Evaluation Of Korea’s Rural Development Oda Projects In Kyrgyzstan Using Neural Network Analysis: Focusing On Local Residents’ Perceptions

Choi Young-Chool, Yanghoon Song, Ki Seo Kong and Ahyoung Lee

Data and Metadata, 2025, vol. 4, 858

Abstract: This study conducted a mid-term evaluation of Korea’s Integrated Rural Development Project (IRDP) implemented in 30 villages of Osh and Batken regions in Kyrgyzstan since 2021, focusing on local residents' perceptions. Particularly, to overcome the limitations of conventional descriptive statistical methods frequently used in previous studies, this research applied neural network analysis to better capture complex and nonlinear relationships among influencing factors. The results indicated that residents generally perceived the Korean rural development ODA project as significantly contributing to local economic development, with the most influential factor being the village-level characteristics. Furthermore, demographic characteristics such as marital status, age, education level, and occupation of residents also had significant effects on their perceived outcomes of the project. This study confirms the usefulness of neural network analysis as an effective method for evaluating ODA project outcomes based on residents’ perceptions and provides meaningful policy implications for enhancing the effectiveness of future Korean rural development ODA projects.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:4:y:2025:i::p:858:id:1056294dm2025858

DOI: 10.56294/dm2025858

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