The Dynamics of Risk: Changing Technologies and Collective Action in Seismic Events 9780691186023

Table of contents :
CONTENTS
FIGURES
TABLES
PREFACE
1. Redefining Risk on a Global Scale
2. Risk in Complex Systems
3. Assessing Risk in Complex Systems: DATA, METHODS, AND MEASURE MEN T
4. Risk in Practice
5. Toward an Auto-adaptive System: The 2013 Lushan County, China, Earthquake
6. Operative Adaptive Systems: 1999 Duzce, Turkey; 2009 Padang, Indonesia; 2011 Tohoku, Japan; and 2015 Nepal Response and Recovery Systems
7. Emergent Adaptive Systems: 1999 Marmara, Turkey; 1999 Chi Chi, Taiwan; 2005 Pakistan; and 2008 Wenchuan, China, Earthquake Response Systems
8. Nonadaptive Systems: 2001 Bhuj, Gujarat, India, Earthquake; 2004 Sumatra, Indonesia, Earthquake/Tsunami; and 2010 Haïti Earthquake Response Systems
9. Evolving Patterns of System Response
10. The Logic of Resilience
Appendix I: Tables of Transactions by Classes of Adaptation
Appendix II: Sources of Electronic Data, 2013 Lushan Earthquake
NOTES
REFERENCES
INDEX

Citation preview

TH E DY NAM I C S O F R I S K

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Princeton Studies in Complexity Series Editors Simon A. Levin (Princeton University) Steven H. Strogatz (Cornell University) Robert Axelrod, The Complexity of Cooperation: Agent-­Based Models of Competition and Collaboration Lars-­Erik Cederman, Emergent Actors in World Politics: How States and Nations Develop and Dissolve Peter S. Albin, Barriers and Bounds to Rationality: Essays on Economic Complexity and Dynamics in Interactive Systems Scott Camazine, Jean-­Louis Deneubourg, Nigel R. Franks, James Sneyd, Guy Theraulaz, and Eric Bonabeau, Self-­Organization in Biological Systems Sorin Solomon, Microscopic Representation of Complex Systems Peter Turchin, Historical Dynamics: Why States Rise and Fall Andreas Wagner, Robustness and Evolvability in Living Systems J. Stephen Lansing, Perfect Order: Recognizing Complexity in Bali Mark Newman, Albert-­László Barabási, and Duncan J. Watts, The Structure and Dynamics of Networks Joshua M. Epstein, Generative Social Science: Studies in Agent-­Based Computational Modeling John H. Miller and Scott E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life Marten Scheffer, Critical Transitions in Nature and Society Michael Laver and Ernest Sergenti, Party Competition: An Agent-­Based Model Joshua M. Epstein, Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science Louise K. Comfort, The Dynamics of Risk: Changing Technologies and Collective Action in Seismic Events

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The Dynamics of Risk Changing Technologies and Collective Action in Seismic Events Louise K. Comfort

PRINCETON UNIVE RSIT Y PRESS P R I N C E TO N A N D OX F O R D

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Copyright © 2019 by Princeton University Press Published by Princeton University Press 41 William Street, Princeton, New Jersey 08540 6 Oxford Street, Woodstock, Oxfordshire OX20 1TR press.princeton.edu All Rights Reserved LCCN 2019934398 ISBN 978-­0-­691-­16536-­3 ISBN (pbk.) 978-­0-­691-­16537-­0 British Library Cataloging-­in-­Publication Data is available Editorial: Eric Crahan and Pamela Weidman Production Editorial: Kathleen Cioffi Cover Design: Pamela L. Schnitter Cover Credit: Nigel Spiers / Alamy Production: Erin Suydam Publicity: Tayler Lord, Nathalie Levine, and Julia Hall This book has been composed in Adobe Text Pro and Gotham Printed on acid-­free paper. ∞ Printed in the United States of America 10 9 8 7 6 5 4 3 2 1

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To the memory of my mother, Valborg Oline Fjøslien Kloos, whose love of learning, humane values, and curiosity about the world profoundly shaped this inquiry

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CONTENTS

List of Figures  ix List of Tables  xi Preface xv 1

Redefining Risk on a Global Scale  1

2

Risk in Complex Systems  22

3

Assessing Risk in Complex Systems: Data, Methods, and Measurement  44

4

Risk in Practice  59

5

Toward an Auto-­adaptive System: The 2013 Lushan County, China, Earthquake  76

6

Operative Adaptive Systems: 1999 Duzce, Turkey; 2009 Padang, Indonesia; 2011 Tohoku, Japan; and 2015 Nepal Response and Recovery Systems  92

7

Emergent Adaptive Systems: 1999 Marmara, Turkey; 1999 Chi Chi, Taiwan; 2005 Pakistan; and 2008 Wenchuan, China, Earthquake Response Systems  134

8

Nonadaptive Systems: 2001 Bhuj, Gujarat, India, Earthquake; 2004 Sumatra, Indonesia, Earthquake/Tsunami; and 2010 Haïti Earthquake Response Systems  176

9

Evolving Patterns of System Response  208

10

The Logic of Resilience  235 Appendix I: Tables of Transactions by Classes of Adaptation  253 Appendix II: Sources of Electronic Data, 2013 Lushan Earthquake  279 Notes 281 References 287 Index 299 vii

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FIGURES

1.1 CASoS engineering design process

10

5.1 Map, Lushan County earthquake, April 20, 2013

79

5.2 Rate of change in 2013 Lushan County, China, response system

85

5.3 Top 20 organizations in 2013 Lushan County, China, response system, with icons sized by betweenness values

86

6.1 Maps, 1999 Duzce, Turkey, earthquake; 2009 Padang, Indonesia, earthquake 93 6.2 Maps, Tohoku, Japan, earthquake, 2011; Nepal earthquake, 2015

94

6.3 Rate of change in 1999 Duzce, Turkey, response system

101

6.4 Top 20 organizations in 1999 Duzce, Turkey, response system, with icons sized by betweenness centrality

102

6.5 Rate of change in the 2009 Padang, Indonesia, response and recovery system

109

6.6 Top 20 organizations engaged in 2009 Padang response system, ranked by betweenness centrality, with jurisdiction and funding sector 110 6.7 Rate of change in 2011 Tohoku, Japan, response and recovery system 118 6.8 Top 20 organizations in 2011 Tohoku, Japan, response and recovery system, ranked by betweenness centrality

119

6.9 Rate of change in 2015 Nepal response system, April 25–­May 16, 2015

127

6.10 Network diagram of top 20 organizations, 2015 Nepal response system, ranked by betweenness centrality

128

7.1 Maps, Marmara, Turkey, earthquake, August 17, 1999; Chi Chi, Taiwan, September 21, 1999

136

7.2 Maps, Pakistan earthquake, 2005; Wenchuan, China, earthquake, 2008

137

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x LI S T O F Fi g u r e s

7.3 Rate of change in 1999 Marmara, Turkey, response system, August 18–September 7, 1999

144

7.4 Top 20 organizations in 1999 Marmara response system, ordered by betweenness centrality

146

7.5 Rate of change in 1999 Chi Chi, Taiwan, response system September 21–October 9, 1999

152

7.6 Top 20 organizations, 1999 Chi Chi, Taiwan, response system, ranked by betweenness centrality, with jurisdiction and funding sector 153 7.7 Rate of change in the 2005 Pakistan response system, October 9–­29, 2005

160

7.8 Top 20 organizations in 2005 Pakistan earthquake response system, ranked by betweenness centrality, with jurisdiction and funding sector

161

7.9 Rate of change in 2008 Wenchuan response system, May 12–­June 1, 2008

169

7.10 Top 20 organizations participating in 2008 Wenchuan, China, response system, icons sized by betweenness centrality, showing jurisdiction and funding sector

171

8.1 Maps, Bhuj, Gujarat, India, earthquake, 2001; Sumatra, Indonesia, earthquake 2004

180

8.2 Map, Haïti earthquake, 2010

181

8.3 Rate of change in 2001 Gujarat response system, January 26, 2001–­February 15, 2001

184

8.4 Network diagram of top 20 organizations, Gujarat response system, ranked by betweenness centrality

186

8.5 Rate of change in 2004 Sumatra, Indonesia, response system, December 26, 2004–January 16, 2005

194

8.6 Network diagram of top 20 organizations in Sumatra, Indonesia, system, ranked by betweenness centrality

195

8.7 Rate of change in 2010 Haïti response system, January 12– February 3, 2010

202

8.8 Network diagram of top 20 organizations in 2010 Haïti response system, ranked by betweenness centrality

203

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TABLES

4.1 Assessment Indicators for Earthquake Response Systems

64

4.2 Preliminary Classification of 12 Earthquake Response Systems Based on Technical, Organizational, and Cultural Dimensions, 1999–­2015

67

4.3 Classes of Sociotechnical Adaptation by Earthquake Response Systems, 1999–­2015

68

4.4 Preliminary Characteristics of Response System Tending toward Auto-­adaptation in Lushan, China, 2013

69

4.5 Preliminary Characteristics of Operative Adaptive Systems

71

4.6 Preliminary Characteristics of Emergent Adaptive Systems

72

4.7 Preliminary Characteristics of Nonadaptive Systems

73

5.1 Frequency Distribution of Organizations Participating in the 2013 Lushan County, China, Response System, by Jurisdiction and Funding Sector

83

5.2 Top 20 Organizations Participating in the 2013 Lushan County, China, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

87

6.1 Frequency Distribution of Organizations Participating in the 1999 Duzce, Turkey, Response System, by Jurisdiction and Funding Sector

100

6.2 Top 20 Organizations Participating in 1999 Duzce, Turkey, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

103

6.3 Frequency Distribution of Organizations Engaged in 2009 Padang Earthquake Response System by Jurisdiction, Funding Sector 108 6.4 Top 20 Organizations Participating in 2009 Padang, Indonesia, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

111

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xii LI S T O F Ta b l e s

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6.5 Frequency Distribution of Organizations Participating in the 2011 Tohoku Earthquake, Tsunami, and Nuclear Reactor Breach Response System, by Jurisdiction and Funding Sector

117

6.6 Top 20 Organizations in 2011 Tohoku, Japan, Response and Recovery System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

120

6.7 Frequency Distribution of Organizational Response System, April–­May 2015, Nepal Earthquakes, by Jurisdiction and Funding Sector

126

6.8 Top 20 Organizations in 2015 Nepal Earthquakes Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

129

7.1 Frequency Distribution of Organizations in the 1999 Marmara, Turkey, Response System, by Jurisdiction and Funding Sector

142

7.2 Top 20 Organizations in 1999 Marmara, Turkey, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

147

7.3 Frequency Distribution of Organizations in the 1999 Chi Chi, Taiwan, Response System, by Jurisdiction and Funding Sector

151

7.4 Top 20 Organizations, 1999 Chi Chi, Taiwan, Earthquake Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding, and Degree Centrality

154

7.5 Frequency Distribution of Organizations in 2005 Pakistan Response System, by Jurisdiction and Funding Sector

159

7.6 Top 20 Organizations Participating in 2005 Pakistan Response System, Ranked by Betweenness Centrality, with Funding Source, Jurisdiction, and Degree Centrality

162

7.7 Frequency Distribution of Organizations Engaged in Response Operations, 2008 Wenchuan, China, Earthquake, by Jurisdiction and Funding Sector

168

7.8 Top 20 Organizations in 2008 Wenchuan Earthquake Response System, Ranked by Betweenness Centrality, with Funding Source, Jurisdiction, and Degree Centrality

172

8.1 Frequency Distribution of Organizations Engaged in Disaster Operations by Jurisdiction and Funding Sector, 2001 Bhuj, Gujarat, Earthquake Response System

183

8.2 Top 20 Organizations in Gujarat Response System, Ranked by Betweenness Centrality and Reporting Funding Sector, Jurisdiction, and Node Degree Centrality

187

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LI S T O F Ta b le s xiii

8.3 Frequency Distribution of Organizations Engaged in the 2004 Sumatra, Indonesia, Response System, by Jurisdiction and Funding Sector

193

8.4 Top 20 Organizations in 2004 Sumatra, Indonesia, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Sector, and Degree Centrality

196

8.5 Frequency Distribution of Organizations Participating in 2010 Haïti Response Systems, by Jurisdiction and Funding Sector

201

8.6 Top 20 Organizations Participating in 2010 Haïti Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Sector, and Degree Centrality

204

9.1 External/Internal Index for Earthquake Response System Moving toward Auto-­adaptation

215

9.2 Comparison of Observed E/I Index Values with Permuted E/I Index Values for Lushan Earthquake Response System Moving toward Auto-­adaptation

216

9.3 External/Internal Indexes for Operative Adaptive Earthquake Response Systems

218

9.4 Comparison of Observed E/I Values with Permuted E/I Values for Operative Adaptive Systems, Significance (P) Values

221

9.5 External/Internal Indexes for Emergent Adaptive Earthquake Response Systems

224

9.6 Comparison of Observed E/I Values with Permuted E/I Values for Emergent Adaptive Systems, Significance (P) Values

227

9.7 External/Internal (E/I) Indexes for Nonadaptive Systems

229

9.8 Comparison of Observed E/I Values with Permuted E/I Values for Nonadaptive Systems, Significance (P) Values

232

10.1 Comparison of Overall E/I Values for Network Moving toward an Auto-­adaptive System

238

10.2 Comparison of Overall E/I values for Whole Networks, Operative Adaptive Systems

239

10.3 Comparison of Overall E/I Values for Whole Networks, Emergent Adaptive Systems

239

10.4 Comparison of Overall E/I Values for the Whole Network, Nonadaptive Systems

240

I.5.1 Types of Transactions Reported in 2013 Lushan County, China, Response System, by Jurisdiction and Funding Sector

254

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xiv LI S T O F Ta b le s

I.6.1 Types of Transactions Reported in 1999 Duzce, Turkey, Response System, by Jurisdiction and Funding Sector

256

I.6.2 Types of Transactions Reported in 2009 Padang, Indonesia, Response System, by Jurisdiction and Funding Sector

258

I.6.3 Types of Transactions Reported in 2011 Tohoku, Japan, Response and Recovery System, by Jurisdiction and Funding Sector 260 I.6.4 Types of Transactions Reported in 2015 Nepal Response and Recovery System, by Jurisdiction and Funding Sector

262

I.7.1 Types of Transactions Reported in August 17, 1999, Marmara, Turkey, Response System, by Jurisdiction and Funding Sector

264

I.7.2 Types of Transactions Reported in 1999 Chi Chi, Taiwan, Response System, by Jurisdiction and Funding Sector

266

I.7.3 Types of Transactions Reported in 2005 Pakistan Earthquake Response System, by Jurisdiction and Funding Sector

268

I.7.4 Types of Transactions Reported in 2008 Wenchuan, China, Response System, by Jurisdiction and Funding Sector

270

I.8.1 Types of Transactions Reported in 2001 Bhuj, Gujarat, India, Response System, by Jurisdiction and Funding Sector

272

I.8.2 Types of Transactions Reported in 2004 Sumatra, Indonesia, Response System, by Jurisdiction and Funding Sector

274

I.8.3 Types of Transactions Reported in 2010 Haïti Earthquake, by Jurisdiction and Funding Sector

276

II.1 Sources of Electronic Data for Network Analysis, Lushan Earthquake, April 20, 2013

279

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PREFACE

Like the San Andreas fault, which runs more than 800 miles along the coast of California, seismic risk is hidden from view, and largely from conscious thought of the nearly 40 million residents of the state. The risk is ever present, although the actual ruptures occur every 40 to 60 years for moderate earthquakes, 90 to 150 years for major events. Through these quiet periods, communities develop, grow, thrive, and expand, putting more people, buildings, infrastructure, organizations, and institutions at risk, should a major earthquake occur. The challenge is how to maintain sufficient awareness of risk to inform the design, construction, and maintenance of communities despite the knowledge that a catastrophic event could shatter the interdependent web of social, economic, and engineered systems that support society. Living with risk requires a framework for managing contingencies and imagining alternative approaches to seemingly permanent structures. In a search to understand how decision makers frame actions to cope with uncertain events, especially large-­scale, potentially destructive events that have regional, national, and international consequences, I undertook this study nearly twenty years ago. Examining community response to actual earthquake events as they happened, I sought to understand the characteristics of decision making by people at different levels of responsibility, capacity, and insight into this complex, dynamic problem. Over the years, many people have assisted me in this journey: practicing emergency managers, scholars, students, and community residents in twelve different countries in local, national, and international organizations. Their names are too numerous to mention, but in each country, several persons were extraordinarily thoughtful and supportive of this effort. In Turkey, Ruşen Keleş, Polat Gulkan, Husein Guler, and Yeşim Sungu guided me through the Turkish laws, policies, and context of seismic risk in the country. Suleyman Celik and Sitki Corbacioglu were thoughtful interpreters of the changing response to disaster as earthquakes continued to threaten Turkey in repeated seismic events of 1999 and later. In Taiwan, Jay Shih, Chung Yuang Jan, Kai Hong Fang, and Wen Jiun Wang provided thoughtful guidance, insight, and importantly, translation in interviewing local personnel and analyzing local news reports following the 1999 Chi Chi earthquake. In Gujarat, India, I am

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xvi P r e fac e

grateful to Haresh Shah for organizing an unusual reconnaissance study that included senior and junior researchers in the social sciences, engineering, and geography. I am especially indebted to V. Thiruppugazh, deputy director of the Gujarat State Disaster Management Authority, Gandhinagar, in 2001, for his thoughtful insight into the uses of information technology that India was beginning to adopt for disaster management. In Indonesia, I am indebted to my longtime colleagues and friends, Harkunti Rahayu, Bandung Institute of Technology, and Febrin Ismail, Andalas University, Padang, for continuing collaboration since the 2004 Sumatran earthquake and tsunami, through the 2009 Padang earthquake and continuing efforts to find credible methods of informing residents of Indonesia’s coastal cities regarding methods of self-­ organization and resilience to confront seismic risk. In Pakistan, several practicing managers made significant contributions to this study, among them Abrar Ismael, Zafar Shah, and Dr. Mohammad Daud Khan, CHEF International, as well as Nauman Afridi, who assisted me with coding news reports from the Pakistani newspaper Dawn, Islamabad, regarding the Pakistan earthquake in 2005. I thank Brent Woodworth for his field observations in both Gujarat and Pakistan, which enriched my understanding of the context of disaster operations in both countries. In China, Haibo Zhang, Nanjing University, facilitated my first visit to the Wenchuan region in 2008. Since that time we have worked together as colleagues and friends, seeking to understand the changing disaster management system as successive earthquakes disrupted communities in China. Xing Tong, distinguished professor at Nanjing University, facilitated the scholarly exchange in the study of disaster management between Nanjing University and the University of Pittsburgh, and Hong­ yun Zhou, Zhongnan University of Economics and Law, Wuhan, graciously provided updates from local newspapers on the Lushan earthquake, 2013. In Haïti, my thanks go to Jacques Gabriel, then minister of public works in Haïti as well as dean, School of Engineering, L’Université d’Etat d’Haïti; Evenson Calixte, dean of science, engineering, and architecture, Quisqueya University; and Dr. Yolène V. Surena, faculty of medicine, UEH. Importantly, I thank my former students Leonard Huggins, Ted Serrant, Michael Siciliano, Steve Scheinert, Rebecca Jeudin, Maria Escorcia, Sebastian Gasquet, and Edgar Largaespada, all of whom traveled with me to Haïti on research trips and engaged with Haïtian students at UEH and Quisqueya Universities. In Japan, my warmest thanks and appreciation go to Professor Yasuo Tanaka, Kobe University, for his assistance and support over the years, and especially in facilitating arrangements for a field study following the 2011 Tohoku, Japan, triple disasters. My deep appreciation goes to Aya Okada, former doctoral student, research assistant, and now professor at Kanazawa University, Japan. Dr. Okada served as translator, analyst, and essential guide to Japan following the Tohoku disasters and also participated in the research and analysis for the 2010 Haïti earthquake. In Nepal, warm thanks and sincere appreciation go to

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P r e fac e xvii

James Joshi, my colleague and coinvestigator on the Nepal reconnaissance trip, and especially to Prabin Joshi and the Joshi family for facilitating our study in Nepal and their gracious hospitality on our visits. Collecting the data for this book was one major task; still another was coding and analyzing the data collected over a period of 16 years, all of which needed to be checked, recoded, and validated, using advanced methods of network analysis in R. For this major task, undertaken largely during the spring and summer of 2017, I was fortunate to have a very talented set of advanced doctoral students at the Center for Disaster Management who assisted me with this painstaking, careful work. My warmest thanks and appreciation go to Jee Eun Song, Seunghyun Lee, Lucy Gillespie, Jay Rickabaugh, Nauman Afridi, and Farhod Yuldashev. Fuli Ai graciously produced the maps for the 12 earthquakes in GIS format, and Mark Dunn assisted with database management in organizing and managing the data sets, greatly facilitating the research process. Karen Cuenco provided a careful expert review of the network analysis findings to validate the results. Importantly, I owe a major debt of gratitude to Todd R. LaPorte, University of California, Berkeley, and Friedemann Wenzel, University of Karlsruhe, Germany, for reading the entire manuscript, chapter by chapter, and providing thoughtful and welcome comments that helped to sharpen the argument and clarify points that I had overlooked. Warm thanks to my longtime friend and colleague Sidney Verba, who offered encouragement, thoughtful advice, and wise insights into the comparative contexts of decision making in the disaster-­ stricken communities. My deep appreciation goes to the anonymous reviewers of the manuscript who offered substantive comments that greatly improved the final manuscript. Eric Crahan, as editor at Princeton University Press, provided consistent, firm, but gracious guidance to bring the manuscript successfully to publication. Throughout this process, I thank John T. S. Keeler, dean, Graduate School of Public and International Affairs, University of Pittsburgh, for providing research support through the Center for Disaster Management and a collegial working environment that enabled me to complete this years-­long project. Throughout this period of nearly twenty years, my family has provided unwavering support, perceptive questions, patience, and much needed laughter to guide me through times that were heartbreaking, challenging, sad, but ultimately hopeful in dealing with wrenchingly painful accounts of human suffering, courage, and determination. To my son, Nathaniel, my daughter, Honore, and their families, I give my deepest love and appreciation. This book would not have been possible without their steadfast encouragement, lively questions, occasional skepticism, and, most of all, willingness to listen. S

Louise Comfort Oakland, California October 15, 2018

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TH E DY NAM I C S O F R I S K

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1 Redefining Risk on a Global Scale

Seismic Risk as a Global Policy Problem “Nepal will rise again,” T-­shirts worn by young Nepalis proudly proclaimed, after the Dharahara Tower in the center of Kathmandu, Nepal, collapsed in the April 25, 2015, earthquake. The city reeled from the severe shock late Saturday morning. Search and rescue teams in hard hats and field gear scoured buildings, checking for persons trapped inside. Families huddled around open cooking fires, fearful of returning to houses still trembling from aftershocks. Groups of young volunteers opened their laptops to create lists of neighbors who were safe and those who were missing. Neighbors looked after neighbors, sharing what food they had and comforting one another in collective grief. As the community began to count its losses and build a web of support for one another, questions regarding human capacity to assess and reduce risk reverberated around the world. Earthquakes are a known risk in Nepal, but dust from the shattered Dharahara Tower belied the ability of the city’s decision makers to curb the sudden, destructive force of the earthquake and its massive disruption of the region’s daily operations. The historic tower, built in 1832 and designated as a UNESCO World Heritage site, was the symbol of the city, connecting its history over two centuries to a modernizing Nepal that engaged in significant programs of disaster risk assessment and reduction, supported by inter­ national agencies and humanitarian assistance (NSET 2015). At risk was not only the structure of the tower, but the design of policies and programs to maintain a complex net of public safety actions stretching across local, 1

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2 C H A P TER 1

district, national, and international agencies against movements of the earth beyond human control. Seismic risk presents an even greater challenge in developed countries, not only for the nations in which they occur, but also for disruption of the interconnected global trade, transportation, communications, and financial networks that sustain the world’s growing populations. Twelve of the 15 most costly natural disasters in the years 1985–2017 have been due to seismic events.1 Collectively, these events have resulted in estimated losses of 732,102 lives, dead or missing, and over $1 trillion in direct economic costs, with almost certainly larger indirect costs due to relocation, anguish, and pain. While two of the largest seismic events over the last 30 years have occurred in Japan, a major earthquake in San Francisco or Los Angeles would generate catastrophic social and economic costs, not just for the United States, but for the global society (USGS 2016a).2 Although this book focuses on seismic events, the findings apply broadly to other natural hazards—floods, hurricanes, wildfires, and rising sea levels— as well as human-­made disasters—nuclear meltdowns, large-­scale terrorist attacks, hazardous materials releases. The technical systems that support the functions of an expanding global society are dependent for design, construction, operations, and maintenance on governance systems that are straining under demands from increasing populations, changing climate systems, and vulnerable social groups. Managing risk in changing environments is a classic challenge for decision makers in public, private, and nonprofit organizations. Twenty years ago, in Shared Risk: Complex Systems in Seismic Response (1999), I examined disaster response systems following 11 earthquakes in nine different countries from 1985 to 1995. In that study, I proposed an interacting set of indicators for assessing response operations across organizations, sectors, and countries. The analysis demonstrated how insights from complex adaptive systems could improve response operations to seismic events. In the intervening two decades, mounting evidence has reinforced the core concept that catastrophic risks represent the intersection of increasingly interconnected systems and require a complexity framework for analysis and understanding. The rapid change in wireless and electronic technologies has transformed digital operating systems in travel, finance, communications, education, commerce, and in electrical power, water, and gas distribution systems, to mention only obvious areas of societal performance. When a major disruptive event such as an earthquake occurs, the consequences cascade through interdependent systems, escalating the impact across organizations, sectors, and even national boundaries with unimagined costs. For example, the Mw = 9.0 earthquake on March 11, 2011, in Tohoku, Japan, triggered a massive tsunami that flooded the genera-

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R e d e fi n i n g Ris k o n a Glo ba l Sc a le  3

tors of the Fukushima Daiichi nuclear reactor, causing radioactive contamination, electrical power shortages, and economic disruption that affected all 43 prefectures in Japan, with an estimated cost of 200% GDP for Japan, the third-­ largest economy in the world. In this study, I build on the initial analysis presented in Shared Risk but offer a deeper, enriched refinement of the earlier concepts of complex adaptive systems, examining an additional 12 response systems following earthquakes from 1999 to 2015. Further, I use methods of network analysis and process tracing to assess the interactions among actors, documenting the degrees of interconnectedness and adaptation observed in the response systems. This set of field studies extends the initial set of 11 earthquakes in 9 countries to a total of 23 earthquake response systems in 14 countries over a 30-­year period as the basis for informed judgment on treating seismic response operations as complex adaptive systems. The challenge of mitigating risk deepens as decision makers discover the interconnectedness of the systems they manage and the unexpected consequences of decisions made to reduce risk in one set of circumstances that actually increase risk for different groups of population under different conditions. In specific contexts, risk entails a set of dynamic, interacting conditions involving multiple actors, changing technologies, conflicting assumptions, different scales of operation, and the need for timely, informed, collective action to mobilize a coherent response. Risk is the probability that harm will occur (Beck 1992), and consequently, decisions made to reduce risk include judgments of uncertainty and trade-­offs of present versus future costs. These estimates are made daily but cumulatively create a culture of risk that calibrates acceptance against avoidance. Decisions regarding risk are especially challenging when risk is shared, that is, when adverse conditions affect all members of a community indiscriminately (Comfort 1999a). Learning to recognize, assess, and manage risk on a global scale is a fundamental challenge of the 21st century. Seismic risk exemplifies this global policy problem in unique ways. Seismic risk creates the potential for catastrophic disruption and loss to the world’s population, as 36 nations of the world are exposed to significant risk from earthquakes, landslides, and related hazards of tsunamis and soil instability. Further, risk escalates as communities exposed to seismic hazards increase in size and scale. For example, the megacities of Tokyo, Istanbul, Jakarta, Mumbai, Mexico City, and Los Angeles are each exposed to significant seismic risk. Their respective metropolitan regions now encompass tens of millions of residents and serve as centers of government, commerce, communications, finance, and transportation in their respective nations. The interdependence of these operational networks in a globally connected world means that if any

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4 C H A P TER 1

one of these megacities experiences a major earthquake, the losses would not only affect the immediate population, but also seriously disrupt vital transactions on a worldwide scale. While interdependence among global infrastructure and organizational systems creates cumulative risk for the global metasystem, this same interdependence creates opportunities for the redesign of interconnected operations to reduce expanding risk. Decisions made in one set of operations create the basis for adaptation in other stages and other locations, enhancing innovative capacity and reducing the overall risk to the global system. Capturing the potential to transform risk into opportunity for redesign of functional systems and infrastructure into more resilient forms represents a positive goal of the risk dynamic. For example, recognizing the potential of landslides generated by earthquakes to disrupt the roads and bridges of rural Nepal creates opportunity to redesign and rebuild these vital roads in ways that strengthen the transportation network nationally. The transformation of risk to constructive redesign of operational systems, however, is not trivial. Prior efforts to analyze and model disaster risk have not resolved the inherent issues of complexity, uncertainty, size, and scale (Wildavsky 1988; Beck 1992; Bruneau et al. 2003; Blaikie et al. 2004; Cutter et al. 2008). Ulrich Beck raised the fundamental issue of the impact of technology on society, and the consequent risks that technology engendered in transforming an industrialized society into a modern one. Left unanswered in his profound analysis is how institutions and organizations could adapt to newly generated risks in constructive ways. Aaron Wildavsky framed the issues of cost versus control in changing environments, acknowledging that the “search for safety” was essentially a process of selecting risks that one could recognize and had the capacity to address. Other risks were either ignored or delayed, given scarcity of resources and public attention. One relied on “resilience,” or anticipation of potential threats, often viewed in individual terms, to adapt available resources to meet unexpected threats. Bruneau and his colleagues at the Multidisciplinary Center for Earthquake Engineering Research (MCEER) at the State University of New York, Buffalo, developed a promising model of resilience that sought to counter risk through the interaction of four basic conditions in any area exposed to risk: robustness, redundancy, resourcefulness, and rapidity (Bruneau et al. 2003). Widely accepted in engineering and considered in social science disciplines, this model has been largely applied in engineering contexts and the design of individual buildings, rather than to the wider context of societal risk. Blaikie and colleagues (2004) document the vulnerability of populations exposed to natural hazards and the extent to which this risk, if not acknowledged, may unwittingly be increased by policies of responsible institutions. Susan Cutter and her colleagues (2008) added the central consideration of geographic location

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to the recognition and assessment of risk, acknowledging the interaction between the physical characteristics of a specific community and the types of risks to which its residents were exposed. While each of these analytical approaches to characterize and analyze risk contributes a useful perspective to understanding the fundamental problem of managing potential threats to communities, none captures the potential for inquiry to change the means of coping with risk in practice. The five perspectives cited above also share a broad focus on technology as an agent that generates risk in an increasingly complex world but differs in application to individual, organizational, and institutional capacities to reduce risk in changing environments. An initial characterization of organized social complexity framed by Todd LaPorte (1975) and his colleagues identified the problem of sociotechnical systems and the critical role of information in managing the interaction between technical systems and the organizations that design, implement, and operate them. Importantly, major shifts in information and communication technologies (ICT) create the possibility to redefine decision processes for large-­scale, sociotechnical, complex systems of systems. While advances in ICT had been building for several decades, they reached a critical point of mass distribution, access, and use in the mid-­1990s. The advent of desktop computers and widespread adoption of cell phone networks fundamentally altered the way in which information was collected, organized, stored, and distributed within and among organizations and institutions. Gone were the manila file folders and green filing cabinets, with weeks of effort required to catalogue records of past performance. Gone, as well, was the ability to hide negative information in obscure reports that were buried in an avalanche of paper. Instead, personal computers made access to information readily available, and communication via internet made sharing information over wide distances and time zones easily possible. These technical changes in managing information and communication within large-­scale, sociotechnical systems enabled a different form of near-­ real-­time communication and exchange of information within and between organizations and institutions. Although the technology is neutral, the organizational processes through which information and communication flow may either enhance or inhibit the capacity for information exchange within and among systems of systems. Earlier analyses of risk that focused on the technical vulnerabilities of systems missed the inseparable connection to vulnerabilities in the organizational systems that operate the technologies. Consequently, large-­scale, sociotechnical systems that manage the critical infrastructure and communications exchange on which the global society operates constitute fundamentally interdependent systems of systems, prone to both error and innovation. Such systems operate on multiple scales with networks that span continents and

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require collaboration across institutional and organizational boundaries that respect different laws, policies, and cultural norms. For example, airline networks that routinely link cities across the globe illustrate both extraordinary capacity in the ability of this interconnected transportation system to enable people to move easily over long distances, but also the fragility of the whole system, if one hub breaks down, delaying or canceling flights in hundreds of other routes simultaneously. Each boundary that is crossed offers an opportunity for further expansion of performance or vulnerability that limits functionality of the system of systems. This study focuses on the extent to which ICT is used effectively to redesign organizations and decision strategies to manage seismic and other continuing risks in more productive, innovative ways, transforming potential risk into resilience in practice. Seismic risk represents the classic dilemma of low probability/high consequence events that has stymied risk analysts for decades (Petak and Atkisson 1982; Kartez 1984; Kunreuther 2010). Given its global reach and the long-­term consequences of managing a potentially severe but intermittent hazard, seismic risk verifies uncertainty as the core issue driving complex adaptive systems. Shared Risk as Public Risk Shared risk represents a distinct challenge, as it threatens potential harm to all persons exposed to hazards that affect the whole community, whether they have contributed to the threat or not (Comfort 1999a, 3). For example, individuals exposed to risk from earthquakes, hurricanes, tornadoes, drought, or tsunamis may have separate insurance plans for protection of their lives and property but still incur major loss if the bridges are out, electrical power is cut off, ATMs, gasoline pumps, and cash registers are not working, and cell towers are down. These interdependent systems are essential for continuity of operations for the whole community. Consequently, shared risk is public risk, and managing public risk is an essential function of governments at multijurisdictional levels of operation. The task confronting governments seeking to manage public risk cannot be achieved by standard means of organizing administrative action. This task, rather, involves assessing known versus unknown risk and, in doing so, acknowledging the limits of science, cognition, and technology to inform decision processes. The problem of managing risk quickly moves from a linear strategy of identifying a sequence of actions that lead to an expected outcome—check all switches that will shut down an electrical system—to recognition that nonlinear interactions among system components drive actual outcomes in unexpected ways—a sudden summer thunderstorm floods the open roof of an electrical transmission station and cuts off electrical power to

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three major hospitals linked through a shared electrical supply, threatening critical medical procedures.3 The interdependent systems characteristic of shared risk exhibit patterns of interaction that are fundamentally nonlinear and reveal different patterns of performance at different levels of operation, simultaneously (Roe and Schulman 2016). In an earthquake, any infrastructure system underground is likely to break: electrical lines, gas lines, water mains, sewage distribution systems, communication cables. In many metropolitan regions, critical infrastructure systems are bundled in the same trenches, increasing the risk of multiple disruptions. For example, in the 1995 Hanshin earthquake, the gas mains ruptured, igniting fires in multiple wards in the city of Kobe. Simultaneously, the water mains ruptured, limiting the capacity of the Kobe fire department to suppress the fires. The escalation of the fires created a secondary disaster for the city, as flames spread from building to building, debris blocked the streets, and emergency vehicles and personnel struggled to rescue residents trapped in collapsed buildings. The traumatic events revealed two levels of disruption occurring simultaneously: rupture of the technical systems that spread destruction in the city, and failure of the organizational systems to function in the degraded disaster environment. Interdependent infrastructure systems, designed for efficiency under normal operations, efficiently spread danger under the severe shock of the earthquake (Comfort 1999a). There is an observable pattern of cascading failure and lack of knowledge, as interdependent sociotechnical systems, stretched beyond their cognitive limits, make successive mistakes and veer toward mutual dysfunction In Shared Risk (Comfort 1999a, 8–9), I identified eight concepts that characterize nonlinear response to shared risk. These eight concepts merit review, as they reveal the dynamic interaction among components that generates the emergence of new forms of public action in anticipation of, or in response to, known risk to the community. The concepts have been further reinforced by later researchers. The more difficult task is to assess “unknown risk,” given the classic problem of cognition in that humans “do not know what they don’t know.” The eight concepts, restated briefly, are as follows: 1. Sensitive dependence on initial conditions sets the context for system development (Prigogine and Stengers 1984; Kaufmann 1993); 2. Random events create stochastic patterns of interaction among components of the system (Gell-­Mann 1994); 3. Effects of random events are irreversible (Prigogine and Stengers 1984); 4. Iterative patterns of communication and coordination transmit information and energy among actors and groups and function as mechanisms of adaptation and coordination (feedback loops)

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within the system (Nicolis and Prigogine 1989; Glass, Brown, et al. 2011); 5. Constraints within the community create dependencies among actors for time and resources within the system (Arthur 2009); 6. Self-­organization among actors within the system changes the dominant orientation and performance of the system (Castells 2009); 7. Cumulative patterns of selection in a system lead to unpredictable results (Axelrod and Cohen 1999; Arthur 2009; Dubey et al. 2014); 8. Self-­organizing patterns of behavior to mobilize resources and action seek to achieve the same goal in different contexts (Peitgen, Jurgens, and Saupe 1992). While the earlier characterization of nonlinear systems captures the profile of systemic change, it does not articulate clearly the dual dynamic that is observed between knowledge and action in complex systems. As knowledge increases, uncertainty decreases, and individuals, organizations, and groups move more readily to action. Timely, informed decisions made at one site in a system’s interdependent operations create the basis for informed decisions at subsequent, interacting sites, triggering a virtuous cycle. Conversely, as knowledge decreases, uncertainty increases, and uninformed actions lead to cumulative instances of failure that reach a threshold point where the entire system may fail. Self-­organization implies error correction, allowing informed adaptation to changing conditions in the operational environment (Doyle 1979; Smith 2008a). Knowledgeable decisions then accumulate throughout the system, lessening uncertainty and enabling the whole system to adapt its performance to avoid a perceived threat or lessen its impact, should one occur. It is this dual dynamic between increasing failure under threat and rapid adaptation to sustain or improve performance under changing conditions that marks the capacity of decision makers to manage risk in practice. Distinctive to this conception of complex systems is the role of information as it flows through the system. Complex adaptive systems differ from traditional forms of organized complexity in that interaction among the components defines the system, not the structure (LaPorte 1975; Arthur 2009, 2015). Timely, valid information activates collective cognition and action in interactive systems (Argyris and Schön 1978; Argyris 1993), but information alone proves to be an uncertain instrument in the overall task of managing risk. It is not sufficient to recognize risk as it is increasing; rather, it is the link from cognition to action that lessens potential danger (Comfort 2007b). The degree of known risk varies with human ability to monitor, measure, and interpret threats to public safety in relation to the resources available to recognize and

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reduce them. For large-­scale, sociotechnical systems, for example, a multistate electrical grid, the ability to collect, aggregate, analyze, and distribute relevant data regarding the operation of the system is a major task, warranting intensive concentration and focus on the continuing performance of the system (Roe and Schulman 2008). The task is necessarily interdisciplinary, interorganizational, and interjurisdictional. The physical, social, technical, and organizational criteria for assessing the status of complex sociotechnical systems demand a fundamentally different approach, a systems perspective that includes recognition of the cultural context in which a potential threat is occurring. Evidence from 12 additional studies of earthquake response systems document the observation that risk cannot be adequately understood without framing the context in which extreme events occur as complex adaptive systems of systems, acknowledging the interactive, interdependent characteristics of multiple actors engaged in dynamic, nonlinear processes that form in response (Glass, Ames, et al. 2011). Unraveling Complexity: Interacting Dimensions of Time, Space, Scale, and Energy The interacting dimensions of time, space, scale, and energy that characterize large-­scale, sociotechnical systems have challenged researchers from many disciplines. Three approaches from this rich body of work are particularly relevant to the underlying question of transforming risk into resilience in practice. First, a team of interdisciplinary researchers at Sandia National Laboratories initiated a research framework, Complex Adaptive Systems of Systems (CASoS) engineering, to address the interaction between emerging threats and the capacity for communities to respond effectively to them (Glass, Brown, et al. 2011; Brown et al. 2013). This framework seeks to integrate systematic engineering methods of identifying performance measures that characterize a system, define factors that influence the system, and create a conceptual model that connects performance measures to factors influencing the system. This conceptual model is redefined as a mathematical model that can be tested computationally with quantitative measures taken from actual field conditions. The computational model, tested against data from an actual field environment, allows evaluation of simulated performance to assess whether the proposed model could work in practice. At each stage of this interrelated process of inquiry, information flows from one set of tasks to the next, and feedback loops at each set of tasks provide review and revision among the participants to keep the process of inquiry grounded in practice, but open to review and redesign. Figure 1.1 illustrates the CASoS process (Glass, Ames, et al. 2011) in application to the dynamic problem of building community resilience to natural

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Defining sociotechnical system goals

Designing and testing solutions

Actualizing integrated solution to achieve system goals

Problem definition Define metrics, policies, components

Test conceptual model for achievability

Define possible composite solutions

Design conceptual model

Model definition

Design solutions Design quantitative metrics, policies, solutions (conceptual model) Compare performance of solutions under uncertainty

Fit conceptual models to context Field solution Characterize performance of models

Test solutions

Monitor attainment

FIGURE 1.1 . CASoS engineering design process, adapted from Glass, Ames, et al. (2011), 383.

hazards. In a possible scenario for managing seismic risk, a group of emergency planners might begin to define the potential impact of a major earthquake on a metropolitan region, for example, the Hayward fault in the San Francisco Bay Area of California.4 Such an effort represents the first loop in the CASoS model. Urban planners would define the metrics for such an impact and call on other experts to complete the scenario. Seismologists would estimate the probability of seismic movement. Demographers would calculate estimates of population in the threatened region. Transportation engineers would assess the impact of a major earthquake on the freeways, rail systems, and airports of the region; lifeline engineers would calculate likely downtime in disruption of electrical, water, wastewater, and gas distribution systems. Other experts would add knowledge of distinct organizational systems that would be affected: schools, hospitals, businesses, households. Each set of decisions is based on details for the operation of a single system, for example, electrical power, but from the overall perspective of the impact of loss of power on the operation of the whole metropolitan region. To continue operations effectively, the whole region needs to calculate the impact of the loss of power on other major lifeline systems and depends on feedback from the com-

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ponent systems to estimate its capacity to continue operations as an inter­ dependent system of systems. Moving to the second loop in the CASoS model, the planning group would devise potential strategies for maintaining continuity of operations, given an earthquake of a certain magnitude and depth, and calculate the range of costs and consequences for the metropolitan region. These steps would fit the scenario to the actual resources and constraints of the communities at risk, identifying measures that would reveal strength or weakness of the planned solution in practice. Building on explicit measures identified in the design and testing cycle, the planning group would move to the third CASoS loop and implement an integrated prototype in an actual field environment to test its performance. At each stage of the developing scenario, the model would be reviewed by participants in the process, updated, and adjusted to provide a realistic estimate of the likely costs, consequences, and types of interaction among the multiple organizations, agencies, and actors that would be generated by a major earthquake in the San Francisco Bay Area. While such scenarios are hypothetical, they provide a framework for tracing the interdependencies among actors and a basis for planning exercises to test decision-­making processes and preparedness plans on a regional scale. The scenario captures ­conceptually the flow of information between scales of operation, but the dimensions of time, energy, and space need to be configured in the actual implementation of a field study. The decision process evolves continuously, as interactions among the subsystems adapt to one another and change the environment in which they are operating, precipitating fresh adaptations in the whole system of systems. Implementation in different contexts may vary, but the method allows visual comparison of results under different constraints of time, space, and energy. Second, the marked shift in information technologies in the mid-­1990s brought the possibility of redefining the interconnections between organizational and technical systems, but the actual design and implementation of sociotechnical structures remains a continuing process of inquiry, experimentation, and reassessment. Sensors that collect data on the status of the environment—engineered, physical, social, and biological—bring a closer interconnection between computational machines and their human counterparts, but the integration, aggregation, analysis, and representation of those data to support collective decision making require understanding of the social context. The development of cognitive machines (Nobre, Tobias, and Walker 2009) and “machine learning techniques” offer technical means to assist managers seeking to address large-­scale problems that exceed limited human capacity for problem solving (Simon 1997). Nobre and colleagues (2009) extend the concept of decision support systems for individuals and small groups to collective

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processes for organizations and communities by incorporating machines directly into the problem-­solving process. For example, Japan has implemented a system of real-­time dissemination of data from its extensive seismic network to all households, businesses, and organizations. This extensive network transmits graphically to television screens in every connected household the location, magnitude, depth, and time of seismic tremors as these events occur. Coupled with public education regarding the interpretation of these results, this program is using technology to engage Japanese citizens in calibrating their actions to mitigate seismic hazards based on real-­time information (Comfort and Okada 2013). The technical means for creating a large-­scale, collective problem-­solving space supported by cognitive machines and real-­time sensing are doubtless available today. More problematic are the social and emotional skills required to use such spaces constructively for collective problem solving (Fligstein and McAdam 2012; Bauman 2006). The shift from knowledge to action is often framed in terms of personal values and social connections. If one’s immediate family, friends, and community are at risk, the incentives to act increase. Although this insight is observable in practice, there is little analytical evidence to support it as a premise for organizational design. One means to strengthen the empathetic and social skills needed for collective problem solving is the use of visual analytics that represent different types of information in different contexts to inform decision making under different degrees of stress, loss, uncertainty, and capacity. Such a vision extends the requirement for coordination to the management of machines that can support informed interaction among large numbers of people in multiple locations to address global collective action problems, such as reduction in infectious diseases or greenhouse gas emissions. Creating a large-­scale, collective problem-­solving space supported by cognitive machines extends the capacity of human communities to design innovative adaptations in the macro system, reducing risk and increasing resilience. Visual representation of these adaptations enhances rapid comprehension of the complex interactions that are involved in collective problem solving (Alford 2009; Nicholson and Schmorrow 2013). Third, changes in the technical decision support infrastructure must be accompanied by changes in the organizational and policy processes through which information flows to drive action. Each complex system consists of multiple agents that are interacting to some degree with one another and their environment (Perrow 2007). The degree of interdependence or dependence among the organizational and computational agents engaged in operations to maintain a CASoS under uncertainty shapes the performance of the system and its vulnerability to failure in environments exposed to risk (Perrow 2007). For example, the extent to which the local fire department depends on the local water department to maintain sufficient water pressure to ensure ade-

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quate distribution to the multiple hydrants in the city constrains the fire department’s capacity to fight fires. Further, the extent to which the local water department depends on electrical power generated by a private utility company to pump water to the hydrants further limits the fire department’s capacity to suppress fires. If a dual dependency triggers failure in a third system, a cascade of failure may ripple across all related systems in the community in catastrophic failure (Roe and Schulman 2016). The vulnerability of organizational systems that conduct basic response operations in a region exposed to risk cannot be calculated separately from the technical systems that support action but rather must be based on careful estimates of the degree of interdependence or dependence across the entire sociotechnical system that provides urgently needed services to a stricken region. The challenge is to identify and model dynamic, temporally changing, and adapting interactions among physical, engineered, and sociotechnical systems that occur during hazard emergence and response as a complex adaptive system of systems (Miller and Page 2007). The CASoS in practice enhances resiliency and enables communities to manage risk of hazards within existing resource and time constraints. For example, a computational model of information flowing through the sociotechnical infrastructure characterized in the Haywired scenario for the San Francisco Bay Area would identify the interconnections that activate the multiple organizations and jurisdictions in self-­ organizing response to minimize risk from an actual earthquake in the region, while also revealing the likely points of breakdown under different degrees of stress in the system of systems. COMPLEX ADAPTIVE SYSTEMS OF SYSTEMS IN PRACTICE

The test of theory is whether it works in practice. The test of practice is whether actions taken can be repeated in a consistent, coherent manner in different contexts and time frames. The puzzle for complex adaptive systems is that, by definition, these systems are not likely to be replicated exactly in different times and places. The task lies in creating a sufficiently common base of knowledge to support broad public action that is timely, informed, and sufficiently flexible to allow adaptation to local contexts. This means creating the capacity for collective cognition of risk but acknowledging multiple perspectives and options for local action on specific local problems. This task is particularly difficult, as it involves recognizing and interpreting scattered signals of risk across different scales of operation involving multiple subunits of a complex, sociotechnical system to detect a coherent pattern of risk for the whole system. For example, a swarm of small seismic movements in the proximity of a major metropolitan region may not indicate danger, viewed independently.

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But add to that pattern a heavy increase in traffic on an aging bridge in the area, and the risk grows. Further, if the bridge crosses a body of water that has had significant development on local landfill areas near its shores, the potential for subsidence increases. None of these risks, separately, may constitute a serious threat to the community. However, should a major earthquake strike, the interaction among them could result in a major catastrophe for the metropolitan region. DUAL ROLE OF TECHNOLOGY IN COMPLEX ADAPTIVE SYSTEMS

In this environment of scattered, intermittent, often weak signals of risk at different locations and under different conditions, technology can provide valuable assistance in monitoring and measuring risk (Weick 1995; Nicholson and Schmorrow 2013). For example, sensors developed to detect ground motion, or bridge stability, or changes in water tables in shoreline construction areas can provide systematic records of related change in the likely impact of seismic movement on the engineered infrastructure of a metropolitan region, with ensuing consequences for the economic, social, and political functions of the region. But data from the separate sets of sensors need to be integrated, analyzed, and represented clearly to present a profile of risk for the whole community. That profile of risk, presented to decision makers of public, private, and nonprofit organizations, needs to be matched against a complementary profile of the capacity of the community to respond to each separate risk. Each set of decision makers will need to take requisite action to minimize collective risk. The comparison of validated measures of risk against actual assessments of capacity and resources within the community would provide decision makers with an informed basis to develop a coherent strategy for risk reduction in the region. Information technology, thus, plays a dual role in complex adaptive systems. It supports the collection and analysis of data regarding the actual state of risk in a community, as well as enables the search and exchange of information among individual, organizational, and institutional actors that produce a deeper understanding of changing risk and capacity for adaptive collective action to reduce risk for the larger community. In doing so, it serves as the collective memory of risks encountered and managed for the region. In large-­scale, complex, interdependent operating environments, sociotechnical systems emerge simultaneously as instruments of inquiry—data collection, monitoring, storage, and data transmission—and products of sociotechnical change, as managers of public, private, and nonprofit institutions invest in the design, implementation, and maintenance of these systems. In the context of risk, the widespread adoption of technical measures has in-

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creased the awareness and range of diverse types of knowledge that affect decisions regarding risk assessment, but also enhanced the capacity of individuals, organizations, and institutions to make more informed decisions regarding the allocation of scarce time, attention, and resources to reduce that risk. This dual role for well-­functioning sociotechnical systems captures the interplay in dynamic processes of information search and exchange that drive the escalation and de-­escalation of risk. Redefining the Role of Information in Complex Policy Environments As the technology through which information flows has changed, the function that information performs in complex policy environments has also changed. Earlier theories of information defined it as a directed process involving five different components: sender → transmitter → signal → receiver → destination, with the added distraction of noise that might disrupt the signal (Shannon 1948). Considered seminal at the time, Shannon’s theory acknowledged that information is a process that operates through interacting human and technical systems. A sender, usually human, uses a transmitter, usually technical, to send a signal, a distinct message, to a receiver, technical or human, to reach an intended destination, usually human. The distraction of noise represents the larger environment in which this distinct information process is operating. A second concept of directed information flow focused on the interaction between humans and machines in processing information as a means of control over communications but includes the important concept of feedback that alters the initial information flow (Wiener 1948/1961). Both theories represent early versions of sociotechnical systems that embedded technical operations into social communications processes. An updated, innovative perspective viewed the integration of technical structure and social process in communications as enabling the flexibility and adaptability of large-­scale, sociotechnical systems (Smith 2008a). Information flows not only through technical channels of communication, but also through organizational and cultural pathways that are receptive to the content of the message that is being transmitted and the form in which the content is presented. Consequently, if the human receptors do not comprehend the message, there is no communication (Luhmann 1995). Both technical and organizational channels have limits in the capacity to transmit and absorb new information (Smith 2008a). These limits place constraints on the overall profile of information that can be exchanged in any given event. During the 2011 Tohoku earthquake, the Japan Meteorological Agency ( JMA) used the existing scientific model, Method of Splitting Tsunami (MOST), of tsunami detection to estimate whether a tsunami wave would

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occur, and if so, what the height and timing of the wave would be. The MOST model essentially matches the profile of the earthquake that has just occurred in location, magnitude, and depth against a database of all recorded earthquakes to determine if there is a previous earthquake with a similar profile that has generated a tsunami (Titov and González 1997). On March 11, 2011, the JMA ran the model immediately and predicted a tsunami wave, first of 3–5 meters, then updated the prediction to 7–9 meters. Given this news, the residents of the town of Taro on the Iwate Prefecture coast assumed they were safe behind their seawall of 10 meters. The model was still running when the first tsunami wave crashed ashore on the towns of Miyagi and Iwate Prefectures at 15 meters and over, with some waves reaching heights of 30 to 40 meters. The current technology for tsunami detection was overwhelmed by the actual occurrence of a tsunami wave; the organizational systems that relied on this technology also failed in terms of providing accurate information to the residents of the coastal communities. Losses from failure of this sociotechnical system are engraved in social memory. Yet insights gained from this tragic failure in the 2011 Tohoku disasters are not lost. They become part of the collective memory of the event and spur the discovery of new channels for estimating the probability of tsunami generation and generating new means of communication of collective risk. Col­ lective memory, rather, advances a fresh perspective on entropy as a characteristic of social knowledge. Entropy is not simply dissipation of energy as assumed by physicists and chemists (Boltzmann 1886/1974; Carnot 1824/ 1960), when understood in social terms. Rather, it is a waning of social attention, given the limits of human cognitive capacity to hold multiple, often conflicting, types of information in a public problem-­solving space simultaneously (Smith 2008a). Information, once created, is not lost; it simply recedes from the social agenda for action (Kingdon 2003). The task for a learning society is to reactivate relevant stored knowledge via new channels of information and types of information exchange for constructive application to an immediate problem. In complex adaptive systems, the interaction between technology and humans is viewed from an overall systems perspective. Information is shaped by the channels through which it flows, but in the process, the content, volume, and speed of information flow shape the structure of the channels. Information can flow only where a channel exists, so if there are no cell towers in the desert, there is no access to cell phone communication. But if there are cell towers and an internet connection, access to social media will likely increase and drive the demand for constructing more cell towers, more types of social media—Twitter, Facebook, Instagram, Weibo—that enable communication among collective groups. The power of this interaction lies in the capacity of technology to construct new channels of communication, and the capacity of

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social organizations to learn and adapt their behavior in response. The technical devices alter in fundamental ways patterns of information search and exchange among their respective users in social organizations that previously had limited access to information from outside their immediate community. Considered in this dual role, it is the relationship between information and technology that generates the social energy that drives complex adaptive systems (Smith 2008a), as the communication process is not only reciprocal between two people or organizations—sender and receiver—but it is multiway, with a much broader audience of people/organizations/actors who are listening, watching, observing, and reacting to what has become a public conversation, intended or not. The fact that communication is public means that control over the interpretation of meaning intended by the sender is essentially lost. Information may be interpreted to have multiple meanings, repeated and extended in ways that may be inconsistent with the sender’s intent. Considering information as a generative force, Smith (2008a) focused on the limits of the sociotechnical system through which information is flowing to reorder and reorganize itself. This insight is especially critical in understanding why, in some social systems, information is available, accessible, and engenders action, but in others, it is neither understood nor accepted as a basis for action, individual or collective. The concept of limits on the capacity for information flow through organizational processes as well as technical structure provides an effective measure to track the performance of a complex, adaptive, sociotechnical system. Counting the presence or absence of cell phone towers or computers ­provides a measurable indicator of how much information can flow to which locations under what time frames. Viewed from a systems perspective, the technical transmitters of information define the physical constraints on communication through large-­scale, complex systems of systems, while the organizational receivers of information face social constraints of trust, knowledge, and understanding. It is the interaction between the technical structure through which information flows and the social organization that generates, receives, interprets, and acts on information that creates the capacity for large-­ scale, sociotechnical systems to both generate and mitigate risk. Information both shapes, and is shaped by, the interacting system of actors, units, organizations, technologies, and context in a continuously evolving, adaptive process (Smith 2008a). Framing Risk as a Continuing Exploration Risk, framed as a continuing exploration of the dynamics between knowledge and action, can be used as a constructive process to assess system performance in balancing available resources against demands for public goods in their

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communities. To do so, however, policy makers are influenced by the initial conditions in which their process of risk management begins. Four types of initial conditions shape the interaction within and among components in complex adaptive systems of systems that determine the capacity of a community to cope with risk. These conditions, stated in general terms, can be used to characterize any risk situation and therefore allow comparison of different types of risk at different levels of threat or exposure. Time: The time available for decision making is a critical factor in the type and quality of decisions made. With sudden onset events and little preparation, decision makers in practice rely on experience, or recognition primed decision making (Klein et al. 1993). That is, decision makers recognize a situation from events they have observed before and make decisions quickly based on prior experience. That experience may or may not be relevant to the actual situation, which may be more complex, more interdependent, or more fragile, increasing the uncertainty of the consequences of action. Rapid decision making may mobilize action quickly based on experience but be prone to error (Kahneman 2012). Or decision making may be slow, deliberate, and more accurate in terms of long-­term problem solving, but miss the opportunity for timely, substantive action needed, for example, in recovery from disaster (Kahneman 2012). Initial conditions generate significantly different results, if the region experiences a sudden, severe disruption such as an earthquake, or a gradual increase in known threat such as an advancing hurricane that allows time for consideration of multiple strategies and adaptation to the most favorable one, evacuation. Time has a critical impact in shaping the community’s collective response in coping with risk. Space: The distribution of actors/clientele affects significantly the capacity of a system to respond to indicators of risk. If actors in a system are scattered over a wide geographic area, as in the mountain villages damaged by the earthquakes in Nepal, or if actors are concentrated in a risk-­prone area, as in the three cities of the Kathmandu Valley, the communication of risk, as well as the capacity for action to reduce risk, will vary. It is more difficult to garner the attention needed for collective action if there are many other claims being made simultaneously on the actors’ attention in a small space. A sparse distribution of actors or clientele likely has the opposite effect. It is easier to get the actors’ attention, but more difficult to mobilize an effective response, as fewer resources may be available and logistics are more likely to be constrained. More than physical space, social space for considering alternative beliefs about risk (Bauman 2006; 1993) acknowledges the boundaries that inhibit or enhance collective action. Scale: In large-­scale, complex, sociotechnical systems, operations to reduce or respond to risk vary as the number of jurisdictions, population af-

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fected, geographic area, and potential magnitude of the disaster increase. The capacity to absorb risk and transform it into resilient performance may be greater across many jurisdictions, but the organizational task of communicating and coordinating collective action to do so is also greater. Small communities operating within single jurisdictions may mobilize more quickly but may not have the resources to withstand a major threat and consequently may incur greater damage with lasting consequences. The scale of operational actions varies with the intensity of the threat as well as the capacity for response to the threat. Estimating the range of variance before the threat occurs is critical to the sustainability of the community. Energy: Determining the energy that most effectively drives interactions among organizations in recognizing and responding to risk is critical. Decision makers in different contexts have focused on various sources of energy to facilitate collective engagement: money, fear, power, information, social norms, and values. Each of these sources may be effective with some group of people but prove ineffective with others. Determining the dominant force that drives interaction among individuals, organizations, and institutions to engage actively in responding to risk or that hinders this process likely depends on local contexts. The four initial conditions outlined above lead to a set of basic questions that can be used to characterize any complex adaptive system that is operating in zones of risk. These questions are as follows: 1. What structures of sociotechnical design either facilitate or constrain the flow of information through a complex adaptive system of operations to anticipate and respond to varying degrees of risk? 2. What processes of information flow either enhance or inhibit the performance of a given complex adaptive system in practice? 3. What mechanisms are used throughout the system to correct error and update performance in alignment with a changing environment? 4. In what ways does information technology enhance or inhibit the recognition and adaptation to risk in changing environments? These four questions characterize a small number of organizational response systems that emerged following 12 earthquakes over a period of 16 years, 1999–2015. This period represented a time of recurring seismic events around the globe, but also a time of rapid advances in information and communications technology. The set of seismic events triggered interactive response operations, allowing a systematic investigation of changes generated in complex social systems for managing seismic risk, as well as an examination of strategies undertaken to convert risk into resilience for mitigating the global policy problem of seismic hazards.

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Premises Underlying Study Five major premises undergird this study. These premises affirm, in many respects, the analysis offered in an earlier study of the emergence of complex systems in response to seismic risk (Comfort 1999a). Yet this analysis examines the emergence of sociotechnical systems at a different stage of technical advancement, access to technologies, and organizational operations worldwide, engendering a different degree of global awareness of risk and demands for collective action. The five premises are as follows: 1. Information activates the energy that drives interactions among systems in recognition of, and response to, shared risk; 2. Technology constrains the structures through which information flows among component actors, units, or institutions within and between operational systems; 3. Organizations create the channels through which communication flows among component actors, units, or institutions that either facilitate or inhibit collective recognition, response to risk; 4. Culture serves as a filter for interpreting information through norms of action under conditions of uncertainty and varies among communities; 5. These interacting components make up a metasystem, or complex adaptive systems of systems, that operates in a continual process of defining and redefining what risk is shared, what resources are allocated to risk reduction, and which threats require collective public action. The ensuing dynamics of collective cognition and action offer guidance for improving the assessment and management of collective risk. The exploration of shared risk, its consequences, and potential strategies for transformation into resilience continues. As this exploration extends globally beyond seismic risk, the benefit of informed action, as well as the cost of failure to act, increases. Next Steps This first chapter outlines seismic risk as a global policy problem. It frames the challenge of seismic risk presented to decision makers at multiple scales of operation, identifies a set of initial conditions that shape the contours of this problem in different contexts, and poses a set of basic research questions to guide the inquiry. Further, it presents a set of premises that offer an initial characterization of seismic risk as a problem to be explored in greater detail in subsequent chapters. The book proceeds as follows. Chapter 2 reviews the

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theoretical framework of complex adaptive systems, discussing recent developments in this extensive literature and refining the underlying concepts that provide a more detailed framework for this analysis of shared risk. Chapter 3 presents the methods and data for the comparative analysis of 12 case studies of earthquake response systems that provide the empirical basis for this book. Chapter 4 presents the context for the four different types of response systems that were identified by degree of adaptation to the problem of seismic risk, and briefly, the initial conditions for each response system that shaped its development. Chapter 5 outlines the findings and analysis for the response system that is moving toward auto-­adaptation, or the set of premises and skills in self-­organization that leads to resilient and sustainable performance in regions of risk. Chapter 6 presents the findings and analysis that look back one step in adaptation to provide the contrast in performance for operative adaptive systems. Chapter 7 reveals the findings and analysis that characterize emergent adaptive systems, and chapter 8 lays out the findings and analysis for nonadaptive systems. Chapter 9 provides a comparison across the set of 12 earthquake response systems, examining the degree of integration achieved between their internal capacity to adapt to an altered disaster environment for managing response operations, and their dependence on external resources, knowledge, and skills to implement coherent actions for response and recovery, based on analyses of External/Internal index values. This measure assesses the evolving coherence of the systems, summarizing the points of change, development, and breakdown in each. Chapter 10 concludes the book with a conceptual model for adaptation, learning, and resilience in addressing the global problem of seismic risk and outlines a series of next steps for continuing the cumulative inquiry essential to managing seismic risk.

