Library House (2007) - An Analysis of UK University Technology and Knowledge Transfer Activities

L I B R A R Y H O U S EE S S E N T I A L I N T E L L I G E N C E

An Analysis of UK University Technology and Knowledge Transfer Activities

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About Library HouseLibrary House is a data and research company that delivers comprehensive, essential intelligence on the companies of tomorrow.

The research and consulting department at Library House has strong expertise in the analysis of the activities, performance and impact of research organisations, universities, innovation-based companies and clusters. We understand how universities, funding organisations, and industry interact through knowledge exchange and technology transfer activities and how this is embedded in policy framework. Our approach is to provide evidence-based insights and analysis in the innovation landscape. We are familiar with the state of research in all fields of innovation, data collection methods and the latest activities at both a national and international level, ensuring the delivery of comprehensive solutions for a broad number of both public and private sector clients. Underlying these strengths is a solid-driven analysis based on a proprietary dataset including extensive information on over 13,000 innovation-based companies across Europe.

Library House’s essential intelligence is accessible via our proprietary databases, daily and weekly intelligence alerts, consultancy and research services, comprehensive reports, and dynamic senior-level events.

Library House’s data and research services create competitive advantage for clients in the investment, corporate, professional services, entrepreneurial, public and academic sectors.

web: www.libraryhouse.nettel: +44 (0)1223 500 550email: [email protected]

The AuthorsMartin HoliRoger Franklin PhDEd HugoJens Lapinski PhD

For more information about the contents of this report please contact:

[email protected]

The Library House LtdKett HouseStation RoadCambridgeCB1 2JXUnited Kingdom

This report was produced in December 2006 to April 2007 and published in November 2007.

Library House is grateful for the support provided by the Gatsby Charitable Foundation.

About Library House

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Library House Track RecordSince the company was founded five years ago, Library House has assembled a world–class team of analysts, consultants and researchers who have produced internationally respected reports. Based on our work, the Library House research and consulting department is now widely regarded as an authority on analysing innovations and the related knowledge and technology transfer. Library House’s consulting and research services are the premier source of evidence-based analysis on innovation management, innovation policy, and innovation-based companies. Examples of publicly available reports are:

The Cambridge Cluster Report – The 2007 report (‘Looking Inwards, Reaching Outwards’) was sponsored by • BDO Stoy Hayward and Pure Resourcing Solutions.

The UK Venture Backed Report – 2007 (‘Funding Growth in a Changing World’) and 2006 (‘Beyond The • Chasm’). These reports were sponsored by UBS and is Library House’s benchmark annual publication on the UK Venture Capital Industry.

Venture Capital, Innovation and IT - June 2007 (‘Driving Forward the Knowledge Based Economy’). • This pan-European report on activity in the software sector was sponsored by Microsoft and publicly-launched by Microsoft’s Chief Strategy Officer.

In March 2007 we published the ‘Spinning out quality: University spin-out companies in the UK’ briefing. • We compared the efficiency of technology transfer across several top universities in the UK and US and analysed which university-level mechanisms have been able to deliver the highest efficiencies.

‘The Impact of the University of Cambridge on the UK Economy and Society’ (published June 2006). • In this study the University of Cambridge was benchmarked against leading UK and US universities. Additionally, the impact of the university’s expenditures on regional and national levels was assessed.

In November 2005, we published a report with the British Venture Capital Association (BVCA) entitled ‘Creating • Success from University Spin-outs’.

Finally, this report (‘An Analysis of UK University Technology and Knowledge Transfer Activities’) contributed to • Lord Sainsbury of Turville’s Review of Government’s Science and Innovation Policies – ‘The Race to the Top’ - that was published in October 2007.

Additionally Library House delivered valuable bespoke research projects for governmental and non-governmental departments, Regional Development Agencies, venture capital investors, business angels, universities and a range of clients from SMEs to multinational corporates.

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Contents

About Library House � � � � � � � � � � � � � � � � � � � � � iLibrary House Track Record � � � � � � � � � � � � � � iiForeword by Lord Sainsbury � � � � � � � � � � � � � � ivExecutive Summary � � � � � � � � � � � � � � � � � � � � � 1

Income Structure of Universities � � � � � � � � � � � � � � 1Collaboration with Industry � � � � � � � � � � � � � � � � � � � 1Patents and Licensing Income � � � � � � � � � � � � � � � � 1Spin-Outs � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 1High-Tech Clusters around Universities � � � � � � � � � 1

Introduction � � � � � � � � � � � � � � � � � � � � � � � � � � � 2Universities as Centres of Excellence � � � � � � � � � � 2Knowledge Transfer � � � � � � � � � � � � � � � � � � � � � � � � 2Clusters � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 2Aims of this Analysis� � � � � � � � � � � � � � � � � � � � � � � � 3

Methodology � � � � � � � � � � � � � � � � � � � � � � � � � � 3University Economic Impact Matrix � � � � � � � � � � � � 3Quantity, Quality and Efficiency of Research � � � � � 4

Data Collection � � � � � � � � � � � � � � � � � � � � � � � � 4Interviews � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 4Universities � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 4

Analysis � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 5Ranking of Universities � � � � � � � � � � � � � � � � � � � � � � 5Input into UK Universities � � � � � � � � � � � � � � � � � � � � 5UK Industrial Income � � � � � � � � � � � � � � � � � � � � � � � 7Academic Research Input of UK Universities � � � � 9Technology Transfer � � � � � � � � � � � � � � � � � � � � � � � 13Licensing � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 13Spin-Outs � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 13Efficiency in Spinning Out Companies � � � � � � � � � 14A UK/US Comparison of University Spin-Outs: Poor Quality in the UK? � � � � � � � � � � � � � � � � � � � � 15Impact of Research Quality � � � � � � � � � � � � � � � � � 18

Contents

Clusters � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 19Why are Clusters important? � � � � � � � � � � � � � � � � 19High-Tech Clusters � � � � � � � � � � � � � � � � � � � � � � � � 19Analysis of High-Tech Clusters � � � � � � � � � � � � � � � 21

University Clusters � � � � � � � � � � � � � � � � � � � � � 21Clusters and Research Quality � � � � � � � � � � � � � � � 24Investors � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 24IPOs � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 24Attractiveness of High-Tech Clusters � � � � � � � � � � 25

Conclusions � � � � � � � � � � � � � � � � � � � � � � � � � � 25References � � � � � � � � � � � � � � � � � � � � � � � � � � 26Appendix –Analysis of Potential High-Tech Regions � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 27

Cambridge � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 28Newcastle � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 28Belfast � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 28Dundee � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 29

Conclusions of Appendix � � � � � � � � � � � � � � � 31

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Foreword by Lord SainsburyIn the recent review that I produced for the Government of its science and innovation policies (The Race to the Top), I highlighted the key role played by universities, and I very much welcome the publication of “An Analysis of UK University Technology and Knowledge Transfer Activities” by Library House.

This is the first time such a comprehensive study of this type has been conducted and its primary purpose is to help everyone interested in the UK’s innovation performance to understand the important contribution UK universities make to the UK economy in terms of knowledge transfer.

In the past we had to guess how effective universities were at engaging and interacting with the business community, and how much they contribute to regional economic development. Any activity in the field of knowledge and technology transfer is very difficult to evaluate and I would like to thank Library House for taking the bold step of delivering an analysis of it.

The results are very encouraging: the analysis shows clearly that important high-tech clusters are growing up around many of our universities. There is undoubtedly, however, more that can be done to encourage the growth of these clusters, and I hope that this excellent evidence-based study will lead to an open discussion among universities, RDA’s, the Government and the business community about how they can give further support to the knowledge and technology transfer activities of universities, and in the process further advance the innovation performance of the UK economy

I also look forward to seeing more work from Library House in this field.

Lord Sainsbury

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Executive SummaryIn this report we analysed the input, output and impact of the 20 UK universities selected for this study (Table 3). Additionally we analysed the structure of the regions around these universities. This comprehensive analysis included all areas of research and commercialisation activities universities are involved in. We benchmarked the universities from a quantitative, qualitative and efficiency perspective and used indicators to evaluate the innovation competence chain. The following statements summarise our findings.

Income Structure of UniversitiesThe total annual research income (2004/2005) of all UK universities is nearly £4.2bn; the research income of the 20 selected universities is nearly £2.3bn. Compared to other industrial companies, universities can be regarded as one of the ‘industries’ which has been exceptionally successful in transforming income into economic impact.

Collaboration with IndustryIndustrial funding is subordinated to other sources of funding for universities. In total, UK universities only receive £243m from the top 850 UK most R&D active companies (DTI Scoreboard) of the £20bn spent on R&D.

All senior university management interviewed displayed a highly friendly and open attitude towards interaction with industry. However, in our experience, the attitude of academics towards industry is more varied.

All universities interact in proportion to their income with industry. There is no correlation whatsoever between the quality of research being conducted at a university and the extent of the industrial interaction of that university. All universities appear to have a similar level of industry interaction, regardless of the quality of the research being conducted.

However, the type of interaction differs. High quality research universities have a higher propensity to interact with large companies, whilst lower quality research universities focus more on the SME market.

In general, more interaction between universities and SMEs is required. The Small Business Service Agency of the DTI counted over 97,000 SME businesses with over 20 employees in the UK. This means that no more than 1% of all SMEs contributed to the industrial income of UK universities. All universities and SMEs should be encouraged to become more interested in collaborations with each other.

Collaborations with SMEs mostly require directly applicable results which involve a large part of knowledge transfer. This type of knowledge transfer between universities and companies takes places across the whole range of the university sector and is not focused on a small number of top research universities.

Industrial funding is mainly available from two industry sectors; pharmaceuticals and engineering. Therefore, any analysis of industrial income has to be seen in the context of a university’s research focus.

SMEs present manifold opportunities for all kind of research activities and the foundations for any future collaborative activities are in place.

Patents and Licensing IncomeThe number of patents filed by universities is declining. This could indicate that the technology transfer offices of universities have developed a better understanding as to which ideas are worth patenting or that there is simply less research outcome to be patented.

The analysis of licensing income shows that several universities currently do not generate enough income to cover the costs of their patenting activities.

Any analysis of efficiency in patenting has to take into account the many difficulties related to these measures. For example, the related impact measure ‘licensing income’ is influenced by the time that is needed to transfer a patent into licensing income and the fact that high licensing income is mostly related to a few or a single very successful licensing agreement.

Finally, our analysis of licensing income shows that a focused knowledge and technology transfer strategy may enable universities to deliver more efficient results.

Spin-OutsHigh quality research universities (in terms of a high RAE-ratio) spin out the majority of high quality spin-out companies (as defined by their ability to attract external funding). Even when lower quality research universities have efficient technology transfer operations, their lack of research output (i.e. publications, patents) means that they struggle to spin out a large number of quality companies.

This means that technology transfer is predominantly carried out by the high quality research universities and to a far lesser extent by all other universities.

High-Tech Clusters around UniversitiesInnovation-based companies tend to locate near the country’s top research universities.

R&D companies tend to locate near clusters of innovation-based companies (either one is dependent on the other or they both choose to locate near centres of research excellence).

The impact that this has on the region depends on the extent of other economical activity in that region.

The University of Cambridge is co-located with the largest number of venture-backed companies in the UK and has the largest percentage of these companies within its postcode district.

The University of Oxford and Imperial College are co-located with a significant number of innovation-based companies, but they are less important to the local economy as a result of significant other activity in their regions.

Executive Summary

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There is no correlation between the number of R&D companies and the total number of other, non-R&D companies, in the same area. This means that having many companies in any one area/city, does not result in the presence of many R&D companies.

However, there is a positive proportional relationship between the number of R&D companies in the vicinity of a university and the number of post-graduate students. This seems to indicate that the number of post-graduate students has a positive impact on the number of local R&D companies. This is true for all universities, regardless of their quality of research.

More importantly, there is an exponential relationship between the quality of research being conducted at a university and both the number of R&D companies and venture-backed companies around these universities. This means that high quality research universities have a disproportionately larger effect on cluster formation than lower quality research universities.

Overall, this means that high-tech/innovation clusters especially form around large research universities that conduct high quality research. This is regardless of the total size of the city surrounding this university (e.g. Cambridge Cluster).

All our analyses show that R&D and venture-backed companies locate around high quality research to a far greater extent than around lower quality research universities.

IntroductionUK universities enjoy an excellent reputation for the quality of their research and teaching but it is an open question as to how well universities transfer their intellectual output into economic impact.

