Supply and Demand Side Innovation

Policies

Annexes of First policy brief

EUROPEAN COMMISSION

Directorate-General for Research and Innovation Directorate A— Policy Development and Coordination Unit A.4 — Analysis and monitoring of national research policies

Contact: NIETO NUEZ Ana E-mail: Ana.NIETO@ec.europa.eu RTD-PUBLICATIONS@ec.europa.eu

European Commission B-1049 Brussels

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EUROPEAN COMMISSION

Supply and Demand Side Innovation Policies

Annexes of First policy brief

Prepared by: Inno AG, University of Manchester (MIOIR), INNOVA Europe,

SQW Limited SQW.

Directorate-General for Research and Innovation 2015 7th Framework Programme (FP7)

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The report was prepared by the project team composed of Marc Pattinson and Sophie Vallet Chevillard (Inno-Group), Dimitri Gagliardi, Chiara Marzocchi John Rigby, Yanchao Li and Deborah Cox (MIOIR), Robin Brighton (SQW), and Gavriel Avigdor and Rebecca Lucas (Innova).The study was carried out on behalf of unit A4 Analysis and monitoring of national research policies led by Román Arjona.

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ANNEXE A. LITERATURE REVIEW .......................................................................................... 6

A.1 Innovation Systems and Innovation Policy 6

A.2 Demand side innovation policies: rationale and policies 9

A.3 Supply side policies: rationale and policies 12

A.4 Framework condition for innovation 13

A.5 Innovation Policy Mix 13

A.6 Interaction between supply and demand: linking demand side policies to supply side for an integrated assessment 13

A.7 Efficiency and effectiveness of the Innovation Policy Mix 14

A.8 Drivers, barriers and challenges 15

A.9 Selected Bibliography 16

ANNEXE B. ILLUSTRATIVE LOGIC MODEL FOR INTERVENTION TO PROMOTE ESTABLISHMENT AND UPTAKE OF STANDARDS .................................................................................... 19

ANNEXE C. CASES STUDIES ............................................................................................... 22

C.1. Small Business Innovation Research (SBIR) 22

C.2. German (solar) Panel Policy (Renewable Energy Heating Act and Market Incentive Programme) 27

C.3. Smart Grid technology Standardisation 31

C.4. Health Information Technology for Economic and Clinical Health (HITECH) Act 35

C.5. Defence-related R&D procurement schemes 38

C.6. Procurement-conditioned SME R&D programme 42

C.7. New Technology Purchasing Assurance Programme 44

C.8. Pre-commercial Procurement by NHS, UK 46

C.9. Forward Commitment Procurement (FCP) 49

C.10. Innovation Procurement Scheme by the Ministry of Defence 51

C.11. Biometrics standardization UK 53

C.12. Danish Program for User-driven Innovation 55

C.13. SBIR in the Netherlands 58

C.14. Small Business Research Initiative (SBRI) in the UK 63

C.15. Top Sectors Initiative 66

C.16. Green energy innovation funds 70

C.17. Transformation of the Greater Manchester Waste System 74

C.18. European Innovation partnerships 76

C.19. Lead Market Initiative (LMI) 80

C.20. SME standardisation initiative 86

Annexe A. Literature Review

A.1 Innovation Systems and Innovation Policy

In the past years there has been an increasing appreciation of how important innovation is to the economy so that Europe 2020 strategy puts forward Innovation at the top of its priorities:

- Smart growth: developing an economy based on knowledge and innovation. - Sustainable growth: promoting a more resource efficient, greener and more competitive

economy. - Inclusive growth: fostering a high-employment economy delivering social and territorial

cohesion.

Moreover, in the Flagship Initiatives, innovation figures as one of the main drivers of growth and job creation. In particular "Innovation Union" is directed at improving framework conditions and

access to finance for research and innovation so that the knowledge generation process can effectively be linked to market applications (to ensure that innovative ideas can be turned into products and services that create jobs and growth EC, 2010, page 5).

The innovation process varies from country to country, sector to sector, and firm to firm.

Innovation studies posit increasing awareness of the significance of interconnectedness between the actors involved in the process (e.g., Dosi, 1982). The importance of interactions between

participants of the innovation process also extends to include efforts to grasp the complexity and the iterative nature of these processes (e.g., Kline and Rosenberg, 1986).

The figure below summarises the interactions between the stakeholders involved in the innovation process highlighting how drivers of innovation emerge from the social and cultural objectives expressed by the system’s components: Citizens, Government, Firms and Universities (and other research organisations). In the same figure it also emerges that the same stakeholders are actively involved in the production of innovation. Their role within the systems can be understood as dual:

they are both drivers and beneficiaries of innovation.

The main message that also emerges refers to the fact that any policy1 attempting to promote engagement between innovation drivers involves necessarily multiple actors. This is because the focus of the analysis, aiming at exploring possible synergies and conflicts between social and cultural objectives and opportunities for innovation provided by accumulating knowledge, requires coordination as well as incentives and multidisciplinary knowledge.

1 Innovation policy is often justified by market failure, referring to the disincentive of firms to invest optimally in innovation because private returns are suboptimal due to spillovers; recently system failure has become a justification for policy intervention. System failure occurs when, within the system of innovation, one or more elements do not perform to their potential or the links between elements might

be missing or misaligned. A discussion of the market and system failure policy rationale can be found in Bleda and Del Rio, (2013). A further objective of policy intervention must however be considered: the opportunity of higher future social and economic returns in steering the economy, or part of the economy, towards different and more promising growth paths.

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Figure 1 – who drives innovation?

Source: Cox and Rigby (2013), page 11

Major achievements of this debate have been the `system of innovation' approaches, advanced by

Freeman (1998), Lundvall (1992) and Nelson (1993), which have formed the basis for policy-making at EU level and amongst a wide range of governments across the developed and less developed world. Further developments include, but are not limited to, analyses of the relation between different key actors, for example university-industry-government (Etzkowitz and Leydesdorff , 1998); the nature of governance and the role of scientific knowledge (Gibbons et al., 1994; Nowotny et al., 2001).

Drawing on the premises that innovation is a systemic occurrence, and that policy is intended to

provide remedies for market failures, support or avert system failures or fast-forward the operations of an economic system, it is clear that an appropriate policy must rest on an accurate understanding of the system it seeks to influence. In this context, we argue that the innovation systems concept is the natural frame in which to design and analyse adaptive policy initiatives.

In practical terms, this suggests a layer of policy themes. Without withdrawing from the role of maintaining macroeconomic stability and the rule of law, the government assumes the remit of overseeing general policies in relation to the education system and public research and

development expenditure, primarily to provide the supply of trained minds whose imagination will be crucial to the experimental process and the growth of knowledge. These are the basic building blocks of the innovation ecology and they require an appropriate supply of properly resourced research organisations in which to work. The range of disciplinary skills available and their closeness to the world best practice frontier will also determine their absorptive capacity to adapt to knowledge generated within foreign ecologies; for science and technology are global systems

and the formation of innovation systems will reflect a search for the best partners wherever they are located (Harvey and McMeekin, 2004, 2007).

More specifically, government can take the lead in supporting particular areas of new generic research, to give firms and other actors the confidence that local capabilities will be available to contribute to innovation problem solving (Antonelli, 2005). Within this framework, governments frequently create new elements of the innovation ecology, for example, establishing capabilities in new areas of science and technology or new research organisations focused on a particular broad

area of exploitation where it is necessary to combine together multiple disciplines to facilitate problem solving (Kaiser and Prange, 2004).

The creation of a rich science and technology base is only one element of the necessary ecology. The primary responsibility for identifying opportunities to innovate, as distinct from opportunities to invent, lies with the firms. They are the focal points in any innovation process and if they are to draw on the science base they must have the appropriate human capital capabilities to connect.

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Hence, a second strand of an innovation systems policy is to further the absorptive capacities of private firms through the employment of qualified scientists and engineers and the conduct of R&D and thus facilitate communication with the public knowledge base as well as with other firms

whether suppliers or customers wherever they are located. A promising policy domain is therefore

that of creating patterns of connections between different actors in the innovation process in the working hypothesis of not taking for granted the free flow of information between the parties but, rather, recognising the barriers to and costs of forming network relationships.

