Band 36 _ PRODUKTION UND ENERGIE Mariana Burkhardt IMPACTS OF NATURAL DISASTERS ON SUPPLY CHAIN peRFORMANCE mpacts of natural disasters on supply chain performance I . BURKHARDT M Mariana Burkhardt Impacts of natural disasters on supply chain performance PRODUKTION UND ENERGIE Karlsruher Institut für Technologie (KIT) Institut für Industriebetriebslehre und Industrielle Produktion Deutsch-Französisches Institut für Umweltforschung Band 36 Eine Übersicht aller bisher in dieser Schriftenreihe erschienenen Bände finden Sie am Ende des Buches. Impacts of natural disasters on supply chain performance by Mariana Burkhardt Karlsruher Institut für Technologie Institut für Industriebetriebslehre und industrielle Produktion u. Deutsch-Französisches Institut für Umweltforschung Impacts of natural disasters on supply chain performance Zur Erlangung des akademischen Grades eines Doktors der Wirt- schaftswissenschaften (Dr.rer.pol.) von der KIT-Fakultät für Wirt- schaftswissenschaften des Karlsruher Instituts für Technologie (KIT) genehmigte Dissertation von Dipl.-Kffr. Mariana Burkhardt Tag der mündlichen Prüfung: 6. Februar 2020 Hauptreferent: Prof. Dr. Frank Schultmann Korreferent: Prof. Dr. Kay Mitusch Impressum Karlsruher Institut für Technologie (KIT) KIT Scientific Publishing Straße am Forum 2 D-76131 Karlsruhe KIT Scientific Publishing is a registered trademark of Karlsruhe Institute of Technology. Reprint using the book cover is not allowed. www.ksp.kit.edu This document – excluding the cover, pictures and graphs – is licensed under a Creative Commons Attribution-Share Alike 4.0 International License (CC BY-SA 4.0): https://creativecommons.org/licenses/by-sa/4.0/deed.en The cover page is licensed under a Creative Commons Attribution-No Derivatives 4.0 International License (CC BY-ND 4.0): https://creativecommons.org/licenses/by-nd/4.0/deed.en Print on Demand 2021 – Gedruckt auf FSC-zertifiziertem Papier ISSN 2194-2404 ISBN 978-3-7315-1020-8 DOI 10.5445/KSP/1000105982 Impacts of natural disasters on supply chain performance Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr.rer.pol.) von der Fakultät für Wirtschaftswissenschaften, des Karlsruher Instituts für Technologie (KIT) genehmigte DISSERTATION von Dipl.-Kffr. Mariana Burkhardt geb. in Dresden Tag der mündlichen Prüfung: 06.02.2020 Hauptreferent: Prof. Dr. Frank Schultmann Korreferent: Prof. Dr. Kay Mitusch To Granny Acknowledgements This dissertation was written during my time as a research associate at the In- stitute for Industrial Production (IIP) at the Karlsruhe Institute of Technology (KIT) under supervision of Prof. Dr. Frank Schultmann. The motivation for this topic was based on my work for the EU project MOWE-IT, funded under the 7th Framework Programme. Later my research was embedded in CEDIM - The Center for Disaster Management and Risk Reduction Technology, espe- cially with the cooperation with the Institute of Economics (ECON), Chair of Network Economics of Prof. Dr. Kay Mitusch. First of all I want to thank Prof. Dr. Frank Schultmann for his supervision and the opportunity to conduct my research, as well as the many insights I got in many interesting research fields. I also thank my former colleagues, especially Heike, Christina and Frank for our common project work. A big thank you must go to Jan for his sporting support, motivation and friendship as well my many friends who accompanied me during the last years, especially: Ana, Alissa, Maren, Lea, Holger, Karin, Werner and Gerlinde. I also thank Kathrin - great to have somebody with the same dreams! Thank you to Franziska and Tomás too, for their support in completing this work! I also want to thank my family for their support, particularly my beloved grandma for inspiring me and for always being on and by my side. I love you! Last but not (at all) least I want to thank my husband Michael for his con- tributing remarks, long discussions and understanding - without him this PhD would not have been possible! Karlsruhe, July 2019 Mariana Burkhardt III Contents Acknowledgements .......................... III List of Figures ............................. IX List of Tables .............................. XI Acronyms ................................ XIII 1 Introduction ............................. 1 1.1 Motivation and objective . 1 1.2 Structure . 3 2 Supply chain vulnerability .................... 5 2.1 Risk, vulnerability and related definitions . 5 2.2 Reasons for increased supply chain vulnerability . 8 2.3 Classification of supply chain risks . 9 2.3.1 - in general . 9 2.3.2 - in accordance to external risks and hazards . 12 3 Natural hazards and disasters .................. 21 3.1 Difference between hazards and disasters . 21 3.2 Types of natural disasters . 22 3.2.1 Hydrological disasters . 24 3.2.2 Meteorological disasters . 26 3.2.3 Climatological disasters . 27 3.2.4 Geophysical disasters . 28 3.2.5 Extra-terrestrial disasters . 29 3.2.6 Biological disasters . 30 4 Impacts of natural disasters on supply chains ........ 33 4.1 Disturbances vs. disruptions . 34 V Contents 4.2 Transport vs. location . 37 4.3 Performance impact and recovery . 