represent 41% of the sample. 7% of the
firms employ 50–249 employees. Firms usually have a founding team of 2 or 3
members and only 24% have only one founder. A large share of firms (40%) has
2 founders, 21% have 3 founders, and only 16% of firms have 4 or more
founders. The educational level of founders appears to be very high. This is
demonstrated by the fact that 28.1% of them have a master’s degree and 10.1%
a PhD. 49.7% have a bachelor or an equivalent degree. Only 4.9% of the
founders have completed only elementary or secondary education and 7.2%
have completed only vocational education. 8 out of 10 of all companies have
founders (or at least one founder in the founding team) holding at least a
University degree. 48% of the firms have at least one founder with postgraduate
studies. Bachelor degree or equivalent is the founders’ highest degree for the
31% of the firms. Finally, a very small number of companies, about 9%, have
founders who completed only elementary, secondary, or vocational education.
Therefore, most firms have founders with a strong educational background.
Respondents indicated the two most important areas of knowledge and skills

that better reflect their professional identity. Most founders (56%) gave as the
first choice the technical and engineering knowledge and as the second choice
the general management (27%). Therefore the dipole “technical and
engineering–general management” reflects better the main areas of expertise of
most founders. The educational level of employees is high. 1 out of 2 of
employees holds a bachelor degree. 18% of employees have a master’s degree
and 4% a PhD. 27% of employees have less educational level. In more details,
14% of employees have completed the vocational education, 12% have
completed the secondary education, and only 1% has completed the elementary
education. The year 2008 is very crucial for the Greek economy because then
appeared the first signs of economic crisis. Therefore, it is important to examine
the same factors affecting the firm formation for the period 2008–2010. The
most important factor for the firm creation is the opportunity from a new market
need and follows the market knowledge. These two factors appear to be of the
same important for the period after 2008. Next are the work experience in the
current activity field and the expectation for revenue growth.
Innovation Performance of Firms
We begin our discussion about the innovative performance of the sampled firms
by presenting the type of innovation which firms introduced the past three
years. As shown in the following figure, 6 out of 10 firms have introduced some
kind of innovation during the last three years. More specifically, 52% of the
firms have introduced improved or new products/services into the market and
29% of the firms have introduced some kind of process innovation. There are
also a 20% of the firms that have introduced both product and process
innovation. Next we consider the way in which this innovation derived. Most
(41%) of the firms stated that their innovation derives from exploitation of R&D
activities. Furthermore, there is a high percentage (31%) of firms which
introduced or adapted technology from abroad. Less (28%) are those firms that
exploited their business practices for the introduction of innovation and those
which imported goods from abroad (20%). The majority (44%) of firms have
introduced some kind of innovation which is new to the firm. The innovations
of the 39% of the firms are new to the market and only 17% of the firms
introduced innovations that are new to the world. This ratio is about the same
with the corresponding results from AEGIS project which also analyzes the
phenomenon of knowledge-intensive entrepreneurship in ten European
countries. For Ssources of knowledge and networks: is highly considered asthe
importance of the founders’ background. In this section we will try to
2

investigate the link between the educational background of the founders and the
sources of knowledge of firms for the exploration of new business
opportunities. Some sources of knowledge are more important for companies
that have founders with postgraduate degree (PhD included) than those whose
founders have completed only elementary or secondary education. In-house
R&D is an important source of knowledge for postgraduate degree holders
versus those who are non-university degree holders. Therefore, this kind of
internal source of knowledge becomes more important for founders with higher
educational background (Morrison, 2000).
AQ10
There is statistically significant difference between different types of education
of the founders. This source of knowledge is more important for founders with
PhD or Master’s degree than those who completed only the elementary or
secondary education. Another source associated with the science and research
community is the “Scientific journals.” There is statistically significant
difference between the highly educated and lower educated founders, with the
former to prefer more the specific source of knowledge. Finally, the research
programs which are either nationally-funded or EU-funded (FP) are “two-
speed” sources. Firms that have at least one founder with a Master’s or a PhD
degree exploit more the research programs as a source of knowledge to explore
new business opportunities related to the companies where the highest
educational level is the elementary or secondary education. We examine how
the educational background of founders affects the way in which each company
leverages networks for its functions. The founders with higher education level
(PhD/Master) utilize more the networks for the recruitment of skilled labor
relative to entrepreneurs who have only basic education (elementary/secondary
education). This operation seems to affect and whether the firm innovates. As
seen, there is a statistically significant difference in innovation between
companies using their networks for recruitment of skilled labor and those who
do not. Firms that use their networks for recruitment of skilled labor are those
who usually have product and process innovation and contrary, the firms which
do not use their networks for this purpose they do not innovate. There are two
business functions exploited by the networks forming companies with founders
who have a low educational background. The first operation is the
“understanding of customer needs” and the second is the “arrangement of
taxation and of other legal issues.” These features are more common in
entrepreneurs who have completed only elementary or secondary education in
relation to the founders who have PhD or Master.