In the past, several reports have been produced presenting UK universities as centres of innovation and economic growth. In 2003, a comprehensive analysis carried out by the Lambert Review of Business-University Collaboration clearly demonstrated the importance of universities to the economy. A more detailed view on the technology transfer process, which included an analysis of all UK university spin-out companies, was provided by the two reports ‘Creating Success from University Spin-Outs’ (BVCA and Library House; 2005) and the ‘UK University Spin-Out Report 2007’ (Library House; 2007).

Universities as Centres of ExcellenceThe UK government and public organisations are aware that world-class research has an important impact on the regional, national and international economy. To maximise this impact several programmes have been initiated to promote knowledge and technology transfer.

Alongside the UK’s research organisations, universities are the main source of high quality research. The work of academics, students and staff is part of the raw material required for innovation. Universities facilitate this output through different knowledge and technology transfer processes into a commercial environment. In turn, these commercial organisations turn innovations into economic growth. This economic growth then creates an impact on an individual, financial, economic and social level.

Knowledge TransferUniversity knowledge and technology transfer is the process by which universities distribute knowledge and technologies. This knowledge is distributed through a range of channels to a variety of recipients, both internal and external. Internal recipients comprise academics, staff and students, whereas external recipients include any individuals and organisations such as corporations, SMEs and non-commercial organisations.

The most important channels of knowledge transfer are:

Publishing and presenting at conferences•

Teaching on an undergraduate, graduate or executive level•

Consulting and collaborative research with external • organisations such as corporates, SMEs and non-commercial organisations

Licensing of intellectual property owned by the university•

Venturing of technology through spin-out companies • that depend on licenses or assignment of technology for initiation, from a university.

The knowledge gain enables the recipients to create a competitive advantage through new or improved products or processes. However, universities also have an impact on the knowledge of the recipient organisations and their performance (Argote & Ingram; 2000) and this enables these organisations to obtain higher profits and create additional jobs. Especially in this context, SMEs are a major part of the UK’s base of innovation and they are very important for economic growth.

University technology transfer faces the challenge that tacit information and know-how is deeply embedded in the members of the university and its internal processes. This embedded knowledge is difficult to exploit and to commercialise. (Nonaka & Takeuchi; 1995). As a result, the recipient individual or organisation demonstrates a change of knowledge or performance (Argote & Ingram; 2000). Knowledge transfer is a complex process that includes several steps from initiation to integration (Szulanski; 2000 & 1996) and can involve several different mechanisms.

University technology transfer in particular is the process that encompasses all activities associated with the identification, documentation, evaluation, protection, marketing and licensing of technology and intellectual property management.

ClustersAs an additional result of knowledge and technology transfer activities, universities can create an environment (a micro-cluster) into which innovation-based companies tend to move.

The reason for this is that, beside the internal knowledge that companies hold, their successful development depends on their ability to incorporate external knowledge. This knowledge could be acquired from within the own company, other companies, hiring skilled people, access to finance, analysis of competitors, collaborative and other formal or informal ways of knowledge exchange. Therefore companies seek proximity to


other organisations from which they can generate knowledge spillovers.

Due to the scientific nature of universities, organisations, especially R&D-intensive ones, will seek to locate close to universities. Near to universities they will find a research and knowledge base and other R&D-oriented or innovation-based companies. If this process reaches a critical mass the basis for a potential high-tech cluster can be met.

Organisations choose to locate near to universities for several reasons:

Proximity to technology creation (Galbraith; 1990)•

Proximity to strategic partners (Mahajan & Peterson; 1979) •

Neighbourhood effect (Brown; 1981)•

Better contacts and easier communication (Czepiel; 1974 / • Ghoshal & Bartlett; 1988)

To benefit from innovation diffusion (Rothwell; 1978).•

In general, organisations that adopt knowledge are more productive and have a higher survival rate than their counterparts (Argote et al.; 1990).

Aims of this AnalysisOur analysis delivers insights into the UK science base around universities and how it is locally structured. The first step was to analyse the output of universities in terms of quantity, efficiency and quality. The next step was to focus on examining the relationship between a university’s quality, and the size and location of innovation-based businesses nearby. For each university, there is a question about whether this type of micro-cluster has already been created or whether there is potential for it to happen. In response, we have developed indicators to analyse and benchmark the innovation base of these regions. Regions around universities have to be differentiated by their economic visibility and activities in their regions and the corresponding implications for the knowledge and technology transfer process have to be shown.

Our analysis has not covered all aspects of cluster formation and processes within a cluster, but it is the first comprehensive data-based analysis of UK universities based on indicators of innovation.

This report also builds on the DTI assessment of ‘Business Clusters in the UK’. According to the invitation to tender the main objective of this assessment was to “draw up a detailed systematic inventory of existing clusters across all sectors of the UK economy”. The intention was to identify what clusters exist and to map them on a nationwide basis while at the same time detailing their geographical distribution region by region (DTI; 2001, p. 12).

In this report, we focus on the relationship between universities and the local economic region. Our main interest is to identify universities and regions with existing clusters and the universities and regions that have the capability to form clusters in the future.

In this analysis we do not focus on a certain cluster topology. Instead, we present data about the structure of universities and their surrounding regions that enable stakeholders to arrive at conclusions.

The results presented in this report will contribute to several questions asked in the report ‘Science and innovation: working towards a ten-year investment framework’ published by HM Treasury, DTI & Department for Education and Skills (March 2004). Our report addresses the questions asked in the section ‘Summary of Consultation Questions’ in this report, especially those ones related to the ‘Management of the Science Base’ and the ‘Knowledge Transfer and the Lambert Review’. (HM Treasury; 2004, p. 47-48).

The evaluation of knowledge and technology transfer combined with an analysis of the surrounding regions helps the government to ensure the UK’s success in wealth creation and scientific policy-making. Our findings will enable all stakeholders to improve the support for universities and many other R&D-based organisations.

Methodology

University Economic Impact MatrixThe evaluation of universities is based on the ‘University Economic Impact Matrix’ developed by Dr. Kevin Cullen of the University of Glasgow and Library House (Table 1). This matrix enables us to quantify all significant and measurable factors. Additionally we have identified and assessed the necessary sources of data. The areas of economic impact are:

Academic Research•

Collaborative Research with Industry•

Consultancy•

Licensing•

Venturing•

Supporting Outreach Activities•

Not included in this report are questions related to the ‘Impact of Teaching’, ‘Societal Impacts’ and secondary economic effects of research, for example jobs in supplier companies and spending of academic researchers. Nor is a larger analysis of the UK-wide economic impact of the university included in this study.

Through these activities, researchers transform public and private money into knowledge and technologies. Universities receive public money in the form of funding from Research Councils and HEFCE, and private money from industrial organisations, SMEs and non-commercial organisations.

Depending on the area of activities, researchers can create different outputs. Examples of outputs include publications, patents, collaborations, spin-outs or consulting projects. How academics prioritise these areas of activity depends on how they are incentivised and on the strategy of the university.

Methodology

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Quantity, Quality and Efficiency of ResearchThe output and the related impact can be analysed in terms of quantity (e.g. numbers of publications, collaborations and spin-outs), quality (e.g. citations per publication, income from collaborations and external investment raised by spin-outs) and efficiency (e.g. research income spend per publication, patent or external venture capital investment raised).

The volume of activity is equal to the total output from the activity, for example the total number of publications is one output of research activity.

An analysis of the quality of an activity simply determines the average quality of a university’s output in each area. A qualitative analysis could also be applied to other activities, for example licensing income per patent.

Neither an analysis of volume nor quality reveals how efficient a university is at converting its financial inputs into outputs and impacts. Efficiency analyses are based on calculating ratios of outputs to inputs/impacts as defined by the ‘University Economic Impact Matrix’.

An efficiency analysis is a function of the output of the financial inputs into the activity, for example the total research income as converted into outputs by academics. In general, efficiencies can be expressed as a percentage of the best performing university. This university can be said to exhibit a practical maximum efficiency of the universities analysed.

Data CollectionAn evaluation of the innovation base of UK universities and regions requires data from a number of sources especially quantitative indicators on universities’ output and performance. Some of the required data points include:

Financials•

Publications•

Patents•

Number of citations•

Total number of licenses and licensing income•

University spin-out companies•

In general, our analysis covers the period from 2001 to 2006. In some cases, data was only available for a more limited period, for example the most recent data from the Higher Education Business and Community Interaction Survey (HEBCIS) is from 2003-2004.

InterviewsAdditionally we conducted interviews with university management, technology transfer offices, Regional Development Agencies, experts on science & technology parks and investors (Table 2).

The interviews were conducted in February and March 2007.

UniversitiesTwenty universities were selected for the analysis (Table 3). These universities account for over 50 % (£2.28bn) of the total research income of all UK universities (£4.24bn) in 2004/2005.

The selected universities reflect the full range of university activities from high ranked research universities to third stream focussed institutions.

Area Academic Research

Collaborative Research with

IndustryLicensing Venturing Consultancy

Supporting outreach activities

InputCombined input (total expenditure excluding tuition) from HESA

Conferences organised for:

- SMEs / industrial partners

- Academics - Business

representation on University board

Total research income University’s research (# publications, patents, citations)

Output # publications# patents

# contracts # licences # spin-outs # contracts

Impact (clustering

effect)# citations

Industrial incomeInterviews:

Vice-Chancellors Head of TTOs

Licensing incomeInterviews:

Vice-Chancellors Head of TTOs

# Employees Revenue

External Investment raised

Exit Values

Consultancy income

Interviews: Vice-Chancellors Head of TTOs

Table 1 – University economic impact matrix

Targeted Interviewed N.A.

Vice-Chancellors 20 17 3

Technology Transfer Offices 20 18 2

Regional Development Agencies 9 4 5

Table 2 – Overview of interviews conducted


of different ways to assess universities. However, most of the measures used are widely accepted in the field of scientometrics. The three above mentioned rankings can be used to draw a preliminary table of the research quality of the twenty universities. An initial grouping of universities by performance in these rankings is displayed in Table 4.

Input into UK Universities

Overall Income of UniversitiesThe UK has a complex system to finance Higher Education Institutes. The money is directly and indirectly distributed by different governmental and non-governmental organisations. Additionally sub-organisations are involved, before the money reaches the universities. The main organisations involved are:

UK Funding Councils (HEFCE in England)•

UK Research Councils (MRC, BBSRC etc)•

Regional Development Agencies (England)•

Industry and other commercial organisations (including contract • and collaborative research, licensing and consultancy)

Non-commercial organisations, for example charities like • the Wellcome Trust and Cancer Research UK

EU Research Programs•

Other Governmental Departments•

Analysis

Ranking of UniversitiesThere are many different ranking tables available for the initial assessment of universities. One of the most popular rankings is the ‘Academic Ranking of World Universities’ (ARWU) from the Shanghai Jiao Tong University (http://ed.sjtu.edu.cn/ranking.htm). The ARWU Ranking is based on metrics assessing alumni, awards, highly cited researchers, publications in the journals ‘Nature’ and ‘Science’, science citation index and the size of the universities.

The Times Higher Education Supplement (THES) publishes a ranking which is available online (http://www.thes.co.uk/worldrankings/). The Times Higher World University Ranking uses metrics based on the perspectives of insiders and outsiders on universities, for example peer review, recruiter review, internationalisation and different additional ratios.

Currently, the most important national research ranking for universities is the ‘Research Assessment Exercise 2001’ (RAE 2001) conducted by the different funding bodies within the UK (http://www.rae.ac.uk/). Submissions to the RAE Ranking are assessed by a panel. We calculated the ratio of departments that achieved a 5 or 5* ranking to the number of departments submitting to the RAE. The ratio is a number between 0 and 1, where one equals the maximum possible score (high research quality).

