Faculty of medicine, University of New south wales, Sydney, NSW. Correspondence: J. Westbrook@unsw. edu. au References 1 Lemay R. E-Health:
Examples of such resources include inputs to R&d activity, e g. scientists and universities, or the knowledge about customers and markets.
Institute of Economic Research, Hitotsubashi University. Bonacich, P.,Oliver, A. & Snijders, T. A b. 1998.'
Leipzig and Center for Social and Economic Research, Warsaw) and Federico Biagi (IPTS, University di Padua and SDA Bocconi.
A key lesson from the analysis of the three subsectors is the critical importance of higher education
particularly elite university research, and of local networks as generated by clusters. Case studies of Apple, Google and Robotdalen emphasize the importance of prior government intervention to form clusters, from
A key lesson from analysis of the three subsectors, particularly web applications, is the critical importance of higher education
particularly elite university research, and of local networks as generated by clusters. Case studies of Apple, Google and Robotdalen emphasize the importance of prior government intervention to form clusters, from
They require long-term investment in human capital often around a centre of technological excellence, such as a university
or the Cavendish Laboratory at the University of Cambridge, which spawned both CDT and Plastic Logic.
First, successful innovation depends to some extent on excellence in education and strong and active links between knowledge generation, knowledge exchange and knowledge exploitation (i e. between universities and firms.
However, it should be recognized that higher education research funding has led to spin-off companies which have gone on to become highly successful,
Cambridge Display Technologies (CDT) key lessons The role of higher education hosting leading edge research is highlighted once again by the case of CDT.
CDT was established in 1992 following the discovery that Light Emitting Diodes (LEDS) could be made from polymers as opposed to traditional semiconductors by researchers at the Cavendish Laboratory at the University of Cambridge.
The case study also highlights the university's lack of capability at that time to respond to the discovery in any meaningful way.
when it became clear that the university was unable to licence the technology itself. CDT also illustrates the fact that the time frame for development
Novaled's resulted from collaboration between the Technical University of Dresden's Institute for Applied Photophysics (IAPP) and the Fraunhofer 13 Startup Intelligence
centres of excellence within universities MIT Media Lab in this case can provide focused and fertile sources of start-ups.
as it sees China as the key future robotics market as it moves from human to automated production lines. irobot key lessons irobot first demonstrates the role of research within an excellent higher education institution.
Shadow was spawned not by a higher education institute, 15 http://www. sba. gov/sba-100/irobot 30 although actually both Shadow and irobot appear to have been characterized by similar amateurism in their early stages. irobot,
Involvement of universities in the seeding process, both for new technological innovation and for driving new technology take-up, is a major factor.
This is shown in the use of university staff and even students to introduce robotics through business cases and technical integration services, at reduced costs to new users.
which are based on developments from an open source operating system from Carnegie mellon University, Mach 3. 0. Note that where there are grey areas in the uses of IPR for web services
(whose origins lie in Steve jobs'Next Nextstep operating system, based on the MACH kernel from Carnegie mellon University, with Freebsd source code extensions), Linux,
therefore indicating that collaborations with the OSS community should exert a positive effect on entrepreneurial ventures'innovation performance. 24 Berkeley Software Distribution a free open source licensed version of the Unix operating system from the Regents of the University
In some of our case studies there is a clear connection between successful innovation and the generation of these highly skilled individuals through higher education.
