Structural PCA-MLR model of the innovation environment in BRICS countries - Petkovski, Ivana (Serbian Journal of Management, 2022)
The process of globalization forces market changes in the form of intense competition. Economies can survive by getting competitive advantage in the global market through developing innovation. The main target of this empirical research is to discover the most important innovation components that constitute structure of the global innovation index (GII) and judge their influence on this ranking in emerging BRICS economies. Innovation process is discussed on the grounds of GII ranking scores accumulated from 2011 to 2019. Proposed methodological framework for finding components that strongly engage with the GII is the principal component analysis (PCA). The PCA is employed to reduce a variety of the GII components to a one-factor or two-factor solution in each of the GII dimension. The research outcome of the PCA adopted nine components that represent seven dimensions. Dimensions that indicate institutions and infrastructure offered two-factor solutions. Extracted components are further used in the regression analysis to establish a multiple linear regression (MLR) equation for predicting the GII score used in the overall ranking. Derived regression solution introduced valuable MLR results with high coefficient of determination where 96.1% of the GII values are explained by the extracted components. The dominant effects on GII are attained in innovation output components that include knowledge impact and intangible assets. Moreover, comparison analysis of the actual and computed GII scores illustrated 98.9% overlap between the two values. Evaluated results of the PCA-MLR analysis serve to investigate the success in developing innovation performances in emerging economies by comparing innovation index accomplished by BRICS.