Estimation of Supply Chain Network Disruption of Companies Across the Country Affected by the Nankai Trough Earthquake Tsunami in Kochi City
Yoshiki Ogawa*1,, Yuki Akiyama*2, Muneta Yokomatsu*3,*4, Yoshihide Sekimoto*1, and Ryosuke Shibasaki*2
*1Institute of Industrial Science, The University of Tokyo
4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
*2Center for Spatial Information Science, The University of Tokyo, Chiba, Japan
*3Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan
*4Risk and Resilience Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
Using various types of big data on the Nankai Trough earthquake and tsunami that struck Kochi, we describe a method of simulating how economic damage to inter-enterprise transactions propagates through the supply chain and how subsequent recovery occurs. First, we enter the human losses and material damage caused by the earthquake and tsunami to estimate the material damage and labor capital loss of each enterprise based on the position information of employees. Next, we simulate the damage repercussions regarding production capacity over the entire supply chain through many tiers, and extract bottlenecks of company risk within the supply chain. It was found that bottleneck companies tend have a slow recovery rate as compared to other affected companies. They also had a tendency of being in the construction, manufacturing, wholesale, and service industry sectors, and small in scale.
-  T. Ono, “Role of private sectors and BCP in Japan,” Disaster Management and Private Sectors, Springer, pp. 135-148, 2015.
-  R. Wakasugi and A. Tanaka, “Recovery of the Supply Chain after the 2011 Mega-quake in Japan,” Millennial Asia, Vol.6, Issue 1, pp. 1-20, 2015.
-  Y. Sadahiro, “Errors in Areal Weighting Interpolation between Incompatible Zonal Systems,” Theory and applications of GIS, Vol.7, Issue 1, pp. 1-9, 1999.
-  Y. Yamamoto, Y. Akiyama, and R. Shibasaki, “Estimation of Inter-regional Money FlowProcess Using Inter-firm Transaction Big Data and People Flow Big Ddata,” CUPUM2017 Conf. Proc., CD-ROM, 2017.
-  M. Takahashi, “Mobile terminal and continuous movement detection method,” U.S. Patent Application, No.9, 255, 942, 2016.
-  T. Kashiyama, Y. Pang, and Y. Sekimoto, “Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas,” Transportation Research Part C: Emerging Technologies, Vol.85, pp. 249-267, 2017.
-  M. Asai, Y. Miyagawa, N. A. Idris, A. Muhari, and F. Imamura, “Coupled tsunami simulations based on a 2d shallow-water equation-based finite difference method and 3d incompressible smoothed particle hydrodynamics,” J. of Earthquake and Tsunami, Vol.10, No.5, 1640019, 2016.
-  A. Musa, T. Abe, T. Inoue, H. Hokari, Y. Murashima, Y. Kido, S. Date, S. Shimojo, S. Koshimura, and H. Kobayashi, “A Real-Time Tsunami Inundation Forecast System Using Vector Supercomputer SX-ACE,” J. Disaster Res., Vol.13, No.2, pp. 234-244, 2018.
-  Y. Akiyama and R. Shibasaki, “Transition Analysis of Regional Characteristics Using Building Geo Big Data and National Census Data Throughout Japan –Focusing on Compact City, Re-urbanization and Suburban Sprawl–,” Proc. of CUPUM 2015, Paper No.295, pp. 1-23, 2015.
-  F. Yamazaki and O. Murao, “Vulnerability functions for Japanese buildings based on damage data from the 1995 Kobe earthquake,” Implications of Recent Earthquakes on Seismic Risk, pp. 91-102, 2000.
-  S. Koshimura, T. Oie, H. Yanagisawa, and F. Imamura, “Developing fragility functions for tsunami damage estimation using numerical model and post-tsunami data from Banda Aceh, Indonesia,” Coastal Engineering J., Vol.51, No.03, pp. 243-273, 2009.
-  T. Oki and T. Osaragi, “Effects of Firefighting Activities Performed by Local Residents to Mitigate Fire Destruction Damage and Human Casualties in Large Earthquakes,” J. Disaster Res., Vol.13, No.2, pp. 272-280, 2018.
-  I. Kawashima, H. Sugita, and S. Kato, “Study on indirect economic damage caused by earthquake,” Report of the Public Works Research Institute, Vol.186, No.1, 1991.