E Ink, irobot are other examples where US start-ups depended to a greater or lesser extent on links with excellent higher education institutions in these cases, MIT.
as there are several European examples in our case studies. For instance, the Institute for Applied Photophysics at the Technical University of Dresden with the Fraunhofer Institute founded Novaled in Germany,
and the Cavendish Laboratory at the University of Cambridge spun out both Plastic Logic and CDT. 45 So how do the EU
and US higher education systems compare in this regard? 27 Of the top 50 departments in the world in different subject areas, the majority are found in the USA (39 of 50 in computer science, 33 in engineering, 37 in neuroscience)( Technopolis, 2011;
The research performance of Europe's universities seems to lag behind that of their US counterparts, particularly in the top 50 universities in the Academic ranking of world universities (ARWU), colloquially known as the‘Shanghai ranking'(Aghion et al, 2005;
it should be noted that even in the Shanghai ranking, a European‘top'university tends to be among the best 25%in the world in at least one discipline,
although the number of disciplines in which it is world leader is on average substantially lower than that calculated for a top US university (Moed, 2006).
In other words, while there are centres of elite academic research in the EU, there are just many more in the USA.
A key lesson from the experiences of all the subsectors, particularly web applications, is the critical importance of higher education and of local networks in the formation of clusters.
And this calls for excellence in education and strong and active links between knowledge generation and knowledge exploitation (i e. between universities and firms.
Bessen, J.,Ford, J. and Meurer, M. 2011), The Private and Social Costs of Patent Trolls, Boston University School of law, Working Paper No. 11-45, Revision
of November 9, http://www. bu. edu/law/faculty/scholarship/workingpapers/documents/Bessen-Ford-Meurer-no-11-45rev. pdf Botero, J.,Djankov, S
Dee, N. and Minshall, T. 2011), Finance, Innovation and Emerging Industries a Review, Centre for Technology Management Working Paper Series, No. 2011/2, Institute for Manufacturing, University
Assessing Europe's University-based Research, Expert Group on Assessment of University-based Research, EUR 24187 EN, DG Research,
http://ec. europa. eu/research/science-society/document library/pdf 06/assessing-europe-university-based-research en. pdf European commission (2012) Conference on Transparency
http://ec. europa. eu/enterprise/sectors/ict/standards/extended/patent pools event en. htm Feldman, M.,Desrochers, P.,(2003), Research Universities and Local Economic Development:
. pdf Moed, H. 2006), Bibliometric Rankings of World Universities, CWTS Report 2006-01, Centre for Science and Technology Studies (CWTS), Leiden University, http
And in the fall of 1996 the project would regularly bring down Stanford's Internet connection. 45 It is hard to imagine a European university providing such a level of support to a couple of renegade Phd students,
and degrees from the best colleges as you would expect, they took a scientific approach
Stanford university and research funding and the support of the university and the access to Silicon valley high tech/angel investor/VC network.
Sources Professor Martin Cave, Imperial College Business school. Co-author of Report on The Perils of Dominance:
Martin Goro ko, head of marketing for the Tallin Tehnopol technology park, says that Skype has had a bigger influence on young entrepreneurs than the Tallinn University of Technology
and the University of Tartu put together. Eighty percent of the business ideas that reach our incubator
Interestingly, the researchers found that that there were no funds available within the university to cover the costs of patenting their discovery;
The university lacked the resources and skills to licence what was a potentially disruptive technology
In 1992, Friend founded CDT Ltd, with support from the university and funding from local seed venture capital fund
The ownership of the OLED IPR was transferred from the university to the new company, while the university remained as one of the company's largest shareholders.
Other early investors included the rock group, Genesis; the Sculley Brothers; the Generics Group; Hermann Hauser, a founding director of Acorn Computer;
http://www. cdtltd. co. uk/Tim Minshall, Stuart Seldon, David Probert, Commercializing a disruptive technology based upon University IP through Open Innovation:
when Professor Sir Richard Friend (now Cavendish Professor of Physics at the University of Cambridge) started research into organic semiconductors.
from innovation to impact, University of Cambridge, Research Features, 01 aug 2009, http://www. cam. ac. uk/research/features/plastic-logic-from-innovation-to-impact/Novaled AG Novaled
The company was spun off in 2001 from the Technical University of Dresden's Institute for Applied Photophysics (IAPP) and the Fraunhofer Institute (Fhg) for Photonic Microsystems (IPMS), both of Dresden, Germany, by four key people.
as well as being spun off from a technical university and a state-aided research institute. The key project has been the Rollex project:
that a bridge between university and industry is critical for successful product commercialization. One example of such a bridge is the Fraunhofer IPMS.
