Until the 1990s, the most dominant approach towards innovation was the linear model of innovation policy focusing on R&D infrastructure, financial innovation support for companies and technology transfer processes. These policies emphasized the supply of innovation inputs and of support instruments. However, these linear models did not take into account the absorption capacity of firms and the specific demand for innovation support in less favoured regions (Lagendijk, in Boekema et al., 2000). The traditional
31 concepts, which considered firms innovating in isolation, have been replaced by modern theories which consider the systematic character of innovation like the National Systems of Innovation (Todtling and Trippl, 2005).
Initially the focus of innovation system theories centred on activity at a national level (Lundvall 1992; Nelson 1993). NIS literature uncovers the differences between countries in terms of economic structure, R&D base, institutional capability and innovation performance (Edquist, 2001). It was soon recognized that the most useable definition of innovation systems might not coincide with national borders, and therefore the concept of ‗technological systems‘ which focus on innovation in particular techno- economic areas emerged (Carlsson, 2006). More recently innovation system theorists have become interested in considering regional level activity as well. Although these theorists agree that national and technological level systems are essential, they argued however that the regional dimension is also very important (Acs, 2000; Mytelka, 2000). ―Regional innovation systems are far from being self-sustaining units. Normally
they have various links to national and international actors and innovation systems‖
(Todtling and Trippl, 2005, p1206). There is a further theoretical category of the innovation systems in existence, mostly recognized as ‗sectoral innovation systems‘ and launched in 1997 (Breschi and Malerba, in Edquist 1997). Thus far then, there are four categories of innovation systems which include, national, regional, sectoral and technological (Niosi, 2002; Carlsson, 2006).
Since the 1970s, following the emergence of the concept of globalization emerged theories around a national innovation strategy have been extended to the regions. This has resulted in a regional innovation strategy, the main aim which was the development of regional and national economies in close cooperation with central and regional governments (Chung, 2004). Since 1990, regional innovation policy has been
32 influenced by the concept of NIS. Therefore, if the concept of NIS is applied to regional policy, a concept of regional innovation systems can be identified as a sub-system of NIS (Chung, 2002).
The existence of critical ingredients necessary in order to have successful regional innovation systems consist of: general environmental factors, industry-related elements and company-specific ingredients. The mixture of these components based on the presence of knowledge generation sources like universities and research institutes, leads to an enhancement of the competitiveness of the region. University-industry collaboration is thus vital to stimulate regional innovation capabilities (Van Looy et al., 2003).
Regional innovation systems are conceptualized as comprising ―…a collective
order based on micro constitutional regulation conditioned by trust, reliability, exchange and cooperative interaction‖. The role of trust is considered here as the core
of successful innovation systems (Cooke, in Braczyk et al., 1998, p24).
Four elements are widely recognized in the literature as key components of a regional innovation system: development of cultural norms of openness to learning, trust and cooperation between firms; the presence of several firms and other organizations (regional agglomeration) in close proximity in specific geographical space, in a single industry, or in complementary industries; the existence and quality of a stock of proximate capital, such as human capital and an associative governance regime (Lundvall and Johnson, 1994; Morgan, 1997; Niosi and Bas, 2001).
The concept of NIS is mostly related to growth and development in developed countries, however it may be relevant for developing and emerging countries as well (Lundvall et al., 2002). The first country to adopt the concept of an NIS as a basic constituent of its science and technology policy was Finland (Sharif, 2006).
33 Furthermore, as noted by Rooks and Oerlemans (2005) the first developing country to adopt an NSI concept in its policy-making was South Africa.
There are various definitions in existence regarding National Systems of Innovation, however there is no consensus exists (OECD, 1997a; Niosi, 2002). This variation in the definition is related to ontological aspects which imply that the historic nature of the object precludes a single definition (Godinho et al, 2006). Table 3.1 lists the various definitions regarding NIS.
From Table 3.1, in all definitions the interaction between the actors is the most common feature. The basic characteristics of National Systems of Innovation are the institutional set-up related to innovation, and the underlying production system (Edquist 1997a). Although different countries have similar institutions to advocate innovation, they differ considerably in the way in which these institutions interact with each other in order to pursue the innovation process; this reveals the importance of the concept of the system in such a consideration (Lee and Tunzelmann, 2005).
