The ways in which universities and research organisations benefit the economy and society is a long-standing and important concern both for policy-makers and the general community. Over recent decades a particular perspective has arisen in prominence—the notion of research commercialisation. ‘Research commercialisation’ refers to the treatment of knowledge as a commodity—an asset over which property rights can be, and are, asserted. The increased prominence given to this ‘capitalised’ knowledge and the role played by universities and research organisations in generating this asset mirrors the attention paid to the ‘knowledge economy’ by economic and social commentators.
This report has been prepared for the Department of Education, Science and Training by Dr John Howard, the founder and Managing Director of Howard Partners. The report proposes a framework for identifying, tracking and understanding the economic contribution of universities and research organisations in the twenty-first century. This framework is characterised by the emphasis placed upon the plurality and the complexity of the channels and mechanisms through which universities and research organisations generate economic benefits.
The report argues that the ‘standard’ research commercialisation model, associated with a linear sequence linking basic research to commercial outcomes, is largely specific to the biomedical sciences. Like the ‘linear model’ of research and development (R&D) itself (basic research—applied research—experimental development) to which it relates, the standard model is easily grasped, and the outputs easily measured, which in turn helps to secure funding. A range of external interests also benefit from the promulgation of this model as the model of how universities and research organisations generate economic benefits.
Lawyers, consultants, venture capitalists and the biomedical researchers themselves all stand to gain from increased resources devoted to this type of commercial focus within universities and research organisations. The standard model also has the advantage that it is compatible with the current emphasis on performance metrics within government. As ‘capitalised knowledge’, patents and licenses are easy to count—and the temptation to set targets, such as a planned numbers of patents and associated spin-out companies, can be hard to resist.
The challenge for policy-makers is that the standard model does not in fact adequately reflect the wide range of circumstances through which universities impact upon the economy. Consequently, if performance measures are based exclusively on this standard model, then there is a risk that other, perhaps more important channels for generating economic benefits, will be given insufficient recognition, thereby potentially distorting policies and practice, including misallocation of resources across the spectrum of research-industry interaction.
The report addresses this challenge by proposing a more comprehensive and realistic framework for understanding research commercialisation and knowledge transfer. The framework consists of the following four ideal typical models:
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Universities and research organisations generating useful economic and social outcomes via encouraging the broad industry-wide adoption of research findings through communication, building capacity within industry through extension, education and training, creating standards relating to production and distribution. |
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Universities and research organisations generating useful economic and social outcomes by selling or licensing the results of research in the form of commodified knowledge—directly exploiting ‘knowledge products’ embedded in intellectual property and other explicitly codified formats. This is a ‘standard’ model of research commercialisation. |
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Universities and research organisations generating useful economic outcomes by providing services that indirectly exploit broad intellectual property (IP) platforms consisting of trade secrets, know-how and other forms of tacit knowledge. This approach centres on cooperation, collaboration, joint ventures and partnerships. |
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Universities and research organisations generating useful economic outcomes as a by-product of shared interests and concerns that transcend the boundaries of the university per se. |
The report shows how current Australian Government support for science and innovation covers all four of these areas. It is therefore not desirable to restrict measures of performance to ‘knowledge production’ processes—the easiest area to measure performance.
The report argues for separate approaches to performance measures and performance indicators. Performance measurement is undertaken on the basis of assessment of overall program performance, having regard to purpose, resources, processes, impacts and effects. This involves using a range of program evaluation methodologies and techniques.
Performance indicators, by contrast, are intended to inform policy-makers, managers and stakeholders at regular intervals about progress in relation to purpose and objectives. Typically, performance indicators relate to processes (throughput) and outputs, and substantial movements in those categories, which can provide comfort—or raise concerns—about the extent to which program performance results will be achieved in the medium-to-longer-term. Interpretation of performance indicator information is often a skill in its own right.
The report argues that indicators should be kept to a minium and adopted only when they can provide relevant and useful information about program performance. Indicators should not be seen as performance measures in their own right. Moreover, availability of large amounts of information generated through administrative processes should not necessarily be seen as constituting performance indicators. It does not follow that just because data are available, they are going to be useful in assessing performance. It may be necessary to establish cost-effective data collection procedures to obtain relevant, accurate and timely data.
The categories of output indicators for the four research commercialisation processes are summarised as follows:
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Communication activities
Capacity-building activities
Extension and education activities
Standard setting activities
Industry output data |
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Academic publication activities
Patenting and licensing activities
Income streams relating to the above
Spin-off company formation activities |
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Contract research and consultancy activities
Income streams
Staff and students working on interchange with industry
Industry research staff with sessional and adjunct appointments in universities
University-appointed ‘visitors’ from industry |
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Participation in non-academic community and economic activities
Jointly owned and operated technology property infrastructure—technology and research parks, buildings, equipment, instruments etc.
University-organised events for community and regional economic and social benefit (workshops, seminars etc.)
University facilities available for non-academic purposes (for example, libraries, cultural centres, sportsgrounds) |
The report argues that performance measurement for research funding programs should be approached at four levels, depending on the purpose of the program:
the level of the economy: covering contributions to wealth, indicated by growth in national production (output), investment, and the contribution to research to economic performance
the level of the industry: relating to factors such as industry productivity and enhanced industry competitiveness and indicated by reference to baseline industry measures
the level of the enterprise: relating to specific commercial outcomes relating to profitability, viability and sustainability and indicated by factors such as sales, employment, exports and investment
the level of the region: relating to regional performance through clustering of activities and the formation and performance of networks and networking.
All of the classifications and typologies involve measurement issues. The forms of measurement are identified as:
analytical/conceptual modelling of underlying theory
surveys
case studies—both descriptive and economic simulation
econometric and statistical analysis
sociometric and social network analysis
bibliometrics—including counts, citations and content analysis
historical tracing
expert judgement.
Each measurement approach has a specific relevance to the level of analysis and the commercialisation processes identified in the report. Moreover, the level of analysis and the measures will vary in their significance among universities and research organisations. Universities that receive a substantial amount of public funding through competitive grants might have a different indicator and measurement profile from institutions that receive substantial levels of funding from state governments and through project research and consultancy.
Universities and research organisations should be encouraged to develop measurement and indicator profiles that are representative, and indicative, of their missions and strategies. Universities in particular should be encouraged to develop profiles relevant and appropriate to their core competencies and distinctive capabilities in the increasingly segmented higher education industry.
It is a matter for funding agencies to decide on the structure, timing and resourcing of program performance measurement and evaluation approaches, and the indicators they wish to collect on a national basis. Those indicators should be limited in number, be consistent in definition, free from ambiguity in interpretation, and relevant to assessing program performance. A ‘minimum data set’ should be developed with a requirement that universities and research organisations design systems that will generate sought-after information in an efficient and timely manner.
Recognition of the different research commercialisation processes creates the conditions for richer and more powerful economic (and social) impacts from universities and research organisations. This will be achieved by avoiding the imposition of a single, and often inappropriate, model of what research commercialisation and knowledge transfer involves in practice, and by encouraging effective proprietary strategic management in our universities and research organisations.