The IPMS in Dresden enables the IAPP of the Technical University of Dresden to scale up its technology in a well-controlled environment (NSF WTEC 2010.
When Novaled started as a spin-off from Fraunhofer and Technical University of Dresden in 2001 with just 4 people,
With no university degree no university backing and very little funding, 93 over a period of 25 years Greenhill and a small team developed the world's most advanced robotic hand.
The original aim of the Shadow Project was to build a genuinely useful general-purpose robot, at a price which people,
Shadow received its first order for the Dextrous Hand in 2004, curiously from the University of Bielefeld in Germany.
Carnegie mellon University also bought one in 2005 for their research work, 94 but the main customer was again NASA who placed an order in 2005 in connection with their Robonaut project.
Nevertheless, it has outlasted all the apparently more credible government-funded and university robot-building projects from the late 80s and early 90s."
Further development took place in this international effort involving EU companies, universities, and research institutes. In the Realsim project, DLR developed a free Modelica multibody library (the download is available at http://www. Modelica. org/library
Note also that KUKA has sponsored university research in the USA. The KUKA Chair of Robotics at the Georgia Institute of technology held by Professor Henrik Christensen,
RUR works with leading universities and other technology providers to gather the latest and most relevant technology for each application it sees its advantage as being able to deploy the very latest in robotics technology.
Some form of support for those customers taking robotics technology for the first time would allay the fears they often see in small companies over investments in robotics. UK universities are not fully supportive they do not seem to be able to partner well with industry.
with a remit to integrate resources for knowledge, skills, infrastructure and innovation expertise, among universities, science parks, incubators,
Thus Robotdalen draws heavily on local universities to provide students who can work with SMES to introduce robots, guided by a team of experienced mentors.
as well as the local universities of Örebro and Mälardalen. Such developments are generating international interest in Robotdalen
underpinned with regional university support and helping start-up suppliers and robot users. Robotdalen's programme has succeeded in mobilizing interested parties across the entire region.
Prevas, as well as the universities of Mäladalen and Örebro. More than 100 pilot studies of SMES have been conducted to strengthen the competitiveness of the local SMES by robotization of their production processes.
Going further it is supporting human capital growth through university education. Sweden's first university course in robotics is held now here.
Robotdalen has cooperated with local universities to set up a Master of Engineering in Robotics course, at Mälardalen University while at Örebro University a new postgraduate school RAP (Intelligent Systems for Robotics
Automation and Process Control) has been created. One example product is the Giraff teleconferencing robot for the elderly and disabled the company moved to Robotdalen from Silicon valley.
A key lesson from the analysis of the three subsectors is the critical importance of higher education, particularly elite university research,
36 5. 1. 1 Universities ranked in QS University ranking...36 5. 1. 2 Academic ranking of a Computer science Faculty...
38 5. 1. 3 Employer Ranking of a Computer science Faculty...40 5. 1. 4 Citations Ranking of a Computer science Faculty...
42 5. 1. 5 R&d Expenditures by ICT Firms...44 5. 1. 6 ICT FP7 Funding to Private Organisations...
46 5. 1. 7 ICT FP7 Participations...48 5. 1. 8 ICT FP7 Funding to SMES...
131 8. 1 QS WORLD UNIVERSITY RANKINGS by QS...131 8. 2 ICT FP7 by EC DG Connect...
