Lundvall B-åke. Introduction. In: Lundvall B-Å, ed. National Systems of Innovation: Toward a Theory of Innovation and Interactive Learning. Anthem Press; 2010:1-20. doi:10.7135/UPO9781843318903.002

1. Definition of National Systems of Innovation (NSI): NSI involves elements and relationships that interact in the creation, diffusion, and use of new, economically useful knowledge within or rooted in a nation state.
2. Role of Nation States in NSI: NSI assumes the existence of nation states, which have cultural-national and étatist-political dimensions. Real-world nation states vary in cultural homogeneity and political centralization, affecting the borders and characteristics of their innovation systems.
3. Public Policy and NSI: Understanding NSI is crucial for designing effective public policies at national and international levels. Government interventions should be compatible with the systemic context of innovation to avoid reinforcing weaknesses or introducing incompatible mechanisms.
4. Performance Indicators of NSI: Performance of NSI should be assessed based on efficiency and effectiveness in producing, diffusing, and exploiting economically useful knowledge. Traditional measures like R&D expenditure and patents have limitations, and a combination of indicators, including new product sales and high-tech exports, is recommended for a more comprehensive assessment.
   • Efficiency and Effectiveness in Knowledge Utilization
   • Core Focus: The primary goal of assessing NSI performance is to evaluate how effectively and efficiently the system produces, diffuses, and exploits economically useful knowledge.
   • Dynamic Nature: This approach contrasts with traditional static economic indicators like GDP, focusing instead on the dynamic aspects of innovation within the national context.
   • Limitations of Traditional Measures
   • R&D Expenditure: While commonly used, R&D spending only indicates the input effort and doesn’t reflect the output or the actual innovation resulting from these investments.
   • Patents and New Products: Patents and the proportion of new products in sales are more direct measures of output, but they still have limitations. Patents may not always lead to economically valuable products, and the focus on new products can miss aspects of innovation in processes or services.
   • Recommended Combined Indicators
   • Comprehensive Approach: A combination of different indicators is advised to get a more accurate picture of NSI performance.
   • High-Tech Exports: The proportion of high-tech products in foreign trade can indicate a country’s success in advanced technology sectors.
   • Diffusion Measures: Incorporating measures of technology diffusion is vital for a complete understanding of NSI performance.
5. Innovation as a Cumulative Process: Innovation in modern capitalism is a fundamental, ubiquitous process rather than rare and exogenous events. It involves continuous learning, searching, and exploring across the economy, resulting in new products, techniques, and markets.
6. Learning and Production Structure: Innovation is rooted in the economic structure and is influenced by routine activities. Institutional set-ups, including technological trajectories and paradigms, guide innovation processes. Institutions provide stability and guidance in an uncertain economic world.
7. Defining NSI – Role of Theory and History: NSI can be defined narrowly (focusing on R&D and scientific institutions) or broadly (including all economic and institutional structures affecting learning and innovation). Historical analysis and theoretical considerations are essential to understand the roles of different subsystems in innovation.
8. Elements of NSI: Key elements of NSI include the internal organization of firms, inter-firm relationships, the role of the public sector, the financial sector, and R&D systems. The organization of information flow and learning processes within firms, cooperation among firms, and the role of the public sector as an innovation user are crucial. National differences in these elements and their interrelationships significantly impact the functioning of NSI.
   • Internal Organization of Firms
   • Innovation Within Firms: Most innovations are developed within firms, making their internal organization crucial for fostering innovation.
   • Information Flow and Learning Processes: How information is shared and processed within firms, especially between sales, production, and R&D departments, significantly impacts innovation capabilities.
   • Inter-Firm Relationships
   • Beyond Competition: Traditional economics emphasizes competition, but for innovation, cooperation between firms is equally vital.
   • User-Producer Interaction: Collaborative relationships, especially in knowledge-intensive industries, are crucial for innovation. This includes not just formal partnerships but also informal exchanges of technical know-how.
   • Role of the Public Sector
   • Direct Support and Influence: The public sector is involved in supporting science and development directly and indirectly influences innovation through regulations and as a user of innovations.
   • Public Sector as an Innovation User: Its competency in utilizing innovations can significantly impact the overall innovation landscape.
   • Financial System and Innovation
   • Schumpeterian View: The financial system’s role in enabling innovation is emphasized, highlighting the need for appropriate financial support and investment in innovative activities.
   • National Differences: Different countries exhibit varying relationships between their financial systems and their innovation processes.
   • R&D System
   • Historical and Current Importance: The evolution and current state of the national R&D system are critical for understanding its impact on NSI.
   • Need for Institutional Innovation: There’s a recognition of the need for ongoing evolution and innovation within the R&D system itself to keep pace with changing technological and economic landscapes.
   • Education and Training
   • Quantitative and Qualitative Differences: Variations in investment, enrollment in science and engineering, and skilled worker training impact innovative capabilities.
   • Social Norms and Values: The education system also plays a role in shaping social norms and values that influence innovation, including attitudes towards egalitarianism versus elitism.
9. Education and Training in NSI: Differences in national education and training systems, both quantitative and qualitative, affect innovative capabilities. Integrating education and training systems into the analysis of NSI is identified as a crucial area for future research.