Multi-Criteria Decision Making for Ranking Innovation Levels of G8 Countries With Extended Gii: an Integrated Bayesian Bwm and Topsis Methodology

Abstract

Innovation is vital in today's economies and its effects extend beyond economic growth to enhancing social welfare. Technological advances achieved through innovation increase social benefit by providing solutions that improve the quality of life. Therefore, innovation should be seen as an important tool that increases the general welfare of society. Yet, the relationship between innovation and human development remains one of the least researched topics in the literature. The aims of this paper are twofold: to introduce an extended GII with only 8 key criteria based on innovation, and to rank the G8 countries’ extended GII scores using the Bayesian Best Worst Method (BWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It then compares the proposed formulation scores with the original GII scores and Human Development Index (HDI) scores. According to the findings of this paper, policymakers need to take action on research and development expenditure (% of GDP), industrial design applications (per million people) and patent applications (per million people) in order to achieve high GII score. Furthermore, the top three countries with the highest scores are Germany, Japan, and the United Kingdom, respectively. The results from the paper reveal a higher level of correlation between innovation and human development compared to that found in the relevant literature. The findings demonstrate that the integration of Bayesian BWM and TOPSIS can be effectively used to evaluate the G8 countries in terms of innovation scores. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.