Munchen Kreisfreie Stadt EIPE ID card Activity Characteristic Name of Indicator Indicator ID Rank R&d Agglomeration Universities ranked in the QS University ranking Agrd 1
32 Academic ranking of a Computer science faculty Agrd 2 10 Employer ranking of a Computer science faculty Agrd 3 11 Citations ranking of a Computer science faculty Agrd 4 29 R&d
Inner London East EIPE ID card Activity Characteristic Name of Indicator Indicator ID Rank R&d Agglomeration Universities ranked in the QS University ranking Agrd 1
18 Academic ranking of a Computer science faculty Agrd 2 7 Employer ranking of a Computer science faculty Agrd 3 3 Citations ranking of a Computer science faculty Agrd 4 6 R&d
Paris EIPE ID card Activity Characteristic Name of Indicator Indicator ID Rank R&d Agglomeration Universities ranked in the QS University ranking Agrd 1 37 Academic ranking
of a Computer science faculty Agrd 2 8 Employer ranking of a Computer science faculty Agrd 3 8 Citations ranking of a Computer science faculty Agrd 4 4 R&d expenditures by ICT
the EIPE ID card Activity Characteristic Name of Indicator Indicator ID Nr R&d Agglomeration Universities ranked in the QS University ranking Agrd 1 1 Academic ranking of a Computer science
faculty Agrd 2 2 Employer ranking of a Computer science faculty Agrd 3 3 Citations ranking of a Computer science faculty Agrd 4 4 R&d expenditures by ICT firms
R&d 5. 1. 1 Universities ranked in QS University ranking Table 13: Top ranking regions according to the Universities ranked in QS University ranking indicator Rank NUTS3 Code Region name Indicator Value EIPE Rank 1 UKL12 Gwynedd 100
266 2 DE711 Darmstadt, Kreisfreie Stadt 83 7 3 DE125 Heidelberg, Stadtkreis 82 23 4 DE423 Potsdam, Kreisfreie Stadt 77
UKH12 Cambridgeshire CC 20 5 Indicator description Indicator ID Agrd 1 Name of indicator Universities ranked in the QS University ranking
Measures the number of universities in QS university ranking based in a region Unit of measurement Region's share in the total number of EU ranked universities to a region's share in the EU population Definition of ICT dimension none Unit of observation
NUTS 3 Source QS WORLD UNIVERSITY RANKINGS by QS (see Section 8. 1) Reference year (s) considered 2011 37 Figure 22:
Frequency of the Universities ranked in QS University ranking indicator values 1248 9 8 8 7 4 3 6 1 1 2 1 1 1
2 1 0 500 1000 1500 Frequency 0 20 40 60 80 100 Number of universities ranked in QS Table 14:
Descriptive statistics of the Universities ranked in QS University ranking indicator Number of observations Mean value Standard deviation Variance 1303 1. 16 7. 01 49.17 38 5. 1. 2
Academic ranking of a Computer science Faculty Table 15: Top ranking regions according to the Academic Computer science faculty QS Ranking indicator Rank NUTS3 Code Region name Indicator Value EIPE Rank 1 UKH12
Cambridgeshire CC 100 5 2 UKJ14 Oxfordshire 87 19 3 UKI22 Outer London-South 73 114 4 UKM25 Edinburgh, City
UKE21 York 27 63 29 ITD55 Bologna 27 76 Indicator description Indicator ID Agrd 2 Name of indicator Academic ranking of a Computer science faculty
Measures the performance of the Computer science faculty according to the academic ranking of QS Unit of measurement The highest rank of a Computer science faculty in the academic ranking Definition of ICT dimension Computer science faculty Unit of observation NUTS
3 Source QS WORLD UNIVERSITY RANKINGS by QS (see Section 8. 1) Reference year (s) considered 2011 39 Figure 23:
Frequency of the Academic Computer science faculty QS Ranking indicator values 1244 1 5 5 12 11 8 9 2 2 1 1
1 1 0 500 1000 1500 Frequency 0 20 40 60 80 100 Academic ranking of a Computer science faculty Table 16:
Descriptive statistics of the Academic Computer science faculty QS Ranking indicator Number of observations Mean value Standard deviation Variance 1303 1. 38 7. 25 52.59 40 5
. 1. 3 Employer Ranking of a Computer science Faculty Table 17: Top ranking regions according to the Employer Computer science faculty QS Ranking indicator Rank NUTS3 Code Region name Indicator Value EIPE Rank 1 UKH12
Cambridgeshire CC 100 5 2 UKJ14 Oxfordshire 95 19 3 UKI12 Inner London-East 68 2 4 UKI22 Outer London
30 GR300 Attiki 28 49 Indicator description Indicator ID Agrd 3 Name of indicator Employer ranking of a Computer science faculty What does it measure?
