Changing Policy Mindsets 2: What's in a Name? The Role of Definitions in Australia's R&D and Innovation Policy

Rajesh Gopalakrishnan Nair

'What's in a name? That which we call a rose by any other name would smell as sweet.' - Romeo and Juliet, William Shakespeare, 1594

Juliet's soliloquy suggests that a name is merely an arbitrary label and does not alter the intrinsic qualities of a person or entity. However, in the context of Australia's policy framework, key terms such as innovation and research and development (R&D) and their meaning (definition) are crucial factors impacting progress.

This Insight is written in response to the ongoing discussions on the recent Strategic Examination of R&D Discussion Paper (SERD 2025). A major critique is that the SERD discussion paper is constrained by its terms of reference, is largely preoccupied with R&D and downplays innovation (Howard 2025). This article interprets this as a definitional issue rather than intent or oversight. It begins by examining the role of definitions in policy and attempts to find how the current definitions of key terms impact R&D policy.

Role of definitions in policy

All around the world, semantics plays an important role in policymakers' understanding, interpretation, and execution of ideas. Definitions (an explanation of the meaning of a word) of key policy terms are important elements in policy construction (Placier 1993). Policy processes occur within a framework of ideas that specify instrument settings, instruments themselves, and the policy goals.

This framework's embeddedness within the prevailing political discourse and its jargon makes it comprehensible and plausible to the policymakers and allows them to take it for granted in their routine work (Hall 1993). Jargon crafted by experts in the field and their definitions control and guide local interpretations of legislation and funding decisions. Policymakers often prefer narrow definitions to limit expenditure by targeting policies to specific groups. World over, R&D policy faces a problem concerning the differential definition of key terms such as innovation and R&D.

The R&D overload of innovation

In the context of the SERD discussion paper, Howard (2025) critiques the paradox in which Australia is celebrated as a 'global powerhouse' in science yet struggles to translate this excellence into tangible innovation outcomes.

A recent review of definitional issues concerning key terms in research, development, and innovation revealed the predominance of R&D in innovation narratives. Lewis & Mikolajczak (2023) found that there has been a tendency in Australia to equate innovation with science and R&D. Since 2014, the interpretation of innovation as business and R&D has gained traction. This has important policy implications.

With the R&D Tax Incentive (R&DTI) legislation of 2011, the R&D definition has provided the framework conditions for R&D tax incentives. The underlying policy objective of R&DTI is to make Australian companies more innovative through a tax credit system for R&D expenditure.

A narrow definition of R&D that ignores the role of innovation would disincentivise firms from prioritising processes fundamental to innovation, such as learning by doing, iterative prototyping, and industry-specific knowledge development. To be more inclusive and flexible, the definition should incorporate tacit knowledge, informal learning processes, and adaptive research. The definition should capture the creation of new knowledge, combining existing knowledge in new ways, modifications/incremental changes, and technology adoption (Arundel 2020).

The diffusion deficit in the R&D definition

Societal benefits of innovation depend on the diffusion of ideas and technologies, old and new, across industries. Critics point out that historically, Australia's performance in knowledge diffusion has been poor and marked by a disproportionate policy focus on new technologies rather than their adoption (Duff 2024). This can lead to inaccurate predictions of science and technology capabilities and impacts and send misleading signals to policy.

For example, policies that emphasise high-tech manufacturing without supporting diffusion are unlikely to achieve a broader societal impact (Ding 2024). Therefore, a broader R&D definition that includes diffusion processes is essential for promoting innovation, especially in low- and medium-technology sectors. Notably, 71% of Australia's manufacturing value added comes from the low-tech sector (World Bank 2022).

Innovation is bigger than R&D

Innovation is a broader and more complex phenomenon than R&D. It involves discovery, incubation, and acceleration. R&D is just an element of the discovery capability, 'invention' (O'Connor 2019). Hence, a good definition of R&D should differentiate itself from innovation.

The conceptual difference between innovation and R&D is that while R&D creates new knowledge or technology, innovation is its application for broader societal benefits. Innovation involves the development of new or improved products or processes and the activation of these in the market. It is a systemic process with much complexity and uncertainty of outcomes.

Technology appears at the end of a science pipeline; innovation emerges through a spider's web of interactions, false starts, and surprises. R&D often results from the 'animal spirits' of the scientist researcher; innovation is more of a 'Promethean spirit' challenging the status quo.

Innovation happens even in the absence of R&D. It is inherent to human behaviour, core to our cultural evolution, and characterised by unstoppable, continuous, and often disruptive changes. Innovative propensities are shaped by individual, social, and ecological influences. Thus, boosting innovation is not achieved by R&D spending but through building innovation capacity as well.

An OECD study found that innovation contributes to at least 50% of global economic growth (OECD 2015). In the long run, it is impossible to achieve growth without innovation, as it accounts for 70–90% of productivity growth. Above all, innovation is an important source of sustainability and emissions reduction.