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2 Risk in Complex Systems

The Logic of Uncertainty A standard F-­1 visa application to study English in California rang no alarms when it was processed, favorably, for a young Saudi seeking entrance to the United States in December 2000. At the time, the application was treated as a routine request for entry by an international student seeking to attend a local college to acquire language skills for participating in business transactions in his home country. Only later was it discovered that the young man never enrolled in classes. Nor was it noticed that this same student had previously obtained a commercial pilot’s license at a flight training school in Scottsdale, Arizona. No one noticed that young men from the same country had entered the United States on tourist visas at approximately the same time but had enrolled in flight schools in Florida and Minnesota instead, in violation of their visa class.1 Do applicants for tourist visas who enroll in flight schools in different states constitute future risk to the security of the United States? Their visa applications were reviewed against requirements for entry set by the US Department of State. Applications to the flight training schools were processed independently by flight schools in the separate states. No one was monitoring the scattered anomalies on a wider scale.2 The outcome of those applications became catastrophically apparent with the terrorist attacks on September 11, 2001, months after the initial visas were granted (National Commission on Terrorist Attacks 2004). Is there a logic that could have determined the risk earlier? Risk is inherently uncertain and varies in degree with the context in which it is observed or assessed. Generations of researchers have grappled with the changing concept of risk and sought to define means of assessing risk that

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reduce uncertainty and enable informed action to counter potentially damaging events (Douglas and Wildavsky 1983; Hollnagel, Mancini, and Woods 1986; Beck 1992; Kaplan and Mikes 2012; Tierney 2014). This search for logical methods to understand risk and inform credible action to reduce risk before destructive events occur drives inquiry into unknown arenas. By definition, risk is a state of plausible events or a set of anticipated conditions that has not yet occurred, but the potential for destruction animates the search to reduce its possible impact. Consequently, risk is a social construct, one created by the human actors who seek to manage a stable world, and who, aware of potential catastrophe, seek to prevent or reduce it. The conundrum is that logical approaches to reduce risk often miss the ambiguous and tentative signals that indicate potential danger and discredit the exploratory, holistic approaches that may, more accurately, identify a threshold of failure. For example, the failure of the Federal Bureau of Investigation to connect reports of questionable actions in San Diego, Minneapolis, and Florida by Saudi citizens who entered the United States on student or tourist visas illustrates the intermittent, inconsistent actions that escape a standard approach of risk detection, but cumulatively led to the devastating 9/11 attacks (Kearns et al. 2012). The challenge is how to construct a mode of considering risk holistically, but systematically in a dynamic environment that is prone to recurring hazards. Changing Concepts of Risk RISK AS THREAT TO SOCIAL ORDER

Over decades, inquiry into risk and strategies to manage it have reexamined and redefined risk in relation to changing environments. Three broad themes have shaped this continuing dialogue in administrative theory and public policy. The first theme focuses on the impact of technology on social institutions, and whether changes introduced by advances in technology exceeded human capacity to manage institutions in constructive ways. Mary Douglas and Aaron Wildavsky argued in their 1983 book Risk and Culture that perceiving risk was a selective process mediated through culture. Since humans cannot not pay attention to the full range of possible threats they encounter in everyday life, they select certain immediate threats as imminent and focus their efforts at risk reduction on the selected risks, ignoring the rest as outside their capacity to comprehend, much less affect. The selected threats, whether a release of radioactive pollution from a nuclear plant, transmission of infectious diseases such as Ebola and Zika, or contaminated aspirin from tampered containers in local drugstores, are amplified through the media and communication networks of the local culture to gain popular recognition and spur preventive action. In this view, the selected risks mask substantive threats to

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the community’s welfare that are not recognized, understood, or addressed. Yet, since the collective attention of community members is being mobilized to avert a named threat, unnamed threats continue, unrecognized and unaddressed, to erode the capacity of the community to cope with substantive issues that may seriously undermine its vitality over the long term. In his classic book Risk Society, Ulrich Beck (1992) perceived technology as potentially disruptive to social order. He considered the process of defining risk in modern societies as essentially identifying threats to the current order of social norms and stability. The underlying goal of organized society is to maintain stability, and consequently, risk represents the forces that threaten stable institutions and established beliefs. Defining risks, then, provides a focus for mobilizing attention and resources to undergird the present order. The threat of new technologies is not the technical advances per se, but the potential dysfunction these technologies may bring, if existing social and economic institutions cannot manage them productively without distorting norms of social interaction and accepted human values. In contrast, a second theme emerged in the risk dialogue. Other theorists (Churchman 1971; Ostrom 1990) saw the organization of collective action as a strategy to counter risk. That is, communities had the capacity to mobilize resources and adapt their performance to accommodate threats from external or internal sources. Such adaptation presumes acceptance of a common goal for the benefit of the community, perceived, understood, and supported by the members of that community. Early theorists were decidedly pessimistic regarding the willingness of individuals to change their behavior voluntarily in support of a shared, or public, goal. Individuals, following their rational interests, would inevitably decimate the public arena, without authoritative requirements to the contrary (Olson 1965). In his powerful essay “The Tragedy of the Commons,” Garrett Hardin (1968) evoked a similar image, arguing that individuals, following inherently selfish interests, would degrade common resources, leaving the community poorer and more vulnerable to external threats. RISK AS A CATALYST FOR COLLECTIVE ACTION

Collective management of risk became increasingly important as industries advanced commerce, but at the cost of increased degradation to public goods, such as air, water sources, and the natural environment. Entering the debate on common pool resources, Elinor Ostrom (1990) presented a fundamentally different perspective with her landmark book Governing the Commons: The Evolution of Institutions for Collective Action. In her perspective, Ostrom held that humans learn to adapt their behavior to changing conditions that create collective harm. That is, individuals could rationally perceive that they were

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better off by sharing resources under commonly agreed-­on rules, rather than seeking to exploit one another for individual advantage. Consequently, the process of establishing clear goals for the community in sharing common resources and rules for allocating use of those resources confirmed a shared decision process among members of the community that achieved a public benefit greater than serving the interests of individual participants. Outlining a systematic approach to summarize the process of governing common resources, Ostrom (2005) presented her Institutional Analysis and Development Framework as a theoretical design based on empirical field research. She explored how communities develop institutions that enable them to articulate shared goals and implement practical means of resolving conflicts and achieving sustainable development of social and economic resources. Ostrom moved beyond individual decision processes and shifted her inquiry to the more complex processes of institution building and collective action to manage shared risk. RISK DYNAMICS IN SOCIAL INTERACTION

As a third theme, the continuing dialogue addressed the escalating impact of risk on social organizations and institutions. As the scale and scope of risk increases in social interactions, the resources and organization needed to counter risk also increase. Individuals play shifting roles in changing environments, and their perception of risk changes with their roles. For example, in his classic study of the Mann Gulch fire, Karl Weick (1993) vividly documented the change in the capacity of a fire crew threatened by an advancing wildfire to heed the command of their captain to drop their tools, light a fire in front of them, and lie down in the burned area for safety. The command ran counter to the crew members’ training; they could not see the fire advancing rapidly over the hill; they could not imagine alternative action. Weick attributed this loss of capacity of crew members to function as an organizational unit under extreme danger to their inability to make sense out of the rapidly changing environment. No previous experience in such a situation informed their decision as a crew, and under threat, most firefighters reverted to limited individual judgments. Thirteen firefighters died in the Mann Gulch fire, a sobering instance of organizational dysfunction as the changing scale of threat exceeded the mental model for crew performance. Ironically, 30 years later, on June 30, 2013, an eerily similar wildfire incident occurred at Yarnell Hill, Arizona, claiming the lives of 19 members of the Granite Mountain Interagency Hotshot Crew (GMIHC) (Hardy and Comfort 2015). In this incident, however, the breakdown was not organizational, but technical, as the crew lost communication with the Aerial Supervision Module (ASM) plane dispatched by the federal Bureau of Land Management flying

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over the area. The ASM pilot missed the urgent request from the GMIHC on the ground for fire retardant, and the rapidly moving fire overtook the crew. All 19 members of the GMIHC died together, its organizational unit intact, but with the technical communications infrastructure among different levels of the multijurisdictional firefighting system broken. Recognition of the need to integrate information from different perspectives to reduce risk emerged as organizations addressed increasingly complex technical tasks. The concept of distributed cognition captures the process of integrating diverse types of information in real time (Hutchins 1995). Drawing on his experience as a naval officer and observing the process of bringing a large ship safely to harbor through narrow channels in busy ports shared with smaller crafts moving at different speeds and in opposite directions, Hutchins noted the rapid exchange of information among crew members with different skills and types of knowledge—navigator, captain, wheelhouse operator. Each perspective was essential to the whole task, but no single member of the crew held all perspectives or relevant skills. Success of the operation depended on developing a shared cognition of risk among all crew members, so that rapid adjustments could be made by the appropriate crew member in real time to bring the ship safely to harbor. Each of the approaches to managing risk outlined above contributes rational insight and partial understanding of the challenges of coping with risk in a changing environment. Each approach illustrates the capacity of human managers to learn from their experiences and documents the complexity of the changing environment. Yet each perspective focuses on control of known resources or functions in the operational environment, rather than identifying the underlying process that is driving change. Dynamics of Change in Risk Environments INFORMATION AS ENERGY IN SOCIAL SYSTEMS

Searching for the forces that drive social change, early theorists (Argyris 1982; Argyris, Putnam, and Smith 1985; Argyris 1993; Kaufmann 1993; Luhmann 1995) focused on information as a catalyst for learning that led to action. While these theorists worked in different fields—organizational theory, biology, sociology—each viewed information as a trigger point for action, among individuals, amoebas, or social groups. None of these theorists, however, considered the technical means by which information was transmitted to others. Face-­to-­face communication among individuals, considered by many theorists to be the most effective (Argyris and Schön 1974; Argyris and Schön 1996; Alford 2009; Innes and Booher 2010), is limited necessarily by the size of the group. As the time, density, and scale of perceived risk increases, the physical means of communicating information directly to the

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affected population becomes part of the underlying structure through which social change evolves. Examining the transmission of information as a process requires an assessment of how information flows as well as the structure through which it flows. Understanding this process is critical in communicating information about risk, as the potential for error in both transmission and reception increases, as clarity in the content of the message decreases (Mileti 1999; Mileti and Sorensen 1990). This diminishing effect is further magnified as the scale of intended senders and recipients increases. Considering information as a process, the fragility of communication derives from both its technical and its human components. If the intent of communication is to transmit a message with reliable accuracy from one point to another (Shannon 1948, chap. 6), the potential for error is present in each of the five components of the process: sender → transmitter → signal → receiver → destination. Add to this process the ever-­present distraction of noise, and the probability of error in both human and technical components increases further. If errors in the technical process of transmission are not identified and corrected, communication has the potential for escalating error in social action, leading to damaging outcomes. If errors in content or interpretation of the message are not corrected in the organizational process, the distortion increases. Consequently, it is essential to assess the validity of information being transmitted as well as the reliability of the technical structure through which it flows. Variance in both content and technical structure for information flow increases as the number of organizational units included in the communication process increases, and, still further, as the scale of operations escalates in size and complexity. The work of Shannon (1948) and Wiener (1948/1961) articulated the role of feedback processes in social and technical systems, a fundamental insight in the theoretical development of complex adaptive systems (Ames et al. 2011). Importantly, their insights demonstrated the capacity of technical structure to facilitate or hinder communication among individuals, organizations, and larger social systems. This capacity for the technical structure to influence communication is compounded by the social context in which it occurs. If information activates the energy that drives all living systems, whether an amoeba’s response to a shift in temperature or a community’s response to a sudden earthquake, it becomes a powerful agent for change. In each case, the recipient— amoeba or community—perceives change in its immediate environment, processes it with its existing cognitive capacity, and responds with resources available without external direction. Action is precipitated by information that communicates change in the state of the system, which triggers the recipient’s internal resources to respond appropriately. This process represents self-­ organization (Kaufmann 1993; Comfort 1999a), a concept recognized in social organizations as well as biological processes. For the community, an already

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complex social organization, the appropriate response to an extreme event is to request external assistance, but the action taken to make that request is initiated by the immediate cognition of disruption in daily operations: collapsed buildings, power outages, people injured or trapped. Measuring the degree of change in information that precipitates action, however, is a more difficult task. Two concepts from Smith’s work explain this dynamic in complex sociotechnical systems. First, information flows through multiple channels in any living system; these channels constrain the rate and content of information flow both within the system and between the system and its immediate environment. Since estimating all possible changes within a system generated by information flow is unrealistic in practice, a more practical method is to identify the constraints on transmission and reception of information within the system, given its existing infrastructure (Smith 2008a). Identifying constraints reveals the channels through which information does or does not flow and allows characterization of actual systems and their capacity for adaptation in changing contexts. For example, if television news programs are broadcast only on high-­definition channels that require subscriptions, access for lower-­income groups may be limited, leaving them less informed and less adaptive to emerging threats. Second, information flowing through the system generates different types of action at different operational levels (Smith 2008a). For example, reports of a strong earthquake will lead fire personnel to check for leaking gas lines, police personnel to check traffic lights and overpasses, hospital personnel to monitor the status of their patients, and provincial administrators to assess available resources for all cities and towns in the province. Consequently, identifying the operational levels within any specific disaster management system creates a knowledge structure that, combined with measures regarding content and rate of information flow among the levels of decision, provides a preliminary model of the system’s functions and performance. The system may change, but the model captures both structure and process in given contexts. Risk lies in the potential mismatch between limiting information to specific units in the system or flooding operational units with information irrelevant to critical tasks. Aligning the flow of information to changing tasks within an earthquake response system reduces error but requires technical support. SHIFTING FIELDS OF ACTION IN DECISION MAKING

Sociotechnical systems operate in ever-­changing environments and require continual effort to monitor and maintain stable performance in midst of flux (LaPorte 1975; Roe and Schulman 2016). This problem-­solving arena is necessarily more complex, and interaction among the social dimensions that shape decisions in actual contexts vary by time, space, scale, and energy. Identifying

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the types of change that occur in the problem-­solving arena for extreme events offers a means of tracking decision processes regarding specific risks as communities grapple with recurring exposure to hazards. Interactions among social dimensions affect both structure and process of decision making in the design of technical operations intended to mitigate risk. As technical information about risk of hazards is updated by knowledgeable experts, organizational decision processes need to adapt to new information, lest risk escalates through ill-­informed action. Initial efforts to manage large-­scale, sociotechnical systems focused on organizing complexity and establishing controls for unexpected disruptions (LaPorte 1975). This work led to the development of theories of high reliability in organizations (LaPorte and Consolini 1991; Rochlin 1993; Roberts 1993; Weick and Roberts 1993; LaPorte 1996; Weick and Sutcliffe 2007). This nascent field focused on organizations that managed advanced technical operations for complex systems that provided vital services to benefit the public good, such as electrical grids or air traffic control, but depended on intrinsically hazardous systems. Consequently, such systems incurred unacceptably high costs and consequences, if they failed, for example, aircraft carriers, nuclear plants, or space shuttles. While high-­reliability theorists have documented remarkable successes in managing large-­scale sociotechnical systems, for example, the NASA missions to the moon in 1969 and to Jupiter on July 4, 2016, they have also documented spectacular failures, such as the sobering crashes of space shuttles, Challenger on takeoff in 1986, and Columbia on reentry in 2003. Although the imperative to manage sociotechnical systems requiring high reliability in performance increases, these behavior patterns are extremely demanding and difficult to assure. The brittleness of methods relying primarily on detailed controls and specialized training to cope with unexpected events reveals the need for additional methods of detecting and coping with uncertainty and risk. Recognizing the inseparability of structure from process in the evolution of complex systems, Stuart Kaufmann (1993), a biologist, held that the most creative systems operate at the edge of chaos. That is, all systems operate on a continuum that ranges from complete disorder, or chaos, on one end to complete order, or rigid control, on the other. In the middle, there is a narrow band where there is “sufficient structure to hold and exchange information, but sufficient flexibility to adapt to changing environments” (Kaufmann 1993, 212). Living systems that maintain this tenuous balance prove the most innovative in adapting their inner structure to meet external demands or to ward off threats, both internal and external. While some systems develop the capacity to adapt to changing environments, both internal and external, others do not. How or why this process of adaptation occurs still needs exploration and explanation.

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Writing nearly 20 years later, sociologists Neil Fligstein and Doug McAdam (2012) proposed a far-­ranging theory of interacting fields of action that extends the dialogue of organizational adaptation to changing conditions and explores how the interaction between structure and process develops in practice. Individuals, groups, and organizations are informed by different disciplines, capacities, and assessments of risk regarding any specific social goal. Further, multiple actors operate at different scales of interaction in seeking to achieve the same goal, for example, reduction of seismic risk, but create interdependencies that both accelerate and constrain collective action. Each field of action, for example, seismic risk reduction, has a unique degree of complexity, and it is essential to bridge disparate types of knowledge to foster collective action for the affected community. How is this bridging done? How do managers discover which fields can be bridged and which are separated by distances too far? Fligstein and McAdam (2012) view social interaction as a continual struggle between stability and change, with risk as an ever-­present element of uncertainty that roils the process. Actors move among states of stability, change, and emergence in developing new patterns of coping with risk that they recognize and define. The authors offer a detailed list of questions and suggestions to guide inquiry in this complex process, many of which are familiar to students of social change and complex systems. They add the important element of empathy as a critical factor in bridging disparities and muting risk in social action and view empathy as a cultural factor to be developed in societies seeking to minimize risk but maximize sustainable stability. Interestingly, the mechanism for social interaction proposed for achieving this rolling balance between stability and change is a strategic action field or an integrated, well-­ organized space for social interaction that allows the exchange of information and correction of error among relevant actors in the field. This proposed mechanism echoes elements of Elinor Ostrom’s (1990) concept of a knowledge commons, showing the continuity of basic insights for managing risk and social change over decades. DEVELOPING FLEXIBLE STRUCTURE FOR ACTION IN CHANGING ENVIRONMENTS

To some analysts, the concept of flexible structure for a sociotechnical system is a contradiction in terms. How flexible? What function is the structure designed to perform for the system? In his early article on the architecture of complexity, Herbert Simon (1962) argued that if systems would incorporate feedback loops on operational performance into their decision processes rather than relying on external controls, better informed adaptations would lessen risk. Implicit in Simon’s argument is the ongoing human cognitive ca-

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pacity for correction of error, as new information replaces old, and previous outdated assumptions are updated with valid information. Reaffirmed by Eric Smith (2008a) more than 50 years later, this underlying premise confirms the centrality of cognition and learning in complex systems (Comfort 2007b). Flexible structure, in Simon’s terms, means a continual process of review, reflection, and redesign to adapt the structure of the system—technical and organizational—more appropriately to the environment in which it is operating. In practical terms, such effort reduces the risk of failure, as participants in a well-­designed sociotechnical system are likely to make more informed decisions, lessening risk if extreme events occur and facilitating the mobilization of assistance for recovery from the incident when they do. Yet, there is no guarantee that the human managers in complex systems will indeed correct their errors. A sociotechnical system that uses technology appropriately to monitor organizational performance and display the results in timely, easy-­to-­ grasp formats to relevant managers can, at best, make the errors visible. Given the nonlinear processes that characterize complex, dynamic systems, the key task is to find the balance between order and disorder in practice (Kaufmann 1993). If there is too much control, the system becomes rigid and loses support from its immediate constituency. If there is too little control, the system veers into chaos and is unable to achieve its goals. Acknowledging that complex systems with many interacting parts generate uncertainty, Axelrod and Cohen (1999) propose that, rather than seeking to control an evolving system, it is more constructive to harness the complexity. The driving force of change cannot be halted, or the system would atrophy. The question is how to guide a complex system in constructive directions at the macro level of operation without thwarting the flow of information and energy that animates its component parts at meso and micro levels of operations. To do so requires detailed knowledge of the operating context, awareness of constraints on existing performance, and access to resources and skills in problem solving among participants in the system. Building a local knowledge base is essential to identify what variation in types of knowledge characterizes the population at risk, which actors are increasingly at risk, which actors, conversely, are reducing risk, and what risks are selected for attention and collective action at what time. Making this knowledge easily accessible allows consideration of what resources and skills are needed to solve problems collectively, overcome obstacles to change, and identify viable strategies of action to achieve community goals. Implicit in this argument is the continuing thrust toward building capacity for collective learning and action, redirecting the cumulative energy of the community to counter risk, and tracking potential avenues of change. The whole set of interacting components that make up an interconnected system shifts its collective energy, creating a different set of initial conditions that change channels in the

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flow of information and action among its components and leads to more ­constructive outcomes, instead of focusing on unachievable standards of control. In practice, the requirements for collective action to reduce risk vary at different levels of operation. For example, the city of San Francisco is vulnerable to seismic hazards. It is not possible to predict when or where an earthquake will occur, but it is highly likely that a severe earthquake will occur on the San Andreas fault that underlies the city within a timeframe of the next 30 to 300 years (USGS 2016a). With a population of over 864,000, the city faces a known risk of serious harm from earthquakes, hedged by uncertainty regarding time and specific location. Given a history of experience with severe losses from earthquakes in 1906 and 1989, city and county officials; building owners and managers; professionals engaged in research and practice in engineering, seismology, architecture, and insurance; and residents and neighborhood groups all have a relatively high degree of awareness of seismic risk. The policy question is what to do about a risk that is known but uncertain in its timing or probability of occurrence. Interestingly, one response to seismic risk in San Francisco has been to initiate a voluntary program that links building owners with responsible professionals to assess and monitor the performance of buildings subject to known standards of seismic safety. The Building Occupancy Resumption Program (BORP) is managed by the Department of Building Inspection (DBI) of the City and County of San Francisco,3 but it has been developed in collaboration with key professional associations of engineers and others, including, for example, Earthquake Engineering Research Institute (EERI), Structural Engineers Association of Northern California (SEAONC), and local branches of the Building Owners and Managers Association, American Institute of Architects, and American Society of Civil Engineers (ASCE). Key features of the BORP are especially relevant to the discussion of coping with risk. First, the program is voluntary; building owners choose to initiate a contract with professional engineers to assess the status of their buildings against current building codes for zones of seismic risk prior to a seismic event. The contract engages professional engineers to assess the building for damage within minimal time, days if not hours, after such an event. Second, the set of contracts, voluntarily initiated by building owners and signed by professional engineers, provides a running inventory of the status of key buildings in the city prior to a seismic event. Many of the buildings house major businesses that are vital to the city’s economy or hundreds of residents in large apartment buildings. Since the contracts require review and reassessment every two years, the resulting database provides a current assessment of existing strengths and potential weaknesses in a select, but important, segment of the city’s built infrastructure. These data will inform decisions by city and county

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personnel regarding where to allocate resources and personnel time under the urgent stress of an actual seismic event. Third, the program demonstrates the benefit of cross disciplinary review of conditions that reduce or magnify risk. By engaging building owners in a voluntary program that assesses building performance against valid criteria informed by professional engineers and architects, the public agency, DBI, is reducing risk in practice as knowledge and awareness of building performance under seismic stress increases. Notably, BORP focuses on systematic monitoring of actual performance of buildings in a local area of known seismic risk, rather than establishing controls that are exercised by some distant authority. The program creates foreknowledge of the capacity of buildings to withstand seismic risk in a given context and identifies the organizational network of support that is available for rapid mobilization in response to an actual event. The result is an investment in time and knowledge to improve decisions and actions by multiple organizations and groups in actual practice at the local level, raising collective understanding of seismic risk among the participants and facilitating collective action when needed. The feedback processes that Simon deemed vital to organizational performance are embedded in the process: feedback between engineers and owners; feedback between owners and DBI officials in the City and County of San Francisco; feedback between DBI and the professional associations that fostered the design of the program. To the extent that feedback processes are aligned and integrated in an active sociotechnical system, resilience in the community of San Francisco is strengthened, and risk is lessened. Design in Mitigating Risk FITTING GOALS TO ACTION THROUGH DESIGN

Since risk is a phenomenon that has not occurred, the most powerful strategy in coping with risk is design for future action. Design creates a temporary structure for human interaction with the environment that can be changed when the environment changes (Simon 1997). Design represents a rational effort to recognize, identify, and assess the components of an interacting system, and the interdependencies among them, as the system seeks to limit risk from a specific agent or hazard in the environment. That is, the design of a building is intended to protect its occupants from wind, rain, snow, or seismic risk that may be experienced in its immediate environment. The design of a public program, similarly, is to protect its participants from some named harm, such as floods or tornadoes, or to build capacity for some group of participants, such as children participating in federally funded education programs. Consequently, the objective of design is not the artifact itself, but rather the fit of the artifact to the environment to serve a specific purpose at

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a given time. Since the environment is continuously changing, the designed artifact, likewise, requires continual review and adjustment to maintain an appropriate fit. In any complex system, decisions made at different levels of operation need to be aligned in a functional design for mobilizing collective action to achieve the overall objective. For example, building codes need to be adjusted as engineers learn more about the technology of welds for steel frames, seismologists learn more about previously unidentified thrust faults, and architects learn more about efficient uses of space. The realigned building codes then need to be communicated to city planners, realtors, and potential builders in the region to achieve a more informed basis for construction and maintenance of building stock for the community. Levels of operation vary by context, but nearly all complex systems include micro, meso, and macro levels of decision that are informed by different sources of information and require integration to form a coherent strategy of action for the community to adapt effectively to its changing environment. Organizations are the product of intentional design. They create processes through which information and action flow among interacting units within a larger system and between the system and its environment to achieve a specific goal, for example, reduction of seismic or other risks. Yet these organizational processes are often modified by random events that precipitate either innovative adaptation or failure under stress (Argyris 1993; Cohen, March, and Olsen 1972). The emergent processes or informal forms of organizational adaptation then become part of the dynamic that drives change within the whole system, and between the system and its environment. If the system is intended to reduce seismic risk, the degree to which members of a given community are already aware of that risk changes the amount and frequency of information needed to activate a collective response to earthquake tremors. Organizations and groups take different actions in response to notification of earthquake events, with schools sheltering children in place, train operators halting traffic, building superintendents stopping elevators, and hospitals switching to backup generators for electrical power. The actions differ, but the goal is shared: to mitigate the impact of a damaging event on community functions. If action is taken in concert by different organizations or groups, the whole community is spared significant damage, and the metasystem of organizations has achieved its goal. UNCERTAINTY IN STRUCTURE AND PROCESS

The continuing interaction of components in any sociotechnical system generates uncertainty between known and unknown risk that modulates action. The degree of uncertainty is influenced by the functions of time, space, scale,

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and energy that affect the interaction among actors and the environment in which they operate. Each function generates a distinct type of uncertainty that indicates unknown risk in an operational context. Time as an Element of Action

With credit to Donald Rumsfeld (2002), there are risks that are known, but the time at which a threat may occur is unknown. For example, a bridge is likely to fail under a certain loading of weight, although the actual time of such failure may be random. Actions necessary to mitigate this risk are also known: strengthen the bridge structure or limit the weight allowed for vehicles to cross it, but the implementation of these actions may be random. There are risks that we know we don’t know, such as whether or when a sudden, massive flood will wash away the footing of a bridge, causing it to fail. There are risks that are known to others, such as the likely duration of steel welds used by engineers in the construction of the bridge, that we do not know. Finally, there are risks that we don’t know we don’t know. These risks are the most difficult. The inherent uncertainty in interaction between a complex system seeking to mitigate risk and its changing environment generates a dynamic between known and unknown risk that varies in intensity over time and drives a continuing search for valid data to inform action. Space as a Defining Boundary of Risk

The primary task in risk assessment is to identify risk in a specific context or space, characterize it, measure it, and transmit that information to others who have the capacity to act on it. Hazard maps reveal that the spatial distribution of risk is nonrandom. That is, hazards tend to cluster in specific regions and occur under identifiable conditions. For example, the California Geological Survey creates maps that display the major earthquake faults in the state, showing in graduated colors the severity of risk to populated metropolitan regions, roads, railways, and infrastructure. Resources tend to cluster as well, with some regions prone to risk attracting resources to study and mitigate risk, while others do not. To illustrate the potential influence of space on disaster mitigation, three San Francisco Bay Area cities—San Francisco, Oakland, and Berkeley—all received grants from the 100 Resilient Cities Program pioneered by the Rockefeller Foundation.4 All three cities are subject to seismic risk; all three cities have access to professional personnel to provide guidance to risk mitigation policies. But the three cities differ in population size, built infrastructure, and degree of engagement with their respective constituencies. These differences create discrepancies in time and effort required for mobilizing policy change, cost in retrofitting engineered buildings, and priorities for action among the subsets of population, actors, and physical infrastructures at risk. The Rockefeller program’s selection criteria for participating cities

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included the intent to foster communication among the three recipient cities and to build a strong regional constituency for risk mitigation in the San Francisco Bay Area (Rockefeller Foundation 2013). The spatial distribution of exposure to seismic risk is clear, and clusters of resources are readily identified, so the three cities could theoretically create a measurable model of regional risk reduction. Yet there is little noticeable change in practice on a regional level. Each city appears to be developing its own program with little interaction with its neighbors, despite the common funding source, common goal of risk reduction, and common seismic hazard in the region. The missing element appears to be an interactive flow of communication among the three cities at the midmanagerial or meso level (Fligstein and McAdam 2012). The incentives to drive the search and exchange of shared values regarding seismic mitigation among the three cities, as well as within each city, are not clearly articulated. Generating the flow of communication to enhance the goal of seismic mitigation in the social space shared among the communities at risk is not likely to occur without conscious design (Bauman 1993; Ghosh and Ingene 1991). Aligning Scales of Operation in Complex Systems

A continuing challenge in the analysis of complex systems is determining how to bound the system under study (Glass, Brown, et al. 2011; Holland 2012). The coherence of the system depends on the exchange of information among different scales of operation in dynamic environments (Barabasi 2002; Watts 2004), and the alignment of actions taken by actors in different locations over time. Tracing the pattern of interaction among participating components across different scales of operation in a complex system is a painstaking task, if done systematically and empirically (Bennett and Checkel 2015). Yet the value of such an exercise is to document the rate of change as it occurs within each level and as it varies across the different scales of operation in a complex system. For example, following the 1994 Northridge earthquake in the Los Angeles metropolitan region, 10 freeway bridges collapsed, seriously snarling transportation in the sprawling region of 15 million inhabitants heavily dependent on automobile traffic. Everyone in the region was affected; businesses could not ship or receive products essential for commercial operations; workers spent hours trying to get to their jobs via alternative routes; tourists, a major source of revenue, canceled reservations and avoided the city, adversely affecting hotels and restaurants; local public officials struggled to find financial support from state and federal agencies, engaging private engineering companies to rebuild the bridges (Comfort 1994). In practice, multiple decision makers had to recognize that their choices were limited by the actions of oth-

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ers; they needed to redefine the scope and scale of the transportation system to regain functionality in commerce, social, and economic operations for the larger metropolitan region. The flow of information across jurisdictional levels of authority in mobilizing emergency response operations following a major earthquake indicates where the functional components of the system are and, conversely, where the gaps or bottlenecks obstruct informed action. If the pattern of information flow can be modeled computationally in actual cases of earthquake response operations, the results will reveal the fluctuating dynamic between stability and change as the system adapts (or fails to adapt) to the damaging event. The issue of scale in complex systems has been recognized over decades by theorists studying change and acknowledging the internal shifts required to adapt to external operations involving larger numbers of actors performing more advanced tasks (Simon 1997; Ostrom 1990, 2005; Barabasi 2002; and Fligstein and McAdam 2012). Activating Cognitive Energy through Computational Modeling

Recent advances in computational modeling provide tools for modeling changing patterns of information flow in complex systems and exploring the consequences of different strategies of action (Prietula, Carley, and Gasser 1998; Glass, Ames, et al. 2011; Linebarger et al. 2012). Although still a nascent field of study, computational modeling offers glimpses into alternate scenarios that are instructive as organizations seek viable modes of adaptation under changing conditions. Yet modeling is an iterative task that requires validation with ground-­level observation and testing (Glass, Ames, et al. 2011; Glass, Brown, et al. 2011) to maintain credibility for decision makers in practice. Technology and Risk INTEGRATING TECHNOLOGY INTO DECISION PROCESSES

Technical advances in monitoring, storing, and transmitting information ­regarding the state of existing systems—physical, technical, organizational— provide a primary means of supporting human decision processes in managing the interaction of communities with their environments. Given the complexity of interaction among the components of these systems and the limits of human cognition (Simon 1997), it is not possible for individual decision makers to comprehend the full range of information relevant to specific risks. Consequently, the design of search and exchange mechanisms through which information regarding a changing environment flows necessarily generates a sociotechnical system. In such a system, the technical monitoring devices, communications infrastructure, and organizational procedures that specify

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types of information to be collected and reported combine to provide decision support for managing risk. Further, the design, construction, and maintenance of the engineered environment for such a decision support system create opportunity, uncertainty, and potential profit or loss for participants in the wider region exposed to risk. Ironically, the very systems that are designed to reduce risk on a macro scale often generate conflicting interests, threats, and benefits on a micro scale for different groups in the community that are exposed to the same risk (Fligstein and McAdam 2012). For example, the trade policy of the North America Free Trade Agreement (NAFTA), designed to foster the free movement of goods among the member states—the United States, Canada, and Mexico—came under direct criticism from workers in the individual US states of Michigan, Ohio, and South Carolina, as companies that produced automobiles in Michigan, furniture and textiles in South Carolina, and rubber tires in Ohio moved their production plants to Mexico to lower their labor costs. The disaffection with this policy from workers who lost well-­paying manufacturing jobs in these US states contributed to the election of Donald Trump as president, who promised to leave NAFTA and impose a tariff on goods from Mexico (Walker 2017). Although the NAFTA policy was poorly explained to the general public and widely misunderstood, it generated conflict and misunderstanding among subsets of workers, company managers, and consumers in all three countries. These same conflicts, not addressed or corrected, are likely to extend to other US and Mexican states and Canadian provinces, subunits in the larger NAFTA system, that are experiencing the strain of economic dislocation, and affect political and cultural interactions among the three countries. In a globally interconnected world, information flows in both positive and negative directions to influence perceptions of the observers and actions that follow. While technical means facilitate the instantaneous communication of information, for example, videotapes of actions being taken or not taken, the task of interpreting these actions within the framework of accepted values and constraints for a given community is more difficult. Giving meaning to these actions requires a different set of social skills and empathy (Fligstein and McAdam 2012). As the limits of human cognition in complex environments are readily acknowledged (Rittel and Weber 1973), so necessarily must be the limits of technical collection, aggregation, and transmission of information. Determining what those limits are and how they affect, positively or negatively, the flow of information through complex systems at risk is central to the integration of technology into decision processes. For example, the global email network Yahoo.com reported two large-­scale hacking attacks in 2013 and 2014 that compromised 1.5 billion accounts (Goel and Perlroth 2016). Attacks at this scale damage not only the credibility of the company, but also confidence of users in digital technologies generally.

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MODELING AS A MEANS OF ANTICIPATING RISK

Measuring and modeling the physical world provide basic information to inform the design and management of operational systems—both technical and social—as they interact with the current environment. This assessment represents a baseline for operations at a given state and time, but anticipating how the systems would perform under different conditions requires a different mental model (Simon 1962). Engaging decision makers in imagining alternative strategies for coping with potential risk serves to broaden the scope of actions they would consider in an actual event. Policy analysts proposing this approach (Bankes 2002; Lempert, Popper, and Bankes 2003) argue that such exercises increase the flexibility of managers in managing actual incidents and reduce the surprise of unexpected events. The International Risk Governance Council, an international nonprofit foundation that analyzes methods of risk reduction, also supports such an approach (Renn 2014). Information technology provides the visual and analytical support to manage the information requirements that sophisticated modeling exercises require. In these and other efforts to model the performance of large-­scale, complex, sociotechnical systems, computers become embedded into the decision processes (Fountain 2001; Nobre, Tobias, and Walker 2009), increasing the interdependence between humans and machines in seeking to manage risk. These methods offer insight into alternative strategies of managing risk, but only to the extent that they can be defined within the bounds of existing knowledge. Pushing beyond the boundaries of current knowledge moves managers into the uncharted region of “unknown unknowns” where intuition and imagination, supported by information technologies, may benefit the continuing search to manage risk. Shared Risk Redefined Previous efforts to model risk have tried, but not succeeded in capturing the rate of change in complex adaptive systems successfully. In an earlier study, I defined shared risk as “public risk, one which affects all residents of a risk-­ prone community, whether or not they have contributed to the conditions producing the threat” (Comfort 1999a, 3). The implication is that those who share the risk also share the responsibility for developing a coherent policy to manage that risk. With this definition, I sought to distinguish risk that affects the public space from risks that individuals may take in private. Shared risk acknowledges the impact of risk to public institutions and infrastructure as well as to the homes and businesses of individuals and organizations. It notes the legal responsibility of public organizations to respond and mitigate that risk, but also the responsibility of individuals and organizations to seek and

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act on the knowledge available to them. Shared risk signals the complexity of interacting organizations and jurisdictions that operate with varying degrees of authority, knowledge, and capacity in seeking to manage the consequences of extreme events. The study examined the evolution of operational response systems following 11 damaging earthquakes in nine different countries to assess how the same type of event was managed in widely different economic, social, and legal contexts. Given the size, scale, and complexity of the response systems as they evolved in different contexts, the systems required collective action among different groups, participating organizations, and jurisdictions. While the analysis presented in the 1999 study acknowledged that the emergent operational systems responding to destructive earthquakes constituted complex systems, the mechanisms of how and when these response systems evolved in different contexts were not fully developed. The 1999 study represented an initial assessment of the interaction between technology, organization, and culture in the emergence of complex, multiorganizational, multijurisdictional systems in response to major earthquakes. Nearly two decades, a dozen significant earthquakes, and five additional countries later, this study returns to the question of shared risk to review the complex systems framework and to identify the conditions that foster integration, coherence, and entropy5 in complex, evolving systems. These factors reflect the dynamic forces that emerge within and among the components that make up the evolving patterns of change, to distinguish between change in the parameters of the operating system over time and change in the environment in which the existing system operates. This study, in contrast, represents an effort to summarize “what we do know” and “what we know that we don’t know,” and to push the boundaries of “what we don’t know that we don’t know” regarding the dynamics of risk in evolving, complex systems. Listed below is a brief set of propositions that roughly reflect acceptance in the literature on complex systems in public policy and administration. Some theorists may disagree, but the set reflects a broad consensus of basic findings from the continuing inquiry on risk. “WHAT WE DO KNOW”

1. Hierarchy, a classic means of organizing multiple actors—individuals, organizations, jurisdictions—to achieve a common goal under stable conditions, fails under stress (Comfort 1999a; Kettl 2004; Erkan et al. 2016). Different forms of hierarchy have been identified—command, coordination, adjudication—but essentially authority is established at a central level to govern actions of subordinate actors. When that authority is challenged in a rapidly changing environment, the functional operation of the system fails (Weick 1993).

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2. Networks of actors representing interdisciplinary, intersectoral, interjurisdictional organizations emerge as the primary mode of organizing collective action in environments at risk. Yet, composition of the networks changes over time, as different actors enter and leave, and different functions are performed in response to changing capacity and demand from the environment. Networks are vulnerable to unexpected disruptions that lead to breaks in performance (Prietula, Carley, and Gasser 1998; Barabasi 2002; Newman, Barabasi, and Watts 2004; Koppenjan and Klijn 2004; Butts 2009) and precipitate redesign in different relationships among the same actors at micro and meso scales of operation, generating new networks of action and transforming the macro system. 3. Systems of interacting organizations, technical structures, and legal institutions endure over time, providing stability for continuing efforts to manage risk, but flexibility to allow adaptation to changing conditions (Glass, Ames, et al. 2011; Linebarger et al. 2012; Holland 1996, 2012). 4. Information triggers the interaction within and among individuals, organizations, networks, and systems; it activates the energy that generates feedback among the components that allows each component to respond—or not—in action, generating the dynamic that drives the system (Smith 2008a, 2008c). “WHAT WE KNOW THAT WE DON’T KNOW”

1. Metrics: We know that components of systems inform and react to change in other components (Glass, Brown, et al. 2011), but we do not yet know how to measure the rate of change within each component of a larger organization or to assess a cumulative rate of change among components within the larger system. 2. Thresholds: We know that increments of change in separate components accumulate to trigger sudden change, or phase transitions, that alter the performance of the whole system (Solé 2011), but we do not know at what threshold this change occurs, or how it varies in specific contexts. 3. Density: We know that actors, resources, and knowledge are not distributed randomly in areas exposed to recurring risk, and that the degree of clustering affects the capacity of actors in these regions to respond effectively (Krackhardt and Stern 1988; Wasserman and Faust 1994). But we do not know what density of actors, resources, and knowledge under given conditions is needed to support effective response.

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4. Space: We know that geographic space defines the size of the area and the number of people affected by risk conditions, but we do not know the boundaries of the social space in which people may construct alternative responses to risk, or the capacity of their imagination and innovative skills to counter destructive threats and transform risk into productive action (Fligstein and McAdam 2012; Bauman 2006). 5. Scale: We know that actions to reduce risk are needed at different scales of operation, and that each scale draws information from different sources (LaPorte 1996; Castells 2009), but we do not yet know how to integrate the flow of information within and across these scales to create practical strategies of action at micro and meso levels of operation that converge to form a coherent strategy for the whole system. “WHAT WE DON’T KNOW THAT WE DON’T KNOW”

By definition, this is an empty set. We have no way of knowing what we don’t know. It is helpful to identify the limits of what we do know, and to use the knowledge we have as the basis for continuing to explore the characteristics of complex systems as they evolve and change in different contexts of operations. Such exploration tests the trade-­offs between individual freedom to act and collective security to protect that are forged in social problem-­solving spaces (Bauman 2006). The very lack of definitive knowledge to resolve this timeless dilemma drives the continuing inquiry to assess the risk of losing either freedom or security, or both. Such inquiry requires a systems approach to model risk in its dynamic modes. This study seeks to identify the types of information that flow through the different components of the macro system or network of networks and to measure the rate of change in information flow among the subnetworks as distinct components of interacting systems that emerge in response to earthquake events. At a second level of analysis, the study seeks to identify information flows between the emerging operational system and the larger society in which it functions. Such information flows indicate change in the collective comprehension of risk by the affected community and in the collective action that follows. The challenge of a systems approach is to identify the boundaries of a system under study and develop the metrics and models that assess the rate of change in information that signals change in practice (Holland 2012). To explore the dynamics of risk empirically, this study examines 12 cases of operational response systems that emerged following the same type of hazard, earthquakes, in nine different countries characterized by different initial conditions, over a period of 16 years, 1999–2015. It focuses specifically on the changing role of information technology and its consequent influence on

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evolving sociotechnical systems, seeking to push back the existing limits of knowledge on metrics, thresholds of change, density, and scale in how communities confront risk. This chapter considered how risk has been viewed from multiple perspectives and raised questions regarding the types of risk that human managers confront in complex, urgent environments. Next, chapter 3 considers different types of data to document risk in practice and explores valid methods to measure risk in changing conditions.

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3 Assessing Risk in Complex Systems DATA , METHODS, AND MEASUREMENT

Measuring Risk On September 1, 2014, the outsize electronic Geiger counter stationed outside the city hall of Fukushima, Japan, fluctuated between 46 and 49 millirems, flashing at five-­second intervals, as a group of academic researchers stepped out of a minibus to observe the cleanup operations still underway following the Fukushima Daiichi reactor breach on March 11, 2011.1 At almost 50 times the amount of radiation deemed tolerable for human exposure, the city of Fukushima was considered unsafe for human habitation, and the researchers were quickly ushered back into the minibus. More than three years after Fukushima was exposed to massive radiation, the town was virtually silent. Houses, undamaged, were empty, with no sign of human life. Flowers bloomed in untended yards; cars parked in driveways waited for drivers who never came. The Geiger counter methodically measured the radiation in the ambient location, but what exactly did these measurements mean in terms of risk for human health? Since risk refers to a state that has not yet occurred, it cannot be measured directly in quantitative terms. Yet, judgments regarding risk are made by virtually everyone, every day, with costs and benefits experienced accordingly. Measuring risk requires a shift from conceptual assumptions to observable actions that can be measured. Identifying the threshold at which the shift from recognition of potential threat to when mitigating action occurs is central to

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understanding the dynamics of risk in any given context. This threshold is critical in assessing collective risk that affects whole communities. Most judgments regarding risk are based on thresholds of uncertainty that are considered acceptable to varying degrees. These thresholds of judgment vary with the degree of knowledge and experience gained from coping with damaging events in actual environments, allowing informed estimates of capacity to withstand an impending threat. Assessing risk systematically is practiced in virtually all professions—­ market analysis (Kerin and Peterson 2007); engineering (Moehle and Deierlein 2004); medicine (Kraisangka, Druzdzel, and Benza 2016); public policy (Dunn 2016); and meteorology (Okal, Fritz, and Sladen 2009). Yet all techniques are limited by constraints imposed by the range of existing knowledge and the organizational and technical systems used to collect data, analyze it, and convey information to others involved in risk situations. Consequently, the measurement of risk is necessarily limited to observable data that is further subject to uncertainty in its collection, analysis, and transmission to wider audiences. Identifying the constraints that characterize this risk detection process becomes an iterative task in a continuing search for credible indicators of potentially damaging events and a strategy for mitigating them. The task of measurement increases in complexity as systems in one area of the social environment interact with other systems to create a system of systems (Glass, Ames, et al. 2011) that can either escalate or reduce risk for the whole society. This process can be observed in the daily performance of electrical power distribution systems, essential to maintaining continuity of operations for most economic, social, and public functions in a community. For example, in the 2011 Tohoku earthquake, tsunami, and nuclear breach in northeast Japan, a major consequence was the lack of electrical power for businesses, transportation, hospital services, schools, community service agencies after the Fukushima Daiichi reactor was damaged and taken out of operation. Hundreds of thousands of people living in the tsunami-­and radiation-­affected prefectures of Miyagi, Iwate, and Fukushima in northeast Japan had to leave their homes because ordinary services were not available (Yomiuri Shimbun, Tokyo, March 11–April 4, 2011). This mass evacuation, in turn, affected other communities in Japan in terms of finding housing, jobs, schools, and medical services for the incoming evacuees. The nuclear breach triggered a cascade of disrupted societal functions in the entire nation that had not been anticipated nor included in any assessment of risk or carefully designed disaster plan. Such an event provides a basis for analyzing future hazards and risk. Risk observed and countered in any one system may generate new risk in adjacent or interdependent systems. As societies move increasingly toward large-­ scale sociotechnical systems to manage basic functions of transportation,

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communications, energy, water and wastewater distribution, health care, and economic exchange, interdependencies increase. The calculation of risk for single systems is often no longer valid, and the calculation of risk for complex, dynamic systems becomes exponentially more difficult (Roe and Schulman 2016). Measuring risk, in practice, aims to hit a moving target. The act of measuring changes the state of perceived risk at that moment, as the information obtained influences the next iteration of measurement. Using data from past events provides an observable baseline for identifying the limits of physical, social, economic, and organizational systems and indicators for systemic change under actual conditions at a given time. The limits identified in actual events, however, indicate the steps necessary to overcome them in a next iteration of risk reduction. Capturing this evolving process eludes standard measures of linear analysis. Signals and Boundaries in Complex Adaptive Systems A persistent question in systems analysis is how, where, and when to bound the system under study. Since in the vernacular of complex systems, “everything is connected to everything else,” it is essential to establish boundaries for the system under observation to confirm that the metrics being used are reliable for that system (Yin 2014; Brady and Collier 2010). But what exactly are the boundaries of a system in a changing, interdependent world? Bounding the system of interest is a necessary limit that allows a measure of rigorous assessment, if only to acknowledge that the measurement strategies available also have limits (Holland 2012). Establishing stated boundaries for a system in terms of time, space, scale, and energy, the initial conditions for its operation, allows the selection of measurement strategies that provide valid assessments within the specified boundaries. Each strategy may have limitations, but a mix of strategies that point in the same direction (Roe 1998; Dunn 2016) leads to reasoned confidence in the results. The challenge is that, over time, the boundaries of sociotechnical systems change, no matter how carefully they are specified (Glass, Ames, et al. 2011). Systems adapt, necessarily, to changing conditions in the environment, despite the rigorous methods applied to measure their previous state. In complex systems theory, the concept of state space or the status of the system at a given point in time and under a specific set of conditions acknowledges this evolving process, but allows the measurement of the components of the system and their interactions for that specific state, as the basis for the next phase in its development. Determining how, when, and under what conditions the state of the system changes encompasses the assessment of risk that is included in its adaptation to new conditions.

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Complex systems adapt to changing conditions by building hierarchies to organize knowledge and action as a mechanism for processing information from a dynamic environment (Holland 2012). This argument echoes Simon’s (1997) view of how humans organize information for decision making, given limited cognitive capacity. John Holland (2012), distinguished computer scientist and theorist of complex systems, focused on the structure of the system and how it responds to changes in the environment. The process evolves as the system encounters limits of existing knowledge and practice in novel situations. The system and actors within detect signals that may lead to new strategies, but cross known boundaries leading into unknown territories. For example, neighbors in an area exposed to seismic risk may detect new cracks in the walls of their homes. They begin to talk with one another about the cracks and ask a local engineer what might be causing the cracks. The local engineer then asks a geology professor at the local university to explain the cracks in the walls, and she, in turn, may organize a group to record and document the timing and occurrence of the cracks, leading to the identification of a splinter of an earthquake fault that had not previously been known. In the process of inquiry, the group of neighbors becomes a subset of a larger system that creates new knowledge and redefines existing boundaries to include new information. The new actors offer a better fit or more appropriate adaptation to the changed environment that acknowledges seismic risk. In adapting to change, complex systems develop mechanisms for processing information that constitute the link between knowledge and action. These mechanisms use the limits of existing knowledge as temporary boundaries for the system under study and seek to define “what we know” about the environment and differentiate it from “what we don’t know” (Ellingwood and Kinali 2009). The process of adaptation occurs over time, and systems that are subject to sudden shock, such as a major earthquake striking a metropolitan region, may not have sufficient time to absorb the range of disparate types of information and incorporate them in a coherent process (Thompson 1967). The result may instead trigger a cascade of failure as the same interdependencies that make a system function efficiently in stable environments also transmit dysfunction through missed connections, limited resources, and lack of experienced personnel. Anomalies in routine performance serve as signals for changing conditions and warrant further investigation and monitoring (King, Keohane, and Verba 1994). Although frequently dismissed as irrelevant in stable operating conditions, such signals indicate the uncertain area between what is perceived in the wider environment and what is missing in the system’s existing structure of operations. The signals transmit information to the system that, if understood clearly, support positive development toward a new configuration that adapts more effectively to changing conditions. If ignored or misunderstood,

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the signals may accrue to indicate increasing dysfunction within the system and its component subsystems. This study seeks to trace the flow of information through actual systems as it activates the cognitive energy that drives change. This assessment is grounded in real-­world situations as a critical check on a system’s capacity to function in actual environments. For example, the recovery in Nepal from the 2015 earthquakes was stalled for nearly a year because of a gasoline crisis precipitated by political conflict among ethnic groups over the designation of provinces specified in the new constitution, passed by the Nepali Parliament in July 2015. The Madhesi, the largest ethnic group in Nepal concentrated in the southeastern Terai region bordering India, argued that the provinces should be designated by ethnicity, rather than geography, which would give them a stronger voice in Parliament. When Parliament passed the constitution designating provinces by geography instead, the Madhesi protested vigorously. Their protests extended across the border into India, and sympathetic Madhesi in India blocked trucks hauling gasoline at the Indian border, seeking to aid ethnic kin in Nepal in their efforts to compel a reconsideration of boundaries of the provinces (Kathmandu Post 2015). Nepal has no gasoline resources of its own. All gasoline must be imported. The border with India is the primary entry point in this landlocked, mountainous country. Without gasoline to fuel transportation, the recovery plans could not move forward. The conflict over the constitutional designation of states in Nepal disrupted the communications among ethnic groups in Nepal and effectively halted recovery progress for a year. The signals of protest by the Madhesi group were not recognized in the parliamentary debates over designing the boundaries of the provinces as a risk of cutting off gasoline imports from India that would, in turn, stall the recovery process. The critical boundary for the economic system in Nepal extended beyond national borders, affecting the operation of the political subsystems within the nation. The rationale for using mixed methods in social science research is that complex problems are most effectively studied using analytical methods that address a problem from multiple perspectives (King, Keohane, and Verba 1994; Box-­Steffensmeier, Brady, and Collier 2010; Dunn 2016). Since no single method is definitive in studying social problems that involve changing conditions and actors, multiple methods used to measure change offer a more comprehensive assessment of dynamic issues such as risk. A Small N Comparative Study of Emergent Response Systems Following Earthquakes S

Searching for actual incidents when communities confronted risk, I conducted a series of field studies on the evolution of operational response systems following earthquakes over a period of 16 years, 1999–2015. This set of

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comparative case studies documents how 12 communities in nine different countries responded to risk and how the collective set of actors in each community translated their perception of risk into action during actual earthquake events. The studies provide a baseline for review of conditions that accelerate or reduce risk, rather than a direct measure of the changing dynamic of risk. Case studies have long been undertaken as a means of exploring what factors contributed to disaster events, and what insights could be gained from them to minimize risk of future disaster events. Research centers such as the Disaster Research Center, University of Delaware, and the Hazards Research Center, University of Colorado, organize and catalogue case studies of distinctive events, many supported by National Science Foundation quick/rapid response grants. Yet most case studies are undertaken for specific disasters and are not structured for comparative analysis. In contrast, the set of case studies presented in this study was framed with the same set of analytical questions and methods of data collection and data analysis to allow comparison of the emerging response systems following the same type of hazard, earthquakes, in 12 different communities. The case study approach allows the characterization of initial conditions, underlying assumptions, and types of actions that framed collective action in response to extreme events in 12 separate communities. Carefully analyzed, these findings from actual cases indicate parameters for modeling risk and potential strategies for reducing risk in future events (Yin 2014; Gilbert and Troitzsch 2005; Collier and Collier 2002). Importantly, case studies, grounded in actual contexts of organizations and jurisdictions responding to damaging events in regions of known risk, provide empirical evidence of key processes related to risk. Each study is characterized briefly by the initial conditions in which the earthquakes occurred. While the content of the initial conditions varies by country, the questions that frame each study are common across the 12 cases. The questions investigate the degree of recognition of seismic risk in the wider community; technical infrastructure available to support communication; organizational policies, procedures, and resources available for rapid mobilization of response operations in damaging events; and cultural frames of reference and values for coping with risk. These initial conditions reflect, roughly, the system’s capacity for adaptation under the demands of an actual event or, conversely, indicate the system’s limits under stress. These studies document each system’s known boundaries in responding to risk but allow the search for signals that cross those boundaries, leading to new mechanisms for identifying risk and managing change. In the previous study, I used a mix of analytical methods to identify systems of interacting organizations that engaged in response operations following earthquakes over the years 1985–95 (Comfort 1999a). Given advances in information technologies and theoretical concepts of complex adaptive systems, the current study presents a comparative analysis of response systems that

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evolved following major earthquakes over the years, 1999–2015 in fresh perspective. It redefines the set of research questions to focus on risk and incorporates process tracing, network analysis, and calculation of External/Internal (E/I) indexes as methods to study the evolving earthquake response systems. Specifically, this study traces changes in information flow through the networks of organizations engaged in response operations and their consequent adaptation in organizational performance to local contexts. Four basic research questions, stated in chapter 1, guide the investigation of the 12 cases and are restated briefly here: 1. What structures of sociotechnical design either facilitate or constrain the flow of information to anticipate and respond to varying degrees of risk? 2. What processes of information flow either enhance or inhibit the performance of a given system in practice? 3. What mechanisms, reflecting cultural values, are used throughout the system to correct error and update performance in alignment with a changing environment? 4. In what ways does information technology enhance or inhibit the recognition of, and adaptation to risk in changing environments? The 12 earthquakes that generated the response systems under study, listed by date and magnitude, are as follows:

1. Marmara, Turkey, earthquake, August 17, 1999 2. Chi Chi, Taiwan, earthquake, September 21, 1999 3. Duzce, Turkey, earthquake, November 12, 1999 4. Bhuj, Gujarat, India, earthquake, January 26, 2001 5. Sumatra, Indonesia, earthquake and tsunami, December 26, 2004 6. Pakistan earthquake, October 8, 2005 7. Wenchuan, China, earthquake, May 12, 2008 8. Padang, Indonesia, earthquake, September 30, 2009 9. Haïti earthquake, January 12, 2010 10. Tohoku earthquake, tsunami, and nuclear breach, Japan, March 11, 2011 11. Lushan, Ya’an, earthquake, China, April 20, 2013 12. Gorkha, Nepal, earthquakes, April 25, May 12, 2015

Mw = 7.4 Mw = 7.6 Mw = 7.2 Mw = 7.7 Mw = 9.2 Mw = 7.6 Mw = 7.9 Mw = 7.6 Mw = 7.0 Mw = 9.0 Mw = 6.6 Mw = 7.8, 7.3

Interestingly, 11 of the 12 earthquakes included in this study occurred in Asia, showing the strong seismic activity that characterizes the Ring of Fire or the circle of tectonic fault lines that runs down the western coasts of the Americas, crosses the Pacific Ocean to New Zealand, turns north to Indonesia, crosses India, China, and Japan, and turns back to Alaska. Four pairs of earth-

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quakes occurred in successive events in the same nations during this period of 16 years, 1999–2015. Two earthquakes occurred in Turkey four months apart in 1999. Two earthquakes occurred in Indonesia, the 2004 earthquake on the Great Sumatran fault that generated massive tsunami waves, severely damaging Aceh Province, and further rippled across the Indian Ocean, and the 2009 earthquake in the Mentawai Sea affecting the city of Padang. India was struck by two seismic events, the Bhuj, Gujarat, earthquake of 2001 and the consequences of the 2004 Sumatran tsunami on India’s southeastern coast. China experienced two earthquakes in Sichuan Province, 2008 and 2013. Further, the earthquakes in Turkey and India were preceded by earthquakes in the previous decade (Turkey in 1992, and India in 1993). Japan was struck by a severe earthquake in the Hanshin region in 1995, only 16 years prior to the Tohoku triple disaster in 2011. Although the 2004 Sumatran earthquake and tsunami struck 12 nations that border the Indian Ocean, and analyses of response operations were done in four severely affected nations—Indonesia, India, Sri Lanka, and Thailand—only the Indonesian case is included in this study. Indonesia was the most severely affected nation in the Sumatran event with an estimated loss of over 237,071 lives (Pomonis et al. 2005). The distribution of earthquake response systems listed above shows a recurring pattern of seismic risk in Asia, where 60% of the world’s population is concentrated. Also noteworthy, but perhaps coincidental, is that the severity of the 12 earthquakes listed as occurring in the 1999–2015 period is higher, with the exception of the Mexico City event, than the 11 earthquakes reported from 1985 to 1995 (Comfort, 1999a). The Bhuj, Gujarat, India, earthquake was initially reported at Mw = 6.9 by the Indian Meteorological Department, but this magnitude was later revised to Mw = 7.7 (EERI 2001). Eleven out of 12 earthquakes in the 1999–2015 list registered over Mw = 7.0, whereas the 8 out of 11 from the earlier set registered less than Mw = 7.0 (Comfort 1999a). These findings confirm that the response systems mobilized for the period 1999–2015 confronted arguably more severe disruption of their respective communities, escalating the demand for coordinated action in urgent events. Field studies were conducted after each of the 12 earthquakes, but at different phases in mobilization of operations in response to the event and its impact on the affected community. Eight field studies were conducted within weeks of the precipitating earthquakes, and from these initial studies, all eight led to continuing studies on managing risk with local researchers in the earthquake-­affected regions. Four of the field studies—Pakistan, Lushan, Tohoku, and Nepal—focused on recovery processes after the event and offered an opportunity to assess how communities that had experienced severely damaging events recovered from them, and how key personnel viewed the recovery and its state of resilience to recurring risk. Assessing the performance of operational systems at different time phases in exposure to seismic

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risk reveals different patterns of action and interaction occurring among the actors involved. Determining how, when, and where the information flows among the components in urgent events reveals the strengths and weaknesses of the systems. Data Sources Three primary types of data were collected for each response system included in the study period 1999–2015, creating a consistent set of data sources for the set of 12 disaster response networks over 16 years. Data from these sources were analyzed for each response system, using methods appropriate for the respective periods of study. The types of data are as follows: Documentary reports. These reports largely characterize the official governing system and context in which the earthquake occurred and provide basic information regarding the initial conditions in which the response system emerged. These data include the existing laws, policies, plans, and procedures that govern the mobilization and operation of an emergency response system within each nation. The reports also include documents from the United Nations Office for the Coordination of Humanitarian Assistance (UN OCHA), which has the responsibility to facilitate humanitarian assistance offered from UN member nations to a disaster-­afflicted UN member nation. Documentary data include official reports of national agencies with legal responsibility for protecting life and property and for maintaining continuity of operations in disaster environments regarding the status of risk perceived prior to the earthquake event and actions taken in response to the actual event. Newspaper reports. News reports were gathered from the leading local newspaper in each major city where the earthquake occurred for the first three weeks following the event. The first three weeks largely covers the period of immediate response operations and the transition to recovery for the affected community. These reports, while not comprehensive, nonetheless provide a daily record of actions reported on the state of disaster operations and include accounts of actions taken by private and nonprofit organizations as well as public agencies with designated responsibilities for emergency operations. Content analysis of these reports is used to identify the networks of interacting organizations that participated in emergency response operations for three weeks following each seismic event and provide a check on the official plans established prior to an earthquake event. The local newspaper used as the source of network data is cited in the brief characterization of each of the 12 cases. On-­site field observations and semistructured interviews. Field studies were conducted on site following each of the 12 earthquakes in collaboration with local researchers who knew the native languages and were familiar with the

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historical and political context of governmental operations. These studies included semistructured interviews with responsible managers involved in disaster response operations from public, private, and nonprofit organizations. The local perspective is vital in each case to interpret the positions of key actors as they adapt and change in response to the disaster environment. The data collected from both semistructured interviews and direct observation are essential for validating findings from other sources and providing a cross-­ check on conflicting sources. Analytical Methods Data from the three types of sources listed above have been reviewed, using a common set of research questions for all 12 response systems (Yin 2014). These data are analyzed using relevant methods for each type. Since each data source provides only a partial account of the complex set of disaster operations for the events under study, mixed methods are used to analyze and validate data from at least three sources regarding the same event. In a classic technique of policy analysis, this strategy triangulates data from different sources to arrive at the most consistent and valid account of the 12 cases under study (Roe 1998). Five analytical steps are presented for each case as outlined below. Initial conditions. A brief profile of initial conditions for each of the 12 earthquake response systems provides a baseline characterization of the state of each system prior to the earthquake event. This characterization includes an estimate of the collective recognition of risk in the community, as evidenced through existing policies and procedures enacted in managing extreme events, as well as programs of public education regarding seismic risk. The profiles also include a brief chronology of key decisions made regarding seismic risk for each case to capture the time frame of the decision process, with attendant allocation of resources and attention to managing that risk. These profiles outline the initial boundaries for each system of risk management and identify preliminary signals of challenges to those boundaries. They provide brief accounts of the context for each response system that allow a preliminary classification of the 12 cases by their capacity for adaptation to extreme events. While these profiles are not intended to provide a detailed assessment of physical, engineered, technical, economic, social, and political subsystems operating in the contexts in which the 12 extreme events occurred, they do identify limits of the local subsystems and the consequent impact of those limits on the capacity of the respective communities to adapt to a sudden, urgent event, such as an earthquake. Documentary analysis of formal plans. Documentary analyses of laws, policies, and official programs designed to reduce risk prior to an actual earthquake outline the organizational structure that characterized each of the 12

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cases. These documents include national disaster laws, if any, and represent the state of risk awareness in the community. They identify the existing boundaries of the systems—social and technical—that could be mobilized for action in response to an actual seismic event. This analysis outlines the formal process for decision making regarding seismic risk for each of the 12 cases and establishes a baseline of capacity for action in response to actual events. This analysis relies on the method of process tracing (George and Bennett 2005; Bennett and Checkel 2015) to elucidate the logic of decisions outlined in formal documents, such as emergency plans, prior to an earthquake. Process tracing identifies the intermediate steps in decision making to determine whether they lead to the intended outcome (Bennett and Checkel 2015, 5–7). This method is useful in assessing asymmetry in decision processes among agencies operating at different levels of authority or jurisdiction in a large, complex, system of systems evolving after a disaster event. Indications of asymmetry in performance, in turn, signal potential weaknesses in the boundary of the system and points of possible adaptation. Network analysis. To capture the actions taken in the context of the actual events, content analyses were conducted on news reports collected from local newspapers for three weeks following each of the 12 seismic events. Also included in the content analyses are professional reports documenting the effects of the earthquakes from experienced observers in different disciplinary fields. The content analyses identified the set of organizations actively engaged in disaster operations by jurisdiction and funding sector. Coding the news reports to identify the organizational networks required specifying a set of assumptions that served as rules to define the boundaries of the network operational systems. News articles reported actions that were taken by organizations, identifying them by name, but did not always specify which organization initiated the transaction or the direction of the interaction. The rule adopted for coding interactions reported in the news reports identified the first named organization as the initiating organization interacting with other organizations named in the transaction, but other organizations named in the same report were not necessarily interacting with one another. This assumption was made to set boundaries for the network, given the information available and based on observation of actual field operations. The assumption differs from the logical identification of all possible interactions among actors in a network (Wasserman and Faust 1994) and restricts the identification of interactions to those reported for the first-­named actor engaging with another actor or actors in a collaborative task as a more realistic profile. The coding was done initially after each earthquake event over the 16-­year period, 1999–2015, but all 12 data sets were reviewed and recoded in a common format for the analyses presented in this study by a coding team of graduate student researchers at the Center for Disaster Man-

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agement, Graduate School of Public and International Affairs, University of Pittsburgh.2 The data sets resulting from the content analyses provide an approximate profile for each of the 12 operational systems, allowing assessment of the frequency, number, and types of transactions performed by, and among, actors engaged in response operations. While the content analyses are based on secondary information and are necessarily incomplete, they represent an approximate characterization of each response system that reveals a measure of collective awareness of seismic risk in the 12 affected communities, as reflected by actions taken and degree of adaptation demonstrated by each emergent operational system in response to an actual event. Three types of network measures are presented for each case study: (1) frequency distributions of organizations engaged in response operations by jurisdiction and funding sector; (2) frequency distributions of types of transactions performed by organizations included in the identified response system; and (3) network analyses of interactions among organizations in each response system, measured by betweenness centrality to identify nodes that played bridging roles among other nodes active in the system and to assess the degree of cohesion or fragmentation within the system. Betweenness centrality measures the extent to which a given node in a network connects two other nodes that would not otherwise be connected (Wasserman and Faust 1994, 189–91). Thirty types of transactions performed in disaster operations were culled from news reports of transactions reported for the 11 earthquake response systems included in Shared Risk (Comfort 1999a). Validated in the 1999 study, this same list of transaction types was used for the initial coding of transactions for the 12 earthquake response systems included in the current study. In addition to the basic frequency distributions and network analysis measures, an External/Internal index (E/I index) (Krackhardt and Stern 1988; Tortoriello and Krackhardt 2010) was calculated for each operational system to show the proportion of organizations at each jurisdictional scale that crossed legal and funding sector boundaries in conducting response operations in comparison to those that did not. An E/I index is a measure of cohesion for the whole system, or conversely, a measure of disconnectedness among the actors operating within a system seeking to achieve a specific goal, for example, resilience to seismic risk. The measure distinguishes the degree of connectedness among organizations that are operating within a designated jurisdiction or sectoral group in a larger system from those that are interacting with organizations external to their group. The equation is defined as E/I index =  Ei – Ii Ei + Ii

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where Ei represents the number of external ties and Ii represents the number of internal ties among components in the operating system. The index ranges from +1.0 (when all ties to/from i are external to the group) to −1.0 (when all ties to/from i are internal to the specific group). The midpoint, 0, represents the rare case when the number of internal ties equals exactly the number of external ties (Tortoriello and Krackhardt 2010, 173). In a disaster environment, actions taken to seek external assistance serve as important signals that the existing system cannot meet the demands of the disaster alone but requires outside resources and support to perform its operational functions. The frequency and duration of these cross boundary signals point to a potential shift in the whole response system to meet the demands of the disaster environment, likely leading to a reconfiguration of relationships within the network. Such a shift in interactions among the components could lead a transition to a new mode of operations for the system, or conversely, return to previous patterns of performance, once the crisis is past. The extent to which the system is transformed by the disaster into a functioning system more attuned to the risk perceived in its environment represents a more resilient, sustainable community. To corroborate the documentary and content analyses, I conducted on-­ site field investigations in conjunction with local researchers for each of the 12 cases. The site visits included semistructured interviews with official personnel responsible for disaster operations in face-­to-­face meetings conducted in local languages, as well as with managers of nonprofit organizations participating in disaster relief and recovery activities. In most cases, I also interviewed representatives from business organizations who were involved in disaster operations. Often private organizations donated services as well as funds and in some instances played critical roles in providing heavy equipment for debris clearing or communications systems to aid communication, as well as timely satellite imagery of disaster-­stricken areas. The expert interviews served two key functions. First, they provided an important validation check on information gathered from secondary sources and filled in missing steps in actual operations not covered in the news or agency reports. Second, they offered added insight into the novel aspects of disaster operations, as well as the barriers that managers encountered in physical, technical, organizational, or cultural constraints in the actual conduct of operations. Resource limitations were considered under organizational constraints, as they inhibited action. Data from field interviews contributed to two sets of findings: (1) a chronology of key decisions that marked turning points in the evolution of the disaster response system; and (2) identification of discrepancies between the initial recognition of risk in the community, as documented by official plans, and the community’s capacity to act as a system, as reported in news reports

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of actions taken. The news reports provide at least a partial record of the flow of information among organizations in the operational context of each event. The network diagrams of betweenness centrality for the top 20 actors operating in each response system offer a visual representation of actual interactions among participating organizations, in contrast to formal plans for managing risk that existed prior to the earthquake. The discrepancy between the formal plans, which show the existing level of awareness of seismic risk, and reported operations reveals the areas where new knowledge needs to be created to reduce uncertainty in future disaster operations. Bayesian techniques (Druzdzel 2009; Lu and Druzdzel 2009; Lin and ­Druzdzel 1999; Druzdzel and Simon 1993) combine findings from the documentary analyses and expert interviews conducted for the case studies to produce plausible models for strategies of reducing risk in future seismic events. While Bayesian modeling is not included in this analysis because of constraints of space and scope, the method is very relevant to assessing partial or conditional uncertainties. For example, seismologists acknowledge with certainty that the movement of the earth’s tectonic plates will continue to generate earthquakes along major fault lines (USGS 2016b), although they cannot predict exactly when or where the next earthquake will occur. With this category of partially identified risk, that is, “knowing what we don’t know,” even partial identification of interacting conditions decreases uncertainty proportionally and would increase the collective capacity of metropolitan regions, viewed as complex adaptive systems, to manage seismic risk in more informed, less costly ways. Guidelines for Comparative Analysis The challenge of conducting informative case study analyses is to identify the factors that are common to a specific set of cases, while acknowledging the distinctive differences among the cases (Yin 2014; Brady and Collier 2010). In addition to the four basic research questions stated for the whole study, five more detailed questions are posed for each response system. Characterizing each response system by these five questions allows a more detailed comparison by focusing on the internal components and interactions within each system. The questions are as follows: 1. What organizations actively engaged in response/recovery operations, and when did these organizations enter the response system? 2. What types of transactions and mechanisms of information flow characterized the interaction among the participating organizations? 3. What was the rate of change in the operations system over the 21-­day period in transition from response to recovery?

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4. What were the major gaps in performance for the operations system, in contrast to the affected community’s stated goals for managing risk? 5. To what extent did the major organizations in the affected community become integrated into a coherent system of systems, capable of sustainable resilience in managing risk? Using mixed methods of documentary analysis, network analysis, and calculation of E/I indexes, this study explores the processes of change, adaptation, failure, and renewal demonstrated in the set of 12 earthquake response/ recovery systems operating in different technical, organizational, cultural, and socioeconomic contexts over the years 1999–2015. This analysis includes assessment of the changes in information technology used by organizations participating in response operations over this 16-­year period. Although this study acknowledges and builds on findings presented in Shared Risk (Comfort 1999a), it asks different questions regarding the set of 12 operational systems that evolved following earthquakes during the years 1999–2015. Specifically, it inquires whether new signals that indicate changing perceptions of risk can be identified in the profiles of the 12 earthquake operations systems, and, if so, at what point do the known boundaries of the system expand or contract? This analysis searches for thresholds of action that may have changed with new technologies for communication and coordination and inquires whether these technologies altered conditions for interaction among the participating organizations. It seeks to push back the boundaries of knowledge regarding the evolution of interacting, interdependent processes that characterize action in complex adaptive systems, expanding the proportion of knowledge available about risk, while shrinking the proportion that is unknown. Chapter 4 explores the context in which these methods and measures are used to assess risk in practice.

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4 Risk in Practice

Designing Networks of Action Using handheld electronic tablets programmed in French, engineering students at l’Université Quisqueya and l’Université d’Etat d’Haïti assessed the structure of buildings in Port-­au-­Prince, Haïti, according to building codes defined by an international group of engineers organized under the rubric of the Global Earthquake Model (GEM). Guided by a research team from the University of Pittsburgh, the Haïtian students quickly mastered the techniques of recording structural data on tablets, and uploading the data to a server housed at a university over 1,500 miles away.1 The intent was to create a knowledge base for neighborhoods in Port-­au-­Prince damaged by the 2010 earthquake, using resources and support given from humanitarian sources, to assess the stability of the buildings before a potential seismic shock threatened the city again. Students at the three universities undertook this project more than two years after the January 12, 2010, earthquake shattered Port-­au-­Prince, guided by a shared goal of recovery to rebuild the city in stronger, more sustainable ways. Having experienced the devastation of the 2010 earthquake, the Haïtian students and their faculty mentors were acutely aware of the risk posed by unsafe buildings. Translating that awareness into action for the benefit of the community was the larger task. Given the range of uncertainty that characterizes seismic risk, communities with known exposure seek to reduce the potential impact of the hazard on their communities through planning processes that involve varying degrees of specificity and acceptance by the residents. Communities differ in their capacity to recognize potential hazards and mobilize response and recovery operations for extreme events in practice, as the 12 cases presented in this study vividly illustrate. Clearly, the initial condi-

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tions in each community set the trajectory for an emerging system of response and recovery operations. Not so clear are the specific conditions that activate this process in each community or how those conditions interact to produce a distinctive pattern of collective action to meet the demands of an immediate disaster and lessen the risk of recurring losses in future events. Specifying the basic concepts of time, space, scale, and energy as material conditions that characterize a given community and its capacity to recognize risk and respond in effective action before a damaging event occurs means identifying the signals of risk for that community, as well as defining the boundaries within which an emerging system can function. Traditionally, these concepts have been embedded in most risk-­reduction processes. Time, for example, is conceived as a chronological, linear metric by which to order tasks to achieve desired outcomes. Space is considered as physical terrain, a geographic location with specific attributes that amplify or minimize risk. Scale indicates a method of allocating authority, tasks, personnel, and resources at graduated levels to fit a defined goal. Energy is often construed as money to drive interaction among individuals, organizations, and systems. Using these basic concepts in a traditional framework leads to the development of hierarchical organizations with well-­ordered plans for action in well-­ defined operational contexts. Risk conditions, however, largely defy such well-­ordered plans, and the actual conditions of emergency operations are more uncertain, more interactive, and more dynamic than anticipated. While planning for potential hazards is a useful exercise, it cannot serve as the only guide to action in rapidly evolving extreme events. As communities identify the probability of hazards, they develop networks of action to cope with that risk, adapting their practices if or when extreme events occur. Networks challenge hierarchical organizations by defining a common goal or a specific problem to be solved and redefining all four basic concepts of time, space, scale, and energy governing operations around that goal. The goal sets the boundaries of the network, not standard administrative jurisdictions or geographical limits (Churchman 1971). Networks operate at multiple levels within a broad area of interaction, for example, seismic risk, that constitutes its operational domain (Thompson 1967). Within that domain several task environments focus on specific activities (Thompson 1967), such as implementing building codes or establishing seismic monitoring systems, that identify actions needed to adapt to seismic risk. In a complex system of networks, information, rather than money, drives interaction among the component actors and serves as its fundamental energy source (Smith 2008a). Change is facilitated by a technical information infrastructure that enables simultaneous transmission and exchange of information among multiple audiences over geographic distances in near-­real time. This change in the capacity to transmit, receive, store, and analyze information, in turn, transforms other conditions of operations for the network.

