EU-SPRI Conference ‘Tentative Governance in Emerging S&T’

Complexity and co-ordination: rethinking the ‘policy mix’ for innovationKieron Flanagan (University of Manchester)Elvira Uyarra (University of Manchester)Manuel Laranja (Technical University Lisbon)

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

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)

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

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

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)

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

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)

Some suggested role typesPolicy 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

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

Voucher Scheme

Stated rationales/goals Targets of policy action Implementation

Stim

ula

te/

rais

e level of dem

and for

R&

D in f

irm

s

Support

R&

D p

erf

orm

ing

institu

tions

Pro

mote

collabora

tion

Make p

ublic R

&D

more

responsiv

e t

o d

em

and

sig

nals

Matc

h s

upply

of

and

dem

and for

know

ledge in

the s

am

e r

egio

n

Eligible voucher recipient

R&D/knowledge partners

Face v

alu

e o

f voucher

Allocation and other conditions

All S

MEs

Only

SM

Es in

specific

regio

n

Specific

secto

rs/

activitie

s t

arg

ete

d

Part

ner

must

be in

sam

e c

ountr

y

Part

ner

must

be in

sam

e r

egio

n

Univ

ers

ity&

public

researc

h institu

tes

Private

secto

r

SM

Es n

ot

pre

vio

usly

in r

eceip

t of fu

ndin

g

New

collabora

tions

only

First

com

e, firs

t

serv

ed

One v

oucher

per

SM

E

Priority

to s

mallest

firm

s

Multip

le v

ouchers

can b

e c

om

bin

ed

SM

E c

o-f

undin

g

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 schemesSource: InnoPolicyTrendChart inventory

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”

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”

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

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)

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

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)

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

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

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

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?

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