The number of published rankings reflects the great variety

University

Queen's University Belfast

University of Bristol

University of Cambridge

University of Cardiff

University of Cranfield

University of Dundee

University of Edinburgh

University of Heriot-Watt

University of Hertfordshire

Imperial College

University of Lancaster

University of Liverpool

University of Manchester

University of Newcastle

University of Nottingham

University of Oxford

University of Southampton

University of Surrey

University College London

University of York

Table 3 – The 20 selected universities and their location in the UK

Analysis

6


University RAE-Ratio 2001 ARWU 2006 Ranking

Times 2006 Ranking

University of Cambridge 0.94 2 2

University of Oxford 0.91 10 3

Imperial College 0.91 23 9

University College London 0.83 26 25

University of Manchester 0.80 50 40

University of Bristol 0.78 62 64

University of Edinburgh 0.57 52 33

University of Nottingham 0.62 79 85

University of Cardiff 0.86 151-200 141

University of York 0.78 201-300 124

University of Southampton 0.71 151-200 141

University of Newcastle 0.56 151-200 133

University of Liverpool 0.47 102-150 139

University of Lancaster 0.54 201-300 0

Queen's University Belfast 0.40 201-300 0

University of Dundee 0.36 201-300 0

University of Surrey 0.53 401-500 0

University of Cranfield 0.00 0 140

Heriot-Watt University 0.24 0 0

University of Hertfordshire 0.05 0 0

Table 4 – Universities and their performance in different rankings (Sources: RAE 2001, Times Higher World University Ranking 2006 and the Shanghai Jiao Tong University AWRU 2006)

Amount (£000s)

0

100,

000

200,

000

300,

000

400,

000

500,

000

600,

000

700,

000

Inst

itution

Heriot-Watt University

University of LancasterUniversity of Cranfield

University of HertfordshireUniversity of York

University of Dundee

University of SurreyQueen's University Belfast

University of LiverpoolUniversity of Bristol

University of NewcastleUniversity of Southampton

University of CardiffUniversity of Nottingham


Imperial CollegeUniversity College London

University of OxfordUniversity of Manchester

University of Cambridge Industrial Income

Research Income (ex-Ind)

Licensing income

Other income (including tuition)

Figure 1 – Overview of universities income (Sources: University Annual Reports, HESA and HEBCIS)


The income a university receives can be split into different types of income:

Total income – The sum of all income a university received • in a certain year.

Research income – All income earned to be used in research • activity. This includes income from research councils, industrial income and other research income.

Industrial income – The part of the research income • universities received from UK industry, commercial and public corporations.

Research income (ex-UK industry) – Research income • excluding industrial income form UK industry, commercial and public corporations.

Licensing income – Income from licensing agreements • signed with external organisations.

Other income – All other income, primarily income related • to tuition.

According to the HESA data all UK universities had an aggregate turnover of over £17.9bn in 2004/2005 (Table 5).

Figure 1 presents a graphical overview of the universities income by source.

UK Industrial IncomeIn general, industrial income reflects a university’s ability to attract commercial organisations for collaborative research and consulting projects. An analysis of the domestic industrial income should provide an insight into the importance and structure of this source of income.

Figure 2 ranks the universities by the ratio of industrial income versus total research income they receive.

The University of Cranfield generates 33.5% of its overall research income from industrial sources. For the second ranked University Heriot-Watt this figure drops down to 16% and the third ranked University of Nottingham is the last university with a two digit-percentage figure (11.8%). The average for all twenty universities is 5.99%.

It is challenging to identify the factors influencing the size of the industrial income the university received. Some of the

University Total Income

Research Income

Licensing Income

Other Income (including tuition)Total Industrial

Income

Research Income (Ex-

industrial income)

University of Cambridge 694,624 270,739 20,332 250,407 2,184 421,701

University of Manchester 539,982 191,491 7,851 183,640 260 348,231

University of Oxford 530,171 263,218 8,476 254,742 1,661 265,292

University College London 516,274 248,880 7,050 241,830 1,783 265,611

Imperial College 458,522 248,342 20,428 227,914 2,176 208,004

University of Edinburgh 401,015 153,766 4,909 148,857 1,022 246,227

University of Nottingham 320,286 92,673 10,916 81,757 1,087 226,526

University of Cardiff 314,735 100,730 6,103 94,627 411 213,594

University of Southampton 287,435 113,830 6,844 106,986 417 173,188

University of Newcastle 276,099 83,072 3,427 79,645 302 192,725

University of Bristol 262,077 99,313 6,266 93,047 269 162,495

University of Liverpool 244,742 84,442 4,219 80,223 133 160,167

Queen's University Belfast 209,634 69,845 2,357 67,488 100 139,689

University of Surrey 167,961 43,099 2,182 40,917 81 124,781

University of Dundee 154,936 56,659 3,903 52,756 1,050 97,227

University of York 150,992 53,962 1,581 52,381 56 96,974

University of Hertfordshire 138,573 5,995 311 5,684 29 132,549

University of Lancaster 125,194 34,431 731 33,700 15 90,748

University of Cranfield 135,473 44,757 15,000 29,757 191 90,716

Heriot-Watt University 94,636 24,689 3,951 20,738 2,461 67,486

Total 20 Universities: 6,023,361 2,283,933 136,837 2,147,096 15,688 3,723,931

Percentage of Total Income: 37.92% 2.27% 35.65% 0.26% 61.82%

Total all UK Universities: 17,993,162 4,242,291 243,405 3,998,886 30,951 13,719,920

Percentage of Total Income: 23.58% 1.35% 22.22% 0.17% 76.25%

Table 5 – Income of universities in £000s (Sources: University Annual Reports, HESA and HEBCIS)

Analysis

8


interviewees suggested that academics view research income generated through collaboration with industry or contract research as a ‘lower’ or ‘inferior’ form of research. This could mean that universities with an excellent research reputation or higher research income are less interested in generating industrial income.

We were therefore interested in finding out whether the proportion of research income derived from industry varied according to the quality of the research establishment.

Do better research universities aspire to attract a greater percentage of their research income from industrial sources or do they seek to avoid industrial funding because they can easily attract public money?

For a more comprehensive view we analysed the research income

of all UK universities. The average percentage of industrial income for all UK universities is 7.3%, and is 1% below the average of our study sample. Our study sample with 20 universities includes most of the large research-based universities. This could indicate that the leading research universities, which already receive a high research income, also attract more industrial income due to their excellent reputation, even if they do not see industrial income as a welcome source of income.

In a final analysis we classified every UK university that participated in the RAE 2001 into one of ten groups based on the ranking they achieved in that exercise. The percentage of research income derived from industrial sources was obtained from the HESA data for each university and averaged for each group.

The universities with a RAE-Ratio between 0.0 and 0.3 seem

University

Cran

field

Her

iot-

Wat

tNot

tingh

amIm

peria

lCa

mbr

idge

Dun

dee

Bristo

lCa

rdiff

Sout

ham

pton

Her

tfor

dshi

reSu

rrey

Live

rpoo

lNew

cast

leM

anch

este

rQue

ens

Belfa

stOxf

ord

Edinbu

rgh

York

UCL

Lanc

aste

r

% o

f Tota

l Rese

arc

h I

nco

me

0

20

40

60

80

100

Industrial Income Other Research Income

Figure 2 – Percentage of industrial income of total research income (Source: University Annual Reports & HEBCIS)

Figure 3 – RAE-Ratio versus percentage of industrial income for all UK universities (Source: HESA and RAE 2001)


to have a relatively higher percentage of industrial income. In contrast, universities with an RAE-Ratio above 0.4 seem to have an industrial income slightly below the average.

A statistical analysis shows that there is no significant difference between the amount of industrial income attracted by a university (as a percentage of its research income) and its RAE ranking. This suggests that the more prestigious UK research universities do not (or do not seek to) derive a greater proportion of their research incomes from industry compared to their less prestigious counterparts (Figure 4).

Every future analysis has to take into account that the potential industrial research income universities could generate has two main origins: The bioscience & pharmaceuticals industry and aerospace & defence industry. UK universities depend on generating the majority of their industrial income from the decisions of a few very large companies, e.g. GlaxoSmithkline, AstraZeneca and Pfizer, which account for more than 70% of total R&D expenditure in the UK. In comparison, the United States has a more diversified industrial research base.

Figures 4 and 5 correlate to the sources from which UK universities received their industrial income. Nearly 40% of total UK university industry income is targeted at the medicine and life science sector.

Academic Research Input of UK Universities

PublicationsThe major output of academic research are publications. Normally the term ‘publications’ covers a wide area of different types of output. For this study we have used publications and world patents as a proxy for research output.

The number of publications can be regarded as a proxy for the quantity of research produced by the university. To add an impact dimension, publications can be assessed by the number of citations they receive (Tables 7 and 8).

The total number of citations accrued was collected for the period 2001-2006. Recent years have lower citation numbers because papers typically receive an increasing number of citations over time. The search terms used to collect these data were identical to those used to collect the number of publications.

CollaborationsWe collected the data on collaborations from the HEBCIS ‘data by institution’ spreadsheet available on the HEFCE website.

The HEBCIS data offer a detailed overview on the different income from large companies, SMEs and non-commercial organisations (Table 9).

In total the 20 universities generated a total value of £2m from 7,675 collaborations.

The 20 universities generated over 60% of the value through collaborations with large corporations, followed by 32% from non-commercial organisations. The value of collaborations with SMEs only counts for about 8% of the total value generated by these universities.

In terms of number of projects, the picture is similar. Large companies count for the majority of projects (65%), followed by non-commercial (32%) organisations and SMEs (13%).

But this also means that the average value of a project with a SME is, in comparison to the value of projects with large companies and non-commercial organisations, higher than many would expect. The ratio between the average values of one SME project

UK

US

% T

ota

l

0

10

20

30

40

50

60

70

80

90

100 Aerospace

Automotive

Chemicals

Electronics

Pharma

IT Hardware

IT Software

Other

Figure 4 – Industrial R&D expenditues in the UK and the US (Source: DTI and FedStats)

Arts

& H

um

anitie

s

Medical & B

iosc

ience

Chem

istry

Physics

Mate

rial Science

Math

em

atics IT

Managem

ent Stu

die

sEngin

eering

Oth

er Science

Oth

er

% U

K I

ndustr

y I

ncom

e

0

5

10

15

20

25

30

35

40

Figure 5 – Distribution of industrial income for UK universities (Source: HESA)

Analysis

10


Number of Publications

University 2001 2002 2003 2004 2005 2006 Total

Queen's University Belfast 2,604 2,595 2,803 2,892 2,989 2,730 16,613

University of Bristol 2,544 2,737 2,723 2,804 2,932 2,832 16,572

University of Cambridge 5,315 5,425 5,688 6,006 5,851 5,706 33,991

University of Cardiff 705 693 640 672 1,508 1,867 6,085

University of Cranfield 339 329 372 441 457 454 2,392

University of Dundee 1,074 1,036 1,054 1,116 1,066 996 6,342

University of Edinburgh 2,603 2,664 2,736 3,042 3,147 2,918 17,110

University of Heriot-Watt 452 436 437 364 463 437 2,589

University of Hertfordshire 229 215 264 175 260 305 1,448

Imperial College 3,874 4,247 4,430 4,981 4,999 4,753 27,284

University of Lancaster 724 712 682 820 793 919 4,650

University of Liverpool 2,116 2,072 2,250 2,342 2,313 2,317 13,410

University of Manchester 3,370 3,531 3,624 3,828 4,302 4,356 23,011

University of Newcastle 2,209 2,393 2,510 2,563 2,711 2,593 14,979

University of Nottingham 2,202 2,177 2,266 2,277 2,467 2,431 13,820

University of Oxford 5,313 5,498 5,286 5,797 5,790 5,751 33,435

University of Southampton 2,145 2,271 2,327 2,395 2,488 2,357 13,983

University of Surrey 911 895 883 985 970 897 5,541

University College London 3,805 3,934 4,017 4,371 4,853 4,755 25,735

University of York 1,876 1,847 1,838 2,061 2,278 2,247 12,147

Year's total: 46,411 47,709 48,833 51,936 54,642* 53,627* 291,137

Year's increase — 2.80 2.36 6.35 5.21 N.A. —

Table 7 – Number of publications from 2001- 2006 (* Figures for these years are still increasing)

Number of Citations

University 2001 2002 2003 2004 2005 2006 Total

Queen's University Belfast 23,526 22,036 17,951 12,099 6,915 1,213 83,740

University of Bristol 29,718 26,732 19,915 14,235 7,725 1,277 99,602

University of Cambridge 86,279 73,525 56,842 41,238 21,506 4,417 283,807

University of Cardiff 7,365 7,016 4,029 3,155 3,302 950 25,817

University of Cranfield 1,839 2,051 1,418 1,136 653 121 7,218

University of Dundee 15,335 13,738 10,715 7,599 4,260 689 52,336

University of Edinburgh 35,319 34,653 25,355 17,567 9,977 1,702 124,573

University of Heriot-Watt 2,303 2,169 1,973 1,144 425 119 8,133

University of Hertfordshire 1,704 1,947 2,197 739 803 292 7,682

Imperial College 57,761 54,699 46,527 31,384 15,659 2,903 208,933

University of Lancaster 6,407 4,566 3,789 3,219 1,553 489 20,023

University of Liverpool 21,571 18,688 14,131 10,907 5,716 1,158 72,171

University of Manchester 35,937 30,089 25,710 18,857 9,968 2,298 122,859

University of Newcastle 21,012 20,598 15,458 11,530 6,083 1,204 75,885

University of Nottingham 20,879 17,881 13,624 9,682 5,624 863 68,553

University of Oxford 84,036 72,948 49,998 38,266 20,910 4,323 270,481

University of Southampton 23,143 20,688 16,449 10,345 5,173 965 76,763

University of Surrey 6,007 5,362 4,015 3,086 1,442 285 20,197

University College London 56,940 46,623 36,031 27,002 14,302 2,632 183,530

University of York 16,897 15,500 10,733 8,852 5,323 1,301 58,606

Year's total: 555,979 493,511 378,863 274,046 149,324* 31,207* 1,870,909

Table 8 – Citations the 20 universities received from 2001-2006 (* Figures for these years are still increasing)


