Factors Influencing the Promotion of Data-Driven Administration in Korea Local Governments

• In Event: Reforming and Renovating Local Governments in South Korea

Abstract

In recent years, data-driven administration has emerged as a critical paradigm for enhancing the efficiency and transparency of public administration, fueled by advances in big data and artificial intelligence (AI) technologies. This approach, which supports objective and scientific decision-making through data generation, management, analysis, and utilization, holds significant potential for local governments. It is particularly vital in the formulation of localized policies and the improvement of public services. However, local governments face unique challenges, including limited human and financial resources in comparison to central or metropolitan governments, and lower organizational continuity, which hinder their ability to effectively implement data-driven governance.

This study aims to analyze the factors that influence the promotion of data-driven administration within local governments and provide both policy and theoretical implications. The research will focus on data collected from 226 local governments between 2022 and 2023. Data-driven administration will be defined broadly as a concept that covers the full spectrum of data processes, from generation and management to analysis and utilization.

The study will categorize the influencing factors into three main dimensions: organizational, technical, and environmental factors. By investigating these dimensions, we will assess their impact on the data-driven administration of local governments in Korea. The research will employ Pearson's correlation analysis and zero-order gamma regression analysis to systematically explore these factors, drawing on insights from previous studies and existing systems.

Authors

• Sun Yeop Kim, SKKU
  Presenting Author

• Hyung Jun Park, Sungkyunkwan University
  Presenting Author

• Choi Su Hyun, Sungkyunkwan University
  Presenting Author