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.

Share
. Reply . Category: Categories . Tags: , , , , , , ,

Unpacking the Triple Helix: Universities, industry and government

This blog was contributed by Helen Lawton Smith, Professor of Entrepreneurship, Director, Centre for Innovation Management Research, Department of Management, Birkbeck.

Nearly 300 people — academics, policymakers and business practitioners — from 35 countries attended the beginning of the 2013 Triple Helix International Conference yesterday.

Why did they travel from across the globe to the three-day event hosted in Bloomsbury by the Big Innovation Centre, Birkbeck and UCL?

The first answer is that they came to be part of the debate on the conference theme: The triple helix in a context of global change: continuing, mutating or unravelling? The conference engages with the challenges for each of the three component spheres, of the triple helix model — universities, industry and government — as they co-innovate to solve global economic and social challenges. Discussions focused on  different contexts and ways of building an ‘enterprising state.’

The second is that they came to network. This is the best bit of every conference. Who knows who you will sit next to on the river cruise, at the dinner at Lincoln’s Inn or in a parallel session or workshop?

The third answer is that they came to hear outstanding speakers. They came to listen to the originators of the Triple Helix metaphor, Henry Etzkowitz and Loet Leydesdorff, and David Willetts, Minister of State for Universities and Science, and Will Hutton, the political economist and writer. They also wanted to hear from other distinguished keynote speakers from high-profile organisations, including the European Commission, the OECD, Unilever, EDF, GlaxoSmithKline,  about the relevance of the triple helix model to their thinking and practice.

What three things will they have learned?

1.That the triple helix model is continuing to be central to the economic, social and technology policy agenda in many countries of the world, such as Brazil and Russia, and to international bodies, such as the European Commission’s Europe 2020 Smart Specialisation agenda. Alongside this is an increasing interest in how the impact of actions which follow from the agenda can be mapped, measured and evaluated in order to identify baselines for policy decisions.

2.That the model is not so much mutating but changing the forms it takes in the relationships between actors. Its inter-relationships are key to businesses, such as Unilever. In the cloud industry the basis of innovation in the market place is changing and requires a ‘convergence of capabilities’.  Whether this counts as ‘open innovation’ is a debate that will continue long after this conference. An emphasis on the broader role of universities in the economy includes employability, an agenda which links all three of the spheres. This can take the form of entrepreneurship education, both formal through teaching programmes and through student and alumni support such as Birkbeck’s Enterprise Hub, and the mentoring programmes organised by Birkbeck’s Entrepreneur-in-Residence, Andrew Atter,  based in the Centre for Innovation Management Research in the School of Business, Economics and Informatics.  Professor David Latchman, Birkbeck’s Master, is himself an entrepreneur and believes that there should be more entrepreneurship.

Changing forms present challenges including the ever-present need for finance for entrepreneurs and innovation, and for universities to maintain their standards and diversify their activities to be more responsive to society’s needs.

3.The triple helix model is also a political agenda. It takes a variety of meanings depending on context for each of the three spheres in an uncertain world, nationally, regionally and locally. Whether the model will unravel will depend on how mismatches between the institutional arrangements in each of the three spheres are resolved. The coordination problems are considerable.  Moreover, it is an issue of prioritisation. How the different stakeholder interests fit with the increasing pressures on universities to recruit students and  enhance their learning experiences is a question yet to be answered.

Share
. Reply . Category: Business Economics and Informatics . Tags: , , , , ,