Collaborative Research Contracts

University Total Value (£000s)

# with SMEs

Value with

SMEs (£000s)

# with Large

Companies

Value with Large Companies

(£000s)

# with Non-Commercial

Organisations

Value with Non-Commercial

Organisations (£000s)

Imperial College 47,300 1 11 931 31,929 496 15,360

University College London 28,109 65 822 438 10,797 427 16,490

University of Oxford 22,356 180 1,700 330 19,000 372 1,656

University of Cambridge 19,099 82 2,710 466 16,389 – –

University of Southampton 18,573 174 2,446 292 5,394 313 10,733

University of Bristol 16,326 37 2,689 196 4,697 324 8,940

University of Newcastle 14,814 26 1,039 69 4,125 – 9,650

University of Dundee 13,764 36 413 189 7,048 274 6,303

University of Cranfield 13,412 62 1,056 132 12,356 – –

University of Nottingham 11,280 45 1,192 334 8,844 47 1,244

University of Surrey 9,859 1 10 93 4,300 26 5,549

University of Manchester 8,478 38 983 150 3,749 68 3,746

University of Edinburgh 6,028 40 710 8 5,318 – –

University of Liverpool 5,475 88 1,086 242 4,389 – –

Queen's University Belfast 4,904 69 1,594 59 2,097 26 1,213

University of Cardiff 4,749 19 326 196 4,423 – –

University of Heriot-Watt 3,776 – – – 3,776 – –

University of York 2,348 6 95 60 2,253 – –

University of Lancaster 1,626 15 152 100 1,047 29 427

University of Hertfordshire 116 3 97 1 19 – –

Total 252,392 987 19,131 4,286 151,950 2,402 81,311

Table 9 – Number and value of collaborations SMEs, large companies and non-commercial organisations (Source: HEBCIS)

University Average Value of Contract (£000s) with SME

Average Value of Contract (£000s) with Large Companies

Average Value of Contract (£000s) with Non-

Commercisal Organisations

Queen's University Belfast 23.10 35.54 46.65

University of Bristol 72.68 23.96 27.59

University of Cambridge 33.05 35.17 N/A

University of Cardiff 17.16 22.57 N/A

University of Cranfield 17.03 93.61 N/A

University of Dundee 11.47 37.29 23.00

University of Edinburgh 17.75 664.75 N/A

University of Heriot-Watt N/A N/A N/A

University of Hertfordshire 32.33 19.00 N/A

Imperial College 11.00 34.30 30.97

University of Lancaster 10.13 10.47 14.72

University of Liverpool 12.34 18.14 N/A

University of Manchester 25.87 24.99 55.09

University of Newcastle 39.96 59.78 N/A

University of Nottingham 26.49 26.48 26.47

University of Oxford 9.44 57.58 4.45

University of Southampton 14.06 18.47 34.29

University of Surrey 10.00 46.24 213.42

University College London 12.65 24.65 38.62

University of York 15.83 37.55 N/A

Table 10 – Average value of the contracts with SMEs, large companies and non-commercial organisations (Source: HEBCIS)

Analysis

12


(£19.38k) to the average value of one project with a large company (£35.45k) is 1.83 (Table 11).

PatentsPatent publications are considered as an alternative output of research activity with a commercial focus. Therefore, patents are simply another form of publication and are included in the output analysis of the research activities.

We have used world patents in this analysis because this designation indicates that the university places a high value on the material being published.

Patents were collected from the European Patent Database (eponline). Searches were for the university as an applicant, the year of publication and a world patent designation. Data was collected for the years 2001-2006 inclusive (Table 12).

Variations between data obtained from the EPO and UKPO Esp@cenet service have been observed. On closer examination these differences appear to be the result of typographical errors. The search terms used were carefully chosen to ensure that all relevant patents were collected.

The data collection was focused on world patents. We have to assume that some universities may prefer to file non-world patents primarily on a national level. Therefore these patents would not be included in our analysis. Patent publication policy varies widely between universities and may not be reflective of research output or even of commercially applicable research output. From this perspective there is no additional value in analysing the efficiency of patent publications.

Table 13 summaries the output of academic research for the 20 universities.

Number (#) Total Value (£000s)

Average Value of Contract (£000s)

SMEs 987 19,131 19.38

Large Companies 4,286 151,950 35.45

Non-Commercial Organisations 2,402 81,311 33.85

Total 7,675 252,392 32.88

Table 11 – Total number, total value and average value of collaborations (Source: HEBCIS)

Number of World Patents

Universitiy 2001 2002 2003 2004 2005 2006 Total

Queen's University Belfast 3 13 8 8 13 10 55

University of Bristol 26 27 15 16 6 4 94

University of Cambridge 20 36 33 47 45 38 219

University of Cardiff 13 4 12 11 9 14 63

University of Cranfield 5 5 7 6 7 9 39

University of Dundee 5 12 13 9 8 6 53

University of Edinburgh 7 10 12 8 10 16 63

University of Heriot-Watt 0 4 1 5 9 6 25

University of Hertfordshire 1 2 2 0 1 0 6

Imperial College 32 42 35 41 35 27 212

University of Lancaster 0 0 1 5 2 1 9

University of Liverpool 6 3 10 12 6 5 42

University of Manchester 22 10 15 12 15 9 83

University of Newcastle 2 1 4 1 9 6 23

University of Nottingham 20 7 19 12 13 7 78

University of Oxford 53 61 64 52 39 32 301

University of Southampton 11 12 18 15 21 8 85

University of Surrey 7 6 8 13 6 6 46

University College London 28 32 27 17 10 6 120

University of York 5 4 9 8 17 8 51

Year's total: 266 291 313 298 281 218 —

Year's increase — 9.40 7.56 -4.79 -5.70 -22.42* —

Table 12 – Overview of world patents filed by the 20 universities (* Figure for 2006 is still increasing� Source: European Patent Database)


Technology TransferA Technology Transfer Office (TTO) is a university team, office or department, or private or public company, that undertakes all activities associated with the identification, documentation, evaluation, protection, marketing and licensing of technology and intellectual property.

Most technology transfer initiatives started in the late 1990s or at the beginning of this century.

Over the last few years, universities have developed different approaches to transforming academic research into applied technology.

The strategy of TTOs is embedded in the overall research strategy of the universities.

University technology transfer is, in general, organised in one of the following ways (Table 14):

LicensingThe license income received by each of the UK comparator universities was analysed for the academic year 2003/2004.

A measure to analyse the efficiency of converting knowledge into licensing income can be obtained by dividing the licensing income by the number of publications for each university and expressing the ratio as a percentage of the top performing university (Figure 5).

Heriot Watt University was excluded from this analysis due to its high ‘license income’ from selling educational materials.

Spin-OutsSpin-out companies (including the amount of external investment attracted) from each university were identified from Library House VenturePedia database and Technology Transfer Office (TTO) websites.

In addition, the incorporation date of each company was obtained either from VenturePedia, Companies House or other sources.

Data was incomplete in the sense that not all venture capital or other deals are disclosed and those that are disclosed often do not disclose the amount of the investment. To control for this in our analysis, the percentage of deals with undisclosed amounts was calculated for each UK university.

University Publications Citations Cits/Pubs Patents

University of Bristol 16,572 99,602 6.01 94

University of Cambridge 33,991 283,807 8.35 219

University of Cardiff 6,085 25,817 4.24 63

University of Cranfield 2,392 7,218 3.02 39

University of Dundee 6,342 52,336 8.25 53

University of Edinburgh 17,110 124,573 7.28 63

University of Heriot-Watt 2,589 8,133 3.14 25

University of Hertfordshire 1,448 7,682 5.31 6

Imperial College 27,284 208,933 7.66 212

University of Lancaster 4,650 20,023 4.31 9

University of Liverpool 13,410 72,171 5.38 42

University of Manchester 23,011 122,859 5.34 83

University of Newcastle 14,979 75,885 5.07 23

University of Nottingham 13,820 68,553 4.96 78

University of Oxford 33,435 270,481 8.09 301

Queen's University Belfast 16,613 83,740 5.04 55

University of Southampton 13,983 76,763 5.49 85

University of Surrey 5,541 20,197 3.65 46

University College London 25,735 183,530 7.13 120

University of York 12,147 58,606 4.82 51

Total: 291,137 1,870,909 — 1,667

Average: 14,557 93,545 6.43 83.35

Table 13 – Summary of research performance

Organisational Form Number

Team within a University Department 8

Wholly Owned Limited Company 5

Department within the University 3

Public Limited Company 1

Table 14 – Organisational form of the Technology Transfer Offices (Source: Library House, March 2007) (n=17)

Analysis

14


VenturePedia includes data on revenue and number of employees. This data was aggregated with similar data available from Companies House filings. In addition, companies about which VenturePedia had limited information were contacted in order to establish the employee number and revenue figures.

The number of spin-outs acquired or floated was collected from VenturePedia and other sources (company websites). Acquisition values and market capitalisations were collected, where possible, from VenturePedia, company websites and the London Stock Exchange.

Efficiency in Spinning Out CompaniesThe assumption behind this efficiency analysis is that research income represents the major input into a university’s research activities. The major output from research is publications. Additionally technology transfer aims to facilitate the conversion of the knowledge generated by research into economic impact through the formation of spin-out companies.

The efficiency of this process can be measured by comparing external investment attracted by spin-out companies (a proxy for spin-out quality) with the research output, publications.

Only spin-outs formed after January 1st 2001 were included in the analysis to reduce bias in favour of those universities with older technology transfer operations.

Dundee

Cra

nfield

Imperial

Nottin

gham

UCL

Card

iff

Cam

bridge

Edinburg

hOxfo

rd

South

am

pto

nNewca

stle

Hertfo

rdsh

ire

Brist

ol

Surrey

Manch

est

er

Liverp

ool

Queens

Belfast

York

Lanca

ster

Rela

tive t

o T

op P

erf

orm

er

0

10

20

30

40

50

60

70

80

90

100

Figure 6 – Ratio of licensing income to number of publications (Source: HEBCIS)

University Total University Income (£000s)

Licensing Income (£000s)

Licensing Income of Total

Income (%)

Avg. number of World Patents

(2001-2006)

Avg. Income per World Patent

(£000s)

Queen's University Belfast 209,634 100 0.05% 9 10.91

University of Bristol 262,077 269 0.10% 16 17.17

University of Cambridge 694,624 2,184 0.31% 37 59.84

University of Cardiff 314,735 411 0.13% 11 39.14

University of Cranfield 135,735 191 0.14% 7 29.38

University of Dundee 154,936 1,050 0.68% 9 118.87

University of Edinburgh 401,015 1,022 0.25% 11 97.33

University of Heriot-Watt 94,636 2,461 2.60% 4 590.64

University of Hertfordshire 138,573 29 0.02% 1 29.00

Imperial College 458,522 2,176 0.47% 35 61.58

University of Lancaster 125,194 15 0.01% 2 10.00

University of Liverpool 244,742 133 0.05% 7 19.00

University of Manchester 539,982 260 0.05% 14 18.80

University of Newcastle 276,099 302 0.11% 4 78.78

University of Nottingham 320,286 1,087 0.34% 13 83.62

University of Oxford 530,171 1,661 0.31% 50 33.11

University of Southampton 287,435 417 0.15% 14 29.44

University of Surrey 167,961 81 0.05% 8 10.57

University College London 516,274 1,783 0.35% 20 89.15

University of York 150,992 56 0.04% 9 6.59

Total / Average: 6,023,36 15,688 0.26% 278 56.47

Table 15 – Overview of licensing income (Sources: European Patent Database and HEBCIS)


In Figure 7, the total investment attracted by a university’s spinout companies (formed between 2001 and 2006) is compared to the research output of the university (number of publications over the same period). The ratio is expressed as a percentage of the top performing university for clarity.

