Received: August Revised: December Accepted: February
RESEARCH AND EVALUATION
Addressing Australia’s collaboration ‘problem’:
Is there a Brave New World of innovation policy
AJ George1Julie-Anne Tarr2
School of Business and Law, Central
Queensland University, Brisbane,
School of Business, Queensland
University of Technology, Brisbane,
Amanda-Jane George, School of Business
and Law, Central Queensland Univer-
sity, Ann Street, Brisbane, QLD ,
Central Queensland University,
In a post-COVID- world, innovation stimuli and well-
aligned policies will assume even greater importance
as various sectors seek to recover lost ground and
to generate new opportunities. Collaborative partner-
ing in innovation research and development (R&D)
between private industry and higher education has
increasingly emerged over the last decade as a lead-
ing key performance indicator for government policy
development, and higher education research funding
allocations. Recalibration of R&D-related policies and
incentivisation will require careful consideration, with
constructive lessons to be learned from outcomes over
the last four decades. This paper presents findings from
a new study of stakeholder perceptions as to the National
Innovation and Science Agenda’s impact on innovation
partnerships, and synthesises outcomes from two prior
studies. It then examines a newly proposed innovation
policy framework, Stimulating Business Investment in
Innovation (SBII), set against a background of the shift-
ing mix of paradigms that have comprised Australian
innovation policy over the last years. It argues that,
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following the SBII, any proposed change of policy direc-
tion will face significant challenges in its implementa-
tion, requiring a fully committed and comprehensive
embrace by Government of the new APS engagement
framework and greater levels of deliberative democracy.
innovation policy, non-R&D innovation, R&D collaboration, sys-
Stimulating collaborative research and development (R&D) has been an important goal over the
last decade in policy aimed at enhanced innovation, productivity, and growth. It has also served
increasingly as a key performance indicator for research funding allocation in higher education.
Post-COVID-, collaborative R&D will be critical in addressing the disease (Clinical Research
Coalition, ;Lee&Haupt,; Zhang et al., ; IISA, ) as well as its economic impacts.
Collaboration, at its simplest, is a ‘partnership, alliance or network, aimed at a mutually beneficial
clearly defined outcome’ (McGauchie, , p. ). Multiple forms of collaborative innovation exist,
ranging from loose engagement with informal networks, to complex multiparty consortia formed
by legally binding contracts. However, the role of collaboration is complex and unsettled, and
outcomes are variable, with the result that this collaboration ‘problem’ has been addressed across
a plethora of reports and policies (including ACIP, ;ACOLA,; Australian Government,
,,,a,;Cutler,; DISER, –,;Howard,; Innovation &
Science Australia, ,,; McGauchie, ;PC,;Watt,).
In early , Innovation and Science Australia (ISA) released a proposed new innovation pol-
icy framework, Stimulating Business Investment in Innovation (SBII). In comparison to the
National Innovation and Science Agenda (NISA), the SBII is remarkable in two respects: it shifts
the near-term policy focus to non-R&D innovation as the mechanism to achieve productivity
growth, and it introduces a clear emphasis on targeted measures (ISA, , p. ). Taken against
successive governments’ flight over the last years away from the interventionist industrial pol-
icy/innovation framework of the s (Dalitz, ; Dodgson et al., ; Marsh & Edwards, ,
), recasting this strategy heralds a significant turnaround. Under NISA, measures to stim-
ulate more collaborative R&D were the main policy plank in a principally neoclassical market
failure-based framework. But its ‘ideas boom’ failed to materialise. A series of reviews and fund-
ing changes from onwards largely removed innovation policy from the national agenda –
until the proposed SBII.
This paper synthesises a new study with two others over the last decade; together, they indicate
that one of NISA’s measures to incentivise collaborative R&D may be starting to impact positively.
Following release of the SBII, however, these findings risk relegation to the ‘too little, too late’ pol-
icy bin. The SBII’s signalled paradigm shift to more openly interventionist measures and its focus
on non-R&D innovation has significant appeal in the austerity of a post-COVID- world. How-
ever, the devastating global impact of COVID- itself demonstrates the importance of R&D, and
a clear policy recommitment to collaborative innovation would bolster the promising trend found
GEORGE TARR 3
by the studies. In addition, the SBII’s targeted policy approach raises legitimacy issues canvassed
three decades ago by Arup (): susceptibility to capture, and favouritism. If the government
adopts the SBII’s targeted approach, it will be necessary for policymakers to more enthusiasti-
cally embrace openness and deliberative democracy in policy development – an area in which the
government has yet to perform convincingly.
2 AIMS AND METHODS
The aims of this research were fourfold: (i) to map the changing mix of paradigms inherent in
Australian innovation policy over the past years; (ii) to determine stakeholder sentiment and
the impact of NISA measures on collaboration, if any; (iii) to examine the proposed change of
policy direction in the SBII; and (iv) to highlight the potential challenges in implementing the
SBII. A mixed methods approach was taken, given that policy research must be ‘of high technical
quality, comprehensive, and jargon-free’; mixed methods satisfy these needs by incorporating both
qualitative analyses, as well as quantitative technical data (Creswell, ,p.).
Discussion of aims (i), (iii), and (iv) rests on a qualitative historical secondary data analysis of
policy, reports, and literature to come to an understanding of past policy paradigms leading up
to the NISA, and to compare and contrast the proposed new SBII policy and its challenges. This
type of analysis is apposite to policy research as ‘much interest’ lies in policy comparison, and
exploration of policy intention, interpretation, and implementation (Tight, ,p.).