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Time, altered by simultaneous transmission and exchange of information among multiple actors, is no longer confined to a chronological record but takes a new form when multiple actors receive the same information at the same time (Stalder 2006). Manuel Castells (2009, 33–36), a sociologist writing about networks, noted this marked shift in the perception of time in networks and termed it “timeless time.” A more accurate term may be “concurrent time,” as actors in the network take concurrent action based on common information. This shift in the concept of time significantly redefines the space and scale at which collaborative action can occur. The network is no longer bound by geographic limits, as information activates actors in multiple geographic locations simultaneously. A new concept of space emerges as the space of flows that is created and supported by the search and exchange of information (Castells 2000, chap. 6). In this space, other functions that support a complex society are enabled by a technical information and communications infrastructure, for example, financial transactions that occur in global economic markets, or airline scheduling among multiple airlines serving hundreds of cities globally, or online education courses connecting faculty and students in multiple venues at the same time in different physical locations. This new space of information exchange, however, creates new risks for the participants in these networks that, unrecognized, may either exacerbate or mitigate known risk, such as seismic threats in metropolitan regions. Interaction between the redefined concepts of space and time further generate a broader concept of scale, that is, the different levels of authority and action needed to address risk generated by large, complex, sociotechnical systems. As the flow of information extends to different types of physical and virtual space, the boundaries of the problem addressed also expand. The task of carrying out substantive action to minimize risk in complex, interacting conditions becomes a global problem, with different functions identified for different levels of performance operating under different jurisdictional authorities. Seismic risk, a global problem, needs to be addressed by multiple actors at varied levels of authority who act collaboratively in different locations. As the impact of an earthquake escalates from a local community with specific resources and vulnerabilities to a wider region that includes the flow of people, goods, and money via transportation and economic networks, the evolving system leads to national and global operations. For example, when the earthquake struck the small town of Chi Chi in rural Nantou County, Taiwan, on September 21, 1999, it disrupted communications and transportation infrastructure in the capital city of Taipei, 223 kilometers distant. In turn, these breakdowns halted the manufacture and shipment of components to the computer industry in Silicon Valley, California (Taipei Times September 1999), threatening to disrupt a global economic supply chain that had negative consequences for both California and Taiwan.

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As the number of interconnections among networks increase, the system becomes more complex, uncertain, and vulnerable to failure (Simon 1997; Fligstein and McAdam 2012). Managing operations to address seismic risk requires a reconsideration of operations at multiple scales, each of which needs information from other scales to perform effectively. To illustrate this global chain of interconnections, sales of Ford and Chrysler automobiles in the United States were restricted following the March 11, 2011, Tohoku, Japan, disasters, when the Onahama plant near the Fukushima Daiichi nuclear reactor that produced the specialty pigment Xirallic, used in red and black paints for their vehicles, was shut down (Dawson 2011). Coordination across multiple scales of operation can only be accomplished through the uses of information technology (Castells 2004). Without a continuing flow of information among all scales of operation, interconnections among the actors weaken, decision makers flounder, and the risk of error increases (Simon 1997). The emergence of networks under conditions of uncertainty is a recurring phenomenon that is apparent in each of the 12 case studies of disaster operations following earthquakes. Networks are not contradictory to formal disaster plans; rather, informal networks form out of experience, knowledge, and interactions among actors who share the common goal of protecting the community from harm (Stalder 2006). To the extent that the shared goal articulated for the informal networks aligns with the goal expressed for the public interest, the networks complement the formal plans implemented by public authorities. In the immediate aftermath of a disaster, the goal is clear; it is to save lives, protect property, and maintain continuity of operations for the community. Before the disaster, the shared goal may not be so clear to different actors in the community. Yet, it is in this period prior to a hazardous event that risk, if recognized, can most easily be addressed (Comfort 2007b). Before an earthquake occurs, the task confronting the community focuses on inquiry, discovering who and what exactly are threatened, to what degree, and what options are available for collective action (Churchman 1971; Comfort 1999a). It means detecting anomalies in routine performance of organizations and operating conditions and reading signals that indicate potential weaknesses in existing functions or possibilities for constructive change (Holland 2012). The capacity to recognize potential hazard before extreme events occur, when it is still ill defined, is greatly facilitated by technical devices, such as accelerometers to measure seismic movement or tide gauges to measure changes in sea levels. Such devices used to collect, aggregate, store, and analyze data from different sources provide decision support to organizational actors engaged in managing risk. Designing networks to identify and measure risk in large-­scale, complex systems is fundamentally a sociotechnical task, involving not only the technical systems used to perform the measurements, but also the organizational systems that manage the technical systems as well as the cultural norms used to interpret and give meaning to the results (Comfort 2007a).

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Networks in Practice The actual performance of emergency operations systems following an extreme event represents a practical test of the community’s ability to recognize hazards and take mitigating action to reduce potential damage and losses. In each of the 12 cases analyzed in this study, awareness of seismic risk existed at some levels in the society, but not all. Awareness of seismic risk was, in many cases, asymmetrical, with knowledge concentrated in scientific or technical circles limited to small groups of professional personnel, but not transmitted to the wider population. The disconnected segments of the societies were unaware, surprised, and suffered disproportionately in the actual earthquakes. These differences in operational performance in response to sudden seismic shocks reflected different baselines of capacity for the societies in question. Adaptation, in practice, requires an integration of at least three dimensions of performance by operational systems: technical, organizational, and cultural (Comfort 1999a, 64–67). The baseline performance of the operational systems included in this study differed along the three dimensions cited above. Under each dimension, a set of indicators identifies characteristics that may affect, to differing degrees, the operational system’s capacity to adapt to sudden seismic shock. This set of initial conditions serves as the starting point for adaptation in each operational system, influencing the rate and direction of change both among units within the system and between the system and its external environment. Other researchers have similarly examined this process of adaptation to extreme events and have added other measures, such as economic (Bruneau et al. 2003), or political (Boin et al. 2005), but these additional measures are largely subsumed under the technical, organizational, and cultural dimensions listed above. Seeking to focus on fundamental dimensions that allow classification of actual response operations in preliminary categories of adaptation, I return to the categories of adaptation developed in my earlier study (Comfort 1999a). Table 4.12 presents a set of indicators that represents different degrees of performance on technical, organizational, and cultural measures regarding seismic risk. This set of indicators is presented in a revised, updated list below. For each of the three classes of indicators—technical, organizational, and cultural—five key criteria are identified as essential for performance within that class. These criteria are used to rank the 12 operational systems by ordinal categories of high, medium, and low. These subsets of performance criteria are not exhaustive for any class but rather represent major characteristics of baseline performance within that class. The rough classification of high, medium, and low performance acknowledges the variation in initial conditions among the 12 operational systems that affected the trajectory of their respective operational systems. The subsets of criteria are qualitative but based on the informed judgment of practicing emergency managers active in the 23 case studies.

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High

Assessment Indicators for Earthquake Response Systems

Facilities vulnerable to seismic risk identified; alternative plans for operation prepared

National disaster response plan

Legal authority for emergency response adopted; specification of responsibilities across jurisdictional levels to mobilize response operations, when needed

Dimension: Organizational Flexibility

Critical infrastructure

Dimension: Technical Structure Assessment of seismic risk Probability assessment of seismic hazards in region conducted by professional seismologists, engineers; findings of known risk widely circulated Building codes Legally enforced codes calibrated to seismic risk, consistent with international standards Geotechnical analysis Geotechnical analysis legally required prior to construction of buildings, bridges, roads Communications infra­ Advanced information infrastructure is in structure place; alternative capabilities identified in event of an earthquake

Indicators

TABLE 4.1.

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Legal authority for response adopted, but not implemented; specification of responsibilities across jurisdictional levels to mobilize response operations is lacking

Geotechnical analysis recommended but not required prior to construction of buildings, bridges, roads Medium capacity in information infrastructure among emergency services; no alternative capabilities identified Facilities vulnerable to seismic risk identified; no alternative plans for operation developed

Codes calibrated to seismic risk, legally adopted, but not enforced

Partial assessment of seismic hazard in region; findings of known risk not widely circulated

Medium

Little to no established legal authority for disaster response; little to no specification of responsibilities across jurisdictions to mobilize response operations

Little to no identification of facilities vulnerable to seismic risk or degree of likely disruption to community, if compromised by an earthquake

Little to no assessment of probable seismic hazards in region; little communication of known risk to relevant audiences Little to no adoption of building codes, or, if adopted, little to no enforcement Little to no geotechnical analysis prior to construction of buildings, bridges, roads Basic capacity among emergency services; no alternative capacities identified

Low

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Correction of error

Monitoring procedures

Collaboration

Information exchange

Shared values

Dimension: Cultural Values

Information infrastructure

National knowledge base

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Corrective actions taken only when mistakes are identified within organizational and/or jurisdictional working groups

Little to no practice of sharing knowledge concerning risk or resources among organizations, jurisdictions, or citizens; few feedback loops among actors Little to no prior experience of collaboration in solving common problems; limited information search, exchange among organizations or jurisdictions Little to no search for anomalies in practice; little to no systematic records of operation, dependencies on other organizations, jurisdictions Little to no willingness to review actions taken or to correct mistakes to prevent future failures

Exchange focused primarily within organization or within jurisdictions, moderate exchange with organizations outside neighboring actors; limited feedback loops Willing collaboration within organizaOpen to new approaches, willing to work, tion and/or jurisdiction; reluctant engage with other organizations, jurisdiccollaboration outside known group tions to achieve shared goals of actors Clear procedures for review, revision, redeReliance on observation of error as it sign of actions taken in disaster operations occurs; no systematic procedures for error detection Error perceived as opportunity for learning; mistakes acknowledged, corrected; iterative search for relevant signals of probable risk; emergence of resources to protect community

Little to no value placed on public and/ or community interest

Little to no communication within or between organizations and jurisdictions regarding seismic risk; few feedback loops established in daily operations

Little to no common knowledge regarding the risk, possible consequences; or criteria for action in seismic events

Focus on commitment to goals of organization, profession rather than to whole community

Commitment to humanitarian goals—­ protection of life, property, continuity of operations—­for all members of com­ munity Access to new information readily sought, accepted from valid sources; established feedback loops within, among organizations

Identification of major actors, potential risks, Partial identification of major actors, incomplete assessment of potential resources to support organizational rerisks, resources, consequences for sponse, consequences for communities communities at risk at risk from seismic events Identified pathways of information exchange Major pathways of information exchange within and between organiwithin and between single organizations, zations, jurisdictions identified; renetworks of organizations; and jurisdicsponsibility for action in tions responsible for action in emergenemergencies, major feedback loops cies; feedback loops within, between orgaidentified nizations

66 C H A P TER 4

The rationale for using a set of indicators with at least three dimensions is to capture the interdisciplinary basis on which judgments are made regarding seismic risk, and to indicate the extent to which these judgments are consistent across jurisdictions and sectors of the population exposed to risk. These indicators allow a preliminary classification of actual response systems that evolved in 12 communities that have experienced earthquakes since 1999, and they reveal how the initial conditions of knowledge, recognition, investment, and preparedness for seismic risk set the trajectory for the evolution of response systems to damaging earthquakes. Such response systems are distinctively sociotechnical. If the system is lacking in any one dimension, it affects the performance of the whole system. Preliminary Classification of Twelve Earthquake Response Systems, 1999–2015 In Shared Risk (Comfort 1999a), the set of indicators for technical, organizational, and cultural characteristics was developed to classify, roughly, the initial conditions of the societies at the time the earthquakes occurred. These initial conditions served as a baseline against which to assess the different patterns of performance among 11 earthquake response systems that evolved over the period 1985–95. In the current analysis, indicators for the technical, organizational, and cultural dimensions are reassessed to determine whether the same basic classification schema is valid for the set of 12 operational systems that emerged in response to earthquakes during the years 1999 to 2015. Accepting the earlier set of indicators as largely valid for the later period, a preliminary classification of the 12 response systems included in this study is listed below. This classification is based on indicators of network assessment listed in table 4.1, applied to a review of documentary data regarding the operational context of the 12 response systems. The influence of some indicators, such as communications infrastructure under the dimension of technical structure, has changed significantly during this period, and the interaction of this indicator with other indicators under the dimensions of organizational flexibility and cultural openness affect the overall performance of the operational networks that emerged following specific earthquakes. Interestingly, the technical dimension does not always lead to stronger performance in organizational flexibility and cultural openness, as engineering studies would assume (Moehle and Deierlein 2004). Although the Turkey response systems demonstrated relatively strong characteristics in the technical dimension, such as the existence of modern building codes and seismic standards under National Disaster Law 7269, these strengths were offset by weaknesses in organizational performance and cultural awareness in the Marmara response system (Comfort and Sungu 2001a, b). Recognition of the serious weaknesses of the Marmara response led to some measures of improve-

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ment in the Duzce operational response system, only three months later. The surprising cases are the Tohoku, Japan, and the Nepal response systems. The Tohoku system exhibited high technical structure, the only system out of the 12 cases to do so, but low/medium organizational flexibility and low/medium cultural openness, which limited its performance in response to both the tsunami and the nuclear disasters. Nepal, a small, economically limited country, nonetheless, showed relatively high technical capacity in its urban areas, but low technical capacity in rural areas, low to medium organizational flexibility, and low to medium openness to cultural change. These preliminary classifications reveal the complex interdependencies among technical, organizational, and cultural characteristics in the evolution of response systems as measures of the respective communities’ capacity to recognize and reduce seismic risk. Classes of Adaptation In Shared Risk (Comfort 1999a, 68–74), four classes of sociotechnical adaptation characterized the different patterns of performance among the 11 response systems included in that study. A similar set of four classes of adaptation follow from the classification schema listed in table 4.2, as applied to the 12 earthquake operational systems included in this study. The classification schema reflects the same goal of moving toward self-­organizing, auto-­adaptive systems in which all residents of a community at risk take an active role in minimizing risk for the benefit of the whole community. The four classes of adaptation for the set of earthquakes included in this study are listed in table 4.3, with a preliminary assessment of the 12 operational systems on this continuum.

TABLE 4.2. Preliminary Classification of 12 Earthquake Response Systems Based on Technical, Organizational, and Cultural Dimensions, 1999–­2015

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Response System

Technical Structure

Organizational Flexibility

Cultural Openness

Bhuj, Gujarat, India, 1/26/2001 Sumatra, Indonesia, 12/26/2004 Haïti, 1/12/2010 Wenchuan, China, 5/12/2008 Pakistan, 10/8/2005 Chi Chi, Taiwan, 9/21/1999 Marmara, Turkey, 8/17/1999 Duzce, Turkey, 11/12/1999 Padang, Indonesia, 9/30/2009 Lushan, China, 4/20/2013 Gorkha, Nepal, 4/25/2015 Tohoku, Japan, 3/11/2011

Low Low Low Low Low Low/medium Low/medium Low/medium Medium Medium Low/high High

Low Low Low Low Medium Low/medium Low Low/medium Low/medium Medium Low/medium Low/medium

Low Low Low Low/medium Low/medium Medium Low Medium Medium Medium Low/medium Low/medium

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TABLE 4.3.

Classes of Sociotechnical Adaptation by Earthquake Response Systems, 1999–­2015

Nonadaptive Systems

Emergent Adaptive Systems

Operative Adaptive Systems

Toward an Auto-­ adaptive System

Bhuj, India, 2001 Sumatra, Indonesia, 2004 Haïti, 2010

Marmara, Turkey, 1999 Chi Chi, Taiwan, 1999 Pakistan, 2005 Wenchuan, China, 2008

Duzce, Turkey, 1999 Padang, Indonesia, 2009 Tohoku, Japan, 2011 Nepal, 2015

Lushan, China, 2013

None of the response systems in this set of 12 fully meet the characteristics for auto-­adaptive systems, but all show some signs of adaptation and appear to be moving in that direction, some more than others. In each of the sets of paired earthquakes—Marmara and Duzce, Turkey; Sumatra and Padang, Indonesia; Wenchuan and Lushan, China—the response systems moved toward greater adaptiveness in the nation’s second event over short periods of time. In contrast, the Tohoku system appeared to recede in adaptiveness from earlier performance in the 1995 Hanshin earthquake (Comfort 1999a), under the harsh onslaught of the 2011 triple disasters. Most interesting is the case of Nepal, which showed strong characteristics of adaptation immediately after the earthquake, but regrettably stalled seriously in the transition to recovery, largely because of an adverse external relationship with its neighboring country India. Each of the four classes of adaptation warrant further explication, given the contexts in which the earthquake response systems evolved. Lushan, China, although it experienced a less severe earthquake in 2013 than the Wenchuan earthquake in 2008, nonetheless clearly exhibited signals of rapid adaptation and movement toward coordinated response. Toward Auto-­adaptive Systems Auto-­adaptive systems are those that are high on technical infrastructure, high on organizational flexibility, and high on cultural openness to new ideas and strategies of action. Such systems recognize risk and reallocate their attention and resources in creative ways to reduce that risk. Further, such communities are able to sustain their adaptive performance in risk reduction over time, as new threats emerge and conditions change. To develop the capacity for auto-­ adaptation, four interdependent functions, each relating to key concepts in complex systems theory, are essential in practice. These functions, critically, enable the operational system to readjust its internal performance to accommodate the urgent demands of a major earthquake and simultaneously develop effective relations with external organizations to mobilize the resources and support essential for meeting the demands of the disaster-­stricken community. These functions are (1) articulation of common meanings; (2) trust

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Preliminary Characteristics of Response System Tending toward Auto-­adaptation, Lushan, China, 2013

TABLE 4.4.

Function

Degree

Articulation of common meanings Trust between leaders and citizens Resonance between response system and environment Sufficient resources to sustain collective action

Medium Medium Medium Medium

between leaders and citizens; (3) resonance between response system and the environment in which it operates; and (4) sufficient resources to sustain collective action. Only Lushan, China, exhibited characteristics that indicated movement toward self-­organization. While not explicitly auto-­adaptive, the Lushan response system in 2013 demonstrated characteristics of community performance that represented a significant advance in this direction from China’s earlier performance in the Wenchuan earthquake in the same province, Sichuan, five years earlier, in 2008 (Zhang et al. 2016). Table 4.4 shows the preliminary characteristics of the Lushan system, moving toward auto-­adaptation, by function and degree of performance. Interestingly, Lushan is not high on any of the four characteristics, but rather is medium on all four characteristics that show the relationship between the response system and the larger community that supports it. The organization of the system appears, largely, to follow a hierarchical plan, but the apparent support of the community and its engagement in response and recovery operations appears to be generated through a broad pattern of media exchange and voluntary response. Whether this pattern will continue to advance, with the Lushan community becoming more self-­organizing in managing known seismic risk, or whether it will regress toward a more hierarchical order is not yet clear. Yet the broad processes of interactive communication among different groups in the community has actively shifted the perspective of the community toward shared management of risk. Operative Adaptive Systems Operative adaptive systems are those systems that demonstrate awareness of seismic risk and a moderate degree of professional planning and preparedness to reduce risk of losses. These systems tend to show mixed patterns of per­ formance on the four critical functions that enable sustainable adaptation in urgent environments. These systems are capable of mobilizing response rapidly following an extreme event and operating with other organizations to bring the incident under control. Their focus tends to remain on response

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70 C H A P TER 4

operations, and they largely do not take the next step of investing in an ongoing program of monitoring risk and generating a self-­organizing system of seismic risk reduction that adapts as other conditions interact and change. Preliminary rankings place four systems in this category: Duzce, Turkey, November 12, 1999; Padang, Indonesia, September 30, 2009; Tohoku, Japan, March 11, 2011; and Nepal, April 25, 2015. Two of the systems, Duzce and Padang, experienced earthquakes that followed earlier seismic events in their respective countries at short intervals, a pattern that indicates the earlier events served as warning signals to both policy makers and citizens, increasing awareness as well as commitment of resources to risk reduction. The Tohoku and Nepal systems each had unusual circumstances that exacerbated already high-­risk events. The Tohoku system in Japan revealed the danger of cascading hazards and their cumulative capacity to overwhelm an otherwise well-­prepared society. Japan ranked high on technical infrastructure and preparedness for earthquakes, but ironically public policy makers had given relatively little attention to the risk of tsunamis, and no attention to the potential threat of a tsunami disabling a nuclear reactor and causing a major breach of radioactive pollution. Nepal also demonstrated a relatively high awareness of seismic risk in its urban centers and had engaged in an effective program of risk reduction for the three cities in the Kathmandu Valley: Kathmandu, Bhaktapur, and Patan. Yet the inability to overcome ethnic divisions that had riven the country for centuries led to a serious conflict with neighboring India for the transport of gasoline, virtually bringing recovery operations to a standstill (Personal communication, Kathmandu, May 1, 2016). Organizational flexibility and cultural openness on seismic risk were limited by an inability to resolve tensions on other ethnic, political, and economic issues. Table 4.5 presents the preliminary characteristics for the four operative adaptive systems. The operative adaptive systems show some indications of change in the perception of the basic initial conditions, time, space, scale, and energy. Although these changes are not fully manifest in any one system, the articulation of common meanings begins to shape an understanding of risk for the whole nation. For example, seismic risk in Nepal was recognized not only by building engineers in Kathmandu, but also by rice farmers and school teachers in the mountain villages of the Middle Himalayas (Personal observation, village, Middle Himalayas, April 29–30, 2016). This shared recognition of risk at different physical locations spurred willingness to learn and collaborate in common projects to reduce risk for the whole society. It also signaled greater awareness that the degree of risk differs in different locations. Mountain villages are more dependent on communication and transportation, given the steepness of the terrain and the geographic distances to cross. Creating a vir-

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TABLE 4.5.

Preliminary Characteristics of Operative Adaptive Systems

Articulation of common meanings Trust between leaders and ­citizens Resonance between response system and environment Sufficient resources to sustain collective action

Duzce, Turkey, 1999

Padang, Indonesia, 1999

Tohoku, Japan, 2011

Nepal, 2015

Medium

Medium

Medium

Medium

Low/medium

Medium

Medium

Low/medium

Medium

Medium

Medium

Medium

Low/medium

Low/medium

High

Low

tual space for shared communication among villagers and urban nonprofit organizations opens new possibilities, not only for risk reduction but also for rebuilding communities in more sustainable ways (Village District Disaster Response Committee, April 29, 2016). Yet operative adaptive systems remain largely focused on response to a seismic event after it occurs. For the community to adapt to changing conditions of risk over the longer term, it is necessary to shift its focus toward self-­organization and auto-­adaptation in preparedness activities before the earthquake. Emergent Adaptive Systems Emergent adaptive systems are those systems that are low on technical structure but show some degree of flexibility in organizational processes and beginning openness to new information and new strategies of action in the cultural dimension. Such systems activate local response operations but require outside resources to provide essential support and direction. Four systems fall in this category: Marmara, Turkey, August 17, 1999; Chi Chi, Taiwan, September 21, 1999; Pakistan, October 8, 2005; and Wenchuan, China, May 12, 2008. The Marmara case is borderline for this category, as given Turkey’s previous history of earthquakes and known seismicity, the nation did have a national earthquake law, number 7269, and a professional set of building codes prior to the 1999 earthquake, indicating awareness of risk at least in professional circles. Implementation of these policies, however, was weak, and there was little to no shared knowledge regarding seismic risk or resources among organizations, jurisdictions, or citizens. In each of the four nations, there was little technical infrastructure to support the search and exchange of information among citizens, a necessary

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TABLE 4.6.

Preliminary Characteristics of Emergent Adaptive Systems

Articulation of common meanings Trust between leaders and citizens Resonance between response ­system and environment Sufficient resources to sustain ­collective action

Marmara, Turkey, 1999

Chi Chi, Taiwan, 1999

Pakistan, 2005

Wenchuan, China, 2008

Low

Low

Low

Low

Low

Low/medium

Low/medium

Low

Low/medium

Low/medium

Low/medium

Medium

Low/medium

Low/medium

Low/medium

Medium

c­ ondition for an adaptive system, although there were beginning indications of technical change in Pakistan in 2005 and in Wenchuan, China, in 2008. In Pakistan, the use of satellite imagery greatly facilitated search and rescue operations in the mountainous Kashmir region. In Wenchuan, the first evidence of widespread use of cell phones emerged as citizen volunteers began to seek information about the disaster and to offer their services for assistance, but this means of communication was largely overlooked by the central government (Personal communication, Mianyang, 2008). The basic characterizations of time, space, scale, and energy remained largely unchanged for this class of cases, as the systems struggled to function under sudden, urgent, stressful operating conditions for which they were ill prepared. Table 4.6 shows the preliminary rankings on conditions essential to adaptation for the class of emergent adaptive systems. All four emergent systems lacked a set of common meanings, or shared information regarding seismic risk among the broad population, an essential characteristic for initiating and maintaining a self-­organizing process to manage risk in practice. Two systems, Chi Chi, Taiwan, and Pakistan, showed modest levels of trust between citizens and government, but importantly, all four systems exhibited some level of resonance between the emerging operational system and the wider society. Further, all four systems demonstrated at least some level of resources committed to disaster operations, with China quickly mobilizing resources from industrialized eastern provinces to assist quake-­stricken cities and towns in Sichuan Province. Interestingly, the beginning impact of advanced information technologies is seen in the satellite imagery made available to disaster managers in Pakistan and in the prevalent use of cell phones to seek and transmit information among the lay public in the Wenchuan operational system. In both cases, use of information technology facilitated emergence of response operations, although after the earthquake occurred, not before the event in shared recognition of risk, and it did not translate into sustained use.

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TABLE 4.7.

Preliminary Characteristics of Nonadaptive Systems

Function Articulation of common meanings Trust between leaders and citizens Resonance between response system and environment Sufficient resources to sustain collective ­action

Bhuj, Gujarat, India 2001 Degree

Sumatra, Indonesia 2004 Degree

Port-­au-­Prince, Haïti 2010 Degree

Low Low Low

Low Low Medium

Low Low Medium

Low

Low

Low

Nonadaptive Systems Nonadaptive systems are those systems unable to mobilize effective response operations independently after an extreme event, and virtually all assistance comes from external sources. With external support, the systems function during the event, but when outside resources leave, the systems are unable to maintain a consistent level of performance and struggle to retain a commitment to seismic risk reduction (Comfort 1999a). Three of the 12 cases fall within this category: Bhuj, Gujarat, India, January 26, 2001; Sumatra, Indonesia, December 26, 2004; and Port-­au-­Prince, Haïti, January 12, 2010. Response systems formed in all three cases, but the local systems were low on the three basic dimensions: technical, organizational, and cultural characteristics listed in table 4.3, as well as low on the functions central to adaptation to a changing environment, shown in table 4.7. The three operational systems classified as nonadaptive systems differed to some extent on the functions identified as essential for adaptation, but not sufficiently to mobilize collective action (Comfort 1999a, 64). None of the three nations reached a threshold point that generated a consistent effort to initiate the transition toward a self-­organizing system that could recognize and adapt to risk without external assistance. The functions listed above are noted as necessary, but not sufficient, conditions to initiate self-­organizing processes for managing risk. The distinctive category of resonance between the response system and its environment for Sumatra and Haïti marks the generous response of the international community to the recipient nations in both events, but this response arrived after the earthquake in both cases, not before the event in recognition of risk. Further, each of the response systems classified as nonadaptive evolved in contexts of substantial stress and dysfunction within their larger national societies. The Bhuj earthquake occurred in India’s Gujarat State, bordering on Pakistan, with which India has had contentious relations since the separation

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of the two nations as independent states in 1947 (Ganguly 1994). When the earthquake and tsunami struck Sumatra in 2004, Indonesia had been embroiled in a decades-­long civil conflict with a separatist movement in Aceh Province. Banda Aceh, the capital of the province and center of the Free Aceh movement, suffered the greatest loss in lives and sustained the heaviest damages from this devastating event (United Nations Relief Web 2005; Comfort 2007b). In 2010, Haïti was just beginning to emerge from decades of civil strife and dysfunctional governments and was operating under the protection of a United Nations peacekeeping force mobilized to stabilize the government and maintain civil order in the society (Resolution 1542; United Nations Security Council 2004). In each nation, recognition of seismic risk before the earthquake and, in the case of Indonesia, specifically tsunami risk, was minimal to nonexistent. Local governments and community residents were unaware of the risk and unprepared for such extreme events. Although scientists had identified seismic risk in each country, this knowledge was not communicated clearly to local government officials or to the wider population. Consequently, the initial conditions in which these events occurred confirmed a sobering lack of recognition of risk and set a steeper trajectory for the evolution of response systems in these three countries than in the other nine nations. Examining the initial conditions for these three response systems in more detail, it is clear why there was little capacity to initiate substantive response in local jurisdictions that bore the immediate impact of the damaging events. Technically, there was little to no monitoring of potential risk of such an event. Haïti, for example, did not have a national geological survey to map the earthquake faults (Calais et al. 2010). Organizationally, there was little to no common knowledge shared among the different groups in the population regarding seismic risk and possible consequences for the community, or criteria for collective action. Culturally, there was little to no search for and exchange of information about seismic risk among organizations and jurisdictions, and importantly, little to no trust or shared experience in solving common problems among organizations, jurisdictions, or citizens. The initial state of operating conditions in the three response systems ranked low on all three dimensions, making it difficult, if not impossible, for local organizations to adapt readily to the extraordinary demands of the disasters. Time remained a chronological sequence in all three systems, as without a robust infrastructure for communications among different actors, tasks were ordered sequentially as a simpler means of regaining control. Space, in turn, was limited to the geographic boundaries affected by the disaster, as access to the internet was not readily available to most lay people, and scale was focused on the immediate demands of the residents affected by the event. Energy reverted to money as the medium that drove the system and

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became the primary reason for decline in performance when external sources of funding receded. Conclusion In practice, initial conditions influenced the formation of response systems following earthquakes in all 12 cases, leading to different types of adaptation. The path dependence that follows from each distinctive set of initial conditions illustrates both the promise and the challenge of shaping communities that are resilient to seismic risk. As the operational systems formed, they influenced the context in which they were operating and altered the environment. In turn, the altered context influenced the evolving systems in substantive ways. Time becomes increasingly concurrent, with multiple operations occurring simultaneously in different locations. Space becomes a virtual space of flows in Castells’s terms (2000), where the exchange of information facilitates the exchange of ideas as well as goods and services. Scale, tentatively, emerges as the systems become larger and more complex, and different levels of operation are necessary to manage risk at varied levels of exposure to different groups within the population. Finally, in this configuration, information, not money, drives the system, altering the very environment through which it flows. When this multiway exchange occurs, there is a general recognition of seismic risk among the population. This chapter has outlined critical ways in which initial conditions shape the trajectory for response systems following extreme events and mark their classification into broad categories of adaptation to urgent conditions. The next chapter, chapter 5, examines in detail the emergence of a response system that is moving toward the goal of auto-­adaptation in extreme events, Lushan County, China, but that still falls short of a fully integrated, sustainable, self-­organizing system in managing seismic risk. Yet the beginning structure of an auto-­adaptive system is emerging as the developing information infrastructure at the local level supports broader participation in response actions. The question is whether the collective learning process demonstrated in Lushan County will continue and extend to other communities in China exposed to seismic risk.

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5 Toward an Auto-­adaptive System THE 2013 LUSHAN COUNT Y, CHINA , EARTHQUAKE

Moving toward Auto-­adaptation in Seismic Response The emergence of a response system following an extreme event varies by the filigree of interactions among the phenomena of time, space, scale, and energy in the actual context of communities at risk. The goal remains the same for all communities exposed to seismic risk—auto-­adaptation to a changing risk environment—but the degree to which this goal is achieved depends on the patterns of interaction triggered by the earthquake in a stricken community. The complexity of these interactions can be seen most clearly in the context of actual response systems that evolved following extreme events. To illustrate this emerging pattern, this analysis of actual cases begins with a profile of the 2013 Lushan County, China, response system as moving toward the model of auto-­adaptation and then proceeds to characterize the other three classes of adaptation in chapters 6, 7, and 8 to document the differences in interaction among these phenomena that enhance or inhibit adaptation to seismic risk in practice. Auto-­adaptive systems are systems that are high on technical structure, high on methods of organizational flexibility, and high on cultural openness to new information and new methods of action. Such systems are alert to signals of possible threats, able to absorb disruptive events by reallocating resources and action swiftly, and quick to access needed sources of external support and knowledge to meet unexpected hazards, and they continue their primary operations informed by adaptive response to continuing risk. Impor-

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tantly, such systems integrate technical devices and sensor systems into a coherent sociotechnical system for detecting threats, monitoring known risk conditions, and transmitting data from the changing risk environment to organizational actors that have both the responsibility and the capacity to act on this information to mobilize effective strategies for reducing risk. The primary innovation of auto-­adaptive systems is the extension of technical means of monitoring, collecting, aggregating, analyzing, and transmitting information in timely ways to diverse organizational actors in complex social systems, enabling the whole sociotechnical system to respond interactively in a coherent, informed way to emerging hazards. In auto-­adaptive systems, the internal subsystems, such as county police and fire departments, and sub-­subsystems, such as emergent volunteer groups from local towns, of a larger metasystem, for instance, the national disaster response system, all engage in a dynamic process of interacting information exchange and adjustment in action. The basic goal is shared by all actors in the system, and while each actor may perform different functions at different times, the adjustment of individual actors is attuned to the requirements needed to maintain performance of the whole system (Churchman 1971). The process of adaptation occurs simultaneously throughout the system as relevant actors respond to the external threat, a major earthquake, levied against the whole system, while actors within the system recognize emergent needs and explore innovative capacities to make internal adjustments to address external demands. To the degree that external resources, such as provincial military units, and specialized knowledge, for example, from the China Earthquake Administration, offset the disruption of performance among internal actors, the system retains its capacity to function as a whole system, albeit with redefined relationships among both internal and external actors. The disruption could be sudden or gradual, but critical to maintaining system performance is detecting the rate of change in the interaction of the system with its environment to inform internal adaptation among the subunits of the system. Measuring the changing dynamic between internal needs, external resources, and overall system performance is analogous to managing a sociotechnical gyroscope in disaster operations. Achieving auto-­adaptation in operational systems is essentially a task of systems integration that needs to be designed and executed to function in different phases of mobilization and action to mitigate seismic risk, anchored in specific local contexts. Four basic functions of systems integration are essential, and they are related to the dimensions of time, space, scale, and energy described earlier. Since seismic hazards are episodic, monitoring signals of seismic movement through seismic networks provides an important source of data, but such networks need to be maintained over long periods of time to provide reliable records of seismic activity and to document the potential for

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sudden, abrupt seismic events. Such an investment requires long-­term commitment and trained personnel to manage its operation and interpret the results to practicing decision makers and community residents. Second, earthquake faults span sizeable distances, and the damaging effects of seismic shaking can spread over wide spatial areas that affect multiple communities, defying administrative boundaries. The spatial extent of seismic risk means recognizing diverse communities as actors in the whole system and acknowledging the need for a shared social space for discussion and action (Ostrom 2005; Bauman 2006), while devising a set of measures that captures both differences and commonalities in exposure to risk among the participating actors. Third, given diversity both in exposure to risk and in capacity to reduce seismic threats for communities in any specific area, system integration needs to accommodate different scales of operation from village-­level volunteer organizations to large-­scale metropolitan regions characterized by different modes of organization, communication, and cultural expectations that shape collective action. Finally, if information is acknowledged as activating the social energy that drives the system to adapt and change its operational environment, system integration necessarily must focus on the technical structure and organizational management of information that flows through the system. The collection, validation, aggregation, analysis, and transmission of information regarding the changing status of risk to relevant actors enables the system to function in auto-­adaptive performance. Such performance is genuinely sociotechnical, as it requires a cognitive function to make judgments regarding the limits of both technical and organizational capacity and to reframe collective action accordingly. None of the 12 disaster response systems included in this study met fully the characteristics specified for the class of auto-­adaptive response systems. Yet the earthquake response system that evolved in Lushan County, Ya’an Municipality,1 Sichuan Province, China, following the earthquake of April 20, 2013, was clearly moving in that direction. In the brief two-­to three-­year period prior to the earthquake, a major technical change had influenced the capacity for communication among residents of the community affected by the earthquake as the near ubiquity of handheld cell phones created ready access to social media for most residents of the region (Zhang 2012). These inexpensive devices allowed their owners to send and receive, almost instantly, messages from the damaged site to others, locally, nationally, and internationally. External controls had little to no effect on local community action in the first hours of response operations, and community residents began to self-­organize by using social media as a critical means of communicating with one another and for sharing information broadly within the community (Zhang 2015).

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FIGURE 5.1 . Toward auto-­adaptation. Lushan County, China, earthquake, April 20, 2013, Sichuan Province,

southwestern China.

The Lushan earthquake, shown on the map in figure 5.1, illustrated the change in overall system performance in China when ordinary citizens could communicate freely with one another at the local level regarding the status of response operations following the earthquake. Using cell phones, residents could share their direct observations of conditions requiring urgent action and actions taken or not taken to assist those injured or who suffered damage from the earthquake. This change in the technical capacity for communication among community residents altered their capacity to engage in collaborative response to the earthquake. Consequently, it shaped the four basic conditions that led to adaptive performance: (1) articulation of common meanings; (2) trust between leaders and citizens; (3) resonance between response system and the environment in which it operates; and (4) sufficient resources to sustain collective action. First, this chapter provides a brief account of the initial conditions of physical, technical, organizational, and cultural structures in the local communities of Lushan County prior to the earthquake. Next, it identifies from media accounts a key set of organizations that participated in response operations and

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presents network analysis of their interactions during the first three weeks following the earthquake. The analysis reveals patterns of change in response operations that evolved following the Lushan earthquake in different dimensions, tracing specifically the impact of changes in information technology on the collective capacity of residents to adapt to urgent needs generated by the earthquake. Finally, the analysis documents patterns of changing performance at different locations and scales of operation, using network analysis and ­External/Internal index analysis among actors in the network.

April 20, 2013, Lushan County Earthquake, Ya’an Municipality, Sichuan Province, China INITIAL CONDITIONS

By 2013, the level of awareness of seismic risk and preparedness for managing earthquakes had increased substantially in western China, nearly five years after the devastating Wenchuan earthquake in Beichuan County, Sichuan Province, on May 12, 2008, killed nearly 70,000 people. Sobered by the heavy losses from the 2008 Wenchuan earthquake (Mw = 7.9), the Central Administration of China invested in earthquake preparedness and established administrative structures in local government offices to assess potential risk and conduct training for local emergency personnel and officials in disaster management (Zhang et al. 2016). The China Earthquake Administration (CEA) monitored seismic hazards and regularly updated local governments in the region regarding potential seismic risks. Further, the Central Administration supported the development of local knowledge bases for seismic risk by local earthquake bureaus, including GIS maps of the Longmenshan fault system that traverses the seismically active region between the Sichuan basin and the Tibetan plateau in western China (Personal communication, Lushan County, June 2015). In March 2013, the CEA monitoring system reported abnormal seismic activity in Yunnan Province in southwestern China and identified a potential threat for Lushan County in the adjacent province of Sichuan. Lushan County now had a full-­time emergency manager who organized training exercises for local emergency services personnel and installed needed equipment (EERI 2013). In response to CEA reports of seismic activity in the region, the Lushan County Earthquake Bureau checked emergency communications equipment in all towns and villages under its jurisdiction. In early April 2013, the bureau purchased emergency supplies as a precautionary measure and reviewed all emergency preparations in the period April 13–19, 2013. Rapid increase in use of cell phones in Lushan County now enabled residents to communicate directly with one another, a marked change in technical communications that

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facilitated collective action. Local officials were clearly aware of the risk and anticipated a potential seismic event. The very next day after completing their review, the officials experienced an actual test of local capacity to manage seismic events. CHARACTERIZATION OF THE APRIL 20, 2013, LUSHAN COUNTY EARTHQUAKE RESPONSE SYSTEM

At 8:02 a.m. on Saturday morning, April 20, 2013, an earthquake registering Mw = 6.6 struck on the Pengguan fault in Lushan County, Ya’an Municipality, Sichuan Province, 84 kilometers from the epicenter of the 2008 Wenchuan earthquake. The Pengguan fault is a branch of the greater Longmenshan fault system that includes the Beichuan fault, which triggered the 2008 Wen­chuan earthquake (EERI 2013; Pei et al. 2014). Given the changes in communications infrastructure and the preparedness activities undertaken prior to the earthquake, the response system formed quickly. Mobilization of emergency resources and public personnel largely followed the emergency plans revised and updated since 2008. Yet, given the increased use of cell phones since 2008, the first persons on scene were local residents informally sharing information and helping one another (Zhang et al. 2016). Formal emergency response personnel quickly followed, according to specified plans, and Lushan County activated its Emergency Operations Center within one hour of the earthquake. Sichuan Province officials arrived in Lushan County within two hours to provide support and direction to response operations. Helicopter overflights identified the main areas of damage (EERI 2013). Additional support arrived from the People’s Liberation Army unit stationed in Chengdu, approximately 170 kilometers distant, to conduct search and rescue operations. Responding to initial reports, the Chinese Central Committee activated the national disaster plan and assigned the event to the most severe category of disaster (Zhang et al. 2016). Time was an influential factor in shaping the trajectory of response to the Lushan event. Occurring on a Saturday morning as families were beginning their day, the earthquake generated immediate response from local residents. Neighbors quickly rushed to help neighbors, engaging in voluntary rescue efforts. Although the impact of the 2013 Lushan earthquake was not as severe as the 2008 Wenchuan earthquake, China’s Central Committee activated the National Disaster Plan to mobilize significant external resources quickly to assist the damaged community. Approximately 200 deaths and 11,000 injuries were reported for the earthquake (UNICEF China 2013), significantly less than the toll in 2008. All four dimensions of time, space, scale, and energy interacted in complementary ways to facilitate the emergence of a coherent response system. The timing of the earthquake, occurring on a weekend

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morning when children were not in school and families were still at home, was fortuitous, lessening the risk. The spatial location of the earthquake, approximately two hours from Chengdu, the provincial capital of Sichuan Province and headquarters of the provincial base of the People’s Liberation Army, enabled rapid response by trained search and rescue and medical teams. The scale of operations actively engaged town, county, municipal, provincial, and central administrators within hours, following the preset national emergency plan and aided by the newly installed emergency communications system in Lushan County. Given the moderate size of the earthquake, high level of awareness and investment in preparedness, clearly defined boundaries of impact, and updated communications infrastructure, the emerging system proved reasonably capable of managing response operations and reducing damage to the community. Actions taken in advance at multiple levels of administrative decision and action enabled a more informed, timely, and organized set of operations, creating a reasonably coherent response system. Table 5.1 reports the frequency distribution of organizations participating in the Lushan County response system, as identified from reports collected from local newspapers, blogs, Weibo records, and working reports accessed through online news sources, listed in appendix II.2 The large response system of 1,111 participating organizations included a robust mix of jurisdictional and sectoral organizations. This system, as documented largely from local online news and media reports, represents a major shift from national-­or macrolevel authority to provincial (meso) and municipal (micro) levels of authority in managing disaster operations in China. The largest jurisdictional group was provincial organizations at 38%, followed by national organizations at 28.4% and closely followed by municipal organizations at 23.1%. Overall, the public sector contributed the largest proportion of participating organizations at 29.9%. These organizations are government agencies, funded fully by public funds. The response system also included two categories distinctive to China: public institutions (10.2%), such as hospitals, research centers, and universities, still operating under the authority of the central government, but allowed to charge fees for services, and state-­owned institutions (11.5%), such as banks, central newspapers, energy companies, and coal mines that are owned and operated by the central government but provide essential economic services. Nonprofit organizations constituted more than a quarter of the organizations engaged in response operations at 26.6%, and private organizations represented 21.8%. A distinctive characteristic of the Lushan response system is the extent to which it engaged organizations across jurisdictional and sectoral levels of authority and action, with strong participation from the nonprofit and private sectors, as well as the categories of state-­owned and public institutions representing organizations in partial transition from public to private management. This pattern demonstrated an alignment across both jurisdic-

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0.09 0.00 0.09 0.54 3.06 3.78

%

N 7.29 2.88 4.05 7.38 6.84 28.44

%

National

81 32 45 82 76 316

Data sources: Electronic online sources, April 20–­May 11, 2013.

1 0 1 6 34 42

N

International

135 36 43 113 95 422

N 12.15 3.24 3.87 10.17 8.55 37.98

%

Provincial

87 24 34 79 33 257

N 7.83 2.16 3.06 7.11 2.97 23.13

%

Municipal

28 21 5 16 4 74

N

% 2.52 1.89 0.45 1.44 0.36 6.66

County

332 113 128 296 242 1,111

N

% 29.88 10.17 11.52 26.64 21.78 100.00

Total

Frequency Distribution of Organizations Participating in the 2013 Lushan County, China, Response System, by Jurisdiction and Funding Sector

Public Public institution State-­owned Nonprofit Private Total

TABLE 5.1.

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tions and funding sectors that indicated a shared understanding of risk and transition to collaborative action in the emerging operational system. The types of transactions performed by organizations in the Lushan County response system over the three-­week period of response and recovery are listed in appendix I, table I.5.1. Surprisingly, the largest category of transactions, 26.1%, reported in the various news media included in this analysis involved donations of money, goods, or services for the people affected by the disaster, and another 6.2% of the transactions involved fund-­raising or account setup. This total, 32.3%, or nearly one-­third of all reported transactions, involved voluntary contributions of financial assistance and services to communities affected by the disaster, in most cases encouraged and celebrated by the central authorities. The effort made to solicit financial donations from individuals, public institutions, private and nonprofit organizations, and international companies reflected a conscious effort to widen the engagement of different types of organizations at different scales of societal activity in earthquake response operations. The heavy focus on donations and fund-­raising appeared to be directed as much at engaging broad public support for earthquake-­ affected survivors as it was to generate funds for response and recovery, not self-­organizing activity but clearly directed by central authority. The second largest category of transactions included reports involving medical care/health, 9.5%, closely followed by disaster relief at 9.3%, coordination of response and recovery operations at 9.1%, and emergency response operations at 8.3%. This set of transactions involving immediate response actions, made up 36.2% of all actions undertaken. Other critical categories included communications at 7.1%, transportation/traffic issues at 5.7% and education issues at 3.9%. The construction of buildings did not warrant much attention, as building codes, a major issue following the Wenchuan earthquake, had been addressed in Lushan, where buildings largely withstood the more modest earthquake. Building inspection, for example, was identified in only one transaction with one actor. Figure 5.2 shows the rate of change among organizations in the Lushan County response system, over the first three weeks of operations. The figure shows a high rate of mobilization of more than 380 organizations on day 1 of disaster operations, followed by a sharp drop on day 2, with rates of mobilization declining daily. A slight uptick on day 9 is followed by minor fluctuations for the remainder of the three-­week period. The cumulative percentage of organizations participating in response operations peaked about day 9 and held relatively steady at approximately 100 organizations for the remaining response period. The rate of change illustrates a response system that mobilized quickly and then declined to relatively steady state over three weeks of response and recovery operations, indicating stabilization of the system.

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400

Lushan response system

350

Number / %

300 250

Total number of organizations Cumulative percentage of organizations Rate of change (%)

200 150 100 50

4/

20

4/ /20 21 13 / 4/ 201 22 3 / 4/ 201 23 3 / 4/ 201 24 3 / 4/ 201 25 3 / 4/ 201 26 3 / 4/ 201 27 3 / 4/ 201 28 3 / 4/ 201 29 3 /2 4/ 01 30 3 / 5/ 201 1/ 3 2 5/ 013 2/ 2 5/ 013 3/ 2 5/ 013 4/ 2 5/ 013 5/ 2 5/ 013 6/ 2 5/ 013 7/ 2 5/ 013 8/ 20 5/ 13 9/ 5/ 201 10 3 / 5/ 201 11 3 /2 01 3

0

Date FIGURE 5. 2 . Rate of change in 2013 Lushan County, China, response system. Data sources:

Electronic online sources, April 20–­May 11, 2013. Figure by Jee Eun Song.

Figure 5.3 shows the network diagram for the top 20 organizations active in the 2013 Lushan County response system, with the icons sized by betweenness values. While public organizations constituted the largest number participating in the system, 9 out of 20, 6 of the 9 public organizations are provincial organizations, 2 are national, and only 1 is municipal. This distribution shows the dominant authority in response operations being exercised at the provincial level, reflecting the extent of investment and training allocated by the Central Administration in lower jurisdictional levels of operation. The number of public organizations is closely followed by nonprofit organizations, 8, with 1 organization for each remaining category: private, state-­owned, and public institution. The diagram illustrates the wider participation of different types of organizations in response operations, a hallmark of a self-­organizing, self-­adaptive system. Table 5.2 presents a profile of the most active organizations engaged in response operations for the 2013 Lushan County earthquake, ranked by betweenness centrality values. Betweenness centrality measures the extent to which an organization connects other organizations that would otherwise not be connected. That is, organizations with high betweenness centrality serve important bridging functions in building relationships across organizational and jurisdictional boundaries. Of the top 20 organizations, 11 were national organizations, 7 provincial, and 2 were municipal. Yet, of the 11 national organizations, 6 were nonprofit organizations, 1 state-­owned, 1 public institution, and only 3 were national public organizations. This distribution

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CF_SC RCS_C DMG

Jurisdiction

RCS_F CAD_SC

AP_SC

Funding sector

National

Public

Province

Private

Municipal

Nonprofit State-owned

G_SC

Public institution

PLA_CMR HD_SC

CH_SC

CYDF EA_C

HFPC

G_YA

CFPA Tenence_F

Sina

OF

Amity_F EM_C FIGURE 5.3 . Top 20 organizations in 2013 Lushan County, China, response system, with icons

sized by betweenness values. Acronyms are listed in table 5.3. Graph level metrics: diameter: 14; density: 0.002; degree centrality: 0.063; betweenness centrality: 0.174. Data sources: Electronic online sources, April 20–­May 11, 2013. Diagram by Jee Eun Song.

shows a significant shift away from centralized public management of disaster response operations in China and toward provincial and nonprofit management, notably augmented by the role played by Sina Corporation, an online media company that connected other organizations that would otherwise not be interacting in disaster operations. This trend is further shown by the Sichuan provincial government’s rank as the organization with the highest betweenness value, that is, it engaged in operations that would otherwise not be connected, with a value of 107933.9, more than twice that of the nearest ranking national nonprofit organization, the China Youth Development Foundation at 49,600.13. Following the Sichuan provincial government, the next four organizations ranked by betweenness values are nonprofit organizations, with three of those organizations operating at the national level, and one, the One Foundation, based at the municipal level. The three national public organizations included in the top 20—Health and Family Planning Commission, China; China Earthquake Administration; and

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Top 20 Organizations Participating in the 2013 Lushan County, China, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

TABLE 5.2.

Acronym

Full Name

Sector

Jurisdiction

Betweenness

G_SC CYDF

Sichuan provincial government China Youth Development Foundation China Foundation for Poverty Alleviation Red Cross Society Foundation One Foundation Sichuan Civil Affairs Department Ya’an municipal government Sichuan Provincial Command Headquarters PLA Chengdu Military Region National Health and Family Planning Commission China Earthquake Administration Sichuan Health Department Red Cross Society, China Sichuan Armed Police Corps Amity Foundation Sina Company Dongfeng Motor Group Co. Sichuan Charity Foundation TenCent Foundation Education Ministry, China

Public Nonprofit

Provincial National

107,933.90 49,600.13

72 17

Nonprofit

National

33,792.90

44

Nonprofit Nonprofit Public

National Municipal Provincial

30,082.76 25,496.90 24,361.04

40 53 18

Public Public

Municipal Provincial

21,832.10 19,854.69

26 32

Public Public

Provincial National

18,439.48 18,184.32

21 37

Public institution Public Nonprofit Public Nonprofit Private State-­owned Nonprofit Nonprofit Public

National

15,908.49

26

Provincial National Provincial National National National Provincial National National

14,648.45 10,495.84 9,525.62 9,470.42 9,077.26 8,804.00 7,701.00 7,525.06 7,114.64

20 18 12 14 8 3 8 8 11

CFPA RCS_F OF CAD_SC G_YA CH_SC PLA_CMR HFPC EA_C HD_SC RCS_C AP_SC Amity_F Sina DMG CF_SC Tenence_F EM_C

Degree

Data sources: Electronic online sources, April 20–­May 11, 2013. Betweenness scores have been rounded to two decimal points.

Education Ministry, China—are organizations more focused on recovery and research than response operations, demonstrating that the key organizations operating in this response system were provincial and nonprofit organizations rather than national public organizations. Importantly, the inclusion of the Sina Company in the top 20 organizations ranked by betweenness values documents the increasing role of social media in mobilizing response operations and informing participants of the status of operations. The Lushan earthquake, downgraded to Mw = 6.6, was notably less severe than the Wenchuan earthquake at Mw = 7.9 (UNICEF Situation Report, April 22, 2013). Nonetheless, the affected communities and provincial and municipal organizations responded to this event with more informed, timely actions, reducing the losses and disruption.

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CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

In many respects, the Lushan earthquake of April 20, 2013, was a test of the plans and procedures that China had put in place after the devastating Wenchuan earthquake of May 12, 2008. In the intervening five years, China had engaged in a major effort to train local personnel and set up preparedness measures specifically in areas prone to earthquakes. Local emergency personnel in Sichuan Province were familiar with the 10 basic steps in the China National Earthquake Plan and sought to follow procedures for systematically activating the designated emergency response agencies, including local units of the Fire Agency, People’s Liberation Army, and Armed Police, to conduct search and rescue operations, assess damage, and mobilize infrastructure repair quickly. Still, other factors influenced the rapid mobilization of response to this earthquake. First, although the event was a relatively moderate earthquake, the Chinese authorities activated a full-­scale response at the most severe level of disaster, mobilizing 2,000 troops from the People’s Liberation Army (PLA) Chengdu Military Command within hours of the earthquake. The PLA division undertook search and rescue operations in the surrounding communities and established an earthquake relief and rescue headquarters for the affected region on the day of the earthquake, bringing abundant resources in personnel and equipment quickly to the damaged communities (Xinhua Net, April 20, 2013). Second, the timing of the earthquake was fortuitous, occurring at 8:02 a.m. on a Saturday morning when children were not in school, and most people were awake in their homes. Given the proximity to Beichuan County and the epicenter of the 2008 Wenchuan earthquake, most residents of Lushan County were aware of seismic risk in the region and had basic knowledge of safety measures to minimize risk. In older, low-­rise buildings, people ran outside to escape falling debris or collapsing buildings; buildings built since 2008 according to earthquake code standards largely withstood the shaking (EERI 2013). Local knowledge informed rapid comprehension of risk among residents. Third, wide availability of cell phones in communities of the region meant that individuals, families, and friends had an effective means of communication that enabled rapid forms of self-­organization as families and friends assisted one another informally before the official SAR teams arrived. Recent memories of the Wenchuan earthquake contributed to creating a more aware, more informed community that proved more capable of responsible collective action under stress. Fourth, private organizations (28.8%) played a sizeable role in China’s response operations in the Lushan disaster for the first time. To a large extent, this role was confined to making donations of money, goods,

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and services, likely in response to requests from the CPC to do so. Yet it is more than double the proportion of private organizations (12.8%) that participated in the 2008 Wenchuan response. The change in proportional distribution of actors by funding sector indicates that a wider base of support for mitigation of risk is emerging in China. SUMMARY

The demonstrated effectiveness of response operations following the 2013 Lushan earthquake constitutes, in many respects, an affirmation of the mitigation and preparedness measures taken by Chinese authorities after the catastrophic losses incurred in the 2008 Wenchuan earthquake. The dynamics of time, space, scale, and energy aligned to a large extent to meet the level of risk and needs generated in the 2013 Lushan event. The dimension of time influenced the evolution of the response system not only at the occurrence of the earthquake, but also in the degree to which a set of local governmental units could mobilize local response quickly and had the training and knowledge to broaden the request for assistance to the next level of governmental and community action. Space further shaped the mobilization, as the earthquake occurred in the same province, Sichuan, as the 2008 Wenchuan earthquake, a scant five years earlier. Consequently, memories from that event created an informed knowledge base within the community that coalesced to respond to calls for assistance. While this event required action at local, municipal, and provincial scales of operation that required communication and coordination, the complexity was relatively moderate and largely fell within the range of experience and skills of the subnational organizations. The event was unusual in that local capacity was stressed, but not overwhelmed, and could incorporate incoming personnel, resources, and management tasks reasonably well. Access to cell phones and social media ignited an initial flash of social energy that triggered the beginning signals of self-­organization, but these voluntary steps were soon refocused and redirected to official channels of emergency response actions. The fortuitous factors of geographic proximity, timing, and widespread access to informal communication among community members likely contributed to the largely effective response and reconstruction operations in Lushan County. Still to be tested is whether this same combination of factors would interact to provide a similarly effective response in another region of China vulnerable to seismic risk, or at a more distant time, or in a more severe seismic event that required greater coordination among many more organizational components. Whether the same level of coherence could be replicated in other, more damaging events at a different time, in a different region, or with a larger, more complex set of actors is yet to be discovered.

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Several questions regarding the rapid mobilization of response operations remain. The spontaneous emergence of volunteers to assist in response activities was remarkable, but why were these volunteers and their informal organizations not fully incorporated into the formal organization mobilized according to the National Emergency Plan? NGOs were housed together in a community building but were left largely to operate on their own and were expected to raise their own financial resources to carry out their specific tasks (Personal communication, Lushan County, 2015). Second, why did so little interaction develop among voluntary organizations to coordinate the services that each organization could provide to assist the damaged communities? To some degree, the voluntary agencies were competing with one another for support and participation from the wider community, hindering the interorganizational coordination vital to organize a coherent set of recovery activities for residents of affected communities. Each organization appeared to define its own mission and respond more to its donor community than to integrate activities onsite for the recovery of the whole community (Personal communication, Lushan County, 2015). Finally, while each of the organizations used social media and had access to information management facilities, there appeared to be no central knowledge base shared among the voluntary organizations or between the voluntary organizations and the emergency operations headquarters established by the municipal government. What links, if any, existed between the emergent voluntary organizations and the official emergency operations centers for this event? The voluntary organizations appeared to operate largely outside the organized public response operations, indicating that these vital components were not fully integrated into the community response system. Developing Auto-­Adaptive Systems: A Continuing Challenge The challenges of developing auto-­adaptive systems in communities exposed to seismic risk are many and vary with the context and initial conditions in which earthquakes occur. Yet the experience of Lushan, China, demonstrates that considerable progress can be made toward this goal. Primary steps include strengthening the built infrastructure so that buildings, bridges, and utilities are resistant to seismic shaking. Further, educating the public to recognize risks in their respective homes, workplaces, schools, and community gathering places contributes to creating an aware, informed public capable of taking collective action and sharing a common set of meanings. Utilizing current means of information technology to manage information search and exchange to support collective action across jurisdictional scales is the step least developed at present, but most likely to have a significant effect in contribut-

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ing to the development of auto-­adaptive systems for managing seismic risk. Importantly, evidence from the Lushan experience documents the critical step of investing in local organizations, building local capacity through training and exercises, and creating the organizational capacity to link with external organizations to create a broader response to meet the urgent needs of a community exposed to the shattering impact of an earthquake. Two questions emerge from the analysis of the 2013 Lushan response system. First, what steps would advance this community to a fully self-­organizing state of auto-­adaptation in managing seismic risk that is almost certain to recur? Second, what are the consequences for a community exposed to seismic risk when investment in both social and technical development is inadequate or missing? The next chapter, chapter 6, on operative adaptive systems, explores the consequences for managing risk in communities that have taken some steps toward risk reduction but have not yet reached sustainable resilience.

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6 Operative Adaptive Systems 1999 DUZCE , TURKEY; 2009 PADANG , INDONESIA; 2011 TOHOKU, JAPAN; AND 2015 NEPAL RESPONSE AND RECOVERY SYSTEMS

Operative Adaptive Systems in Changing Contexts Stretching toward adaptation, operative adaptive systems constitute the class of operational systems that emerge in response to extreme events in practice, but have difficulty sustaining newly adjusted patterns of behavior over time. Such response systems are approximately medium in terms of technical structure, organizational flexibility, and cultural openness to new perceptions of risk (Comfort 1999a). These systems exhibit a modest capacity to recognize and respond to risk prior to an earthquake, and communities in this class demonstrate the ability to mobilize a coherent response to a destructive event in the immediate term but fail to sustain a continuing, collective effort to reduce risk and build an informed, responsible framework for managing long-­ term, future risk. Operative adaptive systems tend to function effectively under moderate, relatively short-­term stress but fracture under the pressure of massive or prolonged disruption or complex transitions to recovery. Four earthquake response and recovery systems included in this study fall in this initial category of operative adaptive systems: the 1999 Duzce, Turkey, earthquake; the 2009 Padang, Indonesia, earthquake; the 2011 Tohoku, Japan, earthquake, tsunami, and nuclear breach; and the 2015 Nepal earthquakes, shown on maps in figures 6.1 and 6.2.

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S FIGURE 6.1 . Operative adaptive systems: Duzce, Turkey, November 12, 1999; Padang, Indonesia, September 30, 2009. Maps created by Fuli Ai.

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FIGURE 6. 2 . Operative adaptive systems. Tohoku earthquake, Japan, 2011; Gorkha earthquake, Nepal, 2015. Maps by Fuli Ai.

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Points of differentiation and dysfunction in operative adaptive systems tend to fracture at the intersections of the four dimensions of time, space, scale, and energy, essential to the integration of a functional, auto-­adapting system in practice. Regarding time, operative adaptive systems are those that have assembled some degree of resources, trained personnel, equipment, and collective knowledge regarding risk to mobilize an immediate response to a destructive earthquake and take informed action to protect the community. Yet resources are limited, and such systems quickly exhaust the reserves of goodwill, voluntary contributions, and limited expertise that can be mustered on a short-­term basis. This condition becomes even more limiting if participants, supplies, and losses are distributed over a wide physical and social space, with relatively few prior social connections, knowledge, or infrastructure to support continued learning and adaptation in the changed disaster environment. As operations move across multiple scales of action and decision making, from local to regional to national to international and back again, interactions among groups of actors become more complex, the potential for error in judgment or action increases, and the initial coherence of the system tends to fracture under stress. Finally, determining what form of energy drives the system is central to understanding adaptation. If information is viewed as activating the response system at multiple levels of operation simultaneously, the technical infrastructure that supports information search, exchange, and access must be sufficiently robust to enable continuous updates, multiway searches, and systematic monitoring of dynamic conditions. Without adequate investment and maintenance, the information infrastructure essential to organizational learning tends to atrophy. The requirements for operational adaptive systems become more demanding in societies that are undergoing physical, economic, social, and political change in conjunction with seismic risk. Systems that produce robust plans for disaster reduction may weaken under indifferent leadership or tightened economic constraints. Technical infrastructure for communications requires ongoing maintenance and investment to support reliable access for diverse groups. The capacity to adapt operational performance to changing contexts is directly related to the investment of time, resources, and energy needed to monitor and update known risk, as a means of building capacity to cope with uncertain, unknown risk. Particularly critical is determining the point at which a multiorganizational response system operating in a disaster context fails to adapt as it moves into recovery and engages in mitigation activities essential to managing long-­term disaster risk. The tasks of transition to recovery require a different set of skills and a redesigned organizational model from immediate response operations. This chapter briefly reviews the initial conditions of physical, technical, organizational, and cultural characteristics that existed prior to each earth-

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quake and created the context for the emergence and evolution of the operational systems that formed in response to the four events: the 1999 Duzce, Turkey, earthquake; the 2009 Padang, Indonesia, earthquake; the 2011 Tohoku, Japan, earthquake, tsunami, nuclear breach; and the 2015 Nepal earthquakes. Network analysis is used to characterize the structure of each response system included in this class, and to show the change in network performance over the three-­week period of study for each system. Analytical methods include network analysis to identify the interactions among organizations in their recognition and response to seismic threat, compare performance of networks operating under stress, identify gaps in the operational networks, and assess the dominant types of interactions among organizations in the system. Important in this assessment of operational systems is the internal capacity of the evolving response system to accept, accommodate, and integrate the influx of external resources, personnel, and diverse cultural characteristics into a coherent strategy of action to meet the needs of the affected community. Resources donated from the international community come from many countries in diverse languages, standards, and approaches to management that, although directed toward a common goal of humanitarian aid, nonetheless reflect different approaches to achieving that goal. Integration of these differences becomes a critical factor for the recipient country, lest it lose connection with its own core constituencies and values. Interestingly, three of the four response systems included in this preliminary classification of operative adaptive systems emerged in regions that had previous experience with major seismic events. The November 12, 1999, Duzce, Turkey, earthquake followed the August 17, 1999, Marmara, Turkey, earthquake. The 2009 Padang earthquake followed the 2004 Sumatran earthquake and tsunami in Indonesia, and the 2011 Tohoku triple disasters followed the 1995 Hanshin earthquake in Japan. These prior events influenced the evolution of the respective response systems in surprising ways. The 2004 Sumatran tsunami in Indonesia precipitated preparedness activities in Padang that focused on tsunami evacuation, not earthquake risk reduction, while the 1995 Hanshin earthquake had the reverse effect in Japan, leading decision makers to focus on earthquake risk reduction, with little emphasis on tsunami evacuation. Ironically, in each case, the actual event differed from the preparedness activities. The earthquake generated the greatest damage in Padang in 2009, while the tsunami created the heaviest losses in lives and livelihoods in the Tohoku region of Japan in 2011. These policy decisions, reminiscent of generals focusing their strategies on the last battle in war, had detrimental consequences for the affected populations in both countries. This set of four earthquake response systems, assigned the preliminary classification of operative adaptive systems, is reviewed and evaluated against existing risk mitigation policies and data collected after each event. Methods

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of network analysis are used to identify the structure of each response system and calculate measures of centrality that permit comparison of the four networks within the class. The capacity of each response system to access needed external resources and integrate money, personnel, and supplies effectively into a coherent, internal mode of operations is a critical measure of performance. This internal/external dynamic will be noted for each response system in this chapter but documented for all 12 response systems to show the evolving trajectory of system integration, or lack of same, in chapter 9. The intersection of time, scale, space, and energy splintered differently in each of the four cases of operative adaptive systems, revealing different weaknesses and varying strengths as the communities responded under stress. Key decisions led to reasonably coherent performance in the short term but failed to build a basis for long-­term, sustainable management of risk. Identifying thresholds of change in actual communities documents the process of adaptation to risk, noting when it occurs and where it fails. The November 12, 1999, Duzce, Turkey, Earthquake INITIAL CONDITIONS

Just before 7:00 p.m. on Friday evening, November 12, 1999, as families were preparing their evening meal, a severe temblor, Mw = 7.2,1 rumbled through the main streets of Duzce, a small city of approximately 80,000 residents in western Turkey, about 117 kilometers east of Kocaeli, the epicenter of the ­August 17, 1999, Marmara earthquake, Mw = 7.4 (Erdik 2000). Buildings, already damaged in the earlier Marmara event, crumbled, and basic civil infrastructure—water mains, electrical transmission lines, and communications—­ collapsed. The earthquake, located on the Duzce fault, an extension of the larger North Anatolian fault system that crosses Turkey from east to west, triggered a shorter rupture of the fault, 40 kilometers in comparison to 150 kilometers for the Marmara earthquake. The earthquake had a shorter duration of shaking, 20 seconds in comparison to 45 seconds, but stronger intensities of near-­field ground motion (Kandilli Observatory 1999). Estimated losses in the Duzce earthquake varied between 845 to 950 deaths (Erdik 2000), much lower human losses in comparison to the Marmara earthquake despite its roughly similar seismic magnitude. Many residents of Duzce had already left the city after they experienced damage from the Marmara earthquake, seeking strategies to cope with the destruction from the earlier event. Other fortuitous conditions reduced the losses and damage in Duzce and enabled the small city to respond relatively quickly after this earthquake. Resources for search and rescue operations were close by, as a battalion of the Turkish Army deployed for the Marmara earthquake remained stationed in the immediate area. Turk Telekom, caught

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off guard by the Marmara event, sent telecommunications equipment and personnel reinforcements to Duzce within hours of the earthquake, enabling rapid communication and quick action among responsible central, provincial, and city agencies as the respective provincial and city governments coordinated actions to support the damaged city (Comfort and Sungu, 2001a, b). An interorganizational response system emerged quickly in Duzce, with resources provided by the Turkish Army and administrative personnel who had participated as volunteers in the larger, more devastating Marmara earthquake. They proved more informed and experienced in anticipating demands for operating in a dangerous disaster environment. The residents of Duzce were also more aware of seismic risk, given their experience with the Marmara earthquake. City officials quickly activated procedures available under National Disaster Law 7269 to request assistance from provincial and central authorities. Cell phones were more widely distributed to personnel within organizations and to managers who used them to communicate between organizations. Amateur radio capacity, brought by the Turkish Radio Amateur Club (TRAC) from Istanbul, came immediately to Duzce to support communications. Public managers, having observed TRAC’s effectiveness in the Marmara earthquake, readily accepted their services. Relationships forged between public managers, Turk Telekom, and the Turkish Army during disaster operations for the Marmara earthquake facilitated coordination among these key organizations, resulting in a more rapid response during disaster operations for the Duzce earthquake. Although GIS capacity had not yet been developed in Duzce, public managers were aware of its potential for informing decisions in disaster operations and regarded it as an important new tool that could be used to assist their mitigation and response processes (Comfort and Sungu, 2001a, b). In many respects, experience gained by personnel and organizations that participated in the Marmara response operations augmented and enhanced the emergence of a multiorganizational response system following the Duzce earthquake. CHARACTERIZATION OF THE 1999 DUZCE, TURKEY, EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

Since the Duzce earthquake occurred less than three months after the Marmara earthquake, most of the same policies, procedures, and personnel were still in place. National Disaster Law 7269 remained the guiding legal platform for governmental action. Turkish Red Crescent had primary responsibility for disaster assistance. Resources and communications in this small city in the mountains of northwest Turkey were constrained, in part because of the damage incurred in the Marmara event. What had changed was the degree of awareness of seismic risk among the population of Duzce and an increased

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understanding among local personnel of policies and procedures to request assistance from provincial, state/central, and international sources. The emerging response system achieved greater coordination both within the immediate field of operations in the city and across organizational boundaries to encompass provincial, central, and international agencies. Table 6.1 presents the frequency distribution of a relatively small response system of 230 organizations identified through newspaper reports from Cumhuriyet, a national newspaper published in Istanbul, Turkey. Of that number, the largest proportion, 83%, were public organizations, representing almost in equal proportion agencies from the central administration and provincial administrations. A sizeable number, 16.2%, represented international organizations, while the smallest proportion was local public agencies. Noteworthy is the proportion of Turkish nonprofit organizations at 11%, many newly active to participating in disaster response following the Marmara earthquake in August, barely three months earlier. This distribution documents a response system dominated by public organizations that is only beginning to incorporate other sectors of the Turkish society. In Turkey’s centralized administrative system, the term “state” referred to central administration, while “national” referred to private or nonprofit organizations operating at the national level. Scant representation of international nonprofit organizations reflected the limited response to the United Nations call for humanitarian assistance following the Duzce earthquake, as many international NGOs were already engaged in response and recovery activities in Turkey initiated in response to the earlier Marmara earthquake. Different scales of operation did exist, but asymmetrically. Figure 6.3 presents the rate of change in participation over the 16-­day period of study, shorter than the 21-­day period included in other cases in this study, as response operations, given moderate losses, largely concluded after day 16. The data show a sharp increase in the number of organizations entering the response system on day 2 following the earthquake, but an even sharper drop on day 3, as the emergent response system moved relatively quickly to recovery operations. The types of transactions performed in the 1999 Duzce response system reveal the patterns of interaction among both jurisdictions and funding sectors and are listed in appendix I, table I.6.1. The largest proportion of transactions, 28%, involved coordination of response and recovery actions, an important indication of the effort to integrate actions among the participating actors across organizational and jurisdictional scales of operation. The second-­largest proportion, at 17%, included transactions offering donations of money and goods to assist the affected residents. In most respects, these donations came from different sectors and jurisdictions and required local knowledge for ef­ fective distribution. Following closely in third place, 13.3%, were transactions

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37 1 2 0 40

N

16.16 0.44 0.87 0.00 17.47

%

International

67 0 11 0 78

N 29.26 0.00 4.80 0.00 34.06

%

State/Centrala

1 8 3 2 14

N 0.44 3.49 1.31 0.87 6.11

%

National

68 0 9 0 77

N 29.69 0.00 3.93 0.00 33.62

%

Provincial

18 0 0 0 18

N 7.86 0.00 0.00 0.00 7.86

%

Municipal

0 3 0 0 3

N

0.00 1.31 0.00 0.00 1.31

%

Regional

Frequency Distribution of Organizations Participating in the 1999 Duzce, Turkey, Response System by Jurisdiction and Funding Sector

191 12 25 2 230

N

% 82.97 5.24 10.92 0.87 100.00

Total

Data source: Cumhuriyet, Istanbul, Turkey, November 13–­December 4, 1999. I am grateful to Dr. Sitki Corbacioglu for generously granting access to a data set of news articles that he collected from Cumhuriyet, a major Turkish newspaper published in Istanbul, Turkey, after I discovered that the data set I had collected in 1999 had been corrupted in storage. a State/Central: public agencies with national authority; National: nonprofit and private organizations operating at national level.

