Slides from the Conference Tentative Governance in Emerging Science and Technology, University of Twente, 28th-29th October 2010.

1. EU-SPRI Conference ‘Tentative Governance in Emerging S&T’
Complexity and co-ordination:
rethinking the ‘policy mix’ for
innovation
Kieron Flanagan (University of Manchester)
Elvira Uyarra (University of Manchester)
Manuel Laranja (Technical University Lisbon)

2. What is this „policy mix‟?
• Recently emerged into innovation policy discourse
• Comprises several (obvious?) observations:
– that innovation-driven economic success depends on
more than traditionally-conceived STI policies (influence
of evolutionary and „systems‟ views)
– that different policy instruments, including policy
instruments from different policy domains, can interact
• Who has realised this (and why)…?
– Not only academics... but also (European) policy-makers
in search of an explanation for relative failure of
(European) innovation policy and influenced by the
broader perspective encouraged by the development of
„systems‟ views

3. Two possible definitions?
• A narrow view: „innovation policy mix‟
– the mix of policy instruments currently defined
as being within the purview of „innovation policy‟
• A broader view: „policy mix for innovation‟:
– the mix of policy instruments which interact to
influence the extent to which the goals of
innovation policy are achieved (innovation
outcomes)

4. Unpacking the concept requires
unpacking our approach to policy
• Much public policy analysis retains an implicit
model of “the policy process” heavily influenced by
the neo-classical welfare economics tradition
• Innovation policy analysis is no exception!
• This model is static, mechanistic, state-centric and
reliant upon a series of unrealistic assumptions
• Such models have increasingly been discarded in
mainstream policy studies in favour of others
• They also contrast starkly with our neo-
Schumpeterian/ institutionalist views of innovation
processes

5. Agenda-setting and rationales
• How are policy problems diagnosed?
• Where do policy ideas come from?
• Much policy analysis implies that
„rationales‟ derived from economic
(innovation) theory are the primary driver of
policy
• In this view “the policy-maker” is a passive
recipient of „rationales‟ which are
straightforwardly translated into policies

6. Agenda-setting and rationales
• The evidence suggests that such cause-
effect relationships are but one factor
amongst many influencing public policy
• Policy makers seldom fully “buy into”
theories
• Theories often lack clear policy implications
• Theories may at best suggest actors and
cause-effect relationships that policy action
can “target” (Laranja et al, 2008)

7. Actors and agency
• Innovation studies highlights a multiplicity of
actors in innovation processes
• But policy analysis often assumes a single
or limited group of State-centric, rational
“policy makers”
• Other actors are often reduced to the
„functions‟ they perform in the “innovation
system” - treated as passive targets with
little or no agency in relation to the policy
process

8. Actors and agency
• The political/policy science literatures point to
a high degree of agency of a diverse range of
actors in the policy process (albeit an agency
constrained by „institutions‟)
• We also need to be careful to distinguish
between actor types and the role(s) that they
play (actors can play multiple roles, play
different roles at different times, and similar
actors in different systems may play different
roles)

9. Some suggested role types
Policy principals Actors mobilising resources in order to achieve
a policy goal/goals
Policy
entrepreneurs
Actors promoting a policy problem/solution
package
Policy targets Existing actors targeted by policy action for
behaviour change
New actors (organisations or networks) created
by policy action in order to play a particular role
in the „system‟
Policy
implementers
Existing or new actors in receipt of resources
from a policy principal in order to achieve a
policy goal
Policy beneficiaries Actors who benefit (or lose out) from the
impacts/outcomes of the policy action

10. Action and instruments
• Innovation policy studies often (implicitly) adopt a
„policy instruments‟ approach
• „Instruments‟ are often treated as if they are
discrete, stable more or less substitutable (e.g. the
Erawatch/Trendchart approach)
• However, especially with partly articulated and
often conflicting „rationales‟, multiple actors playing
multiple roles which change over time, “the same”
instruments can be interpreted and implemented in
different ways (c.f. Innovation Vouchers)
• Instruments can also be an end in themselves

11. Voucher Scheme
Stated rationales/goals Targets of policy action
Implementation
Stimulate/
raiselevelofdemandfor
R&Dinfirms
Support
R&Dperforming
institutions
Promotecollaboration
MakepublicR&Dmore
responsivetodemand
signals
Matchsupplyofand
demandforknowledgein
thesameregion
Eligible voucher
recipient
R&D/knowledge partners
Facevalueofvoucher
Allocation and other conditions
AllSMEs
OnlySMEsin
specificregion
Specificsectors/
activitiestargeted
Partnermustbein
samecountry
Partnermustbein
sameregion
University&public
researchinstitutes
Privatesector
SMEsnotpreviously
inreceiptoffunding
Newcollaborations
only
Firstcome,first
served
Onevoucherper
SME
Prioritytosmallest
firms
Multiplevouchers
canbecombined
SMEco-funding
required
AT Innovation Voucher     <5000    No
info
BE
Wallonia Technology
voucher        550   
CY Innovation Voucher       5000   No
info
DK
Knowledge Voucher -
small innovation
projects
     6670-
13330  
DK
Research voucher for
SMEs       < 0.2m   
GR
Innovation Voucher for
SMEs        7000    No
info
HU
INNOCSEKK Innovation
voucher     No info
12000-
0.12m 
NL Innovation voucher     
2500
(small)
7500
(large)
   