Aim (ii) of this paper requires analysis of NISA’s performance on R&D collaboration. Results
from a new study, and two other Australian studies, are synthesised in order to ‘crystallize’ (Fetters
& Molina-Azorin, ) or ‘combine’ their findings on stakeholder sentiment, to arrive at a more
significant whole (Bazeley & Kemp, ). The first study (‘ study’) was co-designed by one
of the authors of the present paper, and was funded by the Department of Education, Employ-
ment, and Workplace Relations (DEEWR). It was conducted by the Queensland University of
Technology (QUT) (full sample n=; participants completing all questions n=unknown). The
results have been published elsewhere (Heffernan & David, ; Heffernan & Kiel-Chisholm,
; Fitzgerald, ).
The second study (‘ study’) was conducted to update the study (full sample n=,
participants completing all questions n=; ethics approval ID). Recruitment occurred via
expert and snowball sampling, links embedded in social media posts, and an online policy forum
(George et al., ). An online questionnaire was used to collect demographic information, along
with semi-structured and open-ended questions modelled largely on the study. Quantitative
data were analysed using SPSS v. and Microsoft Excel. Qualitative data were analysed using
NVivo Pro software. One author conducted the coding, following reflexive thematic methods
(Braun et al., , p. ), but to optimise reliability, the authors regularly debriefed on emergent
themes and coding (Corbin & Strauss, , p. ; Creswell & Miller, ,p.).The
study is not a repeated cross-sectional study of the study given some variation in questions
and structure, although it drew on the same themes.
The third study (‘Howard study’) was commissioned by ISA, and conducted in by Howard
Partners (full sample n=; participants completing all questions n=). Its quantitative
results were published elsewhere (Howard Partners, ). The authors of the present study
obtained the qualitative data from ISA/Howard Partners for analysis using NVivo Pro software
and reflexive thematic methods. Although both the and studies were skewed towards
the research sector (>% research sector, –% industry), the Howard Study was moderately
skewed towards business (% industry, % research).
3AUSTRALIAN INNOVATION POLICY APPROACHES
Over the past four decades, three broad theoretical approaches may be discerned in Australian
innovation policy: interventionist, free market, and systems thinking. Policy frameworks have
included shifting mixes of both interventionist and free market approaches. Systems thinking
narratives, while increasing over the last years, have yet to be utilised as a main policy anchor.
Although each approach brings differing nuances and perspectives, sufficiently rough boundaries
exist to support a useful heuristic for considering their relative dynamics and tensions (Dodgson
et al., , p. ). This section briefly traces the changing mix of innovation policy paradigms,
and the shift towards a focus on collaborative R&D.
3.1 Interventionist policy
From to the mid-s, Australia moved away from a tariff system established in
the s to protect local industry, towards economic liberalism. Sweeping changes in
macroeconomic and industry policy were introduced to open the country up to interna-
tional competition, with the Hawke Labor government embracing an ‘interventionist’ or ‘tar-
geted/‘selective’/‘corporatist’/‘coordinated’ policy approach (Arup, ;Dalitz,; Dodgson
et al., ; Emmery, b). The government’s Button Plans (–) reduced tariff protec-
tion and import quotas, restructured major industries, and provided targeted industry assistance.
Industry Minister John Button spoke of embracing a ‘culture of innovation’ (Carr, ); industry
policy was viewed in a broad social context, with economic reforms being supported by additional
measures for displaced labour (Capling & Galligan, , p. ; Emmery, b). These ‘atypically
intelligent’ (Jones, ) or ‘enlightened’ (Dodgson et al., , p. ) policies demonstrated that
structural change can be facilitated by ‘establish[ing] closer partnerships between government
and industry’ (Emmery, b).
However, critics opined that interventionist policy, pursued in the absence of industry restruc-
turing imperatives, may generate ad hoc incentives that change at the whim of sectoral interests
or Budget cost cutters (Emmery, b). Public law scholars raise similar legitimacy concerns,
given the cloistered environment of Westminster policy-making, and perceived lack of public
engagement in the government and Australian public service (APS) (Australian Government,
; George et al., ). Ironically, even Button himself cautioned against ‘detailed attempts
to “pick winners”’ (Conley, ).
3.2 Rise of free market policy
‘Free market’/‘market failure’ policy stands in stark contrast to interventionism. This approach
defers to market processes, aligning with the rule of law and its limited, detached role for the
public sector (Arup, , p. ). In this paradigm, economic phenomena are deemed to occur
in ‘a succession of static optimal states’ (Dalitz, , p. ). Policy aims to optimise resource
GEORGE TARR 5
allocations, intervening to correct market problems such as inefficient allocation of goods and
services (market failures).
In this paradigm, innovation is a linear process: invention runs through to commercialisation
in a perfectly competitive market. Where innovation-related market failure arises, policy inter-
vention is justified; for example, where R&D produces spillover benefits for third parties that can-
not be captured by the innovating firm, thereby disincentivising investment in R&D. Financial
instruments are typically used to increase innovation pace – not direction – such as subsidies for
R&D, tax relief, and venture capital market (corrective) regulations. (Edquist, ; Hekkert et al.,
; Marsh & Edwards, ). Within free market orthodoxy, the rejection of ‘picking winners’
is almost religiously observed (Arup, , p. ; Marsh & Edwards, ,p.).