The process of connecting the relevant ecology raises new dimensions of the innovation process. For example, because the connected elements of the ecology form the external capital of the firm or other innovating unit these may be internalised through the market for corporate control, indeed the ability to acquire established bundles of business capability is one of the most important

aspects of any innovation system. Similarly, mobility of knowledgeable minds is surely one of the most effective contributors to the making of connections in innovation systems, which is perhaps an unexpected take on the significance of flexible labour markets. Indeed, historically, if not presently, the mobility of skilled individuals has been a principal form of international technology transfer and innovation diffusion.

This is not to downplay barriers to connection and system emergence or the formulation of policies

that reduce the costs of connection. The natural desire for commercial confidentiality in a firm does not fit easily with the rules of open science in the university system, indeed some authors have

expressed deep concerns that too close a degree of interaction between universities and firms can undermine the nature of academic research and subvert the knowledge commons character of university research (Nelson, 2004). On the other hand, conflicts of a public vs. private nature can be shaped and accommodated by the emergence of new instituted rules of the game, as Harvey and McMeekin (2007) demonstrate for the new biosciences.

Furthermore, because innovation systems are more than invention systems, particular attention has to be paid to the integration of potential users into the innovation process. It is already well established that firms identify their customers and suppliers as key providers of information in relation to innovation, a natural consequence of innovation systems being embedded in the self-organisation of market relationships (von Hippel, 1986, 1988). Public purchasing programmes and the identification of lead users are important ways in which the demand side of innovation systems can be influenced by public policy (Edler and Georghiou, 2007).

It is now apparent that a wide range of complementary policies provide a basis for promoting the formation of innovation systems. They include policy instruments to facilitate collaborative research, to incubate University ideas, to use public procurement to build networks or to stimulate

the formation of clusters but in each case the point is to create connections that will not otherwise arise spontaneously. Their principal purpose is to create opportunities and enhance innovative capabilities by stimulating innovation system formation (Metcalfe 1995, 2003; Smits and

Kuhlmann, 2004).

From the scoping of the literature emerges that, systems of innovation and relative innovation ecologies are situation-specific; therefore, it would be erroneous to think that a broad innovation strategy can be easily transferable. On the other hand, a functional representation of the innovation system can clarify to a degree of generalisation, the broader domains in which innovation policy plays a role in driving forward national economies (Figure 2).

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Figure 2 – innovation system

Source: Miles et. 2009

Policies emerge as tools to strengthen or guide the evolution of the institutional settings, enhance those elements of the innovation system that can be important for the future emergence of innovation and link the various elements in order to foster synergies within the system.

Traditionally these policy objectives have been classified according to the "side" they are affecting. Supply side policies are in fact designed to support the supply side of the innovation process, the firms, whilst, demand side policies aim at addressing and shaping the context within which firms

operate (a taxonomy of innovation policies, their overall orientation and relative goals is discussed in the following sections).

Demand side innovation policies comprise measures to stimulate private demand for innovation,

intelligent and pre-commercial procurement policies, innovation inducement prizes and standardisation and regulation.

Supply side policies include fiscal incentives and direct support to R&D and innovation, support to access to finance of innovative ventures, skill upgrade and human resources policies, entrepreneurship policy, technical services and advice, cluster, collaboration and networking policies.

A.2 Demand side innovation policies: rationale and policies

Demand as a stimulus for growth and as a spur to innovation has been historically an important aspect of economic theory and policy development with the government and the public sector generally playing an important role in the economy as a customer. However, in the last two decades, the public sector’s role as customer has declined in importance for a number of reasons.

Attempts to control government expenditure have curtailed public authorities’ procurement, as has the privatization of government services, which has moved procurement outside the direct remit of government. Also, since 2008, the financial crisis has required governments to implement austerity

programmes, limiting significantly the scope to use the levers of both demand policy and supply side initiatives such as government investment in science and technology. Against this background, governments have sought new ways of stimulating innovation and growth, and attention has been drawn to the use of measures to invigorate and promote demand, including through procurement, but also through other policy measures.

Demand is generally described in economics as the desire and willingness to pay a price for a

specific good or service. While economic and innovation theory in particular has adopted more synthetic accounts of innovation in which innovation is the result of both demand and supply

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activities interacting, there have been significant efforts to tease out the specific role of demand upon innovation (Malerba, Nelson et al. 2007) while the role of public demand for technology and its possible importance in economic policy has also been researched over a long period (Edquist,

Hommen et al. 2000) leading to recognition by the European Union in 2003 of the role demand and

in particular the potential importance of public demand (Georghiou, Amanatidou et al. 2003).

The major impacts of demand upon innovation include:

Selection: demand as ‘selecting mechanisms’ in evolutionary processes;

Feedback: users/markets provide feedbacks to improve innovation;

Stimulation: expected markets stimulating the creation and diffusion of innovation;

Innovation/co-innovation: users as innovators/co-innovators.

Both the size and the structure of demand have been highlighted in these studies. While large-

scaled markets can reduce the uncertainties of innovation processes and provide suppliers with the benefits of economies of scale (Schmookler 1966; Uyarra and Flanagan 2010), demand structures interact and co-evolve with innovation processes in a more dynamic way (Malerba, Nelson et al. 2007). Hence certain arrangements of significantly sized demand can favour innovation processes.

In particular, the notion of ‘lead users’ has been raised by von Hippel to characterize a crucial

demand arrangement for innovation, which is defined as ‘…users whose present strong needs will

become general in a marketplace months or years in the future’; lead users are important since they can ‘serve as a need-forecasting laboratory for marketing research’ and meanwhile ‘provide new product concept and design data’ (Von Hippel, 1986 and Miles, 2010). Moving from lead users to lead markets (Beise 2004), and as argued by Georghiou (2007), success for policy requires early adoption of innovation by multiple users or else through ‘a single user with sufficient purchasing power to constitute a market on its own’.

This role of ‘single user’ and ‘lead user’ can be fulfilled by the government through public

procurement. A literature has emerged in recent years analysing the influence of procurement on the stimulation of innovation and the development of new technologies, and advocating the active use of public procurement as an innovation policy instrument. While an interest in the use of procurement as an industrial and technology policy tool, as we have seen, is not new, there has been a renewed focus on this underexploited policy tool (Edler and Georghiou, 2007). Interest has been encouraged by the recommendations of a number of inquiries, reports and policy documents (e.g. Edler et al., 2005; European Commission, 2005; Aho et al., 2006).The Innovation Union,

Europe 2020 flagship initiative aims at increasing Europe’s research and innovation performance by bringing ideas to markets faster.

Miles and Rigby (2013) investigated various modes and rationales of demand influence on innovation, and NESTA (2010) has investigated how customer demand shapes innovation processes in organizations in selected sectors2. Other important work on the link between demand and innovation and policy includes that by the OECD (2011) which focuses on discussing the

impacts of societal demand upon eco-innovation and introduces a way of designing demand-side policy mixes. The demand side innovation policy-toolbox includes:

1. Measures to stimulate private demand for innovation;

2. Public procurement policies;

3. Pre-commercial procurement;

4. Innovation inducement prizes;

5. Standardisation and standards and

6. Regulation.

Edler and Georghiou (2007) have defined demand side innovation policy as ‘…all public measures

to induce innovations and/or speed up diffusion of innovations through increasing the demand for innovations, defining new functional requirement for products and services or better articulating demand’.

2 Specific country and area reviews of policy include Buchinger, who introduces Austrian experience regarding public procurement as part of the demand side innovation policy mix. Roolaht (Roolaht, 2010) importantly has discussed smaller EU countries as the context for demand-side innovation policies and what pre-conditions in terms of institutional requirement are required for the implementation of demand side instruments.

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The rationale for demand side policies is straightforward: policy makers seek to drive those technologies, products and services in order to promote economic growth and welfare, contribute to societal challenges and to make public services more effective. This is done through demand

side measures. There is however, a great deal of overlapping and interrelation between demand

and supply side as policies do not usually operate in a vacuum. Demand-side innovation policies can be subject to various typologies (conceptual classifications) and they can also be grouped according to what forms the policies have taken in practice according to a single principle of classification (a taxonomic approach). Our view is that while it is useful to employ classificatory approaches of measures that focus upon conceptual distinctions, in practice, the field of demand side policies is complex and at this moment in time a more pragmatic arrangement of the measures is needed that is based on existing understandings and classification approaches, hence

we follow Edler’s approach (OECD 2011; Edler 2013; Peter, Bruno et al. 2013) and use a simple taxonomic method to grouping of the demand-side measures to create clear distinctions and more coherent categories of measures with which to work.