Figure 8 compares the total investment attracted by a university’s spin-out companies (formed between 2001 and 2006) with the total research income a university receives. The ratio is expressed as a percentage of the top performing university for clarity.

The universities are ranked (from left to right) in terms of their performance in the analysis in Figure 7. Hence universities performing worse than their neighbours in this analysis may have efficient technology transfer operations but are less efficient at converting research income into publications.

In a third analysis (Figure 9), we analysed the efficiency of transferring knowledge into venturing. The venturing output is defined as the number of employees and amount of external investment attracted. This information was collected for

each spin-out company. The sum of these numbers for each university was divided by the number of publications generated and the ratio expressed as a percentage of the best performing university. The mean is the average of these values for each university across investment and employment measures.

A UK/US Comparison of University Spin-Outs: Poor Quality in the UK?(This chapter was originally published in the Library House Report: ‘Spinning out quality: University spin-out companies in the UK, 2007’).

Many stakeholders in the field of technology transfer have suggested that UK spin-outs are of poor quality when compared to their US counterparts. The key question is how one arrives at the conclusion that the UK spin-out portfolio is ‘poor quality’. Poor quality compared to what? There are few other countries which have significant activity in this area and so can serve as fair comparators. What is actually meant when critics say the

UniversityNo.

Spin-Out Companies

Venture-backed

spin-outs

Total Institutional

Funding Received (£000s)

Average Institutional Funding per

venture-backed

company

Total No. of Institutional

Deals

Public Companies

Market Cap (05/03/01)

No. Companies

Acquired

Total value of

companies at

acquisition (£000s)

Queen's University Belfast

6 5 7,547 1,509 9 0 – 0 –

University of Bristol 17 10 20,635 2,064 22 0 – 0 –

University of Cambridge

30 20 110,290 5,515 61 0 – 1 30,000 (e)

University of Cardiff 6 6 1,672 279 11 0 – 0 –

University of Cranfield 2 1 546 546 1 0 – 0 –

University of Dundee 6 1 575 575 1 1 20,562 0 –


26 15 14,040 936 21 0 – 0 –

Heriot-Watt University 10 2 3,165 1,583 5 0 – 1 undisclosed

University of Hertfordshire

1 0 0 N/A 0 0 – 0 –

Imperial College 29 19 39,250 2,066 32 1 132,436 1 8,000

University of Lancaster

1 0 0 N/A 0 0 – 0 –

University of Liverpool

3 1 350 350 1 0 – 0 –

University of Manchester

14 7 4,708 673 12 0 – 1 undisclosed

University of Newcastle

11 4 17,010 4,253 9 0 – 0 –

University of Nottingham

9 4 2,340 585 5 0 – 0 –

University of Oxford 24 18 41,505 2,306 36 1 54,739 0 –

University of Southampton

11 9 22,290 2,477 16 2 61,256 1 undisclosed

University of Surrey 9 4 695 174 6 0 – 0 –

University College London

9 6 25,580 4,263 6 0 – 2 undisclosed

University of York 9 5 1,270 254 7 0 – 1 4,800

Total 233 137 313,468 2,288 261 5 268,993 8 —

Table 16 – Overview of spin-outs activity (Sources: Library House and London Stock Exchange)

Analysis

16


Cam

bridge

South

am

pto

nIm

perial

Heriot W

att

Cra

nfield

Oxfo

rdBrist

ol

Newca

stle

Edinburg

hUCL

Dundee

Manch

est

er

Surrey

Queens

Belfast

Card

iff

York

Nottin

gham

Hertfo

rdsh

ire

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ool

Rela

tive t

o T

op P

erf

orm

er

0

10

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30

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80

90

100

Figure 8 – Ratio between financial input into academic research and spin-outs investement attracted (Source: HEBCIS and Library House)

Cam

brid

geSo

utha

mpt

onHer

iot-

Wat

tNew

cast

leIm

peria

lQue

ens

Surr

ey

Oxf

ord

Bristo

lEd

inbu

rgh

Man

ches

ter

Live

rpoo

lCr

anfie

ld

UCL

Dun

dee

Her

tfor

dshi

re

York

Card

iffNot

tingh

amLa

ncas

ter

Rela

tive

to T

op P

erf

orm

er

0

10

20

30

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60

70

80

90

100

Investment Employment Mean

Figure 9 – Efficiency in transferring public knowledge into spin-outs (Source: Library House)

Cam

bridge

South

am

pto

nIm

perial

Heriot W

att

Cra

nfield

Oxfo

rdNewca

stle

Brist

ol

Edinburg

hUCL

Dundee

Manch

est

er

Surrey

Queens

Belfast

Card

iff

York

Nottin

gham

Lanca

ster

Hertfo

rdsh

ire

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ool

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tive t

o T

op P

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orm

er

0

10

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30

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60

70

80

90

100

Figure 7 – Ratio between research output and spin-outs investment attracted (Source: Library House)


portfolio is poor quality is that it is worse than in the US. It is our opinion that this value judgement derives from a perception based knowledge of a few very successful spin-out companies formed from US universities. It is of course true that Stanford and Harvard have spun out truly world beating companies such as Google and Sun Microsystems and have been associated with other companies like Yahoo (a graduate start-up from Stanford). However, in order to fairly compare the US and UK spin-out portfolios a broader and more quantitative analysis is required.

To do this we selected three top US universities for study and compared their spin-out portfolios with a cross section of UK universities. In the US we chose:

Stanford University – historically recognised to have • produced the world’s top spin-out companies and located at the heart of Silicon Valley the world’s most active venture capital market.

University of Wisconsin at Madison – the world’s 16th best • research university according to the Shanghai Ranking system and with a technology transfer operation dating back to 1925.

University of Washington, Seattle – the world’s 17th best • research university and located in a state which receives over four times as much venture capital finance per head as the UK and their UK counterparts since 2001. We then determined the amount of external investment each of these companies attracted as a proxy for quality.

Following this data collection we calculated the aggregate external investment that the spin-out companies of each university collectively attracted. In addition we calculated the average amount of external investment each spinout company received.

As shown in Figure 10, although Stanford University spin-outs attracted the most funding, most of the UK universities studied performed better by this measure than both Washington and Wisconsin.

This suggests that, in terms of how spin-out companies are viewed by investors, the UK spin-out portfolio is not of a generally poor quality. Instead, UK universities are generating companies of a quality substantially higher than would be expected from their worldwide research ranking. Perhaps the most striking example of this is Southampton University which comes third in this analysis despite being ranked over 100 places lower than both Washington and Wisconsin in the Shanghai Jiao Tong Ranking system. At the high end, it is interesting to note that Cambridge University spin-out companies managed to attract over half the aggregate investment of Stanford spin-outs. Given that Stanford is classically seen as the world’s most prolific source of innovation-based companies and is located in a state which receives over eight times as much venture capital per head as the UK, this is a significant achievement. These data suggest that UK universities are exceptionally efficient at commercialising their research- at least by the venturing mechanism.

The efficiency of technology transfer- derived from the ratio of external investment in spin-out companies to research output (number of publications)- was determined for each of the three US universities selected and a cross section of UK universities. The results of this analysis (Figure 11) shows that UK universities are in general more efficient than two of the three selected US universities in venturing activity- in other words they are more effective at converting their basic research into investable ventures. Overall, our analysis refutes the suggestion that the UK spin-out portfolio is poor quality- even in comparison to the US. It also suggests that UK universities are generally very efficient at converting research into spin-out companies.

Stan

ford

Cam

brid

ge

Impe

rial C

olle

geOxf

ord

Sout

ham

pton

UCL

Was

hing

ton

Bristo

lEd

inbu

rgh

New

cast

leM

anch

este

rW

isco

nsin

Belfa

st

Inve

stm

ent

Att

ract

ed (

£m

)

0

50

100

150

200

250

300

World Rank: 3 2 23 10 175 26 17 62 52 176 50 16 225

Figure 10 – External Investment per University (Source: Library House)

Stan

ford

Cam

brid

geSo

utha

mpt

onIm

peria

lOxf

ord

New

cast

leBr

isto

lEd

inbu

rgh

UCL

Man

ches

ter

Was

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Belfa

stW

isco

nsin

Rel

ativ

e to

Top P

erfo

rmer

0

10

20

30

40

50

60

70

80

90

100

Figure 11 – Venturing Efficiency (Source: Library House)

Analysis

18


In both cases we see that the universities with a higher research quality (in terms of the proxies used) attract more income from large corporations (Figures 12 and 13) and that their spin-outs receive more capital (Figures 14 and 15). In contrast, the other universities with lower research quality collaborate more with SMEs.

Impact of Research QualityTo give a measure of the university’s quality, we determined the average number of citations per publication (Figures 12 and 14) and the RAE-ratio for each institution (Figures 13 and 15). This proxy for research quality was plotted against the total value of collaborations (by type) and the aggregate external investment in spin-out companies.

Mean Citations per Publication

3 4 5 6 7 8 9

Aggre

gate

Exte

rnal In

vestm

ent

in S

pin

-Out

Com

panie

s

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

Figure 14 – Correlation between publication quality and investment in spin-outs (Source: Library House)

RAE Ratio

0.0 0.2 0.4 0.6 0.8 1.0

Aggre

gate

Exte

rnal In

vestm

ent

in S

pin

-Out

Com

panie

s

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

Figure 15 – Correlation between investment and RAE ratio in spin-outs (Source: Library House)

RAE Ratio

0.0 0.2 0.4 0.6 0.8 1.0

Tota

l Val

ue

of

Colla

bora

tions

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Value with SMEs


Figure 13 – Correlation between industry collaboration and RAE ratio (Source: HESA)

Mean Citations per Publication

3 4 5 6 7 8 9

Tota

l Val

ue

of

Colla

bora

tions

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Value with SMEs


Figure 12 – Correlation between publication quality and industrial collaboration income (Source: HESA)


Clusters

Why are Clusters important?Alfred Marshall (Marshall; 1920) stated that clusters are important because they provide access to a local pool of specialised labour, allow the sharing of investment into infrastructure, and make it easier for companies and individuals to generate and share new ideas.

According to Michael E. Porter (Porter; 1990) clusters offer several advantages for the economic development of a region:

Increased productivity within the cluster•

Increased innovation (new and better ways of production • and distribution of new or better products and services)

The creation of more businesses•

Clusters are very important for industries that need access to R&D, university research and skilled labour (Audretsch & Feldman; 1996). They are strong and competitive regions of innovation which create a rise in productivity. So in general a cluster is a geographic concentration of companies with strong linkages to financial, funding, governmental and academic institutions and to each other, embedded in an infrastructure (Bekar et al.; 2002).

Additionally many studies have been published analysing the

role of knowledge and related spillovers (e.g. Keppler; 2000). A cluster’s spatial proximity (Bathelt et al.; 2002) enables easier interactions among the stakeholders within the cluster. These interactions result in more interactions, trust, easy observations and learning. Therefore a cluster is a region with enough resources and competences to reach a critical threshold and develop a key position, which leads to a sustainable competitive advantage for the whole cluster.

New cluster theories are switching focus from industrial-based measures (supply chains, costs advantages, number of jobs) to knowledge-based measures (Bathelt et al.; 2002) where knowledge is seen as the main factor in creating economic benefits. The theory of clusters is related to the concept of ‘Regional Innovation Systems’ (Cooke et al., 2004). As such, there is a stronger focus on innovation and on the way the research system and the regulations for immaterial property rights are organised from the regional innovation systems perspective rather than the cluster perspective (Saxenian; 1996).

High-Tech ClustersHigh-tech clusters are regions regarded as the spots where innovations happen. Many high-tech industries are located in these clusters and these companies generate a significant innovative output. These high-tech clusters are regularly formed in regions where knowledge can be transferred from one link on the cluster competence chain to the next. In high-tech clusters a specific mix of companies, services and organisations can be found:

University FPC3Total

Number of Companies

R&D Comp.

% R&D Comp. of all Comp.

Venture-Backed Comp.

% VC-backed

Comp. of all Comp.

% of VC-backed

Comp. of all R&D Comp.

VC-Backed

Spin-Outs in Cluster

%-Spin-Outs of all VC-

Backed Comp.

