Exploring Country Classification Methodology to Enhance the Effectiveness of ODA: Application of Decision Tree Analysis
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(Purpose) The purpose of this study is to enhance the effectiveness of Official Development Assistance (ODA) policies by systematically classifying recipient countries and establishing tailored ODA policies based on these classifications. Specifically, the study aims to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. (Design/methodology/approach) The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. (Findings) The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes. (Research implications and Originality) This study emphasizes the need for systematic classification of recipient countries and the establishment of tailored ODA policies based on these classifications, in a context where the scale and importance of ODA continue to grow. The research's significance lies in its presentation of a practical methodology that can assist donor countries in formulating ODA policies by classifying developing countries through decision tree analysis and proposing specific policy directions for the most vulnerable countries.
Abstract
(Purpose) The purpose of this study is to enhance the effectiveness of Official Development Assistance (ODA) policies by systematically classifying recipient countries and establishing tailored ODA policies based on these classifications. Specifically, the study aims to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. (Design/methodology/approach) The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. (Findings) The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes. (Research implications and Originality) This study emphasizes the need for systematic classification of recipient countries and the establishment of tailored ODA policies based on these classifications, in a context where the scale and importance of ODA continue to grow. The research's significance lies in its presentation of a practical methodology that can assist donor countries in formulating ODA policies by classifying developing countries through decision tree analysis and proposing specific policy directions for the most vulnerable countries.
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