지리가중회귀모형(GWR)을 이용한 김 양식 성과의 공간적 결정요인 분석 = A Spatial Analysis of the Determinants of Laver(GIM) Aquaculture Performance Using Geographically Weighted Regression(GWR)

다국어 초록 (Multilingual Abstract)

This study analyzes the determinants of laver aquaculture performance with a focus on the laver production stage and examines the spatial heterogeneity of their effects. Using data from 161 cities and counties in 2023, laver production volume and unit price were set as dependent variables. Independent variables included production base, environmental conditions, processing capacity, export value, and policy support. Ordinary Least Squares(OLS) was applied to identify global relationships, followed by Geographically Weighted Regression(GWR) to capture regional variations. Spatial clustering analysis was conducted to classify regions with similar determinant structures. The results show that determinants of laver aquaculture performance differ by region. In areas with large scale production bases, such as Jeonnam and Jeonbuk, production-based factors were associated with increases in production volume. By contrast, in Chungnam, the metropolitan area ancd Busan, processing and export factors exerted a greater influence on unit price formation. These findings indicate that laver aquaculture performance is shaped by region specific linkages among production, processing, and export structures, suggesting the need for differentiated, region-based industry policies. Keywords : Laver aquaculture, Determinants of laver aquaculture performance, Geographically Weighted Regression(GWR), Spatial heterogeneity

목차 (Table of Contents)

• Ⅰ. 서론 1
• 1. 연구의 배경 및 목적 1
• 2. 연구의 방법 및 내용 3
• Ⅱ. 선행연구 6
• 1. 김 생산성 영향요인 분석에 관한 연구 6
• 2. 지리가중회귀분석 모형 활용에 관한 연구 10
• Ⅲ. 김 산업 현황 16
• 1. 생산 현황 16
• 2. 수출 현황 24
• Ⅳ. 분석 자료 및 방법 26
• 1. 분석 자료 26
• 2. 분석 방법 31
• Ⅴ. 분석결과 39
• 1. OLS 분석 결과 39
• 2. GWR 분석 결과 44
• 3. 공간 클러스터 분석 결과 60
• Ⅵ. 결론 67
• 1. 연구 결과 67
• 2. 시사점 및 한계점 71
• 참고 문헌 75