The Howard Liberal government’s embrace of free market policy came in conjunction with
several influential reports, including Mortimer’s () wide-ranging inquiry. Innovation policy
of this era has been described as a free market approach that ‘strongly opposed sectoral programs’
(Marsh & Edwards, ), although this may be overstating the case. While the free market narra-
tive has dominated from Howard’s era onwards, governments cannot afford to be purist – realpoli-
tik dictates that all engage in interventionist strategies of some kind (Emmery, a; Jones, ).
Indeed, the Howard government retained the Button Plans (Jones, ), and Mortimer himself
suggested that industry policy should go further than what the market determines (Richardson,
); he ushered in targeted ‘action agendas’ that were criticised by neoclassical pundits such
as the Industry Commission (Gibbs & Emery, ; Richardson, ). Sometimes, calls for inter-
ventionist partnerships were infused with the more acceptable free market narrative, positing that
‘[t]he Commonwealth Government must work in partnership with industry to overcome areas of
market failure and promote more dynamic economic growth’ (Emmery, a).
3.3 Emergence of systems thinking
The ‘systems’ paradigm also emerged during this time. Proponents emphasise innovation sys-
tems as interconnected, profoundly uncertain, and directed often by emergent properties. Systems
thinkers eschew free marketeers’ use of an equilibrium-based linear theory, for one that embraces
dynamic processes that destroy equilibrium (Dalitz, ; Dodgson et al., ). Market failure is
not only tolerated, but taken as part of the fabric of innovation. Joseph Schumpeter’s (,)
work advocating ‘industrial mutation’ and ‘creative destruction’ is commonly referenced, but the
notion of a national innovation system (NIS) actually dates back to the th century (Dekkers
et al., ; Freeman, ; Lundvall, ; Marshal, ; Nelson, ).
For systems thinkers, the principal threat is system failure due to a lack of support for innova-
tion or business model experimentation. Systems-oriented policy thus addresses limiting factors
for actors responding to dynamic change, focusing on connection-forging initiatives (Dalitz, ;
Dodgson et al., , p. ; Hekkert et al., ) rather than single-firm measures such as R&D tax
incentives. Systems policy also considers demand-side activities (such as creating new markets),
in contrast to the usual supply-side (science push) free market approach (Dalitz, ; Dodgson
et al., ; Marsh & Edwards, ,).
A significant benefit of systems theory is its ability to embrace other forms of innovative activ-
ity, such as non-R&D innovation (Dodgson et al., ), and transformative innovation, with its
focus on social and/or environmental issues (Fagerberg, ,; Mazzucato, ). In fact,
innovation policy is itself viewed as a complex system (Dodgson et al., ). Schools of thought
are nuanced. For some, innovation policymaking may constitute an intermediary/facilitator role
whereby ‘the government does not just leave things to the “free market” yet it does not “pick win-
ners” either’ (Dodgson et al., , p. ). For others, it necessarily involves an interventionist
approach: ‘where technological development is the object, selective or focused policies are also
first best’ (Dalitz, ; Marsh & Edwards, ,p.).
Systems narratives have swelled in the last decade, but policy traction remains limited (Dodgson
et al., ; Marsh & Edwards, ). Marsh and Edwards (,) traced an early traction fail
at the National Innovation Summit, in the lead up to the Backing Australia’s Ability policies in
and . The Summit, they concluded, was a ‘decorative activity’ that failed to exercise ‘any
substantive influence’ on policy thinking (Marsh & Edwards, , p. ); it was constrained by
hazards of institutional lock-in with the successful free-market paradigm, multiple veto points,
and pressure to maintain fiscal and policy discipline.
The Productivity Commission report on science and innovation (PC, ) then articulated
a policy theory ‘void’: while conceding that neoclassical policy benchmarks were essentially
unattainable, it failed to engage with systems theory as an alternative (Dalitz, ,p.).The
Cutler Review () and Labor government’s Powering Ideas framework () were infused
with a systems thinking narrative, and included some selective measures, but also ran the mar-
ket failure narrative in tandem, creating a ‘confused co-existence’ that dictated policy outcomes
(Dodgson et al., , p. ). In lieu of focusing on ways to cure the lack of collaboration identi-
fied by the Cutler Review, two thirds of government support for business innovation were devoted
to single-firm support via the R&D tax incentive (Dodgson et al., ).
3.4 Swing back to free market policy
The Abbott Liberal government’s policy from to represented a ‘rejection of an innova-
tion systems [approach] .. . and a recommitment to market mechanisms’ (Howard & Green, ,
p. ). The Industry Innovation and Competitiveness Agenda (IICA) expressly advocated a neo-
classical framework to address market gaps and deficiencies. Set against Liberal austerity imper-
atives, the IICA contended that prior policy frameworks had ‘overreached’ their role, spending,
regulating, and borrowing too much, whereas subsidies had ‘distorted’ business decision-making
without addressing the problems, undermining productivity (Australian Government, b,p.
). Despite strong recommendations for greater incentivisation of R&D collaboration in prior
reports, including by the IICA itself (pp. , , –), the ‘imbalanced’ level of single-firm R&D
support increased from % (Dodgson et al., , p. ) to around % of programs encouraging
business investment in innovation (George et al., ).