Measures the performance of the Computer science faculty according to the employer ranking of QS Unit of measurement The highest rank of a Computer science faculty in the employer ranking Definition of ICT dimension Computer science faculty Unit
of observation NUTS 3 Source QS WORLD UNIVERSITY RANKINGS by QS (see Section 8. 1) Reference year (s) considered 2011 41 Figure 24:
Frequency of the Employer ranking of a Computer science faculty indicator values 1244 1 3 3 12 12 11 6 6 1 1 1 2 0
500 1000 1500 Frequency 0 20 40 60 80 100 Employer ranking of a Computer science faculty Table 18:
Descriptive statistics of Employer Computer science faculty QS Ranking indicator Number of observations Mean value Standard deviation Variance 1303 1. 47 7. 63 58.27 42 5
. 1. 4 Citations Ranking of a Computer science Faculty Table 19: Top ranking regions according to the Citations Computer science faculty QS Ranking indicator Rank NUTS3 Code Region name Indicator Value EIPE Rank 1 UKL12
Gwynedd 100 266 2 PL127 Miasto Warszawa 91 50 3 NL335 Groot-Rijnmond 77 72 4 FR101 Paris 75 3
Gent 37 94 Indicator description Indicator ID Agrd 4 Name of indicator Citations ranking of a Computer science faculty What does it measure?
Measures the performance of the Computer science faculty according to the citations ranking of QS Unit of measurement The highest rank of a Computer science faculty in the citations ranking Definition of ICT dimension Computer science faculty Unit
of observation NUTS 3 Source QS WORLD UNIVERSITY RANKINGS by QS (see Section 8. 1) Reference year (s) considered 2011 43 Figure 25:
Frequency of the Citations Computer science faculty QS Ranking indicator values 1243 3 11 10 9 6 7 3 2 3 2 2
1 1 0 500 1000 1500 Frequency 0 20 40 60 80 100 Citations ranking of a Computer science faculty Table 20:
Descriptive statistics of Citations Computer science faculty QS Ranking indicator Number of observations Mean value Standard deviation Variance 1303 1. 94 9. 57 91.58 44 5
of indicator Universities ranked in the QS University ranking Academic ranking of a Computer science faculty Employer ranking of a Computer science faculty Citations ranking of a Computer science faculty R&d expenditures by ICT firms ICT FP7 funding
Measures the number of universities in QS university ranking Measures the performance of the Computer science faculty according to the academic ranking of QS Measures the performance of the Computer science faculty according to the employer ranking of QS Measures the performance
of the Computer science faculty according to the citations ranking of QS Measures the average annual amount spent on R&d in the ICT sector Measures the amount received for research in ICT R&d Unit of measurement Region's share in the total
number of EU ranked universities to a region's share in the EU population The highest rank of a Computer science faculty in the academic ranking The highest rank of a Computer science faculty in the employer ranking The highest rank of a Computer science
faculty in citations ranking Region's share in the R&d expenditures by ICT firms in the EU to a region's share in the EU population Region's share in the total EU ICT FP7 funding to a region's share in the EU population Definition of ICT dimension None Computer science faculty Based on NACE
Rev. 2 ICT areas of the FP7 programme Unit of observation NUTS 3 Source QS WORLD UNIVERSITY RANKINGS by QS (Section 8. 1) Company level information:
Orbis by Bureau Van dijk (Section 8. 7) ICT FP7 by EC DG CONNECT (see Section 8. 2) Reference year 2011 2005-2011 2007-2011
Data Sources 8. 1 QS WORLD UNIVERSITY RANKINGS by QS The Computer science and Electronic Faculties rankings originate from the QS WORLD UNIVERSITY RANKINGS,
which was formed in 2008 to meet the increasing public interest for comparative data on universities and organisations,
and the growing demand for institutions to develop deeper insight into their competitive environment. 4 The QS WORLD UNIVERSITY RANKINGS currently considers over 2,
000 and evaluates over 700 universities in the world, ranking the top 400. Like any ranking at the global level, it is constrained by the availability of data from every part of its scope.