The proposed taxonomy in this study has four main types of measures: a) support and shaping of demand by the public sector (Public demand); b) shaping and influencing of private demand (Private demand); c) regulatory approaches (Regulations); and d) systemic approaches that

combine measures of the other demand types and that support the supply side (Systemic approaches). In the table below, the four main categories of demand side measures are

introduced.

Table 1 Demand Side Measures Typology

Public demand

• General procurement (innovation as an

essential criterion in the tendering and

assessment processes)

• Strategic procurement (the demand for

certain technologies, products or services is

encouraged)

• Cooperative and catalytic procurement

(public agencies purchase in connection with

private demand)

Private demand

• Direct/financial support (demand

subsidies and tax incentives)

• Indirect/soft steering support (awareness

building; labelling and information

campaigns; training and further education;

articulation and foresight; user-producer

interactions)

Regulations

• Regulation of demand (to create a market;

process and “usage” norms)

• Regulation of the demander – producer

interface (regulating product performance

and manufacturing; regulating product

information; supporting innovation-friendly

private regulation activities)

Systemic approaches

• Integration of demand-side measures

(strategically co-ordinated measures which

combine various demand-side instruments)

• Integration of demand- and supply-side

logic and measures (combination of

supply-side instruments and demand-side

impulses for selected technologies or

services; conditional supporting of user-

producer interaction; pre-commercial

procurement)

Source: Authors adapted from Edler (2013)

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A.3 Supply side policies: rationale and policies

According to Miles and Rigby "one of the oldest schisms in innovation studies is between

technology push and market pull accounts of innovation" (Miles, 2010; Miles and Rigby, 2013, page 37). The technology push side focuses on the fact that innovation lie mainly in research (and

innovation activities of the firms), whereby inventors create opportunities to satisfy consumers' needs. The market pull side conversely, put forwards the idea that innovation derives from people's needs and it is expressed through market demand. Of course, both supply side and demand side are tangible drivers of innovation, but their role in affecting the types and the outcome of the innovation process is rather different. Technology push is in fact supposed to encourage more radical innovation whilst market pull fosters more incremental ones.

Paraphrasing Schmookler (1966), Innovation is a two-sided activity. On the one hand, it involves

the recognition of a need or, in economic terms, a potential market for a new product or process. On the other hand, it involves technical knowledge, which may be generally available or may also include new scientific and technological knowledge, the result of original research activity. The crucial contribution of the entrepreneur is to link the novel ideas and the market (Freeman and Soete, 1997). Needless to say, this is an oversimplification. The search activities aiming to produce new knowledge and transform it into new products - including research, development and

innovation - form a complex nexus. A vast literature has dealt with it the past few decades (Freeman and Soete, 1997; Fagerberg et al, 2005; Tassey, 2007; Malerba and Vonortas, 2009).

While the demand side of innovation has always been of importance to economists,3 in practice supply-side factors for innovation have received much more attention that demand-side factors during the past few decades (OECD, 2011). There are various reasons for that, probably going back to the powerful statement of Vannevar Bush (1945) reasoning at the conclusion of World War II why modern societies just cannot afford to not support science systematically for both security

and a host of socio-economic benefits. All of them did and all of them have needed significant assistance in making their investment decisions in RTDI. From this rationale, supply side innovation policies focused on the role of research and technological development, the provision of a workforce trained in subjects such as Science, Technology, Engineering and Mathematics (STEM) and stipulations of opportunities for innovation to thrive (Edler et al, 2013).

In policy terms these stipulations translated in the measures to facilitate access to financing innovative venture, publicly supported venture capitals and loan guarantees. Entrepreneurship

policies, support measures for exploiting intellectual property and technical services have been added to the toolbox of the innovation policy maker in order to foster efficiency and effectiveness of RTDI investments and translate scientific and technical knowledge into business propositions (Edler et al 2013).

With the recognition of the importance in the innovation process of the links between the various systems' agents (Teece, 1986 and 1992, Tidd et al, 1997, Tether, 2002) and the innovation

augmenting effects of synergies between said agents, the supply side policy toolbox enriched with instruments aiming at fostering co-operations and collaborations. Supply side policies geared towards this aim include cluster policies, policy to support collaboration for R&D and Innovation and innovation network policies (Edler et al, 2013).

More recently, however, following the powerful statements in the Aho report (2006), there has been a strong surge of policy interest in Europe on demand-side instruments (Georghiou, 2005; Edler and Georghiou, 2007; Edquist and Zabala, 2012).

3 For instance, one of the most extensive literatures in economics on diffusion of innovations has dealt disproportionately with demand-side factors than with supply-side (Stomeman, 2002; Rosegger, 1996).

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A.4 Framework condition for innovation

A recent report of the MIoIR (Allman et al 2011) identifies six key categories of framework

conditions. These are defined as those components of the innovation system that are outside the firms, key innovators in the market place, and are characteristics of the competitive environment

within which the innovative firms operate. These six key elements are: 1) the public research base, 2) demand conditions, 3) the degree of competition within the market, 4) human resources, 5) finance and 6) infrastructure and services. Whilst these might pertain to the sphere of either supply or demand for innovation, their role is of a basic systemic nature and are key components of the innovation process either through their role in sustaining the creation of new knowledge and the recombination of existing knowledge, or to providing the necessary incentive to innovate, or even providing key resources to the innovation process. These categories affect the firms’ capabilities to

innovate and are reflected in the firms’ entrepreneurial orientation4 and their innovation capabilities in the wider business environment.

In other words, frameworks conditions provide to the innovation stakeholders basic resources, incentives, capabilities and opportunities to innovate through the provision of scientific and technical knowledge, appropriately skilled people, competitive market conditions, finance and services. The rationale for policy intervention in each of the key components identified is

linked to their unique characteristics as well as the linkages between and amongst each component: as described in this review, innovation policy pertain interventions on the

various elements of the innovation system and those linkages and connections between them that generate superadditivity and additionality.

A.5 Innovation Policy Mix

Bringing together the supply and the demand side policies as part of a more integrated approach is at the centre of a lively debate. Systemic approaches are attempts (1) to combine different

demand side measures or (2) to combine demand and supply side measures and framework conditions. The basic idea is that (a) there are different needs and failures at play at the same time that need to be tackled by policy measures, that (b) needs for support change in different phases of an innovation (over time) or that (3) different target groups have different needs for support.

Nonetheless, combining innovation policies either in mode 1) demand side policies, or in mode 2) supply and demand side policies, described above, presents several hurdles and a high degree of complexity. The complexity derives from interdependencies and interactions between different

policy instruments implemented and the extent to which intended policy outcomes can be achieved (Flanagan et al, 2011). In other words, the outcome deriving from the combination of different policies, specifically supply side and demand side policies may imply a level of complexity that is

difficult to assess ex-ante, in interim, or ex-post.

A recent review has shown that explicit systemic approaches are rare, the Lead Market Initiative or market transformation measures in the energy sector being two examples (Cunningham et al

2013).

A.6 Interaction between supply and demand: linking demand side policies to supply side for an integrated assessment

The interplay of measures has been conceptualised in different “systemic” approaches. Smits and Kuhlmann (2004) in an early paper on the rise of systemic instruments argue that innovation systems need to fulfil five functions, i.e. 1) managing interfaces, 2) construction of systems, 3) providing platforms for learning and experimenting, 4) providing infrastructure for strategic

intelligence, and 5) stimulating demand articulation, strategy and vision development. To fulfil the functions especially the last one which is closely related to the demand side, various instruments need to be integrated. Wieczorek and Hekkert(2012) take the Smits and Kuhlmann arguments and propose their application to sustainability challenges. Borras and Edquist (2013) propose an approach to systemic policy design that is problem oriented. They argue that diagnosis of system

activities need to be conducted and ‘mixes’ of policies need to be designed based on problems identified. Other major contributions include (Beise, Blazejczak et al. 2003) which investigates the

impacts of lead markets on environment friendly innovation and the various demand side policy efforts (notably regulations and subsidies) in creating lead markets. Rigby (2013) reviews the effect of pre-commercial procurement (PCP) on innovation, concluding that in essence pre-commercial procurement is a type of integrated measures lying at the interface between demand (need specified by a clear public demand) and supply (grant for the winner of the competition

4 Entrepreneurial orientation is the entrepreneur’s proactive behaviour towards risk-taking ventures and innovation (Frank et al, 2010).

