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      경기도 바이오 기업 지리적 분포에 관한 연구 - 자생적 클러스터 탐지와 역량 분석 = A Study on the Geographical Distribution of Bio Firms in Gyeonggido Province: Detecting Spontaneous Clusters and Assessing Capabilities

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      https://www.riss.kr/link?id=A110108704

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      The objective of this study was to establish an integrated analytical framework to examine clustering patterns and distributional inequalities among bio firms in Gyeonggi-do. Unlike previous studies that relied on aggregate data by administrative unit, we performed clustering analysis and hot/cold spot analysis based on network distances, which reflect actual road-based travel distances. Using density-based clustering (HDBSCAN), which can simultaneously consider corporate attributes and geographic spatial information, 3,259 bio companies in Gyeonggi-do were classified into 27 clusters and a group of non-clustered firms, and the characteristics of each group were analyzed. In addition, geographic patterns were examined by identifying hot and cold spots based on corporate attributes within the 27 clusters. We propose an integrated analytical framework that utilizes HDBSCAN to reveal the spatial structure of bio firms in Gyeonggi-do and, through hot/cold spot analysis, to identify disparities in R&D expenditures, sales, employment, and patent registrations. Beyond its methodological contribution, the data-driven clustering results obtained highlight the need for tailored development strategies and linkage policies to create synergies among clusters.
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      The objective of this study was to establish an integrated analytical framework to examine clustering patterns and distributional inequalities among bio firms in Gyeonggi-do. Unlike previous studies that relied on aggregate data by administrative unit...

      The objective of this study was to establish an integrated analytical framework to examine clustering patterns and distributional inequalities among bio firms in Gyeonggi-do. Unlike previous studies that relied on aggregate data by administrative unit, we performed clustering analysis and hot/cold spot analysis based on network distances, which reflect actual road-based travel distances. Using density-based clustering (HDBSCAN), which can simultaneously consider corporate attributes and geographic spatial information, 3,259 bio companies in Gyeonggi-do were classified into 27 clusters and a group of non-clustered firms, and the characteristics of each group were analyzed. In addition, geographic patterns were examined by identifying hot and cold spots based on corporate attributes within the 27 clusters. We propose an integrated analytical framework that utilizes HDBSCAN to reveal the spatial structure of bio firms in Gyeonggi-do and, through hot/cold spot analysis, to identify disparities in R&D expenditures, sales, employment, and patent registrations. Beyond its methodological contribution, the data-driven clustering results obtained highlight the need for tailored development strategies and linkage policies to create synergies among clusters.

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