Paper Title
AN EXAMINATION ON THE EFFICIENCY LEVEL OF G20 ECONOMIES TO NEW INVESTMENT AND TECHNOLOGICAL DEVELOPMENT: DATA ENVELOPMENT ANALYSIS AND MACHINE LEARNING

Abstract
Abstract - Problem Statement: All countries race to increase the level of development and welfare."Which of the countries rapid move?" is among the most frequently spoken table talks. However, not everyone competes on equal terms. While analyzing countries, each country should be evaluated according to its resources. Advantages and disadvantages should be considered in subjects such as economic conjuncture, business environment, resources, geography, technology, etc. The issues of comforting the business environment and adapting to technology constitute the infrastructure of economic progress of countries. It will be useful to discover questions about which countries are more efficient in these actions according to their dynamics, and which action is more important. Methods: G20 countries were divided into two subgroups developed and developing to further increase homogeneity, and examined. As comparable data, GDP per capita was chosen as the input, and country efficiencies between 2016 and 2020 were examined in reaching Doing Business and Global Connectivity Index scores as outputs. Data Envelopment Analysis was used to explore efficiency. Then, Machine Learning methods (Decision Tree and Random Forest) were used to determine which output is more important. Results: South Korea (in 2016 and 2020) and India (in 2019) shine out as the most efficient variables. Doing Business scores were more important than Global Connectivity Index for both groups (developed and developing). Conclusion: It may be beneficial for developed countries to focus on South Korea (especially in 2016 and 2020) while developing countries concentrate on India (especially in 2019). Additionally, an examination of their policies can be beneficial to the roadmap of entrepreneurship and policymakers. Regardless of the development level of the countries, providing a facilitating environment for entrepreneurs and investors and increasing their comfort can make significant contributions. In any case, there are opportunities, however, the matter is whether they are supported or not. Abbreviations: GDP (Gross Domestic Product), ICT (Information and Communication Technology), GCI (Global Connectivity Index), DB (Doing Business), DEA (Data Envelopment Analysis), ML (Machine Learning), DMUs (Decision Making Units) Keywords - G20, Doing Business, Global Connectivity Index, Data Envelopment Analysis, Machine Learning, Decision Tree, Random Forest.