3.5 Innovation policy loses its way
The NISA was then launched in under the Turnbull Liberal government. It employed the
usual free market narratives, positioning its role as investing in enablers (education, science,
research, and infrastructure), incentivising business investment (remediating underinvestment),
and removing regulatory obstacles. More than % of total spend was devoted to incentivising
R&D collaboration, given that Australia had placed lowest in the Organisation for Economic Co-
operation and Development (OECD) rankings (Australian Government, ,p.).However,
the NISA’s ‘disparate’ measures (Auditor-General, , p. ) seemed to gain little traction.
Following a damaging performance audit of its design and implementation in , the agencies
GEORGE TARR 7
conceded that little impact would likely be registered from the $. billion spent (Auditor-General,
; George et al., ).
ISA then proposed a new innovation plan (‘ Plan’) (ISA, ). The Plan, following
on from its Innovation Systems Review (ISA, ), adopted a systems thinking narrative. It iden-
tified ‘critical gaps’ in the innovation system, lagging commercialisation and export performance,
and ‘a tendency towards incremental rather than new-to-world innovation’ (ISA, ,p.).
Recommendations included more interventionist measures such as national missions to ‘catalyse
novel and new, rather than incremental, innovations’ (ISA, ,p.),aswellasdirectgrants.A
mix of R&D-focused free market-style initiatives was also included, such as reforming the R&D
tax incentive and a collaboration premium. Reactions to the Plan ranged from it being ‘[one
of the] more serious efforts at strategy development’ (Howard, , p. ); to ‘wildly ambitious’ but
with modest recommendations – which, post-NISA, were tailored for a risk averse, disinterested,
cost-cutting government (Riley, ).
However, governmental response was ambivalent, with just of the recommendations
receiving support (Australian Government, ). Innovation effectively departed the political
agenda, with the newly appointed Minister for the Industry portfolio, Karen Andrews, observing
innovation to be ‘political poison’ after the election (Redrup, ). By , ‘Innovation’
had been deleted from the Industry portfolio title, and the R&D tax incentive program had under-
gone reform and successive cuts (Ferris et al., ). Commentators – depending on perspective –
viewed the government as either having ‘left innovation for dead’ (Powell, ), or putting inno-
vation policy into mothballs for a ‘reset’ period (Howard & Green, , p. ). Figure sets out a
timeline of the shifting innovation policy approaches from to .
The – reset period presented an opportunity to study stakeholder sentiment regarding
R&D collaboration which, as noted, was a central concern of NISA and the Plan. Although
a formal review of measures targeting collaboration is not scheduled until , the studies dis-
cussed in Section suggest NISA’s measures may be shifting stakeholder sentiment. These studies
provide context for the most recent move to change policy direction (SBII), discussed in Section .
4THE R&D COLLABORATION CONUNDRUM
4.1 The policy challenge
Many studies have found that collaboration enhances innovation and productivity (Blomqvist
et al., ; Cin et al., ; Katz & Martin, ; Perkmann & Salter, ; Yasar & Paul, ).
An oft-cited policy statistic is that innovative firms are ‘three times’ as likely to grow productivity
(ISA, , p. ; Australian Government, ,p.;Watt,, p. iii). Although others have
argued that evidence is ‘not always convincing’ (Dickinson & Sullivan, ; Glasby & Dickson,
; Sullivan et al., , p. ), there is a pervasive neoclassical belief in the ‘direct link’ between
R&D and economic growth (Dalitz, , p. ). Reports and policy frameworks for more than
years have embraced the notion that policy must boost R&D collaboration to drive innovation,
commercialisation, and thus productivity (ACIP, ;ACOLA,; Australian Government,
,,,a,;Cutler,; DISER, –,;Howard,;ISA,,;
McGauchie, ;PC,;Watt,). Policymakers have been ‘desperately seeking innovation
nirvana’ (Noble et al., ), but with little success on metrics such as OECD rankings (OECD,
), or the Global Innovation Index, as shown in Figure .
FIGURE 1 Timeline of Australian Innovation Policy Approaches, – [Colour figure can be viewed at
This is perhaps unsurprising, as the innovation triple helix (government, research, and indus-
try) involves significant collaboration challenges for all stakeholders (Bruneel, D’Este, & Salter,
; Dodgson et al., ;Howard,,; McBratney & McGregor-Lowndes, ). The Aus-
tralian experience is illustrative. In , Australia was described as having a relatively low level
of science and technology expenditure, a high level of government financed research, low level of
private sector R&D, and high dependence on foreign technology (Dodgson et al., ;Gregory,
). The situation may have ‘improved somewhat’ (Department of Industry, ,p.),butAus-
tralia remains predominantly a technology taker rather than maker (Green & Logue, , p. ).
Relational and cultural issues dividing the research and industry sectors pose ongoing challenges
GEORGE TARR 9
FIGURE 2 Global Innovation Index, Australian rankings on selected indicators, – [Colour figure
can be viewed at wileyonlinelibrary.com]
The NISA introduced two measures aimed at the research sector in a kind of ‘carrot and
stick’ arrangement: realignment of block grant funding towards industry-focused outcomes, and
engagement and impact reporting (Watt, ). Three studies provide new insights into how NISA
performed in terms of encouraging collaborative R&D, before what may be a step-change in inno-
vation policy focus with the proposed new SBII policy framework.