AQ11
Conclusions
The new established Greek firms operating in high-technology sectors have a
significant stock of knowledge and innovate greatly. They consist of founders
with a very high educational level and they have highly qualified employees.
The main areas of expertise of founders are the technical/engineering
knowledge and the general management. 6 out of 10 firms innovate by mainly
exploiting R&D activities. These innovations are usually new to the firm.
Within this article we studied the link between the educational attainment of the
founders and the sources of knowledge and networking of each firm. The highly
educated founders choose more scientific and research knowledge sources to
explore new business opportunities, such as in-house R&D, universities and
research institutes, scientific journals and research programs, compared with the
founders having lower educational background who prefer other sources.
Regarding the networking of firms, the educational background of the founders
also plays an important role on the different types of operations and activities.
Firms that have founders with Master or/and PhD utilize more their networks
for recruiting skilled labor. As we saw, this function affects the development of
innovations. Firms that use their networks for this operation are those
developing both product and process innovation. Firms founded by
entrepreneurs of lower educational attainment (elementary/secondary education)
mainly use their networks for other purposes, such as the understanding of
customer needs and the arrangement of taxation and of other legal issues.
Administrative science is often viewed with a strategic perspective, and the
effort to find best practices we look for in computational models (Dimitrios et
al. 2014a, b; Dimitrios et al. 2015b; Dimitrios et al. 2017b) where, with the
subscription of Simulation modeling (Dimitrios et al. 2013; 2014c; Sakas et al.
2014), we foresee their evolution.
AQ12
AQ13
AQ14
AQ15
AQ16

References
Akuhwa, P., Gbande, C., Akorga, B., & Adye, Z. (2015). Knowledge-based
entrepreneurship and globalization: correlates for the wealth of nations and
perspectives from Nigeria. Open Journal of Applied Sciences, 05(08), 460–484.
Autio, E. (1997). New, technology-based firms in innovation networks
symplectic and generative impacts. Research Policy, 26, 263–281.
Bosma, N. (2010). Overview of theory, statistical evidence and case studies on
knowledge-based entrepreneurship, clusters and economic growth. AEGIS
project, del. 2.4.1.
Caloghirou, Y., & Protogerou, A. (2015). Knowledge- intensive
entrepreneurship: Exploring a taxonomy based on the AEGIS survey. In F.
Malerba, Y. Caloghirou, M. McKelvey, & S. Radoševic (Eds.), Dynamics of
knowledge intensive entrepreneurship: Business strategy and public policy (1st
ed., pp. 119–144). Abingdon: Routledge.
Carlsson, Bo & Acs, Zoltan & Audretsch, David & Braunerhjelm, Pontus.
(2007). The Knowledge Filter, Entrepreneurship, and Economic Growth.
SSRN Electronic Journal. 10.2139/ssrn.1022922.
AQ17
Cohen, W. M., & Levinthal, D. (1990). Absorptive capacity: A new perspective
on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.
Dimitrios, N. K., & Sakas, P. R. D. P. (2019a). Modeling and simulation of the
strategic use of social media networks in search engines for the business
success of high technology companies, springer proceedings in business and
economics (pp. 227–236). Cham: Springer.
Dimitrios, N. K., & Sakas, P. R. D. P. (2019b). Modeling and simulation of the
strategic use of marketing in search engines for the business success of high
technology companies, springer proceedings in business and economics (pp.
217–226). Cham: Springer.
Dimitrios, N. K., & Sakas, P. R. D. P. (2019c). Modeling and simulation of the

strategic use of the internet forum aiming at business success of high-
technology companies, springer proceedings in business and economics (pp.
169–171). Cham: Springer.
Dimitrios, N. K., Sakas, D. P., & Vlachos, D. S. (2013). The contribution of
dynamic simulation model of depiction of knowledge, in the leading process of
high technology companies. Key Engineering Materials, 543, 406–409.
Dimitrios, N. K., Sakas, D. P., & Vlachos, D. S. (2014a). Modeling the
scientific dimension of academic conferences. Procedia-Social and Behavioral
Sciences, 147, 576–585.
Dimitrios, N. K., Sakas, D. P., & Vlachos, D. S. (2014b). Modeling publications
in academic conferences. Procedia-Social and Behavioral Sciences, 147, 467–
477.
Dimitrios, N. K., Sakas, D. P., & Vlachos, D. S. (2014c). Simulation of
generation of new ideas for new product development and IT services. AIP
Conference Proceedings, 1644(1), 60–68.
Dimitrios, N. K., Sakas, D. P., & Vlachos, D. S. (2015a). Modeling of market
segmentation for new IT product development. AIP Conference Proceedings,
1644(1), 51–59.
Dimitrios, N. K., Sakas, D. P., Vlachos, D. S., & Mavrogianni, A. (2015b).
Modeling of market segmentation for new IT product development. AIP
Conference Proceedings, 1644, 51.
Dimitrios, N. K., Alexandros, N. K., Sakas, D. P., & Vlachos, D. S. (2017a).
Comparing scrum and XP agile methodologies using dynamic simulation
modeling. In Strategic innovative marketing book series (pp. 391–397). Cham:
Springer.
Dimitrios, N. K., Plessias, A. A., & Giakomidou, D. S. (2017b). Modeling of
market segmentation in social networks and media, springer proceedings in
business and economics (pp. 523–529). Cham: Springer.
Drucker, P. (1985). Innovation and entrepreneurship. Practice and principles.
New York: Harper & Row.