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rather than purchase of a product). Finally, innovation policy road mapping (IPRM) has been proposed as an instrument for forward looking systemic policy design (Ahlqvist, Valovirta et al. 2012), to link technological advancement with societal demand, with a consideration of longer term

development goals and public procurement.

All these examples point to the complexity of policy intervention and to the need to understand the co-existence of different needs and measures (deliberate or not), both on the demand and the supply side for the design, implementation and evaluation of policy.

Table 2: Demand-side innovation policy measures – systemic approaches

Systemic Approaches

Integrated demand measures

Strategically co-ordinated measures which combine various demand-side instruments

Integration of demand-

and supply-side logic and measures

Combination of supply-side instruments and demand-side impulses for selected technologies or services (including clusters integrating users and supply chains).

Conditional supporting of user-producer interaction (R&D grants if user involved)

Specific Instrument: Pre-commercial Procurement (Rigby 2013)

Source: Edler (2013)

Moreover, demand policies are aimed at triggering innovative activity on the supply side as a result of increased and more challenging demand. This suggests that the impact of demand side policies have, in general, is multi-dimensional. A simplified impact story of demand side measures, not

differentiated for different kinds of instruments, is illustrated in the figure below.

A.7 Efficiency and effectiveness of the Innovation Policy Mix

Regarding the efficiency and effectiveness of combined supply and demand side innovation policies, a few words are necessary in order to understand the magnitude of the problems at hand and

devise a practical and effective strategy to face them. In the words of Flanagan et al. (2011):"the sheer complexity of the policy process precludes any static-comparative analysis of instruments as

if they were stable, discrete and independent units" (p. 709). Assessing which innovation systems configuration is likely to prevail, or how the policy mix will affect (directly or indirectly) the innovation performance of the system implies that the general framework adopted in the exercise has to be dynamic in nature and consider the connections between instruments and their effects ‘loose’ with many unanticipated outcomes.

The structure of the assessment proposed will therefore necessarily involve consideration of the dimensions in which interactions between and amongst policies will occur (policy space,

governance space, geographical space and time) and the possible types of interactions (between different mixes targeting the same issue; instrument mixes targeting different issues and instrument mixes targeting processes), as shown in the Figure 4 below. This exercise will be conducted across the various dimensions identified. Moreover, it will be necessary to highlight conflicts and tensions between instruments in the policy mix. Such conflicts might relate to the rationale, the policy goals and finally to the particular implementation process.

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Figure 3: conceptualising policy mix interactions: dimensions, types and potential sources of tension

Flanagan et al. 2011, page 709.

A.8 Drivers, barriers and challenges

We have highlighted the three dimensions of impact of demand side measures. This already pointed towards the specific challenge of demand side policy to understand the rationale and

mechanisms of measures in order to create effects on all three dimensions (impact on target group on the demand side, impact on suppliers of innovation, social and economic impact more broadly). There is an enormous challenge of strategic intelligence to understand the policy need and leverage for all three dimensions, which goes far beyond the traditional remit of policy makers on the supply side. Further key challenges following out of that multi-dimensional setting that are associated with demand side policy measures are well covered in the OECD summary (OECD 2011). This study reports on a number of significant barriers to successful implementation of systemic policies where

the aim is to use complementary instruments to generate greater effect. Secondly, the coordination costs of working with both demand and supply mechanisms can be high. In fact, taking the time to understanding the interactions between the demand and supply side can be costly for the public sector. Moreover, the public sector is not always well prepared to take on the lead role required to manage this process. The need for intervention is also sometimes difficult to assess, with the logic and rationale for systemic measures being hard to determine. This can be made more difficult because of the “value chain” of innovation is complex and difficult to

understand, making intervention choices difficult to choose between. Understanding what technologies might be required – in terms of specifying demand – is again difficult for the public sector actors which traditionally may have resources and capabilities to understand the "direction

of change required by the system of innovation", but may lack capacity in identifying and implementing new technologies. The work conducted thus far focuses on teasing out those strategic technology areas whereby there may be lock-in situations that make markets difficult to

shape with particular attention to the structure of incentives which may simply be hard to change even with the benefit of systemic/strategic measures (Tsipouri, 2013).

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A.9 Selected Bibliography

Ahlqvist, T., V. Valovirta, et al. (2012). "Innovation policy roadmapping as a systemic instrument

for forward-looking policy design." Science and Public Policy 39: 178-190.

Allman, Kurt, Jakob Edler, Luke Georghiou, Barbara Jones, Ian Miles, OmidOmidvar, Ronnie

Ramlogan, and John Rigby (2011) Measuring Wider Framework Conditions for successful innovation: A system’s review of UK and international innovation data”, Report NESTA, United Kingdom, January

Beise, M. (2004). "Lead markets: country-specific drivers of the global diffusion of innovations." Research Policy 33: 997-1018.

Bleda, M. and Del Rio, P. "The market failure and the systemic failure rationales in technological innovation systems." Research Policy 42, no. 5(2013) : 1039-1052.

Blind, K., 2013. Standardisation and Innovation, Compendium of Evidence on the effectiveness of Innovation Policy. MIoIR, the University of Manchester and NESTA, London. Available at: http://innovation-policy.org.uk

Blind, K., 2012. The Impact of Regulation on Innovation. Compendium of Evidence on the effectiveness of Innovation Policy, MIoIR, the University of Manchester and NESTA, London. Available at: http://innovation-policy.org.uk

Blind, K., Bekkers, R., Dietrich Y., Iversen, E., Köhler, F., Müller, B., Pohlmann, T., Smeets, S., Verweijen, J., 2011. Study on the Interplay between Standards and Intellectual Property Rights (IPRs). European Commission: Luxembourg.

Borrás, S., and Edquist, E. (2013). The choice of innovation policy instruments. Technological forecasting and Social Change. 80(8), 1513-1522. doi:10.1016/j.techfore.2013.03.002.

Cunningham, P., Edler, J., Gok, A., &Shapira, P. (2013). Impacts of Innovation Policy: Synthesis and Conclusion,

Cunningham, P.; Edler,. J.; Flanagan, K.; Laredo, P. (2013): Innovation policy mix and instrument interaction. A review. Compendium of Evidence on the Effectiveness of Innovation Policy Intervention Project. MIoIR, the University of Manchester and NESTA, London. Available at:

http://innovation-policy.org.uk

Edler, J. and L. Georghiou (2007). "Public procurement and innovation—Resurrecting the demand side." Research Policy 36: 949-963.

Edler, J., Georghiou, L., Blind, K., &Uyarra, E. Evaluating the demand side: New challenges for

evaluation, Research Evaluation, 21, (21012) pp 33-47.

Edler, J., Georghiou, L., Uyarra, E., Cox, D., Rigby, J., &Nugroho, Y. (2009). Monitoring and Evaluation Methodology for the EU Lead Market Initiative. Concept development for the EU Commission.

Edler, J., Cunnigham, P.N., Gok, A., and Shapira P., (2013) Impact of Innovation Policy: Synthesis and Conclusions. Compendium of evidence on the effectiveness of innovation policy intervention.

MIoIR, the University of Manchester and NESTA, London. Available at: http://innovation-policy.org.uk

Edler, Jakob (2013) “Review of Policy Measures to Stimulate Private Demand for Innovation. Concepts and Effects”, MIoIR, the University of Manchester and NESTA, London. Available at: http://innovation-policy.org.uk

Edquist, C. (ed.) (1997). Systems of innovation: technologies, institutions and organizations. Routledge, Milton Park.

Edquist, C. and J. M. Zabala-Iturriagagoitia (2012). "Public Procurement for Innovation as mission-oriented innovation policy." Research Policy 41(10): 1757-1769.

http://innovation-policy.org.uk/http://innovation-policy.org.uk/http://innovation-policy.org.uk/http://innovation-policy.org.uk/http://innovation-policy.org.uk/http://innovation-policy.org.uk/

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Edquist, C. and L. Hommen (1999). "Systems of innovation: theory and policy for the demand side." Technology in Society 21(1): 63-79.

ERAB, 2012) ERAB recommendation on research and innovation policy for Grand Challenges, retrieved http://ec.europa.eu/research/erab/pdf/recommendations-on-gc-research_en.pdf

European Commission (2006) “Creating an Innovative Europe”, (Aho) Report, Luxembourg: Office of the Official Publications of the European Union.

