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Methodological and empirical research on structure analysis of national innovation development performance
Mu Rongping, Zhang Jingjing, Chen Kaihua
2020, 41(1):
12-21.
Innovation development has become a world trend, while global innovation development structure is undergoing profound change. How to scientifically monitor the direction of structure evolution of innovation development performance has attracted increasingly more and more attention from both governments and academia. This paper clearly defines “the structure among countries” as the position of each country located within certain spatial scale or the system composed of countries in terms of some variable(s), and “the methods for analyzing the structure” as the methods for analyzing the structure of some type of subject (e.g. country, region, industry, and company) within certain spatial scale (e.g. the whole world, Asia, Yangtze River Delta Region, Jiangsu Province) or the system (e.g. manufacturing industry, automotive industry, household appliances industry) at a particular point in terms of some variable(s) (i.e. indexes such as innovation development level, innovation capacity, and indicators such as R&D expenditure, number of patents), therefore we define “the methods for analyzing the structure among countries” as the methods for analyzing the structure of certain system(e.g. the whole world, Asia, OECD) composed of countries in terms of some variable(s).
Methods for analyzing the structure among countries can be categorized into one-dimensional and two-dimensional methods based on the number of variable(s). Auxiliary variables such as GDP or GDP per capita can be introduced to broaden policy implication of the structure analysis. We propose the methods for analyzing the two-dimensional structure of innovation development performance among countries, including: (i) the two-dimensional structure of innovation development performance among countries in terms of the innovation development index and the innovation capacity index, and (ii) the two-dimensional structure of innovation capacity among countries in terms of the two sub-indexes of innovation capacity, namely, the innovation strength index and the innovation effectiveness index, based on the clustering method, bisection (or trisection) method, and the balance line method. The clustering method is the method for classifying countries in terms of two variables based on a certain clustering algorithm as shown in Figure 1. Bisection (or Trisection) method is the method for classifying countries in terms of two variables based on the area where every country is located, as shown in Figure 2a and Figure 2b. The balance line method is the method for classifying countries in terms of two variables based on the distance between each country’s position and the balance line as shown in Figure 3a and Figure 3b.
We analyze the structure based on the ranking of the innovation development index, and the innovation capacity index as well as the sub-indexes of the innovation capacity index among 40 countries, and conclude as following.
(1) 40 countries were divided into four categories by using K-means clustering method in terms of the ranking of the innovation capacity index and the innovation development index. The first category is the leading countries of innovation, which consist of countries with high innovation development level and strong innovation capacity, i.e. United Kingdom, France , Japan, Switzerland, Sweden, Singapore, Norway, Netherlands, Denmark, Belgium, and countries with relatively higher innovation development level and strong innovation capacity with large economic scale, i.e. United States, Germany and South Korea. The second category is the advanced countries of innovation, which consist of countries with relatively higher innovation development level and relatively stronger innovation capacity, i.e. Austria, New Zealand, Australia, Canada, Spain, Italy, Greece, Czech, Chile, Portugal and Hungary. The third category is the catching-up countries of innovation, which consist of countries with relatively lower innovation development level and relatively weaker innovation capacity, i.e. Malaysia, Poland, Slovakia, Russia, Argentina, Brazil, Mexico, Romania, South Africa, Thailand and India. The fourth category is the unconventional catching-up countries of innovation, which consist of countries with a large gap between the ranking of the innovation development index and the ranking of the innovation capacity index, i.e. China and Turkey.
(2) The empirical research on the structure analysis of innovation development performance among countries in terms of the ranking of the innovation capacity index and the innovation development index, by introducing the auxiliary variables such as GDP per capita and GDP, shows that countries with higher level of economic development (measured by GDP per capita) usually have higher ranking of the innovation capacity index and the innovation development index, which implies that the level of economic development is highly positively related to the national innovation development performance, while countries belonging to the first category with larger economic scale (measured by GDP) usually have higher ranking of the innovation capacity index than ranking of the innovation development index.
(3) The empirical research on the structure analysis of innovation capacity among countries, by introducing the auxiliary variables such as GDP and GDP per capita, shows that countries with larger economic scale (measured by GDP) usually have higher ranking of the innovation strength index, while countries with higher level of economic development (measured by GDP per capita) usually have higher ranking of the innovation effectiveness index.
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