Fagerberg, J. (2006). Innovation: A guide to the literature. In J. Fagerberg, D.
Mowery, & R. Nelson (Eds.), The Oxford Handbook of Innovation. Oxford:
Oxford University Press.
Foray, D. (2004). The economics of knowledge. Cambridge: MIT Press.
Groen, A. (2005). Knowledge intensive entrepreneur ship in networks: towards
a multi-level/multi-dimensional approach. Journal of Enterprising Culture,
13(1), 69–88.
Hisrich, R., Peters, M., & Shepherd, D. (2005). Entrepreneurship (6th ed.).
Boston: McGraw Hill.
Jones, R., Suoranta, M., & Rowley, J. (2013). Entrepreneurial marketing: a
comparative study. The Service Industries Journal, 33(7–8), 705–719.
Kanellos, N. (2013). Exploring the characteristics of knowledge-based
entrepreneurs in greece. Procedia - Social and Behavioral Sciences, 73, 337–
344.
KEINS (2006). Knowledge based entrepreneurship: institutions, networks and
systems. EU project no CT2–CT–2004–506022, deliverable 0.
Madsen, H., Neergaard, H., Fisker, S., & Ulhøi, J. (2004). Entrepreneurship in
the knowledge-intensive sector: Influential factors at the start-up and early
growth phase. In 13th Nordic Small Business Research Conference. Aarhus:
Aarhus University.
Malerba, F. & McKelvey, M. (2010). Conceptualizing knowledge-intensive
entrepreneurship: concepts and models. AEGIS project, del. 1.1.1.
Morrison, A. (2000). Entrepreneurship: What triggers it? International Journal
of Entrepreneurial Behaviour & Research, 6(2), 59–71.
Neergaard, H. & Madsen, H. (2003). Social capital in knowledge intensive start-
ups. CiteSeerX. Retrieved October 15, 2019, from http://citeseerx.ist.psu.edu/vi
ewdoc/download?doi=10.1.1.873.3869&rep=rep1&type=pdf
OECD. (2005). The measurement of scientific and technological activities. In

Oslo manual: Guidelines for collecting and interpreting innovation data (A
Joint publication of OECD and Eurostat) (3rd ed.). Paris: OECD.
Radosevic, S., Yoruk, E., Edquist, C., & Zabala, J. (2010). Knowledge-intensive
entrepreneurship and national innovation systems, AEGIS project, del. 2.2.1.
Rosenberg N. (1990). Why do firms do basic research (with their own money)?
Research Policy, 19, 165–174.
Sakas, D. P., Nasiopoulos, D. K., & Vlachos, D. S. (2014). Modeling the
development of the online conference’s services. Library Review, 65(3), 160–
184.
Sexton, D., & Smilor, R. (1986). The Art and Science of Entrepreneurship.
Pensacola: Ballinger Publishing Company.
Stam and Garnsey. (2008). Chapter 7 “Entrepreneurship in the Knowledge
Economy”. In J. Bessant & T. Venables (Eds.), Creating wealth from knowledge.
Cheltenham: Edward Elgar.
Von Tunzelmann, N., & Yoruk, E. (2004). Network realignment in the CEE
food- processing industry. In F. McGowan, S. Radosevic, & N. Von Tunzelmann
(Eds.), The emerging industrial structure of the wider Europe. London:
Routledge.
Witt, U., & Zellner, C. (2019). Knowledge-based entrepreneurship: The
organizational side of technology commercialization. In F. Malerba & S.
Brusoni (Eds.), Perspectives on innovation (pp. 352–371). Cambridge:
Cambridge University Press.
Zahra, A., & George, G. (2002). Absorptive capacity: a review,
reconceptualization, and extension. Academy of Management Review, 27(2),
185–203.
IOBE (2008) ΙΟΒΕ: Καινοτοµία Και Κλάδοι Υψηλής Τεχνολογίας,
Naftemporiki.gr. [online] Available at: [Accessed 1 October 2019].
An ANOVA test of significance shows that differences between sectors regarding year of
1

establishment are statistically non-significant (ANOVA F = 0.712, Sig = 0.492).
The AEGIS project aims to analyze knowledge-intensive entrepreneurship and related
strategies and policies from a variety of disciplines and research methodologies such as
economics, organization theory, strategic management, finance, economic history, economic
geography, sociology, science and technology studies, and policy studies (source: http://www.a
egis-fp7.eu/).
2