4.2 The 2008, 2018, and Howard studies
As discussed above in our aims and methods, in this section we gather results from a new study,
plus two earlier Australian studies. The study included a survey to investigate stakeholder
sentiment on collaboration, its challenges (particularly legal and contracting), success factors, and
policy options. The study was designed to update the results. The authors also obtained
data from the Howard study that supported the ISA Plan. The ‘crystallized’ (Fetters & Molina-
Azorin, ) or ‘combined’ findings on stakeholder sentiment present a more significant whole
(Bazeley & Kemp, ).
The study confirmed the research sector’s reluctance to collaborate: universities were less
likely than government, or industry, to be involved with industry (Heffernan & David, ,p.
). In the study, participants selected their most important partners, rather than frequency
of partner collaboration. However, a similar divide in research sector/industry focus was found.
Non-small to medium enterprise (non-SME) participants most frequently selected universities as
an important collaborating partner (.%), then large industry (.%), government (.%), and
SMEs (.%), χ() =., p=.. Conversely, SMEs were over three times more likely to report
large industry, government, or other SMEs as important collaborators, rather than the research
sector, as depicted in the shaded section in Table .
10 GEORGE TARR
TABLE 1 Respondent’s most important collaborative partner (n=)
University/College .% .% .%
Industry/Large enterprise 21 19.6% 18.9% 25.0%
Government 18 16.8% 15.8% 25.0%
Industry/SME 17 15.9% 14.7% 25.0%
Other research institution .% .% .%
Non-government institution .% .% .%
Health service .% .% .%
Client .% .% .%
Other .% .% .%
These findings are supported by the Howard survey. Few (%) agreed or strongly agreed ‘busi-
nesses are actively seeking to engage more effectively with universities over innovation’ (Howard,
, p. ). Less than half (%) of participants agreed or strongly agreed that ‘there have been
major improvements over the last years in how effectively universities engage with business
over innovation’ (Howard, , p. ). However, there was some optimism: % of participants
agreed or strongly agreed that ‘universities are actively seeking to engage more effectively with
business over innovation’ (Howard, , p. ). This may be significant in light of further results
in the and studies.
In the study, participants rated the importance of collaboration outcomes. The survey
was conducted prior to NISA, so there was no option for ‘industry impact’. Given the strong
research sector bias in the sample, unsurprisingly the most important outcome was co-authored
publications (%). Publications, sharing knowledge, and student exchanges were more impor-
tant for researchers than government/industry, and entering formal research agreements, intel-
lectual property, licensing, royalties, and product development were more important for govern-
ment/industry (Heffernan & David, , p. ). These divided interests have given rise to many
of the cultural and relational difficulties inherent in R&D collaborations.
The study asked participants to make selections from the same ‘important outcomes’ as
the study, as depicted in Figure . However, ‘improved research practices’ was replaced with
‘to create industry or community impact for my research’, to test the effect of NISA initiatives. The
‘industry or community impact’ outcome was most frequently selected (%). Further, ‘product
development or solutions for industry’ ranked as the sixth most important outcome, moving up
from th in .
Again, the most important outcomes varied by organisation type. Figure shows that research
organisations, as compared to non-research, were more likely to report creating industry or com-
munity impact as a most important outcome, χ() =., p=., followed by sharing knowl-
edge, χ() =., p=., and co-authored publications, χ() =., p<..
Conversely, respondents from industry, when compared to research, were more likely to select
product development, χ() =., p=., followed by entering formal agreements, χ() =.,
p=., and enhanced research infrastructure, χ() =., p=., as depicted in Figure .
These results suggest that while sectoral divisions remain, there has been a shift in research sec-
tor focus towards industry impact. The positive Howard results on universities ‘actively seeking to
GEORGE TARR 11
FIGURE 3 Percentage of all participants selecting ‘yes’ to important outcomes
FIGURE 4 Research/non-research respondents (%) selecting ‘yes’ to outcome as most important
engage more effectively with industry’ support this finding. However, there are some limitations:
the ‘impact’ outcome was not included in the study; the outcome incorporates both
industry and community impact; and the study measured frequency of selection rather than
rated importance. Nevertheless, the study shows a clear research sector focus on impact and
suggests an increased focus on ‘product development’.
12 GEORGE TARR
FIGURE 5 Industry/research respondents (%) selecting ‘yes’ to outcome as most important
FIGURE 6 Agreement with ways of growing a stronger culture of collaborative research
The survey also asked participants to indicate their level of agreement with ways to grow a
stronger culture of collaborative research. As shown in Figure , the mechanism most agreed and
strongly agreed was ‘aligning block grant funding towards collaboration’ (%). This is significant,
given recent suggestions to include similar requirements for business grant funding (Nous, ,
p. ). In contrast, only .% of participants agreed or strongly agreed that ‘engagement and
GEORGE TARR 13
impact reporting’ would assist; thus, it may not be as effective in driving cultural change as antic-
Although these results signal a new research sector focus on impact, they have not yet translated
to an increase in collaborative innovation. As shown in Figure , Australia’s ranking on collabo-
ration slipped from to in , then down to in . And any success seems to have come
‘too little, too late’. The latest policy advice seeks solace in different metrics, and a change in focus
from collaborative R&D to non-R&D innovation, as discussed in the following section.
