What drives efficiency in knowledge transfer?

Dr Federica Rossi, lecturer in business economics discusses increasing expectations on universities to demonstrate the positive economic and social impacts of their activities, and her research into measuring the efficiency of their efforts. 

Knowledge transfer is a term used to encompass a broad range of activities to support mutually beneficial collaborations between universities, businesses and the public sector. In the face of demands from funding bodies and ultimately taxpayers, universities all over the world are increasingly expected to demonstrate that their activities have a positive economic and social impact. Direct knowledge transfer to businesses, governments and society in general allows universities to make a visible contribution outside the ‘ivory tower’ of academia and can also help them to raise additional funds.

Measuring efficiency

Since knowledge transfer has become as important as a university’s longstanding commitment to teaching and research, the question of how well they perform this mission has gained prominence. Most universities attempt to measure performance in knowledge transfer, but focus on a quantity of outputs rather than the quality or efficiency. Even studies that measure efficiency tend to focus on a limited set of knowledge transfer activities, like technology through the commercialisation of patent licenses, creation of spin-out companies or research contracting with industry.

However, universities fulfil their knowledge transfer mission through many other activities, which include delivering knowledge-intensive services such as consultancies, clinical tests, prototypes and professional development courses, engaging in informal networks and staff exchanges with industry, contributing to community regeneration programmes and engaging with the public through different media.

Findings

The efficiency of 97 universities in the United Kingdom was measured for a range of knowledge transfer activities: research contracts, consultancies, professional development courses, generation of intellectual property and public engagement. Compared with a restrictive definition of knowledge transfer that only includes research contracts and intellectual property, this broader approach produces a different ranking for the most efficient universities: more universities achieve efficiency, and the distribution of efficiency scores is less skewed.

The universities that increase their efficiency when a broader definition of knowledge transfer is used have a lower share of staff in medicine and natural sciences and a higher share of staff in the arts and humanities; they are less likely to have a university hospital, and are more teaching-intensive. By adopting a broader approach to measuring knowledge transfer, some universities that are less research-oriented and less focused on science and medicine can better demonstrate their efficiency. More efficient institutions have a larger amount of staff and students; they are older, but have a more recently established knowledge transfer office; and they are specialised in a few subject areas (although some diversified universities are also efficient). Research, teaching intensity, and geographical location do not have a significant effect on efficiency.

Implications

The findings suggest that universities with different production models can be equally efficient in generating knowledge transfer outputs, and that research intensity is not a prerequisite for efficiency. Universities can achieve efficiency by adopting a model of knowledge transfer engagement that is consistent with their resources, without needing to replicate the knowledge transfer strategies of prominent institutions whose resources may be very different. By improving their reputation for excellence in specific activities that best fit the institution’s resources, universities may increase their ability to generate further knowledge transfer outputs. In fact, institutional reputation appears to increase knowledge transfer opportunities, with more reputable older, larger and diversified institutions achieving greater efficiency.

Another implication of the findings is that, rather than having an established Knowledge Transfer Office (KTO), what affects efficiency are its practices and policies, and the professionalism of its staff. KTOs therefore need to invest in staff training and in the development of best practices. Developing specialised, subject-specific skills and structures to support knowledge transfer, rather than generic ones may also pay off.

While performance is often measured by looking at outputs, thinking about performance in terms of efficiency helps us recognise that universities work with very different resources, which affects the nature of their knowledge transfer engagement. Changes in the resources available to universities, through potential changes in the rules governing the allocation of public funds, will also change their ability to engage in knowledge transfer.

Policymakers need to think systematically about the effect of changes in funding for research and teaching (for example, the replacement of recurrent grants with competitive funding) on a university’s ability to engage in knowledge transfer. The relationship between funding sources and knowledge transfer strategies, which has been largely unexplored to date, would merit greater attention from both researchers and policymakers.

The detailed empirical analysis on which these results build is presented in:

Rossi, F. (2017) The drivers of efficient knowledge transfer performance: evidence from British universities, Cambridge Journal of Economics.

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What does the retreat of public research mean for welfare and innovation?

This article was written by Professor Daniele Archibugi and Dr  Andrea Filippetti, from Birkbeck’s Centre for Innovation Management Research

research-and-developmentAn increasing proportion of knowledge is generated in the private sector, rather than in public research institutions like universities.  For many, this is cause for concern; public research and private research differ economically in terms of public access, potential for future technological innovations and in the criteria of resource allocation. Does it matter whether research is conducted by  private business rather than in universities or government research centres? And will the retreat of public research have negative effects on welfare and innovation?

These are just two of the questions we considered in our recent research . While science and innovation policy in the last decades has focused on exploring the relevance of the interconnections between public and business players in enhancing knowledge-based societies, we argue that a major trend has been ignored: both the quota of public Research and Development (R&D) and its share over the total R&D investment has shrunk in most OECD countries.

The shift from public R&D to business R&D

The evidence for a shift in R&D is reflected in the most visible and measurable component of knowledge creation –  the resources allocated to R&D. In most OECD countries a significant shift in the effort to finance public R&D has occurred: as shown in the tables below, from 1981 to 2013 the share of public-financed R&D to GDP has been reduced from 0.82 per cent to 0.67 per cent. By contrast, the industry-financed R&D has increased from 0.96 per cent of GDP in 1981 to 1.44 per cent in 2013.

