The literature on national innovation systems (NIS) is a relatively new and rapidly growing field of research (1) (Fagerberg 2003; Balzat and Hanusch 2004). The NIS approach was initiated in the late 1980s by Chris Freeman (1987), Giovanni Dosi et al. (1988), and Bengt Ake Lundvall (1992) and followed by Richard Nelson (1993), Charles Edquist (1997), and many others. Markus Balzat and Horst Hanusch (2004, 196) have described an NIS as "a historically grown subsystem of the national economy in which various organizations and institutions interact with and influence one another in the carrying out of innovative activity." It is about a systemic approach to innovation in which the interaction between technology, institutions, and organizations is central.
Since the late 1990s, NIS thinking emerged in a growing number of policy studies (e.g., OECD 1999, 2002). However, Balzat and Hanusch (2004, 200) have rightly observed a conflict between the theoretical conjectures and methodology of the NIS contributions and the practical implementation of the NIS policy benchmark studies. The latter often use benchmark techniques comparing single benchmark indicators across countries with the aim of clear cut policy recommendations and designing optimal institutional framework conditions for innovation performance.
We explain in this paper that on one hand policy makers have interpreted the theoretical NIS contributions according to the new institutional economics (NIE) perspective on institutions. On the other hand we suggest that the theoretical contributions to NIS sufficiently conceptualized neither institutions nor the dynamics of NIS over time (Nelson 2002; Malerba 2005).
We suggest that more attention should be given to the evolutionary concept of a hierarchy of levels of institutions. In this article we perceive the NIS as a layered system with a specific logic based on habits and routines. Not only would such insight show the limitations of copying a benchmark but also the dynamics of the NIS could be captured by explicitly analyzing the interaction between different institutional layers. Such an approach would result in more effective policy recommendations. The purpose of this paper is to discuss the ingredients of such a more layered and dynamic NIS approach.
NIS and Policy Making
The contributions of the NIS literature had a large impact on policy makers. The NIS approach gradually replaced linear thinking about innovation by a more holistic system perspective on innovations focusing on the interdependencies among the various agents, organizations, and institutions. NIS thinking led to a structurally different view of how governments can stimulate the innovation performance of a country.
The various policy studies have in common that they try to describe and compare the most important institutions, organizations, activities, and interactions of public and private actors that take part in or influence the innovation process of a country. Figure 1 provides an illustration.
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The figure demonstrates the major building blocks of a NIS in a practical policy setting. It includes firms, universities, and other public research organizations (PROs) involved in education and training, science, and technology. These organizations embody the science and technology capabilities and knowledge fund of a country. The interaction is represented by the arrows which refer to interactive learning and diffusion of knowledge. The building block "demand" refers to the level and quality of demand that can be a pull factor for firms to innovate. Finally, institutions are represented in the building blocks "framework conditions" and "infrastructure," including various laws, policies, and regulations related to science, technology, and entrepreneurship. It includes a very broad array of policy issues from intellectual property rights (IPR) laws to fiscal instruments that stimulate labor mobility between universities and firms.
The figure demonstrates that in order to improve the innovation performance of a country, the NIS as a whole should be conducive for innovative activities in a country. Since the late 1990s, the conceptual framework as represented in figure 1 serves as a dominant design for many comparative studies of national innovation systems (Polt et al. 2001). The typical benchmark exercises compare a number of innovation indicators. In this way best practice policies are identified and policy recommendations are derived: the so-called one-size-fits-all approach....