-  M. Yokomatsu, Y. Akiyama, Y. Ogawa, and R. Shibasaki, “Numerical Analysis of Dynamic Planning Problems on Corporate Recovery Capital Investment Considering Various Disaster Scenarios,” Committee of Infrastructure Planning and Management Conf. Proc., CD-ROM, 2017.
-  K. Nakano and H. Tatano, “A Methodology for Consistent Measurement of Economic Losses Caused by Natural Hazards Taking Account of Mutual Relations between Industries,” Infrastructure Planning Review, Vol.25, No.1, pp. 255-266, 2008.
-  J. Tokui et al., “The Economic Impact of the Great East Japan Earthquake: Comparison with other disasters, supply chain disruptions, and electric power supply constraint,” RIETI Policy Discussion Paper Series, 12-P-004, 2012.
-  Risk Management Solutions (RMS), “Combines Real-time Reconnaissance with Risk Models to Estimate Katrina Losses,” 2005.
-  Congressional Budget Office (CBO), “TESTIMONY Macroeconomic and Budgetary Effects of Hurricanes Katrina and Rita,” 2005.
-  Bureau of Economic Analysis (BEA), “Damages and Insurance Settlement from the Third quarter Hurricanes,” 2005.
-  R. Wakasugi and A. Tanaka, “Determinants of the Reconstruction Period from the Great East Japan Earthquake: Evidence from manufacturing firms in Tohoku,” RIETI Discussion Paper Series, 13-J-002, 2013.
-  Y. Saito, “The Impact of the Great East Japan Earthquake on Companies in the Non-affected Areas: Structure of the inter-company network of supply chains and its implication,” RIETI Discussion Paper Series 12-J-020, 2012.
-  T. Kondo, “The effects of supply chain disruptions caused by the Great East Japan Earthquake on workers,” Japan and the World Economy, Vol.47, pp. 40-50, 2018.
-  Y. Ogawa, Y. Akiyama, and R. Shibasaki, “Development of Loss and Recovery Model of Corporate Transactions for Earthquake Disaster Based on the Great East Japan Earthquake and Tsunami,” CUPUM2017 Conf. Proc., CD-ROM, 2017.
-  S. Fukushima, H. Yashiro, and H. Yoshikawa, “Seismic risk analysis on business interruption time of supply chain system considering amount of supply,” J. Environ. Eng., AIJ, Vol.75, No.665, pp. 853-860, 2010.
-  K. J. Mizgier, M. P. Jüttner, and S. M. Wagner, “Bottleneck identification in supply chain networks,” Int. J. of Production Research, Vol.51, Issue 5, pp. 1477-1490, 2013.
-  Y. Ogawa, Y. Akiyama, G. Shinohara, R. Shibasaki, and Y. Sekimoto, “Estimation inter-firm transaction data between branch offices using head office transaction data,” Proc. of the 27th Annual Meeting of the Geographic Information Systems Conf., Geographical Information System Association, CD-ROM, 2018.
-  Y. Sekimoto, R. Shibasaki, H. Kanasugi, T. Usui, and Y. Shimazaki, “PFLOW: Reconstruction of people flow by recycling large-scale fragmentary social survey data,” IEEE Pervasive Computing, Vol.10, No.4, pp. 27-35, 2011.
-  Y. Akiyama, S. Ueyama, R. Shibasaki, and R. Adachi, “Event Detection Using Mobile Phone Mass GPS Data and Their Reliability Verification by MDSP/OLS Night light Image,” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.3, No.2, pp. 77-84, 2016.
-  Y. Todo, K. Nakazima, and P. Matous, “Supply Chain Networks Promote the Resilience of Firms to Natural Disasters: Lessons from the Great East Japan Earthquake,” RIETI Policy Discussion Paper Series, 13-P-006, 2013.
-  Cabinet Office of Japan, “Outline of damage damage assumption items and methods of building damage and human damage in the huge earthquake of the Nankai Trough,” http://www.bousai.go.jp/jishin/syuto/taisaku_wg/pdf/syuto_wg_siryo01.pdf, 2012 (in Japanese).
-  Y. Ogawa, T. Sato, Y. Akiyama, R. Shibasaki, and Y. Sekimoto, “Developing a Model for Estimating the Home Return of Evacuees Based on the 2011 Tohoku Earthquake Tsunami – Utilizing Mobile Phone GPS Big Data,” Advances and New Trends in Environmental Informatics, Springer, pp. 227-240, 2018.
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