To construct measures of faculty performance, the QS uses its proprietary datasets that enable to drill down by subject area, namely academic and employer reputation surveys and the Scopus data for the Citations per Faculty indicator in the global rankings.
These have been combined to produce the results. In detail each of the faculty ranking pieces can be described in the following way:
Academic Reputation survey is the centrepiece of the QS WORLD UNIVERSITY RANKINGS since their inception in 2004. In 2010, it drew upon over 15,000 respondents to compile the results.
In the survey, respondents are asked to identify the countries, regions and faculty areas that they have most familiarity with
and up to two narrower subject disciplines in which they consider themselves expert. For EACH of the (up to five) faculty areas they identify,
respondents are asked to list up to ten domestic and thirty international institutions that they consider excellent for research in the given area.
Employer reputation survey considers the students'employability as a key factor in the evaluation of international universities and in 2010 drew on over 5,
The employer survey works on a similar basis to the academic one only without the channelling for different faculty areas.
Citations per Faculty takes into account the size of an institution while allowing observing its penetration the global research landscape.
When aggregated together these totals per faculty and their associated citations provide an indicator of volume and quality of output in the given discipline.
Aggregation, similarly to the approach used in the overall QS WORLD UNIVERSITY RANKINGS a z-score is calculated for each indicator with the results scaled between 0 and 100
32 5. 1 QS WORLD UNIVERSITY RANKINGS by QS...32 5. 2 FP7 database by EC DG Connect...
In particular, the EIPE project builds up a measurement of ICT R&d activity by observing the actual presence of ICT technology producers (universities, companies, R&d facilities), their R&d expenditures and bibliometric data.
the EIPE project builds up this measurement by observing the level of agglomeration of technology producers (universities, companies, R&d facilities), R&d expenditures and bibliometric data.
o Computer science and engineering with respect to university faculties, o Computer science with respect to scientific publications, o ICT hardware and software with respect to R&d activity performed in R&d centres,
FP7 data on FP participation from EC DG Connect, REGPAT by OECD, QS WORLD UNIVERSITY RANKINGS by QS, Web of Science by Thomson Reuters, Design Activity Tool by IHS isuppli, European
the EIPE ID card Activity Characteristic Name of Indicator Indicator ID Nr R&d Agglomeration Universities ranked in the QS University ranking Agrd 1 1 Academic ranking of a Computer science
faculty Agrd 2 2 Employer ranking of a Computer science faculty Agrd 3 3 Citations ranking of a Computer science faculty Agrd 4 4 R&d expenditures by ICT firms
In particular, they acknowledge the importance given in EIPE to the presence and the quality of major knowledge production organisations, such as universities (and their computer science departments), private and public research centres (in particular those of multinational companies), innovative SMES
of indicator Universities ranked in the QS University ranking Academic ranking of a Computer science faculty Employer ranking of a Computer science faculty Citations ranking of a Computer science faculty R&d expenditures by ICT firms FP7 funding
Measures the number of universities in QS university ranking Measures the performance of the Computer science faculty according to the academic ranking of QS Measures the performance of the Computer science faculty according to the employer ranking of QS Measures the performance
of the Computer science faculty according to the citations ranking of QS Measures the average annual amount spent on R&d in the ICT sector Measures the amount received for research in ICT R&d Unit of measurement Region's share in the total
number of EU ranked universities to a region's share in the EU population The highest rank of a Computer science faculty in the academic ranking The highest rank of a Computer science faculty in the employer ranking The highest rank of a Computer science
faculty in citations ranking Region's share in the R&d expenditures by ICT firms in the EU to a region's share in the EU population Region's share in the total EU FP7 funding to a region's share in the EU population Definition of ICT dimension None Computer science faculty Based on NACE Rev
. 2 (see Table 1) ICT areas of the FP7 programme (see Section 5. 2) Unit of observation NUTS 3 Source QS WORLD UNIVERSITY RANKINGS by QS (see Section 5. 1
) Company-level information: ORBIS by Bureau Van dijk (see Section 5. 7) FP7 database by EC DG Connect (see Section 5. 2) Reference year (s) considered 2011 2005-2011 2007-2011 10
The performance of universities and computer science faculties across the world, as reported by the QS University ranking.