This raises a question: why, in countries around the world, has policy not incorporated the broader definition of innovation in R&D, despite its potential economic benefits? It is not a lack of awareness or desire. The answer is that the phenomenon of innovation presents challenges of measurement and management that do not easily fit into general policy practice.

Policy's struggle harnessing innovation.

At least two inherent challenges make innovation difficult for policy to harness: measurement and governance.

Measuring innovation performance is challenging as there is a short supply of competent indicators. Only a few countries have developed efficient innovation indicators. Hence, even reputed global indexing services like GII are constrained to ignore them and substitute them with indicators of framework conditions, S&T, or potential inputs to innovation (Arundel 2020). This confuses and misleads policy.

It is important to distinguish between innovation indicators and R&D indicators. Failure to do so can distort (usually reduce) the level of support for innovation. R&D is more straightforward for policy intervention because the main policy tools (R&D spending or tax credits) are often under direct government control (Arundel 2020). On the other hand, policy response for innovation concerns the far more multi-dimensional task of improving the innovation capabilities of businesses and strengthening the innovation ecosystem in which these are embedded.

Innovation is also hard to govern and regulate. Maintaining a balance between fostering innovation, protecting consumers, and addressing the untinted consequences of disruption challenges policymakers and regulators. These challenges arise from the inherent attributes of innovation, such as its trans-sectoral nature and the way it poses institutional challenges, enforcement issues like attributing liability (e.g., with AI), the need for regulatory frameworks to keep pace with technological transformation, etc. (OECD/KDI 2021).

To be able to invest in innovation, businesses need to increase profitability and cash flows, which can be problematic to regulate. Policies to support business innovation have the inherent risks of favouring some businesses over others, dealing with businesses misappropriating funds, and policy capture by influential businesses.

It is perhaps not surprising that analysis is all too often narrowly focused on certain aspects of innovation, such as spending on R&D. This leads to an underestimation of the role of innovation in national economic performance and provides limited diagnostic data to help better manage innovation as a key driver of growth.

Summary and conclusion

The above discussion boils down to two key facts:

1. The current debate on science, technology, and innovation is ambiguous due to a semantic impasse caused by a disagreement about the meaning of key terms, particularly the differences between R&D and innovation.

2. The current use of R&D spending as a policy proxy for innovation seriously underrepresents innovation. There are, nevertheless, challenges in finding useful measures of innovation.

Resolving Australia's conundrum of improving the performance and relevance of its R&D system may not be accomplished by resolving the semantic impasse or redefining key terms. It requires a different conversation about the relationship between R&D and innovation among all those with a stake in seeing innovation as a major source of productivity, growth, and prosperity in Australia.

The SERD process might have opened up a space to start a broader conversation beyond R&D about the role and organisation of innovation appropriate for a thriving and sustainable Australia.

References

Arundel (2020), Supporting the development of Vietnam's Science Technology and Innovation Strategy 2021-30. Policy Exchange Activity 3 (PE3). Aus4Innovation

Ding Jeffrey (2024), The diffusion deficit in scientific and technological power: re-assessing China's rise, Review of International Political Economy, 31:1, 173-198, DOI: 10.1080/09692290.2023.2173633

Duff Elliot (2024), Towards 3% R&D - Knowledge diffusion a key by Elliot Duff - Australian Manufacturing Forum

Hall, P. A. (1993), Policy Paradigms, Social Learning, and the State: The Case of Economic Policy Making in Britain. Comparative Politics, 25(3), 275–296. https://doi.org/10.2307/422246

Howard John (2025), Can the Strategic Examination of R&D Solve 2025's Innovation Challenges? Acton Institute for Policy Research and Innovation (AIPRI)

Lewis, J. M., & Mikolajczak, G. (2023), Policy on innovation in Australia: Divergence in definitions, problems, and solutions. Australian Journal of Public Administration, 82, 26–45. https://doi.org/10.1111/1467-8500.12575

O'Connor Gina (2019), Real Innovation Requires More Than an R&D Budget. The Harvard Business Review. 

OECD (2015), The Innovation Imperative: Contributing to Productivity, Growth and Well-Being, OECD Publishing, Paris. DOI: http://dx.doi.org/10.1787/9789264239814-en

OECD/KDI (2021), Case Studies on the Regulatory Challenges Raised by Innovation and the Regulatory Responses, OECD Publishing, Paris, https://doi.org/10.1787/8fa190b5-en.

Pierson, P. (2000), 'Increasing returns, path dependence and the study of politics', American Political Science Review 94(2): 251-267.

Placier Margaret L (1993), The Semantics of State Policy Making: The Case of "At Risk". Educational Evaluation and Policy Analysis, Vol. 15, No. 4 (Winter, 1993), pp. 380- 39 URL: https://www.jstor.org/stable/1164536

SERD (2025), Strategic Examination of R&D Discussion Paper, Strategic Examination of R&D independent expert panel. Commonwealth of Australia. https://storage.googleapis.com/converlens-au-industry/industry/p/prj31a02fa37c9ece8370e29/page/SERD_Discussion_Paper.pdf

World Bank (2022), United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database. https://stat.unido.org/analytical-tools/cip?country=036