% of VC-backed


Belfast BT 5,406 46 0.85% 43 0.80% 93.48% 12 27.91% 25.29%

Bristol BS 23,053 140 0.61% 40 0.17% 28.57% 10 25.00% 48.22%

Cambridge CB 9,239 293 3.17% 160 1.73% 54.61% 30 18.75% 39.32%

Cardiff CF 15,299 111 0.73% 36 0.24% 32.43% 8 22.22% 21.43%

Cranfield MK 13,072 88 0.67% 11 0.08% 12.50% 1 9.09% 65.69%

Dundee DD 3,692 31 0.84% 14 0.38% 45.16% 3 21.43% 26.58%

Edinburgh & HW EH 15,602 145 0.93% 82 0.53% 56.55% 19 23.17% 17.76%

Hertfordshire AL 9,375 27 0.29% 6 0.06% 22.22% 0 0.00% 43.45%

Imperial SW 34,863 197 0.57% 115 0.33% 58.38% 20 17.39% 13.27%

Lancaster LA 6,967 37 0.53% 1 0.01% 2.70% 0 0.00% 25.23%

Liverpool L 21,732 79 0.36% 24 0.11% 30.38% 3 12.50% 28.70%

Manchester M 24,745 117 0.47% 54 0.22% 46.15% 8 14.81% 23.70%

Newcastle NE 16,005 108 0.67% 36 0.22% 33.33% 5 13.89% 11.36%

Nottingham NG 20,628 107 0.52% 24 0.12% 22.43% 5 20.83% 16.67%

Oxford OX 15,518 270 1.74% 91 0.59% 33.70% 27 29.67% 44.37%

Southampton SO 16,907 113 0.67% 25 0.15% 22.12% 10 40.00% 22.22%

Surrey GU 71,347 174 0.24% 48 0.07% 27.59% 4 8.33% 67.39%

UCL WC 16,016 102 0.64% 73 0.46% 71.57% 6 8.22% 2.70%

York YO 10,925 66 0.60% 19 0.17% 28.79% 8 42.11% 35.48%

Total 350,391 2,251 0.64% 902 0.26% 40.07% 179 19.84% 32.12%

Table 17 – VC-backed and R&D companies around universities based on a postcode analysis (Sources: Library House and FAME)

Clusters

20


Number of Residents per City

100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000

Num

ber

of

R&

D C

om

panie

s

0

50

100

150

200

250

300Cambridge

Oxford

Guildford

Reading

Southampton

Queens Belfast

York

Dundee

Edinburgh & Heriot Watt

Newcastle

Coventry

Manchester

NottinghamCranfield

Derby

Lancaster

Bristol

Cardiff

Hertfordshire

Stoke-on-Trent

Leicester

Birmingham

Sheffield

LiverpoolLeeds

Dudley

Bradford

Figure 17 – Comparison between city size and number of R&D companies (Source: Library House)

Number of Residents per City

100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000

Num

ber

of

Ventu

re-B

acked C

om

panie

s

0

20

40

60

80

100

120

140

160

180

Cambridge

Oxford

Guildford

Reading

Southampton

Queens Belfast

YorkDundee


Newcastle

Coventry

Manchester

Nottingham

Cranfield

DerbyLancaster

Bristol

Cardiff

Hertfordshire

Stoke-on-Trent

Leicester

Birmingham

SheffieldLiverpool Leeds

Dudley

Bradford

Figure 16 – Comparison between city size and number of venture-backed companies (Source: Library House)


Basic research infrastructure•

R&D-based companies and innovation-based companies•

Supply of risk capital•

The cluster competence chain clearly demonstrates that universities are a very important factor in the formation of clusters. Additionally, companies benefit from the local infrastructure, access to an excellent labour market with educated and well trained specialists and therefore lower skilled staff search costs, access to a pool of service providers and supporting activities, and the creation of technology spillover which leads to economics of agglomeration. For these effects to take place, clusters also need research institutes, service providers, including consulting, market research and testing services, and financing support, including venture capitalists and business angels.

Analysis of High-Tech ClustersThe economic goal for regions should be a high and rising standard of living. This depends upon creating a high-quality business environment that fosters innovation and rising productivity. Strong and competitive clusters are a critical component of a good business environment and are the driving force behind regional innovation and rising productivity. The prosperity of a high-tech region depends on the productivity of its industries. Productivity does not depend on the industries a region competes in, but on how it competes.

In our first analysis of clusters we studied the relationship between the sizes of UK cities (residents) and number of venture-backed companies. This was done to investigate any possible influence of city size on the analysis. The graph does not display London, to improve the clarity of the graph (Figure 16).

There is no relationship between the size of UK cities and the number of companies that received venture capital or the number of R&D companies located nearby. For example, the smaller cities of Cambridge, Oxford, Reading and Guildford include over 30% of all venture backed companies in this sub-sample.

We analysed the same picture for the size of the cities and the number of R&D companies (Figure 17).

University ClustersUniversities are one of the driving forces behind innovation in clusters. Universities can promote innovation and entrepreneurship not only by spinning out companies but also by creating an environment (micro-cluster) into which innovation-based companies want to move. There is a question around where this kind of micro-cluster has already been created and where the potential exists to do so in the future.

We have analysed clusters around universities using both a narrow and wider geographic focus. For the narrow analysis we selected a specific postcode and for the wider analysis we used

University Postcode Sector

# of acq VB comps

(2001-2006)

Total value of acq VB comps at acquistion

(where known) (£000s)

Undisclosed trade sale

amounts

# of IPO 'innovative'

comps (2001-2006)

# of 'top 100 fastest

growing companies

by revenue' in PC sector

Belfast BT 3 49,280 1 0 1

Bristol BS 3 6,120 2 2 1

Cambridge CB 20 706,030 9 15 11

Cardiff CF 3 1,200 2 2 1

Cranfield MK 1 0 1 1 0

Dundee DD 2 32,277 1 2 1

Edinburgh & HW EH 5 3,150 4 4 2

Hertfordshire AL 0 – – 0 0

Imperial College SW 4 217,350 1 3 3

Lancaster LA 0 – – 0 2

Liverpool L 0 – – 0 0

Manchester M 2 2,650 1 4 2

Newcastle NE 0 – – 2 3

Nottingham NG 0 – – 0 1

Oxford OX 8 53,229 4 8 7

Southampton SO 0 – – 2 2

Surrey GU 3 11,856 2 12 3

York YO 1 0 1 2 0

UCL WC 2 0 2 9 1

Total 57 1,083,142 31 68 41

Table 18 – Cluster analysis of innovative companies (Source: Library House)

University Clusters

22


whole postcodes areas, for example CB for Cambridge or NG for Nottingham. Edinburgh and Heriot-Watt were regarded as one microcluster.

As proxies for high-tech cluster formation, we analysed the locations of the following types of organisations:

Innovation-based companies in terms of:1.

R&D companies (R&D companies are defined by Library • House in this analysis based on the 2003 United Kingdom Standard Industrial Classification Codes and own analysis)

Venture-backed companies•

Spin-out companies•

Fast growing companies•

Acquired venture-backed companies•

Initial public offerings of innovative companies•

Supply of risk capital as the number of venture capital 2. investors located in the region.

We sought to assess the number of innovation-based companies located near to the universities under study. We took R&D, venture-backed and spin-out companies as a reasonable proxy for innovation-based companies and determined the number of these within the same postcode area as each university. We removed from the results those companies that are direct spin-out companies of each university. This was done so that the

results reflect the attractiveness of the location to companies without a formal relationship with the university.

Most of the R&D companies were located in the regions of Cambridge (293), Oxford (270), Imperial (197) and Surrey (174). The highest density of R&D companies was found in the regions of Cambridge (3.17%), Oxford (1.74%) and Edinburgh and Heriot Watt (0.93%). In all other regions the percentage was below 0.1%.

Additionally we analysed the more qualitative aspects of the venture-backed companies located near the universities.

According to this analysis the innovation-based companies located in regions around top-ranked universities:

Number of R&D companies:•

University of Cambridge (293), University of Oxford (270), Imperial College (197) and University of Surrey (174)

Number of venture-backed companies:•

University of Cambridge (160), Imperial College (115), University of Oxford (91) and University of Edinburgh & Heriot Watt (82)

Number of IPOs from innovative companies between the • years 2001-2006 with the same postcode like:

Cambridge (15), Surrey (12), University College London (9) and Oxford (8)

Figures 18, 19 and 20 indicate a strong relationship between

Number of Post-Graduate Researchers

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000

Num

ber

of

R&

D C

om

panie

s

0

50

100

150

200

250

300Cambridge

Oxford

Guildford

Reading

Southampton

Queens Belfast

York

Dundee


Newcastle

Coventry

Manchester

Nottingham

Cranfield

Derby

Lancaster

Bristol

Cardiff

Hertfordshire

Stoke-on-Trent

Leicester

Birmingham

Sheffield

LiverpoolLeeds

DudleyBradford

Figure 18 – Comparison between number of post-graduate researchers and R&D companies (Sources: FAME and HESA)

University Clusters


RAE Ratio

0.0 0.2 0.4 0.6 0.8 1.0

Num

ber

of

Ventu

re-B

acked C

om

panie

s

0

20

40

60

80

100

120

140

160

180

Cambridge

Oxford

Imperial

Cardiff

UCL

Manchester

York

Bristol

Sheffield

Southampton

Birmingham

NottinghamLeeds


Newcastle

Lancaster

Surrey

Reading

Liverpool

Leicester

Queens Belfast

Dundee

BradfordKingston upon Hull (Hull)Plymouth

Hertfordshire

Figure 20 – Number of venture-backed companies in a cluster plotted against the RAE ratio of the cluster’s university (Source: FAME)

RAE Ratio

0.0 0.2 0.4 0.6 0.8 1.0

Num

ber

of

R&

D C

om

panie

s

0

50

100

150

200

250

300Cambridge

Oxford

Imperial

CardiffUCL

Manchester

York

BristolSheffield

Southampton

Birmingham

Nottingham

Leeds


Newcastle

Lancaster

Surrey

Reading

Liverpool

Leicester

Queens Belfast

Dundee

Bradford

Kingston upon Hull (Hull)

Plymouth

Hertfordshire

Figure 19 – Number of R&D companies in a cluster plotted against the RAE ratio of the cluster’s university (Source: Library House and RAE)

24


the research base of a region and number of innovation-based companies located in this region.

Therefore we compared an additional aspect of the research base (number of PhD-researchers) with the number of R&D companies located in a region. Also this analysis supports the argument that a strong research base seems to be an essential precondition for a high-tech cluster (Figure 16).

Clusters and Research QualityWe determined the RAE-ratio for each institution. This value was plotted against the number of venture-backed and R&D companies in each institution’s postcode district (excluding direct spin-out companies). Innovation-based companies appear to co-locate with high quality research universities (Figures 17 and 18).

InvestorsInvestors prefer to be located near the companies they invested in (Table 19). Therefore the headquarters of venture capital investors should be seen as a proxy for regions where attractive investment possibilities might occur.

IPOsTable 20 shows the number of ‘innovative’ IPOs that took place between the years 2001-2006 on the London Stock Exchange in the covered postcode areas. Data on IPOs was obtained

from the London Stock Exchange Statistics service. The data provided includes all IPOs since 2001. To reduce this list down to the most innovative companies, Library House first evaluated the companies based on their market sectors. Companies were classified automatically as ‘innovative’ if they operated in the semiconductor, pharmaceutical, or biotechnology sectors. After this, the remaining companies were screened by Library House individually to determine if they should be included in this set. A total of 158 companies were classified as innovative with 68 falling within the postcode areas relevant to this project.

Analysis on the number of innovative IPOs on the London Stock Exchange (main market and AIM) shows that the majority of these IPOs happen in and around London and in the south east,

Postcode Area Region Number of Offices

W London 39

EC London 33

SW London 24

WC London 16

CB Cambridge 8

EH Edinburgh 6

LS Leeds 4

OX Oxford 4

BT Belfast 3

G Glasgow 3

Table 19 – Headquarters of venture capital investors in the UK (Source: Library House)

University PC Sector Total # IPOs Total Market Cap (£m) # on Aim # on Main Market

Belfast BT 0 – – –

Bristol BS 2 77.82 2 0

Cambridge CB 15 1,464.13 14 1

Cardiff CF 2 114.98 2 0

Cranfield MK 1 10.27 1 0

Dundee DD 2 34.33 2 0

Edinburgh / Heriot Watt EH 4 455.33 2 2

Hertfordshire AL 0 – – –

Imperial College SW 3 120.42 3 0

Lancaster LA 0 – – –

Liverpool L 0 – – –

Manchester M 4 380.58 3 1

Newcastle NE 2 35.02 2 0

Nottingham NG 0 – – –

Oxford OX 8 382.07 7 1

Southampton SO 2 75.81 2 0

Surrey GU 12 1,625.92 11 1

York YO 2 58.15 2 0

UCL WC 9 346.47 9 0

Totals 68 5,181.30 62 6

Table 20 – Number of IPOs in each postcode area and market capital of these companies (Note: The total amounts of each column take into account the fact that Heriot Watt and Edinburgh are located in the same postcode area)


University Clusters

although when looking at the total and average market cap figures Scotland does particularly well (Figure 21). This is mainly due to the relatively few companies that have completed an IPO in Scotland having a very large market cap between them.