38 4.3.1 Supply chain characteristics that influence disaster im- pact and recovery . 39 4.3.2 Recovery times and deviation in delivery times . 40 4.4 Risk assessment approaches in the context of disasters . 43 4.4.1 Supply chain risk assessment . 43 4.4.2 Country risk assessment . 48 4.5 Résumé . 53 5 Vulnerability of places - i.e. location .............. 55 5.1 Concept . 55 5.2 Vulnerability indicators . 58 5.2.1 Prerequisites for indicators . 58 5.2.2 Indicators . 60 6 Impact assessment ........................ 73 6.1 Methodology . 73 6.2 Step 1 - Identification business closure times . 76 6.3 Step 2 - Identification vulnerability indicators . 79 6.4 Step 3 - Relation between business closure times and vulnera- bility factors . 81 6.5 Step 4 - Frequency of natural disaster . 84 6.6 Step 5 - Compound distribution . 88 7 Application SCperformND approach .............. 91 7.1 Vulnerability indicators with highest relevance to explain de- livery time deviations . 91 7.2 Case study - United States of America . 104 8 Summary and conclusion .................... 111 8.1 Summary . 111 8.2 Critical appraisal and directions for future research . 114 A Appendix .............................. 117 A.1 Reasons for increased supply chain vulnerability . 118 A.2 Supply chain risk classification - sources . 122 A.3 Factors in social vulnerability . 130 VI Contents A.4 Factors in economic vulnerability . 145 A.5 Factors in physical vulnerability . 160 A.6 Factors in environmental vulnerability . 172 A.7 Natural disaster types - definitions . 187 A.8 Business closure times . 194 A.9 Vulnerability indicator USA 1989 . 200 A.10 Sources vulnerability indicator . 202 References ............................... 203 VII List of Figures 2.1 Risk map external events . 6 2.2 Reasons for increased supply chain vulnerability . 8 2.3 Internal supply chain risks . 15 2.4 External supply chain risks . 16 2.5 External supply chain risks - not related to specific procurement markets . 18 3.1 Types of natural disasters . 23 3.2 Loss events worldwide . 25 4.1 Economic impacts of disasters . 33 4.2 Disruption vs. disturbance . 35 4.3 Supply chain vulnerability - transport vs. location . 38 4.4 Performance impact of procurement risks . 41 4.5 Performance impact of logistics risks . 42 5.1 Vulnerability of places . 56 5.2 Interaction of vulnerability factors . 58 5.3 Social vulnerability factors: percentage of authors referring to different characteristics . 61 5.4 Economic vulnerability factors: percentage of authors referring to different characteristics . 64 5.5 Physical vulnerability factors: percentage of authors referring to different characteristics . 68 5.6 Environmental vulnerability factors: percentage of authors refer- ring to different characteristics . 69 6.1 Vulnerability factor categories . 75 6.2 Visualisation step 1 . 77 6.3 Mean closure time per event-ID . 78 6.4 Linear interpolation for missing data points . 82 IX List of Figures 6.5 Output of multiple linear regression . 84 6.6 Python script to create a frequency plot . 87 6.7 Empirical distribution of differences between successive events . 87 6.8 Compound distribution . 88 6.9 Accumulated claim process . 89 6.10 Loss distribution and Value at risk . 90 7.1 Regression results case study . 97 7.2 Model validation . 100 7.3 Comparison MCT from literature and SCperformND . 101 7.5 Sensitivity analysis Forest area (% of land area) . 102 7.4 Sensitivity analysis rate of birth (per 1000 population) . 102 7.6 Sensitivity analysis Roadways in km . 103 7.7 Sensitivity analysis population living in areas where elevation is below 5 meters (% of total population) . 103 7.8 Probability mass function for N(u) . 106 7.9 Probability mass function for L(t) . 107 X List of Tables 2.1 Classification of supply chain risks . 10 2.2 Classification of supply chain risks in accordance to external risks 13 3.1 Classification of disasters by duration and length of forewarning . 21 3.2 Hydrological disasters . 25 3.3 Meteorological disasters . 26 3.4 Climatological disasters . 27 3.5 Geophysical disasters . 28 3.6 Extra-terrestrial disasters . 30 3.7 Biological disasters . 31 4.1 Supply chain risk assessment approaches . 44 4.2 Country risk assessment approaches . 50 5.1 Factors of social vulnerability . 62 5.2 Factors of economic vulnerability . 65 5.3 Factors of physical vulnerability . 68 5.4 Factors of environmental vulnerability . 71 6.1 Factors of vulnerability and explaining indicators . 80 6.2 Natural disaster types considered for the different regions . 85 7.1 Business closure times . 91 7.2 Natural disaster events . 92 7.3 Extract of data for regression . 95 7.4 Regression coefficients . 96 7.5 Model validation . 98 7.6 Indicators USA . 105 7.7 VaR comparison for sample regions . 108 XI List of Tables A.1 Reasons for increased supply chain vulnerability . 119 A.2 Supply chain risk classification - sources . 123 A.3 Factors social vulnerability . 131 A.4 Factors economic vulnerability . 146 A.5 Factors physical vulnerability . 161 A.6 Factors environmental vulnerability . 173 A.7 Natural disaster types - definitions .