5 FROM THE 2030 PLAN TO STIMULATING BUSINESS
INVESTMENT IN INNOVATION
The Plan’s recommended innovation metrics review was conducted during –. Its
consultation paper signals a shift in innovation focus – away from R&D (DISER, a). It specu-
lates that Australia’s innovation metrics require recalibration, given that Australia has had years of
economic growth and excellent recovery from the global financial crisis, but has slipped in global
comparative innovation measures. Proceedings indicate there is an ‘urgent’ need for metrics cap-
turing ‘hidden’ innovation, such as in the services and resources sectors, where innovation does
not involve R&D, or occurs informally (DISER, b, p. ). Key messages include that ‘innova-
tion is not just about new-to-world innovation, but is also about innovation adoption and diffu-
sion’ (DISER, a, p. ). This echoes the long-held view of some economists that ‘R&D is no
longer the total sum of innovation performance, if it ever was’, and that non-R&D innovation must
be better integrated in the policy narrative, with a greater systems thinking focus, incorporating
targeted measures (Green & Logue, , p. ).
The innovation metrics workshop presaged the release of two supporting reports for ISA’s new
policy framework (AlphaBeta, ; Nous, ), which also emphasise the importance of non-
R&D innovation. In the clearest of calls to a paradigm shift, the Nous report argues that the ‘timing
is right’ for a policy move – ‘away from the Washington Consensus to a more proactive approach’
(Nous, , p. ). The term ‘Washington Consensus’ is often used pejoratively as shorthand for
free market policies. In endorsing a ‘proactive’ approach, the report notes a ‘reluctance to pick
winners’ (Nous, , p. ), but offers the classic ‘critical mass’ response: Australia should con-
centrate its resources in areas of comparative advantage in the global market – because (a) this is
what others are doing: ‘[o]verseas governments have long picked winners’ (Nous, ,p.);and
(b) the current wide range of low-budget generalist support measures do not seem to be working
(Nous, , p. ). ISA’s Plan ran a similar argument (ISA, , p. ); its most recent report
does the same (IISA, , p. ). It should be noted that free marketeers have long rejected this
argument, because Australia is ‘too small to pretend to world domination’, and in any event, strate-
gic trade theory does not provide guidance on what winners to pick, or how (Emmery, a).
The SBII report was then launched in February by incumbent ISA chair Andrew Stevens.
The SBII relies on the Nous and Alpha Beta reports to recommend a major strategy change: a
‘rebalancing’ of initiatives towards non-R&D innovation, via targeted policy measures. While the
SBII cautiously notes ISA’s past emphasis on R&D, and acknowledges R&D’s importance in ‘the
overall innovation system’, it observes what economists knew: Australian business invests signif-
icantly in non-R&D innovation: new or improved business models, organisation and marketing
practices (ISA, , p. ). Business expenditure on R&D (BERD) is not a strong predictor of this
broader innovation spend, and even where firms invest in R&D, % spent more than half of their
innovation budget on non-R&D activity (ISA, , p. ). Accordingly, a different policy mix is
14 GEORGE TARR
suggested: measures stimulating R&D should be complemented by medium term (– year) ‘sig-
nificant additional’ support for non-R&D innovation, predominantly software/digital technology
(ISA, , pp. , ). Funding could come from new investment or ‘streamlining’ current inno-
vation programs, hinting at possible further cuts to the R&D tax incentive (ISA, ,pp.,).
IISA’s latest report also observes that ‘[i]nvestments made through the R&DTI are agnostic to the
priority growth sectors due to the indirect design of the initiative’ (IISA, , p. ), and that this
measure now comprises % of broad-based business support for business (IISA, ,p.).
A review of all SBII’s recommendations is beyond the scope of this paper; for present purposes,
Imperatives and are of interest as they detail the new interventionist/systems approach. Imper-
ative calls for a policy ‘rebalance’ towards non-R&D innovation, including levers such as pro-
curement and missions, as well as selective funding for high-potential firms (ISA, ,p.,).
Imperative recommends a targeted prioritisation of key growth sectors (from the IICA in ).
Here, the SBII relies on the same ‘critical mass’ argument as the Nous report (SBII, ,p.).
However, the SBII adds a compelling rejoinder to the free marketeers’ rejection of strategic trade
theory. Although Australia may have been too small for world market domination, the scalability
of intangibles in the digital environment means that rapid, global growth is possible and may in
fact pave the way for ‘“winner takes all” scenarios’ (ISA, , p. ). Yet the vexed question of how
to pick the winners and mechanisms to fund them requires ‘more detailed analysis’ (ISA, ,p.
). The most recent report is a first step along this path (IISA, ), although detailed analysis
of this report is beyond the scope of this paper.
Interestingly, although the SBII openly adopts a systems/interventionist approach, it displays
the same ‘confused’ reliance on free market justifications as past policy frameworks (Dodgson
et al., , p. ). When asking ‘[w]hy should government encourage additional non-R&D busi-
ness investment? Where is the market failure?’, the answer is not that the paradigm is a poor policy
fit, but that market failure does exist, as an underinvestment in non-R&D innovation (ISA, ,
p. ). Government intervention is required for all those reasons ‘that have long underpinned gov-
ernment support of R&D’: spillovers can be achieved, but information asymmetries and high-cost
legacy ICT systems present problems; ‘all these market failures . . . result in a sub-optimal invest-
ment in innovation’ (ISA, ,p.).
