Earticle

현재 위치 Home

IT Marketing and Policy

Analyzing Inter-Firm Networks of AI Companies in Pangyo Techno Valley : Implications for Gyeonggi Province’s AI Cluster Development

첫 페이지 보기
  • 발행기관
    국제인공지능학회(구 한국인터넷방송통신학회) 바로가기
  • 간행물
    International Journal of Internet, Broadcasting and Communication 바로가기
  • 통권
    Vol.17 No.3 (2025.08)바로가기
  • 페이지
    pp.197-211
  • 저자
    SUJAE LEE, Taekyung Kim, Arum Park
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A472244

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

원문정보

초록

영어
This study investigates the structural characteristics and temporal evolution of the Pangyo AI Cluster’s interfirm networks using Social Network Analysis (SNA). As traditional cluster policies are rooted in physical proximity and manufacturing-oriented supply chains, their applicability to the AI industry—driven by intangible assets and decentralized collaborations—remains uncertain. Using transaction data of 528 AI firms (198,327 transactions from 2021–2023), the study analyzes centrality indicators to compare the Pangyo AI Cluster with conventional manufacturing clusters. Results reveal that while manufacturing clusters exhibit a vertically integrated, conglomerate-driven network, the Pangyo cluster displays a more horizontal, diversified structure involving SMEs and public institutions. Furthermore, the study finds that public agencies, such as the Seongnam Industry Promotion Agency, play a critical intermediary role, underscoring the importance of policy support in early-stage ecosystems. These findings suggest the need for differentiated, digitally focused cluster policies tailored to AI industries, moving beyond physical co-location models. This research provides theoretical and empirical insights into designing future-ready innovation clusters.

목차

Abstract
1. Introduction
2. Research Background
2.1 Industrial Clusters and Transaction Networks
2.2 Characteristics of Firms within the Pangyo AI Cluster and Temporal Network Changes
3. Empirical Study
3.1 Research Objectives and Methodology
3.2. Empirical Analysis
3.3. Analysis Results
4. Conclusion
Acknowledgement
References

키워드

AI Cluster Social Network Analysis Pangyo Industrial Policy Network Centrality Digital Ecosystem.

저자

  • SUJAE LEE [ Department of Urban Bigdata Convergence University of Seoul ]
  • Taekyung Kim [ Big Data Analytics, School of Management Kyung Hee University ]
  • Arum Park [ Big Data Management, School of Management KwangWoon University ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제인공지능학회(구 한국인터넷방송통신학회) [The International Association for Artificial Intelligence]
  • 설립연도
    2000
  • 분야
    공학>전자/정보통신공학
  • 소개
    인터넷방송, 인터넷 TV , 방송 통신 네트워크 및 관련 분야에 대한 국내는 물론 국제적인 학술, 기술의 진흥발전에 공헌하고 지식 정보화 사회에 기여하고자 한다.

간행물

  • 간행물명
    International Journal of Internet, Broadcasting and Communication
  • 간기
    계간
  • pISSN
    2288-4920
  • eISSN
    2288-4939
  • 수록기간
    2009~2025
  • 십진분류
    KDC 326 DDC 380

이 권호 내 다른 논문 / International Journal of Internet, Broadcasting and Communication Vol.17 No.3

    피인용수 : 0(자료제공 : 네이버학술정보)

    함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.

      페이지 저장