Analysis of Factors Influencing the Trust Levels of Kyrgyzstan Residents, Using Neural Network Analysis

Abstract

Objective: Kyrgyzstan, located in Central Asia, is a country which has a strong will to achieve national development. The aim of this study is to measure the levels of trust of local residents, a highly important factor in national development, and to derive suggestions for improving it. To this end, the primary means employed is to target the residents of Kyrgyzstan and measure the levels of trust they have towards each other. Methods: The study uses data relating to aid projects for rural development that Korea’s Good Neighbors International organization (GNI) is jointly carrying out in Kyrgyzstan along with the Korea International Cooperation Agency (KOICA), a Korean aid provider. In order to carry out the aid project to Kyrgyzstan, these organizations conducted a baseline survey at the initial stage, and the results of this study were used for analysis. As regards the analytical method used in this study, neural network analysis was employed for the questionnaire survey data of 583 people in Kyrgyzstan that was used for the baseline survey. Results: Neural network analysis, a component of the big data analysis method, has recently been in the academic limelight. The analysis revealed that ethnicity had the greatest influence on the trust levels of Kyrgyzstan residents, followed by gender and education level, in that order. Conclusions: From this, it can be seen that multifaceted efforts are needed to increase the levels of trust of peoples other than ethnic Kyrgyzstanis, as they occupy a central position in Kyrgyzstan.