管理评论 ›› 2025, Vol. 37 ›› Issue (1): 229-242.

• 风险与应急管理 • 上一篇    

资源型城市产业转型风险预警模型构建与应用

熊志建1, 赵红1,2, 刘秀丽1,3   

  1. 1. 中国科学院大学经济与管理学院, 北京 100190;
    2. 中国科学院大学中丹学院, 北京 100049;
    3. 中国科学院数学与系统科学研究院, 北京 100190
  • 收稿日期:2022-10-13 发布日期:2025-01-18
  • 作者简介:熊志建,中国科学院大学经济与管理学院博士研究生,硕士生导师;赵红,中国科学院大学经济与管理学院教授,中国科学院大学中丹学院院长,博士生导师,博士;刘秀丽,中国科学院数学与系统科学研究院研究员,博士生导师,博士。

Construction and Application of Risk Early Warning Model for Industrial Transformation in Resource-based Cities

Xiong Zhijian1, Zhao Hong1,2, Liu Xiuli1,3   

  1. 1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    2. Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049;
    3. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190
  • Received:2022-10-13 Published:2025-01-18

摘要: 资源型城市产业转型升级对城市实现可持续发展至关重要。本文对其风险因素进行了识别与分析,界定为宏观风险和微观风险。前者主要包括政策、环境、市场以及社会风险,后者则涵盖时机、模式、人才以及资金风险等。在此基础上,从目标维、时间维、因素维三个维度创造性构建了资源型城市产业转型风险识别三维图。采用故障树分析法(FTA)对转型预警指标体系进行构建,兼顾完整性与最小化、可获取与准确度,共包含8个一级、20个二级以及35个三级指标。构建了转型预警模型,选定了7个样本城市,分别对它们进行了风险因素概率分析和影响量分析,计算出各城市转型风险(预警)值,提出了转型预警准则,并给出了转型建议。

关键词: 资源型城市, 产业转型, 风险预警

Abstract: Industrial transformation and upgrading is crucial for the sustainable development of resource-based cities. This paper identifies and analyzes the relevant risk factors, and categorizes them as macro risk and micro risk. The former mainly includes policy, environment, market and social risks, while the latter covers opportunities, models, talents and capital risks. On this basis, a three-dimensional map of risk identification for industrial transformation of resource-based cities is creatively constructed from three dimensions: target, time and factor. Fault tree analysis (FTA) is used to build the transformation early warning indicator system, which gives consideration to integrity and minimization, availability and accuracy, and includes 8 first level, 20 second level and 35 third level indicators. The transformation early warning model is constructed, seven sample cities are selected, and the analysis of their risk factor probability and influence quantity are carried out respectively. The transformation risk (early warning) values of each city are calculated, the transformation early warning criteria are proposed, and the transformation suggestions are given.

Key words: resource-based cities, industrial transformation, risk early warning