RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      KCI등재 SCI SCIE SCOPUS

      Analysis of risk propagation using the world trade network

      한글로보기

      https://www.riss.kr/link?id=A108300164

      • 0

        상세조회
      • 0

        다운로드
      서지정보 열기
      • 내보내기
      • 내책장담기
      • 공유하기
      • 오류접수

      부가정보

      다국어 초록 (Multilingual Abstract)

      An economic system is an exemplar of a complex system in which all agents interact simultaneously. Interactions between countries have generally been studied using the fow of resources across diverse trade networks, in which the degree of dependence b...

      An economic system is an exemplar of a complex system in which all agents interact simultaneously. Interactions between countries have generally been studied using the fow of resources across diverse trade networks, in which the degree of dependence between two countries is typically measured based on the trade volume. However, indirect infuences may not be immediately apparent. Herein, we compared a direct trade network to a trade network constructed using the personalized PageRank (PPR) encompassing indirect infuences. By analyzing the correlation of the gross domestic product (GDP) between countries, we discovered that the PPR trade network has greater explanatory power on the propagation of economic events than direct trade by analyzing the GDP correlation between countries. To further validate our observations, an agentbased model of the spreading economic crisis was implemented for the Russia–Ukraine war of 2022. The model also demonstrates that the PPR explains the actual impact more efectively than the direct trade network. Our research highlights the signifcance of indirect and long-range relationships, which have often been overlooked.

      더보기

      참고문헌 (Reference) 논문관계도

      1 F. Schweitzer, 325 : 422-, 2009

      2 J. M. Johnson, 43 : 40-, 2022

      3 P. Sieczka, 82 : 257-, 2011

      4 J. P. Jääskelä, 34 : 1295-, 2010

      5 D. Garlaschelli, 355 : 138-, 2005

      6 L. De Benedictis, 34 : 1417-, 2011

      7 J. Yun, 16 : 101291-, 2022

      8 C. Borio, 55 : 181-, 2020

      9 M. Xu, 63 : 825-, 2021

      10 O. B. Adekoya, 77 : 102728-, 2022

      1 F. Schweitzer, 325 : 422-, 2009

      2 J. M. Johnson, 43 : 40-, 2022

      3 P. Sieczka, 82 : 257-, 2011

      4 J. P. Jääskelä, 34 : 1295-, 2010

      5 D. Garlaschelli, 355 : 138-, 2005

      6 L. De Benedictis, 34 : 1417-, 2011

      7 J. Yun, 16 : 101291-, 2022

      8 C. Borio, 55 : 181-, 2020

      9 M. Xu, 63 : 825-, 2021

      10 O. B. Adekoya, 77 : 102728-, 2022

      11 V. A. Traag, 9 : 1-, 2019

      12 E. Bonabeau, 99 : 7280-, 2002

      13 T. H. Haveliwala, 15 : 784-, 2003

      14 V. D. Blondel, 2008 : P10008-, 2008

      15 E. A. Leicht, 100 : 118703-, 2008

      16 M. E. Newman, 69 : 026113-, 2004

      17 Y. Kim, 81 : 016103-, 2010

      18 D.J. Berndt, 10 : 359-370, 1994

      19 V. Plerou, 83 : 1471-, 1999

      20 M. J. Lee, 3 : 043136-, 2021

      21 F. Dörfler, 110 : 2005-, 2013

      22 D. M. Eidum, 30 : 033105-, 2020

      23 C. Otto, 83 : 232-, 2017

      24 W. Cho, "arXiv preprint arXiv: 2204. 12687"

      25 L. Page, "Tech. Rep" Stanford InfoLab 1999

      26 R. Monarch, "Available at SSRN 3080857"

      더보기

      동일학술지(권/호) 다른 논문

      분석정보

      View

      상세정보조회

      0

      Usage

      원문다운로드

      0

      대출신청

      0

      복사신청

      0

      EDDS신청

      0

      동일 주제 내 활용도 TOP

      더보기

      주제

      연도별 연구동향

      연도별 활용동향

      연관논문

      연구자 네트워크맵

      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

      이 자료와 함께 이용한 RISS 자료

      나만을 위한 추천자료

      해외이동버튼