Academic journal article Innovation: Organization & Management

Determinants of National Innovation Systems: Policy Implications for Developing Countries

Academic journal article Innovation: Organization & Management

Determinants of National Innovation Systems: Policy Implications for Developing Countries

Article excerpt

While recent research has emphasised the importance of National Innovation Systems or National Systems of Innovation (NIS/NSI)1 to the economic health of countries (Block & Keller 2008). The roots of the empirical work on NIS are found in investigations into the interactions between human capital, diffusion of technology and economic growth (Solow 1960; Nelson & Phelps 1966; Arrow 1996) and further back in terms of Marshallan industrial districts (Marshall 1920). Despite the wealth of conceptual and theoretical contributions, statistical assessments that use dynamic network analysis, structural equation modelling (SEM), and multiple regressions to model NIS are relatively few. This paper examines the phenomenon respective to the literature and provides a statistical framework analysis. It uses cross-sectional data of indices of competitiveness, technology, industrial performance and human development for 26 developed countries and 20 emerging markets economies (EMEs; see Appendix I).

The research attempts to identify the factors that actually depict NIS and establish how the constructs can be measured. The underlying assumption is that certain determinants of coherent and high performing NIS exist in developed economies and emerging markets and these determinants can provide valuable insights to policy for, and management of, NIS in developing countries with not so high-performing economies.

Within the debate concerning the institutions or technology roots of economic growth (Nelson & Phelps 1966) NIS has become especially important in national policy since 1980 (European Commission 2004). This is reflected not only in public policy support for small and mediumsized enterprises (SMEs) as sources of innovation (Audretsch 2004) but also by the Community Innovation Surveys of the EU2. NIS literature has expanded to cover multi-faceted dimensions in the economics of technology, industrial performance and competitiveness and innovation (including regional innovation systems, industrial dynamics and structural change). According to Asheim and Gertler (2005), innovative activities and the economic geographies that conform to the efficiency and effectiveness of knowledge links are crucial to development. Though the dynamics of that knowledge and spatial concentration of economic relations are based on intellectual assets (Cohen et al. 2000). These concepts inform our research. NIS are prevalent in industrialised and emerging market economies. Nevertheless several developing countries aspire to increase the appreciation of innovation to develop their economies. (See African Union Summit 2007 on science and technology for Africa's development). Therefore, empirical understanding of NIS in industrialised and emerging market economies carry significant implications for developing countries (Bartels & Lederer 2009). The international business dimensions of NIS (e.g., technology transfer via licensing or foreign direct investment) are equally important; this, however, is beyond the scope of the paper.

The paper is organised as follows. The seminal literature on NIS is reviewed in section 'current approaches to National Innovation Systems'. A model of NIS for analysis is presented in section 'an approach to modelling NIS'. In section 'methodology', we illustrate the approach used for identifying, standardising and analysing the data. Results of the factor and multiple regression analyses are presented in section 'analytical results and statistical significance'. The discussion of the results is presented in section 'factor interpretation'. Section 'discussion of regression analysis' concludes.


The 1999 conference on 'National Innovations Systems, Industrial Dynamics and Innovation Policy' (Danish Research Unit for Industrial Dynamics [DRUID] 1999) exposed at least eight dimensions of NIS. Within this broadening field, attention has focused on conceptualisation and measurement issues (Sornn-Friese 2000; Carlsson et al. …

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