How to improve the innovation level of a country? A Bayesian net approach

This study aims to provide strategic guidelines to policy makers who are developing strategies to improve their country’s innovativeness. In this paper, we claim that innovation cannot be related only to some factors inherent in the environment of a country, nor is it a single entity to be managed without any linkages to the rest of the actors comprising the competitiveness of a country. Hence, a comprehensive study on innovation should cover the interaction between competitiveness indicators and innovation. For this purpose, the innovation performance of 148 countries is analyzed using an integrated cluster analysis and a Bayesian network framework. These countries are first clustered based on the average values of their competitiveness indicators representing 12 pillars and several sub-pillars adopted from the Global Competitiveness Reports of World Economic Forum for the 2009-2012 period. As a result, five appropriate clusters emerge: Leaders, Followers, Runners Up, Developing Ones, and Laggers. A factor analysis is then conducted to reveal the main characteristics of each cluster in terms of competitiveness indicators. Subsequently, a Bayesian network is constructed and sensitivity analyses are performed to reveal important policies for each cluster.