中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (10): 31-39.doi: 10.16265/j.cnki.issn1003-3033.2022.10.1660

• 安全社会科学与安全管理 • 上一篇    下一篇

基于系统动力学的城市安全重点风险管控机制

王晓庆1,2,3(), 陈东4, 王安娜2,3, 钱城江5,**()   

  1. 1 南京财经大学 公共管理学院,江苏 南京 210023
    2 南京航空航天大学 经济与管理学院,江苏 南京 211106
    3 南京财经大学红山学院,江苏 南京 210003
    4 国家信息中心 大数据发展部,北京 100045
    5 南京南工应急科技有限公司,江苏 南京 210047
  • 收稿日期:2022-04-10 修回日期:2022-08-17 出版日期:2022-10-28 发布日期:2023-04-28
  • 通讯作者: 钱城江
  • 作者简介:

    王晓庆 (1981—),男,江苏如东人,博士研究生,高级工程师,主要从事数字经济与应急管理等方面研究。E-mail:

    陈东 工程师

    王安娜 讲师

  • 基金资助:
    江苏省高校哲学社会科学研究项目(2019SJA2097)

Research on key risk control mechanism of urban safety based on system dynamic

WANG Xiaoqing1,2,3(), CHEN Dong4, WANG Anna2,3, QIAN Chengjiang5,**()   

  1. 1 School of Public Administration, Nanjing University of Finance & Economics, Nanjing Jiangsu 210023, China
    2 College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing Jiangsu 211106, China
    3 Nanjing University of Finance & Economics Hongshan College, Nanjing Jiangsu 210003, China
    4 Big Data Development Department, State Information Center, Beijing 100045, China
    5 Nanjing NJTech Emergency Technology Co., Ltd., Nanjing Jiangsu 210047, China
  • Received:2022-04-10 Revised:2022-08-17 Online:2022-10-28 Published:2023-04-28
  • Contact: QIAN Chengjiang

摘要:

为明晰城市区域安全生产重点风险演变趋势,建立有效的风险管控机制,根据江苏省某地级市城区范围内实际调研结果,针对交通运输、建筑施工、商业场所3类重点行业领域特性,深入剖析存在的主要风险因素;运用系统动力学(SD)理论和方法,构建城市安全生产重点风险系统模型,并使用Vensim软件动态模拟城市区域安全风险值,结合调研数据、模拟结果,从3类重点行业实际风险角度,提出提升城市本质安全水平的对策。研究结果表明:城市区域安全生产重点风险演变趋势大致为缓慢降低→极速降低→趋于平缓;3类重点行业风险影响因素、风险总量、风险消除数量、风险消除速率、风险消除转折点等均因行业不同而有所差别。

关键词: 城市安全, 重点风险, 管控机制, 系统动力学(SD), 重点行业

Abstract:

In order to study evolution trend of key risks in urban regional work safety and establish an effective risk control mechanism, according to actual survey results in a prefecture-level city in Jiangsu Province, main risk factors in three key industries, namely transportation, construction and commercial places, were deeply analyzed in view of their field characteristics. Then, a system model of key risks in urban work safety was constructed by using SD theory and method, and risk value was dynamically simulated by adopting Vensim software. Finally, countermeasures to improve urban intrinsic safety were put forward from perspectives of actual risks of the three key industries based on survey data and simulation results. The results show that the evolution trend of key risks in urban work safety is roughly as slow decrease → extremely rapid decrease → gradual flattening out. Moreover, risk influencing factors, total risk, number of risk elimination, rate of risk elimination, and turning point of risk elimination of the three key industries are different due to different industries.

Key words: urban security, key risk, control mechanism, system dynamic (SD), key industries