Evaluating global intelligence innovation: An index based on machine learning methods

This study investigates national intelligence innovation through machine learning methods. We propose a global intelligence innovation index (GIII) to evaluate the global landscape of intelligence innovation of 101 countries around the world. First, we develop a conceptual framework of national intelligence innovation based on the innovation ecosystem theory to construct GIII. Second, we measure GIII based on machine learning methods, including the k-means clustering algorithm and the random forest model. Finally, we evaluate the national intelligence innovation using GIII and provide theoretical and practical insights. The results show that global intelligence innovation development presents a convoluted situation, as high income doesn't necessarily promote intelligence innovation. Furthermore, intelligence innovation shows interesting relationships with unemployment, aging, and shares of economic sectors. GIII provides a reference to the level of intelligence innovation in various countries around the world and helps decision-makers better formulate policies to facilitate intelligence innovation development.