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People-centered early warning systems in China: A bibliometric analysis of policy documents.
Zhang, Xiaojun; Zhong, Qixi; Zhang, Rui; Zhang, Mengchen.
  • Zhang X; School of Economics and Management, Fuzhou University, China.
  • Zhong Q; School of Economics and Management, Fuzhou University, China.
  • Zhang R; School of Public Administration and Communication, Guilin University of Technology, China.
  • Zhang M; School of Marxism, China University of Geoscience, China.
Int J Disaster Risk Reduct ; 51: 101877, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-783273
ABSTRACT
People-Centered Early Warning Systems (PCEWSs) is thought to be low-cost but effective, however, existing studies fail to discuss the basic characteristics of PCEWSs, how a PCEWSs should be built, and the extensible applications of PCEWSs. This study aims for making a significant contribution to the literature through the analysis of the PCEWSs trajectory of and fundamental shifts in policy pertaining to PCEWSs in the disaster domain in China. By using bibliometric analysis of policy documents, this study presents a comprehensive review of China's PCEWS policy system from 1977 to March 2020, which focuses on various types of disasters. The characteristics of policies and the contributing factors of the policy changes in each of the four phases are discussed in depth. Four main tendencies of PCEWSs are identified. This study provides a quantitative foundation for understanding the dynamic policy changes in China's PCEWSs and certain experience includes the disaster characteristics that PCEWSs are suitable to get involved, the orientation that experience and technology should be combined and multi agent participation which calls for more emphasis may serve as a basis for exploring the potential pathways to the effective PCWSs in other countries and regions.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Int J Disaster Risk Reduct Year: 2020 Document Type: Article Affiliation country: J.ijdrr.2020.101877

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Int J Disaster Risk Reduct Year: 2020 Document Type: Article Affiliation country: J.ijdrr.2020.101877