PT
SME Skills Support
System - Innovation
voucher
    No info <25000  No
info
Are Innovation Vouchers an instrument? Diversity of goals, targets and means in Innovation Voucher schemes
Source: InnoPolicyTrendChart inventory

12. Time and policy learning
• The time dimension, in particular, is downplayed in
much (innovation) policy analysis
• Each use of an “instrument” intervenes at a certain
moment in a continuous stream of events that both
condition and constrain the evolution of the
instrument and which are influenced by the
instrument
• In particular, all actors in the policy process learn
over time and this can impair our attempts to
understand cause-effect relationships
• This should focus our attention on “policy learning”

13. Interactions and trade-offs
• This idea of interactions between “policies” is
central to the policy mix concept, but most policy
studies remain overwhelmingly focused on single,
standardised and interchangeable “instruments”
• But even nominally similar instruments in fact differ
in terms of rationales, goals, use and impacts over
time, across space and policy domains
• Public policy goals are often (necessarily) diffuse,
vague and contradictory
• It is often policy rationales and goals, as well as
means, that are in tension in a “policy mix”

14. Conceptualising interactions in a policy mix
Dimensions of policy interactions Forms of interaction
Policy „space‟
Governance „levels‟
Geographical space
Time
Between different instruments targeting the
same actor or actors (within/across policy
dimensions)
Between different instruments targeting
different actors involved in the same social
or economic process (within/across policy
dimensions)
Between different instruments targeting
different processes in a broader „system‟
(within/across policy dimensions)
Between (nominally) „the same‟ instruments
across different policy dimensions
Possible sources of tension between instruments in a policy mix
Conflicting rationales
Conflicting goals
Conflicting implementation approaches

15. Some key questions/challenges
• The term was developed to describe the effect of
varying the mix of two relatively discrete economic
policy instruments (and generally with respect to a
single simple outcome indicator)
• „Innovation‟ is not a single, measurable outcome
(indeed it is arguably not a meaningful policy
outcome at all)
• Policy instruments affecting the outcomes sought
by innovation policy are likely to be complex and
flexible to changing interpretation - especially in
implementation - across time and space (e.g. the
diversity of nominally similar „innovation voucher‟
schemes)

16. How is the term used?
• The term is assumed to need no definition – it is
under-conceptualised
• Despite this lack of definition, normative assertions
are made about „mixes‟:
– Mixes should be “appropriate”, “effective”, “balanced”…
– …and this is a challenge of “coherence” and “co-
ordination”
• These prescriptions are generally seen as
unproblematic

17. Possible challenges
• Conflicting policy goals and rationales within and
especially across domains
• Challenges to co-ordination (weak central
structures versus strong vertical structures in many
governments; risk of silo mentality or clientalism
within ministries or agencies)
• Dispersion of power away from national
governments and their agencies – less and less
ability to influence regulation, standards, financial
markets etc. (emergence of multi-level, multi-actor
policy mixes)

18. Fundamental challenges
• How could we evaluate the effectiveness of
a policy mix?
– How can we identify and measure interactions
and influences?
– Part of „systems level‟ evaluation?
• How can we improve the governance of the
policy mix? What mechanisms are/could be
used?
– „Procedural‟ (governance) instruments such as
high level councils are seen in many countries

19. Fundamental challenges
• Can an “optimum mix” be constructed?
– Implications of evolutionary economics and
„systems‟ thinking not fully incorporated into
policy analysis?
• Designed versus emergent mixes
• Few policy mixes are in any sense an active construct
• Most are the emergent result of many separate
decisions taken by different actors, for different
reasons, at different times

20. Can the „policy mix‟ concept be
useful?
• We can‟t “co-ordinate” the policy mix for innovation
because “innovation” will always be just one of a
large number of intermediate policy goals
• We can‟t identify “optimum” policy mixes
• The concept should be useful to the extent that it
draws our attention to policy complexity, to the
need to actively consider the trade-offs and
tensions between very different policy goals, and
to the likelihood of positive and negative
interactions over time as well as across
(geographic or „policy‟) space

21. Can the „policy mix‟ concept be
useful?
• As policy analysts, we understandably wish
to be useful!
• We understandably believe the problems of
public policy should be amenable to rational
analysis
• If we expect too much of rational analysis
we simply risk „devaluing the coin‟ (Nelson)
• More modest ambitions, coupled with more
empirical attention to the policy process
might lead to more useful insights?

22. Finally…
• A work-in-progress version of this paper is
available in the Manchester Institute of
Innovation Research/MBS Working Paper
series, and at SSRN:
• http://www.mbs.ac.uk/research/workingpapers/image.aspx?a=209
• http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1629744
• Corresponding author: kieron.flanagan@manchester.ac.uk