Public Private Nonprofit Political Total

TABLE 6.1.

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Duzce response system

300

Total number of organizations Cumulative percentage of organizations Rate of change (%)

Number / %

250 200 150 100 50

99 /2

1/

19

99 11

/2

0/

19

99 11

/1

9/

19

99 11

/1

8/

19

99 11

/1

7/

19

99 11

/1

6/

19

99 11

11

/1

5/

19

99 19 4/ /1 11

11

/1

3/

19

99

0

Date FIGURE 6.3 . Rate of change in 1999 Duzce, Turkey, response system. Figure by Jee Eun Song. Data source: Cumhuriyet, Istanbul, Turkey, November 13–­21, 1999.

involving the provision of disaster relief, food and shelter, to the affected households. Again, the provision of disaster relief goods to affected households required alignment in scales of operation from international through the central government to provincial and municipal agencies, informed by local knowledge. These actions contributed to a growing local knowledge base to inform disaster operations, echoing the concept of a knowledge commons (Ostrom 2005). Emergency response transactions, at 7.3%, and visits by officials, at 6.3% were respectively fourth and fifth in importance, indicating an odd juxtaposition of officials checking to determine that emergency response operations were in fact being carried out. Other categories of transactions, earthquake assessment and research at 5.3% and damage/needs assessment at 4.6%, were identified as contributing to the full disaster operations system over the 16-­day period. In total, 715 actors performed 302 transactions, as identified in the daily news reports documenting disaster operations. Interestingly, communications constituted a small category of transactions at 1.7%, as well as medical care, health, at 3.6%, in contrast with reported transactions in other earthquake response systems. These low figures indicate that much of the affected population had already evacuated the damaged city before the November 12, 1999, earthquake occurred, mitigating losses in lives and property. The transition to recovery, however, was an uncharted situation that required reconsideration of the ­status of Duzce as a city which, in Turkey, provides specific governing authority as a

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Jurisdiction

P_IST

Funding sector

International

Public

State/central

Nonprofit

National Province Municipal

HD_BAL

BUL

M_IST

PMCMC

P_KAY

GER DIR_PS CMC_ DUZ

GF

P_SAK

PM CMC_ BOLU KIZ CMC_ KAY

HM

M_ANK P_TEK

P_ANK FIGURE 6.4 . Top 20 organizations in 1999 Duzce, Turkey, response system, with icons sized by betweenness centrality. Acronyms are listed in table 6.2. Graph level metrics: diameter: 8; density: 0.014; degree centrality: 0.315; betweenness centrality: 0.401. Diagram by Jee Eun Song.

DIR_RA

province and a direct relationship with the central administration. To speed the reconstruction process in Duzce, the Turkish Parliament passed a law with changes in policy and practice following the 1999 Duzce earthquake that elevated Duzce in Turkey’s governmental administration structure to become the 81st city in the nation, the equivalent of provincial status. This change in administrative authority was adopted to facilitate recovery from the damage incurred in the earthquake (Personal communication, Duzce, May 2000). The largest proportion of transactions was carried out by public organizations at the state (central) and provincial levels of governmental operations, with supporting transactions conducted by nonprofit and private organizations. Figure 6.4 presents the top 20 organizations in 1999 Duzce, Turkey, response system, with icons sized by values of betweenness centrality, indicating those organizations that connected actors that would otherwise not be connected in re-

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Top 20 Organizations Participating in 1999 Duzce, Turkey, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

TABLE 6.2.

Acronym

Full Name

Funding

Jurisdictiona

CMC_DUZ PMCMC

Duzce CMC Prime minister’s Crisis Management Center Bolu CMC Istanbul Great City Munici­ pality Health Ministry Ground forces Istanbul Province Ankara Great City Munici­ pality Tekirdag Province Sakarya Province Balikesir Health Department Directory of Public Safety Kizilay Kaynasli CMC Kayseri Province Prime minister Religious Affairs Ankara Province Bulgaria Germany

Public Public

CMC_BOLU M_IST HM GF P_IST M_ANK P_TEK P_SAK HD_BAL DIR_PS KIZ CMC_KAY P_KAY PM DIR_RA P_ANK BUL GER

Betweenness

Degree

Province State

10,504.73 4,077.18

75 44

Public Public

Province Municipal

3,039.15 2,602.92

23 9

Public Public Public Public

State State Province Municipal

1,701.04 1,472.42 1,256.36 936.50

13 13 9 14

Public Public Public Public Nonprofit Public Public Public Public Public Public Public

Province Province Province State State Province Province State State Province International International

936.32 903.40 820.35 815.64 760.67 734.00 698.00 655.75 530.54 464.35 434.56 384.86

7 17 5 7 11 10 6 17 5 3 4 4

Data source: Cumhuriyet, Istanbul, Turkey, November 13–­December 4, 1999. a State: public agencies with national authority.

sponse operations. As shown, the Duzce Crisis Management Center operating under the governor appointed by the central administration plays the key role in connecting other organizations in mobilizing response operations. Neighboring organizations, such as the Bolu Provincial Crisis Management Center and the Municipality of Istanbul also played key connecting roles, as did the prime minister’s office and the prime minister’s Crisis Management Center. All but one of the organizations identified in the top 20 organizations ranked by betweenness values were public organizations. Only one nonprofit organization, Kizilay, was listed in this set of organizations that served to connect other organizations in disaster response operations. Kizilay is the informal name for the Turkish Red Crescent organization that engaged primarily in the distribution of disaster relief supplies and services. The mix of jurisdictional actors identified in the top 20 organizations that played key connecting roles in the Duzce response system is listed in table 6.2. As shown in Table 6.2 neighboring provincial organizations played an important role in response operations following the Duzce earthquake, as nine

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provinces were listed in the top 20 organizations. State agencies, or central administration authorities, also exercised significant influence, constituting seven of the top 20 organizations. Two municipalities, Istanbul and Ankara, the two largest cities in Turkey, served connecting roles among organizations participating in the Duzce disaster operations, and two international actors, Bulgaria and Germany, were also actively engaged. Both nations host guest workers from Turkey, an economic exchange that extends cultural and political ties between the host nations and Turkish communities. The overall response system for Duzce was a relatively small set of largely public organizations, with state/central administrative agencies assisting provincial organi­ zations in providing disaster relief to the affected population. CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Many professional reports considered the Marmara and Duzce earthquakes as related events, given their proximity in both time and space (Ghasemi et al. 2000; Comfort and Sungu 2001a, b; EERI 2003). Yet there were distinct differences between the two earthquakes and the consequences they generated for the respective communities. The response system documented following the 1999 Duzce earthquake was smaller, operated over a shorter period, and shifted into recovery operations more easily than the response system following the 1999 Marmara earthquake three months earlier. The proximity to the Marmara earthquake in both physical space and time allowed responsible jurisdictions and organizations to exchange knowledge and information more easily. In an interesting example of learning from experience, actors responsible for managing seismic risk in Duzce from local, provincial, and central administrative agencies gained significant insight into this complex process from their direct observation of the Marmara operations. They began to explore wider options for recovery, including relocating the city. Although Duzce did not relocate as a city, the planning and reconstruction processes confirmed careful consideration of seismic risk in the redesign and reconstruction of the damaged structures. The changes made in Duzce immediately after the earthquake created the basis for improving management of seismic hazards in the region.2 SUMMARY, 1999 DUZCE, EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

The dimensions of time, space, scale, and energy shaped the changes in the Duzce response system that fit a different class of adaptation from the Marmara event. First, the time of the Duzce earthquake, occurring less than three weeks after the Marmara earthquake, raised the level of awareness of seismic

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risk for the residents of Duzce. The severity of damage and high losses in lives and property incurred from the Marmara earthquake underscored the potential threat to Duzce, located less than 120 kilometers to the east. Since many personnel in Duzce had volunteered to assist in the Marmara earthquake, they gained insight and experience from those operations and acted quickly to facilitate implementation of existing policies and resources that had been mobilized in response to the Marmara event (Comfort and Sungu, 2001a, b). Second, space influenced the design of housing and engineered infrastructure in Duzce. Exposed to comparable seismic hazards as the Marmara region, construction patterns in Duzce were regrettably similar to those found in the collapsed structures of the Marmara earthquake, and confirmed the discrepancy between building codes and practice. Although building codes and the National Disaster Law were in place, the knowledge, commitment, and action needed to implement them were not. Evidence from the Duzce case underscored the lack of implementation of engineering standards and the need for stronger review of construction and enforcement of building codes and other mitigation practices. The Duzce case provoked debate regarding the wisdom of rebuilding the damaged city at its existing location on the Duzce fault and prompted an external offer of resources to rebuild the city at a different site (Personal communication, Duzce, May 2000). Third, growing recognition of seismic hazard in this vulnerable region and compelling need for change in construction practices in Duzce confirmed that multiple scales of operation are required to manage seismic risk sustainably in areas exposed to seismic hazards. This need led to the designation of Duzce as the 81st city of Turkey, a status that conferred provincial authority to the city and greater access to central government’s resources and guidance. Finally, the rapid establishment of telecommunications capacity by Turk Telekom after the Duzce event demonstrated the role of information as the energy that activates interorganizational performance in complex adaptive systems. The four dimensions illustrate progress made in Duzce in managing seismic risk but also point to gaps in integration that identify constraints and require further commitment and investment to achieve sustainable risk reduction. Largely missing were the private and nonprofit organizations that could serve as intermediaries in building a local network of actors to sustain a focus on seismic risk reduction. The 2009 Padang, Indonesia, Earthquake INITIAL CONDITIONS

As one of six cities selected by the government of Indonesia to demonstrate its commitment to disaster planning and preparedness after the devastating 2004 Sumatran earthquake and tsunami, Padang, located on the west coast of Sumatra, benefited from systematic public investment in disaster preparedness.

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This investment focused on disaster planning and training exercises for tsunami evacuation, construction of new vertical tsunami shelters, and newly installed signage for tsunami evacuation routes throughout the city. In January 2009, the Indonesian government implemented a newly developed national disaster management plan intended to overcome weaknesses in disaster response operations that led to an estimated 220,000 deaths in the 2004 Sumatran earthquake and tsunami (EERI 2005; Comfort 2007a). Residents of Padang are exposed to substantial seismic risk, as two-­thirds of the population of this coastal city of approximately 900,0003 live in the “red zone,” an area of the city that is less than five meters above sea level. With keen recognition of risk from tsunami hazards, the national, provincial, and city agencies responsible for disaster preparedness had taken substantive actions to reduce disaster risk. CHARACTERIZATION OF THE 2009 PADANG EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

On September 30, 2009, at 5:18 p.m., school children were leaving their classes, businesses were closing for the day, and the evening rush hour was already underway when a severe earthquake, Mw = 7.6, struck the city of Padang, West Sumatra. The earthquake, with an epicenter located in the Menta­wai Sea about 60 kilometers west-­northwest from Padang, generated a powerful shock that severely tested Indonesia’s newly implemented national disaster plan (BNPB 2009). At a depth of approximately 80 kilometers, the earthquake produced a barely perceptible tsunami of approximately 10 centimeters but damaged buildings and infrastructure heavily in Padang and surrounding coastal districts (EERI 2009). Further, intensive public education on tsunami preparedness had an unintended harmful effect in Padang’s urban context, given extensive damage to infrastructure, communications, and transportation routes caused by the earthquake. Residents had been taught to evacuate immediately to high ground when they feel the ground shake from an earthquake. As people felt the tremors, hundreds of thousands of residents of Padang City, including emergency personnel, swarmed into the streets to seek high ground, using any means of transportation available—cars, trucks, motorbikes—instead of evacuating on foot as the plans outlined. Crowds spilled into narrow streets and blocked the limited number of bridges in the city, creating a colossal traffic jam that endangered lives and obstructed passage for emergency services vehicles as they sought to put out fires ignited by broken gas lines or ruptured electrical connections. The city’s Planning Department collapsed, rendering the GIS system and mapping database unusable, limiting support for timely, informed decisions regarding allocation of resources to meet immediate demands. Communica-

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tions fell silent as landlines were disrupted and cell phone towers were damaged, leaving only one cell phone service out of three available for the city, and another functioning only in parts of the city (EERI 2009). Newly constructed vertical tsunami evacuation structures incurred structural damage from the earthquake and proved unsafe; fortunately, the structures were still unfamiliar to city residents and most people did not try to use them. An estimated 1,117 lives were lost in this event.4 Ironically, many actions taken to reduce risk of a near-­field tsunami increased risk to residents from the stronger earthquake hazard. This finding underscored the known fact that not all undersea earthquakes generate tsunamis and highlighted the uncertainty of determining which earthquakes do and which do not. The frequency distribution of organizations participating in the 2009 Padang response system, as documented by a content analysis of reports in local Indonesian newspapers, is presented in table 6.3.5 Public organizations represented the largest proportion, 75.5%, of the 282 actors engaged in disaster operations in Padang, with nonprofit organizations at 16.7% and private organizations at 7.1%, as reported in the news articles for three weeks after the event. Surprisingly, the largest proportion of actors by jurisdiction was international, at 43.27%, with national organizations at 32.62%, and smaller proportions participating from subnational jurisdictions, despite the roles specified for these organizations in the National Disaster Management Plan (BNPB 2009). Figure 6.5 presents the rate of change among the full system of organizations over the first three weeks of response operations, as identified in reports from local Indonesian newspapers. The findings show a sharp increase in the number of organizations participating in response operations on day 2, followed by a sharp drop on day 3, a small uptick on day 4, and declining irregularly to virtually steady state by day 12. Investment in disaster preparedness following the 2004 Sumatran earthquake and tsunami contributed to more timely organizational response, but weaknesses appeared that had not been anticipated in the January 2009 disaster plan. The impact of disaster preparedness education and training is shown in the types of transactions that were identified in the content analysis of news reports regarding disaster operations, presented in appendix I, table I.6.2. The largest proportion of identified transactions included emergency response (15%) coupled with coordination (14%), for 29%. The combined categories of disaster relief (10.2%), medical care/health (9.4%), and donations (8.5%) accounted for 28.1% of transactions. Lesser categories included transactions involving repairing/restoring utilities and reconstruction (7.7%) and damage/ needs assessment (5.1%). Other categories of reconstruction and recovery made up the remaining 30% of transactions. Overall, the transactions reported a more focused set of response operations with priorities largely following

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99 19 4 0 122

N

35.11 6.74 1.42 0.00 43.27

%

International

65 16 9 2 92

N 23.05 5.67 3.19 0.71 32.62

%

National

2 1 0 0 3

N 0.71 0.35 0.00 0.00 1.06

%

Special Region

26 3 2 0 31

N 9.22 1.06 0.71 0.00 10.99

%

Provincial

3 0 1 0 4

N 1.06 0.00 0.35 0.00 1.42

%

Regency

12 0 3 0 15

N 4.26 0.00 1.06 0.00 5.32

%

Municipal

4 0 0 0 4

N

1.42 0.00 0.00 0.00 1.42

%

District

2 8 1 0 11

N

0.71 2.84 0.35 0.00 3.90

%

Local

Frequency Distribution of Organizations Engaged in 2009 Padang Earthquake Response System, by Jurisdiction, Funding Sector

Data sources: Antara, newswire feed of local newspapers from West Sumatra and Indonesia, October 1–­21, 2009.

Public Nonprofit Private Political Total

TABLE 6.3.

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% 213 75.53 47 16.67 20 7.09 2 0.71 282 100.00

N

Total

O p e r ativ e A da ptiv e Syste ms 109

180 160

Number / %

140

Padang response system Total number of organizations Cumulative percentage of organizations Rate of change (%)

120 100 80 60 40 20

9/

30

10 /20 /1 09 10 /20 /2 09 10 /20 /3 09 10 /20 /4 09 10 /20 /5 09 10 /20 /6 09 10 /20 /7 09 10 /20 /8 09 10 /20 /9 09 10 /20 /1 09 10 0/2 /1 00 10 1/2 9 /1 00 10 2/2 9 /1 00 10 3/2 9 /1 00 10 4/2 9 /1 00 10 5/2 9 /1 00 10 6/2 9 /1 00 10 7/2 9 /1 00 10 8/2 9 /1 00 10 9/2 9 /2 00 10 0/2 9 /2 00 10 1/2 9 /2 00 2/ 9 20 09

0

Date FIGURE 6.5 . Rate of change in the 2009 Padang, Indonesia, response and recovery system.

Data sources: Antara, Indonesian newspapers, October 1–­21, 2009. Figure by Jee Eun Song.

planned guidelines. The relatively high number of transactions involving coordination document a noticeable effort to integrate response operations from different agencies, jurisdictions, although the system-­wide integration of response operations proposed by the National Disaster Plan still eluded the residents of Padang. Figure 6.6 presents a network diagram of the top 20 organizations participating in Padang disaster response operations, ranked by betweenness centrality. The icons are sized by the organizations’ values in betweenness centrality, reported in table 6.4. The diagram shows a sparse network with density of 0.006 and a diameter of 14, indicating a wide dispersion of actors. Reflecting the structure of the 2009 National Disaster Management Plan, adopted in January 2009, before the earthquake, interactions among the participating organizations largely followed the designated plan. The organization with the largest value of betweenness centrality (5,118.9), that is, the actor connecting organizations in response operations that would otherwise not be connected, is the government of Indonesia in general, including the Parliament, which passes legislation to serve the whole nation. Ranking second is the Office of the President of Indonesia at 4,630.2. Next as connecting links with similar degree centrality values, that is, the number of organizations in the network to which they are connected, but differing ­betweenness values, are the United Nations and the Indonesian Red Cross,

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Jurisdiction

Funding sector

International

Public

National

Private

Province

Nonprofit

PadGOV

IoMPW

Municipal IoOVP

PadOOM WSP

WSOOG AusOFM

GoAUS

IoRC

IoOOP

ISAR GoINDO WSPWD

IoBNPB

AusADF UN

UNICEF FIGURE 6.6 . Top 20 organizations engaged in 2009 Padang response system, ranked by betweenness centrality, with jurisdiction and funding sector. Acronyms listed in table 6.4. Graph level metrics: diameter: 14; density: 0.006; degree centrality: 0.101; betweenness centrality: 0.128. Data sources: Antara, Indonesian newspapers, October 1–­21, 2009. Figure by Jee Eun Song.

WSBPBD

Telkom PTPLN

with the UN ranking higher in betweenness, that is, in connecting organizations that would otherwise not be connected. Interestingly, the government of Australia ranks higher in betweenness centrality than the mayor of Padang, but the order is reversed for degree centrality, as shown in table 6.4. Table 6.4 also reports the jurisdiction and funding sector for the top 20 organizations. Interestingly, and consistent with the 2009 national disaster plan, 18 of the top 20 organizations are public, with one nonprofit organization, Indonesian Red Cross, and one private organization, PT Telkom Group, identified as actively connecting organizations that would otherwise not be connected in response operations. Of the 18 public organizations, 6 are international, 6 national, 4 provincial, and 2 municipal, indicating a distribution of responsibility across jurisdictions, but verifying the significant role that inter-

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TABLE 6.4. Top 20 Organizations Participating in 2009 Padang, Indonesia, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

GOINDO IOOOP

Government of Indonesia Office of the President of Indonesia (Susilo Bambang Yudhoyono) United Nations Indonesian Red Cross Government of Australia Office of Mayor, Padang (Fauzi Bahar) UN Children’s Fund (UNICEF) West Sumatra Province West Sumatra Disaster Center Australian Office of Foreign Minister (Stephen Smith) Indonesian National Disaster Management Agency (head: Syamsul Maarif ) Indonesian Ministry of Public Works International SAR Team (rescue workers) Padang government PT Telkom Group Australian Defence Force Office of Vice President of Indonesia ( Jusuf Kalla) PT PLN Electricity Company West Sumatra Public Works Office of West Sumatra Governor (Gamawan Fauzi)

Public Public

UN IORC GOAUS PADOOM UNICEF WSP WSBPBD AUSOFM IOBNPB

IOMPW ISAR PADGOV TELKOM AUSADF IOOVP PTPLN WSPWD WSOOG

Betweenness

Degree

National National

5,118.87 4,630.19

26 30

Public Nonprofit Public Public

International National International Municipal

2,635.26 1,430.95 1,403.30 1,221.58

16 16 7 14

Public

International

1,125.00

2

Public Public

Provincial Provincial

1,040.66 1,023.00

9 3

Public

International

720.57

10

Public

National

685.54

12

Public

National

645.00

4

Public

International

525.43

5

Public Private Public Public

Municipal National International National

523.00 520.00 464.33 429.83

3 2 8 6

Public Public Public

National Provincial Provincial

393.00 393.00 360.25

2 2 9

Data sources: Antara, Indonesian newspapers, October 1–­21, 2009.

national organizations played in this response system. These findings indicate that substantive change occurred in Indonesian capacity for managing risk during the five-­year period following the 2004 Sumatran earthquake and tsunami, but that the challenges continue. Notably missing are local private and nonprofit organizations that could serve as intermediaries between international and national organizations and community residents in building long-­ term, sustainable management of seismic risk.

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CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Professional reports from Indonesian agencies, international reconnaissance teams, and governmental development agencies contributed careful analysis and assessment of the scientific, technical, and organizational characteristics of this event (Boen 2005; 2009/2010; Sengara et al. 2010; United Nations 2009). With its high vulnerability to seismic, meteorological, and climate hazards, Indonesia represents a virtual international field laboratory for the study of risk and likely consequences for coastal and urban populations. Continuing assessment of seismic risk in these areas that are changing dynamically in physical, engineered, organizational, and social characteristics is essential to plan strategies that are both practical and effective. Importantly, the 2009 Padang earthquake served as a catalyst for invoking systematic study across both jurisdictional and disciplinary boundaries. SUMMARY, 2009 PADANG, INDONESIA, EARTHQUAKE

The 2009 Padang earthquake served as a robust test of the National Disaster Management Plan enacted by the government of Indonesia in 2008 and implemented in January 2009. It is unusual to have such a timely opportunity to assess the feasibility of disaster management policy and procedures in practice, as well as to review the effectiveness of nearly three years of public education and training among varied population groups. The dimensions of time, space, scale, and energy focused the trajectory of response and recovery operations for the Padang response system in different ways than anticipated. Regarding the dimension of time, the shadow of the 2004 Sumatran earthquake and tsunami influenced public perception and response to the 2009 event in not altogether constructive ways. Given the intense losses in Sumatra from the 2004 event, community preparedness and disaster training activities had focused primarily on tsunami risk, not on earthquake safety. In practice, the guidance for the two types of events differs, and it is essential for the community at risk to distinguish between the types of threats. In tsunamis, the guidance is that everyone should run immediately to higher ground. In earthquakes, people are taught to find the strongest, safest structure immediately at hand and “duck, cover, and hold on!” In the Padang event, vivid recollection of the 2004 tsunami sent the residents of Padang into the streets, without waiting for verification of a tsunami. The resulting cacophony in traffic and disruption despite no significant tsunami created a near secondary disaster for the city and underscored the need for a continual process of interdisciplinary assessment and review of seismic risk. The natural setting and geological space of a coastal city, vulnerable to interacting

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hazards of earthquakes, tsunamis, and flooding, cannot be managed from one analytical perspective alone. While communications and coordination clearly improved among the public agencies with responsibilities in disaster operations following the Padang earthquake, different scales of operation were not clearly defined. For example, the mayor of Padang played a stronger role in organizing response operations than the governor of West Sumatra, as designated in the formal disaster plan. When the earthquake seriously damaged the city of Padang’s Emergency Operations Center, the mayor moved the Operations Center to his home in an area of the city that still had cell phone service. Consequently, both national and international organizations reported to the city’s EOC, not the provincial EOC of West Sumatra. The dynamic mayor simply filled the vacuum left by a provincial office with staff that had little experience or training in disaster management and had not fully implemented the newly adopted national plan. In doing so, the mayor interacted directly with national and international organizations, blurring the roles of leadership in areas that were not well defined.6 Further, private and nonprofit organizations—businesses, schools, hospitals, mosques—were not well represented in the operational system. Especially for a threat from near-­field tsunamis that allow a warning time of 30 minutes or less, the full set of community organizations needs to be involved in planning, exercising, and updating designed strategies for managing seismic risk. Finally, findings from the analysis of the 2009 Padang response system confirm the continuing role of information in activating the energy that drives the iterative inquiry into the dynamics of risk. It is through the process of conducting inquiry into interorganizational, interjurisdictional, interdisciplinary management of seismic risk that responsible managers, scholars, and citizens develop the capacity for collaborative risk reduction, in Indonesia and elsewhere. The March 11, 2011, Tohoku, Japan, Earthquake, Tsunami, and Nuclear Breach INITIAL CONDITIONS

By all accounts, the population of Japan is keenly aware of seismic risk. Located at the juncture of four tectonic plates, Japan is subject to earthquakes of some magnitude almost daily. Experience with major earthquakes and tsunamis over centuries, with ensuing heavy losses in population and property, has led the government of Japan to invest heavily in risk reduction measures as a means of anticipating extreme events and enabling more informed, timely response to known seismic risk. Yet, given the current state of knowledge in geophysics, it is not possible to predict the actual time, place, or severity of

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such an event. Consequently, the risk is real, and the challenge for Japan is to determine the appropriate mix of public policies and investment to assure robust technical design, reliable organizational procedures, and broad cultural awareness to protect the population and its civil infrastructure from seismic hazards. Sobered by the loss of over 6,000 lives and the costs of an estimated $100 billion incurred in the 1995 Hanshin-­Awaji earthquake, which severely damaged the city of Kobe, policy makers in Japan made a concerted effort to review and revise disaster plans for the nation (Comfort 1999a; Aldrich 2012). Over a ten-­year period, 1995–2005, the government of Japan invested approximately $59.2 billion in programs to revise and update seismic monitoring, earthquake building codes, training for emergency personnel, and community education (Cabinet Office of Japan, 2011b). School children learned to “duck and cover” in event of an earthquake; local governments organized training exercises for emergency services personnel; and communities held neighborhood meetings for sharing information regarding shelters, supplies, and basic earthquake preparedness. Japan implemented an advanced seismic network that sent messages directly to households for any earthquake over 4.0 Richter scale. Building codes were reviewed and updated, and engineering firms were tasked to plan for transportation safety in metropolitan regions. Developing careful and measured plans, Japanese policy makers and managers of public, private, and nonprofit organizations made conscious, informed decisions to mitigate earthquake risk. Although tsunamis are generated by undersea earthquakes, such hazards occur less frequently than earthquakes and were given less attention in the national planning process. Rather, preparedness for tsunamis was considered a subset of earthquake mitigation tasks. A third hazard, potential damage to coastal nuclear power plants by earthquakes and tsunamis, was largely not included in disaster planning by public agencies, as responsibility for managing nuclear plants was essentially assigned to private engineering companies that built and operated the plants. Disaster plans, detailed by jurisdictional level, were designed separately for each hazard—earthquake, tsunami, nuclear breach—with little recognition of their potential interaction and catastrophic disruption for the whole system (Comfort, Okada, and Ertan 2011). On March 10, 2011, the operational conditions for managing seismic hazards in Japan portrayed a technically sound infrastructure designed to meet existing building codes, emergency response personnel well trained for earthquake response operations, and an informed public that ostensibly could manage seismic risk appropriately with minimal damage to population, infrastructure, and socioeconomic productivity (Fujinawa and Noda 2013). Coastal villages were protected from tsunamis by seawalls or breakwaters, designed to withstand the threat of the most recent tsunami. Nuclear plants were pre-

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sumed to be operating under existing safety standards, managed by engineering companies. By standard measures, Japan appeared well prepared for seismic risk. CHARACTERIZATION OF 2011 TOHOKU, JAPAN, EARTHQUAKE, TSUNAMI, AND NUCLEAR RELEASE SYSTEM

On Friday, March 11, 2011, at 2:46 p.m., Japan time, a major undersea earthquake, measuring Mw = 9.0, struck off the northeast coast of Japan. In seconds, Japan’s advanced seismic network automatically alerted practiced teams of emergency response personnel who activated emergency plans and alerted local populations in communities of the Tohoku region. Buildings built to seismic standards largely held. Electrical power shut down throughout the Tohoku region, but in most locations, it was quickly brought back by emergency generators, purchased to provide backup power, if needed. In immediate reaction to the earthquake, residents of the small cities and fishing villages along the coasts of Iwate, Miyagi, and Fukushima Prefectures believed they had escaped potential damage at minimal cost. Five minutes later, there was an alert for a tsunami, potentially three meters in height. Yet small cities like Taro in Iwate Prefecture were confident that their seawall, 10 meters high, would protect them and did not leave the city. In 15 minutes, a second warning increased the estimated height of the incoming tsunami to five to seven meters. Still, residents of the town were confident that the seawall would protect them. Forty-­five minutes later, while the tsunami model was still seeking to match the characteristics of the Mw = 9.0 earthquake, a 15-­meter tsunami crashed onto the coast of Taro, overtopping the seawall and destroying much of the city. Similar scenes occurred along the 450-­kilometer coastline of northeastern Japan, as coastal communities were deluged by three successive tsunami waves, some reaching 40 meters in height in inlets along the jagged coastline. Most damaging was the wave that struck Fukushima Prefecture, and disabled the generators that cooled the Fukushima Daiichi nuclear power plant, releasing radioactive pollution into the air, land, and sea in the immediate vicinity. There was virtually no provision in the Disaster Countermeasures Basic Act of 1961 (Cabinet Office of Japan, 2011a) for managing failure in a nuclear power plant. That responsibility had largely been assigned to the engineering company that built and operated the plant, Tokyo Electric Power Company, because of the specialized knowledge and skills needed manage such a highly advanced, very complex, sociotechnical system. This cascade of extreme events—a severe undersea earthquake generating massive tsunami waves that disabled a nuclear reactor—overwhelmed the capacity of Japan’s well-­honed disaster response system at every jurisdictional level—municipal, prefectural,

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and national. An estimated 18,391 persons were reported dead or missing in this extreme event; the total cost of damages, initially reported at $200 billion (Comfort, Okada, and Ertan 2013), is still being tallied, eight years later. Table 6.5 presents the frequency distribution of organizations engaged in response and recovery. The distribution of actors for the Tohoku system differs from other response systems included in this class of operative adaptive systems both in the large size of the overall system, 1,100 actors, and in the distribution of actors among funding sectors and jurisdictions. Nearly 50% of the actors in the Tohoku response system were from the public sector, but significantly, over 35% of the actors were from the private sector, with the largest proportion of private organizations operating at the national level. Public sector actors were distributed relatively evenly across the jurisdictions, with national organizations representing 16.1%, but prefectural, international, and municipal jurisdictions contributing 11.9%, 11.1% and 10.1% respectively, of actors to the system. Nonprofit organizations represented a modest proportion of the whole system, or 11.7%. Also interesting was the small but notable participation of political parties in the dialogue at the national level, 3.4%. This relatively even distribution of participating actors demonstrates a substantial degree of awareness of risk, engagement in risk reduction activities, and integration of risk preparedness policies into practice across the whole Japanese society. Figure 6.7 shows the rate of change in the 2011 Tohoku, Japan, response and recovery system, indicating an immediate high response of organizations entering the system on day 1, followed by a sharp drop on day 2, an increase of organizations entering the system again on day 3, and a relatively jagged pattern of participation over the remaining three-­week period. This graph represents the number of organizations identified in news articles in the Yomiuri Shimbun, a national newspaper of Japan published in Tokyo, reporting transactions over three weeks, March 11, 2011–April 1, 2011. The number of transactions as well as the number of actors engaged in them are reported in appendix I, table I.6.3, documenting a response and recovery system for this catastrophic sequence of events. Over 3,882 transactions were performed by 4,721 actors over the period March 12–April 1, 2011. Using the same set of categories that were coded for the other earthquake response systems, articles on transportation and traffic issues received the highest number of mentions, or 11.8%, as airports were closed, railroads were shut down, and highways were damaged from the sequence of destructive events, earthquake, tsunamis, and radioactive pollution over the three-­week period. Communications/IT ranked second, at 9.5%, in types of transactions reported in the content analysis, documenting the focus on interaction among organizations in Japan, as practicing managers at every level of decision-­ making authority scrambled to mobilize effective operations to this extra­ ordinary set of events. Emergency response (8.3%) and coordination for re-

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122 8 36 0 166

11.09 0.73 3.27 0.00 15.09

% 177 71 230 37 515

N 16.09 6.45 20.91 3.36 46.82

%

National N 11.91 2.00 3.27 0.00 17.18

%

Prefectural

131 22 36 0 189

Data source: Yomiuri newspaper, Tokyo, Japan, March 12–­April 1, 2011.

Public Nonprofit Private Political party Total

N

International

3 1 27 0 31

N 0.27 0.09 2.45 0.00 2.82

%

Regional

111 19 19 0 149

N 10.09 1.73 1.73 0.00 13.55

%

Municipal

3 8 39 0 50

N

Local

0.27 0.73 3.55 0.00 4.55

%

547 129 387 37 1,100

N

% 49.73 11.73 35.18 3.36 100.00

Total

TABLE 6.5. Frequency Distribution of Organizations Participating in the 2011 Tohoku Earthquake, Tsunami, and Nuclear Reactor Breach Response System, by Jurisdiction and Funding Sector

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180

Tohoku response system

160

Total number of organizations Cumulative percentage of organizations Rate of change (%)

Number / %

140 120 100 80 60 40 20

1 /2

01

1 31 3/

/2

01

1 29 3/

/2

01

1 27 3/

/2

01

1 25 3/

/2

01

1 3/

23

/2

01

1 21 3/

/2

01

1 19 3/

/2

01

1 17 3/

3/

15

/2

01

1 01 /2 13

3/

3/

11

/2

01

1

0

Date FIGURE 6.7. Rate of change in 2011 Tohoku, Japan, response and recovery system. Data source: Yomiuri Shimbun, Tokyo, Japan, March 12–­April 1, 2011. Figure by Jee Eun Song.

sponse, recovery (7.6%) together accounted for 15.9%. Disaster relief (7.4%) and damage/needs assessment (6.3%) combined tallied 13.7%. Some categories differed markedly from transactions reported in other earthquake response systems, documenting differences in both organization and culture. For example, no actions were reported for the categories of security/prevention of looting, building inspection, or building code issues, a striking difference that underscores the communal response to disaster in Japanese culture and to sound technical performance of engineered buildings built to earthquake resistant codes. Closely related sets of transactions drew attention, as categories of business recovery and economic/business issues combined constituted 11.4% of transactions, transportation/traffic at 11.8%; repairing/restoring utilities, and repair/reconstruction/recovery, combined, represented 9.4% of total transactions, indicating severe disruption of electrical power with the shutdown of nuclear power plants. Figure 6.8 shows a network diagram of the top 20 organizations engaged in response and recovery operations in the 2011 Tohoku response system, ranked by betweenness centrality. Public organizations dominated the response operations, with one prominent private actor, Tokyo Electric Power playing a large role. Two nonprofit organizations, the Japan Diabetes Society and the Prefab Club, served as connecting links between organizations, and the Democratic Party of Japan, a political party, was active in linking organizations through disaster relief and medical care. The organizations shown in the diagram, with their acronyms and full organizational names, are listed in table 6.6. The distribution of organizations

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maff

mofa_min

miac

us_gov

fukushima_gv mod_min

japan_gov tepco

jp_pm

dpj_sg

iwate miyagi

sdf

mlit

fukushima

us_army

Jurisdiction

prehab

mhlw

Funding sector

International

Public

National

Private

Regional

Nonprofit

Prefectural

Political party

fukushimam_hosp

jds

Municipal FIGURE 6.8 . Top 20 organizations in 2011 Tohoku, Japan, response and recovery system, ranked by be-

tweenness centrality. Acronyms listed in table 6.6. Graph level metrics: diameter: 11; density: 0.001; degree centrality: 0.08; betweenness centrality: 0.037. Data source: Yomiuri newspaper, Tokyo, Japan, March 12–­ April 1, 2011. Figure by Jee Eun Song.

among jurisdictions and types of funding sectors in Japan reveal a largely well-­ informed response system that was guided by national policy for the earthquake threat. Of the top 20 organizations active in response operations ordered by betweenness centrality, that is, actors linking organizations that would otherwise not be connected, 12 were national, 5 were prefectural, 1 was regional (encompassing two or more prefectures), and 2 were international. Community residents and prefectural and local governments were less informed, less prepared for the tsunami threat, and less integrated into the overall response system. The Fukushima Nuclear Reactor breach with the ensuing release of radioactive pollution into the surrounding region was almost wholly beyond the capacity and range of local government officials. The lack of awareness of the tsunami threat weakened the overall capacity of Japan’s operational system to manage a well-­designed response to earthquake risk.

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Top 20 Organizations in 2011 Tohoku, Japan, Response and Recovery System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

TABLE 6.6.

Acronym

Full Name

Funding

Jurisdiction

jp_pm

Office of the Prime Minister, Japan Government of Japan Tokyo Electric Power Company Iwate Prefecture Self-­Defense Force, Japan Ministry of Health, Labor, and Welfare Miyagi Prefecture Fukushima Prefecture Office of Secretary General, Democratic Party of Japan Office of the Minister of Foreign Affairs Fukushima Medical University Hospital (Fukushima Prefecture) Japan Diabetes Society Ministry of Land, Infrastructure, Transport, and Tourism Government of United States Ministry of Internal Affairs and Communications Office of the Governor, Fukushima Prefecture Prehab Club Ministry of Agriculture, Forestry, and Fisheries Office of the Defense Minister, Japan US Army

Public

japan_gov tepco iwate sdf mhlw miyagi fukushima dpj_sg mofa_min fukushimam_hosp

jds mlit

us_gov miac fukushima_gv prehab maff mod_min us_army

Betweenness

Degree

National

22,680.29

89

Public Private

National Regional

16,708.57 10,753.81

68 40

Public Public Public

Prefectural National National

9,591.03 8,941.33 6,830.43

36 16 14

Public Public Pol. party

Prefectural Prefectural National

5,700.91 5,632.11 5,314.26

22 20 32

Public

National

5,146.03

33

Public

Prefectural

4,144.00

2

Nonprofit Public

National National

3,939.00 2,641.60

14 13

Public Public

International National

2,500.25 2,231.92

7 9

Public

Prefectural

2,216.89

8

Nonprofit Public

National National

2,177.59 2,170.75

12 6

Public

National

1,876.34

7

Public

International

1,852.93

18

Data source: Yomiuri Shimbun, Tokyo, Japan, March 12–­April 1, 2011.

CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Given the size, scale, and extraordinary consequences of the Tohoku triple disasters of March 11, 2011, in Japan, extensive review and analyses of the conditions and characteristics that led to this cascade of destructive events have been conducted by researchers in Japan and in the international research com-

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munity (Fujinawa and Noda 2013; Maki 2013; Comfort, Okada, and Ertan 2013; Tatsuki 2013; Brittingham and Wachtendorf 2013; Kajitani, Chang, and Tatano 2013; Iuchi, Johnson, and Olshansky 2013; Holguín-­Veras et al. 2012). A range of experienced analysts from multiple disciplines—engineering, seismology, sociology, economics, public policy—examined this set of interacting events in detail to understand the interdependencies that led to such devastating consequences. A consensus emerged in the research community that Japan had made informed, substantial investments in earthquake mitigation and preparedness that significantly reduced the impact and cost of earthquake damage. The interaction between the earthquake and tsunami generation, however, exceeded the capacity of current tsunami detection models and gravely underestimated the subsequent impact of a large tsunami on the Fukushima nuclear reactor, Daiichi. The event exceeded not only the estimates employed, but also the imagination of the policy makers who designed the nuclear plant and its safety constraints. Many experienced analysts reached the sobering conclusion that the catastrophic scope and scale of this series of interacting events was beyond the capacity of policy makers constrained by single disciplines or single modeling approaches. The critical question is how to construct a valid process of inquiry to explore what scientists and engineers do not know or understand about seismic risk. Further, if constructed, how could such a method be applied to the still unexplored areas of seismic risk interacting with human communities and physical infrastructure in changing conditions. The limits of Japan’s conscientious disaster mitigation and policy making were revealed in this event, but systematic study of the underlying conditions necessarily continues. SUMMARY, 2011 TOHOKU TRIPLE DISASTERS

The 2011 Tohoku triple disasters created the largest challenge to seismic risk assessment, mitigation, planning, and response that Japan—or any other country to date—had experienced. The event, which exceeded Japan’s carefully designed and developed procedures for earthquake risk mitigation that were moving toward auto-­adaptive capacity with advanced seismic monitoring, automatic early warning systems, and significant investment in community preparedness activities (Comfort 1999a; Comfort 2004b), returned Japan to the classification of operative adaptive systems. Japan has achieved substantial advances in technology, organizational preparedness, and cultural awareness of earthquake risk, but the comprehension of risk from massive tsunami waves striking vulnerable coastal communities and malfunction of large-­scale sociotechnical systems triggered by tsunamis was outside the capacity of Japanese policy makers and disaster management planning in 2011. The event and its consequences engendered a global inquiry into seismic risk, and Japan has

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established an International Research Institute in Disaster Science at Tohoku University, with collaborating institutions from all of Japan and many international regions subject to seismic risk (IRIDeS 2012). This research institute has a specific mission to explore the potential of megadisasters on a global scale. While the research is ongoing, and definitive models are elusive, the commitment and investment in time, personnel, and funding to develop innovative approaches to identify and model potential catastrophic events represents a productive step toward addressing dynamic interactions in large-­ scale sociotechnical problems that are characterized as complex adaptive systems of systems. The dimensions of time, space, scale, and energy influenced the emergence of the disaster operations system in unexpected ways in the Tohoku event. In terms of time, the 1,000-­year interval from the last earthquake of magnitude 9.0 off the Sanriku coast of Japan defied current estimates of seismic activity in Japan. The most advanced tsunami model run by the Japan Meteorological Agency failed to identify a match in the historical record of earthquakes and missed timely warning to the coastal population at risk (Personal communication, Iwate Prefecture, Japan, 2011). The standard measures of seismic activity proved inadequate to assess this event by a very large margin. Consequently, the transition from response to recovery activities in Japan in 2011 proved difficult, painful, and slow. The credibility of Japanese public agencies responsible for managing seismic hazards suffered significant setbacks as the nation struggled to cope with the losses and aftermath from this major disaster. The resignation of Premier Naoto Kan, the public face of the Japan government’s response, in August 2011, reflected a loss of confidence in his leadership by the Japanese Diet and the population (Yomiuri Shimbun, August 26, 2011). Space proved to be a defining dimension that shaped response operations as Japanese policy makers sought practical solutions to this cascading problem. All 47 prefectures of Japan were affected to some degree by this disaster. Further, the spread of radiation had not only national but also international consequences, as radioactive material polluted not only the soil in Fukushima Prefecture, the “rice bowl” of Japan, but also the ocean waters, harming Japan’s fishing industry and tainting the fishing industries of neighboring South Korea and China. Coping with the wide span of damaging consequences from this event proved challenging to policy makers at all jurisdictional levels: local, prefectural, national, and international. Given the broad physical and social spaces that were affected by the disaster, different scales of operation were essential. Managing basic functions like the delivery of electrical power required cooperation across national, prefectural, and district boundaries, as well as collaboration among government agencies, private companies, and nonprofit organizations. To achieve cooperation and collaboration, the search and exchange of information among mul-

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tiple actors is an ongoing task. Activating the organizational infrastructure to accomplish shared tasks required a constant infusion of social energy through the steady flow of updated, valid information. Slowly, social energy returned to Japan, and a national consensus regarding an expanded awareness of interacting hazards is emerging, as new groups in Japanese society engage in the transition process, but the overall system is not yet integrated or fully adaptive to ongoing seismic risk. New questions emerge from the experience of this catastrophic event. What are the minimal criteria for integration among social and technical systems to maintain coherent performance as the size and scale of the potential seismic hazard increases? What are the consequences of interdependence among social and technical systems when either type of system reaches its design limits? These and other questions remain for further study. The 2015 Nepal Earthquakes INITIAL CONDITIONS

Unlike other regions that experienced severe earthquakes, seismic risk was well known in Nepal.7 A history of severe earthquakes in the nation over centuries had alerted government agencies and nonprofit organizations to the continuing reality of earthquakes in this mountainous region. This recognition led to a series of preparedness actions taken prior to the April 25 and May 12, 2015, earthquakes that created a basic awareness of seismic risk among government agencies, nongovernmental organizations, and residents. Such preparedness actions, largely taken separately, served as an initial baseline for mobilizing collective action when the 2015 earthquakes occurred. In 1994, Nepal drafted a national building code to strengthen standards of construction in a nation of high seismic risk. The National Building Code was approved by the Nepal government in 2003 and became legally binding for all new construction (EERI 2015). Importantly, the nation had adopted a National Disaster Response Framework (NDRF) in March 2013 (Ministry of Home Affairs 2013). In the NDRF, the Ministry of Home Affairs serves as lead agency in managing disaster operations, with specified responsibilities assigned to other ministries and agencies. Recognizing the possibility of large-­scale disasters as well as limitations of resources and capacity, Nepali disaster planners included in the NDRF a detailed specification of responsibilities for Nepali government agencies that would serve as in-­country counterparts to United Nations (UN) agencies in implementing the UN cluster system for humanitarian aid. The cluster system, developed in 2005 under the UN Office for Coordination of Humanitarian Affairs (OCHA), is designed to facilitate the appeal for, and organization and distribution of, humanitarian aid from UN member nations to assist a fellow UN member that has experienced disaster. The UN organizational framework is activated by a request for humanitarian assistance from the government of

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an afflicted nation in event of a major disaster. The cluster system functions to allocate contributions of UN member nations seeking to assist nations stricken by disaster into 11 designated sectors for assistance, including food security, health, shelter, water, sanitation, and hygiene (United Nations 2005). In 2015, the government of Nepal requested assistance from the UN to cope with demands from the April 25 and May 12 earthquakes. In addition to positive steps taken by the government of Nepal to prepare for disaster, a national nonprofit organization, National Society for Earthquake Technology (NSET), has been actively engaged in disaster preparedness activities in Nepal for more than 20 years (Guragain 2015). While NSET is only one organization, it nonetheless has had a significant impact in raising awareness of seismic risk in Nepal through its training programs for masons, retrofitting of 300 schools, and enacting a broad campaign to inform local communities about seismic risk and practical measures to reduce it. Yet there are some 49,000 schools in Nepal, 6,000 of which suffered damage in the 2015 earthquakes (Lizundia et al. 2016). The scope of potential danger to schools exceeds the present capacity of a single organization, NSET, to reduce it alone. Other resources indicate positive steps taken by Nepal to form a coherent system for collaborative action among government agencies, nonprofit organizations, and community groups against seismic hazards. Importantly, the Nepal Police had established radio communications with all 75 districts in the country; the Armed Police had a working radio network with 48 of the 75 districts and used internet connections with districts in the lowlands of the Terai region and the Kathmandu Valley (Personal communication, Kathmandu, 2016). The Nepal Army actively used its GIS unit to guide response operations, and Kathmandu University created a GIS knowledge base of maps and other relevant information regarding the 14 districts that were severely affected by the 2015 earthquakes. An international nonprofit organization, International Centre for Integrated Mountain Development (ICIMOD), developed advanced satellite profiles and geographic spatial analysis of regions at risk from earthquakes and landslides in Nepal (Personal communication, Kathmandu, 2016). These cumulative actions show increasing awareness of seismic risk and progress toward building a digital knowledge base to inform decisions for managing seismic risk in Nepal as physical, social, and technological conditions changed. CHARACTERIZATION OF EMERGENT RESPONSE AND RECOVERY SYSTEM

Given broad awareness of seismic risk and marked investment in preparedness for seismic hazards, public agencies responded to the April 25, 2015, Nepal earthquake largely with timely, professional performance in the urban areas,

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but with greater difficulty in the mountain villages. The Mw = 7.8 earthquake, fortuitously, occurred on a Saturday morning, April 25, at 11:56 a.m., when children were not in school. Many families were in the markets, shopping or enjoying weekend activities outdoors. The epicenter of the earthquake was near Gorkha, some 76 kilometers northwest of the Kathmandu Valley, so the severe shaking largely missed the three major cities of Kathmandu, Patan, and Bhaktapur. In Kathmandu, newer buildings largely withstood the shaking, validating the implementation of the National Building Code adopted in 2003. Heritage buildings in all three valley cities, in contrast, were heavily damaged. The earthquakes documented the fact that investment in earthquake-­resistant design paid major dividends in reducing the loss of lives and built infrastructure in urban areas. While the official tally of deaths was 8,889, unacceptable by any measure, the number would likely have reached tens of thousands more without these preparedness measures (PDNA 2015; Personal communication, June 2015). Mobilization of response operations followed the National Disaster Response Framework (Ministry of Home Affairs 2013) with public agencies carrying out designated activities, facilitated by the radio network of the Nepal Police that operated in all 75 districts of the country. The Nepal Police network was augmented by the radio network of the Armed Police in 48 of the 75 districts (Personal communication, May 2016). Through these communications networks, the emergency services organizations could establish contact with mountain villages and determine the extent of losses and damage in the mountain areas. More difficult was transportation to provide humanitarian aid and medical care to the injured in these damaged villages, as mountain roads were blocked by more than 545 landslides in addition to erosion of roads and bridges damaged by the earthquake, severely limiting access to rural areas (Ministry of Mines and Geology 2015). In the capital city of Kathmandu, the National Information Technology Center (NITC) established an intranet for direct communication among all government agencies, as well as an earthquake portal web page to provide timely updates on the status of disaster operations for the public. The NITC web page also provided a link for donations to the prime minister’s Relief Fund (Personal communication, Kathmandu, June 2015). Satellite maps of the damaged mountain regions initially were provided by Google, a private company contributing valued expertise to the humanitarian response effort. Further detailed maps were provided by ICIMOD, Nepal Army, and Kathmandu Living Labs (KLL) to guide access to isolated areas. A major component of ­response operations was the government of Nepal’s request to the United ­Nations for humanitarian aid. This request activated UN OCHA and its cluster system, to which UN member nations responded with offers of assistance to Nepal, and designated Nepali public agencies and organizations played

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Frequency Distribution of Organizational Response System, April–­May 2015, Nepal Earthquakes, by Jurisdiction and Funding Sector

TABLE 6.7.

International

Public Nonprofit Private Total

National

District

Subdistrict

Total

N

%

N

%

N

%

N

%

N

%

120 23 7 150

35.50 6.80 2.07 44.38

72 32 18 122

21.30 9.47 5.33 36.09

48 7 2 57

14.20 2.07 0.59 16.86

6 1 2 9

1.78 0.30 0.59 2.66

246 63 29 338

72.78 18.64 8.58 100.00

Data source: Kathmandu Post, Kathmandu, Nepal, April 25–­May 16, 2015.

counterpart roles to UN agencies operating under the guidelines of OCHA to coordinate the receipt and distribution of international humanitarian assistance. Through a content analysis of newspaper articles published in the Kathmandu Post, a major English-­language newspaper published in Kathmandu, a research team at the Center for Disaster Management, University of Pittsburgh, identified a network of 338 organizations that were actively involved in disaster operations. While we acknowledge that this content analysis, conducted from articles published from April 25 to May 15, 2015, is likely incomplete, the results provide a partial profile of the types of organizations that were actively involved in disaster operations. As shown in table 6.7, the largest proportion of responding organizations, 72.8%, was public, with nonprofit organizations at 18.6% and private organizations a modest 8.6%. International organizations made up 44.4% of total participants identified in response operations, with national organizations at 36.1% and district organizations at 16.9%. Subdistrict organizations important in heavily damaged rural villages represented only 2.7%. While it included active participants at all levels, the response system proved to be clearly asymmetrical in practice. Figure 6.9 shows the rate of change in organizations entering the response system, tracked over 21 days following the April 25, 2015, earthquake, that were actively involved in disaster operations. The participation of organizations increased sharply on day 2 by more than 900%, followed by a steep decline on day 3 to a cumulative rate of relatively low participation of approximately 100 organizations for the remaining 18 days. This pattern documents the most intensive activities of search and rescue operations occurring during the first three days, then shifting to related operations of humanitarian assistance and recovery. The types of transactions performed during response operations for this same period of 21 days are reported in appendix I, table I.6.4. While the types

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1,000 900 800

Number / %

700

Nepal response system Total number of organizations Cumulative percentage of organizations Rate of change (%)

600 500 400 300 200 100

4/

25 / 4/ 201 26 5 / 4/ 201 27 5 / 4/ 201 28 5 / 4/ 201 29 5 /2 4/ 01 30 5 / 5/ 201 1/ 5 2 5/ 015 2/ 2 5/ 01 5 3/ 2 5/ 015 4/ 2 5/ 015 5/ 2 5/ 015 6/ 2 5/ 015 7/ 2 5/ 015 8/ 20 5/ 1 5 9/ 5/ 201 10 5 / 5/ 201 11 5 / 5/ 201 12 5 / 5/ 201 13 5 / 5/ 201 14 5 / 5/ 201 15 5 / 5/ 201 16 5 /2 01 5

0

Date

FIGURE 6.9 . Rate of change in April 25–­May 12, 2015 Nepal earthquakes response system.

Data source: Kathmandu Post, Kathmandu, Nepal, April 25–­May 16, 2015. Figure by Jee Eun Song.

of transactions listed in table I.6.4 have been documented in all 12 response systems, one new category, information technology–related transactions, was specifically added for the Nepal response system. Although representing a relatively small proportion of transactions, 2.2%, the interactions involved private sector organizations, both international and national, and indicate a growing capacity in technical expertise that was vital to the response effort in Nepal. These transactions validated the incorporation of information technology into disaster response operations by integrating new actors, advanced equipment, and data collection skills. Given the rugged terrain of the country and extensive damage to mountain roads, satellite imagery was used extensively in Nepal to identify communities that had incurred heavy damage and to assess possible strategies for rebuilding roads and reconstruction of schools, clinics, and water, electricity, and communications infrastructure for the mountain districts. The technical resources and skills of private companies, both national and international, added significant value to response operations. Reviewing the total number of transactions, 537, reported in the Kathmandu Post, the highest proportion, 15.3%, dealt with disaster relief. The second-­highest category, 15.1%, included donations of money or goods, followed by communications/coordination at 13.4%. Emergency response and medical care/health, combined, accounted for a total of 17.7%. Smaller categories important in Nepal included damage/needs assessment/preparedness,

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MOHAP

TUTH TIA USAID PM NTA NC

FB

NPOLI

IE

MOHA

PMDRF GON

MOF

DAO DEO

MOUD

ADB

Jurisdiction VDC

UN

Funding sector

International

Public

National

Private

District

Nonprofit

Subdistrict

FIGURE 6.10 . Network diagram of top 20 organizations, 2015 Nepal response system, ranked by betweenness centrality. Graph level statistics: diameter: 10; density: 0.005; degree centrality: 0.12; betweenness centrality: 0.071. Figure by Jee Eun Song.

building inspection issues, education issues, and repair/reconstruction/recovery (18.2%), with other types (20%) distributed among categories of community recovery. Over 55% of total actors (791) performing transactions were from national organizations, with 32% from international organizations and 12% from district organizations. Figure 6.10 presents a network diagram of the top 20 organizations participating in response ranked by betweenness centrality, that is, a network measure ordering actors that link organizations operating in the response system that would otherwise not be connected. Consequently, organizations with high betweenness values extend their influence throughout the whole network, providing a degree of coherence through connections that otherwise would not exist (Newman 2010). Full names of organizations, with their acronyms, are listed in table 6.8. As shown in figure 6.10, the prime minister and his office report the highest betweenness score (4,110.83), indicated by the icon in center of diagram. The Ministry of Home Affairs has legal responsibility for coordinating the overall system of response operations but ranks second, with betweenness values rounded to one decimal point, at 3,283.1 in between-

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TABLE 6.8. Top 20 Organizations in 2015 Nepal Earthquakes Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

PM MOHA DAO GON PMDRF

Prime minister Ministry of Home Affairs District Administration Office Government of Nepal Prime minister’s Disaster Relief Fund Ministry of Finance Tribhuvan University Teaching Hospital Ministry of Health and Population Tribhuvan International Airport Nepal Telecommunication Authority Nepal Police Ministry of Urban Development US Agency for International Development Nepali Congress Facebook Asian Development Bank Village Development Committee Indian Embassy District Education Office United Nations

Public Public Public Public Public

National National District National National

4,110.83 3,283.07 2,927.27 2,202.83 2,179.69

26 38 19 21 19

Public Public

National District

1,180.67 1,134.00

11 2

Public

National

1,041.00

8

Public Public

District National

871.23 719.48

4 4

Public Public Public

National National International

674.36 665.32 659.00

9 5 5

Nonprofit Private Public Public Public Public Public

National International International Subdistrict International District International

623.88 564.67 527.00 524.00 409.77 406.97 398.00

10 4 7 2 3 3 3

MOF TUTH MOHAP TIA NTA NPOLI MOUD USAID NC FB ADB VDC IE DEO UN

Betweenness

Degree

Data source: Kathmandu Post, Kathmandu, Nepal, April 25–­May 16, 2015.

ness centrality, and the District Administrative Office for the country, which works directly with the rural villages, ranks third, at 2,927.3, higher than the government of Nepal, the administrative category that includes the national Parliament, at 2,202.8. The active participation of international organizations in response operations for the 2015 Nepal earthquakes is indicated by the inclusion of the US Agency for International Development (659.0), Asian Development Bank (527.0), Indian Embassy (409.8), and the United Nations (398.0) in the list of top 20 organizations ranked by betweenness centrality. Although the UN is included in the top 20 organizations, it ranks the lowest of the top 20 in terms of betweenness values, an indication that the cluster system may not have served its intended role of connecting international with national and local organizations as fully as anticipated. The importance of electronic communication in response operations is underscored by the inclusion of Facebook, a private company, in the list of top

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20 organizations with a betweenness score of 564.7. The response system operated across all jurisdictions, from the international UN agencies to the Village Development Committees (524.0) and District Education Office (407), representing the mountain villages that were further damaged in the second May 12, 2015, severe aftershock, Mw = 7.3. While the full network of organizations engaged in response operations identified through the content analysis of news reports in the Kathmandu Post included 338 organizations, the 20 organizations represented in figure 6.10 played important roles in guiding response operations. Figure 6.10 shows a loosely connected network, with a density of 0.005 and degree centrality of 0.12. The low density and degree centrality values reflect the rugged terrain and limited resources of Nepal that constrained disaster response activities, despite efforts taken prior to the 2015 earthquakes by the government of Nepal and NSET to mitigate losses from known seismic risk. Figure 6.10 also illustrates that the primary organizations leading the response system were public organizations, and that 15 out of the top 20 were Nepali organizations. Four were international public organizations and one private organization was an international company, Facebook. One distinctive organization is the Nepali Congress Party, a political party that was heavily engaged in disaster relief activities. Three of the four international organizations developed strong connections to different jurisdictions in the Nepali response system: USAID connected directly to the prime minister of Nepal in the capital city; the Indian Embassy connected directly to the District Administrative Office, managing response in the 75 districts, and United Nations connected directly to Village Development Committees in rural, mountainous regions. CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

For Nepal, a nation of nearly 29 million people in 2015, the cost of the earthquake represented roughly one-­third of its national income (EERI 2016). The transition to recovery proved extraordinarily challenging. Faced with mounting costs, the monsoon season about to begin, and anticipating a harsh winter, the government of Nepal hosted a major United Nations Donors’ Conference in Kathmandu on June 25, 2015. The conference was well attended; international donors generously pledged $4.1 billion to meet the estimated costs needed for recovery (National Reconstruction Authority 2016). The National Planning Commission initiated the development of a Reconstruction and Rehabilitation Policy that included members of all government line ministries to manage the complex recovery process. In early July 2015, the recovery process in Nepal was scheduled to begin. Yet one component was

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missing. In its complex political/historical context, the Federal Democratic Republic of Nepal, officially established in 2008, had not ratified its constitution. Acceptance of the UN offer of assistance required a legally established administrative structure. The passage of the constitution had been stalled for seven years over conflicting views on how to designate the boundaries of the provinces, either by approximately equal geographic areas or by ethnic groups of the population. In July 2015, Nepal held national elections, and a new prime minister took office. Seeking legitimacy for the national government to lead the reconstruction and recovery effort, the Nepal Parliament approved a new constitution on September 20, 2015, that designated seven states (provinces) as the second-­ level administrative units of the country. This action triggered an angry response from the largest indigenous ethnic group, the Madhesi, who lived primarily in the Terai flatlands bordering on India and feared loss of power in the national Parliament. Their political reaction carried over to an economic effort to blockade the transport of goods, particularly gasoline, from India. Landlocked Nepal is dependent on imported fuel, without which virtually all transport in the country stalled. For six long months the blockade continued, with political recriminations levied from all sides. The practical consequences were that the recovery process in Nepal was effectively stalled for an entire year, requiring a full reassessment of disaster needs in May 2016, given the intervening winter and monsoon rains on communities damaged by the earthquakes (Comfort and Joshi 2017). The continuing political struggle within the country has further stalled recovery, as close to the third anniversary of the April 25, 2015, earthquake, only an estimated 5% of the international assistance had been allocated for reconstruction (Ministry of Finance 2015). This inability to move forward in recovery is likely to move Nepal back toward the category of emergent adaptive systems. SUMMARY, 2015 NEPAL EARTHQUAKE

The Nepal response system illustrates the classic characteristics of an operative adaptive system in the initial response phase. Given medium recognition of seismic risk and medium investment in preparedness efforts for a small nation, Nepal used its local resources effectively to mobilize immediate response operations for the earthquakes. In significant respects, this mobilization was self-­organizing as the Nepali Army and Armed Police responded immediately to engage in search and rescue operations, although limited by lack of advanced equipment. The Nepali government agencies were aligned with the UN OCHA cluster framework and initiated the call for international assistance. Community residents helped one another spontaneously and shared available resources.

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The breakdown occurred in the transition from response to recovery, in which the nation’s unresolved constitutional issues created a political crisis exacerbated by geopolitical strategies from neighboring countries apparently seeking to influence the recovery process in Nepal. Further, the four dimensions of time, space, scale, and energy influenced the evolution of the response system in Nepal, but in different respects from the other operational systems designated as operative adaptive systems. Time was critical, as Nepal had taken several positive steps before the earthquake occurred to lessen exposure to seismic hazards through the adoption of building codes, initiation of a program to retrofit schools, and development of a national disaster plan. Space served a unique role in Nepal, as virtually the entire country is exposed to risk, from the high Himalayas to the ancient cities in the Kathmandu Valley. Creating viable programs of community resilience to hazards in these very different geographic, geologic, technical, and cultural regions requires multiple scales of operations to adapt goals, rules, and practices to fit the size, scope, and resources of the specific communities. The flow of information through these various communities serves as a prime activator of social energy needed to develop a coherent strategy of disaster risk reduction for the nation. The Nepal case, more than any other, illustrates the importance of a global framework to facilitate mitigation, response, and recovery to major hazards, such as seismic risk, and the vulnerability of such a framework, if it is not grounded in the political, economic, and organizational structure of nations that are both giving and receiving humanitarian assistance. The unresolved constitutional conflicts in Nepal weakened its internal capacity to accept external assistance from the international community and stalled the transition to recovery, despite informed actions to mitigate seismic risk. Adaptation in Operational Systems Spurred by Changing Contexts The four cases of operational adaptive systems outlined in this chapter offer insight into the process of change that occurs within each response system and between the operational system and the wider societal environment in which it functions. All four response systems share the characteristic of seeking to adapt rapidly to an environment suddenly altered by a major earthquake. Yet, the capacity of each governmental system to extend the process of adaptation beyond the immediate response into a newly restabilized recovery system varied markedly, depending on the scale of the destruction incurred, the scope of reconstruction required, and the rate of change over time needed for recovery (Solé 2011). In each operational system, the transition from response to recovery proved the largest challenge. Although policy makers in Duzce had learned

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what steps were necessary in recovery from close observation of the Marmara earthquake three months earlier, the localized impact of the November 12, 1999, earthquake on the much smaller city of Duzce required a change in its administrative status from town to municipality to secure the resources and authority needed to proceed with reconstruction and recovery. In Padang, lessons learned from the 2004 Sumatra tsunami ironically inhibited informed response to the 2009 earthquake, resulting in a chaotic evacuation process that proved both unnecessary and costly. In Tohoku, the size and scale of the tsunami waves generated by the severe undersea earthquake overwhelmed existing policy and practice in Japan and necessitated wholesale redesign of tsunami detection systems and modeling. In Nepal, a timely response to earthquake damage was offset by a stalled recovery process largely due to an unsettled political conflict over legitimate participation in governmental decision processes that disrupted the daily functions of an already fragile national system. In each earthquake-­affected community, the dimensions of time, space, scale, and energy required reconfiguration of models of action to fit the specific context of that community, acknowledging the adjustments needed to support the transition from damaged community to resilient society. The flow of valid, timely information constitutes the critical link to maintaining a process of iterative learning and adaptation in regions exposed to seismic risk. When information flow is disrupted or distorted, the transition process from response operations to sustainable management of risk is adversely affected, as documented in each of the four cases. Maintaining an operational system requires both technical and social capacity at multiple scales: local, provincial, and national. While each of these four cases exhibited some capacity in technical and social areas, none had strong midlevel networks that could bridge national and local functions easily. Integrating the two types of capacity into a functioning sociotechnical system remains an elusive goal. The complexity of the task of building resilience to seismic risk over time is demonstrated vividly in each of the four cases classified as operative adaptive systems. In what ways does time intersect with the scale of operations needed across jurisdictional boundaries? How does the physical space that is subject to seismic risk constrain the virtual space of information needed to manage it? In what ways do current information technologies support the development of midlevel networks that can bridge international, national, and local networks of action in coherent programs of risk reduction? How is a community’s capacity for adaptation affected when basic functions of information search and exchange are taken away in an extreme event? The next chapter, chapter 7, explores these and other questions regarding the emergence of adaptive systems.

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7 Emergent Adaptive Systems 1999 MARMARA , TURKEY; 1999 CHI CHI, TAIWAN; 2005 PAKISTAN; AND 2008 WENCHUAN, CHINA , EARTHQUAKE RESPONSE SYSTEMS

Emergent Adaptive Systems, Redefined Stepping back two levels in systems integration and coherence, the set of emergent adaptive systems provides insight into the gradations of adaptation that ripple through systems of organizational interaction following extreme events. Emergent adaptive systems are characterized by low technical structure, medium organizational flexibility, and emerging cultural openness to new interpretations of seismic risk in their communities. Such systems include multiorganizational, multijurisdictional networks that mobilize after an extreme event to meet immediate needs in a damaged community. These systems have relatively little planning in place before the earthquake but demonstrate the capacity to engage community residents and relevant organizations in collaborative action after the event. Innovative actions, such as the paired assistance program that China instituted after the 2008 Wenchuan earthquake between wealthy eastern provinces and damaged cities and counties of western China, characterize immediate response to urgent needs of the disaster-­ stricken communities. Such actions are often impromptu and largely temporary, as organizations return to their pre-­earthquake routines after the urgency of immediate response with little permanent change in performance. According to the classification criteria defined in 1999 (see tables 4.1–3), four earth-

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quake response systems are characterized as emergent adaptive systems: the 1999 Marmara, Turkey, earthquake; the 1999 Chi Chi, Taiwan, earthquake; the 2005 Pakistan earthquake; and the 2008 Wenchuan, China, earthquake, shown on maps in figures 7.1 and 7.2. Emergent systems are recognized in virtually every discipline as organized structures that form from the interaction of actors, conditions, constraints, and resources available in a given context to meet a specific need (Quarantelli 1994; Howitt and Clower 2000; Braakeman 2013; Hobson and DeDeo 2015). Applying the concept of emergence to operational response systems that form following an extreme event acknowledges three factors that distinguish disaster response systems from other operational systems. Emergent adaptive systems form as actors operating in a specific context share an experience that creates a common base of understanding and recognition of a common goal or need (Comfort 2007b). Shared recognition implies rapid communication of meaning among actors to articulate a clear goal for action (Klein et al. 1993). Based on the shared goal, actors adapt their behavior in the short term to meet immediate needs. For example, neighbors engaged in daily routines may shift to collective search and rescue actions in a collapsed building when they experience an earthquake. Since the shared goal may not be well developed or deeply embedded in the local culture, the commitment for collective action may fray under longer-­term requirements or conflicting demands (Meltsner and Bellavita 1983). Nonetheless, emergent systems mark changes in the behavior of participant groups. While an emergent system may not continue in its initial formation, it alters the social context in which it was developed. What drives the emergence of an operational system in response to an extreme event, and what distinguishes emergent adaptive systems from the operative adaptive systems portrayed in chapter 6? A basic premise underlying this study is that information serves as the energy that activates participating actors and components of an operational system (Smith 2008a). Yet for emergent systems, it is not clear exactly how this happens, or why the same information yields different results in different contexts. Three possible explanations are suggested by recent researchers. First, the level of knowledge and understanding of risk in any given situation serves as the initial baseline against which information is received; new information regarding threat generates a stronger response in contexts with greater knowledge and awareness of risk (Castells 2009; Fligstein and McAdam 2012). In areas of known risk and a high degree of awareness among community members regarding potential threats, incoming signals of potential threat are likely to be perceived more accurately by a greater number of people, triggering a quicker, more informed, collective response. Risk communication is a reciprocal process in which the sender’s information activates the receiver’s understanding, and the connection precipitates action

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FIGURE 7.1 . Emergent adaptive systems: Marmara, Turkey, August 17, 1999; Chi Chi, Taiwan, September 21,

1999. Maps by Fuli Ai.

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S FIGURE 7. 2 . Emergent adaptive systems. Pakistan earthquake, 2005; Wenchuan, China, earthquake, 2008.