The SBII then switches back to a systems narrative, stating government’s role is to ‘coordi-
nate, facilitate, and act as a catalyst for innovation and develop new markets for businesses’ (ISA,
, p. ). However, as its name implies, the SBII’s focus is clearly on ‘industry ecosystems’
(used times) rather than ‘innovation systems’ (used five times). The need for industry–research
collaboration is reimagined as the need to facilitate industry’s ‘access to capabilities’ via con-
tract research (ISA, , p. ) – what others call ‘merchandising knowledge products’ (Howard,
, p. ). Otherwise, ‘industry–government’ collaboration is to be funnelled through Indus-
try Growth Centres (ISA, , p. ). Subsequently, ISA was renamed Industry, Innovation and
Science Australia (IISA) in October .
As the above discussion shows, the trajectory back to interventionist policy was signalled by
ISA for some time pre-COVID-, although the new systems narrative is industry-focused, and
the confused reliance on free market justifications has lingered. The Howard study also found
that stakeholders would support an interventionist approach. In the final open-ended question,
‘[p]lease feel free to provide any additional points you would like to stress in your feedback’
(n=), the largest node (coded theme) to emerge was ‘policy, political issues’. Almost two thirds
of the participants were coded for this node (n=; .%). Within this node, child nodes were
created to capture sub-themes within the data. The largest child nodes were ‘lack credible govt
GEORGE TARR 15
FIGURE 7 (A) NVivo coding-all parent nodes. (B) ‘Policy’ parent and child nodes [Colour figure can be
viewed at wileyonlinelibrary.com]
FIGURE 8 NVivo cluster analysis
partial dendrogram: Strongest correlations
[Colour figure can be viewed at
support’ (.%), ‘bipartisan approach needed’ (%), and ‘focus on “winning” sectors’ (%). Fig-
ure A depicts all parent nodes, and Figure B depicts the ‘policy’ parent and child nodes.
NVivo cluster analysis was then performed. Nodes with similar words cluster more closely,
suggesting similar themes. Pearson correlation coefficient was applied. As shown in Figure ,
there were very strong correlations between parent node ‘policy, political issues’ and its child
nodes ‘lack credible govt support’ (.), ‘bipartisan approach’ (.), and ‘focus on “winning”
Both node sizes and cluster analysis suggest that although there is ambivalence about inno-
vation policy performance, stakeholders want to see a bipartisan, more interventionist approach
moving forward. Comments included reference to non-R&D innovation (such as business model
innovation), as well as targeted policy –
There is too much attention paid to Technology based innovation and not enough
on the humanities or human-centred aspects such as Business Model Innovation .. .
The issue of government having an obsession with not picking winners was not
addressed in the survey except in one question relating to risk. Other countries with
successful innovation systems do not have such constraints (Respondent ).
16 GEORGE TARR
Howard’s latest study urges that ‘[w]e must dispense with the idea that an active industrial
strategy is about “picking winners”’ (Howard, , p. ). On the SBII, he dismisses ISA as ‘side-
lined’ and relegated to producing ‘safe information papers’ (Howard, , p. ). He calls for
a ‘major investment commitment’ to research, development, and innovation in new technology
areas (Howard, , p. ). Minister Karen Andrews has indicated that the government will con-
tinue to support R&D collaboration, but this does not mean a ‘Spend-A-Thon’ of new initiatives
The SBII’s focus on non-R&D innovation aligns with emerging research on COVID--related
business activity. The Australian Bureau of Statistics’ (ABS) Business Impacts of COVID- sur-
vey in March found that % of businesses responded to the impact of COVID- by engag-
ing in non-R&D innovations, changing their method of delivery of products and services, includ-
ing shifting to online. Only % introduced new products (ABS, a). As Stevens noted of this
COVID- data, ‘leaders ... are shifting their business models .. . investing in technology and sys-
tems and investing or changing their marketing and branding strategies’ (Stevens, ). IISA
suggests that five years of progress was made in consumer and business digital adoption in just
eight weeks (IISA, , p. ). The COVID- pandemic may thus lend unexpected impetus for
the government to accept the SBII’s push for a policy ‘rebalance’ toward non-R&D innovation,
given its more incremental nature compared to collaborative R&D: % of businesses reported no
intentions of capital expenditure for – (ABS, b). No doubt, the SBII’s recommended
‘streamlining’/cost-cutting will also be front of mind for a government that has expended around
$ billion to date on COVID-related economic measures (Carnon, ).
Whether government accepts the SBII’s recommendations remains to be seen, although early
indications suggest it will receive a warmer embrace than the Report (Andrews, ; Riley,
b). IISA’s latest report reinforces the SBII’s call to interventionism, asserting that ‘Govern-
ment’s traditional ISR [innovation, science and research] role of stepping in only to address market
failures and asymmetries is being challenged internationally’ (IISA, , p. ). It recommends ‘a
progressive shift toward direct investment mechanisms to achieve targeted outcomes for business-
and higher education-performed ISR’ (IISA, , p. ). If a more openly interventionist style is
adopted, legitimacy concerns will demand an increased focus on openness in innovation policy-
making, as discussed in the next section.
6INTERVENTIONIST POLICY: THE NEED FOR OPENNESS,
As free marketeers have observed, there is an ‘old’ and ‘new’ push for interventionist innovation
policy. The ‘new’ push, freed from the Hawke-Keating era wider economic reform agenda, brings
with it heightened concerns. The ‘picking winners’ dilemma remains. Policy may be ad hoc, and
subject to capture (Emery, a). Howard suggests the problem is that funding decisions are made
‘under a wide range of public administration and political processes’, including opaque criteria,
ministerial discretion, and ‘informal one-off grants arising from advocacy and lobbying’ (Howard,
, p. ). He suggests a new commission and suite of new councils to provide accountability.