Definition Reference
―. . . The elements and relationships which interact in the
production, diffusion and use of new, and economically useful knowledge . . . and are either located within or rooted inside the borders of a nation state.‖
Lundvall (1992, p2)
―. . . A national system of innovation is the system of interacting
private and public firms (either large or small), universities, and government agencies aiming at the production of science and technology within national borders. Interaction among these units may be technical, commercial, legal, social, and financial, in as much as the goal of the interaction is the development, protection, financing or regulation of new science and technology.‖
Niosi et al., (1993, p212)
―That set of distinct institutions which jointly and individually
contributes to the development and diffusion of new technologies and which provides the framework within which governments form and implement policies to influence the innovation process.‖
Metcalfe, in Stoneman (1995, p2)
34 In developing countries three levels are assumed for NIS (Figure 3.1). The first level is made up of the industrial clusters within a country (all producers, buyers, and suppliers). This layer is known as a national industrial cluster and is crucial to local technological development and competitiveness. The second level consists of a set of institutions and organizations which support the learning process in industrial clusters. The exchange of knowledge and information between these institutions leads to interactive learning. These institutions include: universities, financial institutions, physical infrastructure and technological support. The final level is the set of policies that stimulate the learning processes between industrial clusters and institutions. These policies include: political and macroeconomic environment measures, trade and competition regimes, tax regimes and legislations. It is worth mentioning that NIS differs from one developing country to another. The reason underlying this is that there are differences in terms of strength of enterprises within them, efficiency of their collective learning processes and the intensity of external links. Unfortunately most NIS in developing countries has a degree of deficiency in one, some or all of these factors (Wignaraja, 2003).
35 Figure 3.1: National innovation system (NIS), Adapted from Wignaraja, 2003.
In many developing countries, e.g. Thailand, the scope for innovation is limited and the network between institutions is fragmented and incomplete. This problem, which is prevalent in most developing countries, can be classified on three levels. On a macro level, the NIS is weak and fragmented and there is a lack of policy coherence and direction. On a Meso level, linkage between university, industry and government agencies is also weak and fragmented. On the Micro level, there is a low absorptive technology and innovation capability in SMEs; also there is a lack of innovation culture in SMEs, and a lack of industrial networking and social capital which is vital for creating knowledge and innovation. Trust - as an important element of social capital- is crucial for networking between companies and government, between companies and
36 universities, and also amongst firms. Particularly for these developing countries Governments should strive to create an environment that increases trust, entrepreneurship and knowledge sharing. Network facilitators who are either government-sponsored or operate independently are needed in order to create such an environment (Yokakul and Zawdie, 2009).
According to Yim and Nath (2005) developing countries also can achieve the goal of leapfrogging their economy from production-based to knowledge-based. Malaysia is the clearest example, where the government has chosen to use the advantage of a cluster approach, and has created specific specialized agencies to achieve this goal. The Malaysian case confirms that NIS is a system that has to be continuously aligned and realigned along with national priorities. This implies other developing countries have opportunities to evolve an effective NIS. Effective strategic planning and implementation are more important than relying on natural resources in building national technological capacity.
There are four pillars and actor groups which build the NIS for each country. These groups are industry, academia, government and public research institutes (Chung, 2004). According to Niosi (2002) there are two major building blocks of NIS - institutions and linkages. These institutions are: private firms, government laboratories, public agencies and universities. The second building block is linkages and flow, which are categorized using the following determining characteristics that may help or impede the efficient operation of the NIS (Niosi, 2002):
Financial flow between government and private organizations; start-up companies and venture capital firms are the good examples;
Human flow between universities, government laboratories and industries;
Regulation flow which is mostly initiated by government agencies for innovative organizations;
37 According to Rooks and Oerlemans (2005) firm is one of the important actors in NIS and requires thorough analysis. The innovative performance of firms depends partly on the support of other actors in the NIS. Regarding this issue a variety of flow into business firms can be assumed. There are four types of flow, and the effectiveness of each may lead to an increase in the innovative performance of industry:
Effectiveness of Knowledge Flow
Effectiveness of Financial Capital Flow
Effectiveness of Human Capital Flow
Effectiveness of Regulatory Flow
Government has a critical role in NIS. Designing proper policies and regulation can facilitate innovation in a country. Many developing countries suffer from government weakness in the design of effective technology policies. In the case of South Africa for example, this weakness includes the absence of a policy framework for intellectual property and fragmentation of government science and technology (Rooks and Oerlemans, 2005).
