产业网络灾害经济损失评估研究进展

doi:10.18306/dlkxjz.2018.03.004

摘要/Abstract

摘要：

开展产业网络灾害经济损失评估研究,是理解产业网络脆弱性和潜在风险,科学指导灾前风险防范及灾后恢复重建决策的关键环节。本文从产业网络中灾害扩散的角度,对其造成的经济损失类型及研究进展进行了系统梳理。结果表明,产业物理损失方面,主要通过建立灾害强度参数与厂房建筑、生产设备及存货等物理损失程度间的脆弱性曲线进行评估。受灾产业中断损失方面,应关注其组合投入要素物理受损情景下的生产能力损失程度(PCLR)。产业网络灾害波及损失方面,主要存在微观“企业供应链网络”和宏观“产业链网络”二种研究尺度。其中,前者以微观企业个体为基本粒度,利用复杂网络分析方法,模拟灾害依托企业供应关系扩散的空间过程及其造成的供应链中断损失;后者以聚合的产业部门或区域为基本粒度,利用投入产出(IO)、可计算一般均衡(CGE)等宏观经济计量模型,模拟灾害在产业部门或区域间的扩散过程及其造成的宏观区域经济损失。最后,从情景分析的视角,构建包括灾害事件场景、产业网络暴露、节点物理损失和中断损失、供应链网络中断损失、宏观产出损失于一体的多过程、多尺度经济损失集成评估体系,以综合模拟灾害损失在产业网络中的放大效应。

关键词: 产业网络, 灾害, 直接损失, 间接损失, 进展

Abstract:

Assessing the economic losses induced by disasters in complex industrial networks is fundamental for understanding the vulnerability and potential risks in industrial networks, and for making decisions on pre-disaster risk reduction and post-disaster reconstruction. From the perspective of disaster impact propagation in industrial networks, we systematically reviewed the types of disaster-induced economic losses and the remarkable research advances in recent years. The main method used in asset damage assessment is to establish the fragility curves between hazard intensity and damage degree of assets such as buildings, equipment, and inventory. For business interruption loss assessment, more research should be focused on production capacity loss rate (PCLR) of industrial sectors resulting from the physical damages of various input factors. Two distinctive analysis scales are often adopted for ripple loss assessment in industrial networks: micro-scale supply chain network and macro-scale industrial chain network. The former takes individual firms as basic units of analysis and utilizes complex network analysis to model the disaster impact spreading through inter-firm transactions and estimate the resulting supply chain disruption losses. In contrast, the latter considers industrial sectors or administrative regions as basic units and employs macro-scale econometric models, such as Input-Output (IO), Computable General Equilibrium (CGE), and so on, to simulate disaster impact propagation among industrial sectors or administrative regions, and evaluate the resulting gross output losses. Finally, from the perspective of scenario analysis, we proposed a multi-process, multi-scale integrated assessment methodology that combines hazard scenario, industrial network exposure, asset damages and business interruption losses at local nodes, supply chain disruption losses, and gross output losses, to comprehensively simulate the amplification effect of disasters in industrial networks.

Key words: industrial network, disaster, direct losses, indirect losses, research progress

李卫江, 温家洪, 李仙德. 产业网络灾害经济损失评估研究进展[J]. 地理科学进展, 2018, 37(3): 330-341.

Weijiang LI, Jiahong WEN, Xiande LI. Progress of research on economic loss assessment of disasters in industrial networks[J]. PROGRESS IN GEOGRAPHY, 2018, 37(3): 330-341.

图/表 2

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模型	国家	建立方式	损失形式	洪水强度参数	韧性因素	损失评估内容
HAZUS-MH (Scawthorn et al, 2006)	美国	灾损统计与工程模拟	损失率	水深	承灾体类型、尺寸	分为厂房建筑、生产设备、存货3个值
FLEMOcs (Kreibich et al, 2010)	德国	灾损统计	损失率	水深、浑浊度	承灾体类型、员工数量、防灾措施	分为厂房建筑、生产设备、存货3个值
Multicoloured Manual(Penning-Rowsell et al, 2005)	英国	灾损统计与工程模拟	损失绝对值	水深、持续时间	承灾体类型、提前预警时间	1个综合值