Maps by Fuli Ai.

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138 C H A P TER 7

(Luhmann 1989/1996). If the receiver hears the message, but does not comprehend the content, there is no substantive communication. The baseline knowledge of risk in a community sets the initial parameter for collective action in response to an extreme threat. Different levels of awareness of known risk in the community will generate varying degrees of action to the same message or event. Second, the technical infrastructure available for exchanging information among the residents of a threatened community creates a set of constraints through which information flows (Shannon 1948; Wiener 1948/1961; LaPorte 1996). This infrastructure, from cell phones to satellites, computers to hand-­ drawn posters, can either facilitate or inhibit the flow of information through a dense network of interconnected individuals, groups, organizations, and systems. Information can be transmitted globally via telecommunication networks in minutes, but if the existing technical infrastructure is damaged, absent, or fails to function, whole communities can be isolated and marginalized from an intended national response. For example, mountain communities in the high Himalayas of Azad Kashmir in northeast Pakistan lost all communications after the October 8, 2005, earthquake, and damage to these communities was discovered only by helicopter overflights. Third, equally important, the organizational infrastructure for establishing, maintaining, and updating communication channels through which information flows is a central factor in facilitating the rapid transmission of information to key agents who then activate other actors and agents in a progressive effort to respond appropriately to the threat (LaPorte 1996; Ostrom 2005). If the organizational channels are long and tortuous, the message may be delayed, misread, misunderstood, and fail to generate collective action, despite timely initiation. If the flow of information is diminished under any of these conditions, the kinetic energy generated by collective recognition of risk dissipates. Conversely, when the three primary conditions are met, conditions are favorable for self-­organizing action and adaptive behavior to emerge. Considering the emergent adaptive systems in practice during the period 1999–2015, four earthquake response systems are analyzed in terms of changes in communication technologies that speed and extend the transmission of risk information to responsible actors within each system. Two of these cases, the Marmara, Turkey, earthquake and the Chi Chi, Taiwan, earthquake, occurred in 1999, the first year of this 16-­year study period. The other two earthquakes, Pakistan in 2005 and Wenchuan, China, in 2008, occurred in the middle years of this period. A primary assumption is that as the technology of communication changes, the capacity of organizations to communicate across jurisdictions and disciplines also changes. If validated in practice, the rate of organizational change in response to known risk is also expected to change. If so, the degree of adaptation in communities under threat would reflect the interac-

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tion between technical advances in communications and organizational capacity of the response systems that are mobilized following extreme events. Chapter 7 is organized as follows. For each response system, a brief account of initial conditions of physical, technical, organizational, and cultural conditions prior to the earthquake provides a baseline for comparison among the four cases included in this class of emergent adaptation. The networks of organizations engaged in response operations are identified by content analyses of local news reports for three weeks after the event, documentary sources of policies and procedures regarding response operations, and professional reconnaissance studies. Multiple methods of analysis are used to characterize the networks and to reveal changes in performance over the three-­week period of study. External/internal relationships that reveal change within each earthquake system are identified for this class of emergent systems, with detailed analysis that compares the degree of change among the classes of adaptation for all 12 earthquake response and recovery systems presented in chapter 9. Interestingly, the total set of 12 cases analyzed in this study includes three subsets of response systems in which operational performance that emerged following a specific event can be compared to performance that evolved following a second event in the same country within a relatively short period of time. This unusual situation allows comparison of change in performance between two similar hazard events, and an assessment of the extent to which the nation’s policy and practice regarding seismic risk became stronger or weaker over time. Two response systems characterized in chapter 7—those following the 1999 Marmara, Turkey, earthquake and the 2008 Wenchuan, China, earthquake—represent the first instances of paired earthquakes that occurred respectively in Turkey and China, within short periods of time. The August 17, 1999, Marmara event preceded the November 12, 1999, Duzce, Turkey, earthquake, analyzed in chapter 6, by less than three months. The 2008 Wenchuan, China, earthquake preceded the 2013 Lushan, China, earthquake, analyzed in chapter 5, by less than five years in the same province, Sichuan. These paired events created natural experiments for assessing change in operational response systems following seismic events and illustrate the extent to which the multilevel structure of seismic response systems developed in the respective countries adapted to the continuing risk they faced. Chapter 7 explores conditions for change in performance documented by successive extreme events, identifies gaps in the operational networks across jurisdictional levels of performance, and investigates conditions in each of the four societies that may have precipitated change. It also explores connections initiated to fill gaps discovered in the earlier networks and compares the response networks within each class. The subset of cases of emergent adaptive systems begins with the 1999 Marmara, Turkey, earthquake. Turning to the

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detailed reports of organizational response to these four events, it is instructive to note what is missing organizationally in these four events that was present in the class of operative adaptive systems documented in chapter 6. The Marmara, Turkey, Earthquake, August 17, 1999 INITIAL CONDITIONS

At 3:02 a.m. on Tuesday, August 17, 1999, a major earthquake struck the Marmara region of western Turkey. Buildings crumbled, electrical power shut down, communications went dead, and 10 cities in the most industrialized region of Turkey experienced heavy damage. The shaking lasted for 45 seconds, sending shock waves throughout the region. The earthquake, measured initially at 6.7 on the moment magnitude scale, was upgraded the next day by the Turkish Earthquake Research Department to Mw = 7.4. Caused by a rupture of the North Anatolian fault, the epicenter of the earthquake was located near the town of Golcuk in the city of Izmit, Kocaeli Province, at the eastern end of the Marmara Sea (Kandilli Observatory 1999; EERI 1999).1 Ten cities and towns in the heavily industrialized region of northwestern Turkey suffered serious damage simultaneously from the earthquake. The provinces of Istanbul, Kocaeli, and Adapazari, and specifically the cities of Izmit, Yalova, Sakharya, Avcilar-­Istanbul, Sapanca, Korfez, Akyazi, and Golyaka and the towns of Golcuk and Duzce suffered severe destruction. Bogazici University reported the total number of deaths on September 4, 1999, to be 15,135.2 Other reports estimated the number of dead to be over 17,000. At least 50,000 household units were reported destroyed or heavily damaged. At least 600,000 people were dislocated from their homes. The total losses in built infrastructure and socioeconomic costs were estimated at $16 billion, or about 7% of Turkey’s gross domestic product in 1999.3 The extensive damage to the Marmara region, center of economic production for the country, heavily impaired Turkey’s economic activity. Illustrating the interdependence of technical and social modes of failure, the economic losses exacerbated the severe losses to both the population and the technical infrastructure of the country. Mobilizing response operations to meet the needs of hundreds of thousands of residents of the devastated communities necessarily involved the exchange of information at multiple levels: within each of the 10 communities, between the major cities and the central administration in Ankara, between the smaller towns and their provincial governments, and between the provincial governments and the central administration. In addition, there were multiway exchanges among the 10 damaged communities, three provincial governments, and central government, as well as between private and nonprofit organizations at local, national, and international levels of operation. These exchanges created the basis for observation and documentation of the action

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patterns that evolved within and among the organizations. The set of interactions among individuals, groups, and organizations participating in disaster response operations following the Marmara earthquake represent an emerging complex adaptive system for seismic response in Turkey (Comfort and Sungu 2001a, b; Glass, Ames, et al. 2011; World Bank 1999). CHARACTERIZATION OF THE 1999 MARMARA, TURKEY, EMERGENT RESPONSE AND RECOVERY SYSTEM

Earthquakes are a well-­known risk in Turkey, with the North Anatolian fault crossing the nation from east to west, and nearly 95% of the country reporting some degree of seismic risk (National Earthquake Research Center 1999.) In 1999, the nation had a well-­developed set of building codes, comparable to building codes adopted in California and Japan. Turkey also had an advanced National Earthquake Research Center since the early 1990s, initially funded by the Japan International Cooperation Agency ( JICA). The Turkish Parliament had enacted National Disaster Law 7269 in 1959, which specified policies and procedures for reducing earthquake risk and allocating responsibilities to specific public agencies in event of major earthquakes.4 Records of professional associations showed that there were approximately 80,000 professional engineers registered in Turkey in 1999.5 Yet there was an obvious gap in performance between the laws and policies adopted prior to the earthquake, August 17, 1999, and actions taken in practice in response to the event. A response system did emerge following the earthquake, but the discrepancies between formal policies and actual practice were sobering. What factors contributed to the discrepancies between known risk, enacted policies, and actual practice in 1999, given well-­known seismicity and a well-­recognized scientific and professional community in Turkey in 1999? A profile of the response system that emerged in Turkey after the Marmara earthquake follows, based on accounts of response operations reported in Cumhuriyet, a national newspaper published in Istanbul, for three weeks, August 17–­ September 8, 1999;6 professional reports; and notes from expert interviews conducted in 1999.7 Table 7.1 presents the frequency distribution of the 610 organizations identified as engaged in disaster response operations following the August 17, 1999, earthquake, by jurisdiction and funding source. The largest proportion of organizations participating in the Marmara response operations were public organizations. Of those, the proportion of organizations from the Turkish Central (also designated as State) government, constituted 24.3%. International entities that included public, private, and nonprofit organizations constituted 22.1% of the total system. The third-­largest category included private and nonprofit organizations that operated nationally, with a small number of

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65 28 42 0 135

N

10.66 4.59 6.89 0.00 22.13

%

International

148 0 0 0 148

N 24.26 0.00 0.00 0.00 24.26

%

State/Central

0 55 43 8 106

N 0.00 9.02 7.05 1.31 17.38

%

National

79 8 0 0 87

N 12.95 1.31 0.00 0.00 14.26

%

Province

0 5 10 0 15

N 0.00 0.82 1.64 0.00 2.46

%

Regional

40 32 28 0 100

N

6.56 5.25 4.59 0.00 16.39

%

Municipal

19 0 0 0 19

N

3.11 0.00 0.00 0.00 3.11

%

District

Frequency Distribution of Organizations in the 1999 Marmara, Turkey, Response System, by Jurisdiction and Funding Sector

Data source: Cumhuriyet, Istanbul, Turkey, August 18–­September 7, 1999.

Public Nonprofit Private Political Total

TABLE 7.1.

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351 128 123 8 610

N

% 57.54 20.98 20.16 1.31 100.00

Total

Em e rg e nt A da ptiv e Syste ms 143

political organizations, at 17.4%. The provincial and district jurisdictions consisted largely of public organizations, while municipal or city jurisdictions included public, private, and nonprofit organizations. This operational system represented organizations that interacted with one another to provide services to the damaged communities and excluded those organizations that made single donations or acted independently. The large number of organizations that engaged in disaster operations strained the existing communications infrastructure. Importantly, national agencies in Ankara, obligated under national law to assist provinces, municipalities, and districts, had limited access to communications for the first two days after the earthquake (expert interview, Ankara, September 1999). The design of interorganizational coordination of response operations across jurisdictional boundaries was limited by the lack of technical infrastructure to support multiway communications in practice. Coordination across sectoral boundaries did occur, but it was not strong. As noted in table 7.1, the number of national private organizations participating in response operations (43) was virtually matched by international private organizations (42). The participation of nonprofit organizations, that is, organizations that provided public services but did not profit from those services, was stronger at the national level (55) than the provincial (8) or municipal (32) levels. A sizeable segment of international nonprofit organizations (28) also actively participated in response organizations. The relatively modest levels of participation by both nonprofit (21%) and private (20%) organizations indicate that the dominant actors in organizational response operations were public organizations, and that the system was not strongly integrated across the society. Figure 7.3 presents the rate of change in the Marmara response system over the three-­week period of study. The data show uneven participation of organizations in response operations in the first three days after the earthquake, followed by a sharp increase in the number of organizations participating at the beginning of the second week, reflecting in part incoming international aid and reconnaissance organizations, but declining toward the end of the week. The third week reported an uneven number of new entrants with the total number of organizations engaged in response holding steady at about 100 organizations. The types of transactions performed by organizations engaged in response operations are reported by jurisdiction and funding sector for three weeks after the earthquake in appendix I, table I.7.1. The transactions categorize the actual types of work or services performed by the organizations engaged in response operations and were identified from reports in Cumhuriyet, published in the Turkish language and coded by native speakers. The 30 transaction codes identified the same categories of response activities used to analyze

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120

Marmara response system

Total number of organizations Cumulative percentage of organizations Rate of change (%)

Number / %

100 80 60 40 20

8/

18

/ 8/ 199 19 9 / 8/ 199 20 9 / 8/ 199 21 9 /1 8/ 99 22 9 / 8/ 199 23 9 / 8/ 199 24 9 / 8/ 199 25 9 / 8/ 199 26 9 / 8/ 199 27 9 / 8/ 199 28 9 /1 8/ 99 29 9 / 8/ 199 30 9 / 8/ 199 31 9 /1 9/ 99 1/ 9 1 9/ 999 2/ 1 9/ 999 3/ 1 9/ 999 4/ 1 9/ 999 5/ 1 9/ 999 6/ 1 9/ 999 7/ 19 99

0

Date FIGURE 7.3 . Rate of change in 1999 Marmara, Turkey, response system, August 18–­September

7, 1999. Data source: Cumhuriyet, Istanbul, Turkey, August 18–­September 7, 1999. Figure by Jee Eun Song.

transactions reported for the earlier response systems presented in chapters 5 and 6. In the Marmara response system, 2,192 actors engaged in 1,281 transactions, documenting a sizeable response system. The transactions differed among jurisdictions and funding sectors, but the frequencies of both did not differ markedly from distributions in other response systems. Nearly one-­quarter of the transactions, 23%, involved emergency response, communication, and coordination. The next-­largest proportion, 17%, involved donations to the residents of the affected communities. Other categories that warrant notice included damage/needs assessment, repair/recovery/reconstruction, and medical/health, as well as hazardous materials, reflecting the Tupras refinery fire. The total number of actors engaged in performing these transactions was 2,192, with the largest proportion of actors participating at public state or central government level, 32.7%. Actors engaged at the public provincial level constituted about one-­quarter, or 25.2% of the participants, and actors at the municipal and district levels made up 9.4%. The total number of actors from domestic public organizations represented more than two-­thirds of all actors engaged in transactions, or 67.3%. At the public international level, including search and rescue teams and professional engineering reconnaissance teams, the number of actors represented 9.9%. These four categories of public actors represented over three-­

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fourths, or 77.2% of the total number of actors performing transactions in the response system. Actors from other categories included nonprofit organizations, 14.2%; and private organizations at half that amount, 7.6%. A small category of political parties, 21 or a scant 1%, made up the last category and engaged primarily in political dialogue regarding the strategies for response and recovery. Network Analysis As identified in Cumhuriyet news reports, an operational system of 610 organizations participated in response operations following the Marmara earthquake, engaging in search and rescue operations, restoring downed power lines and communication, and providing shelter, food, and medical care to survivors who lost their homes and livelihoods. Using network analysis, two measures of centrality, degree and betweenness, were calculated for the identified operational system. Degree centrality counts the number of ties that a specific node has with other actors in the network. Average degree centrality reports the number of existing ties within the entire network, in comparison to the possible number of ties (Wasserman and Faust 1994). Betweenness centrality measures the extent to which a given node in a network connects two other nodes that would not otherwise be connected (Wasserman and Faust 1994, 189–91). Figure 7.4 shows the network diagram of the top 20 organizations in the 1999 Marmara earthquake response system, ordered by betweenness centrality with icons sized according to influence. This subset of 20 organizations represents those organizations with the greatest influence in linking other organizations in coherent response actions. Confirming the analysis of transactions, figure 7.4 illustrates that public organizations dominated the response system, with 18 of the 20 organizations identified as public. One nonprofit organization, Kizilay, operating at the national level, as well as one private organization, Tupras, the oil refinery that suffered heavy damage, were included in the 20 organizations with greatest connecting influence in the system. Table 7.2 lists the acronyms and full names of the top 20 organizations ordered by betweenness centrality and identifies them by funding source, jurisdiction, and degree centrality, or the number of ties that each organization has with other organizations operating in the response network. Consistent with National Disaster Law 7269, the prime minister’s Crisis Management Center (PMCMC) demonstrates the highest betweenness value of 26,905, indicating the number of instances in which the PMCMC linked other organizations operating in the system that otherwise would not have been connected. Kizilay (Turkish Red Crescent) is the only nonprofit organization

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146 C H A P TER 7 CMC_GOL

P_MUG

KPE CMC_REG

TUPRAS AZB

CMC_KOC

KIZ

CMC_SAK

PMCMC CMC_ BOLU

P_YAL HM

NEM

P_SAK CMC _YAL USA

P_KOC

PWSM

Jurisdiction

Funding sector

International

Public

State/central

Private

National

Nonprofit

Province Municipal TURKI FIGURE 7.4 . Top 20 organizations in 1999 Marmara response system, ordered by betweenness centrality. Graph level statistics: diameter: 8; density: 0.004; degree centrality: 0.152; betweenness centrality: 0.144. Data source: Cumhuriyet, Istanbul, Turkey, August 17–­September 8, 1999. Figure by Jee Eun Song.

in this list of top 20 organizations, ranking second highest. Interestingly, 11 of the 20 organizations included on this list were provincial organizations, indicating the significant role that provincial organizations played in response operations. Also noteworthy, 6 of the 11 provincial organizations included in the list of top 20 organizations ordered by betweenness values were Crisis Management Centers activated in accordance with National Disaster Law 7269. Only two international actors were identified in the top 20 organizations, the United States and neighboring Azerbaijan. Tupras refinery, the only private organization, was included on the list, given the size and scope of the fire generated by the earthquake at the refinery and the scope of losses it sustained. Three central government (state) agencies—the Turkish government, the Ministry of Public Works and Settlement, and the Ministry of Health—were included on the list, but all ranked lower than the provincial agencies, an indication that the provincial organizations were closer to the field operations activated for the delivery of services.

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TABLE 7.2. Top 20 Organizations in 1999 Marmara, Turkey, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Source, and Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

PMCMC

PMCMC Management Crisis Center Kizilay Kocaeli CMC Yalova Province Crisis Center Kocaeli Province government Mugla Province Bolu Crisis Center RCMC Center Sakarya Province Crisis Management Center Yalova Province United States Sakarya Province government Golcuk CMC Kocaeli Province Environment Department National Education Ministry Azerbaijan Turkish government Public Works and Settlement Ministry Health Ministry Tupras

Public

State/Central

Nonprofit Public Public Public Public Public Public Public

KIZ CMC_KOC CMC_YAL P_KOC P_MUG CMC_BOLU CMC_REG CMC_SAK P_YAL USA P_SAK CMC_GOL KPE NEM AZB TURKI PWSM HM TUPRAS

Betweenness

Degree

26,905.22

95

National Province Province Province Province Province Province Province

9,131.73 8,182.00 6,014.72 4,466.12 3,923.30 3,885.63 3,375.47 3,315.78

41 43 33 31 15 29 17 28

Public Public Public Public Public

Province International Province Province Province

3,307.35 2,857.46 2,826.83 2,548.34 2,461.75

23 14 23 18 13

Public Public Public Public

State/Central International State/Central State/Central

2,268.44 1,934.25 1,892.00 1,758.50

18 8 7 14

Public Private

State/Central National

1,650.88 1,570.00

10 2

Data source: Cumhuriyet, Istanbul, Turkey, August 18–­September 7, 1999.

CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Many reconnaissance reports and analyses sought to assess the impact of the August 17, 1999, earthquake on the 10 Turkish communities that were most severely affected, and to evaluate the efforts that Turkey, as a nation, had made to mitigate seismic risk (EERI 1999; Comfort 1999a, b; Balamir 2000, 2002; Comfort and Sungu 2001a, b; Bakır and Boduroǧlu 2002; EERI 2003). The sobering consensus is that, despite known seismic risk, significant efforts by the Turkish government to establish laws and policies to mitigate risk, and an internationally recognized community of professional engineers, urban planners, seismologists, and public managers focused on risk reduction in Turkey, this level of professional knowledge and skills was not translated into practical action to reduce the potential consequences for Turkish communities in 1999.

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In the hours immediately following the earthquake, communications were severely disrupted. The central administrative agencies in Ankara were not fully aware of the extent of the damage in the Marmara region for two full days (Personal communication, September 1999). The size and scope of this event escalated the damage beyond the expected range of a single city. This earthquake affected not just one city, but ten; not just one province, but three; not just one government agency, but hundreds at multiple levels of jurisdiction and authority. The severity and complexity of this event escalated beyond the capacity of the institutions, organizations, and personnel charged with responsibility for mitigating and managing known seismic risk in Turkey. Given the geographic range of this event and the urgent need for assistance at multiple locations simultaneously, communications were critical. Yet, despite the availability of satellite phones and satellite images for the devastated areas, such instruments of communication were not widely used, and lack of reliable communication hindered prompt mobilization of resources and personnel to cope with this disaster. Despite the adoption of building codes by law, the lack of adherence to those codes in practice weakened the technical structures and undercut policies intended to protect communities. Reconnaissance studies of collapsed buildings revealed inferior materials used in construction; inadequate bracing used in the design of buildings; and verification that many of the collapsed buildings were constructed after the building codes were adopted (Bakır and Boduroǧlu 2002). The gaps in performance were not due to lack of recognition of seismic risk by public agencies, but lack of capacity to translate that recognition into practical action for the communities exposed to continuing risk posed by the North Anatolian fault. SUMMARY, 1999 MARMARA, TURKEY, EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

Response operations that emerged following the 1999 Marmara, Turkey, earthquake represent a classic case of multiple organizations and jurisdictions searching for assistance, but unable to manage the complex, interacting conditions that rapidly escalated the event beyond the capacity of the local, provincial, and national government agencies that had designated responsibilities for action. Information and communication functions among the participating actors were broken or missing, limiting the timely exchange and updating of information essential for coherent action under stress. Limited enforcement of building codes weakened the technical structure of buildings and bridges. The nation of Turkey and its affected communities mobilized a response system to this extreme event but were late in doing so and struggled to sustain constructive measures of recovery and redesign after the initial period of chaos, search and rescue, and delivery of immediate relief. An adaptive orga-

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nizational response system emerged from this event but frayed under the conflicting demands of recovery and reconstruction. The lack of basic knowledge regarding seismic risk in the general population left communities unguarded when building codes were adopted in policy, but not implemented in practice. The limited communications infrastructure inhibited widespread sharing of critical information about known risk among residents that may have precipitated informed adaptation in construction in these rapidly developing cities in western Turkey. Organizational networks of volunteers formed to provide temporary assistance in local communities but lacked the public recognition and professional organization needed to sustain them over time (Comfort and Sungu 2001b). Missing were the midlevel organizations essential to link volunteers in local communities with the national and international organizations that could provide support, experience, legitimacy, and resources to response and recovery operations. The Chi Chi, Taiwan, Earthquake, September 21, 1999 INITIAL CONDITIONS

Less than two months after the Marmara, Turkey, earthquake captured the world’s attention on August 17, 1999, a powerful earthquake shattered buildings and infrastructure in central Taiwan during the early morning hours of Tuesday, September 21, 1999. At 1:47 a.m., cities, towns and villages throughout much of the island were left in total darkness as the earthquake knocked out electrical power transmission stations, disrupted telephone communications, collapsed buildings, shut off water and sewage distribution systems, and damaged roads, railroads, and bridges. Stunned by the violence of the event, residents of stricken communities and public officials with emergency responsibilities struggled to cope with the demands of extraordinary destruction.8 The earthquake occurred on the Chelanpu fault, with the epicenter located in the small town of Chi Chi, Nantou County. The magnitude registered Ms = 7.6, Ml = 7.3. The depth measured 1.0 kilometers, shallow in comparison to other large magnitude events. The duration of shaking was timed at 40 seconds, a long period of seismic activity. The rupture extended 70–80 kilometers in length, with the rupture velocity measured at 2 kilometers per second. The intensity of this earthquake was not anticipated on the Chelanpu fault, classified as moderately active in Taiwan. Waves of aftershocks continued in the days immediately following the main shock, with two registering Ms = 6.8 within the first 100 hours. The effects of the earthquake were widespread, causing significant damage in five counties, with 90% of the damage occurring in Nantou and Taichung Counties. Six additional counties reported minor damage, for a total of 11 out of Taiwan’s 21 counties incurring losses from the earthquake.9

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This sudden, devastating event claimed a high toll in lives and property, with the total number of dead reported at 2,405; number of missing, 39; number of patients treated for injuries, 10,718, with at least 1,000 patients requiring hospitalization. Approximately 5,004 persons were rescued, and an additional 4,685 persons were evacuated. Buildings were heavily damaged, with more than 31,534 buildings reported as totally collapsed and 25,506 reported as partially collapsed within the disaster region.10 Twenty-­seven towns reported serious damage, and aboriginal communities were affected in isolated mountain areas. These figures give scant profile to the level of destruction in the damaged communities, or to the scale of human suffering endured in the event. CHARACTERIZATION OF THE 1999 CHI CHI, TAIWAN, EMERGENT RESPONSE AND RECOVERY SYSTEM

As in Turkey, seismic risk is well known in Taiwan. Located at the juncture of four tectonic plates—Yangtze subplate of the Eurasian plate to the west and north, Okinawa plate on the northeast, Philippine plate to the southeast, and Sunda plate to the southwest—Taiwan has experienced earthquakes repeatedly over the centuries (Chen, Shei, et al. 2000) and has undertaken measures to counter them. The National Science Council of Taiwan established the National Center for Research on Earthquake Engineering (NCREE) in 1980 to study the risks posed to the island’s engineered infrastructure. In 1999, Taiwan had mapped the geological fault lines and identified areas of the island subject to greatest seismic stress (Chen, Shei, et al. 2000). Further, Taiwan had revised its National Emergency Plan in 1994, a plan that was in effect on September 21, 1999. Aware of seismic risk, the question for responsible policy makers was how to translate knowledge of risk into action to protect Taiwan’s cities and communities most effectively, and how to inform the citizens to manage known risk with unknown consequences in a small society with changing population mobility and land use patterns. In 1999, the economy in Taiwan was also changing; manufacture of electronic parts for computational devices for sale abroad had become an important part of the island’s economy. Cell phones were altering patterns of communication but were not yet widely used among the general population. Government agencies were beginning to recognize the need to update record keeping and accounting procedures but had not fully incorporated computational technologies and programs into everyday information management for public services (Personal observation, Nantou County and Taipei, Taiwan, October 10–14, 1999). A latent capacity for enhancing the technical infrastructure for communication and information exchange and management existed in Taiwan but was not fully implemented in social practice. Taiwan’s central administration mobilized response operations quickly, but the basic direction for the affected county and municipal agencies in central Taiwan came from

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TABLE 7.3. Frequency Distribution of Organizations in the 1999 Chi Chi, Taiwan, Response System, by Jurisdiction and Funding Sector

International

Public Nonprofit Private Total

National

County

Municipal

Total

N

%

N

%

N

%

N

%

N

%

20 12 3 35

1.72 1.03 0.26 3.01

152 163 144 459

13.09 14.04 12.40 39.53

234 127 110 471

20.16 10.94 9.47 40.57

138 29 29 196

11.89 2.50 2.50 16.88

544 331 286 1,161

46.86 28.51 24.63 100.00

Data source: United Daily, Taipei, Taiwan, September 21–­October 8, 1999.

executive leaders and ministries in Taipei. The network of organizations that emerged in response to the September 21, 1999, earthquake is documented from news accounts of response operations reported in United Daily, a major newspaper published in Taipei.11 Table 7.3 presents the distribution of organizations engaged in disaster operations for three weeks following the earthquake, September 21–October 8, 1999. The organizations and their respective transactions were coded through content analysis of news reports from the United Daily, conducted by a native speaker and confirmed by a coding team at the Center for Disaster Management, University of Pittsburgh. As acknowledged, newspaper sources do not provide a complete account of the response system, but they do provide a daily record of operations and include private and nonprofit organizations as well as public organizations in a publicly accessible format. The “9/21” earthquake generated a large response system with a total of 1,161 organizations; public organizations made up the largest proportion of the system, 46.9%; with nearly half, or 20.2%, of that proportion from the county jurisdictional level. In 1997, Taiwan transferred most provincial functions of government to the national government of the Republic of China, essentially omitting the province as a jurisdiction in Taiwan (McBeath 2000). The People’s Republic of China (PRC) continues to claim Taiwan as an administrative province, but Taiwan has operated independently since splitting from the mainland in 1947. In practice, Taiwan has now eliminated the provincial structure of administration, and “national” is interpreted to mean the nation of Taiwan. County governments are designated as the subnational level of administrative organization, and municipal governments are subcounty (McBeath 2000). Notably, nonprofit organizations constituted the next-­highest category of participants, with more than a quarter, 28.5%, participating in the overall response system. The role of nonprofit organizations in disaster response and recovery is especially significant in Taiwan, given the continuing position held by China that Taiwan is not an independent nation, but remains a province of

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Chi Chi response system

400 350

Total number of organizations Cumulative percentage of organizations Rate of change (%)

Number / %

300 250 200 150 100 50

9/

9/

21

/1 9 22 99 /1 9/ 99 23 9 /1 9/ 99 24 9 /1 9/ 99 25 9 /1 9/ 99 26 9 /1 9/ 99 27 9 /1 9/ 99 28 9 /1 9/ 99 29 9 /1 9/ 99 30 9 /1 10 99 /1 9 /1 10 99 /2 9 /1 10 99 /3 9 /1 10 99 /4 9 /1 10 99 /5 9 /1 10 99 /6 9 /1 10 99 /7 9 /1 10 99 /8 9 /1 10 99 /9 9 /1 99 9

0

Date FIGURE 7.5 . Rate of change in the 1999 Chi Chi, Taiwan, response system, September 21– October 9, 1999. Data source: United Daily, Taipei, Taiwan, September 21–­October 9, 1999. Figure created by Jee Eun Song.

China. Under this interpretation, Taiwan is not an independent member of the United Nations, and established UN rules of interaction among member nations in disaster environments do not apply. International nonprofit organizations, however, engaged with their national-­level counterparts or branches in Taiwan, and did so, both directly and indirectly, by transferring resources and knowledge to local branches to support direct engagement for field services. Accordingly, nonprofit organizations played a vital role in response and recovery operations in Taiwan following the 1999 earthquake. Figure 7.5 presents the rate of change in 1999 Chi Chi response system over the three-­week period of study. The data show a rapid mobilization of more than 350 organizations on the day that the earthquake occurred, but a steady drop over the next four days. The number of new organizations entering the system gradually increases in the second week but declines to virtually steady state during the third week of disaster operations. Types of transactions performed in disaster operations, reported in the content analysis of news articles published in the United Daily, Taipei, Taiwan, September 21–October 9, 1999, are listed in appendix I, table I.7.2.12 The large majority of actors (58%) engaged in five types of transactions—damage/needs assessment, disaster relief, donations/fund-­raising, recovery, and emergency response—in the response system that are directly comparable to types of transactions coded for the other 11 earthquake response systems. Nearly a quarter of the transactions, 23.5%, combined restoration/repair, medical

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cbtw

chcogov

mfaey

cpami moiey

moeaey mlcogov tycogov

eytw

tccgov doetpcgov

tccogov

mondey ntcogov twpwco president tpcogov

moeey

klcgov

Jurisdiction National

Funding sector Public

County Municipal

phbklgov FIGURE 7.6 . Top 20 organizations, 1999 Chi Chi, Taiwan, response system, ranked by betweenness central-

ity, with jurisdiction and funding sector. Graph level statistics: diameter: 11; density: 0.0027; degree centrality: 0.1068; betweenness centrality: 0.1542. Data source: United Daily, Taipei, Taiwan, September 21–­October 12, 1999. Figure by Jee Eun Song.

care/health, communication/coordination, and government aid/services. Over 80% of the actors participating in the Chi Chi, Taiwan, response system engaged in operations comparable to transactions coded for the other 11 earthquake response systems. This finding confirms that the basic types of actions documented for earthquake response systems share a high degree of similarity, despite differences in context and initial conditions in which the event occurs. Figure 7.6 reports the top 20 organizations participating in the 1999 Chi Chi response system, ranked by betweenness centrality values. The nodes in the network diagram are sized according to influence. Although private and nonprofit organizations were also identified in the content analysis of news reports in United Daily, nearly half, or 46.9%, of the total organizations participating in response operations were public organizations. The top 20 organizations

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154 C H A P TER 7 TABLE 7.4. Top 20 Organizations, 1999 Chi Chi, Taiwan, Earthquake Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding, and Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

mondey

Ministry of National Defense, Executive Yuan Executive Yuan of the Republic of China Taichung County government Ministry of Education, Executive Yuan Nantou County government Ministry of Interior, Executive Yuan Keelung City government Public Health Bureau, Keelung City government Miaoli County government Taiwan Power Company Ministry of Foreign Affairs, Executive Yuan Central Bank of the Republic of China Changhua County government Ministry of Economic Affairs, Executive Yuan Construction and Planning Agency Ministry of the Interior Taichung City government Taoyuan County government Bureau of Education, Taipei City government Taipei County government President of the Republic of China

Public

eytw tccogov moeey ntcogov moiey klcgov phbklgov mlcogov twpwco mfaey cbtw chcogov moeaey cpami tccgov tycogov doetpcgov tpcogov president

Betweenness

Degree

National

104,435.10

127

Public

National

56,399.50

83

Public Public Public Public Public Public

County National County National County County

54,364.50 47,481.86 43,930.00 30,148.64 26,487.06 26,029.17

90 64 105 62 21 33

Public Public Public

County National National

24,082.13 23,314.05 20,243.08

52 34 27

Public

National

19,607.28

33

Public Public

County National

18,247.58 18,187.06

37 40

Public

National

17,080.83

38

Public Public Public

Municipal County County

16,771.61 16,322.48 16,229.45

50 21 26

Public Public

County National

16,047.14 14,834.47

35 29

Data source: United Daily, Taipei, Taiwan, September 21–­October 12, 1999.

ranked by betweenness centrality were all public organizations, indicating the dominant role that public organizations played in mobilizing and executing response operations. The graph level statistics, reported as density and degree centrality, indicate a loosely connected network with dense feedback loops among national and county agencies. Table 7.4 presents the top 20 organizations with their full names, ranked by betweenness centrality, in the Chi Chi response system. Ten of the top 20 organizations were from the national jurisdiction; nine were county organizations, and only one was municipal. The linkages observed between national and county organizations document the direct interaction among these jurisdictions after the elimination of provincial government functions in 1997 (McBeath 2000).

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Importantly, betweenness rankings indicate the dominant role played by the Ministry of National Defense in mobilizing and executing response operations. Within the network, the MOND, Executive Yuan, shows a betweenness value of 104,435, nearly double the value, 56,339, of the next ranking agency, Executive Yuan of the Republic of China. CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Multiple response organizations conducted reconnaissance studies and analyses to create a valid profile of the conditions that precipitated the 1999 Chi Chi earthquake, and consequences of the event for the cities and communities of Taiwan (RCUSS 1999; Lee 2000; Comfort 2000; Uzarski et al. 1999; Uzarski and Arnold 2001). The critical issue, documented in multiple reports, appeared to be the gap between the capacity of the organizations and institutions responsible for seismic risk reduction and the actual demands of the seismic event. Information regarding damage to affected areas was slow and incomplete in the first hours after earthquake. Not all towns established emergency operations centers immediately, and in most of the affected towns, existing emergency planning and preparedness proved inadequate for an event of this magnitude. Mobilization of personnel and equipment for disaster response over five counties demanded a complex set of operations and coordination of actions among multiple agencies, governments, and private and nonprofit organizations. While most decisions were taken quickly, the logistics required to enact them were not readily in place, resulting in delayed imple­mentation. International search and rescue teams arrived with advanced technical equipment and trained personnel, but late in the process. Search and rescue teams arrived from 20 countries but rescued a total of six live persons. International assistance was complicated by the unique situation of Taiwan in the international community. Humanitarian assistance was delayed in several instances by political constraints. Although individual managers made extraordinary efforts to re­spond to the demands of the earthquake, these efforts were hampered by insufficient knowledge of seismic risk in rural regions and its impact on the built environment and communities; lack of timely, accurate information from the multiple sites affected; inadequate emergency preparedness training; and a damaged infrastructure for communication. Yet a striking cultural openness to new information, new ideas, and new modes of operation shaped in significant ways the evolving disaster response operations in Taiwan. Professional managers at every level exhibited a clear “bias toward inquiry,” or acknowledged effort to discover what the effects of the earthquake on the communities were; why the buildings, roads, and

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bridges failed; and how both technical and organizational infrastructures could be redesigned to prevent such losses in the future. This effort was matched by the remarkable social cohesion of the Taiwanese people, who contributed generously to disaster relief from every city and county in the island nation. Having faced extraordinary hardship in their history, the Taiwanese people re­sponded to the severe earthquake as the immediate challenge that they must overcome. A process of inquiry, evaluation, and documentation of response operations by government research agencies reinforced the courageous response of ordinary Taiwanese people to the sudden, urgent circumstances of the disaster. Although there was relatively little integrated information available to policy makers regarding seismic risk in the affected region prior to the disaster, governmental agencies and national research universities and centers quickly mobilized a knowledge base for the affected counties and towns. In doing so, they used advanced information technologies such as GIS,13 remote sensing, and a distributed information system to link separate knowledge bases of the responsible national ministries into a shared knowledge base accessible to policy makers with responsibilities for disaster operations.14 Taiwan also had an extensive seismic network installed and operational at the time of the earthquake, providing timely information to national decision makers regarding the location of the epicenter, depth, and magnitude of the shock (Uzarski and Arnold 2001). Information regarding the disaster was made available to the public via websites established specifically for that purpose. Although this knowledge base was not available to guide the immediate response operations, it was developed quickly following the earthquake with the intention of using it to facilitate the complex process of recovery opera­ tions, and to learn from this event in preparation for improving response to future earthquakes.15 SUMMARY, 1999 CHI CHI, TAIWAN, EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

The focus on research, evaluation, and development of new methods in response and recovery operations represented an innovative development in disaster management, led by the national governmental agencies and the research centers and universities. It also reflected a bias toward inquiry by governmental ministers in Taiwan, many of whom held PhD degrees in a range of disciplines and had formal training in research methods and analysis. This focus on inquiry created a favorable situation for transforming a destructive event into an opportunity for learning to mitigate future seismic risk. It demonstrated a productive collaboration between governmental agencies with responsibilities for disaster management and research institutions with capac-

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ity for data collection, analysis, and professional evaluation. There appeared to be sufficient knowledge of risk and professional skills to support the emergence of a coherent, interorganizational system for seismic risk reduction in Taiwan, but the driving dynamic of information flow essential to activate actors at different levels of operation and sustain their interactive performance in practice was not yet in place (Comfort 2000). The Pakistan Earthquake, October 8, 2005 INITIAL CONDITIONS

On Wednesday morning, October 8, 2005, at 8:50 a.m., children were sitting at school desks throughout the provinces of northern Pakistan. In the mountain cities and towns, markets were bustling with activity, as residents of communities in the highest, most rugged areas of Pakistan were bracing for winter. In homes, mothers were caring for young children and elderly family members, while husbands and sons were at work, many outdoors. Abruptly, a major earthquake, Mw = 7.6, rumbled through the area (Dawn October 9, 2005; EERI 2006b). Buildings collapsed, roofs caved in on schools, bridges buckled, landslides blocked roads, and communications were disrupted. In seconds, the earthquake shattered the ordinary routine of daily life in these mountain communities. The epicenter of the earthquake was located 19 kilometers north-­northeast from Muzaraffabad, the capital of Azad Jammu Kashmir (AJK) Province. Damage was heaviest in the cities of Muzaraffabad and Balakot, capital of the adjacent province, Khyber Pakhtunkhawa (KPK). The losses were staggering; 73,338 lives lost, 128,309 persons injured, more than 600,000 homes destroyed, more than $5 billion in damaged infrastructure according to initial government reports. The damage decimated core services of the communities, with 6,298 schools destroyed and 782 health institutes rendered unusable in conditions requiring urgent medical care (EM-­OFDA, Belgique 2005; Ismael 2012). The estimated number of deaths increased to over 80,000 as more data from remote villages were reported (EERI 2006b), further documenting the sobering losses generated by the earthquake. The event illustrates the bold gamble of building communities in areas of seismic risk and questions the extent to which the risk was known and shared among the residents of the nine affected mountain districts. From a policy perspective, this event raises basic questions regarding strategies of recovery for communities in the region that almost certainly face future risk. For Pakistan, ranking 147th on the United Nations Human Development index, designing the recovery process became inextricably enmeshed with development of economic, social, and cultural goals. Acknowledging seismic risk made the process more expensive. Failing to consider future risk in recovery and reconstruction would create the basis

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158 C H A P TER 7

for future disaster. Either alternative presented a major challenge that Pakistan could not meet alone. CHARACTERIZATION OF THE 2005 PAKISTAN EMERGENT RESPONSE AND RECOVERY SYSTEM

Four conditions shaped the response and recovery strategies to this severe earthquake in northern Pakistan. First, the logistics of providing search and rescue operations and humanitarian assistance were extraordinarily difficult, given the mountainous terrain and the extensive damage to roadways, bridges, and physical infrastructure. The primary means of transportation were helicopters that could fly over the damaged roads and landslides to reach the high mountain communities that were heavily destroyed. This meant that the primary organizations that participated in the initial search and rescue operations were militaries, both Pakistani and international, given the rugged terrain. The rescue efforts were limited by the number of helicopters and pilots available, and the sheer difficulties of physical access. Second, Pakistan at this time did not have an extensive geological survey that could monitor seismic risk and report changes in seismic activity to local communities. Consequently, it was initially difficult to identify the extent of the seismic rupture and the communities that were most heavily affected. Third, this event was the first international disaster in which the newly adopted cluster plan for humanitarian assistance was implemented by the United Nations Office for Coordination of Humanitarian Assistance (OCHA). Although the plan had been developed in August 2005, it was still new to international participants. Yet the implementation of the plan and its efforts to organize international assistance by basic types of services—food, shelter, health, water and sanitation, security and protection, logistics, and search and rescue—provided a structure for international governments and nonprofit organizations to implement the delivery of much-­needed resources in more efficient and effective ways. Fourth, in part facilitated by the international cooperation extended to, and accepted by, Pakistan from international participants under the UN OCHA cluster system, this event saw extensive use of satellite imagery to identify areas of damage in the mountainous regions that could not be reached by land transportation. Further, wireless communication systems were quickly implemented in key locations to facilitate difficult search and rescue operations and to track the delivery of humanitarian assistance to the damaged communities. For example, the IBM Crisis Response Team, sponsored by an international company with business operations in Pakistan, contributed a consulting team and software to facilitate the management of humanitarian relief and its distri-

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Frequency Distribution of Organizations in 2005 Pakistan Response System, by Jurisdiction and Funding Sector

TABLE 7.5.

International N Public 160 Nonprofit 54 Private 22 Total 236

National

Province

District

Subdistrict

%

N

%

N

%

N

%

N

%

22.86 7.71 3.14 33.71

115 49 42 206

16.43 7.00 6.00 29.43

84 25 4 113

12.00 3.57 0.57 16.14

92 28 15 135

13.14 4.00 2.14 19.29

9 1 0 10

1.29 0.14 0.00 1.43

Total N

%

460 65.71 157 22.43 83 11.86 700 100.00

Data source: Dawn, Islamabad, Pakistan, October 9–­29, 2005.

bution to communities in need (Woodworth 2005). This emerging use of information technology began to inform the decision processes used by both Pakistani and international participants in this event, as response operations transitioned into recovery operations in difficult terrain. Table 7.5 reports the distribution of organizations participating in Pakistani response organizations, reflecting different jurisdictional levels and types of funding for operations in the response system. The data in table 7.5 present findings from a content analysis of news articles regarding emergency operations from the newspaper, Dawn, published in Islamabad, for 21 days, October 9–29, 2005. Noteworthy is the proportion of international organizations involved in this response, slightly over one-­ third of all participating actors. Also interesting is the strong participation of district-­level organizations in comparison to provincial-­level organizations. Closer in physical distance and familiar with needs and local norms in the damaged communities, district organizations—public, private, and nonprofit—­ engaged more productively in managing constraints of local contexts and providing necessary services. Figure 7.7 shows the daily rate of change in the number of organizations participating in response operations for 21 days following this event. After an initial spike in the number of organizations entering the response system on day 2, the rate of change in the response system dropped precipitously over the first week of operations and appeared to settle into a functional pattern for the remaining two weeks. The total number of organizations varied over the three-­week period, with a noticeable increase in week 2, but dropping during the third week. Overall, the data show a relatively steady cumulative increase in participation by organizations in the response system. The types of transactions performed in response operations in the 2005 Pakistan earthquake are reported in appendix I, table I.7.3, totaling 1,027 transactions in 32 categories.16 The highest number of transactions was

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160 140

Number / %

120

Pakistan response system Total number of organizations Cumulative percentage of organizations Rate of change (%)

100 80 60 40 20

10

/9 10 /20 /1 05 0 10 /20 /1 05 1 10 /20 /1 05 2 10 /20 /1 05 3 10 /20 /1 05 4 10 /20 /1 05 5 10 /20 /1 05 6 10 /20 /1 05 7 10 /20 /1 05 8 10 /20 /1 05 9 10 /20 /2 05 0 10 /20 /2 05 1 10 /20 /2 05 2 10 /20 /2 05 3 10 /20 /2 05 4 10 /20 /2 05 5 10 /20 / 2 05 6/ 10 20 /2 05 7 10 /20 /2 05 8 10 /20 /2 05 9/ 20 05

0

Date FIGURE 7.7. Rate of change in the 2005 Pakistan response system, October 9–­29, 2005. Data

source: Dawn, Islamabad, Pakistan, October 9–­29, 2005. Figure by Jee Eun Song.

r­ eported for donations, 23.6%, reflecting the generous response of the Pakistani people and the international community. Communications, 14.5%, combined with IT-­related transactions, ranked second at 15.1%. This combined category documented the intensive need for communications in organizing response, recovery, and relief operations in the mountainous terrain. It also included the use of satellite technology to identify remote villages that had lost communications with the district emergency response organizations. Medical care/health transactions constituted the third-­highest category of reported transactions, followed by disaster relief, transportation, coordination, emergency response, and damage/needs assessment. These six categories, representing 45.95% of identified transactions, were comparable to other response systems but underscored the difficulty of organizing response operations in mountainous terrain as winter was approaching. Other transactions, approximately 15.3%, were distributed among the remaining categories. Interestingly, the largest number of actors engaging in these transactions, 455 or 23.6%, was tallied for the category of donations, followed by actors engaged in communications/IT, 16.4%, verifying the critical role of communications in disaster operations. Examining the distribution of actors engaged in transactions by sector, public sector actors, national through subdistrict, tallied 57.5% of the total (1,932), with nonprofit actors, national through subdistrict, constituting 9.3%, and private actors, 5.6%. International actors— public, private, and nonprofit—engaged in performing transactions made up

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MOH_PAK

MOFA_PAK

PAF_CHAKLALA EDHI

ARMY_PAK ARMY_PAK DAWN

PM_PAK PRESIDENT_PAK

MOH_NWFP GOV_AJK

DCO

GOV_NWFP UN

GOV_PAK

GOV_JAPAN

WFP

GOV_PUNJAB

GOV_SINDH

Jurisdiction

ANP

PRF

Funding sector

International

Public

National

Private

Province

Nonprofit

District

FIGURE 7.8 . Top 20 organizations in 2005 Pakistan earthquake response system, ranked by betweenness centrality, with jurisdiction and funding sector. Acronyms listed in table 7.6. Graph level statistics: diameter: 10; density: 0.0037; degree centrality: 0.1794; betweenness centrality: 0.1642. Data source: Dawn, Islamabad, Pakistan, October 9–­29, 2005. Figure by Jee Eun Song.

more than a quarter, 27.6%, of the total. The use of the UN OCHA cluster system framework facilitated the call for needed relief supplies and discouraged well-­intentioned but ill-­advised contributions, given Pakistan’s climate and terrain. Figure 7.8 presents a network diagram of the top 20 organizations participating in the Pakistan response system. The dominant organizations in the network were public organizations, but from across the jurisdictional spectrum. National organizations—government of Pakistan, President’s Relief Fund, and the president of Pakistan—played major roles, but they were supported by the Pakistani Army and the prime minister of Pakistan, as well as international organizations—the UN, World Food Program, and the government of Japan. Provincial and district organizations from the affected area and two nonprofit organizations were also actively engaged in response opera-

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Top 20 Organizations Participating in 2005 Pakistan Response System, Ranked by Betweenness Centrality, with Funding Source, Jurisdiction, and Degree Centrality

TABLE 7.6.

Acronym

Full Name

Funding

Jurisdiction

GOV_PAK PRF

Government of Pakistan President’s Relief Fund for Earthquake President of Pakistan Provincial government of Punjab Government of North-­West Frontier Province (NWFP) Prime minister of Pakistan Pakistan Army Government of Japan Dawn Foreign Ministry Edhi Foundation Government of Azad Jammu Kashmir UN Office for the Coordination of Humanitarian Affairs Chaklala air base District administration, district coordination officer Health minister of Pakistan Government of Sindh Awami National Party chief, Bashir Bilour World Food Program Health Minister of NWFP

Public Public

National National

40,550.54 34,089.52

128 72

Public Public

National Province

25,995.72 20,432.16

84 33

Public

Province

17,485.01

49

Public Public Public Private Public Nonprofit Public

National National International National National National Province

17,057.10 16,813.79 13,285.35 12,471.03 8,618.79 7,356.66 6,794.77

40 32 14 37 22 14 27

Public

International

5,574.43

23

Public Public

National District

5,478.73 5,172.14

24 10

Public Public Nonprofit

National Province Province

4,776.46 4,691.65 4,660.45

16 14 7

Public Public

International Province

4,623.62 4,418.61

15 17

PRESIDENT_PAK GOV_PUNJAB GOV_NWFP PM_PAK ARMY_PAK GOV_JAPAN DAWN MOFA_PAK EDHI GOV_AJK UN PAF_CHAKLALA DCO MOH_PAK GOV_SINDH ANP WFP MOH_NWFP

Betweenness Degree

Data source: Dawn, Islamabad, Pakistan, October 9–­29, 2005.

tions. Yet the centrality statistics show a sparse network with a density of 0.004 over a diameter of 10, but within that network, degree centrality of 0.18 and betweenness centrality of 0.16, indicating moderate connectivity among a smaller subset of eight organizations, as displayed in figure 7.8 and shown by values of betweenness and degree centrality cited in table 7.6. The findings presented in table 7.6 rank the government of Pakistan as the central actor in organizing response operations, with a betweenness centrality value of 40,554.5. The government of Pakistan served as the chief intermediary for other organizations participating in the response system. This ranking reflected the implementation of the UN OCHA cluster system, in which international donors operated through the government of Pakistan, which, in turn,

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channeled supplies and assistance to strengthen other national and provincial organizations. The Prime Minister’s Relief Fund ranked second on betweenness centrality, a key organization in terms of receiving donations and directing them to other actors and locations for direct delivery of services. Ten of the top-­ranked actors were national-­level institutions or ministries; six were provincial-­level agencies, three were international actors, and one, a collective category for district coordination officers, referred to district administrators who linked local households and businesses to provincial or national sources of assistance. All but three of the top 20 actors were public organizations, with two actors, the Edhi Foundation and the humanitarian arm of the Awami National Party (ANP), operating as nonprofit organizations. The newspaper Dawn, a privately owned Pakistani organization, played a major role in reporting news of disaster operations to the Pakistani people. It is noteworthy that the Edhi Foundation, a family-­organized and family-­managed Pakistani nonprofit foundation, follows directly the Ministry of Foreign Affairs in serving as a link between donors and other organizations participating in response operations. CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Professional reports from reconnaissance teams, private organizations, and public agencies documented the complex search and rescue operations, damage assessment process, and design of recovery programs (Durrani et al. 2005; Woodworth 2005; Hussain et al. 2006; EERI 2006b; Ismael 2012; Nazeer 2011). These reports, from separate perspectives, essentially corroborated the characterization of the 2005 Pakistan response and recovery system presented above. Each report underscored the extraordinary difficulty of conducting response and recovery operations in the high Himalayan areas affected by the earthquake. The physical terrain shaped in substantive ways the operations that could be implemented and limited the actors who could take part. These harsh conditions framed the remarkable contribution of the militaries—Pakistani and international—that had the logistical resources in helicopters and trained pilots to survey the area, identify damaged communities, and strive against wintry weather and limited time to bring relief supplies to the affected villages and towns. These conditions further highlighted the timely use of wireless information technologies to reestablish communications with isolated communities that had lost contact with external agencies, and the necessity of satellite imagery to provide accurate assessments of the damaged areas to decision makers managing scarce resources. Given the difficulty of managing resources in the harsh disaster environment, the first implementation of

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the United Nations cluster system received interest and attention from the international donor community. The Pakistani government welcomed international assistance and largely supported the organizational structure of the UN’s Office for the Coordination of Humanitarian Affairs (OCHA) for requesting and receiving humanitarian assistance. Professional judgment further confirmed the constructive role played by district officers in Pakistan’s governmental administration. District officers, with responsibilities for tax collection and adjudication of routine disputes, served as intermediaries between provincial governors and municipal mayors in matching scarce resources to local needs in the disaster-­affected areas. Still, the task of managing recovery for this region was especially challenging. The Pakistan government created a special agency, the Earthquake Reconstruction and Recovery Authority (ERRA), to manage the rebuilding process. This task necessarily involved all levels of government: national organization and authority to initiate action, provincial policies and personnel, districts within the AJK and KPK provinces that suffered different levels of damage, and municipal records, land tenure policies, cultural norms, and international resources and funding. An example of the successful exercise of this interjurisdictional, intersectoral mobilization of resources and action was the reconstruction of Balakot, a city of approximately 250,000 residents in the KPK province that had been virtually obliterated by the earthquake, to a higher standard of resistance to seismic risk (Ismael 2012). SUMMARY, 2005 PAKISTAN EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

Prior to the October 8, 2005, earthquake, Pakistan demonstrated the requisite conditions to mobilize an emergent operational system in response to a major earthquake. First, substantial knowledge of seismic risk existed in scientific circles and among senior practicing managers. Pakistan has long supported a national geological survey, originally established by 19th-­century British geologists in search of mineral resources. The national geological survey had created maps of the country, including the mountain provinces, and identified the major earthquake faults, but had not included detailed development from recent years. Second, Pakistan had secured the beginning elements of a technical infrastructure for communications and quickly mobilized assistance and external resources to access the internet, request satellite images, and establish wireless communication for remote areas. Third, Pakistan had retained a well-­ designed administrative structure, a legacy from British colonial administration, that specified clear responsibilities among national, provincial, district, and municipal jurisdictions. This administrative structure had the capacity to

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organize planned actions for recovery at respective levels of operation. Components essential for adaptation—knowledge of risk, technical infrastructure, and organizational processes—were sufficient in Pakistan to catalyze the emergence of an adaptive system; but the depth of resources and trained personnel required to sustain adaptive risk management was lacking. Wenchuan, China, Earthquake, May 12, 2008 INITIAL CONDITIONS

On Monday afternoon, May 12, 2008, school children were in their classrooms in Beichuan, a town of 20,000 residents nestled in the mountains of northwestern Sichuan Province, China. At 2:28 p.m., a massive earthquake registering Mw = 7.9 struck on the Longmenshan fault, approximately 25 kilometers from Beichuan, collapsing the school and crushing the children and their teachers. The severe shaking shattered schools, hospitals, and residential structures; damaged bridges and electrical transmission stations; and fractured highways throughout four provinces in northwest China (Lew et al. 2008; EERI 2008). Nearly 70,000 people were reported dead, with approximately 18,000 injured and more than 10 million left homeless. The losses affected nearly 57% of the total population of Sichuan (Wu et al. 2012). The earthquake triggered many secondary and tertiary consequences that further endangered villages and towns in the wide area affected by the earthquake. Heavy rains in the area led to landslides that blocked roads and rivers with rocks and debris, creating natural dams in the rivers that formed quake lakes. Estimates of losses, including costs of reconstruction, totaled US$441 billion on relief and reconstruction after this earthquake ( Jacobs 2012). The earthquake was the most severe reported in China since the Mw = 7.8 Tangshan earthquake of 1976, which claimed over 250,000 lives.17 Among the villagers in Beichuan and other towns in the area, there was little to no knowledge of seismic risk before the earthquake. Many had lived in the area for generations but had no awareness of the Longmenshan fault, less than 25 kilometers away, and the deadly risk that it posed to their communities (Personal interview, Beichuan County, September 23, 2008). Although China’s Seismological Bureau had mapped the country’s major earthquake faults, the intercontinental plate region in Sichuan was considered at low risk for rupture (Klinger et al. 2010). The technical infrastructure in these rural mountain communities was limited, at best. China had adopted a building code with specifications for seismic resistance, but there was little evidence of code implementation in building construction in rural towns and villages (EERI 2008). Gaps in the design and construction of schools and hospitals were especially acute, with an estimated 100 schools that collapsed

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in the region, killing an estimated 10,000 children (Ericksen 2008). For many families following China’s “one child” policy in the effort to restrict population growth, collapse of the schools meant the loss of their only child. Yet in 2008, changes beginning in access to telecommunications, the internet, and satellite imagery enabled the rapid response to this event both within China and from the global community. The technical information structure available to government agencies, nonprofit organizations, and citizens following the Wenchuan earthquake provided the basis for rapid mobilization of response operations. The premier of China, Wen Jiabao, learned of the earthquake immediately and, within hours, visited the heavily damaged sites in Sichuan Province to assess the damage. Government agencies exchanged GIS files and satellite images of the damaged area. Students, journalists, and household residents used cell phones and email messages to communicate updates on the status of damaged communities and to offer direct observations from the field. International scientific agencies issued bulletins (USGS 2008), and the international media reported scenes from the damaged areas in near-­real time. The result was a much broader public response in China to this 2008 earthquake than in previous events, with citizens riding their bicycles into damaged areas to offer their assistance, and students coming from universities in other provinces of China to bring needed skills and willing hands for recovery and reconstruction. Information spread among the population quickly and facilitated an active response to the damaged cities and towns from across China as well as other nations (Personal observation, Mianyang, China, September 2008). CHARACTERIZATION OF THE 2008 WENCHUAN, CHINA, RESPONSE AND RECOVERY SYSTEM

Identifying the networks of organizations involved in response operations offers a means to assess the degree to which a community has recognized the risk to which it is exposed, and the factors that influence the transition from immediate response to sustainable recovery from damaging events. It is essential to identify the factors that facilitate or inhibit the community’s capacity to assess its continuing risk, and to anticipate and respond effectively to recurring hazards. The 2008 Wenchuan earthquake represents an unusual action arena for studying the transition from response operations to recovery. This analysis involves a systematic effort to document the complex process of decisions and actions among the hundreds of local, national, and international organizations that were involved in the early search, rescue, and response tasks as the operations initiated in response shifted to the longer-­term process of reconstruction and sustainable recovery.

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The challenge is to identify the critical points of decision that build community capacity before an extreme event and, following the crisis, to mark the transition from response to recovery. These transition points may then be incorporated into a conceptual model to inform decision processes in other communities exposed to recurring risk. Without building capacity before an event to make a timely transition from response to recovery, a disaster-­stricken community risks interdependent, escalating failures in performance of key functions, such as provision of health services, housing, and education, all essential to sustainable renewal. Disaster response systems constitute a distinct type of dynamic network that emerges out of interactions among organizations converging on a disaster scene to assist stricken community residents and adapts to the severely damaged context of a disaster-­stricken region as it evolves. This adaptation creates the basis for transition to the next phase in the evolving process of disaster risk reduction for the community, recovery, and reconstruction. In many cases, the same organizations are involved in recovery, but their personnel may change, and organizations may perform different functions, interact with different agents, and achieve different results for the community. The action system also shifts from the clear, urgent goal of life safety in disaster response to a more nuanced set of multiple and sometimes conflicting goals for economic, social, and political development during recovery, with different strategies affecting different groups in different ways. For example, following the Wenchuan earthquake, a major issue for displaced families in Beichuan was relocation to newly constructed housing developments far from their fields, with little prospect for employment. The benefit of qualifying for a newly constructed home was offset by the loss of employment or means of earning their livelihood (Personal communication, Beichuan County, China, 2010). How the disaster response system forms, what degree of effectiveness it achieves, at what rate it develops over a given period, and how it is perceived by both internal and external actors become critical factors in determining the shape and performance of the transition to sustainable recovery and reconstruction. Table 7.7 presents a frequency distribution of organizations engaged in disaster operations by jurisdiction and funding sector, based on news reports from China News Net (2008), an online newspaper published in Chengdu, Sichuan Province.18 This network of 404 organizations represents a relatively small network of actors participating in response operations following the Wenchuan earthquake, but actors are selected from only one newspaper to avoid duplication from multiple sources. The dominant type of organization is public, with nearly half of the 404 organizations, 48%, identified as public organizations. The second-­largest category, public institutions (20.5%), represents a category of organizations distinctive to China that includes major

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0.00 0.00 0.00 0.74 1.49 2.23

% 49 19 12 12 29 121

N 12.13 4.70 2.97 2.97 7.18 29.95

%

National

46 23 11 9 8 97

N 11.39 5.69 2.72 2.23 1.98 24.01

%

Provincial

Data source: China News Net, Chengdu, Sichuan Province, China, May 12–­June 1, 2008.

0 0 0 3 6 9

N

International

70 36 13 14 9 142

N 17.33 8.91 3.22 3.47 2.23 35.15

%

Municipal

29 5 0 1 0 35

N

% 7.18 1.24 0.00 0.25 0.00 8.66

County

194 83 36 39 52 404

N

% 48.02 20.54 8.91 9.65 12.87 100.00

Total

Frequency Distribution of Organizations Engaged in Response Operations, 2008 Wenchuan, China, Earthquake, by Jurisdiction and Funding Sector

Public Public institutional State-­owned Nonprofit Private Total

TABLE 7.7.

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160

Wenchuan response system

140

Number / %

120 100 80 60 40 20

5/

12

/ 5/ 200 13 8 / 5/ 200 14 8 / 5/ 200 15 8 / 5/ 200 16 8 / 5/ 200 17 8 / 5/ 200 18 8 / 5/ 200 19 8 / 5/ 200 20 8 / 5/ 200 21 8 / 5/ 200 22 8 / 5/ 200 23 8 / 5/ 200 24 8 / 5/ 200 25 8 / 5/ 200 26 8 / 5/ 200 27 8 / 5/ 200 28 8 / 5/ 200 29 8 / 5/ 200 30 8 / 5/ 200 31 8 /2 6/ 00 1/ 8 20 08

0

Date FIGURE 7.9. Rate of change in 2008 Wenchuan earthquake response system, May 12–­June 1,

2008. Data source: China News Net, Chengdu, Sichuan Province, China. Figure by Jee Eun Song.

institutions, such as hospitals, research centers, and universities, still operating under the authority of the central government, but allowed to charge fees for services. State-­owned institutions (8.9%) are institutions such as banks, central newspapers, energy companies, and coal mines that are owned and operated by the central government but provide essential economic services. Noteworthy is the proportion of private organizations, 12.9%, and a small but active group of nonprofit organizations, 9.7%, participating in response operations. Figure 7.9 shows the rate of change in the 2008 Wenchuan response system over the 21-­day period following the event. The data show a sharp increase in the number of organizations participating in response operations on the second day following the earthquake, with a substantial decline in the rate of change by day 3, with some variance in the number of participating organizations and specifically a noticeable increase some 10 days after the event. This increase was likely due to a stronger mobilization of resources from organizations—public, private, and nonprofit—external to Sichuan. The cumulative percentage of organizations participating in response operations continued to increase over the 21-­day period of study. The types of transactions performed in disaster response operations are presented in appendix I, table I.7.4, by jurisdiction and funding sector (N = 273), with the number of actors engaged in each type of transaction

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(N = 962). This is a relatively small operations system, identified from one source, China News Net (2008), to avoid duplication, but it provides a working profile of the larger active response system. In this modest operations system, the largest proportion of transactions, nearly one-­quarter of the total, 24.9%, included donations of money, goods, and services. The second-­largest category, disaster relief, 11.4%, reported actions taken to distribute food, shelter, and clean water to the earthquake-­damaged areas. The combined categories of transactions in medical care/health, repair/reconstruction, and coordination tallied 20.5%. Other categories that merit notice were transportation/ traffic, visits by officials, condolences, and education issues, totaling 14.3%. Surprisingly, only 4.4% of the identified transactions fell under emergency response. Interestingly, the total number of actors reported, 962, exceeds the number of separate transactions, 273, by more than threefold, indicating that the transactions involved multiple actors, with some types—coordination, disaster relief, donations, repair/reconstruction—involving many actors. Yet the relatively low proportion of transactions classified as coordination, 5.9%, and the even lower proportion of transactions classified as communication, 1.5%, show that disaster operations were directed primarily by the Central Government and executed by the People’s Liberation Army, using a command and control structure. Figure 7.10 presents a network diagram of the top 20 organizations that participated in response operations for the 2008 Wenchuan earthquake, as identified in news articles from China News Net (2008) with nodes sized by betweenness centrality. The two organizations with the highest betweenness values, municipal government of Chengdu (23,154.06) and provincial government of Sichuan (21,862.48) connected organizations within the network that were not connected to one another. Both are public organizations that serve bridging functions among other jurisdictional organizations and private and nonprofit organizations within the response system. Table 7.8 reports the full names of organizations shown as acronyms for icons displayed in figure 7.10 and corroborates the visual diagram of the network, noting the distribution of organizations by jurisdiction and funding sector. The majority, 16 out of 20, are listed as public organizations with three listed as public institutional and one listed as a nonprofit organization. The 20 organizations show a mixed distribution among national organizations (8), provincial organizations (4), and municipal organizations (8) operating across jurisdictional levels to carry out shared tasks in response and recovery. This profile reveals the relatively high participation of subnational organizations in the operations system, which may reflect the perspective of the China News Net (2008), rather than the full organizational system. As the graph level statistics reported in figure 7.10 indicate, the organizational response network was a loosely connected network with degree central-

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MZB

HSZH GSSZF

GWY

FCZX

BJH GWYKZJZZHB SCMZT

FGW SCSZF

CDJQ SCSW

CDKZJZZHB

PZJKZX CDZX

CDSW CDSZF

CDGSJ

Jurisdiction

CDGHJ

CDRH

Funding sector

International

Public

National

Nonprofit

Provincial

Public institutional

Municipal FIGURE 7.10 . Top 20 organizations participating in 2008 Wenchuan, China, response system, icons sized by

betweenness centrality, showing jurisdiction and funding sector. Acronyms presented in table 7.12. Graph level statistics: diameter: 14; density: 0.006; degree centrality: 0.193; betweenness centrality: 0.282. Data source: China News Net, May 12–­June 1, 2008. Diagram by Jee Eun Song.

ity of 0.19, low density of 0.006, but in comparison, a stronger overall measure of betweenness centrality that indicated that key organizations played important roles in directing operations within the network. The measures of degree centrality reported for individual organizations complement this assessment and indicate a largely hierarchical structure of response operations. Particularly interesting is the depiction of the Sichuan Province Department of Civil Affairs in figure 7.10, disconnected from the rest of the network.

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TABLE 7.8. Top 20 Organizations in 2008 Wenchuan Earthquake Response System, Ranked by Betweenness Centrality, with Funding Source, Jurisdiction, and Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

CDSZF

Municipal government of Chengdu Provincial government of ­Sichuan State Council Earthquake Relief Headquarters Provincial government of Gansu Insurance Regulatory Com­ mis­sion of PRC State Council Red Cross of China Municipal party committee of Chengdu Provincial party committee of Sichuan Ministry of Civil Affairs of PRC Planning Bureau of Chengdu People’s Political Consultative Con­ference of the Chengdu Municipality Earthquake relief headquarters of Chengdu military CDC of Pengzou District

Public

Municipal

23,154.060

81

Public

Provincial

21,862.480

39

Public

National

9,570.052

16

Public

Provincial

7,981.814

27

Public insti­ tu­tional Public Nonprofit Public

National

7,445.131

12

National National Municipal

7,302.425 5,658.347 4,955.807

8 14 30

Public

Provincial

4,562.921

16

Public

National

4,104.779

9

Public Public

Municipal Municipal

3,491.518 3,044.741

18 6

Public

Municipal

2,658.437

21

Public insti­ tu­tional Public

Municipal

2,285.000

4

Provincial

1,994.052

6

Public

National

1,778.616

3

Public

Municipal

1,731.659

10

Public

Municipal

1,724.611

3

Public insti­ tu­tional Public

National

1,716.000

2

National

1,619.583

9

SCSZF GWYKZJZZHB GSSZF BJH GWY HSZH CDSW SCSW MZB CDGHJ CDZX

CDKZJZZHB

PZJKZX SCMZT FGW

CDGSJ CDRH FCZX CDJQ

Department of Civil Affairs of Sichuan Province National Development and Re­form Commission (NDRC) Commerce Bureau of Chengdu Chengdu branch of the People’s Bank of China China Welfare Lottery Management Center Chengdu military area

Betweenness Degree

Data source: China News Net, May 12–­June 1, 2008.