In the absence of effective mechanisms to sure up governance and accountability issues, inter-
ventionist policy also raises complex legal issues around executive power and the cloistered nature
of policy-making in the Westminster system, given its conventions of secrecy. More than years
ago, Arup () raised legitimacy concerns with the increase in government–industry partner-
ships and selective innovation policy, given that policymaking is largely beyond parliamentary
GEORGE TARR 17
or judicial scrutiny. He suggested procedural reforms, and audits, to check policy-making power.
However, the audit results on NISA show that neither agency policy guidelines nor the prospect of
an audit was sufficient to prevent deficient innovation policymaking (George et al., ). Lessons
from the audit no doubt factored into Minister Andrews’ request for, and IISA’s recent production
of, its further report on ‘the effectiveness of the Commonwealth Government’s investment in, and
system performance of, ISR’ (IISA, ).
Another checking mechanism is the Freedom of Information (FOI) regime, which was
designed to provide the public with some level of oversight of government and agency policy-
making. In , the Australian Law Reform Commission (ALRC) noted FOI requests for policy
information are the litmus test for increased government accountability and citizen participation
– but FOI costs, inconvenience, and frustration resulted in few applications (ALRC, ). The
regime presently fails to provide the intended level of public scrutiny of policymaking (George
et al., ).
The other means of increasing accountability lies in government engagement initiatives. How-
ever, reform initiatives over the past two decades designed to increase levels of openness and
deliberative democracy within the government and APS have failed to gain traction (George et al.,
). The recent independent review of the APS recommended a Charter of Partnerships to set
expectations around engagement (Department of the Prime Minister & Cabinet, ,p.),but
the government instead adopted the newly minted APS Framework for Engagement and Partic-
ipation (Australian Government, ). The ‘deliberative’ engagement mechanism in this new
framework has a welcome emphasis on policy co-design and is apposite in the innovation port-
folio where, if government deliberates alone, this ‘will create winners or losers’ (Australian Gov-
The SBII framework is the first step in a potentially significant move to more interventionist
policy, and the shift from a largely R&D focus to make way for non-R&D will understandably rattle
the nerves of the collaborative R&D sector. IISA’s latest report certainly recommends accelerated
support for non-R&D innovation, although not at the expense of ‘effective’ investment in R&D
(IISA, , p. ). A clearer policy recommitment to R&D would bolster the emerging positive
trend in stakeholder sentiments around innovation in this sector. Whether the SBII can succeed
where the Plan failed in achieving government acceptance of more interventionist policy
remains to be seen. But if it does, there will be clear ‘winners’ and ‘losers’, and policy development
will need to adhere closely to the deliberative co-design prescriptions in the new APS Framework,
to avoid another disappointing outcome like the NISA. IISA’s latest report does not feature sig-
nificant narratives around co-design for the government’s ISR investments, apart from the newly
emerging space sector program (IISA, ,p.).
This paper has mapped the trajectory of Australian innovation policy over the past years, from
interventionist policy of the s to a predominantly ‘free market’ paradigm. Policymaking up to
the NISA was dominated by supply-push, generalist financial policies, such as the R&D tax incen-
tive. The focus on R&D collaboration has evolved from the free marketeers’ view of innovation
as a largely linear process, which government can ‘boost’ by pulling policy levers to drive inno-
vation and hence productivity. However, the systems approach also focuses on collaboration, by
driving up the level of connectivity between elements of the system (Dalitz, ; Dodgson et al.,
;Howard,). The failure to increase research–industry collaboration has been called a
18 GEORGE TARR
fundamental ‘system failure’ (Howard, , p. ), but although systems thinking has entered
policy narratives, there has been little success in implementing systems-oriented policy design.
Although the NISA was largely ineffective, our study, taken together with the and
Howard studies, suggests that its realignment of block grant funding may actually be having an
impact on research sector sentiment towards collaboration and industry impact. However, any
success in this area may be ‘too little, too late’. The SBII signals a policy paradigm shift on two
important fronts: greater adoption of interventionist measures, and a new focus on non-R&D
innovation. The SBII has moved to embrace non-R&D innovation at a fortuitous time. ABS data
indicate the likely impact of COVID- is that firms will gravitate towards more incremental, con-
tinuous innovation as a means to secure recovery and growth in the austerity of a post-COVID-
business environment. Yet collaborative R&D has an important place in the emerging answers to
the COVID- problem (IISA, ), and this factor alone highlights the need for policy balance,
and a recommitment to its long-term support. The government has yet to respond to IISA’s call
(IISA, , p. ) to shift business- and higher education-performed ISR toward direct mecha-
nisms to achieve targeted outcomes.
The paper argued that any return to interventionist policy will necessarily encounter the usual
objections from free market policy proponents: ‘picking winners’ is a dangerous game, expos-
ing the government to sectoral capture. Finding funds to selectively stimulate non-R&D inno-
vation in the post-COVID austerity will likely involve cost cutting, and losers, in other industry
sectors. Interventionism also attracts the public lawyer’s ire, given policymaking in Australia, at
this stage, largely remains beyond the scrutiny of parliament, the courts, and the public. If the
government accepts the SBII’s challenge, the move will require an enthusiastic embrace of the
new APS Framework, and greater levels of deliberative democracy than we have seen hitherto in
This study was carried out with funding from CQUniversity under a New Staff Grant.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
AJ George https://orcid.org/---
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