Attractiveness of High-Tech ClustersBeside the attractiveness a cluster already has for the companies located within, there also might be several reasons why companies relocate into a cluster. Table 21 presents the most attractive regions for spin-outs to move away from their origin to another region.

ConclusionsUniversities drive innovation through various knowledge & technology transfer channels. In this report we analysed these knowledge and technology transfer processes for 20 UK universities.

In the academic year 2004/2005 the 20 analysed universities had an aggregate research income of £2.3bn, of which only a small fraction came from industrial partners. The majority

of these industrial partners are from the pharmaceutical and engineering sectors. Although there was no correlation found between the research quality of a university and the extent of industrial interaction of that university, it was indicated that high quality research universities have a higher tendency to interact with large companies, whilst lower quality research universities focus more on the SME market.

Our analysis showed that the number of patents filed by universities is declining and that several universities don’t receive enough licensing income to cover the costs of patenting activities. It also indicated that a more focused knowledge & technology transfer strategy in universities may generate more licensing income.

High quality research universities spin out the majority of high quality spin-out companies (as defined by their ability to attract external funding). This means that technology transfer is predominantly carried out by the high quality research universities and to a far lesser extent by all other universities.

In our study on clusters we found that high-tech / innovation clusters especially form around large research universities that conduct high quality research. This is regardless of the total size of the city surrounding this university (e.g. Cambridge Cluster). All our analyses show that R&D and venture-backed companies locate around high quality research to a far greater extent than around lower quality research universities.

In general, UK Universities deliver remarkable returns in terms of output and impact. From Library House 2007 Spin-Out report and our report of the impact of the University of Cambridge we know that many UK universities perform competitive on an international level.

Region Postcode# Of Companies

Moved Into Area From Other Universities

Cambridge CB 15

Oxford OX 8

Surrey GU 4

Reading RG 4

Table 21 – Regions spin-out companies relocated to (Source: Library House)

Figure 21 – Map showing the total market cap of IPO-companies per region (Source: London Stock Exchange)

26


ReferencesArgote, L. & Ingram, P. (2000): Knowledge Transfer: A Basis for

Competitive Advantage in Firms. Organizational Behavior and Human Decision Processes, Vol. 82, No. 1, May, p. 150-169.

Argote, L., Beckman, S. L., & Epple, D. (1990): The Persistence and Transfer of Learning in Industrial Settings. Management Science, Vol. 36, No.2, February, p. 140–154.

Audretsch, D. & Feldman, M. (1996): R&D Spillovers and the Geography of Innovation and Production. The American Economic Review, Vol. 86, No. 3, p. 630-640.

Bathelt, H. & Malmberg, A. &r Maskell, P. (2002): Clusters and Knowledge: Local Buzz, Global Pipelines and the Process of Knowledge Creation. DRUID Working Papers, No. 02-12, Aalborg University.

Bekar, Clifford & Lipsey, Richard G. (2002): Clusters and Economic Policy. ISUMA (Canadian Journal of Policy Research), Vol. 3, No. 1, Spring, available under: http://www.isuma.net/v03n01/bekar/bekar_e.pdf

Brown, L. A. (1981): Innovation diffusion: A New Perspective. New York: Methuen.

Cooke, P., Heidenreich, M. & Braczyk, H.-J. (eds, 2004). Regional Innovation Systems. The Role of Governances in a Globalized World. Second edition. London: Routledge.

Czepiel, J. A., (1974): Word-of-Mouth Processes in the Diffusion of a Major Technological Innovation. Journal of Marketing Research, Vol. 11, No. 2, May, p. 172-80.

DTI (2001): Business Clusters in the UK – A First Assessment, February 2001, available under: http://www.dti.gov.uk/regional/clusters/clusters-assessment/page17380.html

DVCA and Library House (2005): Creating Success from University Spin-Outs, Report, Cambridge.

Galbraith, C. S. (1990): Transferring Core Manufacturing Technologies in High-Technology Firms. California Management Review, Vol. 32, No. 4, Summer, p. 56-70.

Ghoshal, S. & Bartlett, C. A. (1988): Creation, Adoption and Diffusion of Innovations by Subsidiaries of Multinational Corporations. Journal of International Business Studies, Vol. 19, No. 3, Autumn, p. 365-388.

HM Treasury, DTI & Department for Education and Skills (2004): Science and Innovation: Working Towards a Ten-Year Investment Framework, March 2004, available online: http://www.hm-treasury.gov.uk/media/F1761/science_406.pdf

Klepper, S. (2000): Firm Capabilities and Industry Evolution: The Case of the U.S. Automobile Industry. Working Paper, Carnegie Mellon University, available online: http://www.druid.dk/uploads/tx_picturedb/ds2001-211.pdf

Lambert, R. (2003): Lambert Review of Business-University Collaboration: Final Lambert Report, London, 2003, available online: http://www.hm-treasury.gov.uk/consultations_and_legislation/lambert/consult_lambert_index.cfm

Library House (2007): Spinning Out Quality: University Spin-Out Companies in the UK, Report, Cambridge.

Mahajan, V., & Peterson, R. A. (1979): Sage University Series on Quantitative Applications in the Social Sciences: Models for Innovation Diffusion. Beverly Hills, CA: Sage.

Marshall, A. (1920): Principles of Economics, London: Macmillan and Co. Ltd., 8th edition, online available: http://www.econlib.org/library/Marshall/marP.html

Nonaka, I. and Takeuchi, H. (1995): The Knowledge Creating Company, New York: Oxford University Press.

Porter, M. (1990): The Competitive Advantage of Nations. New York: Free Press.

Research Assessment Exercise 2001, results online available: http://www.hero.ac.uk/rae/

Rothwell, R. (1978): Small and Medium Sized Manufacturing Firms and Technological Innovation. Management Decision, Vol. 16, No. 1, p. 362-370.

Saxenian, A. (1996): Regional advantage: Culture and Competition in Silicon Valley and Route 128: Harvard University Press.

Szulanski, G. (1996): Exploring Internal Stickiness: Impediments to the Transfer of Best Practice within the Firm. Strategic Management Journal, Vol. 17, Special Issue, Winter, p. 27-43.

Szulanski, G. (2000): The Process of Knowledge Transfer: A Diachronic Analysis of Stickiness. Organizational Behavior and Human Decision Processes, Vol. 82, No. 1, p. 9-27.


Appendix – Analysis of Potential High-Tech RegionsSome regions in the UK are well-known for a climate that stimulates innovative and entrepreneurial behaviour. These regions are mostly found around universities or research organisations with world-class research capabilities. These centres of excellence attract innovation-based companies that benefi t from proximity and spillover effects. Famous examples of high-tech regions are the clusters around Cambridge, Oxford and London. These have been studied and covered in detail by many previous reports, for example, Library House's 2006 Cambridge Cluster Report 'The Supercluster Question'.

But beside these well-known clusters many other regions are now actively trying to create high-tech regions around their universities. In discussions with stakeholders all cross the UK, including University Vice-Chancellors, Heads of Technology Transfer Offi ces and the Management of Regional Development Agencies, we found that they were trying to emulate the conditions that allowed micro-clusters to form. But in general all stakeholders are mostly aware that they won't be able to replicate the degree of success seen in the comprehensive clusters of Cambridge, London or Oxford.

Instead we found different reasons and strategies by which other UK universities are involved in creating micro-clusters that attract innovation-based companies.

Besides the leading clusters, several other regions have created a benefi cial climate for innovation-based companies. In this document we present three regions - among many other regions within the UK - which seem to be attractive for innovation-based companies.

We chose to look at Newcastle, Dundee and Belfast, and included Cambridge for comparison purposes. These four regions were selected as they all contain a university that was included in our main report.

To determine the potential for high-tech cluster formation, we used some of the proxies developed earlier in the main report. For the analysis of innovative regions we included the following types of organisations:

R&D-based companies•

Venture-backed companies•

Spin-out companies•

The average percentage of venture-backed companies to total companies in the whole of the UK is about 0.12% (Table 1). All four UK regions are above the UK average, suggesting at least an accumulation of innovative companies is occurring in these areas. Although it must be noted that Cambridge has a much higher percentage of venture-backed companies than all of the other areas.

The UK distribution of investors, and therefore the UK average, is heavily skewed towards London and Cambridge but it can be seen that Newcastle and Belfast both have a good level of investors present in the region. The University of Dundee benefi ts from the proximity of investors located in the regions around Edinburgh and Glasgow.

Figure 1 – Percentage breakdown of Cambridge Cluster companies by sector 2006 (Source: Library House)

University FPC3Total

Number of Comp.

R&D Comp.

% R&D Comp. of all Comp.

Venture-Backed Comp.

% VC-backed

Comp. of all Comp.

% of VC-backed


VC-Backed

Spin-Outs in Cluster

%-Spin-Outs of all VC-Backed

Comp.

Belfast BT 5,406 46 0.85% 43 0.80% 93.48% 12 27.91%

Cambridge CB 9,239 293 3.17% 160 1.73% 54.61% 30 18.75%

Dundee DD 3,692 31 0.84% 14 0.38% 45.16% 3 21.43%

Newcastle NE 16,005 108 0.67% 36 0.22% 33.33% 5 13.89%

20 Universities' Total / Average 350,391 2,251 0.64% 902 0.26% 40.07% 179 19.84%

Table 1 – Collated cluster data

Perc

enta

ge o

f C

om

panie

s

0

20

40

60

80

100Information Technology

Healthcare & Life Science

Industrial

Communications

Services & Retail

Chemicals & Materials

Energy

Other

Appendix

28



contracts, it does have a large volume of business interaction. This suggests that good knowledge transfer activities of the university are contributing to the economic development of the region as a whole.

DundeeThere are early indications that an innovative region for Biosciences is beginning to form in Dundee. The 'BioDundee' (http://www.biodundee.co.uk) region is a collection of companies based within a 3 km radius. Table 1 shows that Dundee already has the highest percentage of R&D companies compared with the other potential clusters included in this report. In terms of the percentage of venture capital backed companies to total companies, even though it is far above the national average, it is the lowest of the potential clusters except Newcastle. This suggests that the University of Dundee and the area as a whole has a high propensity for R&D collaboration but the university is not spinning out as many companies that attract external funding as other universities do.

We believe that for an innovative region to form, a number of different conditions have to be present. These include the presence of a good research base, a large number of R&D companies, fast growing companies, spin-outs and start-ups, access to fi nance and the ability to attract external innovative companies into the area.

Figure 2 shows that, out of the 20 universities in this project Dundee is the best at converting publications into licensing

income. (Note: We excluded Heriot-Watt, also a very effi cient university from the analysis, due to it using a broader defi nition of licensing income).

Table 2 shows that the University of Dundee has both a very high licensing income and income per patent ratio compared with the other 19 universities covered in this project. This suggests that the University of Dundee is particularly profi cient in patenting inventions that have a high fi nancial value. Additionally, previous analysis in this project has shown that the University of Dundee also had the highest citation to publication ratio. The data presented suggests that the University of Dundee is very good at producing high-quality commercially useful research.

Figure 3 shows that the University of Dundee is very good at converting publications into industrial income with only four universities in our sample performing better.

Table 3 shows that Dundee collaborates heavily with large companies and non-commercial organisations and is outperforming the majority of its peers. The number of contracts it has with non-commercial organisations puts the university in the same league as Imperial, Oxford and UCL. The amount of funding Dundee receives from non-commercial organisations has also increased heavily since this data was published with funding from The Wellcome Trust and Cancer Research UK alone in 2006 reaching £12.5m. Dundee ranks 8th out of 18 universities for the amount of money received from the Wellcome Trust and 6th out of 22 universities for the amount of money received from Cancer Research UK. The fact that Dundee ranks in the top few

Table 2 – Overview of licensing income (Sources: European Patent Database and HEBCIS) (Table 15 in the main report)




Income (%)


(2001-2006)


(£000s)





University of Cranfi eld 135,735 191 0.14% 7 29.38
















Total / Average: 6,023,36 15,688 0.26% 278 56.47

Cambridge

Cambridge is the most well known Cluster in the UK and has been studied comprehensively. The Cluster and the University of Cambridge consistently top the majority of graphs, tables and rankings that measure the effi ciency or quality of any aspect of the university or Cluster. The Cluster has a wide variety of technology companies in it and has been through both the 'dotcom' and the 'biotech' booms of the early 2000s. The current cluster companies span many sectors with biotech and IT companies accounting for around 60% of the total number of companies (Figure 1).