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CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Professional reports from reconnaissance teams, published accounts from humanitarian aid organizations, and papers presented at an international conference in Chengdu, one year after the May 12, 2008, earthquake all confirmed three basic findings. First, there was a serious lack of local knowledge of seismic risk among the population in the areas affected by disaster. Mayors of small villages in Beichuan County stated they had no knowledge of the Longmenshan fault, less than 25 kilometers away, prior to the earthquake (Personal interview, Beichuan County, 2010). Training for local officials had not included information about seismic risk (Personal interview, Mianyang, September 2008). County residents experienced deep shock over the sudden loss of children, schools, businesses, and farm animals and struggled to comprehend the extent of the earthquake’s impact on their lives and to regain a sense of connection to their communities (Personal observation, Beichuan County, September 2009). Second, although China had adopted a building code for seismically active regions, the implementation of this code in practice was seriously deficient, especially in rural counties. Most of the schools in the affected counties were relatively newly built, but over 100 schools in the region collapsed, killing or injuring over 10,000 children (EERI 2008). Many of the structures were built without engineering design and constituted a major vulnerability in the event. The technical structure of schools and hospitals, as well as housing, was not designed to withstand seismic risk. Third, organizational design for a comprehensive system of disaster management had begun in China only after the SARS epidemic of 2003 (Tong 2008; Zhang 2015). Five years later, officials in Beijing were familiar with disaster management, but most local managers in the western provinces were not aware of the risks in their communities. Consequently, they had not introduced basic measures of risk assessment and management to their constituencies. Information technology was only beginning to be used as a tool by local managers to monitor and adjust the performance of their agencies in risk environments. The gap between known risk and existing capacity to sustain a healthy, functioning community remained substantial. Reassessment of Emergent Adaptive Systems in Practice The set of four earthquake response systems assessed in this chapter reveals insights into the challenges of managing seismic risk. The cumulative knowledge of seismic risk is, in fact, an emerging science. Three of the four earthquakes outlined in this chapter were literally breaking new ground. The Mw 7.7

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Chi Chi, Taiwan, earthquake in 1999, the Mw 7.6 Kashmir earthquake in 2005, and the Mw 7.9 Wenchuan earthquake in 2008 constituted large continental thrust earthquakes with field observations recorded by several geophysical networks (Hubbard, Shaw, and Klinger 2010). Such faults are difficult to detect until they occur, making preparation for earthquake events an exercise in building legitimate support for collective action against an unknown threat. Data from the four cases presented above suggest modifications of the earlier premises regarding factors that distinguish emergent adaptive systems. Regarding awareness of seismic risk, scientists and researchers had studied and mapped seismic risk in each case, but this knowledge was not widely transmitted to the local communities in which the earthquakes occurred, nor was it integrated into public policy and practice. In 1999, for example, Turkey had a well-­developed seismic network and building codes specified for seismic resistance, but that knowledge was not translated into the construction of buildings that collapsed in the Marmara earthquake region. In the Taiwan, Pakistani, and Wenchuan, China, cases, sophisticated groups of scientists and engineers were aware of the level of seismic risk to which their respective populations were exposed, but this knowledge was not extended broadly to increase public understanding of the probability of hazard. Consequently, awareness of seismic risk did exist, but within relatively small scientific and earthquake engineering groups within each broader society. Regarding technical infrastructure for communication, each of the four earthquake-­affected communities had modest technical infrastructures for communication, but they were not yet widely distributed through the communities. In 1999, satellite phones were introduced into response operations in Marmara, Turkey, but they were only intermittently effective. Cell phones were available in Taiwan in 1999, but again, they were not widely adopted by the general population. In 2005 Pakistan, the physical environment of the earthquake-­affected area was even more challenging. Sophisticated technologies, such as satellite imagery and GIS mapping, were used effectively to provide timely information to practicing managers but were largely not available to the general population. Technical communication infrastructure in the earthquake-­affected area of Pakistan was largely limited to the radio system provided by military personnel. In Sichuan Province, China, in 2008 cell phones were available, although they were not widely in use by the general population. Similarly, in each of the four earthquake response systems, some organizational capacity existed in the communities prior to the events. This capacity allowed responsible actors to mobilize resources to meet immediate needs generated by the earthquakes, but in all four cases, the local capacity was easily overwhelmed by the size, scope, and severity of the events experienced and could not be sustained by the operational system that was generated.

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The set of four earthquake response systems discussed in this chapter demonstrates the wide variation in time, scale, space, and impact of such events on their respective communities. Common to all four earthquake systems, however, is the need for timely, valid information to initiate collective action and sustain energy in the continual redesign of learning processes that mark adaptation to seismic risk as an ongoing hazard.

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8 Nonadaptive Systems 2001 BHUJ, GUJARAT, INDIA , EARTHQUAKE; 2004 SUMATRA , INDONESIA , EARTHQUAKE/ TSUNAMI; AND 2010 HAÏTI EARTHQUAKE RESPONSE SYSTEMS

Nonadaptive Systems, Redefined With no warning, no preparedness activities, and no communications system to alert community residents to the silent risk of earthquakes, local managers struggle to cope with the devastation of a sudden earthquake, without resources or training for an event that is beyond their comprehension. Under such conditions, their capacity to adapt has no baseline of knowledge or local experience from which to mobilize response operations. Their only resource is to call for help . . . often hours, days, kilometers distant. The task becomes even greater as unfamiliar organizations respond, but enter a disaster-­degraded environment, lacking the knowledge of local conditions and residents. The limited capacity of local managers and organizations to adapt under urgent stress strains the larger system. Nonadaptive systems are systems that are low on technical structure, low on organizational flexibility, and largely low on cultural openness to change. Such systems depend on external assistance to meet the immediate needs of earthquake-­damaged communities. After the urgent crisis passes, nonadaptive systems largely fall back to their previous modes of operations with little change in risk reduction or resilience to disaster. Given the changes in technical, organizational, and cultural systems since 1999, the process of adaptation in complex systems merits careful review and reconsideration. Adaptation in

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practice can be viewed essentially as a process of self-­organization among multiple organizations focused on a common goal. Carried out largely through multiway communications facilitated by a technical information infrastructure, interacting organizations adapt to changing conditions and one another through shared knowledge and experience (Castells 2004). Without access to a functioning information infrastructure, the local organizations are unable to create the multiway processes that forge new collaboration across traditional boundaries of jurisdiction and funding sectors. In communities with little capacity to mobilize external resources to anticipate or lessen losses from a destructive event, the local operational system turns almost immediately from response to the longer-­term issues of reconstruction, as losses deepen and cascade into further destructive impacts on the community. For example, damage to the rudimentary water systems in the dry regions of western Gujarat exacerbated already primitive health and sanitation facilities. Disruption of roads and railroads halted the flow of goods to and from markets, affecting the daily exchange of goods and services among people in the area with little reserve, and worsening the impact of a major earthquake in an already fragile area. External response actions cannot halt the progression of cumulative losses when local capacity is initially weak and further disabled by an extreme event. The damaged community then slides deeper into dysfunction, and immediate losses shift to major needs for reconstruction. Yet the affected community is unable to muster the local capacity needed to manage the more complex challenges entailed in sustainable recovery, without continuing external support. The duration of network performance depends on the capacity of the nascent network to attract support from the wider environment in which it operates (Luhmann 1995). In a community ravaged by an earthquake, ordinary people will come forward to help one another and share scarce food, water, and shelter. This spontaneous exchange becomes a network of mutual support and assistance. But if scarce supplies and operational personnel are not reinforced from outside sources, the network may falter as participants no longer have the capacity for exchange. The transition from response operations to recovery from an extreme event is difficult, as the urgency of immediate response gives way to the longer-­term, interdependent issues of recovery. At this point, old conflicts among community groups may reemerge, new conflicts may generate, and the commitment to a common goal may strain in the uncertain, often conflictual context of recovery from disaster. Participating actors select different signals from the same events, given their specific experience, knowledge, and capability. Old boundaries for interaction are redrawn, but new boundaries may not be commonly accepted. The transition period allows a reassessment of risk that may guide community action toward a more informed, resilient vision.

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If there is no public space (Castells 2004) available for the discussion and resolution of conflicts over future risk versus present need, the initial energy that led to the formation of the response system in the immediate aftermath of disaster may dissipate (Tong 2008; Comfort, Oh, and Ertan 2009). By public space, Castells means a public forum where different views may be proposed by interested parties, contested, redesigned, and integrated into a coherent strategy of action that wins consensual support from the whole community. His concept of public space echoes that of Ostrom’s (1990, 2005) concept of a knowledge commons for information search and exchange, with the distinctive difference that Castells views the public space as created primarily through informal media platforms, such as Twitter and Facebook, that are not controlled by governments or owned by commercial corporations. Accepting Castells’s (2012, chap. 1) argument that transformation of the communications environment directly affects the forms of meaning construction for a community, I propose that the degree to which informed judgments of known risk are acknowledged and assessments of future risk are incorporated into policies and plans for rebuilding a community after a disaster constitute measures of adaptation. The test of adaptation is whether the damaged community can effectively learn from the extreme event and integrate insights from that experience with previous knowledge of risk to rebuild the community in a more constructive, resilient form to reduce future risk. This process becomes nonlinear, as different groups in the community adapt their behavior at different rates and in irregular sequence. Using an updated concept of adaptation—or conversely, nonadaptation— three seismic response systems developed following earthquakes in Bhuj, Gujarat, India, 2001; Sumatra, Indonesia, 2004; and Haïti, 2010, shown on maps in figures 8.1 and 8.2. The three cases were analyzed rigorously to determine if their preliminary classification as nonadaptive was supported by the data. Networks of interacting organizations engaged in response operations were identified for the three-­week period following the precipitating earthquake, based on content analysis of news reports, documentary analysis, and professional reconnaissance reports. Each response system was analyzed using the same methods to allow comparison among cases (Yin 2014). The systems illustrate in practice the gaps in awareness, communication, and interaction that inhibit adaptation to unanticipated risk. Bhuj, Gujarat, India, Earthquake, January 26, 2001 INITIAL CONDITIONS

On January 26, 2001, a sunny, clear morning in old Anjar, a city in the western state of Gujarat, India, preparations were underway for celebrating Republic Day, the nation’s 51st anniversary of independence.1 Four hundred school chil-

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dren were assembling to march down the main street, in proud recognition of their citizenship in the world’s largest democracy. At 8:46 a.m., a powerful earthquake shattered the town, collapsing buildings on both sides of the main street. Debris falling inward toward the center of the street struck the children as they were marching, killing at least 200 and injuring many others. This sudden loss of life, with severe damage and extensive injuries, was repeated in villages, towns, and cities throughout the districts of Kachchh, Jamnagar, Rajkot, Surendranagar, and Ahmedabad, as the most severe seismic event in India in nearly 200 years took its toll. The epicenter of the earthquake was located about 20 kilometers north-­ northeast of the town of Bhuj, in the Kachchh District. The Indian Meteorological Department reported the earthquake as registering 6.9 on the Richter scale at a depth 23.6 kilometers. The US Geological Survey registered the event as Mw = 7.7 with slightly different coordinates, UTC 23.40N 70.32E (EERI 2001), not unusual in the global measurement of seismic motion. Strong motion records obtained from Ahmedabad, the largest city in Gujarat State some 250 kilometers from the epicenter, indicated a peak ground acceleration of about 0.11g, a powerful force. Official statistics reported 20,005 dead from the event, with approximately 166,836 persons injured, including 20,717 seriously injured. The earthquake cut a wide swath of damage, with 21 of the 27 districts of Gujarat affected to some degree. This area included 7,904 villages in 182 talukas, or local administrative districts. Damage to housing created a major problem; 332,188 houses were destroyed, while 725,802 houses suffered damage to varying degrees. An estimated 1.59 million people were affected out of a population of approximately 4.78 million residents of the area, or roughly one out of every three persons incurred damage. The Ministry of Agriculture, which has responsibility for disaster management under India’s disaster laws, reported total losses for the region at US$2.1262 billion in March 2001, while estimates from other agencies ranged over US$3 billion. The size and scope of these losses for India compelled a careful analysis of measures for reducing risk and managing the recurring threat of earthquakes in the region. While the Kachchh District of Gujarat was known to be prone to seismic activity and was assigned the highest rating of V on India’s scale of seismic risk, the sobering losses suffered in Gujarat reflected the initial conditions in which the earthquake occurred. Grouped under three major dimensions of technical structure, organizational processes, and cultural values, these conditions interacted to amplify the consequences of this earthquake, resulting in extraordinarily high costs. Under technical structure, the number of buildings that collapsed, the heavy damage to rail and roadways, the limited communications and information infrastructure document the discrepancy between design practices used in constructing the built environment and the degree of seismic

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FIGURE 8.1 . Nonadaptive systems: Bhuj, Gujarat, India, 2001; Sumatra, Indonesia, 2004. Maps by Fuli Ai.

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FIGURE 8. 2 . Nonadaptive systems. Haïti earthquake, 2010. Map by Fuli Ai.

risk for the area. Although a well-­designed building code existed in India at the time, the nation, struggling with poverty and lagging in development, had made little investment in ensuring the enforcement of that code in the actual construction of the buildings. Under organizational capacity to mitigate risk and mobilize response, the heavy losses in lives and the high numbers of injured and displaced families from the 2001 Bhuj earthquake provided sobering evidence of the lack of attention and investment in disaster plans and preparedness in local communities. Disaster management is a relatively new concept to India, as the traditional response has been to mobilize relief after a disaster occurred. After the devastating cyclone of 1998, initial steps were taken to develop an emergency plan for cyclones in Gujarat State, but no similar effort was made to develop an equivalent plan for seismic risk. In the January 2001 earthquake, the wide geographic area and dense population of the affected region exceeded the limited capacity of the local managers to respond to critical needs. Although extraordinary efforts were made by state, national, and international organizations to mobilize personnel, equipment, and supplies to meet

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immediate needs, the scale of operations and extent of resources needed to respond to a disaster of this magnitude required organizational capacity and skills that were not available at the local levels of district, taluka, and village administrations. Without that crucial link to microlevel management in the local districts, midlevel state managers and upper levels of national and international management struggled to form a coherent system. Economic conditions further exacerbated the vulnerability of the area to hazards. As a developing nation, India had largely not invested in preparing for disasters that might not occur. Yet the heavy losses incurred by the number of vulnerable communities and the high costs of reconstruction meant that India could continue to ignore the issue of emergency preparedness only at peril of endangering further economic and social development efforts in the region. Cultural values in the region, observed generally as openness to new information and willingness to act on that information, reflected a population that, absorbed in meeting the demands of daily life, had little reserve or capacity to attend to new information, and less ability to act on it. For example, the lack of scientific knowledge at the local level exacerbated the vulnerability of the area, as new buildings were constructed by homeowners without benefit of seismic design. Although the Indian Meteorological Department had identified the Kachchh District as an area of high seismic risk, this assessment was not widely known among the people living in villages. Nor were most local officials aware of the degree of risk to which their communities were exposed. Scientific knowledge of the geologic conditions and the seismic history of the region had not been incorporated into local planning or community awareness programs (Personal communication, Ahmedabad, 2001). The discrepancy between known seismic risk and informed action to reduce that risk at multiple levels of responsibility in governmental, nonprofit and private organizations compounded the damaging consequences of the earthquake. The actual conditions in Gujarat existing prior to the earthquake are largely consistent with the indicators listed under the three dimensions of technological, organizational, and cultural characteristics presented in chapter 4, table 1. Low economic conditions and lack of scientific knowledge at the local level are cross products of the three major dimensions, demonstrating the interaction among these conditions. The problem of seismic risk is complex, interactive, and dynamic, in which a low ranking on one indicator often leads to a low ranking on other indicators, compounding the degree of risk in a specific area. Notably, India had experienced the Latur earthquake, Mw = 6.8, eight years earlier on September 30, 1993, in Maharashtra State (Comfort 1999a). While conditions of seismic risk vary among the Indian states and the Bhuj earthquake at Mw = 7.7 was more severe, the organizational capacity mobilized in

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the Bhuj earthquake appeared less coherent than the response in 1993. This observation suggests a lower level of recognition of seismic risk in Gujarat State, at least among local administrators and their clientele. CHARACTERIZATION OF THE 2001 BHUJ, GUJARAT, EMERGENT RESPONSE AND RECOVERY SYSTEM

A test of a community’s capacity to adapt to sudden, urgent demands of a major earthquake is the degree of awareness of risk extant among the population before the event occurred, and its capacity to mobilize an operational response system to meet demands generated by the event. In Gujarat, an organizational response system did emerge, relatively small at 335 organizations for the size and scope of the event, but one that included participants from private and nonprofit organizations as well as public. Based on a data set compiled from newspaper reports culled from the Hindu, an English-­language newspaper with offices in Delhi and Mumbai, for three weeks immediately following the earthquake, January 26–February 15, 2001, key characteristics of this response system are reported below. While newspaper accounts constitute secondary data, they include the identification of private and nonprofit organizations as well as public organizations, and organizations from at least four jurisdictional levels. The lowest jurisdictional levels of talukas and villages are included under the category of district. These reports do not offer a complete representation of the emergency response system, but news accounts provide an organizational profile of response actions and their daily evolution, representing a public characterization of the system that is widely available to the affected community. Table 8.1 reports the frequency distribution of organizations engaged in the full Gujarat response system by jurisdiction and funding sector. The low proportion of local public organizations, 7.7%, and of private and nonprofit orga-

Frequency Distribution of Organizations Engaged in Disaster Operations by Jurisdiction and Funding Sector, Bhuj, Gujarat, Earthquake Response System, 2001

TABLE 8.1.

International

Public Private NGO Total

National

State

District

Total

N

%

N

%

N

%

N

%

N

%

54 13 19 86

16.12 3.88 5.67 25.67

106 23 40 169

31.64 6.87 11.94 50.45

39 1 5 45

11.64 0.30 1.49 13.43

26 4 5 35

7.76 1.19 1.49 10.45

225 40 70 335

67.16 12.24 20.60 100.00

S

Data source: Hindu, Delhi, India, January 26–­February 15, 2001.

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140

Growth rate of Gujarat response system

120

Number / %

100 80 60 40

Total number of organizations Cumulative percentage of organizations Growth rate (%)

20

1/

26

/ 1/ 200 27 1 / 1/ 200 28 1 / 1/ 200 29 1 /2 1/ 00 30 1 / 1/ 200 31 1 /2 2/ 00 1/ 1 2 2/ 001 2/ 2 2/ 001 3/ 2 2/ 001 4/ 2 2/ 001 5/ 2 2/ 001 6/ 2 2/ 001 7/ 2 2/ 001 8/ 2 2/ 001 9/ 2 2/ 00 10 1 / 2/ 200 11 1 / 2/ 200 12 1 / 2/ 200 13 1 / 2/ 200 14 1 / 2/ 200 15 1 /2 00 1

0

Date

FIGURE 8.3 . Rate of change in 2001 Gujarat response system, January 26, 2001–­February 15, 2001. Data source: Hindu, Delhi, India, January 26–­February 15, 2001.

nizations, 1.2% and 1.5%, respectively, underscores both the level of poverty and the lack of preparedness for seismic risk in the region. Over half of the organizations, 50.5% were national, but more than a quarter, 25.7%, were international, demonstrating the reliance on external sources for assistance. Figure 8.3 shows the growth rate of the response system as new organizations entered the system daily. Approximately 75% of the organizations engaged in disaster operations entered the system within the first week, with 87% of all organizations responding within the first 10 days. The sharp increase shown on January 29, 2001, represents the arrival of the Indian Army in the most affected districts of Gujarat to extricate the dead from the debris and to restore communications with other army bases and state agencies using their radio networks (Comfort 2004a). The distribution of types of transactions performed by jurisdictional and sector actors varied within the Gujarat response system, as shown in appendix I, table I.8.1. Five types of activities reflected nearly 60% of the total of 589 reported transactions, with nearly two-­thirds, or 64.7%, of the 865 identified actors engaged in the five primary types of activities: donations, coordination, disaster relief, communication, and medical care. Additionally, emergency response, damage assessment, and earthquake assessment and research activities were reported with noticeable frequency. Surprisingly, the categories of repair and reconstruction, and building inspection and code issues received relatively little attention in the news articles, revealing that little planning for either mitigation or recovery was reported within the first three weeks after

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the event. This pattern indicates little awareness or prior effort to reduce seismic risk at the local level, despite national efforts to initiate disaster planning for cyclones (Comfort 2002; 2004a). NETWORK ANALYSIS

Using the data set of interacting organizations identified from news reports from the Hindu, two measures of centrality were calculated, degree centrality and betweenness centrality. Degree centrality counts the number of ties that a specific node has with other actors in the network. Average degree centrality reports the number of existing ties within the entire network, in comparison to the possible number of ties (Wasserman and Faust 1994). Betweenness centrality measures the extent to which a given node in a network connects two other nodes that would not otherwise be connected (Wasserman and Faust 1994, 189–91). Figure 8.4 shows the network diagram of betweenness centrality for the top 20 organizations that were actively engaged in disaster operations in the Gujarat network. The average degree centralization for the whole network is 0.21, indicating low connectivity. A given node may serve as a bridge between two other nodes, creating a measure of dependency for the nodes that it connects. Figure 8.4 shows visually the centrality of the Gujarat state government in linking national, international, and nonprofit organizations. There is only one district level organization, Bhuj government, in the top 20 organizations of the network, indicating that the dominant resources in response to this event came from external sources. There were no private organizations involved, only two nonprofit organizations and one political party organization. Public organizations from state, national, and international jurisdictions were clearly primary actors. The nodes in the diagram are sized by influence, indicating that the larger the size, the greater the number of organizations in the network that are connected through that specific node, but would otherwise not be connected to one another. This bridging function is important in building capacity for coordinated response. Table 8.2 presents the data from which figure 8.4 is drawn and provides the full names of the acronyms shown in figure 8.4, as well as the values of betweenness and degree centrality. The Gujarat state government reported the highest value on betweenness centrality and played a key bridging role as a mediating organization in the complex Indian administrative structure. Three national organizations, the prime minister’s cabinet, the Central Crisis Management Group, and the Central Administration, also played strong bridging roles. Importantly, the Bhuj District Collectorate at the epicenter of the earthquake played a strong connecting role, but it is the only district-­level organization included in the list.

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Funding sector

Jurisdiction GOV_AUS

UN

International

Public

National

Private

State

Nonprofit

District

Political party

GUJ_BHU

CSIT

HAM NRSA AP_GOV GUJ_GOV

MIN_DEF PM MIN_LPA CENTRE

RC

CABINET

EU

CONGRESS ARMY

CCMG

MIN_AGR MIN_POW

FIGURE 8.4 . Network diagram of top 20 organizations, Gujarat response system, ranked by betweenness centrality. Graph level statistics for network: diameter: 12; degree centrality: 0.214; density: 0.005; betweenness centrality: 0.112. Data source: Hindu, Delhi, India. January 26–­February 15, 2001. Acronyms listed in table 8.2. Diagram by Jee Eun Song.

Two nonprofit organizations and a political party organization linked other national, state, and district ministries and nonprofit organizations within the network, but no private organization is included in this list of top organizations. Notably, the Center for Spatial Information and Technology, National Remote Sensing Agency, and ham radio operators are among the top 20 groups in the operational response, indicating the significant role of advanced information technology and communications in facilitating decision making. Inclusion of national agencies indicates that spatial data were produced and available, but not widely diffused within the whole network’s operations, a critical omission in understanding the degree of risk for the community. Ham radio volunteers provided vital links to communities cut off from other means of communication.

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TABLE 8.2. Top 20 Organizations in Gujarat Response System, Ranked by Betweenness Centrality and Reporting Funding Sector, Jurisdiction, and Node Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

GUJ_GOV CABINET CCMG CENTRE PM HAM RC UN NRSA GUJ_BHU CONGRESS CSIT

Gujarat government Cabinet Crisis Management Group Centre Office of Prime Minister Ham radio operators International Red Cross United Nations National Remote Sensing Agency Bhuj Collectorate National Congress Party Center for Spatial Information Technology Ministry of Defense European Union Indian Army Parliamentary affairs minister Minister of state for power Andhra Pradesh government Australian government Agriculture secretary

Public Public Public Public Public NGO NGO Public Public Public NGO Public

State National National National National National International International National District National National

6,280.14 2,638.78 1,879.88 1,832.09 1,354.65 1,237.11 891.77 870.59 764.70 732.71 714.82 662.89

73 19 19 20 20 5 7 5 3 3 17 5

Public Public Public Public Public Public Public Public

National International National National National State International National

644.37 612.75 582.46 575.16 571.00 512.05 429.00 387.12

7 6 6 15 4 10 2 7

MIN_DEF EU ARMY MIN_LPA MIN_POW AP_GOV GOV_AUS MIN_AGR

Betweenness Degree

Data source: Hindu, Delhi, India, January 26–­February 15, 2001.

CORROBORATING ASSESSMENT FROM PROFESSIONAL REPORTS

Findings from documentary analysis and other professional reports essentially corroborated the findings from the network analysis, reported above. Specifically, an earlier study focused on identifying types of information technology used to support communications and organizational interaction following the Bhuj, Gujarat, earthquake drew three conclusions regarding the uses of information technology during the Gujarat response operations (Comfort 2004a). These findings were based on direct field observations and interviews with key decision makers on reconnaissance trips to Gujarat in February 2001 and May 2002. First, the field study noted substantial differences in information technology used by decision makers at different jurisdictional levels, from primarily face-­to-­face communication at the district and taluka levels to the wireless radio systems used by the Indian Army to communicate with other army bases and state agencies to the sophisticated satellite imagery used to create GIS

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maps and satellite phones used at the Ministry of Defense. Second, the different types of information technologies used for communications among organizations produced different results in terms of rapid recognition of changing conditions and capacity to mobilize coordinated action among different jurisdictional levels. For example, the newly organized Gujarat State Disaster Management Authority (GSDMA) had established a Remote Sensing and Communications Centre (RESECO) with direct access to the Indian Satellite System. GSDMA created GIS maps of the damaged areas but had no technical means to share the maps with district administrators who did not have the computers, software, or technical skills to receive them. Paradoxically, these differences in information technologies created obstacles in managing disaster operations. For example, international and national organizations that contributed relief supplies and disaster assistance expected local managers to track the distribution of these supplies, ensuring that all disaster-­affected villages received needed aid and distributed it without bias to their clientele. In the broad disaster region that encompassed more than 7,900 villages and 1.59 million affected people, this was nearly an impossible task to do with traditional accounting methods. An international company, US-­based IBM, mobilized volunteers from its Indian offices and created a software program to track the supplies. Since there was no internet available in the villages, IBM staff drove from village to village to collect the information, enter it into a computational file, and transfer it onto computer diskettes to create a cumulative record for the event (Woodworth 2001). This proved to be a very useful but temporary measure that could not be maintained after the IBM volunteers returned to their home cities. SUMMARY: BHUJ, GUJARAT, INDIA, EARTHQUAKE RESPONSE SYSTEM

The findings in this brief analysis document the initial conditions in Gujarat that were low on technical structure, low on organizational capacity, and low on cultural awareness of risk. Compounding these conditions was the lack of access for most residents of the region to the technical means to communicate more widely with other organizations and access sources of knowledge that could facilitate adaptive response to continuing seismic risk in the region. Six key decisions revealed the challenges and constraints of the evolving response system.2 These decisions largely involved access to, and dissemination of, information to the wider public. The first decision was not to make public the data from the Indian Satellite System that showed the areas of damage in Kachchh near the Pakistan border.3 Presumably this decision was made for security reasons, but it deprived the local managers of heavily damaged districts and talukas of an ac-

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curate assessment of damage in these sensitive areas. Second, the Central Administration distributed satellite phones to the district collectors to facilitate communication with, and among, the district collectors, but without clear instruction for their use or assistance in overcoming their limitations. Consequently, the phones, which could have greatly facilitated communication across administrative boundaries, were largely unused. Third, while the GSDMA did develop GIS maps of the affected area using the advanced facilities of the Indian Satellite System, it did not have the capacity to distribute maps to local managers, limiting access to accurate location data for a­ssessing needs and distributing relief supplies. Fourth, given the lack of information regarding which villages were affected most heavily, the Indian Army arrived days late in many of the remote areas, extending the suffering of those affected. Fifth, confronting enormous need and limited support, the humanitarian arms of the political parties assisted in the distribution of relief goods but did so along partisan, religious lines, exacerbating already tense relations among religious and ethnic groups. In a positive decision, GSDMA accepted the voluntary support of the international firm IBM to mobilize programmers from Chennai to set up a reporting system to account for the distribution of relief supplies, a welcome, if limited, program with no internet connection (Woodworth 2001). These practical decisions made in the context of managing disaster operations reveal the extent to which access to infor­ mation—or lack of it—influenced the operations of the response system in Gujarat.

Sumatra, Indonesia, Earthquake and Tsunami Response System, December 26, 2004 INITIAL CONDITIONS

On a balmy Sunday morning, December 26, 2004, people in coastal communities of northern Aceh Province, Sumatra, Indonesia, were out in their neighborhoods, many on the beaches. Suddenly, a massive earthquake, measuring 9.2 on the moment magnitude scale of earthquake severity4 struck at 0758 (local time) on the Sunda trench, off the western coast of Aceh Province, northern Sumatra (Borrero 2005). People in their homes and on the beaches felt the earthquake as a strong, prolonged shaking event but were relieved when the shaking stopped, thinking the danger had passed. They did not know that the earthquake had ruptured the fault line for approximately 1,300 kilometers and caused a massive uplift of the sea floor of approximately five meters (Pomonis et al. 2005). This sudden alteration of the sea floor generated a powerful tsunami that affected a dozen nations in and around the rim of the Indian Ocean basin.

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Approximately 30 minutes after the earthquake, the first tsunami wave struck Banda Aceh without warning. A city of 322,000 residents and capital of the province of Aceh, Banda Aceh is located at the northern tip of Sumatra, some 250 kilometers northeast from the epicenter of the earthquake. Although it is a coastal city, Banda Aceh had no recent experience with tsunamis, and its residents were almost wholly unaware of the risk. When the water first receded from the coastline, residents did not recognize this unusual event as an indicator of a tsunami but rather walked toward the beach to take a closer look and pick up the fish that were left behind. When the returning wave engulfed the city, residents were caught by surprise and could not escape the oncoming rush of water. The destruction was caused in part by the powerful wave, but also by the crushing force of cars, trucks, refrigerators, and other debris that it picked up along the way. People clung for their lives to trees or buildings, but for many, it was too late. The tragic aspect of this event was both the lack of local knowledge of tsunami risk for coastal regions and the lack of an information infrastructure to warn the local authorities and residents of this danger.5 The effects of the tsunami varied according to the physical formation of the coastlines, with waves traveling at speeds up to 500 miles per hour and reaching heights that varied from 2.5 to 30 meters (NASA 2005) in areas where the physical features of the coastline focused the waves. The four nations most severely affected—Indonesia, Sri Lanka, India, and Thailand—suffered different degrees of damage and losses in lives and property. Two of these nations, Indonesia and Sri Lanka, already torn by long-­r unning civil conflicts in which internal groups had been seeking independence from their respective national governments, confronted serious challenges in mobilizing disaster operations. This analysis focuses on the impact of the 2004 earthquake and tsunami on Indonesia, specifically northern Sumatra and the Aceh region, with its capital city, Banda Aceh. The initial conditions in Aceh reflected both the limited state of awareness of seismic risk in the region and the low capacity of the community, weakened by ongoing civil conflict, to adapt to the massively altered conditions of a full-­ scale catastrophe. Referring to the three dimensions of technical, organizational, and cultural characteristics for the province of Aceh as a region, the interactions among these dimensions created an unusual web of interdependence that limited the capacity of Aceh to respond to immediate needs in practice. Historically, Aceh Province had never accepted colonial rule, as had other parts of Indonesia; in December 2004, the province was engaged in a 40-­year armed conflict with the national government to gain its full independence. Organized as the Free Aceh movement, this armed struggle for independence compounded the drain on local resources and limited investment in economic and social development from the national government. Located

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approximately 1,100 miles from the capital city, Jakarta, Banda Aceh is a port city that has a long history of trading with Portugal and later, the Middle Eastern nations ringing the Persian Gulf and the Gulf of Oman. The city had the basic physical infrastructure needed to maintain its port and shipping operations, and railroads to transport goods to and from markets, but its communications and information infrastructures were not well developed. The economic and cultural links of the region were historically stronger with external nations than with the national government of Indonesia. Organizationally, in 2004, Aceh was a semi-­autonomous province formally included in the national administrative structure of Indonesia but granted the power to implement local laws referring to development of its extensive natural gas and oil resources and religious practices (Indrayana 2008, 161). Informally, the region operated largely independently, with relatively little economic and social interaction with other provinces of Indonesia. Culturally, the people of Banda Aceh were proud of their heritage of trading with Middle Eastern countries and practiced a more conservative version of Islam than in other parts of the nation. Committed to their strict religious beliefs, the residents of Aceh were largely concerned with maintaining their sheltered society6 and did not readily engage with their fellow citizens in other provinces. Under conditions of low technical development, limited organizational interaction, and low openness to new information, the massive earthquake and ensuing tsunami of December 26, 2004, generated catastrophic damage, killing approximately 1 in 3 persons in the city of Banda Aceh and destroying roads, railroads, bridges, public and private buildings, and other infrastructure over a large part of the city and surrounding region. Other coastal towns, such as Meulaboh on the western coast of northern Sumatra, were also heavily damaged. The destruction was so extensive that Aceh had no alternative but to turn to the national government and external sources for assistance. CHARACTERIZATION OF 2004 SUMATRA, INDONESIA, EARTHQUAKE AND TSUNAMI RESPONSE SYSTEM

Even under difficult initial conditions, an operational response system formed to address the demands from the earthquake and tsunami, with a major influx of support and assistance from the national government, other provinces in Indonesia, and the international community. Then-­president Yudhoyono requested assistance from the United Nations Office for the Coordination of Humanitarian Assistance (OCHA), and the international community responded quickly and generously to the UN call (United Nations Relief Web 2005; AusAid 2005). This class of nonadaptive earthquake response systems also includes the unusual case of four nations—Indonesia, Sri Lanka, India, and Thailand—­

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responding to the same event, the Sumatran tsunami of 2004 (also known as the Indian Ocean tsunami) that experienced different degrees of severity of damage, loss, and capacity for collective action. Given constraints of time and space, only the Indonesian case is included in this study. The selection of Indonesia from the four most heavily damaged nations is warranted, given the size and scale of losses in the nation that suffered the brunt of destruction from this unusual, ocean basin–wide event. In 2004, Indonesia, prone to disaster, had a national policy on disaster response, but the major responsibility for managing response operations was assigned to the Indonesian Army (TNI). Units of the TNI immediately responded to the need for assistance in Banda Aceh and established relief centers for residents damaged by the event. Yet, given the prolonged conflict with the TNI, residents of Aceh did not trust the army units that were presumably providing disaster assistance. The official centers, staffed by military officers from Jakarta, were largely empty, as the local residents stayed away, or sought assistance from international nongovernmental organizations that responded rapidly to meet the critical needs for shelter, food, clean water, and medical care in the affected communities.7 The damage was so extensive that local residents lost not only their homes, but also their livelihoods, as fishermen lost their boats and nets; businesses lost their inventory and equipment; and hospitals, severely damaged, lost both equipment and personnel, and thus the capacity to provide medical care. Given the tensions in the region, then-­ president Yudhoyono requested UN OCHA to manage the distribution of disaster relief supplies and services, with Indonesian agencies, public, private, and nonprofit, working under the UN leadership to provide impartial assistance to the disaster-­affected people in the region (Personal observation, Banda Aceh, March 10, 2005). Based on newspaper accounts from the Jakarta Post collected for 21 days after the event, December 26, 2004–January 15, 2005, our study team conducted a content analysis to identify the organizations that were involved in disaster operations. The study team used the same format for coding the news reports that were coded for all 12 earthquake response systems included in the study and followed the same procedures for checking and validating the coding results. Table 8.3 shows the distribution of organizations engaged in the Sumatran earthquake and tsunami response system by jurisdiction and funding sector. Over 60% (60.7%) of the organizations participating in disaster response were public organizations, and of those, nearly 28% were international. Adding private and nonprofit organizations to the category of international respondents, nearly 42% of all organizations in the response system were international, with 32% national. This distribution confirms the lack of preparedness and capacity at the subnational levels of jurisdiction.

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152 41 36 1 230

N

27.69 7.47 6.56 0.18 41.89

%

International

87 35 50 4 176

N 15.85 6.38 9.11 0.73 32.06

%

National

17 10 8 0 35

N 3.10 1.82 1.46 0.00 6.38

%

Special Region

31 7 3 2 43

N 5.65 1.28 0.55 0.36 7.83

%

Provincial

26 4 7 0 37

N 4.74 0.73 1.28 0.00 6.74

%

Municipal

12 3 0 0 15

N

2.19 0.55 0.00 0.00 2.73

%

Regency

8 2 3 0 13

N

% 1.46 0.36 0.55 0.00 2.37

Local

Frequency Distribution of Organizations Engaged in the 2004 Sumatra, Indonesia, Response System, by Jurisdiction and Funding Sector

Data source: Jakarta Post, Jakarta, Indonesia, December 26, 2004–­January 16, 2005.

Public Nonprofit Private Political Total

TABLE 8.3.

S

L

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333 102 107 7 549

N

% 60.66 18.58 19.49 1.28 100.00

Total

194 C H A P TER 8

140

Sumatra response system

Number / %

120

Total number of organizations Cumulative percentage of organizations Rate of change (%)

100 80 60 40 20

12

12

/2

6/

2 /2 004 7 12 /20 /2 04 8 12 /20 /2 04 9 12 /20 /3 04 0 12 /20 /3 04 1/ 1/ 200 1/ 4 2 1/ 005 2/ 2 1/ 005 3/ 2 1/ 005 4/ 2 1/ 005 5/ 2 1/ 005 6/ 2 1/ 005 7/ 20 1/ 05 8/ 2 1/ 005 9/ 1/ 200 10 5 / 1/ 200 11 5 / 1/ 200 12 5 / 1/ 200 13 5 / 1/ 200 14 5 / 1/ 200 15 5 / 1/ 200 16 5 /2 00 5

0

Date

FIGURE 8.5 . Rate of change in 2004 Sumatra, Indonesia, response system, December 26, 2004–

January 16, 2005. Data source: Jakarta Post, Jakarta, Indonesia, December 26, 2004–­January 16, 2005.

Figure 8.5 shows the irregular entry of new organizations into the response system, with a peak of new organizations entering the system on day 3, followed by a sharp drop in new organizations on day 6. A new peak was reached on January 4, 2005, when international organizations responded to the UN call for all member organizations to assist Indonesia and other nations affected by the tsunami waves (United Nations Relief Web 2005; Comfort 2007a). New organizations continued to enter the system throughout the three-­week period, revealing a strong commitment to humanitarian assistance. The international organizations showed a jagged pattern of entry into the system, surpassing the national organizations in the second week of response, and continuing through the three-­week period. Local organizations entered the system, but provincial and subdistrict organizations showed low rates of entry, at least as documented by the news reports. Organizations from the Special Capital Region, Jakarta, revealed a low but steady rate of entry into the system. NETWORK ANALYSIS

Given the size, scale, and scope of the Sumatran disaster, the number of transactions and the number of actors involved in carrying them out were very large, with 1,660 transactions undertaken by 2,999 actors, as identified in the Jakarta Post reports. Frequencies of transactions carried out in disaster operations by type, jurisdiction, and funding sector are reported in appendix 1, table I.8.2. As secondary data, the news reports were likely incomplete, but they provide a daily record of activities and a profile of the types

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accor

Jurisdiction

idrcros bha

Funding sector

International

Public

National

Private

Provincial

Nonprofit

Special region mhealid navid govid

eu

milid opid

un

natpol

govaceh

ovpid afid ocmpwid

asndra

asean idcci

ogns

ogj

FIGURE 8.6 . Network diagram of top 20 organizations in Sumatra, Indone-

sia, response system, ranked by betweenness centrality. Acronyms listed in table 8.4. Graph level statistics for whole network: diameter: 9; density: 0.006; centrality total (degree): 0.253; centrality (betweenness): 0.106. Data source: Jakarta Post, Jakarta, Indonesia, December 26, 2004–­January 16, 2005. Figure by Jee Eun Song.

of transactions involved in disaster operations and the interactions among the actors who carried them out for the whole system in contrast to single agency situation reports. Reviewing the distribution of types of transactions, three types of transactions were undertaken most frequently: coordination of response, recovery (15.7%), donations (15.2%), and disaster relief (8.1%). Medical care/health was in fourth place (6.93%). Other types of transactions focused on political dialogue/legislation, and visits, condolences sent by officials, transportation, loans, and repair/reconstruction of the damaged infrastructure. Figure 8.6 shows a network diagram of the top 20 organizations ranked by betweenness centrality. Betweenness values are important indicators of organizations that bridge other organizations in the network not connected to one another (Wasserman and Faust 1994). While the graph level betweenness score for the network is low at 0.106, the 20 organizations listed in table 8.4 all report values well above that mean score. Notably, the first five organizations on this list of top 20 are national level organizations, with the Office of the President of Indonesia ranked highest in betweenness scores. The Indonesian Red Cross, a national nonprofit organization linked to the International Confederation of Red Cross and Red Crescent Societies, played a key role in

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Top 20 Organizations in 2004 Sumatra, Indonesia, Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Sector, and Degree Centrality

TABLE 8.4.

Acronym

Full Name

Funding

Jurisdiction

opid govid idrcros milid mhealid asean

Office of the President of Indonesia Government of Indonesia Indonesian Red Cross Military of Indonesia Ministry of Health, Indonesia Association of Southeast Asian Nations Government of Aceh Province Office of the Governor of North Sumatra Office of the Vice President of Indonesia Office of the Coordinating Minister for the People’s Welfare, Indonesia Office of the Governor of Jakarta Bali Hotel Association United Nations Indonesian Air Force National Police of Indonesia Indonesian Chamber of Commerce and Industry Accor Group Aceh–­North Sumatra Natural Disaster Relief Agency Indonesian Navy European Union

Public Public Nonprofit Public Public Public

National National National National National International

Public Public

govaceh ogns ovpid ocmpwid ogj bha un afid natpol idcci accor asndra navid eu

Betweenness Degree 16,013.20 9,232.40 7,541.19 6,783.49 5,212.51 4,457.54

142 85 35 80 24 62

Provincial Provincial

3,660.64 3,156.00

31 4

Public

National

3,001.47

33

Public

National

2,983.10

31

Public Nonprofit Public Public Public Nonprofit

Special Region Provincial International National National National

2,958.00 2,310.77 1,962.72 1,902.01 1,881.90 1,765.18

20 21 27 10 17 11

Private Public

International Provincial

1,360.00 1,359.00

8 8

Public Public

National International

1,214.55 1,110.83

8 13

Data source: Jakarta Post, Jakarta, Indonesia, December 26, 2004–­January 15, 2001.

linking other organizations engaged in disaster operations. These national actors served as key connecting links to the international community that both played a critical role in humanitarian assistance and provided services to the devastated area. The Indonesian military continued to play a major role in logistics, as it operated a helicopter port near Banda Aceh to bring supplies to the disaster-­affected region and to transport people who were injured or otherwise needed to travel to other locations (Personal observation, Banda Aceh, March 2005). The significant role of international organizations engaged in disaster response is highlighted by the inclusion of the United Nations and the European Union in this list of 20 organizations with the highest betweenness values. There is also one private international organization, ACCOR Group, included in this network, indicating the global character of the event.

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CORROBORATION ASSESSMENT FROM PROFESSIONAL REPORTS

Multiple professional reports confirmed the findings from the content analysis of newspapers and the results of the network analysis. The Earthquake Engineering Research Center (EERI) had established a clearinghouse website to assemble key reports, both national and international, from this significant event in one location.8 The low degree of connectivity reported in findings from the network analysis was confirmed by the shattered communications networks both within and between organizations that were seeking to mobilize resources and services in response to the extraordinary demands of this catastrophe. The local government agencies were almost wholly disabled, as the tsunami had destroyed their buildings and records, and killed or injured vital personnel. With near total disruption of the local communications infrastructure and the influx of hundreds of international and national aid organizations into Aceh Province, communications became critical in efforts to achieve a coordinated response to the disaster. It was difficult to create a common operating picture to inform the multiple actors of a coherent course of action. Rather, multiple operating pictures emerged, as the sectors worked largely independently. Militaries provided logistics, working at the request of the government of Indonesia, but in accordance with United Nations standards for providing humanitarian assistance. International aid organizations were welcomed by the Indonesian government but also were tasked to follow UN standards for humanitarian assistance in delivering food, shelter, and medical care directly to the disaster-­affected communities. International financial institutions interacted with national governments to manage financial contributions, again in accordance with UN guidelines. Following the UN standards meant placing the needs of the disaster-­affected people above any single organizational or national goal. The sheer enormity of the destruction in Aceh Province and the number of organizations that offered assistance made it difficult for groups to plan a coherent strategy for coordinated action, let alone implement one. This task was made more difficult by the lack of a common information infrastructure among the participating actors that could transmit urgent information to multiple nations, governments, and groups simultaneously. This vital function meant that organizations and groups often did not know where they could support one another, or where they might provide mutual assistance in reestablishing basic services. Some households and villages were overlooked in the general effort to assist people in need. Small matters that could have been easily solved became larger problems through inattention and delay. The pattern of asymmetry in information processes in this large-­scale, multilevel set

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of disaster operations inhibited the coordination needed to address the urgent problems of the area in a timely way (Comfort 2007a). This pattern of asymmetry in information processes is shown most clearly in an analysis of the interactions among the international, national, provincial, and local organizations in Indonesia. As table 8.3 shows, more than two-­fifths of the organizations participating in the disaster response system, 41.9%, were international and provided welcome funding, expertise, and technical assistance for the badly ravaged communities of Aceh. Yet interactions with the disaster-­affected communities required knowledge of the local context and language that could most effectively be provided by Indonesian organizations. This situation created mutual dependencies within the evolving response system, where international organizations depended on national organizations for knowledge of the local context and language, and the national organizations depended on the international organizations for funding, specialized skills, and guidance in meeting international standards for humanitarian assistance. In practice, two networks evolved in disaster operations: (1) an international network that operated under United Nations standards for humanitarian assistance; and (2) a national network that operated under the legal authority of the government of Indonesia. The two networks interacted at critical points in response operations but in many, if not most, operations acted independently of one another. The inability to coalesce this large set of 549 organizations into a coherent, unified response system reflected the size, complexity, and severity of the event, but also the significant asymmetry in information processes among the jurisdictional levels of authority and action involved in the networks. SUMMARY, SUMATRA, INDONESIA, EARTHQUAKE AND TSUNAMI RESPONSE SYSTEM

The findings presented from the network analysis of the Sumatra response system reveal a community with high physical exposure to the seismic hazard of earthquakes and tsunamis caught almost wholly unaware of this risk and the extreme destruction it could wreak on a community. The devastation of the 2004 Sumatra earthquake and tsunami in Indonesia was compounded not only by the lack of awareness of seismic risk, but also by the inability of the local community to adapt and adjust its engineered, organizational, and cultural infrastructures to cope with such an extreme event. Information regarding seismic risk did exist, but in isolated niches in the society; it was not translated into a common framework to support daily decisions. This asymmetry in information flow inhibited the rapid mobilization of a coherent response system among the multiple, diverse actors in the response system.

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One very positive outcome emerged from the catastrophic destruction of this event. In negotiations brokered by the president of Finland, the Free Aceh movement and the Indonesian government resolved their long-­r unning conflict over independence. The Free Aceh movement agreed to put down their arms and to recognize the legal authority of the national government of In­ donesia in return for semi-­autonomous management of key resources of natural gas and oil, and local ordinances for the implementation of their social and religious customs (Aspinall 2005). This historic agreement served as the basis for beginning a reassessment of earthquake and tsunami risk in this nation of islands. Haïti Earthquake, January 12, 2010 INITIAL CONDITIONS

At 4:53 p.m. on January 12, 2010, government officials in Port-­au-­Prince, Haïti, were closing their files and preparing to leave their offices for the day when a severe earthquake, Mw = 7.0, jolted the city and surrounding area.9 Still in his office, President René Prèval watched in disbelief as the presidential palace crumbled around him. Unharmed, the president, an engineer by training, walked outside to a scene of unimaginable devastation. Port-­au-­ Prince the capital city of Haïti and the political, economic, and cultural center of this small Caribbean island nation, was in ruins. Eleven out of 12 governmental ministries collapsed, with records and administrative files scattered across ministry grounds, leaving an already fragile government in Haïti with limited capacity to respond to the enormous need generated for its affected population. Estimates of losses varied widely; the Haïtian government reported 230,000 deaths, the United Nations Office for the Coordination of Humanitarian Assistance (UN OCHA) calculated approximately 220,000 deaths; the US Agency for International Development reported the lowest figure at approximately 50,000 deaths. A professional research group from Karlsruhe Institute of Geophysics, using multiple methods of estimation and many sources, reported approximately 136,933 deaths (Daniell, Khazai, and Wenzel 2013). Although the exact number of deaths will never be known, the impact of this event on the city of Port-­au-­Prince and the vulnerable country of Haïti was devastating. Approximately 1.5 million people were left homeless as approximately 80% of the buildings in the city were damaged or destroyed. Nearly 80% of the schools’ infrastructure was destroyed or damaged; three of the four universities were severely damaged, and General Hospital, the primary medical institution in the city, collapsed (EERI 2010; MCEER 2010; Government of Haïti 2010; Comfort, Siciliano, and Okada 2010).

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The catastrophic damage to this port city devolved directly from the initial conditions in which the earthquake occurred. There was virtually no awareness of seismic risk or preparedness for earthquakes in this small island nation, located on the edge of the Caribbean plate. For the previous 50 years, the level of poverty, illiteracy, and limited infrastructure that gripped the society had been exacerbated by a series of unstable governments, creating a set of interacting conditions that ranked Haïti 149th out of 189 nations on the United Nations index of human development (UNDP 2009). When the earthquake occurred, Haïti had no national disaster plan; no building codes were in effect, and the government’s limited capacity to respond was further constrained by the direct loss of personnel, buildings, and equipment in the devastated city. Haïti was in urgent need of assistance from the international community. The initial conditions in which the January 12, 2010, earthquake occurred in Haïti created a surprising mix of a very fragile society with a small proportion of the population already connected to the internet and using it to access information and resources externally. The basic conditions in Haïti prior to the earthquake were extremely limited, with unemployment reaching 60%; illiteracy at 62%,10 a set of governmental institutions edging toward stability after decades of dysfunction with the support of the United Nations Mission to Stabilize Haïti (MINUSTAH), and a physical environment exposed not only to seismic risk, but also to hurricanes, floods, and landslides. Although the Enriquillo Plantain Garden fault, the source of the January 12, 2010, earthquake, had long been identified by geophysicists and geologists working on Caribbean plate tectonics as likely to rupture (Calais et al. 2010), this knowledge had not been communicated clearly to city planners and policy makers, and certainly not to the resident population. Consequently, there was almost no existing knowledge base to which managers might turn for an accurate and timely assessment of hazards, including earthquakes, and vulnerability to risk for the region. CHARACTERIZATION OF THE 2010 HAÏTI EARTHQUAKE RESPONSE AND RECOVERY SYSTEM

In these difficult initial conditions, a response system emerged in Haïti, largely dominated by international organizations, given the extraordinary damage to the local physical, engineered, and organizational infrastructure. In these conditions, our study team conducted a content analysis of news reports from a local online newspaper, Caribbean News Online (CANA), January 12–February 3, 2010. published in Barbados in English, to gather local information on questions regarding response operations in Haïti. We considered French-­language newspapers, such as Le Nouvelliste published in Port-­au-­Prince, but given the language skills of our joint research team, we accepted the limitations of work-

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Frequency Distribution of Organizations Participating in 2010 Haïti Response Systems, by Jurisdiction and Funding Sector

TABLE 8.5.

International

Public Nonprofit Private Political Total

National

Regional

Municipal

Total

N

%

N

%

N

%

N

%

N

%

66 16 8 1 91

41.51 10.06 5.03 0.63 57.23

10 0 0 0 10

6.29 0.00 0.00 0.00 6.29

38 11 8 0 57

23.90 6.92 5.03 0.00 35.85

0 1 0 0 1

0.00 0.63 0.00 0.00 0.63

114 27 16 1 159

71.70 16.98 10.06 0.63 100.00

Data source: Caribbean News Online, January 12–­February 3, 2010.

ing only in English, recognizing that we would need supplementary material to provide a valid characterization of the Haïti response and recovery system. Table 8.5 cites the distribution of actors identified from the CANA reports. It is a small network, but it includes the regional organizations in the Caribbean cluster of islands that were largely omitted in reports published in US newspapers that focused chiefly on US organizations active in Haïti. Regional in this characterization of the network for Haïti means regional Caribbean nations, or Haïti’s immediate neighbors in the geographic Caribbean region, many of whom share both Haïti’s natural beauty and its vulnerability to extreme events. As shown, the largest proportion of organizations participating in the response network identified from the CANA reports consists of international public organizations, approximately 60%, while in this tally, provincial and local Haïtian organizations are not included. This omission is likely due to the limited data set, as our field research teams observed local and provincial Haïtian organizations delivering relief goods and services to disaster-­affected neighborhoods during three field trips to Port-­au-­Prince and the Artibonite Valley in 2010, 2011, and 2012. Figure 8.7 shows the growth rate of the response system over the four-­ week period, January 12–February 3, 2010. The growth rate represents the organizations identified in the daily reports from the Caribbean News Online electronic newspaper. The CANA reports capture specifically interactions among Caribbean nations taken to assist Haïti in coping with this catastrophic event. The heaviest entry of new organizations into the operational system occurred during the first three days, and the system identified from the CANA data was nearly complete within 10 days. Public organizations were clearly the dominant type of organization engaged in disaster response. Private and nonprofit organizations began entering the disaster operations system on the second day, more fully on the third day. A small influx of public organizations entered the system on the fourth day but tapered off by the end of that week.

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400

Growth rate of Haiti response system

350

Number / %

300 250 200

Total number of new organizations Cumulative percentage of organizations Growth rate (%)

150 100 50

1/

12

1/ /20 13 10 1/ /20 14 10 1/ /20 15 10 1/ /20 16 10 1/ /20 17 10 1/ /20 18 10 1/ /20 19 10 1/ /20 20 10 1/ /20 21 10 1/ /20 22 10 1/ /20 23 10 1/ /20 24 10 1/ /20 25 10 1/ /20 26 10 1/ /20 27 1 0 1/ /20 28 10 1/ /20 29 10 1/ /20 30 10 1/ /20 31 10 / 2/ 201 1/ 0 2 2/ 01 2/ 0 2 2/ 01 3/ 0 20 10

0

Date FIGURE 8.7. Rate of change of 2010 Haïti response system, January 12–February 3, 2010.

Data source: Caribbean News Online, January 12–­February 3, 2010.

Other professional reports, such as United Nations Relief Web and national aid organizations such as US Agency for International Development (USAID) reported continuing activity by international nonprofit and public organizations, but the records of assistance, overall, were not carefully kept. Only about 50% of the relief organizations working in Haïti reported their activities to official sources, leaving a large gap in official records.11 The number and types of transactions performed by the actors in the response system, as reported in the CANA data set, are presented in appendix I, table I.8.3. This limited data set identified six major types of transactions performed in response operations, accounting for damage/needs assessment, 6.9%, and donations, 6.3%. These figures reveal the extent to which the Haïtian government agencies necessarily relied on external assistance to meet the most basic needs of the affected population. Emergency response operations, law enforcement, and fund-­raising represented notable commitments of time and effort. Fund-­raising, essential in all response operations, was a key component in the network of organizations that emerged following the Haïti earthquake. Over 21% of the transactions involved coordination with other nations, organizations, and groups who responded to the dramatic visual images of the city in ruins that circulated in global news reports. Figure 8.8 presents a network diagram of the top 20 organizations engaged in response operations in the 2010 Haïti response system by jurisdiction

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Jurisdiction govhaimh cmc

Funding sector

International

Public

National

Private

Regional

Nonprofit

jamcc jcg

odpem cdema

nlcr govjam

govus govhai

caricom

ccc

un govdom

wb

jdf

oas

govguy

eccu

govant

FIGURE 8.8 . Network diagram of top 20 organizations in 2010 Haïti response system, ranked by betweenness centrality. Graph level statistics: diameter: 6; density: 0.014; total degree centrality: 0.278; betweenness centrality: 0.12. Data source: Caribbean News Online, January 11–­February 15, 2010. Figure by Jee Eun Song.

and funding sector, with the nodes sized by degree of influence. As shown in figure 8.8, regional public organizations dominated the response system, and CARICOM, the Caribbean Community organization of 15 nations committed to economic cooperation and regional integration played the largest role in connecting participating nations in the shared goal of assisting Haïti. Table 8.6 presents the top 20 organizations represented in the diagram, with their full names, by jurisdiction, funding sector, betweenness centrality,

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TABLE 8.6. Top 20 Organizations Participating in 2010 Haïti Response System, Ranked by Betweenness Centrality, with Jurisdiction, Funding Sector, and Degree Centrality

Acronym

Full Name

Funding

Jurisdiction

Caricom Govjam Govdom Govhai Jcg Odpem

Caribbean Community Government of Jamaica Government of Dominica Government of Haïti Jamaica Consulate General Office of Disaster Preparedness and Emergency Management Caribbean Disaster Emergency Management Agency United Nations Government of United States Organization of American States Jamaica Chamber of Commerce Eastern Caribbean Currency Union Caribbean Conference of Churches Jamaica Defense Force World Bank Government of Antigua and Barbuda Caribbean Media Corporation Government of Guyana Ministry of Health, Haïti New Life Children’s Refuge

Public Public Public Public Public Public

Regional Regional Regional National Regional Regional

1,528.27 977.07 693.56 521.51 471.00 465.00

46 30 23 12 8 6

Public

Regional

417.49

15

Public Public Public Nonprofit Public Nonprofit Public Public Public

International International International International International Regional Regional International Regional

372.95 362.45 333.81 240.00 203.19 161.00 148.72 85.57 85.02

15 11 10 4 5 3 7 4 3

Private Public Public Nonprofit

Regional Regional National International

81.00 81.00 81.00 81.00

2 2 2 2

Cdema Un Govus Oas Jamcc Eccu Ccc Jdf Wb Govant Cmc Govguy Govhaimh Nlcr

Betweenness Degree

Data source: Caribbean News Online, January 12–­February 3, 2010.

and node degree centrality. The set of top 20 organizations reflects the significant role of international organizations in mobilizing response to the affected population in Haïti. The table especially documents the activities of the regional Caribbean island nations in their efforts to assist Haïti, as well as the actions of the government of the United States and international organizations such as the United Nations, Organization of American States, and World Bank. Of the 20 organizations included in this network, only two are Haïtian, the government of Haïti and the Ministry of Health, Haïti. In the diagram, CARICOM, the regional economic market for the Caribbean, clearly serves as the most influential organization in this subnetwork, linking other organizations that would not otherwise be connected. The network diagram, although limited in size, offers documentation for the types of interactions that occurred among the island nations in the Caribbean and also among the financial organizations, such as World Bank and Organization of American States.

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Corroboration from Professional Reports Given the size, scale, and severity of the disaster in Haïti, there has been a plethora of professional reports written on this disaster from multiple perspectives: seismological, engineering, sociological, medical and health, economic, political, legal, and international development. From these many perspectives, a basic consensus emerges on three fundamental premises regarding Haïti’s capacity to achieve sustainable resilience to seismic risk. First, the basic science of seismic risk was not well developed in Haïti, and consequently, this lack of knowledge undercut any existing engineered, technical, or socioeconomic structures. The majority of Haïtians, including managers of the responsible public agencies, was unaware of seismic risk, and consequently, the country was woefully unprepared. There was no national building code; there was no national seismic network; there were no alternative plans for electrical power, water, and wastewater distribution systems. The impact of the earthquake on an already limited infrastructure was far more damaging than anticipated for a 7.0 magnitude shock. Second, the conditions facing Haïti were far more substantive than recovery from earthquake damage. Rather, the small nation confronted the much larger tasks of reconstruction and economic and social development that were inextricably linked to recovery. Yet reconstruction and development were costly, long-­term tasks that required planning and persistent effort that the fragile Haïtian government was ill-­prepared to undertake without considerable assistance. Third, the well-­intentioned and generous efforts of the international community to assist Haïti were often not well designed, not well understood, nor well received by Haïtians. The international community had worked, in many instances, without the full participation of the affected Haïtian population, and consequently, well-­intended efforts regrettably did not achieve the expected results. While many Haïtians were eager to rebuild their country in sustainable, resilient ways, they faced many complex constraints and obstacles in doing so. Overcoming these obstacles requires time, resources, and commitment among both national and international partners. Without external resources and support, the recovery process stalled. Without internal organization and commitment, the recovery process cannot be sustained. Although there have been promising starts, the process is long and arduous, and years later there are still only tentative results. SUMMARY, HAÏTI RESPONSE SYSTEM

Although the data from CANA provides only a partial characterization of the Haïti response system, the data set identified a largely international/regional response network that mobilized to assist and support the traumatized Haïtian

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population. The lack of Haïtian organizations reported in this network of the top 20 organizations verifies the extent to which the Haïtian government was itself a casualty in this disaster. The lack of awareness of seismic risk within government organizations and among the general public clearly contributed to the sobering losses, as few mitigating actions had been taken. There was no set of uniform building codes for the nation. There was no national geological survey to monitor seismic risk systematically. The gaps in basic information about seismic risk revealed a nation uninformed and unprepared to cope with a major seismic event. The transition to recovery in Haïti turned to virtual reconstruction of the whole society and to rebuilding institutions to manage risk that had been eroded by decades of political dysfunction and poverty. Reassessment of Nonadaptive Systems in Practice Given the performance of the three earthquake response systems characterized above—Gujarat, Sumatra, and Haïti—the term “nonadaptive” takes on different meanings in different contexts. In practice, each system adapted to the shattered context in which it was operating to some extent. What differed among the response systems were the initial conditions in which the systems evolved, the impact of the extreme event on those conditions, and the requisite resources and commitment to sustain changes that were initiated. In each of the three cases, some adjustments were made, but none altered the operational environment substantially. In Gujarat, the shadow of hostility with neighboring Pakistan curbed the flow of information between jurisdictional levels to support rapid response and recovery. In Sumatra, the earthquake and tsunami led to the resolution of the long-­standing civil conflict with the Free Aceh movement, a very positive outcome, but the organizational networks and communications channels among national, provincial, city, and district jurisdictions that had been ruptured for decades needed to be rebuilt. This proved to be a much more difficult task than the physical reconstruction of roads and buildings. In Haïti, the existing government, fragile before the earthquake, was overwhelmed by the enormous tasks confronting the small nation, which, in most cases, involved full-­ scale redesign and development. These tasks involved fundamental reconstruction of basic institutions of schools, hospitals, universities, banking, and rule of law, as well as reconstruction of roads, infrastructure, and housing. The requirements for continuing the adaptive processes that had been initiated with external assistance during response operations in all three cases were simply not available to support sustained adaptation. In each case—Gujarat, Sumatra, and Haïti—the international community gave generously in humanitarian assistance to meet the immediate needs of the affected populations, but the local capacity to carry out the longer-­term

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tasks needed to be developed, a process that required more time and resources than either the affected countries or the international community anticipated. The basic needs for organization and communication essential for reconstructing shattered communities were largely not recognized, and therefore not met. The transition between response and recovery in these seriously damaged disaster environments needs to be reframed as a separate set of responsibilities that requires continuing external assistance and collaborative mentoring to build the local institutions and organizations that can manage the complex technologies and organizational processes needed for sustained resilience. Without a continuing level of support through this critical process of transition to recovery, adaptations initiated during the response phase dissipate in a daily struggle for survival.

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9 Evolving Patterns of System Response

Building Adaptive Resilience from Extreme Events In managing the risk of seismic events, the work is never done. Building adaptive resilience in communities exposed to seismic risk is a continuing process that, if it is not moving forward with new energy, resources, and committed action, regrettably falls back into less effective states. Understanding what factors contribute to maintaining resilience and what factors inhibit resilience in practice is essential for communities seeking to adapt their daily operations to continuing risk. Review of the 12 operational systems mobilized in response to severe earthquakes between the years 1999 and 2015 against empirical data that characterized the actual contexts of these events provides the basis for comparative reflection across the four categories of adaptation. Findings from these empirical analyses summarize characteristics of adaptation to risk in the different physical, economic, social, legal, and cultural contexts of the nine countries in which these earthquakes occurred, refining and validating the categories of adaptation in performance that had been identified in an earlier study (Comfort 1999a). This chapter returns to the set of 12 field studies classified by type of adaptation and explores the threshold points of change under different conditions that lead to an increase in resilience for communities at risk in some cases or, conversely, conditions that lead to a decline in resilience in others. Hazards researchers assert that systematic inquiry into response and recovery operations following actual disasters reveals insights and findings from these complex events that increase understanding of human decision making

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under conditions under uncertainty. The characteristics of seismic hazards, given the long geological time span between events and the severe consequences for communities that experience earthquakes, represent a unique challenge that requires a long-­term view and a systems perspective to increase resilience for communities exposed to continuing risk. For example, the Learning from Earthquakes (LFE) Program managed by the Earthquake Engineering Research Institute (EERI), with headquarters in Oakland, California, has received long-­standing support from the US National Science Foundation to conduct reconnaissance studies of major earthquakes, both in the United States and around the world. The LFE program is supplemented by in-­kind support from national engineering firms and universities that send engineers and researchers from other disciplines to participate in field studies of actual seismic events. While earthquake reconnaissance studies were initially motivated by engineers seeking to determine how and why buildings fail during severe seismic shaking, the reconnaissance teams are interdisciplinary in their composition and include seismologists, geotechnical engineers, and social scientists as well. These studies have been immensely valuable in documenting the characteristics of building failure, disruption of lifeline systems, and emergency response operations in specific seismic events.1 The larger question of whether communities that experienced major earthquakes actually learned from these events and were able to translate those lessons into decisions and actions that reduced seismic risk in subsequent events has largely fallen outside the scope of the LFE reconnaissance studies of specific earthquakes. With a small-­N comparative study of 12 earthquakes over a period of 16 years in nine countries, this analysis offers preliminary findings regarding longitudinal changes in the design, implementation, and practice of information communications and technology (ICT) that shape organizational performance in actual field environments. Changes in technical infrastructure may enhance or inhibit the flow of information through the complex adaptive systems of response and recovery operations that emerged in different cultural, political, engineered, and socioeconomic contexts. This analysis, fortuitously, is facilitated by the occurrence of three pairs of earthquakes occurring in roughly the same geographic areas in different national contexts—Turkey, Indonesia, and China—within the short span of 16 years. Also included in the study are two earthquakes that occurred less than 16 years after earlier seismic events in their respective countries. The 2001 Gujarat, India, earthquake followed the 1993 Maharashtra, India, earthquake by less than eight years, and the 2011 Tohoku, Japan, earthquake, tsunami, and nuclear breach followed the 1995 Hanshin-­Awaji, Japan, earthquake by 16 years. Further, the 2005 Pakistan earthquake was followed by the 2010 Pakistan floods, a different type of disaster, but one that severely tested changes that had been made to the national disaster response system of Pakistan, less

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than five years after the 2005 earthquake devastated the cities of Muzaraffabad and Balakot and neighboring villages in the northern provinces. Given the relatively brief periods of time intervening between these subsets of events, it is instructive to consider whether the 12 field studies included in this analysis constitute a sufficient longitudinal record to allow identification of threshold points of change in the sociotechnical response systems generated by earthquakes over the period of 16 years. Continuity in Operational Systems As noted in earlier chapters, the operational systems that emerge following extreme events are forged from the initial conditions that characterize their actual contexts. Once formed, these operational systems adapt, in practice, to the altered conditions of a damaged disaster environment, adjusting to new demands for services, reallocating personnel and resources to meet urgent needs, and coping with incoming personnel who may not be familiar with existing organizational constraints or resources that may be limited for immediate tasks. These are essentially management issues that may change hourly in the flux of actual response operations but continue through weeks and months as the community moves from immediate response to recovery and reconstruction following the disaster event. This process is characterized by the flow of information through an operational system both internally among different participating units and externally with other organizations and systems that provide resources, knowledge, and access to needed sources of support. The flow of information, if monitored, creates a metric that tracks the cohesion of operational systems and reveals the changing dynamics of system interactions among its internal units that shape the exchange between the whole system and external organizations and jurisdictions engaged in disaster operations. Traced carefully, information flow documents an interconnected system of systems in response and recovery operations. For example, the increased use of cell phones by residents in earthquake-­damaged communities enabled a more coherent local response to the 2013 Lushan earthquake than to the 2008 Wenchuan earthquake, five years earlier in the same province of Sichuan. Information flow tracked by cell phone use provides a measure of adaptation observed in the whole system’s performance and captures the degree to which a system under stress can effectively adjust its internal performance to adapt more appropriately to external demands, resources, requirements, and shortfalls. Developing the capacity for organizational adaptation under stress is central to the ongoing process of building community resilience to hazards like seismic risk.

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EXTERNAL/INTERNAL INDEXES

Identifying the threshold point in an operational system at which demands for assistance from external organizations shift to managing internal collaboration among units within the system to accept and allocate incoming aid effectively represents a major step toward building resilience for communities exposed to risk. In an extreme event, a community experiencing severe damage necessarily requests outside assistance. Yet that same damaged community needs to function sufficiently well to manage incoming assistance—in resources, advanced knowledge, skills, and personnel—as it is delivered in a disaster-­ degraded operating environment. Making this shift from dependence on external resources to managing effectively an enlarged operational system to meet immediate demands under altered conditions, and finally returning the emergency operations system to daily management tasks and recovery functions at a more complex level of interaction requires dynamic adaptation and coherent management strategies. Such strategies allow the operational system to adjust its internal capacity to accommodate new needs, diverse personnel, and varied resources over time, while maintaining coherence of the whole system. This internal process of adaptation in its operational system constitutes a critical transition that enables the damaged community to move from response to recovery to resilience against future hazards. The inability to make that transition, as observed in the case of Nepal, marks a retreat from resilience. In April 2018, the $4 billion in international assistance pledged to Nepal by UN member nations in June 2015 had still not been effectively transmitted and allocated to reconstruction activities (Himalayan Times, March 30, 2018), underscoring the challenges of disaster recovery in developing nations, despite a credible initial response. The flexibility required for rapid adaptation to changing conditions depends on creating a balance between the exercise of legal authority and the organizational capacity to act in degraded disaster environments. The content analysis of the organizational response systems reported in chapters 5, 6, 7, and 8 presented distributions of organizations participating in response operations classified by jurisdictional authority and by funding sector. This initial classification was used to identify the frequency of interactions among different types of organizations, that is, whether public organizations interacted primarily with other public organizations or with private and nonprofit organizations as well, and to what extent. This frequency count of interactions among types of organizations serves as an empirical basis for assessing the coherence of the system, that is, its capacity to function as an integrated system to engage its internal units constructively with external sources of resources and support. This inquiry identifies points of strength as well as

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weakness within an operational system that may forecast likely performance in future extreme events. One measure to assess the changing balance in organizational interactions under stress is the External/Internal (E/I) index, developed by Krackhardt and Stern (1988). The E/I index measures the extent to which a system’s performance can be characterized by in-­group ties versus out-­group ties. This characterization reveals the evolving trajectory of the whole operational system over time and space in a specific action arena. The formula is the difference between external ties and internal ties, divided by the number of total ties [E/I index = (E-­I) ⁄(E + I)], described in detail in chapter 3, under “Analytical Methods.” Important for this analysis, a complex system can be characterized by different levels of internal organization that allow the assessment of interaction between levels within the system for a more detailed analysis of its performance in interaction with organizations external to the system. Using data from the content analysis of daily newspapers for three weeks following each earthquake, interactions between organizations were identified by jurisdiction and funding sector (public, nonprofit, private) for each of the 12 earthquake response systems. These distributions were used as graduated systems of classification for determining which interactions were external and which internal in assessing the performance of the whole system. The order of jurisdictions represents a vertical classification of organizations denoting levels of public authority in decision processes within the operational systems, whereas the order of funding sectors is essentially a horizontal classification of collaboration across types of organizations with different economic and social functions. To evaluate the degree of coherence within the whole system, this analysis explores the balance between the exercise of authority among different legal and administrative units participating in the system and the extent of collaboration among organizations with different economic and social functions. The two types of distributions of interactions were reformatted into square matrixes, that is, matrixes with the same number of rows and columns, for each earthquake operational system. The square matrixes constructed for the 12 earthquake response systems provided rough profiles of the interacting sets of organizations as operational systems evolving over the three-­week period of response actions and the transition to recovery. These square matrixes were symmetrized to identify the number of interactions among the different types of organizational units by jurisdiction and by funding sector. Using the igraph program in R, edgelists (lists of ties among organizations) were created that included both funding sector and jurisdictional attributes to avoid overcounting. Using these edgelists, E/I indexes were calculated, using the igraph program in R and the formula cited above, for both jurisdictional and funding sector performance for each of the 12 earthquake systems.