European Commission, (2008) DG Research and Innovation, Challenging Europe’s Research: Rationales for the European Research Area (ERA) - Report of the ERA Expert Group, Publications Office of the European Union, Luxembourg, 2008

European Commission. (2010) Europe 2020: a strategy for smart, sustainable and inclusive growth. Communication from the Commission:Com(2010) 2020 final

European Commission (2012), final A Reinforced European Research Area Partnership for Excellence and Growth. European Commission, COM(2012) 392

Fagerberg, Jan, David C. Mowery and Richard R. Nelson (eds.) (2005) The Oxford Handbook of Innovation, Oxford University Press.

Flanagan, K., Uyarra, E., &Laranja, M. (2011). Reconceptualising the ‘policy mix’for

innovation. Research Policy, 40(5), 702-713.

Frank, H., Kessler, A., and Fink M., (2010): Entrepreneurial Orientation and Business Performance: A replication study, in SBR, 62, April 2010, 175-198.

Georghiou, L., Edler, J., Uyarra, E., &Yeow, J. (2013). Policy instruments for public procurement of innovation: Choice, design and assessment. Technological Forecasting and Social Change. October, 2013

Georghiou, L., Rigby, J., , E. Amanatidou, et al. (2003). Raising EU R & D Intensity - Improving the Effectiveness of Public Support Mechanisms for Private Sector Research and Development: Direct

Measures. Report to the European Commission from an Independent Expert Group.

Harvey, M. and McMeekin, A., 2004, ‘Public-Private Collaborations and the Race to Sequence Agrobacterium tumefaciens’, Nature Biotechnology, Vol. 22, No. 7, pp. 807-810.

Harvey, Mark, and McMeekin, Andrew, 2007. ‘Public or Private Economies of Knowledge: Turbulence in the Biological Sciences’. Cheltenham: Edward Elgar. Hippel, E.v. (1986): Lead Users. A Source of novel product concepts, in: Management Science, Vol. 32, S. 791-805.

Hippel, E.v. (1988): The Sources of Innovation. The MIT Press

Izsak, K. and J. Edler (2011). Trends and Challenges in Demand- Side Innovation Policies in Europe.

Knell, M. (2012). Demand Driven Innovation in Economic Thought. UNDERPINN conference. Manchester.

Levin, R. C., Klevorick, A. K., Nelson, R. R., & Winter, S. G. 1987. Appropriating the returns from

industrial research and development. Brookings Papers on Economic Activity, 3: 783-820.

Malerba, F., R. Nelson, et al. (2007). "Demand, innovation, and the dynamics of market structure: The role of experimental users and diverse preferences." Journal of Evolutionary Economics 17: 371-399.

Metcalfe JS, De Liso, N., Gagliardi, D. and Ramlogan, R. (2012) Innovation Systems and Innovation Ecologies: Innovation Policy and Restless Capitalism, Openloc – University of Trento working paper, Number: 3/2012 - http://www.openloc.eu/page/?/working-papers/

Miles, I. (2010) Demand-led Innovation, Mini Study 11, Global Review of Innovation Intelligence and Policy Studies. PRO INNO EUROPE – INNOGRIPS, 2010.

Miles, I. and J. Rigby (2013). Demand-Led Innovation. Innovation Policy Challenges for the 21st Century. D. Cox and J. Rigby.

OECD (2011). Demand-side Innovation Policies, OECD Publishing.

Paraskevopoulou, E. (2012). "Non-technological regulatory effects: Implications for innovation and innovation policy." Research Policy 41(6): 1058-1071.

http://ec.europa.eu/research/erab/pdf/recommendations-on-gc-research_en.pdfhttp://www.openloc.eu/page/?/working-papers/id/50http://www.openloc.eu/page/?/working-papers/id/50http://www.openloc.eu/page/?/working-papers/

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Peters, M., M. Schneider, et al. (2012). "The impact of technology-push and demand-pull policies on technical change - Does the locus of policies matter?" Research Policy 41(8): 1296-1308.

Rigby, J. (2013). Review of Pre-commercial Procurement Approaches and Effects on Innovation. Compendium of Evidence on the Effectiveness of Innovation olicy Intervention.

London/Manchester, NESTA/MIOIR.

Rigby, J., Boekholt, P., Semple, A., Deuten, J., Apostol, R., Corvers, S., Edler, J. (2012). Feasibility study on future EU support to public procurement of innovative solutions: Obtaining Evidence for a Full Scheme

Rogers, Everett M. (1983), Diffusion of Innovations, 3rd ed. New York: The Free Press.

Rolfstam, M. (2012). "Understanding Public Procurement of Innovation : Definitions , Innovation types and Interaction modes." 1-16.

Schmookler, J. (1966), Invention and Economic Growth, Harvard University Press, Cambridge, MA.

Schumpeter, Joseph A. (1942) Capitalism, Socialism and Democracy, Harper & Row.

Smits, R. and S. Kuhlmann (2004). "The rise of systemic instruments in innovation policy." International Journal of Foresight and Innovation Policy 1: 4-32.

Stefano, G., A. Gambardella, et al. (2012). "Technology push and demand pull perspectives in innovation studies: Current findings and future research directions." Research Policy 41: 1283-

1295.

Stoneman, Paul (2002) The Economics of Technological Diffusion, Blackwell.

Teece, David 1986. Profiting from technological innovation: implications for integration, collaboration, licensing and public policy." Research Policy 15:285-305.

D.J. Teece (1992) Competition, cooperation and innovation: organisational arrangements for regimes of rapid technological progress Journal of Economic Behaviour and Organization, 18 (1992), pp. 1–25

Tether B.S. (2002) Who co-operates for innovation, and why: An empirical analysis Research Policy, Volume 31, Issue 6, August 2002, Pages 947–967

Tidd, J., Bessant, J., Pavitt, K., 1997. Managing Innovation: Integrating Technological, Market and Organisational Change. Wiley, Chichester.

Tispoury, L. (2013), Innovation strategies articulating supply side and demand side aspects, Discussion paper for the 2013 ERAC mutual policy learninf seminar on research and innovation policies – SESSION II – Brussels, March 2013.

Utterback, J. and F. Suarez 1993. Innovation, competition, and industry structure. Research Policy 22:1-21.

Uyarra, E. (2012). Review of Measures in Support of Public Procurement of Innovation. Compendium of Evidence on the Effectiveness of Innovation Policy Intervention. MIoIR, the University of Manchester and NESTA, London. Available at: http://innovation-policy.org.uk

Uyarra, E. and K. Flanagan (2010). "Understanding the Innovation Impacts of Public Procurement."

European Planning Studies 18: 123-143.

http://innovation-policy.org.uk/

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Annexe B. Illustrative logic model for intervention to promote establishment

and uptake of standards

Standards enhance the diffusion of innovation and also provide technical information to producers. More specifically, the literature identifies four types of benefit5:

Providing for inter-operability or compatibility between different parts of a product or between products as part of a system or network.

The provision of a minimum level of quality, which may be defined in terms of functionality or safety of products (potentially valuable to consumers and producers)

The reduction of variety, allowing for economies of scale.

The provision of information (through the technical specification of the standard. In addition, standards may be a useful predictor of future regulations).