Gross R&D (GERD) expenditure as a percentage of GDP by source of funds (G-7 countries plus South Korea and OECD average), rate of change 1981-2013

Industry-financed GERD as a percentage of GDP Government-financed GERD as a percentage of GDP
rate of change 1981-2013 rate of change 1981-2013
Canada 53.06% -6.56%
France 63.16% -21.21%
Germany 38.81% -13.27%
Italy 33.33% 38.46%
Japan 85.82% 15.38%
South Korea* 86.90% 126.19%
United Kingdom -19.15% -59.26%
United States 48.21% -29.63%
OECD – Total 50.00% -18.29%

Source: OECD Main Science and Technology Indicators (MSTI).

*  Data for South Korea refer to 1995 instead of 1981.

 

Table 2 – Percentage of Gross R&D (GERD) expenditure by source of funds (G-7 countries plus South Korea countries and OECD average)

 

Percentage of GERD financed by industry Percentage of GERD financed by government
year 1981 2013 rate of change 1981 2013 rate of change
Canada 40.77 46.45 13.93% 50.61 34.86 -31.12%
France 40.92 55.38 35.34% 53.4 34.97 -34.51%
Germany 56.85 65.21 14.71% 41.79 29.78 -28.74%
Italy 50.08 44.29 -11.56% 47.21 42.55 -9.87%
Japan 67.71 75.48 11.48% 24.91 17.30 -30.55%
South Korea* 76.26 75.68 -0.76% 19.04 22.83 19.91%
United Kingdom 42.05 46.55 (70)** 10.70% 48.1 26.99 -43.89%
United States 49.41 60.85 23.15% 47.8 27.75 -41.95%
OECD – Total 51.64 60.76 17.66% 44.19 28.28 -36.00%

Source: OECD Main Science and Technology Indicators (MSTI). Data for South Korea refer to 1995 instead of 1981; the sum of the shares does not add up to 100% since there are other minor sources that are not considered, namely “other national sources” and “abroad”.

* Data for South Korea refer to 1995 instead of 1981.

** In the UK a significant higher proportion of R&D funding comes from overseas. When this is taken into account the share of private-funded R&D stands at 70% (Economic Insight, 2015, p. 7)

 

This data also indicates significant differences across countries. Japan and South Korea exhibit a virtuous trend where both  business and  government have increased their R&D expenditure; in South Korea, particularly, government expenditure increase has been spectacular. In the US, the UK, Canada, France and Germany, by contrast, we see simultaneously the growth of industry-financed R&D and  the decline of government-financed R&D.

Beyond the knowledge-as-a-public-good view

The current privatisation of research activity and knowledge (which is often praised) can have major consequences on innovation and, ultimately, on long-term economic growth and social welfare. But why is the threat to knowledge largely ignored or under-estimated?  We believe that it is due to an unclear understanding of the economic characteristics of knowledge. Historically, knowledge has been considered to be a public good; Nobel Prize winner in Economics, Kenneth Arrow, is cited arguing that knowledge is costly to produce but could be disseminated as information at zero or very low costs. While this view recurs frequently in literature, and is repeated by another authoritative Nobel Prize winner, Joseph Stiglitz, a great body of research has demonstrated that knowledge has both public and private components.

Public-generated knowledge and private-generated knowledge have different economic characteristics, which will shape future knowledge-creation and innovation. The way in which knowledge production is funded – public or business – matters for subsequent application for innovation, particularly in:

  1. Resources allocation
  2. Excludability in consumption
  3. Excludability in production
  Private-generated knowledge Public-generated knowledge
A.

 

Resources allocated through market mechanism.

The main purpose is to contribute to profits though knowledge-based products, services and processes.

Resources allocated through political process.

The main purpose is to contribute to the advancement of knowledge and social welfare.

B. Excludability in consumption pursued through active strategies such as industrial secrecy and proprietary forms of intellectual property. Non-excludability in consumption implemented through technology transfer policies and full disclosure (e.g. open science and non-proprietary forms of intellectual property).
C. Excludability in production associated to firm-specific technical knowledge and tacit knowledge. Non-excludability in production actively sought reducing tacit knowledge.

Our research suggests that, up until now, little attention has been given to the major shift from public to private consequences. We are calling for a change: while the long-term consequences of this shift have not yet been discussed at length, they have the potential to be extremely relevant to long-term technological opportunities, the role of major scientific breakthroughs, and vital knowledge exchange from basic research in the public sector.

Further reading:

  • Archibugi, D. and Filippetti, A. (2016) ‘The Retreat of Public Research and Its Adverse Consequences on Innovation’. CIMR Research Working Paper Series Working Paper No. 31.
  • Archibugi, D. and Filippetti, A. (2015) The Handbook of Global Science, Technology, and Innovation, John Wiley & Sons.
  • Mazzucato, M., 2013. The Entrepreneurial State: Debunking Public vs. Private Sector Myths. Anthem Press, London.
  • I.T., 2015. The Future Postponed. Why Declining Investment in Basic Research Threatens a U.S. Innovation Deficit. M.I.T. Washington Office, Washington D.C.

Further information:

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