Research conducted by Godinho et al., (2006) shows that different NIS can be categorized based on eight major dimensions which are: market conditions; institutional conditions; intangible and tangible investments; basic and applied knowledge; external communication; and diffusion and innovation. Twenty nine indicators were selected to provide empirical evidence for these dimensions. Based on these indicators 69 countries were selected and the analysis indicates that nations can be classified as either ―developed NIS‖ or ―developing NIS‖. In the next stage of his analysis he narrows down his focus, progressing to provide greater detail of analysis. As a result he assumes three branches for ―developing NIS‖ which may be considered. These ‗branches‘ include: unformed NIS; emerging NIS and catching up NIS. This study placed Iran in the first branch which is developing but unformed NIS. A study carried out by Svarc
38 (2006) considers the impact of socio-political factors on innovation policy in transition countries like Croatia, concluding that in order to move efficiently towards a knowledge economy, it is crucial to redesign present development policies.
3.3.1.1 The importance of universities as a pillar for regional innovation systems
Historically the development and diffusion of knowledge has been considered as a push model viewed in linear terms. This definition assumes knowledge was created outside the production system, e.g. universities, and was then ―pushed out‖ to industry to undergo further development and adoption. This view considers universities as a source of conducting trials or other experiments to prove concepts identified during research (Smith, 1990). NIS theory which emerged after traditional theories, assumed a more active role for universities in economic development, further assuming more complex interaction between all innovation actors (Freeman 1991; Lundvall 1992). NIS concepts evolved to increase attention to the role universities perform in fostering regional agglomeration through knowledge spillovers resulting from their research and educational activities (Camagni, 1991; OECD, 2001a).
Many countries have concerns regarding the diffusion of scientific and technical human capital from the home to the host country. Many nations have designed initiatives and aims for potential policy solutions. In New Zealand for example, these initiatives have been designed in two phases which include the control phase – traditional- that regulates the flow of individual human capital. This phase focuses on forcing scientists to remain in, return to, or emigrate to the home country. The second phase is a stimulation stage which creates more opportunities for research, innovation and entrepreneurship at home, stimulating the return of migrants e.g. by developing
39 excellence in research and investment in R&D. The latter is more efficient and more systemic in nature than the former (Davenport, 2004).
3.3.1.2 Culture: An important component of National Systems of Innovation Important cultural norms can facilitate interactive learning in a regional innovation system. These norms include openness to learning, trust and cooperation between firms (Cooke and Morgan, 1998). Referring to the importance of cultural norms that support learning and interactive innovation, Cooke points to the degree of embeddedness of a region; its institutions and its organizations, as key structural issues (Cooke, 2002). Embeddedness is defined as: ―the extent to which a social community operates in terms
of shared norms of cooperation, trustful interaction, and untraded interdependencies, as distinct from competitive, individualistic, arms length exchange, and hierarchical norms‖ (Cooke, 2002, p14).
Such socio-institutional and cultural factors have a significant role in shaping science, research and innovation (Ney, 1999). According to Nelson and Rosenberg (1993) National Science and Technology policy performance is considerably affected by the socio-institutional configuration in which research, innovation and technological advance take place. Although development of cultural norms is recognized as a key constituent of regional innovation systems, Ney (1999) indicated a weakness in the national innovation systems account of culture, the national differences at empirical and theoretical level are not considered in the constructs of NIS‘s. Ney (1999) argues that at the empirical level Nelson‘s (1993) work on the national political cultures has an effect on the structures and practices of NIS‘s, and discusses the reason for France and Britain‘s difference in this regard. Although true generally, at an empirical level it offers little convincing explanation that this is the case. In this view political culture is the ―uncaused cause‖ of the structural features of the innovation system. In this
40 approach, the analysis of which factors cause a political culture to change is not plausible, rendering it impossible to discern how changes in national innovation systems affect political culture (Ney, 1999). The theoretical approach which is based on the work of Lundvall (1988) also views this relationship in the same way and assumes that culture is a relatively constant entity impacting on national systems of innovation. Both views assess the impact of culture to be essentially in one direction. In these views, national culture has an effect on the process of innovation; however, neither is able to explain the means through which development of national innovation systems has impacted on specific national cultures (Ney, 1999).