Note there may also be drawbacks:

Timing is key; too early and the sector may have to work with inappropriate standards; too late and many of the potential benefits may be lost

Standards can constrain as well as promote innovation. The DTI study6 found that a positive

correlation between firms which felt they promoted innovation (because of the information

provided), but also constrained because they dictated a certain technology trajectory7

Less variety may reduce competition

The rationale for intervention must explain why standards do not emerge through market forces (as some do). Possible explanations include:

The benefits accrue to many without imposing additional costs – Standards as a public good

Public standards may have greater credibility than industry defined ones and require public

intervention of some sort

Coordination costs may be lower when the public sector is involved; perhaps especially true in relation to international standards

More speculatively, government may have a better overview of the links between different markets and services and the impacts of standards on non-market considerations (e.g. the environment). It may therefore be well-placed to assess whether emerging standards are appropriate

5 DTI 2005 The Empirical Economics of Standards, DTI Economics Paper No. 12.

6 2005 op cit

7 It is often said that the QWERTY keyboard was designed to slow typists down because the first machines could not handle rapid typing. It has remained the de facto standard

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Objectives Inputs Activities Outputs Intermediate Outcomes

Final Outcomes

Objectives could

include:

Promoting adoption

of existing

standards

Development of new

standards

In both cases the

objective being to

promote the diffusion of

innovation to meet

economic and social

needs

Funding

Technical

expertise

Consensus

building

Uptake of existing standards

Awareness raising

Access,

(libraries/repositories)

Technical assistance with

adoption

Developing new standards

Technical support (for

public laboratories or

funding research

programmes)

Convening stakeholders and

consensus building

Coordination with

international developments

Articulating public sector’s

requirements. This could be

because it is a major

purchaser, for example

health, defence, or because

it has a specific policy

responsibility, for example

environmental protection

Processes

established to

develop standards

Businesses involved

in these processes

Number of new

standards developed

Links to

international

standards

Adoption of

standards by

businesses

Adoption of

standards by

businesses

Potentially, revisions

to international

standards

New improved

products and

services

Diffusion/adoption of

new products/services

more widely, e.g. as

determined by sales of

products/ services

Enhanced technical

knowledge of businesses

Business performance

benefits in terms of

turnover, profitability

Possible contribution to

Policy objectives :

Environment

Energy

Transport

Health.

Education

Defence

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Objectives Inputs Activities Outputs Intermediate Outcomes

Final Outcomes

Underpinning theories of change

Theory of change assumptions: strategy

The four key issues which standards

address, (see above) especially the

first two are constraining the

diffusion of innovation

New (or revised) standards, or

increased adoption of existing

standards are the most appropriate

way to address these issues or have

a significant role in relation to other

interventions

New standards and their adoption are

a cost-effective means of addressing

market/system failures

There are market or system failures

which inhibit new standards merging

or the adoption of existing standards.

The public sector has a role in

addressing these failures

Theory of change assumptions:

implementation

Public sector agents have sufficient

knowledge and contacts to make a

real contribution

Policy interventions work with the

grain of private sector developments

(industry defined standards) rather

than as a substitute

Technology has developed to the stage

where appropriate standards can be

identified

Need for a clear view on the

appropriate level of standards: de

facto, national, international

Theory of change assumptions: benefits

All in terms of additionality/net benefits

Standards open up new markets through interoperability of

technologies. This creates opportunities for businesses to

supply complementary product and services. Probably

more importantly, users (businesses and consumers) are

able to access new technologies more effectively and at

lower cost leading to more effective production processes

and increased final consumer benefits.

Standards also provide technical information and ‘quality’

mark for consumers, which results in greater uptake

Economies of scale arising from a narrow range of products

outweigh any costs from reduced user/consumer choice and

reduced competition in product/service markets

Target group of beneficiaries is able to exploit standards in

the face of potential increased competition from non-target

businesses (other regions/countries etc.)

Standards are appropriate, so that constraints to innovation

are outweighed by the stimulus. Timing is important to

avoid introducing the standards either too early or too late

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Annexe C. Cases studies

C.1. Small Business Innovation Research (SBIR)

Key characteristics

The Small Business Innovation Research (SBIR) program is a competitive program that encourages domestic small businesses to engage in Federal Research and Development that has the potential

for commercialization. Through a competitive awards-based program, SBIR enables small businesses to explore their technological potential and provides the incentive to profit from its commercialization. The program’s goals are the following:

1. Stimulate technological innovation

2. Meet Federal research and development needs.

3. Foster and encourage participation in innovation and entrepreneurship by socially and economically disadvantaged persons.

4. Increase private-sector commercialization of innovations derived from Federal research and development funding.

Each year, Federal agencies with extramural research and development budgets that exceed $100 million are required to allocate 2.8% of their R&D budget to these programs. Currently, 11 Federal agencies participate in the program (see under “level of involvement” the list of participating agencies). Each agency administers its own individual program within guidelines established by

Congress. These agencies designate R&D topics in their solicitations. Awards are made on a competitive basis after proposal evaluation.

SBIR targets the entrepreneurial sector because that is where most innovation and innovators thrive. However, the risk and expense of conducting serious R&D efforts are often beyond the means of many small businesses. By reserving a specific percentage of federal R&D funds for small

businesses, SBIR protects the small business and enables it to compete on the same level as larger businesses. SBIR funds the critical start-up and development stages and it encourages the

commercialization of the technology, product, or service, which, in turn, stimulates the U.S. economy.

The SBIR is in fact, a public procurement program for small firms. This policy instrument aims at providing early-stage financial support to high-risk innovative technology-based small firms with commercial promise. From the governments’ perspective, SBIR stimulates technological innovation, ultimately boosting innovation and growth, while at the same time provides government agencies with new, cost-effective, technical and scientific solutions to meet their needs. From the firm’s

Policy Name

and URL

Small Business Innovation Research (SBIR)

http://www.sbir.gov/

Promoting Institution

US government Country (Region)

United States

Level of involvement

US Federal Agencies. The following 11 federal agencies currently participate in the program:

Department of Agriculture

Department of Commerce - National Institute of Standards and Technology

Department of Commerce - National Oceanic and Atmospheric Administration

Department of Defence

Department of Education

Department of Energy

Department of Health and Human Services

Department of Homeland Security

Department of Transportation

Environmental Protection Agency

National Aeronautics and Space Administration

National Science Foundation

http://www.sbir.gov/

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perspective, features that make SBIR contracts attractive (besides from the funding itself), include the fact that there is no dilution of ownership or repayment required. Award recipients retain rights to intellectual property developed using the SBIR award, with no royalties owed to the government.

The government retains royalty-free use for a period, but this is very rarely exercised. The SBIR Program is structured in 3 phases:

Phase I. The objective of Phase I is to establish the technical merit, feasibility, and commercial potential of the proposed R&D efforts and to determine the quality of performance of the small business awardee organization prior to providing further Federal support in Phase II. SBIR Phase I awards normally do not exceed $150,000 total costs for 6 months.

Phase II. The objective of Phase II is to continue the R&D efforts initiated in Phase I. Funding is based on the results achieved in Phase I and the scientific and technical merit and commercial potential of the project proposed in Phase II. Only Phase I awardees are eligible for a Phase II award. SBIR Phase II awards normally do not exceed $1,000,000 total costs for 2 years.

Phase III. The objective of Phase III is for the small business to pursue commercialization objectives resulting from the Phase I/II R&D activities but the SBIR program does not fund

Phase III.

Side - Type - Interactions

Demand side- Public procurement; need specified by a public demand. Supply: grant for the winners (rather than purchase of a product).

Interactions with demand/supply side

The SBIR is a public procurement program for small firms where SMEs receive funding up to the commercialization stage. The SBIR programme offers professional assistance to companies in order to seek advice and services from an external consultant. The external consultant is often used to provide the applicant with an assessment of their proposal and, most often, especially assist the small business with technology commercialization assistance, in order to improve their commercialization strategy. The commercialization plan is a very important part of the SBIR

programme, as the programme’s ultimate priority is to bring to market new technological solutions in which the nation is in need. More recently, some federal agencies have been experimenting funding firms beyond phase II to help them develop their project at a sufficient level for interest by third parties.

Note that:

Some US federal government agencies organise the SBIR program mainly as a grant scheme (so-

called "granting" agencies). Other US federal government agencies - mainly those with large operational responsibilities and thus large procurement needs - implement the SBIR program as a procurement scheme (so-called "contracting" agencies). The granting agencies let companies make the specifications for concrete project proposals in broadly defined areas of interest to the agencies. The contracting agencies define more concrete problems to be addressed and performance targets to be met.

Assessment of impacts

Several evaluations have been carried out of the SBIR programme, showing that SBIR awards have had a positive effect caused by the creation of new firms, with positive benefits in employment and growth for the local economy8. Some studies have also given evidence that SBIR awardees grew significantly faster in terms of employment and growth and were more likely to attract venture financing than comparable firms9.

8 The Small Business Innovation Research Program: An Assessment of the Department of Defense Fast Track Initiative(2000), National Research Council, Charles W. Wessner, ed. Washington, D.C. National Academy Press

9 The Government as Venture Capitalist: The Long-run Impact of the SBIR Program (1999), by Lerner, J. Harvard University and National Bureau of Economic Research Journal of Business, vol.72, no.3.

