Application of country classification methodology for enhancing the effectiveness of official development assistance (ODA) policies
Utilization of decision tree analysis
Bibliographic Data
| ID | 22190165 |
|---|---|
| Authors | Young-Chool Choi (0009-0009-6770-9333, Chungbuk National University, corresponding author) |
| Year | 2024 |
| Volume | 8 |
| Issue | 15 |
| Pages | 9871 |
| Publication date | 2024-12-17 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Infrastructure Policy and Development (JOURNAL) |
| Journal identifiers | ISSN: 2572-7923 • E-ISSN: 2572-7931 |
| Publisher | EnPress Publisher (PUBLISHER) |
| DOI | 10.24294/jipd9871 |
| OpenAlex | W4405483879 |
| Language | EN |
| References cited | 7 |
Objective: As the scale and importance of official development assistance (ODA) continue to grow, the need to enhance the effectiveness of ODA policies has become more critical than ever before. In this context, it is essential to systematically classify recipient countries and establish tailored ODA policies based on these classifications. The objective of this study is 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. Results: 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
Business · Decision tree · Management science · Operations research · Computer Science · Engineering · Global Trade and Competitiveness · Artificial Intelligence
| Highly cited | No |
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