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The jurisdictional and funding sector classifications of interacting ties capture different aspects of organizational performance within the larger operational response system. Since each matrix represents a specific empirical profile of the set of disaster operations that emerged following that earthquake, the matrixes offer insight into the functions and performance of the actual response systems, given the limitations of time and resources in each case. While it is acknowledged that organizational matrixes created from a content analysis of local newspaper reports are likely incomplete, they nonetheless represent an empirical assessment of disaster operations by jurisdiction and funding sector for each earthquake system based on local sources and validated through expert interviews with practicing managers in on-­site field studies. Throughout this analysis of 12 earthquake response systems, two questions guided the research. They are as follows: 1. What structures of sociotechnical design either facilitate or constrain the flow of information through a complex adaptive system of operations to anticipate and respond to varying degrees of risk? 2. What processes of information flow either enhance or inhibit the performance of a given complex adaptive system in practice? The data show that change occurs in performance for each operational response system, but this evolution is not chronological. It depends on the capacity of the emerging response system to create a viable balance between seeking assistance from external sources and accepting the incoming resources, while readjusting its internal organizational performance to manage the added, often newly demanding tasks effectively. This changing balance can be estimated by calculating the ratio of external to internal interactions within the organizations identified as participating in the system of response operations that emerged following each extreme event (Krackhardt and Stern 1988). This ratio represents a measure of the coherence of the operating system, or the extent to which it has achieved sufficient integration to function effectively in an altered disaster environment. Calculating the E/I indexes for each response system reveals whether key parameters for the evolution of response systems identified within the four classes of adaptation have changed in comparison to those identified between the four classes, 1999–2015. Importantly, the indexes also reveal whether a consistent set of parameters that facilitates adaptation to seismic risk can be identified over this 16-­year period (George and Bennett 2005; Bennett and Checkel 2015). The E/I analysis explores to what degree, in what direction, and under what conditions adaptation to risk conditions occurs, and the likely consequences for the affected communities. Based on these parameters, it is possible to explore dynamic models of adaptation to global seismic risk, based

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on systems thinking, in contrast to previous static plans for disaster management implemented in each separate society exposed to risk. Toward an Auto-­adaptive System in Managing Seismic Risk None of the 12 earthquakes under study met all the characteristics proposed for auto-­adaptive systems, although the 2013 Lushan, China, earthquake appeared to be moving in that direction. In contrast to prior assumptions regarding adaptive systems, the Lushan response system emerged in a decision-­ making framework that was formally centralized, but, in practice, allowed the transmission of information through multiple channels and formats. The question is whether the flexibility exhibited among the different scales of operation in the Lushan earthquake occurred by chance, or whether it reflected a substantially different pattern of interaction among the participating actors that led to more adaptive behavior of multiple participants in practice. The 2013 Lushan, China, earthquake generated a response system that appears sufficiently distinct in its pattern of interaction both between external actors and the operational system and among actors within the system to warrant characterization as a system moving toward auto-­adaptation in the context of seismic risk. Table 9.1 presents the E/I indexes by funding sector and jurisdiction for the 2013 Lushan County, China, earthquake response system. Like all other earthquake response systems, the first level of interaction for both funding sector and jurisdiction is heavily dependent on external sources, funding sector, E/I = 0.86; jurisdictional, E/I = 0.77. Yet, the next level of interaction by funding sector shifts to an internal balance, E/I = −0.27. The internal ratio increases among the five types of funding sectors, distinctive to China, until a full system of internal connections is reached, E/I = −1.00. A similar pattern appears in moving across the five jurisdictions, as the E/I value at the county level is heavily external, E/I = 0.77. The E/I ratio drops to 0.36 as municipal organizations are added but shifts significantly to an internal balance of −0.23 at the provincial level. When national organizations are included, the E/I ratio is predominantly internal, at −0.90, and the full system includes international organizations at −1.00. This pattern of performance demonstrates significant strength within the system to distinguish the Lushan response system from the other 11 response systems included in this study. Yet these findings must be interpreted with caution. The reported interactions are taken from Chinese electronic news sources that likely favor the Central Government’s interpretation of events. Even though the data are drawn from many sources and the articles reported were checked for duplications, it is acknowledged that the articles may be not be fully independent reports but drawn

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External/Internal Index for Earthquake Response System Moving toward Auto-­adaptation

TABLE 9.1.

Lushan, China, Earthquake, April 20, 2013, Mw = 6.6 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Ties Ties Private Private + nonprofit Private + nonprofit + state-­owned Private + nonprof. + state-­owned + publ. institutions Priv. + nonprof. + state-­owned + publ. inst. + public Overall E-­I (rescaled)

19 346 454 537 1,033 512

249 198 192 226 0 521

Total Ties

E/I Index

268 544 646 763 1,033 1,033

0.86 −0.27 −0.41 −0.41 −1.00 0.01

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Ties Ties County County + municipal County + municipal + provincial County + municipal + provincial + national County + municipal + provincial + nat’l + internat’l Overall E-­I (rescaled)

11 125 490 980 1,033 500

86 268 308 49 0 533

Total Ties

E/I Index

97 393 798 1,029 1,033 1,033

0.77 0.36 −0.23 −0.90 −1.00 0.03

from government sources. The full list of sources for these articles is included in appendix II. To check the reliability of the findings presented in table 9.1 against possible chance occurrence, the observed E/I values were compared to a set of E/I values generated by conducting a set of random permutations. The set used the same number of nodes, rows and columns as the observed matrix with empirical attribute data, but with the links, or ties, among the nodes randomly distributed (Borgatti et al. 2013; Krackhardt and Stern 1988). This set of random permutations was replicated 5,000 times, creating new E/I indexes with each permutation. The randomly created set of E/I indexes formed a distribution that had the same number of rows, columns, and nodes as the observed E/I indexes cited in table 9.1. An average E/I index was calculated from the distribution of random permutations to compare the results against the observed E/I index for the response system. The results, shown in table 9.2, indicate that the difference between observed E/I indexes and E/I indexes obtained by random permutation for both funding sector and jurisdiction was significant at the 0.00 level, indicating that the observed results did not occur by chance.

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TABLE 9.2. Comparison of Observed E/I Index Values with Permuted E/I Index Values for Lushan Earthquake Response System Moving toward Auto-­adaptation

Observed E/I Indexes Earthquake System Lushan, 2013

Average E/I Index, Permutations

Significance (P-­Value)

Sector

Jurisdiction

Sector

Jurisdiction

Sector

Jurisdiction

0.01

0.03

0.54

0.43

0.00

0.00

Again, the findings show a near balance between external and internal connections in both sector and jurisdictional categories for the observed E/I values, but it also affirms the finding that the observed values did not occur by chance. The marked shift in performance of the response system mobilized following the 2013 Lushan earthquake from that mobilized following the 2008 Wenchuan earthquake indicates a distinct change in the organizational structure for managing disaster operations in China in less than five years. Although the Lushan earthquake was less severe, Mw = 6.6, in comparison to the Wenchuan earthquake, Mw = 7.9, it occurred in the same province, Sichuan, and many of the same organizations were mobilized in response. The significant change in operational conditions appeared to be wider and more immediate access to information among residents of the area, as cell phone use in the province had dramatically increased during this short time. Further, the local county government officials reported significant investment in planning and preparedness activities over the five years following the 2008 Wenchuan earthquake (Personal communication, Lushan County, June 29, 2015). While the local county and municipal organizations still relied on external actors to access resources and support in response to this event, the provincial level shifted the operations to internal capacity, E/I = −0.26, and the national level showed very strong capacity, E/I = −0.90. These data are not conclusive but indicate a change in direction toward a more self-­organizing, auto-­adaptive capacity of the community to manage risk. The interesting question is what constraints within the Lushan system inhibited its movement toward a fully self-­organizing, adaptive system? Gaps in Integration: Operative Adaptive Systems The subset of response systems classified as operative adaptive systems demonstrated a substantial commitment to seismic risk reduction before the respective earthquakes occurred, as well as modest capacity to engage other organizations and jurisdictions in collective response operations. Yet there were gaps in integration of performance among both jurisdictional and funding sector transactions. None of the four systems attained sustainable levels of

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risk management over time, but three of the four systems—Duzce, Padang, and Tohoku—showed evidence of change in behavioral patterns from earlier experiences with destructive earthquakes. Operational performance in the November 12, 1999, Duzce, Turkey, and 2009 Padang, Indonesia, response systems improved in coherence from earlier performances in the August 17, 1999, Marmara, Turkey (Comfort and Sungu, 2001a, b) and 2004 Sumatra, Indonesia (Comfort 2007a), response systems respectively. In contrast, performance in the Tohoku response system in 2011 declined in observed coherence from that reported following the 1995 Hanshin earthquake in Japan (Comfort 1999a). The search for a model of collective learning to reduce earthquake losses in risk-­prone areas of the world continues, and the E/I indexes offer a useful measure of how the process develops. Table 9.3 presents the E/I indexes for the four systems classified as operative adaptive systems and allows comparison of system performance within the class of adaptation. Performance in response operations following the November 12, 1999, Duzce, Turkey, earthquake noticeably improved a scant three months following the much larger, more devastating August 17, 1999, Marmara, Turkey, earthquake. Several factors contributed to the more rapid response in the Duzce system. First, Duzce is located near the eastern border of the Marmara region, 117 kilometers east of Kocaeli, the epicenter of the August 17, 1999, earthquake. Given this proximity to the region affected by the recent Marmara earthquake, residents were keenly aware of seismic risk. Secondly, external resources were readily available, as a battalion of the Turkish Army was stationed close to Duzce. Other organizations that had mobilized following the Marmara earthquake were still on alert. Turk Telecom, a private company, quickly contributed extra telecommunications equipment to facilitate rapid information exchange across jurisdictions and between national agencies in Ankara and emergency response organizations in the disaster-­damaged field (Comfort 1999b). The E/I indexes for Duzce at jurisdictional levels showed the shift from dependence on external resources at the municipal level, E/I = 0.73, to a modest internal ratio, E/I = −0.06 when provincial interactions enter the system, but the system’s internal capacity jumped to E/I = −0.63 when state (central administration) organizations entered the system. Fully internal operations registered only when international organizations entered response operations. A similar shift in performance between provincial and national levels of jurisdiction occurred in the Indonesian response system between the 2004 Sumatran earthquake and tsunami and the 2009 Padang earthquake, a period of only five years. After the devastating 2004 Sumatran earthquake and tsunami, the Indonesian government, supported by a distinct cadre of in­ ternational organizations organized through the United Nations Office for the Coordination of Humanitarian Assistance (UN OCHA), made a strong

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TABLE 9.3.

External/Internal Indexes for Operative Adaptive Earthquake Response Systems

Duzce, Turkey, Earthquake, November 12, 1999, Mw = 7.2 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total E/I Ties Ties Ties Index Political Political + private Political + private + nonprofit Political + private + nonprofit + public Overall E-­I (rescaled)

0 3 17 324 238

3 30 79 0 86

3 33 96 324 325

1.00 0.82 0.65 −1.00 −0.47

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total E/I Ties Ties Ties Index Regional Regional + municipal Regional + municipal + provincial Regional + municipal + provincial + national Reg. + municipal + prov. + national + state/central Reg. + municipal + prov. + nat’l + state/central + international Overall E-­I (rescaled)

1 11 130 153 264 324

9 70 115 100 60 0

10 81 245 253 324 324

0.80 0.73 −0.06 −0.21 −0.63 −1.00

110

214

324

0.32

Padang, Indonesia, Earthquake, September 30, 2009, M w = 7.6 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total E/I Ties Ties Ties Index Political Political + private Political + private + nonprofit Political + private + nonprofit + public Overall E-­I (rescaled)

0 0 13 209 166

1 18 27 0 43

1 18 40 209 209

1.00 1.00 0.35 −1.00 −0.59

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total E/I Ties Ties Ties Index Local Local + district Local + district + regency Local + district + regency + municipal Local + dist. + regency + municipal + provincial Local + dist. + regency + municipal + prov. + Jakarta Loc.+ dist.+ reg.+ municipal + prov.+ Jakarta + nat’l Loc.+ dist.+ reg.+ municipal + prov.+ Jakarta + nat’l + int’l Overall E-­I (rescaled)

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0 1 2 2 15 15 99 209 90

10 10 13 38 52 56 71 0 119

10 11 15 40 67 71 170 209 209

1.00 0.82 0.73 0.90 0.55 0.58 −0.16 −1.00 0.14

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TABLE 9.3.

(continued)

Tohoku Earthquake and Tsunami, March 11, 2011, Mw = 9.0 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total E/I Ties Ties Ties Index Political party Pol. party + private Pol. party + private + nonprofit Pol. party + private + nonprofit + public Overall E-­I (rescaled)

26 44 72 496 360

32 103 118 0 136

58 147 190 496 496

0.10 0.40 0.24 −1.00 −0.45

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total E/I Ties Ties Ties Index Local Local + municipal Local + municipal + regional Local + municipal + regional + prefectural Local + municipal + reg. + prefec.+ national Local + municipal + reg. + prefec. + nat’l + int’l Overall E-­I (rescaled)

0 15 22 75 394 496 246

7 48 75 128 93 0 250

7 63 97 203 487 496 496

1.00 0.52 0.55 0.26 −0.62 −1.00 0.01

Nepal Earthquakes, April 25, May 12, 2015, Mw = 7.8 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total E/I Ties Ties Ties Index Private Private + nonprofit Private + nonprofit + public Overall E-­I (rescaled)

1 18 201 154

21 41 0 47

22 59 201 201

0.91 0.39 −1.00 −0.53

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total E/I Ties Ties Ties Index Subdistrict Subdistrict + district Subdistrict + district + national Subdistrict + district + national + international Overall E-­I (rescaled)

0 5 113 201 106

3 45 55 0 95

3 50 168 201 201

1.00 0.80 −0.35 −1.00 −0.05

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commitment to develop disaster preparedness for the Indonesian archipelago that is exposed to a wide range of hazards. Caught unaware by the 2004 tsunami, the Indonesian government made a determined investment in disaster preparedness for the risk-­prone nation. Six cities exposed to major risk were selected to be demonstration sites for emergency preparedness, one of which was Padang, a city on the west coast of Sumatra, exposed to high seismic risk. The city, with support from the national government, engaged in a program of preparedness activities, primarily focused on tsunami awareness. Interestingly, the Padang earthquake of September 30, 2009, Mw= 7.6, occurred in the Mentawai Sea, directly across from the city of Padang, but at a depth of 58 kilometers. Consequently, the earthquake generated only a very minor tsunami wave but caused heavy destruction to the city’s built infrastructure, including 11 new tsunami shelters (EERI 2009). After action reports documented an increase in awareness of seismic risk, with the major shift in interactions occurring from the provincial (E/I = 0.58) to the national level, (E/I = −0.16). This shift occurred at the same jurisdictional threshold, provincial to national, as in the 2004 Sumatran earthquake, where the index measured high dependence on external sources at the provincial level, (E/I = 0.73), advanced to slightly positive evidence of internal management at the national or central administrative level (E/I = −0.03) (see table 9.7 and discussion below). The difference in performance is shown also in the change in the overall E/I indexes between the two response systems in the same nation. The rescaled E/I index for the jurisdictional network in the Sumatran response system dropped from E/I = 0.21 (table 9.7) indicating dependence on external resources to E/I = 0.14 (table 9.3) in the Padang system, still reliant on external sources but indicating a noticeable increase in internal performance. Ironically, the reverse pattern occurred in Japan, when performance of the whole disaster operations system stalled under the extraordinary burden of cumulative demands from the March 11, 2011, earthquake, tsunami, and nuclear breach. The resulting decline in overall performance of response operations in Japan following the 2011 events contrasted with the more coherent performance of the response system mobilized following the January 17, 1995, Hanshin earthquake (Comfort 1999a). The break in performance for the 2011 response system appeared to occur most strongly in the shift from the prefectural level, where the external links still dominated internal links, E/I = 0.26, to the national level, E/I = −0.62 (table 9.3, Tohoku). Only when national-­ level agencies entered the system did the ratio of external to internal links shift to demonstrate substantial internal capacity to manage this event. Although the ratio shifted from external to internal with the introduction of national resources, the response system did not reach full internal capacity, E/I = −1.0, until the international agencies entered the system. Clearly, the earthquake at

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Comparison of Observed E/I Values with Permuted E/I Values for Operative Adaptive Systems, Significance (P) Values

TABLE 9.4.

Observed E/I Indexes

Duzce, 1999 Padang, 2009 Tohoku, 2011 Nepal, 2015

Average E/I Index in Permutations

Significance (P-­Value)

Sector

Jurisdiction

Sector

Jurisdiction

Sector

Jurisdiction

−0.47 −0.59 −0.45 −0.53

0.32 0.14 0.01 −0.05

−0.50 −0.19 0.01 −0.15

0.46 0.40 0.38 0.25

0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

Mw = 9.0 was more severe than the event in Kobe at Mw = 7.2. Nonetheless, the cascading disruption triggered by the earthquake generated massive tsunami waves that, in turn, flooded the Daiichi nuclear reactor in Fukushima and created pathways of destruction that were simply beyond the capacity of Japan’s advanced disaster management plans, policies, and agencies to manage. The sobering finding from this analysis is that even Japan, arguably well prepared for major earthquakes, had not anticipated the full destruction of powerful tsunami waves in the design and construction of technical infrastructure on its vulnerable coastlines. In contrast to Japan, Nepal’s capacity to mobilize a response system following a major earthquake, Mw = 7.8, was greater than anticipated for the size, scale, and resources available in this small country. Not surprisingly, the shift in the ratio of external to internal connections among agencies occurred in moving from the district level of operations, E/I = 0.80, to the national level, E/I = −0.35. A second major shift in the ratio of connections between external and internal organizations occurred in moving from the national level to the international level at E/I = −1.0. International organizations played an immediate role in the initial response operations, but lack of internal capacity in Nepal to manage these interactions led to prolonged and detrimental conflict with its immediate neighbor, India, as the country moved into the more contentious and difficult recovery and reconstruction process. A set of permutations was also run, using the same number of nodes and links as the observed E/I values reported in table 9.3 to assess whether the observed E/I values could have occurred by chance. The results are reported in table 9.4. For all four response systems, the difference between the observed E/I values and the permuted E/I values is statistically significant at the 0.00 level, indicating that the observed E/I values did not occur by chance. Interestingly, the critical factor that characterizes these four earthquake systems is not time, as chronologically the earthquakes range in occurrence from 1999, the first year of study, to 2015, the last year included in the study.

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Nor do the earthquake systems cluster in terms of geographic space; all four are broadly located in Asia, but none are adjacent or geographically similar. Importantly, each earthquake system is characterized by multiple scales of operation that need to be coordinated for effective response. Notably, the largest gaps are in the midlevel jurisdictions that link the national or state jurisdictions to the local district or municipal jurisdictions, validating the importance of mesolevel interactions in complex adaptive systems. The energy that drives each system—or fails to do so—appears to be the information flow both within and between the scales of operation. In all cases, the information flow appears constrained by both time and technical infrastructure for transmission. The question is whether altering the technical infrastructure for information transmission would change the timing and validity of information flowing through the different scales of operation in each system to increase resilient performance. Missing Links: Emergent Adaptive Systems: Marmara, Turkey, 1999; Chi Chi, Taiwan, 1999; Kashmir, Pakistan, 2005; and Wenchuan, China, 2008 The subset of earthquake response systems classified as emergent adaptive revealed structural changes in mobilizing response that reflected varying capacities to mobilize response operations from the national or state level, yet with little to no capacity or engagement from local levels of jurisdiction. The response systems in this category followed severe earthquakes in four Middle Eastern/Asian countries: Marmara, Turkey, August 17, 1999; Chi Chi, Taiwan, September 21, 1999; Kashmir, Pakistan, October 8, 2005; and Wenchuan, China, May 12, 2008. The E/I indexes for these response systems are presented in table 9.5. Reviewing the E/I indexes reported by jurisdiction for the 1999 Marmara, Turkey, earthquake shown in table 9.5, findings show that submunicipal jurisdictions were largely dependent on external resources, despite planning efforts of the National Earthquake Research Center located in Ankara, Turkey’s capital city. During the decade of the 1990s, Turkey had committed substantial resources and effort to develop a national disaster plan following earlier earthquakes: Erzincan, March 13, 1992; Dinar, October 1, 1995; and Adana-­Ceyhan, June 27, 1998 (Kandilli Observatory 1999). Given the nation’s high exposure to seismic risk,2 Turkey’s research community—including geologists, seismologists, earthquake engineers, and urban planners—was clearly aware of the earthquake hazard. The National Disaster Law 7269, initially implemented in 1959, was still in effect. The Marmara response system generated modest participation from nonprofit organizations in the funding sector, shown in the decline in dependence on external organizations to 0.54 as they enter the system (table 9.5, Mar-

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mara). Yet the system shifted to a full functionality among funding sector organizations, −1.00, only with the inclusion of public organizations. Performance among jurisdictional levels showed dependence on external resources at all substate levels, including national nonprofit and private organizations. The threshold ratio of external to internal interactions by jurisdiction shifted to an internal balance of −0.50 only when the central (state) government exercised its authority and mobilized resources. Further, the full system gained coherence only through interactions with international agencies. The overall rescaled E/I index for the whole network measured by jurisdictional interactions was 0.49, indicating a high proportion of external organizations participating in response operations during the first three weeks following this event. This high ratio of external to internal participation carried over into the recovery process that involved substantial funding from international sources, such as the World Bank (1999). Despite substantial investment in planning and high awareness of seismic risk, the actual earthquake caught the nation of Turkey by surprise and revealed the deep differences between planning and capacity to act in real time. The response system that emerged following the Chi Chi, Taiwan, earthquake of September 21, 1999, represents an unusual case, given the political constraints under which Taiwan operates. Officially still a province of China, Taiwan nonetheless operates as an autonomous nation. Yet not recognized as an independent member of the United Nations (UN), Taiwan was not able to request formal assistance from the UN through its Office for the Coordination of Humanitarian Assistance (OCHA). United Nations member states, such as the United States and Japan, contributed assistance to Taiwan but had to do so largely through nonprofit organizations that could function as independent entities directly with the government of Taiwan. Consequently, the performance of the response system that emerged following the earthquake in Taiwan was largely national; that is, response functions were performed by municipal and county organizations operating under the authority of executive and legislative bodies of the island serving in a national role. After the earthquake, the former provincial level of government was eliminated as an unnecessary and redundant layer of bureaucratic control. Given the legal administrative structure, the balance of external to internal relations in the Taiwanese response system revealed high dependence on external organizations at the municipal level, E/I value of 0.95; a substantial drop in this proportion at the county level to 0.04; and a nearly full reversal to −0.93 when national (that is, Taiwanese) organizations joined the system. Only one international public organization is reported as participating in the system, with the full system at −1.00. The overall rescaled index for the entire operational system by funding sector showed modest internal capacity, E/I index value, −0.27, but registered E/I = 0.11, by jurisdictions, indicating an overall ratio of dependence on external organizations, although relatively low.

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TABLE 9.5.

External/Internal Indexes for Emergent Adaptive Earthquake Response Systems

Marmara, Turkey, Earthquake, August 17, 1999, Mw = 7.4 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Political Political + private Political + private + nonprofit Political + private + nonprofit + public Overall E-­I (rescaled)

0 4 55 701 504

4 105 183 0 197

4 109 238 701 701

E/I Index 1.00 0.93 0.54 −1.00 −0.44

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties District District + regional District + regional + municipal District + regional + municipal + provincial District + reg. + municipal + provincial + national District + reg. + municipal + prov. + nat’l + state Dist. + reg. + municipal + prov. + nat’l + state + int’l Overall E-­I (rescaled)

10 10 72 160 240 499 701 179

62 75 124 296 268 165 0 522

72 85 196 456 508 664 701 701

E/I Index 0.72 0.76 0.27 0.30 0.06 −0.50 −1.00 0.49

Chi Chi, Taiwan, Earthquake, September 21, 1999, Ms = 7.6 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Private Private + nonprofit Private + nonprofit + public Overall E-­I (rescaled)

15 108 1,503 953

216 518 0 550

231 626 1,503 1,503

E/I Index 0.87 0.65 −1.00 −0.27

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties Municipal Municipal + county Municipal + county + national Municipal + county + national + international Overall E-­I (rescaled)

11 524 1,448 1,503 668

389 565 54 0 835

400 1,089 1,502 1,503 1,503

E/I Index 0.95 0.04 −0.93 −1.00 0.11

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TABLE 9.5.

(continued)

Pakistan Earthquake, October 8, 2005, Mw = 7.6 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Private Private + nonprofit Private + nonprofit + public Overall E-­I (rescaled)

2 49 770 507

120 251 0 263

122 300 770 770

E/I Index 0.97 0.67 −1.00 −0.32

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties Subdistrict Subdistrict + district Subdist. + district + provincial Subdist. + district + provincial + national Subdist. + district + prov. + nat’l + international Overall E-­I (rescaled)

0 38 148 447 770 329

8 128 164 244 0 441

8 166 312 691 770 770

E/I Index 1.00 0.54 0.05 −0.29 −1.00 0.15

Wenchuan, China, Earthquake, May 12, 2008, M w = 7.9 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Private Private + nonprofit Private + nonprofit + state-­owned Private + nonprof. + state-­owned + publ. institutions Priv. + nonprof. + state-­own. + publ. inst. + public Overall E-­I (rescaled)

3 35 60 110 452 266

68 77 78 123 0 186

71 112 138 233 452 452

E/I Index 0.92 0.38 0.13 0.06 −1.00 −0.18

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties County County + municipal County + municipal + provincial County + municipal + provincial + national County + municipal + provincial + nat’l + internat’l Overall E-­I (rescaled)

4 136 252 441 452 222

34 138 131 11 0 230

38 274 383 452 452 452

E/I Index 0.79 0.01 −0.32 −0.95 −1.00 0.02

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The 2005 Pakistan response system also demonstrated unique characteristics that affected the emergence of a response system following the severe earthquake in the steep, mountainous terrain of the northern provinces. As a member of the United Nations, the government of Pakistan appealed to the United Nations for assistance in this devastating event. The UN Office for Coordination of Humanitarian Assistance (OCHA) responded in its first implementation of the newly designed cluster system for organizing relief activities offered by UN member nations to a fellow UN member stricken by disaster. The UN cluster system, described briefly in chapter 7, was designed to facilitate the critical task of identifying the needs of the afflicted nation and matching donations from member UN nations to meet those needs more efficiently and appropriately. The E/I index values for jurisdictions reveal that the subdistrict level was wholly dependent on external sources, E/I = 1.0, but this dependence dropped markedly at the district level, to E/I = 0.54. The balance of external to internal organizations shifted further from 0.54 to 0.05, with the entry of provincial organizations into the system. At the national level, the E/I index moved toward internal coherence (E/I value = −0.29), but the threshold shift in the Pakistan system occurred with the entry of international organizations into the system, producing an E/I value of −1.00. The overall index for the system by jurisdiction, E/I = 0.15, indicated that the jurisdictional response networks were still noticeably dependent on external organizations. The interactions among funding sector organizations showed limited participation by private sector organizations, modest participation by nonprofit organizations, and dominant participation by public organizations. The overall E/I index by funding sector showed modest internal capacity for the country with an E/I index of −0.32. International organizations clearly played a significant role in mobilizing response operations for the Pakistan earthquake, transforming the emergent response system into a more coherent, operational system in an extremely difficult, disaster-­degraded environment. The 2008 Wenchuan response operations illustrates the emergence of a response system under very difficult operational conditions, but with a sharp distinction from earlier efforts to manage disaster response in China. As noted in table 9.5, the internal ties for the funding sector were minimal, with a positive E/I value at 0.92 for private organizations. The balance shifted to 0.38 when nonprofit organizations joined the operational system, indicating stronger capacity within the system, and shifted still further when state-­owned and public institutions were included. The threshold change in the index occurred with the entry of public organizations into the response system, shifting from 0.06 to −1.00, for a system inclusive of all funding sectors. Yet the overall E/I index for funding sector was −0.18, showing only modest internal capacity. The indexes for transition in the Wenchuan system varied by jurisdictional level, with the county organizations largely dependent on external resources,

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TABLE 9.6. Comparison of Observed E/I Values with Permuted E/I Values for Emergent Adaptive Systems, Significance (P) Values

Observed E/I Indexes

Average E/I Index, Permutations

Significance (P-­Value)

Earthquake System

Sector

Jurisdiction

Sector

Jurisdiction

Sector

Jurisdiction

Marmara, 1999 Chi Chi, 1999 Pakistan, 2005 Wenchuan, 2008

−0.44 −0.27 −0.32 −0.18

0.49 0.11 0.15 0.02

0.06 0.25 0.00 0.39

0.62 0.32 0.47 0.44

0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

as shown by the E/I value of 0.79. Adding municipal organizations to the calculation altered the index substantially, as the E/I external value dropped to 0.01. Including provincial organizations shifted the E/I balance to internal interactions, as the E/I value changed to −0.32, and including national organizations further changed the ratio to an almost fully internal system, with an E/I value at −0.95. Modest inclusion of international organizations completed the composition of the response system at −1.0. The overall E-­I index, rescaled for the whole Wenchuan jurisdictional network, was almost balanced between internal and external organizations, with an E/I index value of 0.02.3 The four response systems included in the emergent adaptive systems category showed a modest but limited capacity for adaptation to increased demands from the respective earthquake-­damaged communities, but in each system, the shift to internal management of disaster operations came most effectively when national organizations entered the system. In the Marmara and Pakistan cases, international organizations also played a major role. Interestingly, the cases of Chi Chi, Taiwan, and Wenchuan, China, revealed different constraints and capacities of disaster management in China. In the Chi Chi case, absence of international organizations explicitly involved through the UN OCHA system proved only partially offset by international organizations operating through linkages to local Taiwanese nonprofit organizations. In contrast, the presence of international organizations, although not strong, was evident in the Wenchuan case. Changes introduced into China’s disaster management system following the 2008 Wenchuan earthquake were tested again in the 2013 Lushan County earthquake, analyzed in the class of response systems moving toward auto-­adaptation. Table 9.6 reports differences between observed E/I indexes and those obtained by permutation for the four earthquake response systems included in the emergent adaptive category. The differences between the observed E/I indexes and those obtained by permutation, again, are significant, by both funding sector and jurisdiction, for all four response systems in this category.

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The p-­values for all four systems indicate that the observed E/I indexes could not have occurred by chance. Initial Conditions, Nonadaptive Response Systems: Gujarat, India, 2001; Sumatra, Indonesia, 2004; Haïti, 2010 Three cases were included in the category of nonadaptive response systems: the 2001 Gujarat, India, earthquake; the 2004 Sumatran earthquake and tsunami, Indonesia; and 2010 Haïti earthquake. Table 9.7 presents the E/I indexes by funding sector and jurisdiction for the response systems, reporting the frequency of internal ties among units within each system in comparison to external ties with organizations outside the system. The indexes present the data by graduated inclusion of categories into the whole operating system to reveal where the breaks in coherence are most evident. For each set of organizational interactions measured by the number of ties, an overall E/I value is calculated for the whole system, which shows differences in strength and weakness in the exercise of jurisdictional authority or collaborative capacity among funding sectors for the whole system. The differences in the exercise of jurisdictional authority and funding sector capacity for action indicate the degree of integration of these critical functions in the overall response system, revealing its capacity for adaptation to external conditions, as well as the limits. Response systems emerged following each of these three seismic events in Gujarat, India, in Sumatra, Indonesia, and in Haïti, but the systems reflected communities that had little awareness of seismic risk, less investment in preparedness for major destruction from earthquakes, and almost no local capacity to manage a severe disruption of community functions. Consequently, each of these three communities was almost wholly dependent on external assistance in the first days following the respective earthquakes and, in Indonesia, the ensuing tsunami. Over the three-­week period following each extreme event, organizations from all funding sectors and jurisdictions were incorporated into a whole system functioning as the responsible entity for managing response activities and transitioning to recovery. Yet the threshold point for transition came at different jurisdictional levels for each response system. In Gujarat, the dominant proportion of interactions at the lowest jurisdictional level of operations, district, was with external organizations, E/I value = 0.85. This proportion dropped to E/I = 0.44, as state-­level organizations joined response and recovery operations. The threshold shifted substantially toward an internally organized system, E/I = −0.57, when national forces arrived. The final change came with the integration of international organizations into the system, with an E/I index at −1.0, registering the full set of 226

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TABLE 9.7.

External/Internal (E/I) Indexes for Nonadaptive Systems

Gujarat, India, Earthquake, January 26, 2001, Mw = 7.7 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Private Private + nonprofit Private + nonprofit + public Overall E-­I (rescaled)

1 10 226 147

26 74 0 79

27 84 226 226

E/I Index 0.93 0.76 −1.00 −0.30

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties District District + state District + state + national District + state + national + international Overall E-­I (rescaled)

2 24 162 226 124

25 61 45 0 102

27 85 207 226 226

E/I Index 0.85 0.44 −0.57 −1.00 −0.10

Sumatran Earthquake, December 26, 2004, M w = 9.2 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Political Political + private Political + private + nonprofit Political + private + nonprofit + public Overall E-­I (rescaled)

1 28 93 497 357

9 76 96 0 140

10 104 189 497 497

E/I Index 0.80 0.46 0.02 −1.00 −0.44

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties Local Local + regency Local + regency + municipal Local + regency + municipal + provincial Local + regency + municipal + prov. + spec. region Local + reg. + municipal + prov. + spec. reg. + national Loc. + reg. + municipal + prov. + spec. reg. + nat’l + int’l Overall E-­I (rescaled)

0 1 3 17 38 210 497 197

16 28 63 107 112 196 0 300

16 29 66 124 150 406 497 497

E/I Index 1.00 0.93 0.91 0.73 0.49 −0.03 −1.00 0.21

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TABLE 9.7.

(continued)

Haïti Earthquake, January 12, 2010, M w = 7.0 Cumulative Assessment of Organizational Interactions in Response System by Funding Sector Internal External Total Ties Ties Ties Political Political + private Political + private + nonprofit Political + private + nonprofit + public Overall E-­I (rescaled)

0 1 10 138 122

1 8 15 0 16

1 9 25 138 138

E/I Index 1.00 0.78 0.20 −1.00 −0.77

Cumulative Assessment of Organizational Interactions in Response System by Jurisdiction Internal External Total Ties Ties Ties Municipal Municipal + national Municipal + national + regionala Municipal + national + regional + international Overall E-­I (rescaled) a

0 0 53 138 70

1 26 59 0 68

1 26 112 138 138

E/I Index 1.00 1.00 0.05 −1.00 −0.01

Regional = nations of the Caribbean region.

interacting organizations engaged in response actions, still relatively small for the 1.59 million people affected by this earthquake. Nonprofit organizations played an important role in the Gujarat response system, as shown by the drop in the E/I index value from 0.93 to 0.76 when their participation in the response system is included. Nonetheless, public organizations dominated the response system measured by funding sector as the E/I index value tipped from 0.76, indicating a strong balance in favor of external organizations to −1.0 for internal organizations when public sector organizations, both national and international, joined the response system. These measures indicate that the Gujarat response system relied heavily on public national and international organizations and likely could not have functioned without external sources. The overall rescaled values for the Gujarat response system, by funding sector, E/I = −0.30 and by jurisdiction, E/I = −0.10, reveal that the system’s capacity to adapt was more limited among organizations from different funding sectors, but approached balance among jurisdictional sectors that included the international sector in the system. Not surprisingly, the Sumatran system emerged following the December 26, 2004, earthquake and tsunami in Indonesia as a much larger and more complex response and recovery system that affected 12 nations in the Indian

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Ocean basin. This analysis includes only the response system that emerged in Indonesia, which bore the brunt of losses in lives and property from this extraordinary event (Comfort 2007a). With little awareness or preparedness for the severe Mw = 9.2 earthquake that generated three massive tsunami waves, the subprovincial jurisdictions were almost wholly dependent on external support. Some provincial activity registered (E/I index value = 0.73), and more interactions occurred internally when organizations from the special region of Jakarta, the nation’s capital, entered response operations (E/I index value = 0.49), but the major shift occurred when the national actors entered the disaster operations system and created a virtual balance in action between internal and external organizations (E-­I index value = −0.03). Yet only when international actors were included did the system coalesce into a functioning entity with E/I index value = −1.0. The overall E/I value for the whole network assessed by jurisdictional performance was 0.21, demonstrating that the overall jurisdictional network was substantially dependent on external sources for operations. This measure contrasted with the overall E/I index for funding sector performance at −0.44 reported in table 9.8, indicating substantial capacity within the whole system that included participation of international public and nonprofit organizations. The documented dependence on external sources in jurisdictional interactions slowed the transition to reconstruction and recovery, despite major policy changes initiated by the Indonesian government (Comfort 2007a). Demonstrably the most fragile of the three systems classified as nonadaptive, the 2010 Haïti response system identified from regional Caribbean news articles, registered only 138 interactions among organizations participating in response operations over the first three weeks following the January 12, 2010, earthquake. Likely many more organizations were involved, but this regional source of news articles, Caribbean News Online (CANA), reported specifically the interactions among the regional Caribbean nations and Haïti that were often omitted from other international news accounts. Of the set of organizational interactions reported in CANA, only one verified a Haïtian municipal organization interacting with an international organization; 26 reported interactions involving organizations at the national level. Based on these reports, both municipal and national organizations in Haïti were almost fully dependent on external support, with E/I values at 1.00. The CANA reports confirmed strong participation from neighboring Caribbean island nations to support Haïti, response activities that represented a significant shift in operations toward regional support. These reported interactions registered a near balance between internal and external sources with an E/I index value of 0.05. Yet only when international public organizations engaged in response activities did the system coalesce into a functioning internal system,

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Comparison of Observed E/I Values with Permuted E/I Values for Nonadaptive Systems, Significance (P) Values

TABLE 9.8.

Observed E/I Indexes

Average E/I Index in Permutations

Earthquake System

Sector

Jurisdiction

Sector

Gujarat, 2001 Sumatra, 2004 Haïti, 2010

−0.30 −0.44 −0.77

−0.10 0.21 −0.01

−0.12 0.10 −0.13

Jurisdiction 0.29 0.41 0.13

Significance (P-­Value) Sector

Jurisdiction

0.00 0.00 0.00

0.00 0.00 0.00

E/I = −1.0. The overall rescaled E/I index value for the whole network was a near balance between internal and external organizations at −0.01, with regional Caribbean organizations counted as internal to the system, a unique context for Haïti. The actual performance of the three response systems that emerged following extreme events illustrate that, in each case, the local capacity to function was overwhelmed by the impact of a severe earthquake. In all three cases, the ability to adapt to incoming resources and personnel from external sources came late in the evolution of each response system. In Gujarat, the threshold of change emerged as national-­level organizations entered the system, and it began to coalesce at an E/I value of −0.57. In contrast, for Sumatra and Haïti, the thresholds of coherence occurred only at the international level, in a shift from −0.03, representing a slight balance for internal organizations in Indonesia in comparison to a similar shift that included a slight balance for external organizations, 0.05, in Haïti. The limited capacity for adaptation in all three cases was directly grounded in the initial conditions of lack of awareness of seismic hazards, lack of preparedness specifically for seismic risk, and lack of timely, valid information to activate community residents to engage in their own safety measures. Table 9.8 reports differences between observed E/I indexes and those obtained by permutation for the three response systems included in the nonadaptive category. The differences are statistically significant, by both funding sector and jurisdiction, for all response systems in this category, indicating that the observed E/I indexes could not have occurred by chance. These findings indicate that differences in performance between jurisdictions were significant in each earthquake system, as well as differences among public, private, and nonprofit organizations for this set of nonadaptive systems. These differences also corroborate observations that transition between jurisdictions in disaster operations is a consistent focal point at which each of the three systems lost coherence in practice.

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Conclusions Not surprisingly, the four subsets of earthquake response systems demonstrated capacity for adaptation to varying degrees, but importantly, the variance appeared not to depend on the presence of technical infrastructure alone. Nor did the variance depend on the robustness of the organizational infrastructure of planning and preparedness for a seismic event alone. Rather, the variance appeared to depend on the degree of integration of the technical infrastructure for communication into the organizational plans for seismic risk reduction. This integration of social/organizational planning with the advances of technical communications infrastructure produced a powerful vehicle for expanding communication and information exchange that creates a new pattern of building community resilience to disaster. In the nonadaptive systems—Gujarat, Sumatra, and Haïti—little planning or preparedness had been done before the earthquake, so the communities were unaware and overwhelmed when the earthquake, and in Sumatra, the ensuing tsunami, occurred. In the emergent adaptive systems—Marmara, Turkey; Chi Chi, Taiwan; Pakistan; and Wenchuan, China—some organizational planning for risk reduction had been done at the national level in each case, but these plans were not communicated well to, nor implemented in, the local jurisdictions. Nor was there a clear understanding of seismic risk communicated to the public in this set of earthquake-­affected communities. In the Marmara, Turkey, earthquake, for example, building codes were well designed by engineers, but not enforced in the actual construction of housing (Balamir 2000). Further, these organizational disaster reduction plans were not supported by a technical information infrastructure that could facilitate collective search and exchange for information, recognition of risk, and informed response actions by the community. In the operative adaptive systems subset—Duzce, Turkey; Padang, Indonesia; Tohoku, Japan; and Nepal—investments had been made in both technical and organizational planning for risk reduction, but they had largely been made separately and consequently did not produce a sustained, informed, adaptive response to seismic risk. For example, in Padang, extensive organizational planning had been done in preparation for tsunami evacuation, but the technical infrastructure for communicating timely information to the residents of the city was not well developed. When the earthquake occurred with no measureable tsunami threat, the unwarranted evacuation of the city resulted in confusion and massive disruption instead of an orderly response to the damage caused by the earthquake (EERI 2009). Only in the Lushan, China, response did the technical and organizational preparedness activities

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appear to be sufficiently coordinated to produce a collective response. Yet the response actions were not fully coherent, and there were elements of surprise in the implementation, suggesting that the response by the local residents may have been due to prior familiarity with seismic risk, given the Wenchuan earthquake in the same province, Sichuan, less than five years earlier, in 2008. The prevalence of cell phones and their active use by the residents of the affected area clearly appeared to facilitate the self-­organizing response actions of the communities. Referring to the two questions posed at the beginning of this chapter, the findings show that neither the technical infrastructure alone, nor the organizational infrastructure alone, is sufficient to stimulate the flow of information through a community to enable a coherent, timely response to severe risk. The experience of the Lushan response system suggests that a sociotechnical system—informed planning supported by a technical information infrastructure—offers an integrated approach that would enable adaptive performance in communities exposed to recurring seismic risk.

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10 The Logic of Resilience

The Design of Resilient Systems The changing contours of risk in different communities as policy makers and managers sought to confront the same type of hazard, earthquakes, initiated a continuing inquiry over decades that has focused this study. Why does the same type of hazard—earthquakes—generate such different responses and consequences in different countries, given known characteristics of the hazard? The major earthquake faults have largely been mapped; scientific understanding of seismic risk, while still incomplete, has advanced in the global community. Professional development of building codes for earthquake-­ resistant buildings has widely been accepted by international engineering associations. Yet major differences in capacity for managing the response, costs, and consequences of exposure to seismic risk continue in developed as well as developing nations. These differences have been explored in the analyses of operational response systems generated following 12 actual events from 1999 to 2015 in nine different countries throughout the chapters of this book. The larger question is whether resilient systems can be designed that enable communities with different physical, technical, organizational, and cultural characteristics to recognize, assess, and manage the risk to which they are exposed. Findings from the empirical analyses presented in chapters 5–8, as well as professional assessments from the literature on risk assessment and resilience, suggest the redesign of a framework for assessing resilience of communities exposed to hazards and calibrating investments in risk reduction to achieve sustainable resilience to hazards over time. The initial classification of operational response systems used throughout this book (see chapter 4) served as

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a preliminary means of assessing the adaptive capacity of communities to respond to the abrupt, urgent demands of earthquakes. The E/I indexes presented in chapter 9 take a further step toward measuring the degree of coherence within earthquake response systems composed of multiple actors operating at diverse locations simultaneously. Coherence in system performance emerges as a critical factor in developing functional, effective communities that prove resilient in their capacity to manage hazards. To withstand shocks, a system needs to integrate internal components that perform key functions in an altered disaster environment as it interacts simultaneously with external actors to solicit needed resources to achieve the overall system goal of maintaining continuity of operations. Throughout this analysis, the organizations that engage in disaster operations have been identified by two key characteristics: jurisdiction of legal authority and source of funding. These characteristics allow cross characterization of the same organizations by different attributes and provide a means of assessing patterns of association and interaction among organizations that affect performance in practice. Funding and jurisdictional authority are essential to build collaborative action in rapidly changing environments, but these attributes almost always require adaptation from daily, routine tasks that are specified to meet explicit standards of accountability and control. Coherence reveals the extent to which organizations with diverse characteristics of funding and jurisdictional authority are integrated within the operational system, enabling the system to adapt its performance to sudden disruptions of routine procedures and provide an effective response to the external shock of a major earthquake. Classes of Adaptation in Managing Risk The four classes of adaptation—nonadaptive, emergent adaptive, operational adaptive, and auto-­adaptive—discussed throughout this book illustrate different stages of coherence in the complex operational systems of communities seeking to build resilience to recurring hazards. In the three nonadaptive systems—Gujarat, Sumatra, and Haïti—local decision makers were largely unaware of seismic risk when the earthquakes occurred, but in each of the other nine systems, some conscious effort had been made to acknowledge the risk to which the respective communities were exposed. Yet all 12 communities experienced significant losses and disruption, some more than others. At what point does a community’s operational system fracture, or lose capacity to function under the stress of an earthquake? More important, at what point does a stricken community regain the capacity to provide basic services and support to the population it serves? The E/I index, which assesses the degree of dependence on external sources for a system’s continued operations, or

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conversely, the degree of integration of diverse components within the system’s internal operational framework, provides a measure of coherence for a complex adaptive system. In the analyses presented in chapter 9, E/I indexes are reported by jurisdictional levels of authority and types of funding sources for each earthquake response system. Both measures are calculated to show the degree of dependence on external associations or the capacity to integrate all components into a functioning system. The extent to which these key attributes can be adapted flexibly within a system’s operations to respond effectively to external hazards indicates the level of overall coherence for each response system. Findings from the E/I analyses also reveal the breaking points in performance of a system under actual stress and provide a quantitative means of distinguishing types of adaptation and points for likely reinforcement or strengthening of the operational systems against future hazards. In actual field environments, a community’s operational system can be most effective when its exercise of jurisdictional authority at every level is backed by collaborative action from organizations with multiple funding sectors, public, private, and nonprofit. To the extent that these measures of integration diverge, the operational system varies in its capacity to adapt performance to the rapidly changing demands of a disaster environment. Comparison of the findings from the E/I indexes calculated for the 12 operational systems validate the designation of the four classes of adaptation in terms of varying levels of coherence, as measured by the E/I indexes. TOWARD AN AUTO-­ADAPTIVE SYSTEM

The Lushan, China, operational system presents a very interesting case. The E/I index values are close to 0 in both funding sector and jurisdictional performance. This finding indicates a near balance between external and internal associations in the network, although the measures are both positive, indicating a very slight dependence on external support. While these results warrant validation from independent sources, the system as characterized by the data available shows that jurisdictional and funding sector interactions occurred in a manageable balance between external and internal associations as reported for Lushan operations. The system is neither wholly dependent on external resources, as represented by its interactions with other jurisdictions, nor is it wholly internally self-­sufficient in managing resources. Rather it is close to balancing access to external resources with management of internal performance to implement resources effectively in practice. As presented in this analysis, the system is approaching coherence in its performance. This near balance is shown in table 10.1.

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TABLE 10.1. Comparison of Overall E/I Values for Network Moving toward an Auto-­ adaptive System

Response System

Overall E/I Value Jurisdiction

Overall E/I Value Funding Sector

0.03

0.01

Lushan, China, 2013

OPERATIVE ADAPTIVE SYSTEMS

At the operative adaptive level (see table 10.2), the overall E/I values increasingly reflect internal coherence among funding sectors, but the overall E/I values scaled for jurisdiction reflect reliance on external associations for three of the four operational systems, although only slightly for Japan. Only Nepal, the smallest, least developed nation of the four cases, shows a modest turn to internal coordination. The chronological change in this set of operational systems is interesting, as expert managers in Nepal had reported extensive use of GIS, satellite mapping, and multiway communication to facilitate informed action. The sizeable discrepancies in E/I indexes between overall performance among jurisdictions and overall performance among funding sectors likely contributed to constraints that each system confronted in resolving more complex and contentious issues involved in recovery and achieving sustainable resilience for their respective communities over time. In this class of operative adaptive systems, the break in performance appears to occur most sharply between the provincial/prefectural level and the national level of operations, as shown in chapter 9, table 3. Interestingly, integration among funding sectors appears stronger than integration among jurisdictions for all four response systems. This finding confirms the strong humanitarian response articulated by nonprofit organizations in each system. EMERGENT ADAPTIVE SYSTEMS

At the emergent adaptive level, the overall E/I indexes for the four response systems, reported in table 10.3, reveal greater discrepancies among jurisdictions in their reliance on external sources than among organizations with diverse funding sources in integrating operational performance into overall response systems. This pattern shows the limits of the jurisdictional systems in managing the full response operations over the three-­week period of study and shows striking breaks in coherence of integrated operations for each response system. None of the jurisdictional E/I measures reported in table 10.3 shows positive average internal capacity. In the detailed reporting of E/I indexes by ju-

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TABLE 10.2.

Comparison of Overall E/I Values for Whole Networks, Operative Adaptive

Systems

Response System Duzce, 1999 Padang, 2009 Tohoku, 2011 Nepal, 2015

TABLE 10.3.

Overall E/I Value Jurisdiction

Overall E/I Value Funding Sector

0.32 0.14 0.01 −0.05

−0.47 −0.59 −0.45 −0.53

Comparison of Overall E/I Values for Whole Network, Emergent Adaptive

Systems Response System

Overall E/I Value Jurisdiction

Overall E/I Value Funding Sector

Marmara, 1999 Chi Chi, 1999 Pakistan, 2005 Wenchuan, 2008

0.49 0.11 0.15 0.02

−0.44 −0.27 −0.32 −0.18

risdiction in chapter 9, table 5, the break appears to occur between the lowest jurisdictional level—local/district—and the next jurisdictional rank—municipal/county. Lack of capacity at this basic level in the system affects the capacity of all other jurisdictional levels to function, weakening the capacity of the whole system. The data show that all four response systems were dependent on external resources at the system level, albeit to differing degrees. The overall E/I values indicate greater integration among public, nonprofit, and private organizations, likely responding to observed participation by nonprofit organizations in humanitarian assistance, and incorporating the role of international nonprofit organizations in strengthening the response operations of domestic nonprofit organizations. NONADAPTIVE SYSTEMS

In nonadaptive systems, local governments are overwhelmed by the demands of a major earthquake and have little capacity to respond. Interestingly, it is exactly under these conditions that other organizations—nonprofit, private, international—spontaneously offer assistance and support to the afflicted community. Yet these generous offers of external assistance often create strain for the internal governing systems that are not prepared to accept or manage volunteered resources. The overall E/I indexes reported in table 10.4 for the

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TABLE 10.4. Comparison of Overall E/I Values for the Whole Network, Nonadaptive Systems

Response System Gujarat, 2001 Sumatra, 2004 Haïti, 2010

Overall E/I Value Jurisdiction

Overall E/I Value Funding Sector

−0.10 0.21 −0.01

−0.30 −0.44 −0.77

three earthquake response systems classified as nonadaptive reveal that in all three cases, the overall E/I value for jurisdictions indicates greater dependence on external support than the E/I value for source of funding. The discrepancies in the E/I values, calculated for the whole networks, reveal stronger dependence of the jurisdictional authorities on external assistance for each earthquake operational system. Interestingly, higher E/I values for internal integration on funding sector indexes likely indicate stronger participation of nonprofit organizations in response operations, as well as the inclusion of international nonprofit organizations in the overall response systems. The findings confirm greater dependency on external sources for governmental jurisdictions. SUMMARY, ADAPTATION IN COMPLEX SYSTEMS

The E/I indexes provide a useful measure of the internal integration of complex operational systems as they seek external resources and support to cope with urgent demands in rapidly changing disaster environments. For all four classes of adaptation, local and subnational organizations appear to be weak points in the respective systems, as without strong institutional capacity at subnational levels of jurisdictional authority and action—local, district, county, state/prefectural—national and international actors are constrained in their capacity to mobilize resources and information across funding sectors as needed. The E/I indexes show weaker results for jurisdictional performance than for funding sector performance across all classes of adaptation, an important finding in the search for resilient communities. The E/I indexes show that international support is critical in many, if not most, of the operational systems, but integration of international support into the overall response system appears to be a source of contention. A Bridge to Resilient Systems S

The study of past earthquake response systems provides no guarantee of avoiding the same errors in judgment that led to previous disasters or ensuring

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greater insight into potential means of managing risk of future hazards. Yet insights from this study lead to the identification of a set of core requirements for building resilient systems. These requirements are acknowledged both by experienced analysts of risk and dynamic systems (Arthur 2009, 2015; Glass, Ames, et al. 2011; Smith 2008c; Holland 1996, 2012; Miller and Page 2007), as well as by practitioners in the field (Tamang 2015; Ismael 2012). This set of requirements includes the following basic elements essential to support collective action to counter risk. SHARED VISION OF A RESILIENT COMMUNITY

To build a basis for collective action, it is essential to articulate a shared vision of system goals and functional performance for the community. Individuals, groups, and organizations may have different interests, skills, and backgrounds, but the key requirement for collective action is a shared vision of the common effort, one that benefits every member of the community. Each participant may contribute different skills and insights, but the collective effort is most effectively bound by a shared goal to reduce seismic risk and ensure the safety of the whole community. SHARED KNOWLEDGE AND SKILLS IN PRACTICE

The shared vision of a resilient community requires a base of shared knowledge and skills regarding how to create a working community that minimizes risk in practice. This knowledge base includes basic understanding of the types of risk that may be generated in that specific community from seismic hazards. Not all communities have the same level of risk, nor the same experience from previous seismic events. Organizing this knowledge and making it available to all residents of the specific community seeking to build resilience strengthens the capacity of that community to respond collectively to hazards when they occur. OPEN PLATFORM FOR INFORMATION SEARCH, EXCHANGE, AND UPDATING

Building resilience requires sharing different types of knowledge, skills, values, and information that enable community residents to follow a changing situation and learn new insights regarding a previous or continuing challenge. This requirement warrants an open information platform that serves multiple functions: continuous public and professional education regarding an ongoing threat; continuous updating regarding a potentially hazardous set of events or exposures; and a public forum for error correction, documentation of insights

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gained and lessons learned in the process of response. Such a platform also requires regular review and verification by the wider community to avoid inaccurate or outdated information, and to ensure validity. CAPACITY TO SOLICIT AND SECURE ADEQUATE RESOURCES FOR RECOVERY

Earthquakes are destructive events, damaging built environments as well as socioeconomic contexts. Response operations entail not only rescue and relief operations, but also a slow, costly, and often conflictual process of rebuilding and recovery. Reconstruction requires securing external resources and integrating these incoming resources and personnel effectively into an existing internal management system. Such integration may be fraught with differences in competence, training, knowledge, and experience that challenge coherent strategies and practice. Yet managing the integration of diverse personnel, skills, resources, and approaches to serve the needs of the whole community is a basic challenge in building a resilient system. The four core requirements outlined above serve as the starting point for designing a resilient community. Yet this complex task requires a more explicit theoretical framework for development in practice. A Sociotechnical Framework for Building Resilient Systems At the outset of this study, five preliminary premises were stated to frame an initial approach for building resilient communities exposed to seismic risk (chapter 1, under “Premises Underlying Study”). Redefined in light of practice, these five premises offer a preliminary model for building resilient systems in communities at risk. INFORMATION

The initial premise asserted that information serves as a catalyst that drives interactions among systems in recognition of, and in response to, shared risk. While the basic assumption regarding information as a catalyst for action is affirmed by the 12 cases of earthquake response systems, the analyses present a far more complex and nuanced role for information in activating or inhibiting resilient systems. It is not only the content of information that triggers action, but also the channels through which information is transmitted that shape the level of cognitive understanding of risk among community recipients and culminates in collective action. For example, the rapid escalation of

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cell phone use among young Nepalis linked farmers in mountain villages with nonprofit organizations in the Kathmandu Valley, creating an exchange of information that enabled farmers to consider growing new crops, such as mushrooms, that would provide more return and profit on their investment (Personal observation, Sindhupalchok District, Nepal, April 29, 2016). Further, it is the context within which information is received that leads to responsible, informed action that stimulates further action in networked development, as shown in the analyses of the 12 earthquake response systems. Conversely, if the context distorts the information, collective trust is diminished and the system likely falters, evidenced also in instances of practicing response systems. In a troubling example, the actions by the Bharata Janata Party (BJP) political party in Gujarat, India, to distribute relief goods along religious lines in the city of Ahmedabad following the Bhuj earthquake of 2001 led to riots between Hindus and Muslims that worsened relations among the two groups and deepened distrust of governmental action (Mistry, Dong, and Shah 2001). The role of information both activates certain aspects of the system in powerful thrusts for change but distorts others. Designing the information flow to support learning and adaptation, but also to correct error and distortion, is a fundamental task for building resilient systems. TECHNOLOGY

The preliminary premise stated that technology constrains the structures through which information flows among component actors, units, or institutions within and between operational systems. Again, the basic premise is supported by the 12 empirical analyses of earthquake response and recovery systems, but the concept of technology is revealed as a much broader, more diverse set of interacting components that constitutes the collective set of tools, instruments, and devices that enable a community to recognize and respond to risk. The empirical studies demonstrated vividly that technologies operate at different scales within the same society, and consequently affect the degree to which risk is perceived, communicated, and translated into action. The differences between the technologies available for seismic risk detection in the talukas of Gujarat State in India, for example, contrast vividly with the sophisticated technologies of the Indian Space Research Organization with headquarters in Hyderabad. Bridging those differences in a coherent strategy for managing risk to benefit the whole society is a function of resilience. These differences are even sharper between classes of adaptation, for example, the absence of a seismic network in Haïti, classified as a nonadaptive system, and the sophisticated seismic monitoring network that transmits seismic data to households in Japan, classified in this

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analysis as an operative adaptive system, but previously as nearing auto-­ adaptation (Comfort 1999a). ORGANIZATION

The premise stated regarding organizations asserted that organizations create the processes through which communication flows among component actors, units, or institutions that either facilitate or inhibit collective recognition of and response to risk. This premise asserts that organizations structure actions taken by individuals, groups, or institutions regarding a shared task or mission, for example, seismic risk reduction. Organizations serve as the social construct through which work is performed in mobilizing collective action to achieve a shared goal or meet a collective need. That is, organizations undertake the gritty work of assisting families to find shelter and rebuild their homes after a disaster and in managing the process of defining actual tasks, setting schedules, allocating personnel, mobilizing supplies, and determining direction of recovery within the context of specific communities and their constraints. Achieving the goals of risk reduction is a complex and varied set of tasks that cannot be accomplished by a single jurisdiction or agency. Such tasks include the design of disaster management plans in Indonesia or Turkey, training emergency personnel for immediate dispatch to a damaged area in Japan, or mobilizing viable social institutions to respond to local needs, as the Catholic Charities in Haïti. The initial premise of organizations as the primary actor in response operations is affirmed by the empirical findings from the 12 analyses of earthquake response systems, but the range and diversity of organizational interaction depends fundamentally on the technologies available to participants. Further, the interaction between technologies and their local audiences can either accelerate or diminish collective learning and action. Whether it is an imam striking a gong in a local mosque in Padang, Indonesia, to alert the neighborhood to potential harm, or a young Nepali sitting on the floor with his laptop in a mountain hut at 9,000 feet in the Himalayas, connecting via a wireless network to his NGO’s headquarters in Kathmandu, the process of communication is shaped by the technology available at that specific place and time (Arthur 2015). The empirical cases demonstrate that communication has costs in both time and effort, but that effective communication can be achieved only by design in large-­scale, sociotechnical systems. While the technologies are neutral, the senders and receivers are not. Selecting method and content of communication may either facilitate or hinder collective action. Determining which technologies facilitate collective action under what conditions, and

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what social, economic, and cultural conditions inhibit the use of available technologies to manage risk is a continuing task. CULTURE

The initial premise stated that culture serves as a filter for interpreting information through norms of action under conditions of uncertainty and varies among communities. The 12 empirical studies showed that culture, as a set of shared meanings, was an extraordinarily powerful factor in explaining both an emerging capacity for collective action or the inability to address problems of shared risk productively. In a deeper illustration of the interdependency of these key elements, information flow is constrained or facilitated by the technical means available at each level of action. Making satellite phones available to district collectors in Gujarat State, without detailed guidance on how to use them, meant that this means of communication largely went unused, limiting access to essential information for the residents in the villages. In contrast, access to satellite images of damaged villages in the KPK region of Pakistan enabled search and rescue teams to reach villages that had been cut off from all other means of communication. Information flow is doubly constrained by the organizational rules and procedures accepted by the group or community. The interactions of all three functions—technologies, organizations, and information—contribute to the reinforcement of existing norms or the generation of extended or adaptive norms that fit existing conditions more appropriately. INTERACTION

The final premise stated these interacting components make up a metasystem, or complex adaptive systems of systems, that operates in a continual process of defining and redefining what risk is shared and requires collective public action, and what risk can be ignored at relatively little cost. The complexity generated by interacting processes of cognition and action only increases with the size of the community at risk, the scale of the hazardous event, and the scope of destruction that has been inflicted on the community. In such events, planning for extreme events is necessary, but seldom does the actual event match the plans designed to reduce risk. In such instances, understanding the dynamics of collective cognition and action offers practicing managers more effective guidance for improving the process of managing collective risk than adhering to predesigned rule-­based systems. Information, again, serves as the basic currency of learning and adaptation in a continuously changing world.

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Methods of Analysis to Capture Interactive Rates of Change If the premises undergirding the design of resilient systems differ from conventional organizational hierarchy, the methods of measuring performance must also differ. These types of methods include the following. SYSTEMATIC METHODS OF MONITORING MULTIPLE CONDITIONS SIMULTANEOUSLY

For resilient systems, recognized as dynamic systems that adapt to threats or changing conditions, it is essential to develop metrics that capture the actual rates of change, not only in interactions among the components of the whole system, but also in interactions among the components of the subsystems and the sub-­subsystems that are involved. This process is made more complex by the action/reaction dynamics that are characteristic of social change, as the component subsystems and sub-­subsystems change in reciprocal reaction to other actions taken by different components at varying scales, rates, and times of operation. Even more difficult, many processes and subprocesses of change occur simultaneously, with action by one set of components triggering reaction at a different scale, type, and time of operation. Measuring change in complex systems involves multiple measurements being conducted simultaneously, with appropriate metrics for each process or subprocess, and integration of the set of measurements as part of the process. Technology changes continuously, in large and small ways. For example, the remarkable shift in communications technology from September 1999— when researchers doing reconnaissance studies in the heavily damaged city of Adapazari following the Marmara, Turkey, earthquake struggled to use heavy, clumsy satellite phones that would work only sporadically—to April 2016— when volunteer workers assisting Nepali communities located at 9,000 feet in the Himalayas could link easily via wireless networks to NGO headquarters in Kathmandu—greatly improved organizational performance in 2016. The difference in organizational capacity created by inexpensive, easy-­to-­use wireless technology for communications in 2015–16 was striking. Consequently, the network of organizations engaged in providing support to persons affected by the 2015 earthquake in Nepal and engaged in the 2016 recovery revealed a very different pattern of decision making than comparable networks following the Marmara earthquake of 1999.

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MODELS OF CHANGE THAT FOCUS ON FUTURE STATES, INFORMED BY PAST RECORDS

The focus on capturing the rate of change in dynamic systems has also shifted the degree of certainty accorded to analyses of past performance by organizations. No longer are previous records of performance considered the best estimates of future performance. Although not excluding knowledge of past performance and mindful of previous records, models that focus on exploring possible future states of performance or reconfiguration of the system are more relevant to decision makers seeking to manage complex systems (Lempert, Popper, and Bankes 2003). Consequently, alternative ways of exploring how systems fail and what the breakpoints are for system integration provide practical assessments of system performance that can be updated as conditions change. Network analyses that show change over time and External/ Internal indexes that reveal break points in change within organizational performance, as well as thresholds of interaction with organizations external to the operating system, provide measures that offer insight into the evolving direction of the system. These models cannot be imbued with certainty, but they are instructive in terms of anticipating future performance and indicating likely points of investment of resources and time to achieve the system’s desired goal. INTEGRATION OF DIVERSE TYPES OF DATA

Data management for complex systems becomes a unique set of skills and functions that requires continual monitoring, updating, verifying, and validating of data from different sources, collected in different formats, often at different times and places, and made accessible to different audiences. Since the construction of a timely, valid knowledge base of shared information is vital for responsible decision making at multiple levels in complex systems, the design, maintenance, and assessment of the methods of data collection, management, modeling, and dissemination are critical. Well-­designed and executed, such a data management schema becomes a knowledge commons, a concept articulated by Elinor Ostrom (1990) to characterize a platform for the interactive exchange of information among participants engaged in a common enterprise. The management of such a platform becomes self-­organizing, as the technical design both facilitates and constrains the organizational performance that it supports. To the extent that such a platform becomes autocorrecting, that is, when it can detect and correct its own errors, the knowledge commons becomes the core technology of the adaptive system. S L

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INNOVATION IN MANAGING LEARNING PROCESSES ON A COLLECTIVE SCALE

When the three previous methods of monitoring performance and context of operations are functioning in a systematic effort to achieve a stated goal, for example, seismic risk reduction, the methods create, synergistically, conditions for innovation in designing and developing learning processes on a collective scale. Innovation depends on the capacity to visualize new approaches, imagine alternative strategies to existing practice, elicit feedback on proposed courses of action, and compare potential outcomes against preferred priorities. Such tasks depend on the capacity to engage large numbers of people simultaneously in an exploration of alternative modes of collective action, with the opportunity for feedback, time for absorption of new information, and trial representation of novel ideas for achieving a shared goal NETWORKS OF ACTION LEADING TO NEW PATTERNS OF COLLABORATIVE PERFORMANCE

The anticipated result of the sequence of measures outlined above is an emerging forum of innovative practice informed by theory and chastened by reality. The focus is on practice, getting work done guided by a clear goal, but within the constraints of time, resources, knowledge, and skills of an actual, living community. The sequence of measures listed above reveals the logic of resilience, a capacity-­building process that progresses as one set of skills creates the basis for the next innovation, and the cumulative process contributes to the novel capacity of a community to cope with unknown risk. Specific Challenges of Seismic Policy A lingering question for scholars who study resilience is whether the concept of managing risk is appropriate for all hazards. Or do the characteristics of specific hazards limit the degree of resilience that can be achieved in communities exposed to certain types of risk at certain scales? For example, the failure of the carefully orchestrated Japanese disaster management plan to anticipate the scale of the destructive cascade of events that was triggered by the 2011 Tohoku earthquake was considered by many to be beyond human capacity to imagine, and therefore, outside the realm of human management. Is there a limit to the degree of resilience that can be expected from human communities, and if so, what is it? Is the concept of resilience valid in the context of seismic risk, or is the prospect of resilience doomed forever to fail in communities exposed to severe seismic risk?

