현재 위치
Home
Culture Convergence (CC)
Identifying Cluster Patterns in Relationship Between Municipal Revenue Configuration and Fiscal Surplus : Application of Machine Learning Methodologies
-
- 발행기관
- 국제문화기술진흥원 바로가기
-
- 간행물
- International Journal of Advanced Culture Technology(IJACT) KCI 등재 바로가기
-
- 통권
- Volume 12 Number 3 (2024.09)바로가기
-
- 페이지
- pp.159-164
-
- 저자
-
- 언어
- 영어(ENG)
-
- URL
- https://www.earticle.net/Article/A456480
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Net surplus serves as a crucial indicator of how efficiently local governments utilize their resources. This study aims to analyze and categorize the patterns of net surplus across 75 local governments in Korea. By employing machine learning techniques such as K-means clustering and silhouette analysis, this research delves into surplus patterns, revealing insights that differ from those provided by traditional analytical methods. Machine learning enables a broader spectrum of discoveries, leading us to identify three distinct clusters in the net surplus of Korean local finances. The characteristics of these three clusters show that the wealthiest cities have the highest surplus ratios. In contrast, mid-sized municipalities, constrained by limited central government support and scarce local resources, exhibit the lowest surplus ratios. Interestingly, a significant number of cities maintain a median surplus ratio even under challenging fiscal conditions. Additionally, we identify critical thresholds that differentiate the three clusters: a grant-in-aid ratio of 19.31%, a debt ratio of 3.52%, and a local tax ratio of 25.58%. This identification of thresholds is a key contribution of our study, as these specific thresholds have not been previously addressed in the literature.
목차
Abstract
1. INTRODUCTION
2. LITERATURE REVIEWS
2.1 Financial Status Analysis
2.2 Behavioral Analysis
2.3 Lesson for This Study
3. RESEARCH DESIGN FOR MACHINE LEARNING
3.1 Dataset and Preprocessing
3.2 Process of Analysis and Algorithms
4. Results of Analysis
4.1 Current Status of Municipal Revenue Configuration and Surplus
4.2 Identifying Clusters by K-means
4.3 Financial Threshold for Classification
5. CONCLUSION
REFERENCES
키워드
Government Fiscal Surplus Machine Learning Methodologies Revenue Configuration Cluster by Financial Sources저자
간행물 정보
발행기관
-
- 발행기관명
- 국제문화기술진흥원 [The International Promotion Agency of Culture Technology]
- 설립연도
- 2009
- 분야
- 공학>공학일반
- 소개
- 본 진흥원은 문화기술(Culture Technology) 관련 산·학·연·관으로 구성된 비영리 단체이다. 문화기술(CT)은 정보통신기술(ICT), 문화적 사고 기반의 예술, 인문학, 디자인, 사회과학기술이 접목된 신융합기술(New Convergence Technology, NCT)로 정의한다. 인간의 삶의 질을 향상시키고, 진보된 방향으로 변화시키고, 문화기술 관련 분야의 학술 및 기술의 발전과 진흥에 공헌하기 위하여, 제3조의 필요한 사업을 행함을 그 목적으로 한다.
간행물
-
- 간행물명
- International Journal of Advanced Culture Technology(IJACT)
- 간기
- 계간
- pISSN
- 2288-7202
- eISSN
- 2288-7318
- 수록기간
- 2013~2025
- 등재여부
- KCI 등재
- 십진분류
- KDC 600 DDC 700
이 권호 내 다른 논문 / International Journal of Advanced Culture Technology(IJACT) Volume 12 Number 3
피인용수 : 0건 (자료제공 : 네이버학술정보)
함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.
출처 : 네이버학술정보
0개의 논문이 장바구니에 담겼습니다.