Government R&D Funding and Company Behavior

Measuring Behavior Additionality

H.C. Kuo 2009.11.12

Problematic

Evaluation

The Grant Cycle

Problematic

• Questions about the effectiveness of government financing of business R&D are of growing importance to policy makers

• Does it encourage firms to pursue different types of R&D, or to include more collaboration in the R&D process?

• Do firms develop improved R&D management capabilities that lead to enduring changes in their R&D strategy and performance?

Problematic

– Project Fallacy

• Traditional studies of the impact of public R&D grants on recipient firms have often failed to distinguish between a single sponsored project and the longer-term business innovation effort of which it is part

– Measurement and attribution

• It is also difficult to define which effects to measure, and to attribute these to a specific government intervention

Research Framework

DefinitionTheoretical foundations

Cases by Countries

Additionality: a Definition

• Important concept in public finance• Addressing the issue of whether public support is resulting in new

activity rather than substituting for private support that would have occurred in the absence of the intervention

• Dimensions– Input Additionality: budget…

– Output Additionality: profits, patents, products…

– Behavioral Additionality

The Grant Cycle

The Grant Cycle

Input Additionality

Behavioral Additionality

Output Additionality

Measuring Behavioral Additionality

Theoretical foundations

• Resource-based view of the innovative firm– Firms: bundles of resources

• that are unique and difficult to imitate, such as technological knowledge, human resources (including R&D personnel), and capital strength

– proposes resource building and construction as a way to leapfrog the competition

• Value innovation– proposes that companies that grow the most are those

that are able to get into entirely new market segments

– Kim and Mauborgne (2004)

Measuring Behavioral Additionality

• Cases by Countries

Case Study: UK

Case Study: the UK SMART & LINK

• SMART

SME • a company of less than 250 employees group wide and • has either annual turnover of less than €50million or a

balance sheet of no more than €43 million. • No more than 25% of the business may be owned (capital

or voting rights) by one or more other businesses

SMART • the Small firms' Merit Award for Research and Technology

– run by the UK Department of Trade and Industry for a number of years in the 1980s and 1990s.

Case Study: the UK SMART & LINK

Case Study: the UK SMART & LINK

• LINK– Collaborative Research: two partners –

one business and one research base

– Peer Review: the scientific quality of the research is maintained by peer review

– Pre-Commercial

– Maximum Funding

• 75% for feasibility

• 50% for core research

• 25% for development

Case Study: the UK SMART & LINK

Case Study: the UK SMART & LINK

• Behavioral Additionality Effects – Human resources:

• people recruited as a result of one grant were subsequently key contributors to later work.

– Technological knowledge and skills:

• enhancements during one grant were applied in subsequent innovation activities.

– Networking:

• partners and contacts acquired as a result of one grant formed the basis of subsequent collaborations.

Case Study: the UK SMART & LINK

• Behavioral Additionality Effects – Reputational and prestige benefits accumulated

through a track record of awards.

– External knowledge absorption:

• distinct from networking but often a consequence

– Using public support:

• in the context of the critical role of public funding for R&D that was reported by these SMEs, it can be argued that an important dimension of learning is the ability initially to win, and then to sustain, public support through successive applications

– Improved innovation management capabilities

Case Study: EU

Case Study: the EU’s 5th FP

• European Context• fund as a structural policy tool

• The EU Framework Programs for Research and Technological Development

• the main instrument: research, science and technology policies.

• introduced in 1984

• originally conceived as research support mechanisms promoting scientific excellence and the competitiveness of European industry.

• the fifth framework programme (FP5, 1999-2003)

Case Study: the EU’s 5th FP

• Rejected applicants: actual changes in project characteristics

Case Study: the EU’s 5th FP

• Amongst the population of rejected applicants, the absence of FP5 funding resulted in carrying out some of these projects: – a longer time scale

– similar expectations and partners

– with no substitute for EU funds

– more ambitious objectives

Conclusion

BAs: During the Project BAs: After the Project

Contribution

During the Project

BAs: During the Project

• Decision Changes– At least at the Project Level

• Acceleration– Enabling a firm to move ahead

• Expansion– Scale and Scope

• Risk Taking– To take on more challenging R&D projects

After the Project

BAs: After the Project

• Collaboration– ½ to 2/3 new collaboration

• Follow-up– ½ to 2/3 Additional projects funded

• Management capabilities– Further participation in Government programs

– Organizational changes for R&D

– Management strategies changes

BAs Summary

No. Behavioral Additionality During/After

1 Project Additionality D

2 Acceleration Additionality D

3 Scope & Scale Additionality D

4 Challenge additionality D

5 Network Additionality A

6 Follow-up Additionality A

7 Management Additionality A

Contribution

• BAs: – Useful vocabulary for explanation, rather illustration（ the black box）

• Conceptual – bridging the neo-classical approach with the systemic approach

by evaluating the difference in behavior on the firm level due to government financial support has gained support

– The delivery mechanism for grants and the contacts between the agency and firms are as much a part of the effects as is the finance itself

– The legitimacy of policy intervention

Tax or Grant ?

Contribution

• Measurement Issues– Case studies

• a still favored method

– Survey approach

• much of the evidence comes from surveys of program participants

– Cumulative approach

• accurate results may take years rather than the three months typically allocated to a routine evaluation

• the assessment of long-term learning and persistence of effects is crucial

The End

Thank You