For a detailed description of the data source, see Section 5. 1. Information about the funding
1. QS WORLD UNIVERSITY RANKINGS by QS, 2. FP7 database by EC DG Connect, 3. Bibliometrics: Web of Science by Thomson Reuters, 4. ICT R&d centres locations:
each of the data source is described. 5. 1 QS WORLD UNIVERSITY RANKINGS by QS The rankings of Universities
and Computer science and Electronic Faculties originate from the QS WORLD UNIVERSITY RANKINGS. It was formed in 2008 to meet the increasing public interest in comparative data on universities and organisations,
and the growing demand for institutions to develop deeper insight into their competitive environment. 16 The QS WORLD UNIVERSITY RANKINGS currently considers over 2,
000 universities in the world and evaluates over 700 of them, ranking the top 400.
This list is used to build an indicator of the location of a ranked university in a region within the current project.
In addition due to the fact the QS ranking includes 52 subject disciplines, one of which is Computer science,
additional faculty-level information is extracted for the purpose of the EIPE study. To construct measures of faculty performance,
the EIPE study used QS proprietary datasets to investigate its subject area at three levels, namely academic and employer reputation surveys and the Scopus data for the Citations per Faculty indicator.
In detail, each of the faculty ranking pieces can be described in the following way: The Academic reputation survey is the centrepiece of the QS WORLD UNIVERSITY RANKINGS since their inception in 2004.
In 2010, it drew upon over 15,000 respondents to compile the results. In the survey, respondents are asked to identify the countries,
regions and faculty areas that they have most familiarity with and up to two narrower subject disciplines in
which they consider themselves expert. For each of the faculty areas they identify, respondents are asked to list up to ten domestic
and thirty international institutions that they consider excellent for research in the given area. They are not able to select their own institution.
The Employer reputation survey considers the students'employability as a key factor in the evaluation of international universities and in 2010 drew on over 5,
The employer survey works on a similar basis to the academic one only without the channelling for different faculty areas.
Citations per faculty takes into account the size of an institution, and also observes its penetration into the global research landscape.
When aggregated, these totals per faculty and their associated citations provide an indicator of volume and quality of output in the given discipline.
in addition to the university ranking, it also offers the rankings described above by teaching subject, including Computer science.
The main constraint is that it offers only a limited number of universities, which does not allow us to cover the entire population of the European higher education institutions. 5. 2 FP7 database by EC DG Connect The Framework Programmes for Research and Technological Development,
also called Framework Programmes or abbreviated to FP1, through to FP7, are funding programmes created by the European union
University of Technology. Ottaviano, G, . & Thisse, J.-F. 2004). Agglomeration and economic geography. In J. V. Henderson, P. Nijkamp, E s. Mills, P. C. Cheshire & J. F. Thisse (Eds.
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