NewcastleNewcastle has benefi ted from funding distribution towards the historically less prosperous areas of England, particularly those in the north.

Increased investment in the Newcastle area has brought greater prosperity to the region. The university and the Regional Development Agency are now actively trying to create a high-tech region around the university. The top line fi gures in Table 1 do suggest that there is some clustering of innovative companies occurring, with the percentage of venture-backed and the percentage of R&D companies to total companies both exceeding the national average. The percentage of R&D companies to total companies is particularly high, which suggests that the area is proving an attractive place for R&D companies to conduct operations.

In terms of the 13 active investors into UK companies based in the Newcastle area identifi ed by Library House, two of them are VC/PE fi rms, fi ve are corporates, two are public sector organisations, one is a public sector backed fund, one is a trust and two are classifi ed as other institutional investors. The two active VC/PE fi rms based in the Newcastle area are Northern Venture Managers and NEL Fund Managers. The public sector backed fund, NStar, currently runs two funds, a proof of concept fund to fi nance the development of early stage technologies into attractive prospects for further investment, and a co-investment fund to promote the development of high growth innovative businesses in the region and to encourage co-investment from other public and private sector investors.

BelfastBelfast has a lot of the characteristics of a geographical cluster due to its position as the capital and biggest city in Northern Ireland. Although Belfast is mostly not among the most effi cient universities in converting publications to licensing income, patents to licensing income, or publications to industrial income, it does have a lot of interaction with SMEs with 69 contracts reported in the 2003/04 HEBCIS data. Although this suggests that the University of Belfast does have problems attracting large companies to interact with, Belfast places 5th out of the 20 universities covered in this project, in terms of the number of SME contracts. Belfast also has a relatively high number of venture-backed spin-outs which suggests that quality spin-outs are being formed at the university or being attracted to the area. While Queen’s University Belfast may not receive a large amount of money in contract income, due to the smaller nature of SME

Dundee

Cra

nfield

Imperial

Nottin

gham

UCL

Card

iff

Cam

bridge

Edinburg

h

Oxfo

rdSouth

am

pto

nNewca

stle

Hertfo

rdsh

ire

Brist

ol

Surrey

Manch

est

er

Liverp

ool

Queens

Belfast

York

Lanca

ster

Rela

tive t

o T

op P

erf

orm

er

0

10

20

30

40

50

60

70

80

90

100

Figure 2 – Licensing income per publication (Figure 5 in the main report)

Appendix

28



contracts, it does have a large volume of business interaction. This suggests that good knowledge transfer activities of the university are contributing to the economic development of the region as a whole.

DundeeThere are early indications that an innovative region for Biosciences is beginning to form in Dundee. The 'BioDundee' (http://www.biodundee.co.uk) region is a collection of companies based within a 3 km radius. Table 1 shows that Dundee already has the highest percentage of R&D companies compared with the other potential clusters included in this report. In terms of the percentage of venture capital backed companies to total companies, even though it is far above the national average, it is the lowest of the potential clusters except Newcastle. This suggests that the University of Dundee and the area as a whole has a high propensity for R&D collaboration but the university is not spinning out as many companies that attract external funding as other universities do.

We believe that for an innovative region to form, a number of different conditions have to be present. These include the presence of a good research base, a large number of R&D companies, fast growing companies, spin-outs and start-ups, access to fi nance and the ability to attract external innovative companies into the area.

Figure 2 shows that, out of the 20 universities in this project Dundee is the best at converting publications into licensing

income. (Note: We excluded Heriot-Watt, also a very effi cient university from the analysis, due to it using a broader defi nition of licensing income).

Table 2 shows that the University of Dundee has both a very high licensing income and income per patent ratio compared with the other 19 universities covered in this project. This suggests that the University of Dundee is particularly profi cient in patenting inventions that have a high fi nancial value. Additionally, previous analysis in this project has shown that the University of Dundee also had the highest citation to publication ratio. The data presented suggests that the University of Dundee is very good at producing high-quality commercially useful research.

Figure 3 shows that the University of Dundee is very good at converting publications into industrial income with only four universities in our sample performing better.

Table 3 shows that Dundee collaborates heavily with large companies and non-commercial organisations and is outperforming the majority of its peers. The number of contracts it has with non-commercial organisations puts the university in the same league as Imperial, Oxford and UCL. The amount of funding Dundee receives from non-commercial organisations has also increased heavily since this data was published with funding from The Wellcome Trust and Cancer Research UK alone in 2006 reaching £12.5m. Dundee ranks 8th out of 18 universities for the amount of money received from the Wellcome Trust and 6th out of 22 universities for the amount of money received from Cancer Research UK. The fact that Dundee ranks in the top few

Table 2 – Overview of licensing income (Sources: European Patent Database and HEBCIS) (Table 15 in the main report)




Income (%)


(2001-2006)


(£000s)





University of Cranfi eld 135,735 191 0.14% 7 29.38
















Total / Average: 6,023,36 15,688 0.26% 278 56.47

Cambridge

Cambridge is the most well known Cluster in the UK and has been studied comprehensively. The Cluster and the University of Cambridge consistently top the majority of graphs, tables and rankings that measure the effi ciency or quality of any aspect of the university or Cluster. The Cluster has a wide variety of technology companies in it and has been through both the 'dotcom' and the 'biotech' booms of the early 2000s. The current cluster companies span many sectors with biotech and IT companies accounting for around 60% of the total number of companies (Figure 1).

NewcastleNewcastle has benefi ted from funding distribution towards the historically less prosperous areas of England, particularly those in the north.

Increased investment in the Newcastle area has brought greater prosperity to the region. The university and the Regional Development Agency are now actively trying to create a high-tech region around the university. The top line fi gures in Table 1 do suggest that there is some clustering of innovative companies occurring, with the percentage of venture-backed and the percentage of R&D companies to total companies both exceeding the national average. The percentage of R&D companies to total companies is particularly high, which suggests that the area is proving an attractive place for R&D companies to conduct operations.

In terms of the 13 active investors into UK companies based in the Newcastle area identifi ed by Library House, two of them are VC/PE fi rms, fi ve are corporates, two are public sector organisations, one is a public sector backed fund, one is a trust and two are classifi ed as other institutional investors. The two active VC/PE fi rms based in the Newcastle area are Northern Venture Managers and NEL Fund Managers. The public sector backed fund, NStar, currently runs two funds, a proof of concept fund to fi nance the development of early stage technologies into attractive prospects for further investment, and a co-investment fund to promote the development of high growth innovative businesses in the region and to encourage co-investment from other public and private sector investors.

BelfastBelfast has a lot of the characteristics of a geographical cluster due to its position as the capital and biggest city in Northern Ireland. Although Belfast is mostly not among the most effi cient universities in converting publications to licensing income, patents to licensing income, or publications to industrial income, it does have a lot of interaction with SMEs with 69 contracts reported in the 2003/04 HEBCIS data. Although this suggests that the University of Belfast does have problems attracting large companies to interact with, Belfast places 5th out of the 20 universities covered in this project, in terms of the number of SME contracts. Belfast also has a relatively high number of venture-backed spin-outs which suggests that quality spin-outs are being formed at the university or being attracted to the area. While Queen’s University Belfast may not receive a large amount of money in contract income, due to the smaller nature of SME

Dundee

Cra

nfield

Imperial

Nottin

gham

UCL

Card

iff

Cam

bridge

Edinburg

h

Oxfo

rdSouth

am

pto

nNewca

stle

Hertfo

rdsh

ire

Brist

ol

Surrey

Manch

est

er

Liverp

ool

Queens

Belfast

York

Lanca

ster

Rela

tive t

o T

op P

erf

orm

er

0

10

20

30

40

50

60

70

80

90

100

Figure 2 – Licensing income per publication (Figure 5 in the main report)

Appendix

30



It is questionable as to whether these areas will be able to achieve the scale of a cluster, but they will undoubtedly contribute to the regional economy and to the UK as a whole, and do so in ever increasing levels in the future.

Conclusions of AppendixAlthough three main high-tech clusters exist in the UK (London, Cambridge and Oxford), other areas are showing signs of potential cluster growth. In this section we analysed potential cluster formation around the Universities of Newcastle, Belfast and Dundee.

Figure 4 – Diffusion of research

In addition, the University of Dundee has the chance to increase its consulting income using the newly gained reputation in the fi eld of life sciences.

university recipients of money from these two life-science based organisations confi rms Dundee's profi ciency in life-sciences research.

The area of Dundee lacks investors, having the least amount of investors in the area of any of the other potential clusters. However, this may be mitigated by the proximity of Edinburgh, which has a relatively high number of investors, and the ability of these investors to invest into companies located in the Dundee area. As the Dundee Cluster, and Scotland as a whole, continues developing economically we may well see more investors locating in these areas. Looking at the investors present in Edinburgh in more detail it is obvious that there is considerable interest in biotech investment opportunities so this bodes well for the future development of Dundee's bio-region.

So in conclusion, the University of Dundee has a good research base, good collaboration with industry but a disproportionately low number of venture-backed companies and spin-outs. This may be due to the University actively encouraging licensing agreements over spin-outs or the lack of nearby investors.

The model in Figure 4 indicates that the University of Dundee is very good at the fi rst two stages of the research lifecycle (basic research and the diffusion of this research).

The data suggests that Dundee is in a good position to transform its research in mature applications which could form the basis for future university spin-outs and start-ups.

Univer

sity

of Dundee

Univers

ity o

f Cam

bridge

Avera

geIn

dustr

ial In

com

e /

Publication (

£)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Figure 3 – Industrial income per publication of Dundee, Cambridge and the average of the 20 universities

Appendix

University Total Value

# with SMEs

Value with SMEs

# with Large

Companies

Value with Large

Companies


Organisations


Organisations









University of Cranfi eld 13,412 62 1,056 132 12,356 – –












Total 252,392 987 19,131 4,286 151,950 2,402 81,311

Table 3 – Table of contract research fi gures, showing Dundee outperforming its peer group universities (Source: HEBCIS)(Table 9 in the main report)

30



It is questionable as to whether these areas will be able to achieve the scale of a cluster, but they will undoubtedly contribute to the regional economy and to the UK as a whole, and do so in ever increasing levels in the future.

Conclusions of AppendixAlthough three main high-tech clusters exist in the UK (London, Cambridge and Oxford), other areas are showing signs of potential cluster growth. In this section we analysed potential cluster formation around the Universities of Newcastle, Belfast and Dundee.

Figure 4 – Diffusion of research

In addition, the University of Dundee has the chance to increase its consulting income using the newly gained reputation in the fi eld of life sciences.

university recipients of money from these two life-science based organisations confi rms Dundee's profi ciency in life-sciences research.

The area of Dundee lacks investors, having the least amount of investors in the area of any of the other potential clusters. However, this may be mitigated by the proximity of Edinburgh, which has a relatively high number of investors, and the ability of these investors to invest into companies located in the Dundee area. As the Dundee Cluster, and Scotland as a whole, continues developing economically we may well see more investors locating in these areas. Looking at the investors present in Edinburgh in more detail it is obvious that there is considerable interest in biotech investment opportunities so this bodes well for the future development of Dundee's bio-region.

So in conclusion, the University of Dundee has a good research base, good collaboration with industry but a disproportionately low number of venture-backed companies and spin-outs. This may be due to the University actively encouraging licensing agreements over spin-outs or the lack of nearby investors.

The model in Figure 4 indicates that the University of Dundee is very good at the fi rst two stages of the research lifecycle (basic research and the diffusion of this research).

The data suggests that Dundee is in a good position to transform its research in mature applications which could form the basis for future university spin-outs and start-ups.

Univer

sity

of Dundee

Univers

ity o

f Cam

bridge

Avera

geIn

dustr

ial In

com

e /

Publication (

£)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Figure 3 – Industrial income per publication of Dundee, Cambridge and the average of the 20 universities

Appendix

University Total Value

# with SMEs

Value with SMEs

# with Large

Companies

Value with Large

Companies


Organisations


Organisations









University of Cranfi eld 13,412 62 1,056 132 12,356 – –












Total 252,392 987 19,131 4,286 151,950 2,402 81,311

Table 3 – Table of contract research fi gures, showing Dundee outperforming its peer group universities (Source: HEBCIS)(Table 9 in the main report)

Documents

Library House (2007) - An Analysis of UK University Technology and Knowledge Transfer Activities