Assessment of Supply Chain Vulnerability to Earthquake Risks
Jun Nakatani
The University of Tokyo
Jun Nakatani is Assistant Professor of Department of Urban Engineering at the University of Tokyo. His background is environmental system engineering. The scope of his research includes environmental impacts of supply chains and recycling systems. In particular, he has published a number of papers on plastic recycling system. LCA (life cycle assessment) is the core methodological tool in his studies, but MFA (material flow analysis), IOA (input–output analysis), multi-criteria optimization tools such as MILP (mixed-integer linear programming), and tools for consumer preference assessment such as CA (conjoint analysis) and CV (contingent valuation) are also applied to design environmentally-friendly and socially-acceptable recycling systems. Recently, he has expanded the scope of his research to analysis of supply chain risks. He has published in peer-reviewed journals such as Omega; Resources, Conservation and Recycling; Sustainability; Journal of Industrial Ecology; International Journal of Life Cycle Assessment; Waste Management; and Journal of Environmental Management. He also serves as vice-chairman of the 13th Biennial International Conference on EcoBalance, which will be held in October 2018.
Abstract
Owing to the growing number of risk factors that can be triggered by natural and manmade disasters, management of disruption risks in supply chains has become increasingly significant. The Great East Japan Earthquake in 2011... [ view full abstract ]
Owing to the growing number of risk factors that can be triggered by natural and manmade disasters, management of disruption risks in supply chains has become increasingly significant. The Great East Japan Earthquake in 2011 affected many production facilities and distribution networks, resulting in disruptions to both domestic and global supply chains. In some cases, a decrease in supplies of certain materials propagated through the supply chain and affected the availability of a variety of products and services. Thus, bottlenecks or vulnerability factors in supply chains could arise in the production sites that dominate the market for certain commodities, or in regions in which such production sites are concentrated. Through the interviews with Japanese manufacturers, however, it was revealed that bottlenecks in their supply chains became apparent only after supplies of parts and materials were damaged and/or disrupted. If raw materials vital in the supply chain and concurrently whose production sites are subject to disaster risk are comprehensively identified, it will help not only with supply chain risk management (SCRM) in raw material procurement by individual firms, but also in devising nation- and industry-wide SCRM strategies. So far, we have developed a graph theory-based methodology for assessing supply chain vulnerability to disruption risks by using the life cycle inventory (LCI) database as a data source for nationwide supply chains (Nakatani et al. under review). A supply chain structure, i.e., physical raw material-to-product links and overall chain, was modeled by a directed graph and its adjacency matrix, adapted from physical input–output data in the Inventory Database for Environmental Analysis (IDEA), the national-level LCI database of Japan. Then, commodities directly and/or indirectly linked to the focal product in the supply chain were identified by Boolean matrix calculations. In our previous study, vulnerability indicators for each commodity were determined on the basis of market concentration as measured by the Herfindahl–Hirschman Index (HHI) in terms of domestic production regions and import partners as a proxy for the extent of supply disruption risks. However, as the HHI concept essentially focuses only on the extent of monopoly/dispersion in the market, differences in frequency and magnitude of risk sources between regions or nations were beyond the scope of measurement of disruption risks. Therefore, the above vulnerability indicators based on the non-weighted HHI values were not necessarily indicative of the susceptibility to a specific risk event such as a catastrophic earthquake. To address this issue, we develop advanced measures of supply chain vulnerability to earthquake risks in this study. We calculate two differently-defined weighted HHI (wHHI) values that indicate the supply disruption risk stemming from earthquakes for Japanese domestically produced commodities: (1) the Earthquake Probability-wHHI, which is based on the district-scale earthquake probabilities in 30 years; (2) the Nankai Trough-wHHI, which is based on the district-scale predicted intensities in the great Nankai Trough earthquake. Then, we identify raw materials at high earthquake risk and products which directly and/or indirectly link to such raw materials according to the supply chain structure adapted from IDEA.
Authors
-
Jun Nakatani
(The University of Tokyo)
-
Hideaki Kurishima
(Shibaura Institute of Technology)
-
Kiyotaka Tahara
(National Institute of Advanced Industrial Science and Technology)
-
Yuki Kudoh
(National Institute of Advanced Industrial Science and Technology)
-
Ichiro Daigo
(The University of Tokyo)
-
Yuichi Moriguchi
(The University of Tokyo)
Topic Areas
• Complexity, resilience and sustainability , • Sustainability and resilience metrics , • Advances in methods (e.g., life cycle assessment, social impact assessment, resilience a
Session
MS-12 » Materials Criticality and Resilience 1 (11:45 - Monday, 26th June, Room I)
Presentation Files
The presenter has not uploaded any presentation files.