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Metrics/indicators

The National Research Council carried out an assessment of the Small Business Innovation and Research (SBIR) programme from 2001 to 2009. This comprised a general survey, and particular surveys by the five government departments that account for 96% of SBIR programme

expenditures10. Regarding commercialization, the NRC assessment concluded that the SBIR programme has a strong commercial focus, with considerable efforts to bring projects to market, which has known some success. Products come to market quickly and approximately 30-40% of projects generate products that reach the marketplace. 65% of companies involved make business

from their SBIR development within 1 year.

Audretsch et al. (2001) estimated the expected sales for each SBIR project on the basis of actual sales realised until 1999 from 112 DoD-funded Phase II SBIR projects. Average actual sales were $175 021 per project, which reflected the large number of firms with no actual sales (78 out of 112 made no sales of their product). However, when the sample was limited to the 34 projects reporting sales, the average increased to $575 539 per project. The study concluded that if the

SBIR programme did not exist, the probability of these projects reaching the Second Phase would be very limited, showing the strong positive impact of the SBIR programme.

Metin Ege in his thesis on “How do grants influence firm performance? An econometric evaluation of the SBIR programmes at NIH” (2009) compared two samples of data, a test and a control one in order to check the effect of the SBIR programme on the average sales growth for the NIH projects for three, five and eight years. The results demonstrated at 1 % significance level that the average

sales growth was higher in the groups of Phase II awardees than the non-recipients group. The

sales growth of the SBIR firms reached 18, 13 and 8 % in three, five and eight years respectively. At the same time, the non-SBIR firms demonstrated a growth of 8, 7 and 5 %.

Regarding SBIR effects on employment, the NRC survey sought detailed information about the number of employees at the time of the award and at the time of the survey and about the direct impact of the award on employment. Overall, the survey data showed that the average employment gain at each responding firm from the date of the SBIR award to the time of the survey was 29.9 full-time equivalent employees. The NRC Phase II Survey also showed that

respondents enjoyed strongly positive employment growth after receiving a Phase II award. The percentage of companies with at least 50 employees more than doubled, from 16.5 % to 35.4 % of all respondents. Overall, survey respondents reported gains of 57,808 full time equivalent employees, with the top five respondents accounting for 18.4 % of the overall net gain. The NRC survey also sought to directly identify employment gains that were the direct result of the award. Respondents estimated that specifically as a result of the SBIR project, their firm was able to hire

an average of 2.4 employees, and to retain 2.1 more.

In the econometric evaluation of the SBIR at NIH (Ege 2009) the author compared two samples of

data in the same way as described above for sales growth to check the effect of the SBIR programme on the average employment growth for the NIH projects for three, five and eight years. The results demonstrated at 1 % significance level that the average employment growth was higher in the groups of Phase II awardees than the non-recipients group. The employment growth of the SBIR firms reached 16, 15 and 10 % in three, five and eight years respectively. At

the same time, the non-SBIR firms demonstrated a growth of 6, 4.4 and 4 %.

As for its impact on growth, all the respondents to the NRC survey declared that a large share of their company growth was attributable to their SBIR awards. In 44% of cases SBIR awards were credited with over 50% of company growth. Ege in his thesis concluded that the programme had a measurable impact on sales and employment growth for the companies involved.

Policy lessons

The SBIR programme is often taken as a model for promotion of innovation and commercial

application of new technologies and a large number of successful US companies owe their initial success to SBIR contracts. As mentioned in the previous section above, several evaluations of the SBIR programme have taken place and have shown that SBIR awards have caused the creation of new firms, with positive benefits in employment and growth for the local economy. The SBIR-

programme has thus proven to be successful in the United States for enabling small business to develop technical innovation attracting third party interest (whether public or private).

10 The Department of Defence (DoD) (the SBIR programme at DoD is the largest of all the SBIR programmes, and accounts for over half the programme’s funding), the National Institutes of Health (NIH), the National Aeronautics and Space Administration (NASA), the Department of Energy (DoE), and the National Science Foundation (NSF).

25

Its main strengths are the following11:

Encourages novel research: it has a high-risk focus and projects involve novel research, rather than incremental change.

Catalyst for employment and sales growth: the programme has had positive effects for

award-winning firms in terms of employment and sales growth.

Certification: SBIR facilitates links with angel and venture capital investments – awards play an important role in certifying firm quality as they validate technology concept and commercialisation.

External links: SBIR provides a bridge between universities and the marketplace; an important percentage of SBIR awards involve university researchers.

Size and breadth: the size and broad spectrum of the programme mean that support is distributed to a wide number of different firms, of which nearly a third are new to the programme each year.

Flexibility: the programme allows to meet different mission needs of the government agencies.

However, there are also some risk factors that have been identified and that need to be taken into account:

Risk of non-additionality: awards crowd out firm-financed R&D instead of increasing R&D

activities or employment; they therefore only transfer costs of commercial R&D to the government12.

Lobbying: serial participation of un-achieving firms whose probability of winning an award is strongly increased by relationships with federal officials (“SBIR mills”).

Lack of motivation and evaluation: many government agencies can regard SBIR as a “tax”

on their programmes and will not invest time in choosing the award-winners and follow-up on programme outcomes.

Length of the application process: long cycle time between the application phase, and phase I and phase II awards, can be an issue for small firms with constrained monthly cash flow.

In addition, one of the main criticisms of the SBIR programme in the United States, has been that it tends to only develop a technology to a certain readiness level. Most commercialisation successes require substantial post-SBIR research and funding from a

variety of sources and although the results of a survey carried out indicated that 56% of the surveyed projects managed to attract additional funding, many award-winning firms have stressed the difficulties in obtaining funding for the commercialisation phase (Phase III).

Some federal agencies have been experimenting funding firms beyond phase II to help them develop their project at a sufficient level for interest by third parties.

11 Sources for this section: Public procurement programmes for small firms – SBIR-type programmes (2010), OECD; “Secrets” of the world’s largest seed capital fund: How the United States Government uses its Small Business Innovation Research (SBIR) Programme and Procurement Budgets to Support Small Technology Firms (2006) by David Connell Centre for Business Research, University of Cambridge.

12 Econometric evaluation of the SBIR programme in the United States has raised some doubts about the success of the programme, pointing to risk of non-additionality of SBIR funds. Data showed that SBIR awards a) did not lead to an increase in employment in firms and b) appeared to crowd out private money that companies previously spent on R&D (Wallsten, 2000).

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References

Public/Private Technology Partnerships: Evaluating SBIR-Supported Research (2001) by David

B. Audretsch (Institute for Development Strategies), Albert N. Link (Department of Economics-

University of North Carolina) and John T. Scott (Department of Economics Dartmouth College

Hanover)

An Assessment of the Small Business Innovation Research Program (2008) by Charles W.

Wessner, Editor, Committee on Capitalizing on Science, Technology, and Innovation; National

Research Council http://www.nap.edu/catalog/11989.html

Public procurement programmes for small firms – SBIR-type programmes (2010), OECD

Innovation Policy Platform www.oecd.org/innovation/policyplatform

“Secrets” of the world’s largest seed capital fund: How the United States Government uses its

Small Business Innovation Research (SBIR) Programme and Procurement Budgets to Support

Small Technology Firms (2006) by David Connell Centre for Business Research, University of

Cambridge.

Success stories in the SBIR official web-site: http://www.sbir.gov/success-stories

http://www.nap.edu/openbook.php?record_id=11989&page=8

The Government as Venture Capitalist: The Long-run Impact of the SBIR Program (1999), by

Lerner, J. Harvard University and National Bureau of Economic Research Journal of Business,

vol.72, no.3.

Study on pre-commercial procurement in the field of Security Within the Framework Contract of

Security Studies – ENTR/09/050 Final report, November 2011, ECORYS

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The Effects of Government-Industry R&D Programmes on Private R&D: The Case of the Small

Business Innovation Research Program (2000) by Wallsten, S. in Rand Journal of Economics,

Vol. 31, N°1 (Spring 2000).

The Small Business Innovation Research Program: An Assessment of the Department of

Defense Fast Track Initiative(2000), National Research Council, Charles W. Wessner, ed.

Washington, D.C. National Academy Press.

