Learning, innovation and competence building systems -

LICS

Interfacing Innovation

April 21 2009 Bruxelles

Bengt-Åke Lundvall

Aalborg University

Historical roots

• The concept national innovation system was coined by Christopher Freeman – brilliant economist and founder of European innovation research and SPRU (Science Policy Research Unit) in a consultancy report for OECD 1983. (That he has not received the Nobel Prize in economics reflects the narrowmindedness of mainstream economists!!)

• As always, when you start digging, you find conceptual ancestors. Freeman refers to Friedrich List (1841). Others have gone even furthe back in history and pointed to Antonio Serra (1613) and Babbage (1829) as scholars who had ideas that were close to the modern concept of national innovation system.

Early and new applications of the modern innovation system concept

• 1987-88 Freeman, Nelson and myself published the first books and articles on the national innovation system. We were all involved in OECD’s TEP-project and OECD ’legalised’ the concept in publications around 1990.

• The first leading politician who used the concept of national innovation system was my co-ambassador Esko Aho – as Prime Minister in 1990 he launched the idea that Finland’s innovation system must be strengthened.

• One recent application is China’s 15 year plan for science and technology. This plan designed under leadership of the Prime Minister refers to the national innovation system as the methodological framework.

• See also www.globelics.org and references on the web to asialics and cicalics (China) and other emerging lics-networks.

The List-Freeman-Lundvall NSI-concept was rooted in the production system

• List, Freeman and Aalborg versions of innovation system analysis were broad and linked innovation to the production system and to the organisation of firms.

• The aim was to understand catching-up or international competitiveness.

• Triple Helics concept that links university-state-industry only captures part of the innovation system.

Why do we need broad definition of innovation systems and innovation policy?

• In order to explain how new ideas are brought to the market and transformed into economic performance it is necessary to take into account both science-based learning and experience-based learning

• Human ressources and organisation within and across firms are thus among the most important dimensions of the innovation system. The role of users is fundamental.

• All innovations need interaction with users as well as employee involvement (User-driven and Employee-driven innovation are recent misconceptions of what should be seen as a systemic process).

The message

• The drift away from the original concept of NSI has made it too narrow - linking innovation mainly to science-based learning (STI) and neglecting experience-based learning (DUI).

• Strong science with weak innovation within a nation or within Europe is not a paradox! It reflects a misconception of the innovation process.

• A call for a broader innovation policy strategy for Europe. Do you as journalists contribute to STI-bias in the public innovation discourse?

The paradox and the built in STI-bias

The Paradox (Europe for instance): ’Systems with a lot of good domestic science but less successful in innovation’

• Reflects the limited perspective with too much focus on Science based learning (STI) to the neglect of Experience based learning (DUI).

• Two reasons for bias: – STI-learning can be measured and manipulated

more easily than DUI-learning– Policies aiming at stimulating STI are less

controversial – tax rebates on R&D are popular.

The double change in context

• ICT and access to elements from the science base becomes increasingly important for firms in all sectors – calls for a strengthening of STI-mode of learning

• But these changes and globalisation contribute to accelerating change and requires learning organisations – calls for a strengthening of DUI-mode of learning

Illustrating empirically how DUI- and STI-learning promote innovation

• Year 2001, DISKO survey on technical and organisational change addressed to Danish firms in the private sector.

• Survey and register data from 692 firms included in the following analysis.

• Establishing four clusters Low effort, DUI, STI and DUI&STI

• See: Jensen, Johnson, Lorenz and Lundvall in Research Policy 2007.

DUI-learning - seven indicators reflecting ’learning organisation’ and ’user focus’

• The firm makes use of some of the following practises:– Interdisciplinary workgroups– Quality circles/groups– Systems for collecting employee proposals from

employees– Autonomous groups– Integration of functions

• Demarcations between groups of employees have become less sharp 1998-2000.

• The firm has established closer relationships with customers 1998-2000.

STI-learning – three indicators reflecting R&D-effort and networking with scientists

• The firm has positive expenditure on R&D.

• The firm has personnel with academic degree in natural science or engineering.

• The firm interacts with researchers attached to universities or other science institutes.

Odds ratio estimates (control for sector, size & ownership) - using low effort-cluster as

benchmark

Odds ratio Coefficient estimate

DUI&STI 5.064 1.6222**

STI 2.355 0.8564**

DUI 2.218 0.7967**

On the need to combine science-based with experience-based learning

• Firms combining science-based (STI-mode) with experience-based (DUI-mode) learning are more innovative than firms biased toward one mode.

• Implies broad definitions of innovation systems, innovation policy and knowledge management.

Two kinds of bias in innovation and industrial policy

1) Promoting the science base of high-tech firms assuming DUI takes care of itself

2) SME policies often neglects the importance of linkages to sources of codified knowledge

The big challenge lies in stimulating firms to combine the DUI- and the STI-mode.

One challenge is to upgrade the STI-mode in traditional industries and in SMEs

• Stimulating SMEs to hire academic personel (Rene Nesgaard Nielsen’s thesis).– Natural science and engineering personel promotes

technical innovation (STI).– Social science and management personel promotes

organisational change (DUI)

• Orient technical institutes and consultancy firms so that they support the interaction between science-based organisations and SME’s in ’traditional sectors’.

Lessons to be learnt for policy makers

• Combine investment in knowledge with strengthening the demand for knowledge.

• Need to promote DUI and STI-modes in Low Tech- as well as High Tech-sectors.

• Innovation policy needs support from education and labour market policy.

• Environmental and energy policy require innovation dimension.

Are there lessons to be learnt for innovation journalists?

• Does the current profile of specialisation and interest of innovation journalists contribute to the STI-bias in innovation policy?

• Is there a bias among innovation journalist toward quadrant 4 (STI-mode in Hi Tech)?

Low tech

High tech

DUI-mode

1. 2.

STI-mode

3. 4.

• THANK YOU FOR YOUR ATTENTION