Exploring the interaction between competitiveness of a country and innovation using Bayesian networks

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. World Economic Forum (WEF)’s competitiveness model consisting of 12 pillars and 19 sub-pillars is an attempt along these lines. By analysing the interaction between the Innovation pillar and the remaining 11 pillars and their sub-pillars comprising the competitiveness indicators, this paper aims to provide strategic guidelines to policy-makers who search for strategies to improve their country’s innovativeness level. For this purpose, WEF’s Global Competitiveness Index data for the period (2009-2012) is employed. The innovation performance of 148 countries is analysed using an integrated cluster analysis and a Bayesian Network (BN) framework. The use of BNs enables us to discover the probabilistic dependency structure of competitiveness indicators and its innovation performance, which may be analysed in more detail through evidence observation and sensitivity analyses conducted in the network. Thus, with this research, presenting the multidimensional nature between competitiveness indicators and Innovation, a decision support tool for policy-makers is presented, which can be used to form strategy guidelines for enhancing a country’s Innovation level.