Ege (2009). How Do Grants Influence Firm Performance? An Econometric Evaluation Of The Sbir

Program At NIH. Thesis submitted to the Graduate School-New Brunswick Rutgers, The State

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http://www.nap.edu/catalog/11989.htmlhttp://www.oecd.org/innovation/policyplatformhttp://www.sbir.gov/success-storieshttp://www.nap.edu/openbook.php?record_id=11989&page=8http://ec.europa.eu/enterprise/policies/security/files/doc/pcp_sec_finalreport_en.pdf

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C.2. German (solar) Panel Policy (Renewable Energy Heating Act and Market Incentive Programme)

Key characteristics

The Renewable Energy Heating Act and Market Incentive Programme seeks to foster the development of the sector of renewable energies by specifically encouraging the use of renewable energies in heating processes, with the overall objective to increase the share of renewable energies of 14 % in the heating market by 2020 (in 2012, the part of RES in heating supply was 10%).

The Renewable Energy Heating Act (EEWärmeG) was created in 2009 with the triple goal to oblige the use of renewable energies in new buildings, to provide financial support to building owners

modernising heating systems and to facilitate the expansion of the heating grid. It therefore sought to interact on both supply and demand factors.

In fact, the EEWärmeG obliges owners of new constructed buildings to have a certain amount of renewable energy in heating processes. Besides, the EEWärmeG now includes an important policy instrument: the Market Incentive programme.

The Market Incentive Programme (MAP) was originally launched in 2000, as part of the support of Renewable Energy Resources in Heating processes (RES-H) in Germany. It is now part of the 2009

EEWärmeG and only supports already existing buildings. The MAP supports Renewable Energy technologies (such as solar heating installations, wood pellet stoves, and efficient heat pumps).

Everyone investing in RES heating processes can be a beneficiary of the measure: private individuals, independent tradesmen, non-profit organisation, municipalities and enterprises. Large companies can also be beneficiaries (under special conditions), as well as energy-service enterprises.

The MAP includes two different support programmes applying to beneficiaries according to the size and type of the investment, funded either by the Federal Office of Economics and Export Control (BAFA) or by the German government-owned development bank, the KfW. Both measures have been funded up till 2013 with around €500 million a year.

Investment grants (BAFA-Support) concern smaller installations and is mostly conducted by

private investors in family houses. (Note that BAFA investment support is given for heat

produced in existing buildings but installations in new buildings are eligible if process heat is used). 13 measures are granted through this means, granting owners with lump sum amounts (at least 1300€ for a heating pump, with a possible bonus) or a percentage (for example 36 €/kW for a biomass installation).

In 2013, the Grant measures (BAFA-Support) supported a total of 71 172 installations, foremost

solar, biomass and heat pumps in existing family houses: 35 979 Biomass heating systems, 30

204 Solar thermal collector, 5 349 heat pumps and 595 installations to visualisation of the gains

obtained through the use of RE. The percentage of new demands for BAFA-subsidies was in

2013 18% superior than 2012 (79 203 against 66 920 new demands). In 2013, MAP Grant

Policy Name

and URL

Renewable Energy Heating Act and Market Incentive Programme (MAP)

http://www.res-legal.eu/search-by-country/germany/

http://energytransition.de/2012/10/renewable-energy-heating-act-and-market-incentive-program-map/

Promoting Institution

Federal Ministry for Economic Affairs and Energy (BMWi) German federal Agency: Federal Office of Economics and Export Control (BAFA)

Country (Region)

Germany

Level of involvement

National

http://www.res-legal.eu/search-by-country/germany/http://energytransition.de/2012/10/renewable-energy-heating-act-and-market-incentive-program-map/http://energytransition.de/2012/10/renewable-energy-heating-act-and-market-incentive-program-map/

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measures represented public support of 321 million euro and triggered 1,23 billion euro

investment by the grant beneficiaries . This represents a clear increase compared to the 2012

and 2011 periods.

With loans measures (KfW-Support), KfW provides low-interest loans with grant payback

support for the development and expansion of heat installations/plants. This applies to investment in larger heating solutions (for example solar installations from 40 m², Biomass installations above 100 kW, efficient heating pumps from 100 kw, Biogas, local heating network and heat storage facilities for heat from renewable energy as well as mine water projects – mainly realised in commercial and communal domain)..

Regarding the loan part (KfW-support) of the MAP for constructions in larger service types as

well as for heating network and heat-storage devices (recharged with RE), 2 695 project loans representing 289 million euro have been given. Heating networks are here the most important investment with 1 677 loans (representing 191 million euro), followed by biomass installations (705 loans), heat storage devices (190 loans) and solar thermal installations (59 loans). In 2013, the KfW loan supply part of the policy represented also 2 093 new demands. This is a lower level than 2012, where it represented 2 336 demands.13 Nonetheless, the entire available budget has been used in 2013.

Note that owners have to choose between the two kinds of support measures.

Side-type interactions

The rationale of the policy aims at supporting the demand for RES by citizens and public structures, through several instruments:

Through the EEWärmeG and the obligation for new building owners to include a part of RE in the heating systems, one can talk about regulation of demand (the aim is to create a market; process and “usage” norms)

Through the Market Incentive Programme designed to have building owner invest in RE, there is a private demand policy: Direct/financial support (demand subsidies)

One can also see an Indirect/soft steering support through the PR campaigns aimed at informing people about the policy.

Interactions with demand/supply side

This policy is thus addressing foremost demand side via the support of investment for all kinds of property owners and investors.

The figure below illustrates the different demand side factors linked to this policy action.

13 http://www.erneuerbare-energien.de/die-themen/foerderung/marktanreizprogramm/

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Assessment of impacts

According to the 2010 evaluation, the total Funds in 2010 reached €265 million, while the funds

actually used represented €115 million (due to the economic crisis of 2010). Those investments triggered €844 million of private investments, about €150 million tax revenues and positive effects on employment.14 The Heinrich Böll Foundation thus declares: “Every euro spent here generates more than 7 euros in private investments”15

The German renewable energy market increased and continues to increase. According to a MAP policy evaluation from 2010 on 2009 actions, the policy has had an overall positive effect on the demand for RES in Germany. As a matter of fact, it is estimated that 70% of German RES

installations are given grants by the MAP: 80% in Biomass domain, 45% of heating pumps and 80% of solar energy. The incentive effect of MAP is illustrated by the fact that 50% of beneficiaries declare they would not have invested – or only partially – without the MAP measures. This figure suggest that policy mix is clearly having an impact on the supply side i.e. increasing the provision of housing built or renovated with the use RE and is having an impact on the suppliers of RE equipment.

MAP measures beneficiated mostly to German producers: 80% of solar industry MAP investment address German production, as well as 65% in heating pumps sector.

Besides, the evaluation report gives an estimation of the part of MAP-induced workers in the RES labour market: this represents 60 % in solar energy domain, 12 % in heating pumps and 8 % in biomass domain.

Policy lessons

The support programme for Renewable Energy in heating systems in Germany can be divided in two major parts: the investment grants concerning foremost private owners and loans incentives, concerning larger installations such as enterprises or municipalities.

14 http://www.solarordinances.eu/LinkClick.aspx?fileticket=XOpuYPRZXVo%3D&tabid=423

15 http://energytransition.de/2012/10/renewable-energy-heating-act-and-market-incentive-program-map/

http://energytransition.de/2012/10/renewable-energy-heating-act-and-market-incentive-program-map/

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The evaluation reports state that the implemented measures have reached their goal of improving the RES sector for heating systems.

The major strengths of the policy are the following:

The obligation of a percentage of Renewable Energies for new buildings is seen as particularly efficient. Most MAP beneficiaries are owners of new buildings.

Besides, the BAFA-funded grants for private users are a success, as the number of MAP beneficiaries increases since the launch of the policy.

The 2010 evaluation report shows that the sector of RES heating is also expanding without MAP grants – this can be explained through the fact that the MAP has “prepared the ground” by changing housing of building constructors approach and the desire of consumers to use

RE, for an even larger expansion of RES.

German RES equipment producers seem to have taken especially advantage of the MAP measures, as much of the increasing demand goes to domestic producers.

However, there are also some weaknesses:

The sustainability of the MAP financial measures can be put on hold by policy-makers – as was the case during the economic crisis, the incentive measures were frozen in May 2010 (and launched again in July 2010), which slowed down the whole policy.

Moreover, one can observe that the number of KfW-funded loans is lightly decreasing, which can be seen as a failure in terms of the long-term policy. However, this is balanced by the increase of BAFA grants.

References

Contact details of key person for this policy: Mr. Wagner, solar@bafa.bund.de Tél: +496196 908 301

Policy documents, evaluation reports