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Such questions haunt policy makers in regions of seismic risk for good reason. In terms of time, there are long periods of inactivity between earthquakes. Moderate earthquakes occur, on average, every 40 to 60 years; severe earthquakes, every 90 to 150 years, and catastrophic earthquakes every 300 to 1,000 years. These time spans are off the scale for policy makers, who usually work with annual budget cycles. Regarding scope, earthquakes occur around the globe, with 36 nations exposed to serious seismic risk, and approximately 10 earthquakes registering over Mw = 7.0 every year. Consequently, the variation in laws, policies, and practices governing organizational response to earthquakes is both wide and deep. Regarding scale, earthquakes range from barely perceptible events measuring Mw = 1.0/2.0 to massive events measuring Mw = 9.4 and over, with an equally wide-­ranging set of destructive consequences. These are not easy events to classify, and they have largely been studied as unique events in specific contexts. The one factor that has been increasing steadily regarding seismic policy is the quality, timeliness, and accuracy of information regarding earthquake events as they occur, obtained through more refined sensors and more systematic means of data collection and dissemination to communities at risk. Japan’s advanced seismic network is a case in point. Improved methods of data collection contribute to a cumulative knowledge base regarding the occurrence of earthquakes and their location, magnitude, and consequences as they occur in different parts of the world. This cumulative information is generating a more informed audience for the consideration of seismic risk and contributing to recognition of seismic risk as a problem that can and should be addressed. This loosely connected audience represents an interdisciplinary, international group of scientists, policy makers, managers, and concerned citizens who are receptive to proposals for managing seismic risk, likely for different reasons. While information serves as the activating source of energy to mobilize this distinctive group for global action regarding seismic risk reduction, the momentum needed to precipitate actual change on a global scale is not yet evident. Transfer of Resilience Framework to Other Types of Hazard? If seismic risk is a particularly challenging type of risk to manage, are there insights from this study of resilience that can be transferred to other types of hazard? At first glance, such transfer would appear obvious and relatively easy, but on second glance, it is necessary to assess the parameters for such transfer and evaluate which insights could provide momentum for which actors at what scale. If it is possible to transfer insights gained from this study of risk, a

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key set of interrelated concepts creates a logic of resilience. Understood in abstract terms, the interrelated concepts of information, technology, organization, and culture can be applied to any hazard in any community in any country. Yet the power of explication inherent in this set of concepts lies in the detailed design of a knowledge commons that enables the interactive sharing of information, knowledge, concepts, and practical mechanisms that change practice in a specific time and place. The most critical finding from the analysis of the E/I indexes for earthquake response systems is that the midlevel or meso scale of organization is weak or missing in all 12 communities that experienced serious losses from seismic risk. The meso scale links specific needs at the micro or local scale to relevant resources at the macro or national/international scale to mitigate actual risk. For example, if the specific schools in the mountain villages that were shattered by the 2015 Nepal earthquakes are not identified as a priority for reconstruction, the national or international resources that have been contributed to rebuild the schools are not activated. More critical, if there is no intermediate or meso organization to conduct the transfer functions, for example, transporting supplies to the mountain village, or mobilizing skilled masons to build earthquake resistant schools, the connection between the serious need for school construction at the micro level and provision of resources and skills through UN donations at the macro level is not completed. The capacity of the response and recovery system is not strengthened; the specific need is not met, and the available resource is not used. The difficulty encountered in transferring frameworks and applications for resilience to other contexts illustrates a primary insight into the nature of resilience. Resilience, as observed in the 12 analyses of earthquake response systems, is an evolving process. It is a learned set of responses based on shared knowledge and shared commitment to a common goal. It evolves from prior actions that create the basis for a larger application. Three basic components of resilience—technology, organization, and culture—are inextricably interconnected through the flow of information that not only links one to the other but also has a generative effect in producing the next iteration of technology, organization, and culture needed to enact the shared mission of reducing risk. Emergence of Resilient Societies Much attention, effort, and research funding has focused on the design of resilient communities, and more broadly, resilient societies. Yet, this effort has not always led to practical results. The insights from this study complement the perspective that resilience evolves through combinations of prior experience, insights, technologies, associations, mechanisms, skills, and shared val-

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ues (Arthur 2015). This perspective, articulated persuasively by Brian Arthur (2015), an economist studying complex adaptive systems, implies that the construction of resilient societies depends on building the basic relationships among people, technologies, organizations, and, importantly, cultural norms and humanitarian values that enable the residents of communities to adapt their actions interactively to achieve collective action for the whole community. Viewed from this perspective, creating resilience is a social act; it cannot be achieved by a single person or organization. Rather, it is the interactions among residents, organizations, policies, and the physical environment that create the context in which people learn to value resilience and consciously choose actions that reduce risk, not just for themselves, but for the whole community. Over time, residents of a community at risk gain insight and understanding into the conditions that generate risk and consciously reorder their actions to minimize risk and promote resilience. Novel mechanisms for risk reduction emerge from previous efforts, as different groups and organizations strive to improve existing performance. Again, this evolving process depends on a consistent and open information infrastructure to enable learning, adaptation, and correction of error among participants in the system. Investment in information technologies and organizational networks builds resilience. Next Steps in Research and Policy Arguments over resilience, how to build it, what it looks like, who creates it, and what it costs, will continue, as communities struggle to cope with risk. This book closes with an argument for the logic of resilience as an unfolding, reasoned process of discovery that shows human intelligence grappling with unknown conditions and fashioning workable solutions out of the concepts, technologies, tools, associations, and practices that are available in contexts exposed to risk. With this understanding, resilience is not a grand enterprise, but rather a quiet accumulation of both science and intelligent reasoning applied to recurring threats in practical ways. It is not simple, as the 12 analyses show, but there is a slim, steady logic of action that demonstrates the human capacity to learn, adapt, and transform extreme events into opportunities for collective action and learning. What, then, are the next steps in an agenda to minimize risk in a rapidly changing world? Three tasks warrant investment in energy and effort in the continuing task of managing risk. First, since determining future action, not explaining past events, is the primary orientation in managing risk, investment in modeling future states of interacting conditions and actors promises substantive benefits to managers grappling with uncertainty. While this investment will engage the scientists and scholars in nations exposed to risk, it must

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necessarily be understood, supported, and financed by the policy makers and citizens of those nations as a guide to practical action. Second, given the complex, interdependent character of earthquakes as well as other types of hazards, it is imperative to build an interdisciplinary, international knowledge commons to inform the process of learning, exchange, adaptation, correction, and innovation. Creating a global knowledge forum for major hazards becomes a major technical, organizational, and cultural responsibility that, if led by scientists, scholars, and policy makers in the developed world, will engage the emerging communities of scientists, scholars, and policy makers in the developing world in the shared task of managing risk for the planet. Third, since the process is ongoing, it is essential to educate the next generation of scholars, researchers, managers, policy makers, and informed citizens to carry on this continuing task. The goal of this complex, sociotechnical system of systems is to inform timely strategies of collective action in regions exposed to recurring seismic and other types of hazards, and to imagine alternative policies and practices that will lessen those risks as the planet and its populations continue to evolve and change. As this book closes, the next study begins, focusing on the integration of advancements in wireless communications and information technologies into organizational policy and practice as a means to engage informed action across households, community groups, organizations, and jurisdictions that build resilient communities.

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APPENDIX I

Tables of Transactions by Classes of Adaptation

253

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Chapter 5. Toward an Auto-­adaptive System: The 2013 Lushan County, China, Earthquake TABLE I.5.1 . Types of Transactions Performed by Organizational Actors in the 2013 Lushan County, China, Response System, by Jurisdiction and Funding Sector

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In te r

Types of Transactions

1 Emergency response 2 Communication 3 Coordination: response/ recovery 4 Medical care/health 5 Damage/needs assessment 6 Certificate of deaths: est. 7 Earthquake assessment/ research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief (food, shelter) 11 Donations (money, goods, services) 12 Building inspection 13 Building code issues 14 Repair: roads, bridges, railroads 15 Repair/restore utilities 16 Repair/reconstruction/ recovery 17 Transportation/traffic issues 18 Hazardous materials release 19 Legal/enforcement/fraud 20 Political dialogue/ legislation 21 Business recovery 22 Economic/business issues 23 Visits by officials/ condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans (private, international) 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers Total

State-­Owned

Public Institutions

na Na tio tio nal n Pr al ov in M cial un ic Co ipal un ty Na tio n Pr al ov in M cia un l ic Co ipal un ty In te rn a Na tio tio nal n Pr al ov in M cial un ic i Co pal un ty

Public

1

0 0 0

52 22 40

66 36 85

26 14 22

7 1 8

23 4 0

10 7 0

5 5 0

0 4 0

0 0 0

7 32 5

2 12 7

3 6 9

0 1 1

0 0 0 0

45 17 3 10

56 19 3 8

16 16 0 4

8 0 1 0

0 0 4 0

0 0 7 0

0 0 5 0

0 0 4 0

0 0 0 0

5 1 0 2

5 5 0 0

4 2 2 1

0 1 0 0

0

3

13

1

0

0

0

0

0

0

0

0

0

0

0 0

6 15

6 48

1 16

0 6

0 3

0 1

0 0

0 0

0 0

2 7

0 6

1 9

0 0

0

17

77

34

7

23

10

5

0

0

20

16

7

0

0 0 0

1 0 6

1 0 4

0 0 1

0 0 4

0 0 6

0 0 35

0 0 25

0 0 22

0 0 0

0 0 0

0 0 3

0 0 0

0 0 0

0 0

3 1

9 17

3 3

3 2

6 13

17 2

7 2

2 1

0 0

15 1

8 0

4 0

1 0

0

21

48

14

3

6

17

7

2

0

10

8

4

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0 0

4 0

11 1

3 1

0 0

0 0

0 0

0 0

0 0

0 0

2 0

2 0

0 0

0 0

0 0 0

0 0 7

1 2 10

2 1 6

0 0 2

0 0 13

0 0 2

0 0 2

0 0 1

0 0 0

0 0 1

0 0 1

0 1 0

0 0 0

0 0 0 0

7 0 0 0

12 0 0 0

11 0 1 0

4 0 0 0

6 0 0 0

35 0 0 0

25 0 0 0

22 0 0 0

0 0 0 0

3 0 4 0

2 0 1 0

0 0 1 0

0 0 2 1

0

1

6

1

0

0

0

0

0

0

1

0

0

0

1

1

10

9

1

4

7

5

4

1

5

7

4

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

282 549 206 57

111 150 93

62

1

123 85

58

7

Data sources: Electronic online sources, April 20–­May 11, 2013.

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App e n d ix I 255

na Na tion tio a na l l Pr ov in ci M a un l ic i Co pal un ty

Total Actors

In te r

In te r

ty

ou n

Private

na Na tion tio al n Pr al ov in ci M a un l ic i Co pal un ty

Nonprofit

Total Number of Transactions

N

%

N

%

0 1 1

1 0 2

6 24 23

16 8 16

15 17 15

2 1 1

0 11 3

5 27 6

4 8 9

0 3 2

1 0 0

251 243 254

8.38 8.11 8.48

100 86 110

8.24 7.08 9.06

0 1 0 0

1 0 0 0

14 6 0 5

22 3 0 1

10 2 0 2

3 0 0 0

3 1 0 0

5 1 0 0

7 1 0 0

3 0 0 0

0 0 0 0

207 75 29 33

6.91 2.50 0.97 1.10

115 33 4 29

9.47 2.72 0.33 2.39

0

0

0

0

0

0

0

0

0

0

0

17

0.57

5

0.41

0 0

0 2

1 42

2 24

1 29

0 3

1 3

3 18

1 9

0 5

0 0

25 246

0.83 8.21

11 113

0.91 9.31

0

2

134

103

76

4

32

61

67

17

1

713

23.79

317

26.11

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

2 0 106

0.07 0.00 3.54

1 0 7

0.08 0.00 0.58

1 0

0 0

2 7

2 6

1 2

0 0

0 0

1 2

0 1

2 1

0 0

86 61

2.87 2.04

20 16

1.65 1.32

0

0

4

8

5

1

1

3

9

4

0

175

5.84

69

5.68

0

0

0

0

0

0

0

0

0

0

0

0

0.00

0

0.00

0 0

0 0

0 1

0 1

0 0

0 0

0 0

0 0

0 0

0 0

0 0

22 4

0.73 0.13

10 2

0.82 0.16

0 0 0

0 0 0

0 0 0

1 0 1

1 0 3

0 0 0

0 0 0

0 0 0

0 0 0

1 0 1

0 0 0

6 4 50

0.20 0.13 1.67

5 2 14

0.41 0.16 1.15

0 0 2 1

0 0 0 0

14 0 2 0

17 0 0 0

8 0 0 0

1 0 0 0

2 0 1 0

2 0 2 0

1 0 0 0

1 0 0 0

0 0 0 1

173 0 14 2

5.77 0.00 0.47 0.07

47 0 6 1

3.87 0.00 0.49 0.08

0

0

4

2

2

0

0

0

0

0

0

17

0.57

16

1.32

0

3

37

25

21

6

0

6

11

12

2

182

6.07

75

6.18

0

0

0

0

0

0

0

0

0

0

0

0

0.00

0

0.00

11

326

258

210

22

58

142 128

52

5

2997

100.00

1214

100.00

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256 App e n d ix I

Chapter 6. Operative Adaptive Systems: 1999 Duzce, Turkey; 2009 Padang, Indonesia; 2011 Tohoku, Japan; and 2015 Nepal Response and Recovery Systems TABLE I.6.1 . Types of Transactions Reported in 1999 Duzce, Turkey, Response System, by Jurisdiction and Funding Sector

 1 Emergency response 13  2 Communications/IT 0  3 Coordination: response/ 24 recovery  4 Medical care/health 2  5 Damage/needs assessment 0  6 Certificate of deaths, est. 0  7 Earthquake assessment/research 1  8 Security/prevention of looting 0  9 Housing issues 0 10 Disaster relief: food, shelter, 2 clothing 11 Donations: money, goods, 21 services 12 Building inspection 0 13 Building code issues 0 14 Repair: roads, bridges, railroad 0 15 Repair/restore utilities 1 16 Repair/reconstruction/recovery 0 17 Transportation/traffic 0 18 Hazardous materials release 0 19 Legal/enforcement/fraud 0 20 Political dialogue/legislation 0 21 Business recovery/banking 0 22 Economic/business issues 0 23 Visits by officials/condolences 7 24 Education issues 0 25 Government assistance 0 26 Insurance-­related issues 0 27 Loans: private/international 2 28 Psychological/counseling 0 29 Fund-­raising/account setup 0 30 Volunteers 0 Total

S

73

na tio St na at l e/ ce nt Na ra l tio na l Pr ov in ce

In te r

In te r

Types of Transactions

Nonprofit

na tio na St at l e/ ce nt ra Pr la ov in ce M un ic ip al

Public

16 3 64

18 4 82

1 0 18

0 0 0

0 0 6

2 0 4

0 0 1

10 5 5 20 0 0 14

3 9 2 0 2 0 32

0 3 0 0 0 1 22

0 0 0 0 0 0 0

0 1 0 0 0 0 8

0 0 0 0 0 0 1

2 0 0 1 0 0 43

30

61

11

2

4

3

1

0 0 3 5 2 6 0 0 10 0 0 20 1 1 0 2 0 0 0

0 0 1 4 0 4 0 0 3 0 0 20 0 1 0 0 0 7 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0

0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

217

253

56

2

22

11

49

Data source: Cumhuriyet, Istanbul, Turkey, November 13–­December 4, 1999. a State/central: public agencies with national authority; National: nonprofit and private organizations operating at national level.

L

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App e n d ix I 257

Political

Total N, Actors

Total N, Transactions

Na tio na l

Na tio na l Re gi on al

e

Private

N

%

N

%

0 2 2

0 0 0

0 0 0

50 9 201

6.99 1.26 28.11

22 5 84

7.28 1.66 27.81

0 0 0 0 0 0 15

0 0 0 0 0 0 9

0 0 0 0 0 0 0

17 18 7 22 2 1 146

2.38 2.52 0.98 3.08 0.28 0.14 20.42

11 14 4 16 2 1 40

3.64 4.64 1.32 5.30 0.66 0.33 13.25

0

1

0

134

18.74

51

16.89

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0

0 0 5 10 3 11 0 0 15 0 0 49 1 2 1 4 0 7 0

0.00 0.00 0.70 1.40 0.42 1.54 0.00 0.00 2.10 0.00 0.00 6.85 0.14 0.28 0.14 0.56 0.00 0.98 0.00

0 0 3 4 2 7 0 0 6 0 0 19 1 1 1 2 0 6 0

0.00 0.00 0.99 1.32 0.66 2.32 0.00 0.00 1.99 0.00 0.00 6.29 0.33 0.33 0.33 0.66 0.00 1.99 0.00

20

10

2

715

100.00

302

100.00

S L

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258 App e n d ix I

TABLE I.6.2 . Types of Transactions Reported in 2009 Padang, Indonesia, Response System, by Jurisdiction and Funding Sector

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

S

Emergency response Communications/IT Coordination: response/ recovery Medical care/health Damage/needs assessment Certificate of deaths, est. Earthquake assessment/ research Security/prevention of looting Housing issues Disaster relief: food, shelter, clothing Donations: money, goods, services Building inspection Building code issues Repair: roads, bridges, railroads Repair/restore utilities Repair/reconstruction/ recovery Transportation/traffic Hazardous materials release Legal/enforcement/fraud Political dialogue/legislation Business recovery/banking Economic/business issues Visits by officials/ condolences Education issues Government assistance Insurance-­related issues Loans: private, international Psychological/counseling Fund-­raising/account setup Volunteers Total

L

In te r

Types of Transactions

na tio na Na l tio na l Sp ec ial Re gi Pr on ov in cia l M un ic ip al Re ge nc y D i st ric t Lo ca l

Public

48 4 75

33 18 52

0 0 0

9 3 11

3 1 3

2 0 2

0 0 0

0 0 1

23 16 2 1

11 17 9 10

1 0 0 1

0 3 12 4

4 3 3 0

1 0 0 0

0 3 0 0

2 0 2 0

0

0

0

0

0

0

0

0

0 30

1 15

0 1

0 3

0 2

0 0

0 0

0 0

28

11

1

13

0

1

0

0

0 0 1

0 1 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

4 3

9 21

0 1

4 1

2 3

0 0

0 0

0 0

14 0 0 4 0 0 25

18 0 0 1 1 3 13

1 0 0 0 0 0 0

0 0 0 1 1 1 6

1 0 0 0 0 0 3

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

7 0 0 1 1 4 0

9 1 0 0 3 4 4

0 0 0 0 0 0 0

4 0 0 0 0 1 1

1 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 1 0

0 0 0 0 0 0 0

291

265

6

78

29

6

4

5

Data sources: Antara, Indonesian newspapers, October 1–­21, 2009.

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App e n d ix I 259

Political Party

Total N, Actors

Total N, Transactions

N

2 0 5

1 0 3

0 1 0

0 0 0

0 0 0

5 5 0

0 0 0

3 0 0

0 0 0

0 0 0

106 32 152

13.07 3.95 18.74

83 15 77

15.06 2.72 13.97

3 1 0 0

16 2 0 0

0 0 0 0

2 0 0 0

9 0 0 0

0 0 1 0

0 0 0 1

1 1 0 0

0 0 0 0

0 0 0 0

73 46 29 17

9.00 5.67 3.58 2.10

52 28 29 17

9.44 5.08 5.26 3.09

0

0

0

0

0

0

0

0

0

0

0

0.00

0

0.00

0 8

0 9

0 0

0 0

0 0

0 4

0 0

0 0

0 0

0 1

1 73

0.12 9.00

1 56

0.18 10.16

8

4

0

0

0

4

0

0

1

1

72

8.88

47

8.53

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 1 1

0.00 0.12 0.12

0 1 1

0.00 0.18 0.18

0 0

0 0

0 0

0 0

0 0

4 0

1 0

0 0

0 0

0 0

24 29

2.96 3.58

22 21

3.99 3.81

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

5 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

39 0 0 6 2 4 47

4.81 0.00 0.00 0.74 0.25 0.49 5.80

26 0 0 5 2 3 24

4.72 0.00 0.00 0.91 0.36 0.54 4.36

0 0 0 2 0 3 0

0 0 0 0 2 6 0

0 0 0 0 0 0 0

0 0 0 0 1 0 0

0 0 0 0 0 0 0

0 0 0 0 0 1 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

21 1 0 3 7 20 5

2.59 0.12 0.00 0.37 0.86 2.47 0.62

15 1 0 1 6 15 3

2.72 0.18 0.00 0.18 1.09 2.72 0.54

32

43

1

3

9

29

2

5

1

2

In te r

Na tio na l

Na tio na l Pr ov in ci al M un ic ip al Lo ca l

Private

na tio Na na tio l na l Sp ec ial Re Pr gi ov on in cia l Lo ca l

Nonprofit

Comfort.indb 259

%

N

%

811 100.00

551 100.00

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260 App e n d ix I

TABLE I.6.3 . Types of Transactions Reported in 2011 Tohoku, Japan, Response and Recovery System, by Jurisdiction and Funding Sector

S L

1 Emergency response 2 Communications 3 Coordination: response/ recovery 4 Medical care/health 5 Damage/needs assessment 6 Certificate of deaths, est. 7 Earthquake assessment/ research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief: food, shelter, clothing 11 Donations: money, goods, services 12 Building inspection 13 Building code issues 14 Repair: roads, bridges, railroads 15 Repair/restore utilities 16 Repair/reconstruction/ recovery 17 Transportation/traffic 18 Hazardous materials release 19 Legal/enforcement/fraud 20 Political dialogue/legislation 21 Business recovery 22 Economic/business issues 23 Visits by officials/ condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans: private, international 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers Total

na tio na Na l tio na l Pr ef ec tu ra l Re gi on al M un ic ip al Lo ca l

In te r

In te r

Types of Transactions

Nonprofit

na Na tion al tio na l Pr ef ec tu Re ral gi on al M un ic ip al Lo ca l

Public

74 14 97

193 101 261

74 64 85

1 0 3

25 16 31

0 1 0

3 0 0

8 19 10

0 2 3

0 0 0

0 1 0

2 1 0

8 11 0 8

33 133 24 67

24 42 20 0

1 0 0 0

13 10 10 0

1 0 0 0

0 0 0 0

32 10 0 2

8 1 0 0

1 0 0 0

5 1 0 0

7 2 0 0

0

0

0

0

0

0

0

0

0

0

0

0

0 14

15 70

35 96

1 3

12 72

0 0

0 0

11 17

1 6

0 0

1 4

0 1

26

13

17

0

4

0

3

16

1

0

0

0

0 0 0

0 0 1

0 0 1

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

1 3

52 89

11 17

0 1

7 24

0 0

0 0

32 2

2 1

0 0

0 1

0 2

4 2 0 11 12 0 31

30 32 24 99 50 26 42

15 3 13 14 1 2 5

2 1 0 0 0 0 0

20 0 5 7 3 0 6

0 0 1 0 0 0 0

0 0 0 0 0 0 1

8 0 1 3 3 2 1

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

4 0 0 0 2

22 5 7 11 9

12 0 0 0 35

0 0 0 0 1

1 1 0 0 1

0 0 0 0 0

0 0 0 0 0

4 0 8 1 1

0 0 0 0 1

0 0 0 0 0

0 0 0 0 0

1 0 0 0 0

1 0

6 5

83 2

0 0

32 4

0 0

4 0

30 8

1 5

0 0

0 55

0 1

323 1,420 671

14

304

3

11

229

32

1

68

17

Data source: Yomiuri Shimbun, Tokyo, Japan, March 12–­April 1, 2011.

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App e n d ix I 261

diction

Pol. Party

Total N, Actors

Total N, Transactions

N

2 1 0

1 24 0

5 92 21

2 1 1

29 46 19

0 3 2

0 11 2

2 0 60

419 396 595

8.88 8.39 12.60

320 370 295

8.24 9.53 7.60

7 2 0 0

3 4 0 0

12 22 3 11

4 2 0 0

2 46 0 1

3 0 1 0

4 0 0 0

2 0 0 0

163 284 58 89

3.45 6.02 1.23 1.89

123 243 53 86

3.17 6.26 1.37 2.22

0

0

0

0

0

0

0

0

0

0.00

0

0.00

0 1

0 0

3 53

1 3

0 1

1 3

1 3

2 60

84 406

1.78 8.60

66 287

1.70 7.39

0

3

46

1

1

0

0

0

131

2.77

97

2.50

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 1

0 0 0

0 0 0

0 0 3

0.00 0.00 0.06

0 0 2

0.00 0.00 0.05

0 2

0 0

19 19

2 1

96 9

1 2

1 0

0 2

224 173

4.74 3.66

214 151

5.51 3.89

0 0 0 0 0 0 0

45 1 0 2 10 7 1

57 0 1 3 89 160 0

145 0 0 0 15 6 1

81 8 1 2 3 6 8

27 0 0 0 5 0 0

43 0 0 0 30 35 1

1 2 0 0 0 0 0

478 49 46 141 221 244 97

10.12 1.04 0.97 2.99 4.68 5.17 2.05

458 39 41 147 206 236 70

11.80 1.00 1.06 3.79 5.31 6.08 1.80

1 0 0 0 0

0 0 0 0 1

1 0 16 5 2

0 0 0 0 0

0 0 1 1 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 2

45 6 32 18 55

0.95 0.13 0.68 0.38 1.17

40 6 24 12 50

1.03 0.15 0.62 0.31 1.29

0 1

0 0

21 3

0 0

3 0

0 0

0 0

0 0

181 83

3.83 1.76

171 75

4.40 1.93

17

102

664

185

364

49

131

133

4,721 100.00

3,882

100.00

Lo

In te r

ca l

ip

Na tio na l

al

na tio na Na l tio na l Pr ef ec tu ra l Re gi on al M un ic ip al Lo ca l

Private

Comfort.indb 261

%

N

%

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262 App e n d ix I

TABLE I.6.4 . Types of Transactions Reported in 2015 Nepal Response and Recovery System, by Jurisdiction and Funding Sector

In te r

Types of Transactions

1 Emergency response 2 Communications/IT 3 Coordination: response/ recovery 4 Medical care/health 5 Damage/needs assessment 6 Certification of deaths, est. 7 Earthquake assessment/research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief: food, shelter, clothing 11 Donations: money, goods, services 12 Building inspection 13 Building code issues 14 Repair: roads, bridges, railroads 15 Repair/restore utilities 16 Repair/reconstruction/recovery 17 Transportation/traffic 18 Hazardous materials release 19 Legal/enforcement/fraud 20 Political dialogue/legislation 21 Business recovery/banking 22 Economic/business issues 23 Visits by officials/condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans: private, international 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers 31 IT-­related actions Total

Nonprofit

na tio na Na l tio na l D i st ric t Su bd i st ric t In te rn at io na Na l tio na l D i st ric t Su bd i st ric t

Public

24 10 21

38 25 47

3 5 3

0 0 0

0 0 0

2 8 5

0 0 0

0 0 0

14 3 1 4 0 0 40

13 15 2 8 1 0 43

10 12 1 2 0 1 7

0 3 0 0 0 0 5

10 0 0 0 0 0 1

2 7 0 1 0 0 10

4 1 0 0 0 0 0

0 0 0 0 0 0 0

49

39

3

0

9

13

1

0

4 0 0 4 11 11 0 0 1 0 2 5 2 5 0 0 2

17 2 2 4 13 8 0 7 12 0 5 5 5 9 0 1 0

8 2 0 0 1 3 0 0 1 0 0 1 14 13 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1

3 0 0 0 9 0 0 0 4 0 0 3 1 0 0 0 0

2 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0

1 0 1

0 0 5

0 0 0

0 0 0

0 0 1

1 7 2

0 0 1

0 0 0

215

326

90

8

24

78

10

1

Data source: Kathmandu Post, Nepal, April 25–­May 16, 2015.

S L

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App e n d ix I 263

Total N, Actors

ic

t

Total N, Transactions

str di Su b

t ric i st D

In te r

na tio na l Na tio na l

Private

N

%

N

%

0 0 1

0 0 1

0 0 0

0 0 0

67 48 78

8.47 6.07 9.86

56 28 44

10.43 5.21 8.19

0 0 0 0 0 0 3

0 0 0 0 0 0 6

1 0 0 0 0 0 0

2 0 0 0 0 0 0

56 41 4 15 1 1 115

7.08 5.18 0.51 1.90 0.13 0.13 14.54

39 29 4 12 1 1 82

7.26 5.40 0.74 2.23 0.19 0.19 15.27

4

9

0

0

127

16.06

81

15.08

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0

0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

34 4 2 8 36 22 0 9 18 0 9 14 23 27 0 1 3

4.30 0.51 0.25 1.01 4.55 2.78 0.00 1.14 2.28 0.00 1.14 1.77 2.91 3.41 0.00 0.13 0.38

29 4 2 5 22 13 0 5 10 0 9 10 18 10 0 1 3

5.40 0.74 0.37 0.93 4.10 2.42 0.00 0.93 1.86 0.00 1.68 1.86 3.35 1.86 0.00 0.19 0.56

0 0 6

0 0 3

0 0 0

0 0 0

2 7 19

0.25 0.88 2.40

1 6 12

0.19 1.12 2.23

14

21

2

2

791

100.00

537

100.00

S L

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Chapter 7. Emergent Adaptive Systems: 1999 Marmara, Turkey; 1999 Chi Chi, Taiwan; 2005 Pakistan; and 2008 Wenchuan, China, Earthquake Response Systems TABLE I.7.1 . Types of Transactions Reported in August 17, 1999, Marmara, Turkey, Response

System, by Jurisdiction and Funding Sector

In te r

Types of Transactions

1 Emergency response 2 Communications/IT 3 Coordination: response, recovery 4 Medical care/health 5 Damage/needs assessment/ preparedness 6 Certification of deaths, est. 7 Earthquake assessment/research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief: food, shelter, clothing 11 Donations: money, goods, services 12 Building inspection 13 Building code issues 14 Repair: highways, bridges, railways 15 Repair/restore utilities 16 Repair/reconstruction/recovery 17 Transportation/traffic 18 Hazardous materials releases 19 Legal/enforcement/fraud 20 Political dialogue/legislation 21 Business recovery/banking 22 Economic/business issues 23 Visits by officials/condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans: private, international 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers

S

Total

Nonprofit

na ti St at ona e/ l Ce Pr ov ntra in la M ce un ic D ipal ist ric t In te rn a Na tio tio nal n Pr al ov in Re c e gi on M al un ic ip al

Public

30 12 13 0 14 14 38 113 129

3 1 14

8 2 8

2 1 6

4 5 27

0 0 1

1 1 4

0 0 7

4 0

32 42

11 28

1 5

1 3

5 0

10 6

1 0

3 1

5 1

2 2 0 0 5

12 31 9 31 73

10 2 7 10 75

4 1 0 1 12

0 1 0 1 5

0 1 0 0 2

0 1 0 3 20

0 0 0 0 1

0 0 1 0 1

0 0 0 1 3

80 117 132

21

20

17

36

6

3

6

0 0 0

8 5 3

10 1 0

0 1 0

0 0 0

0 0 0

4 6 1

0 0 0

0 0 0

1 2 0

3 3 0 23 0 4 0 2 15 0 2 0 3 0

17 37 5 24 7 33 2 10 33 23 3 0 4 4

17 12 1 16 12 4 0 1 11 16 3 0 0 4

2 12 0 1 0 1 0 0 2 34 0 0 0 0

1 1 0 0 0 3 0 0 0 31 0 0 0 0

0 1 0 1 0 1 0 0 1 0 0 0 0 1

4 7 1 2 8 11 0 0 1 5 1 1 0 3

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 1 0 0 0 0

0 11 0 7 23 2 0 1 0 0 0 0 0 2

1 0

12 0

14 0

2 1

1 0

2 0

2 0

1 0

0 0

5 0

217 716 553 119

86

41 169

10

16

77

Data source: Cumhuriyet, Istanbul, Turkey, August 17–­September 8, 1999. a State/Central: public agencies with national authority; National: nonprofit and private organizations operating at the national level.

L

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App e n d ix I 265

Political

In te r

na tio na Na l tio na l Re gi on al M un ic ip al Na tio na l

Private

Total Actors

Total Transactions

N

%

N

%

1 0 6

2 1 9

0 0 0

0 0 4

0 1 9

76 40 375

3.47 1.82 17.12

46 29 218

3.59 2.26 17.03

0 0

2 1

0 0

2 0

0 0

77 87

3.51 3.97

56 65

4.37 5.07

0 0 0 0 13

1 0 0 0 10

0 0 0 0 8

0 0 0 0 15

0 1 0 0 0

29 40 17 47 243

1.32 1.82 0.78 2.14 11.09

24 36 16 29 117

1.87 2.81 1.25 2.26 9.13

31

24

1

7

2

503

22.95

277

21.62

0 0 0

4 0 0

0 0 0

0 0 0

0 1 0

27 16 4

1.23 0.73 0.18

12 15 3

0.94 1.17 0.23

0 0 0 0 0 0 0 1 0 2 0 0 0 0

0 2 0 1 0 0 0 6 0 1 0 1 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 6 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 5 0 0 0 0 0 0 1 0

44 86 7 81 50 64 2 21 63 113 9 2 8 15

2.01 3.92 0.32 3.70 2.28 2.92 0.09 0.96 2.87 5.16 0.41 0.09 0.36 0.68

23 56 5 36 24 45 2 18 35 38 5 2 6 11

1.80 4.37 0.39 2.81 1.87 3.51 0.16 1.41 2.73 2.97 0.39 0.16 0.47 0.86

1 0

2 0

1 0

0 0

1 0

45 1

2.05 0.05

31 1

2.42 0.08

55

67

10

35

21

2,192

100.00

1,281

100.00

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266 App e n d ix I

TABLE I.7.2 . Types of Transactions Reported in 1999 Chi Chi, Taiwan, Response System, by Jurisdiction and Funding Sector

1 Emergency response 2 Damage/needs assessment 3 Cancel activities, service increase 4 Communications 5 Disaster relief 6 Medical care/health 7 Restore/remove/repair 8 Recovery 9 Mitigation 10 Government aids, services 11 Legal/enforcement/fraud 12 Donations/fund-­raising 13 Political activities 14 Religious ceremony 15 Earthquake assessment/ research 16 Other 17 Coordination Total

In te r

Types of Transactions

Nonprofit

na tio Na na l tio na l Co un ty M un ic ip al In te rn at io Na na l tio na l Co un ty M un ic ip al

Public

19 4 0

107 187 71

161 248 47

32 120 23

7 2 0

10 36 6

24 50 2

2 12 1

0 0 0 0 0 2 0 0 1 0 0 0

54 64 70 114 122 31 79 26 53 32 2 37

49 163 71 72 164 73 63 69 147 28 12 5

14 124 20 56 55 10 23 6 104 6 14 5

0 4 1 0 1 1 0 0 15 1 0 1

13 48 19 12 58 10 3 7 117 25 18 3

3 23 26 8 38 6 0 3 30 0 5 0

0 5 0 4 4 0 1 0 9 0 2 0

0 0

17 112

20 62

17 30

0 0

4 43

2 16

0 1

1,178 1,454

659

33

432

236

41

26

Data source: United Daily, Taipei, Taiwan, September 21–­October 12, 1999.

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App e n d ix I 267

Total Transactions

ic

ip

al

Total Actors

M un

In te r

na tio na Na l tio na l Co un ty

Private

N

%

N

%

0 0 0

2 26 14

9 27 19

1 0 0

374 712 183

8.39 15.97 4.11

195 394 145

7.43 15.02 5.53

0 0 0 0 2 0 0 1 0 0 0 0

16 27 1 8 27 5 0 19 69 1 0 0

14 7 25 4 5 2 0 2 3 1 0 0

2 0 19 0 0 1 0 0 6 0 0 0

165 465 252 278 476 141 169 133 554 94 53 51

3.70 10.43 5.65 6.24 10.68 3.16 3.79 2.98 12.43 2.11 1.19 1.14

91 277 143 166 266 104 113 83 384 51 37 38

3.47 10.56 5.45 6.33 10.14 3.96 4.31 3.16 14.63 1.94 1.41 1.45

0 0

9 14

2 8

0 0

71 286

1.59 6.42

34 103

1.30 3.93

3

238

128

29

4,457

100.00

2,624

100.00

S L

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268 App e n d ix I

TABLE I.7.3 . Types of Transactions Reported in 2005 Pakistan Earthquake Response System, by

Jurisdiction and Funding Sector

1 Emergency response 2 Communications 3 Coordination response/ recovery 4 Medical care/health 5 Damage/needs assess./prep. 6 Certif. of deaths, est. 7 Earthquake assessment, research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief: food, shelter 11 Donations: money, goods, services 12 Building inspection 13 Building code issues 14 Repair: roads, bridges, airport 15 Repair/restore utilities 16 Repair/reconstruction/ recovery 17 Transportation/traffic issues 18 Hazardous materials releases 19 Legal/enforcement/fraud 20 Political dialogue/legislation 21 Business recovery/banking 22 Economic business issues 23 Visits by officials, condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans (private, international) 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers 31 Relief/rescue/equipment 32 IT-­related transactions Total

S

In te r

Types of Transactions

NGO

na Na tion al tio na l Pr ov in ce D i st ric t Su bd i st ric t In te rn a Na tion al tio na l Pr ov in ce D i st ric t Su bd i st ric t

Public

22 66 24

23 122 44

14 43 15

10 21 8

0 1 0

9 4 2

0 19 5

0 9 3

0 0 1

0 0 0

38 17 2 0

46 18 13 14

34 9 2 1

68 8 0 0

2 2 0 0

20 4 0 0

15 1 0 0

13 0 1 1

17 0 0 0

1 0 0 0

0 1 55 84

7 4 63 154

7 2 33 73

1 1 19 24

0 0 1 2

0 0 9 25

0 2 14 23

0 0 5 9

0 0 10 3

0 0 0 0

0 0 2 2 5

1 1 9 14 14

2 0 0 1 1

1 4 0 1 0

0 0 0 0 0

0 0 0 1 0

0 0 0 0 4

0 0 0 0 1

0 0 0 0 0

0 0 0 0 0

61 0 0 0 0 0 22 2 7 0 0 3

48 0 4 0 0 0 13 2 9 0 1 6

4 0 3 0 0 0 3 4 10 0 4 1

0 0 2 0 0 0 3 5 1 0 0 1

0 0 1 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 0 0 0 0 1

3 0 1 0 0 0 0 2 1 0 0 3

1 0 0 0 0 0 1 2 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0

1 0 5 5

4 0 6 7

1 4 1 0

1 2 1 0

0 0 0 0

0 3 1 1

2 4 0 2

0 1 0 0

0 0 0 0

0 0 0 0

424

647

272

182

9

81

101

47

31

1

L

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App e n d ix I 269

Total Actors

In te r

ric

t

na tio na Na l tio na l Pr ov in ce D i st ric t

Private

N

Total Transactions

%

N

%

1 3 0

2 12 2

0 0 0

0 0 0

81 300 104

4.19 15.53 5.38

43 149 47

4.19 14.51 4.58

1 3 0 0

10 9 1 5

0 0 0 0

4 0 0 0

269 71 19 21

13.92 3.67 0.98 1.09

143 40 11 13

13.92 3.89 1.07 1.27

0 1 1 15

0 0 7 29

0 0 0 3

0 0 1 11

15 11 218 455

0.78 0.57 11.28 23.55

9 9 132 242

0.88 0.88 12.85 23.56

0 0 0 0 0

1 0 0 0 0

0 0 0 0 0

0 0 0 0 0

5 5 11 19 25

0.26 0.26 0.57 0.98 1.29

3 3 7 9 14

0.29 0.29 0.68 0.88 1.36

4 0 0 0 0 0 0 0 0 0 0 0

3 0 0 0 0 0 0 0 0 0 1 0

0 0 1 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0

125 0 12 0 0 0 42 17 28 0 6 15

6.47 0.00 0.62 0.00 0.00 0.00 2.17 0.88 1.45 0.00 0.31 0.78

67 0 9 0 0 0 11 12 15 0 3 8

6.52 0.00 0.88 0.00 0.00 0.00 1.07 1.17 1.46 0.00 0.29 0.78

0 0 0 0

4 0 1 1

0 0 0 0

0 0 0 0

13 14 15 16

0.67 0.72 0.78 0.83

7 6 8 7

0.68 0.58 0.78 0.68

29

88

4

16

1,932

100.00

1,027

100.00

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270 App e n d ix I

TABLE I.7.4 . Types of Transactions Reported in 2008 Wenchuan, China, Response

System, by Jurisdiction and Funding Sector

1 Emergency response 2 Communications/IT 3 Coordination: response, recovery 4 Medical care/health 5 Damage/needs assessment 6 Certification of deaths, est. 7 Earthquake assessment/ research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief: food, shelter, clothing 11 Donations: money, goods, services 12 Building inspection 13 Building code issues 14 Repair: roads, bridges, railroads, airports 15 Repair/restore utilities 16 Repair/reconstruction/ recovery 17 Transportation/traffic issues 18 Hazardous materials releases 19 Legal/enforcement/fraud 20 Political dialogue/legislation 21 Business recovery/banking 22 Economic/business issues 23 Visits by officials/condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans: private, international 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers Total

In te r

na Na tion al tio na l Pr ov in ci al

State Owned

In te r

Types of Transactions

Public Institutional

na Na tion al tio na l Pr ov in ci a M un l ic ip al Na tio na l Pr ov in ci a M un l ic ip al Co un ty

Public

8 0 51

4 0 17

9 2 25

2 1 4

1 0 13

0 0 2

2 2 1

1 0 0

0 0 0

0 6 0

1 2 0

9 4 2 2

5 5 0 1

8 5 0 6

7 2 0 3

2 2 0 3

7 0 0 1

18 1 0 1

0 0 0 0

0 0 0 0

0 0 0 0

1 0 0 0

0 0 9

3 7 8

3 8 42

0 0 6

0 0 1

0 0 2

0 0 12

0 0 0

0 1 2

0 0 0

0 0 9

8

30

18

1

2

8

7

0

8

4

4

0 0 0

0 0 0

3 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

1 49

4 8

4 27

1 5

0 17

0 6

0 5

0 0

2 0

0 0

0 2

3 0 2 0 1 1 10 2 1 0 0 0

8 0 6 0 0 2 11 1 1 0 0 0

3 0 9 0 3 51 7 7 0 0 3 0

3 0 2 0 1 1 3 0 0 0 0 0

0 0 0 0 1 0 1 0 0 0 0 0

3 0 0 0 0 0 4 2 0 0 0 4

9 0 0 0 0 0 0 4 0 0 0 3

0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 1 0 0 0 0 1 0

0 0 0 0 1 1 0 0 0 1 1 0

2 0 0 0 0 2 0 2 0 0 0 0

0 0

0 0

0 0

0 0

0 0

2 0

0 1

0 0

0 0

0 0

0 1

163

121

243

42

43

41

66

1

15

14

26

Data sources: Electronic online sources, April 20–­May 11, 2013.

S L

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App e n d ix I 271

In te r

In te r

ci al

Total Actors

na Na tion al tio na l Pr ov in ci a M un l ic ip al

Private

na Na tion al tio na l Pr ov in ci a M un l ic ip al Co un ty

Nonprofit

N

Total Transactions

%

N

%

0 0 0

1 0 0

0 0 0

1 0 2

0 0 0

0 0 0

1 2 2

0 1 0

0 0 0

31 16 117

3.22 1.66 12.16

12 4 16

4.40 1.47 5.86

1 0 0 0

1 1 0 0

0 1 0 0

0 0 0 0

0 0 0 0

0 0 0 0

2 0 0 0

0 0 0 0

0 0 0 0

61 21 2 17

6.34 2.18 0.21 1.77

21 8 1 5

7.69 2.93 0.37 1.83

0 0 0

0 0 4

0 0 0

0 0 13

0 0 0

0 0 0

0 7 7

0 2 0

0 1 1

6 26 116

0.62 2.70 12.06

3 6 31

1.10 2.20 11.36

1

21

9

13

1

6

21

3

2

167

17.36

68

24.91

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

3 0 0

0.31 0.00 0.00

1 0 0

0.37 0.00 0.00

0 0

0 0

0 0

0 0

0 0

0 1

0 2

0 1

0 2

12 125

1.25 12.99

6 19

2.20 6.96

0 0 0 0 0 0 1 0 0 0 0 1

1 0 2 0 0 0 2 7 0 0 0 0

0 0 0 0 0 0 2 2 0 0 0 1

3 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 2 0 0 0 0

2 0 2 0 0 8 0 3 0 0 0 0

1 0 0 0 0 2 0 1 0 1 0 0

0 0 4 0 0 1 0 0 0 0 1 0

39 0 27 0 7 70 41 33 2 2 6 9

4.05 0.00 2.81 0.00 0.73 7.28 4.26 3.43 0.21 0.21 0.62 0.94

14 0 11 0 3 10 14 11 1 1 3 2

5.13 0.00 4.03 0.00 1.10 3.66 5.13 4.03 0.37 0.37 1.10 0.73

0 0

0 0

0 0

0 2

0 0

0 0

0 0

0 0

0 0

2 4

0.21 0.42

1 1

0.37 0.37

4

40

15

34

1

10

59

12

12

962

100.00

273

100.00

S L

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272 App e n d ix I

Chapter 8. Nonadaptive Systems: 2001 Bhuj, Gujarat, India, Earthquake; 2004 Sumatra, Indonesia, Earthquake/Tsunami; and 2010 Haïti Earthquake Response Systems TABLE I.8.1 . Types of Transactions Reported in 2001 Bhuj, Gujarat, India, Response System, by

Jurisdiction and Funding Sector

1 Emergency response 2 Communication/IT 3 Coordination: response/ recovery 4 Medical care/health 5 Damage/needs assessment/prep. 6 Certification of deaths, est. 7 Earthquake assessment, research 8 Security/prevention of looting 9 Housing issues 10 Disaster relief: food, shelter, clothing 11 Donations: money, goods, services 12 Building inspection 13 Building code issues 14 Repair: roads, bridges, rail, airports 15 Repair/restore utilities 16 Repair/reconstruction/recovery 17 Transportation/traffic issues 18 Hazardous materials releases 19 Legal/enforcement/fraud 20 Political dialogue/legislation 21 Business recovery/banking 22 Economic/business issues 23 Visits by officials/condolences 24 Education issues 25 Government assistance 26 Insurance-­related issues 27 Loans: private, international 28 Psychological/counseling services 29 Fund-­raising/account setup 30 Volunteers

S

Total

L

t ric i st D

na tio Na na tio l na l St at e

In te r

i st

ric

t

Nonprofit

D

In te r

Types of Transactions

na tio Na na tio l na l St at e

Public

12 11 15

14 49 73

4 10 25

0 7 2

0 3 3

1 10 17

0 0 0

0 0 2

3 3 0 3 0 0 15

15 16 1 20 3 1 20

22 3 2 2 1 2 23

2 1 0 0 0 1 1

2 0 0 0 0 0 5

5 2 0 4 0 0 14

2 1 0 0 0 0 0

0 0 0 0 0 0 1

45

37

32

12

15

17

2

1

0 0 0

5 3 1

1 0 0

5 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 2 1 0 0 0 0 0 0 0 0 0 0 0

12 8 11 5 1 21 1 0 14 1 7 2 0 1

5 5 3 0 2 5 0 0 2 2 4 0 0 0

0 0 2 0 2 5 0 0 0 1 0 0 0 0

1 0 2 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 1 2 0 5 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 4

6 4

6 2

1 1

2 1

5 4

0 1

0 0

114

352

163

43

34

87

6

4

Data source: Hindu, New Delhi, India, January 26–­February 15, 2001.

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App e n d ix I 273

ric i st D

In te r

Total Transactions

t

Total Actors

na tio na Na l tio na l St at e

Private

N

%

N

%

1 0 1

0 10 4

0 0 0

0 0 3

32 100 145

3.70 11.56 16.76

24 48 63

4.07 8.15 10.70

1 0 0 0 0 0 0

1 1 1 0 0 0 4

0 0 0 0 0 0 0

1 0 0 0 0 0 1

54 27 4 29 4 4 84

6.24 3.12 0.46 3.35 0.46 0.46 9.71

35 23 4 25 2 3 59

5.94 3.90 0.68 4.24 0.34 0.51 10.02

5

9

1

1

177

20.46

144

24.45

0 0 0

0 0 0

0 0 0

0 0 0

11 3 1

1.27 0.35 0.12

10 2 1

1.70 0.34 0.17

0 0 2 0 0 0 0 0 0 0 0 0 0 0

4 0 1 0 0 0 0 0 0 0 0 1 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0

22 15 22 5 5 32 3 0 22 4 11 3 1 1

2.54 1.73 2.54 0.58 0.58 3.70 0.35 0.00 2.54 0.46 1.27 0.35 0.12 0.12

14 14 20 5 3 18 2 0 19 4 7 2 1 1

2.38 2.38 3.40 0.85 0.51 3.06 0.34 0.00 3.23 0.68 1.19 0.34 0.17 0.17

4 0

2 0

0 0

1 0

27 17

3.12 1.97

22 14

3.74 2.38

14

39

1

8

865

100.00

589

100.00

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274 App e n d ix I TABLE I.8.2 . Types of Transactions Reported in 2004 Sumatra, Indonesia, Response System, by Jurisdiction and

Funding Secto

Types of Transactions 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

S L

29 30

Emergency response 9 14 Communication/IT 0 5 Coordination: response, 221 200 recovery Medical care/health 25 45 Damage/needs assessment, 8 28 preparedness Certification of deaths, est. 12 34 Earthquake assessment/ 7 20 research Security/prevention of 24 57 looting Housing issues 2 20 Disaster relief: food, shelter, 52 59 clothing Donations: money, goods, 179 80 services Building inspection 0 0 Building code issues 0 1 Repair: roads, bridges, 1 1 railroads Repair/restore utilities 4 9 Repair/reconstruction/ 22 49 recovery Transportation/traffic issues 19 27 Hazardous materials releases 0 0 Legal/enforcement/fraud 9 50 Political dialogue/legislation 36 102 Business recovery 1 6 Economic/business issues 10 10 Visits by officials/condol­ 103 75 ences Education issues 6 17 Government assistance 8 26 Insurance-­related issues 1 5 Loans: private, international 47 64 Psychological/counseling 2 13 services Fund-­raising/account setup 3 6 Volunteers 0 4 Total

Nonprofit

In te rn Na atio tio na l n Sp al ec ia Pr l Re ov g in io M cia n un l ic Re ipa ge l n Lo c y ca l In te rn Na atio tio na l n Sp al ec ia Pr l Re ov g in io M cia n un l ic Re ipa ge l n Lo c y ca l

Public

1 0 8

1 3 18

2 1 29

0 0 7

2 0 0

0 5 18

1 3 18

2 2 4

0 0 6

0 13 1

0 0 2

0 0 0

4 2

13 3

11 11

6 4

1 0

24 4

23 1

9 0

0 6

2 0

2 2

0 0

0 1

12 0

3 0

8 1

0 0

0 0

0 0

0 0

2 0

0 0

7 0

0 0

5

8

3

1

0

2

4

0

0

0

0

0

1 3

0 15

0 25

0 0

1 8

0 19

6 27

0 0

0 3

0 0

0 1

0 1

8

27

4

2

2

19

42

2

13

8

0

2

0 0 0

0 0 0

0 0 1

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 1

0 3

0 4

0 3

0 0

3 0

0 5

0 0

0 5

0 0

0 0

0 3

1 0 0 0 0 4 5

1 0 10 1 0 0 7

14 0 8 1 0 1 4

0 0 2 0 0 0 2

0 0 0 0 0 2 1

4 0 3 1 0 0 4

1 0 8 6 0 0 1

0 0 0 0 0 0 0

0 0 1 0 0 1 4

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

7 0 0 1 1

8 0 0 0 0

2 0 0 0 4

3 0 0 0 0

2 0 0 0 1

4 1 0 9 5

2 0 2 2 5

3 0 0 0 0

0 0 0 0 4

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

6 5

5 3

0 3

0 0

0 0

14 4

13 5

4 0

7 3

1 0

0 0

0 1

811 1,027 64 138 131

39

20

143 175

26

55

25

14

7

Data source: Jakarta Post, Jakarta, Indonesia, December 26, 2004–­January 16, 2005.

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App e n d ix I 275

Total Actors

In te r

na Na tion al tio na l Pr ov in cia l

Political

na Na tion al tio na l Sp ec ial Re Pr gi ov on in cia M un l ic ip al Lo ca l

Private

In te r

oc al

nd Total Transactions

N

%

N

%

0 0 0

0 0 29

2 21 10

0 2 0

0 3 1

0 6 0

0 0 1

0 0 0

0 0 0

0 0 0

34 64 573

1.13 2.13 19.11

24 36 261

1.45 2.17 15.72

0 0

0 0

0 1

2 0

0 0

4 0

0 0

0 0

1 0

0 0

172 70

5.74 2.33

115 48

6.93 2.89

0 0

1 0

4 0

0 0

0 0

1 0

0 0

0 0

1 0

0 0

85 29

2.83 0.97

69 15

4.16 0.90

0

0

1

0

0

0

0

0

1

23

129

4.30

68

4.10

0 1

0 2

1 4

0 0

0 0

0 0

0 0

0 0

0 1

0 0

31 220

1.03 7.34

17 134

1.02 8.07

2

33

27

8

1

2

1

0

1

0

461

15.37

253

15.24

0 0 0

0 0 0

1 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

1 1 3

0.03 0.03 0.10

0 1 3

0.00 0.06 0.18

0 3

1 8

0 7

0 0

0 0

0 0

0 0

0 0

0 0

0 0

17 110

0.57 3.67

9 56

0.54 3.37

0 0 0 0 0 0 0

5 0 0 0 2 1 0

6 0 0 1 8 2 0

0 0 0 0 0 0 0

0 0 0 0 1 1 0

0 0 0 0 0 1 0

0 0 0 0 0 2 0

0 0 0 0 0 0 2

1 0 0 0 0 0 1

0 0 0 23 0 0 0

79 0 91 171 18 35 209

2.63 0.00 3.03 5.70 0.60 1.17 6.97

47 0 59 86 12 25 81

2.83 0.00 3.55 5.18 0.72 1.51 4.88

0 0 0 0 0

1 0 0 7 0

3 0 5 0 1

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

2 0 0 0 0

0 0 0 0 0

60 35 13 130 36

2.00 1.17 0.43 4.33 1.20

38 21 7 75 28

2.29 1.27 0.42 4.52 1.69

0 1

6 0

12 1

4 0

0 0

4 0

6 0

0 0

0 2

0 0

91 31

3.03 1.03

51 21

3.07 1.27

S

7

96

118

16

7

18

10

2

11

46

2,999

100.00

1,660

100.00

L

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276 App e n d ix I

TABLE I.8.3 . Types of Transactions Reported in 2010 Haïti Earthquake, by Jurisdiction and

Funding Sector

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Emergency response Communication/IT Coordination: response, recovery Medical care/health Damage/needs assessment Certification of deaths, est. Earthquake assessment/research Security/prevention of looting Housing issues Disaster relief: food, shelter, clothing Donations: money, goods, services Building inspection Building code issues Repair: roads, bridges, railroads Repair/restore utilities Repair/reconstruction/recovery Transportation/traffic issues Hazardous materials releases Legal/enforcement/fraud Political dialogue/legislation Business recovery Economic/business issues Visits by officials/condolences Education issues Government assistance Insurance-­related issues Loans: private, international Psychological/counseling services Fund-­raising/account setup Volunteers Total

na tio na Na l tio na l M un ic ip al

In te r

In te r

Types of Transactions

Nonprofit

na tio na Na l tio na l Re gi on al a

Public

20 7 72 5 23 13 7 8 0 9 12 0 0 0 1 7 3 0 18 12 2 4 9 2 0 0 0 0 29 0

1 0 13 2 5 0 0 0 0 0 5 0 0 0 0 3 0 0 0 1 2 0 1 0 0 1 0 0 5 0

11 1 52 4 8 2 6 1 0 1 8 0 0 0 0 11 2 0 4 3 0 0 1 1 0 2 0 0 16 0

1 0 3 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 4 0 0 0 1 0 0 0 0 0 5 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0

263

39

134

17

3

1

Data source: Caribbean News Online, January 12–­February 3, 2010. a Region in coding the organizational response to the Haïti network indicates Caribbean region, that is, other island states in regional proximity to Haïti. This is a distinct category that is used only for the Haïti response system. The rationale is that these small states are linked not only by geographic proximity, but also by economic, cultural, and political exchanges.

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App e n d ix I 277

Total Actors

In te r

na tio na l Re gi on al a

Private

Total Transactions

N

%

N

%

5 0 2 2 1 0 0 1 0 1 0 0 0 0 0 2 0 0 0 0 0 1 1 0 0 0 0 0 2 0

0 2 1 1 2 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0

38 10 143 15 39 16 13 10 0 12 26 0 0 0 1 23 5 0 28 16 4 5 14 3 0 3 0 0 61 0

7.84 2.06 29.48 3.09 8.04 3.30 2.68 2.06 0.00 2.47 5.36 0.00 0.00 0.00 0.21 4.74 1.03 0.00 5.77 3.30 0.82 1.03 2.89 0.62 0.00 0.62 0.00 0.00 12.58 0.00

32 6 61 12 21 14 13 7 0 10 19 0 0 0 1 9 4 0 22 12 1 4 11 3 0 2 0 0 39 0

10.56 1.98 20.13 3.96 6.93 4.62 4.29 2.31 0.00 3.30 6.27 0.00 0.00 0.00 0.33 2.97 1.32 0.00 7.26 3.96 0.33 1.32 3.63 0.99 0.00 0.66 0.00 0.00 12.87 0.00

18

10

485

100.00

303

100.00

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APPENDIX II

Sources of Electronic Data, 2013 Lushan Earthquake TABLE II.1.

Sources of Electronic Data for Network Analysis, Lushan Earthquake, April 20, 2013

Source

Dates

163 News

2013: 4/21; 4/22; 4/22; 4/23; 4/23; 4/26; 5/1; 5/2; 5/4 5/13; 5/15 2013: 5/14 2013: 5/10 2013: 5/7 2013: 4/25 2013: 4/24; 5/14 2013: 5/1; 5/4; 5/8 2013: 4/23 2013: 4/24 2013: 9/19 2013: 5/7 2013: 4/28 2013: 4/25 2013: 4/23 2013: 5/19 2013: 4/22 2013: 5/3 2013: 5/7 2013: 4/30 2013: 5/6 2013: 4/22; 4/23; 4/24; 4/25; 4/26; 4/23; 4/22; 4/24 2013: 5/13 2013: 4/21 2013: 4/22 2013: 4/22; 4/24; 4/24; 4/26; 4/27; 4/28; 5/7 2013: 4/23 2013: 4/29 2013: 4/30; 4/30; 4/30; 4/30; 4/30; 5/3 2013: 4/20; 4/21; 4/21; 5/5 2013: 4/22 2014: 03/25 2013: 4/22; 4/23 2013: 4/22 2013: 4/21 2013: 4/23 2013: 4/22; 4/25 2013: 5/20 2013: 4/25

21-­SUN AnyChem.com Baoan Daily Baoan News BBS Beiwei Net Bioon News Blmik.com Blog CaaC News CCID Net CCIN News ccm-­1 CCTV Net Chengdu government China Economy China.Com.CN China Aviation Industry of CI China Byte China Daily China Economy Net China Foundation Center China Mobile China News China-­Sichuan Foundation for Poverty China Youth Development Foundation Chinese Red Cross Foundation CPC.People.com Cww Daodianzui DongbeiWang Finance.ifeng.com Fisen.com Gold.cnfol Guangming News Guizhou Daily Guizhou Xinxi

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280 App e n d ix I I TABLE II.1.

(continued)

Source Hefei 365 News Hexun News House.China.Com.Cn Huaxun ICEO ifeng Jiangxi News Net Jiankang diyizhan Jieju Net Jinshi Net Kaixian Lanzhhou government Ministry of Justice of PRC Ministry of Land Resource, PRC National Library of China nd.fjsen.com News.CN News, Jiangsu Provincial Com. Com­ munist CP People.CN PR newswire Qianlong Qinghai News Red Cross Society of China Reteng Shanxi News Shengyang Net Shenzhen News Sichuan Online Sichuan Provincial People’s Government Sina Blog Sina News

Souhu news Taizhou.com.cn TenCent Ministry of Public Security of the People’s Republic of China People’s Government of Henan Province Wuzhou government www.caijing.com.cn www.chinanpo.gov www.news.CN Xinhua Net Xinmin.Cn Xueqiu Yuyao News Zhejiang Online

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Dates 2013: 4/25 2013: 4/22; 4/23; 4/28 2013: 4/25 2013: 4/23 2013: 5/20 2013: 4/22; 4/22; 4/23; 4/23; 4/26; 4/27; 5/9; 5/17 2013: 4/24; 5/2 2013: 4/22 2013: 4/24 2013: 4/22 2013: 4/24; 5/8 2013: 4/22 2013: 5/14 2013: 5/6 2013: 5/22 2013: 4/28 2013: 4/21; 4/24; 4/23; 4/23; 4/24 2013: 4/26 2013: 4/22; 4/23; 4/23; 4/26; 4/26; 4/27; 5/7; 5/8; 5/30 2013: 4/26; 4/28 2013: 4/30 2013: 4/27 2013: 4/22; 4/24; 4/29 2013: 4/30 2013: 5/3 2013: 4/24 2013: 4/20 2013: 5/3; 5/6; 5/6 2013: 4/20; 4/24 2013: 4/21 2013: 4/20; 4/21; 4/21; 4/21; 4/22; 4/22; 4/23; 4/23; 4/23; 4/24; 4/27; 5/2; 5/5; 5/5; 5/20; 5/1; 4/22; 4/23; 4/23; 4/24; 4/28; 5/2; 5/3; 5/14 2013: 4/25; 4/25; 4/22; 4/23; 5/4; 5/3 2013: 4/30 2013: 4/20; 4/21; 4/22; 4/23; 4/27; 5/8 2013: 4/22 2013: 4/23 2013: 4/24 2013: 5/22 2013: 5/13 2013: 5/22 2013: 4/22; 4/22; 4/22; 4/22; 4/23; 4/24; 5/3; 5/5; 4/20; 4/20; 5/14; 4/24; 4/28; 5/6 2013: 5/13; 5/6 2013: 5/14 2013: 4/23 2013: 4/26

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NOTES

Chapter 1. Redefining Risk on a Global Scale 1. The following table indicates the estimated losses of the most costly natural disasters occurring from 1985 to 2017:

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Mexico City, Mexico, earthquake Kobe, Japan, earthquake Kocaeli, Turkey, earthquake Bhuj, India, earthquake Bam, Iran, earthquake Indian Ocean tsunami Hurricane Katrina, US Pakistan earthquake Wenchuan, China, earthquake Haïti earthquake Tohoku earthquake and tsunami Christchurch, New Zealand, earthquake Superstorm Sandy, US Nepal earthquake 2017 disasters, US Total

1985 1995 1999 2001 2003 2004 2005 2005 2008 2010 2011 2011 2012 2015 2017

Dead, Missing

Cost, US$ Billions

10,000 6,434 17,127 20,023 26,271 230,000 1,833 87,351 87,587 220,000 18,391 185 285 8,889 1,000

4.0 200.0 8.5 2.0 1.9 15.0 100.0 6.2 150.0 14.0 150.0 40.0 68.5 10.0 306.0

735,376

1,076.0

2. A scenario developed for a Mw = 7.05 earthquake on the Hayward fault documents the estimated social and economic costs for the San Francisco Bay Area. The development of this detailed scenario, titled “Haywired,” was led by Kenneth Hudnut and Dale Cox of the US Geological Survey and included a wide group of participants from interdisciplinary backgrounds. See https://www2.usgs.gov/natural_hazards/safrr/projects/haywired.asp. 3. This event occurred in Pittsburgh, Pennsylvania, on August 13, 2009. Interview, assistant vice president for facilities, systems, and maintenance, University of Pittsburgh Medical Center. 4. Development of the scenario, “Haywired,” US Geological Survey, represents the type of interactive, multidisciplinary exploration of risk to identify potential actions that would mitigate a serious hazard that cannot be eliminated. See again https://www2.usgs.gov/natural_hazards​ /safrr/projects/haywired.asp.

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282 n ote s to Ch a pte r 2

Chapter 2. Risk in Complex Systems 1. The account of entry to the United States by the 19 hijackers who executed the attacks of September 11, 2001, is cited by the Federation for American Immigration Reform (FAIR), http://​ www.fairus.org/issue/identity-and-immigration-status-of-9-11-terrorists, accessed May 8, 2017. 2. These discrepancies were reported by Coleen Rowley, FBI agent in Minneapolis who followed the case of Zacarias Moussaoui, suspected of aiding the 9/11 hijackers. See case study by Kearns et al. 2012. 3. San Francisco Department of Building Inspection, City and County of San Francisco, BORP Guidelines for Engineers, http://sfdbi.org/borp-guidelines-engineers, accessed May 12, 2017. 4. This program, funded by the Rockefeller Foundation, reached its full membership of 100 cities, worldwide, in May 2016. The program has focused on encouraging public/private partnerships to conduct critical risk assessments and mobilize local resources for reducing the specific risks to which a particular city is exposed. Please see http://www.100resilientcities.org/pages​ /100-resilient-cities-challenge. 5. The term “entropy” is used here as explained by Eric Smith (2008a) in his discussion of stability and change in complex systems. See above, chapter 1.

Chapter 3. Assessing Risk in Complex Systems 1. This reconnaissance trip was organized by professors of Japanese universities who were monitoring the risk of exposure to radiation in Fukushima and the impact of exposure on the residents of the city. As an international visitor, I was grateful to be included in the delegation. Fukushima, Japan, September 1, 2014. 2. The graduate student researchers are Jee Eun Song, Nauman Afridi, and Jay Rickabaugh, all advanced doctoral students at the Graduate School of Public and International Affairs, University of Pittsburgh, in 2017. The coding and analyses were further checked by Dr. Karen T. Cuenco, experienced data analyst, as an outside check on the reliability of the coding and analytical methods.

Chapter 4. Risk in Practice 1. This project, Developing Community Resilience to Disaster in the Caribbean Region, was funded by two small research grants from the Widgeon Foundation, 2012–14. The project created a partnership among three universities—l’Université Quisqueya, l’Université d’Etat d’Haïti, and the University of Pittsburgh—to develop skills for risk assessment to reduce seismic risk among local Haïtian students. The project was initiated by the Center for Disaster Management, University of Pittsburgh, http://www.cdm.pitt.edu/Projects/Community-Resilience-Haiti. 2. Table 4.1 adapts the table of assessment indicators for seismic response systems presented in an earlier study (Comfort 1999a, 65–67).

Chapter 5. Toward an Auto-­adaptive System 1. In the Chinese administrative structure, counties are subordinate to municipalities, and municipalities are subordinate to provinces. Lushan County is one of several counties included in the larger municipality of Ya’an, which is one of several municipalities within Sichuan Province. 2. The initial coding of news articles was done by a student research team at Nanjing Univer-

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n ote s to Ch a pte r 7 283

sity, Nanjing, China, working under the supervision of Dr. Haibo Zhang. Subsequent coding and data analysis was done by a team of GSPIA graduate student researchers working under my supervision at the Center for Disaster Management, Jee Eun Song, Nauman Afridi, and Jay Rickabaugh. A third check of methods and analysis was done by Karen Cuenco. I gratefully acknowledge the contributions made by this group of young professionals.

Chapter 6. Operative Adaptive Systems 1. The earthquake magnitude was reported as Mw = 7.2 in Turkish newspapers (Cumhuriyet, November 1999). Variation in estimates of earthquake magnitude occur, as seismic movement is measured by records reported from multiple locations. 2. Changes in building design and construction following the 1999 Duzce earthquake were confirmed by personal observation in a visit to the small city of Kaynasli, less than 15 kilometers from Duzce, in early June 2014. This visit, at the invitation of city officials in Kaynasli, demonstrated the substantive change in practice, planning, construction, and public education regarding seismic risk in this small city since the 1999 earthquake. 3. Estimated Padang population, 2009, Indonesian census. 4. The actual number of lives lost is almost never known in disaster events, and estimates varied from 383 deaths in the city of Padang (EERI 2009) to 1,117 deaths for the wider region of West Sumatra (Sengara et al. 2010). 5. The articles for this study were selected from Antara, the leading newswire feed for assorted newspapers across West Sumatra and Indonesia, through a search of the Nexus database for the first three weeks following the September 30, 2009, earthquake. All articles were returned based on variations of the search term “Padang earthquake.” In total, 129 articles were obtained for week 1 (September 30 to October 6, 2009) while 153 articles were obtained for weeks 2 and 3 combined. The data were then coded for interactions based on explicit transactions that occurred. In each case, an initiating organization was recorded, and if there was a corresponding responding organization, it was also recorded. In addition, any organization that carried multiple names or abbreviations was classified as a single organization. Each organization was further classified by funding status (public, private, or nonprofit) and by jurisdiction (local, provincial, national, or international). This process of coding was conducted by three different individuals and then reviewed by the “Socioteam” at the Center for Disaster Management at the University of Pittsburgh (i.e., seven additional doctoral and postdoctoral researchers) to validate systematic social network coding and to minimize threats to validity. 6. Personal observation, Padang, Indonesia, October 8–12, 2009. 7. This section on Nepal draws heavily on an article published in Earthquake Spectra for a special issue on the Nepal earthquakes, Comfort and Joshi 2017.

Chapter 7. Emergent Adaptive Systems 1. These figures were first cited by Kandilli Observatory and Earthquake Research Institute, Bogazici University, Istanbul, Turkey, and later reported in EERI 1999. 2. Initially reported on the Kandilli Observatory website, these figures were later cited in EERI 1999. 3. EERI 1999. 4. Nilgun Okay, 2005, Risk Profile and Disaster Management System, Turkey, World Bank Indicators—Natural Disaster Risk Management Program (Washington, DC: World Bank). 5. Personal communication, member, International Association for Earthquake Engineering, Ankara, September 1999.

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284 n ote s to Ch a pte r 7

6. I acknowledge, with thanks and appreciation, Dr. Sitki Corbacioglu, who graciously granted me use of data he collected for the 1999 Marmara earthquake from the same source, Cumhuriyet, for the same period, August 18–September 7, 1999, using the same format, after I discovered that data I collected for this event had been corrupted in storage over a 15-­year period. 7. A set of 27 expert interviews with government officials, practicing managers of public and nonprofit organizations, and Turkish academic researchers was conducted in Istanbul, the disaster-­affected cities in the Marmara region, and the capital city of Ankara, September 9–15, 1999. Interviews with local managers were conducted in Turkish, with a native speaker as interpreter. For reasons of professional confidentiality, names of interviewees are not provided. This reconnaissance study was supported by the US National Science Foundation and the Research Center for Urban Safety and Security, Kobe University, Kobe, Japan. 8. This section draws largely on an account from a previous article, Comfort 2000. 9. These measurements of the earthquake were presented in a briefing on the September 21, 1999, Chi Chi earthquake given by Dr. Chin-­Hsiung Loh, director, National Center for Earthquake Engineering Research, Taipei, Taiwan, October 3, 1999. 10. These statistics were reported by the Taiwan Ministry of Interior, October 21, 1999, as cited in the EERI special report The Chi-­Chi, Taiwan Earthquake of September 21, 1999, December 1999. The report is published on the EERI web page, http://www.eeri.org/Reconn/TaiwanFinal .htm. 11. I acknowledge Dr. Wen Jiun Wang with warm thanks and appreciation for granting me the use of data that she had collected and translated from United Daily, September 21–October 12, 1999, after I discovered that data I had collected for the 1999 Chi Chi, Taiwan, earthquake had been corrupted after 15 years in storage. 12. Appendix I, table I.7.2 includes only 17 types of transactions instead of 30, as coded for the other 11 response systems in this study. Yet 12 of the 17 types of transactions are essentially the same as types included in the longer list, with the remaining five types broadly encompassing categories that are broken out more specifically for the other earthquake systems. 13. Briefing on 921 Chi Chi earthquake, J.C.H. Lin, director, National Science and Technology Program for Hazard Mitigation, National Taiwan University, Taipei, Taiwan, October 2, 1999. 14. Yeh, Wei-­Chuan, director, Department of Overall Planning, Research, Development and Evaluation Commission, Executive Yuan. Taichung, Taiwan, October 6, 1999, 9:30 a.m. 15. Interview, Webster Kiang, vice chairman, Research, Development and Evaluation Commission, Executive Yuan, Taichung, Taiwan, October 6, 1999, 11:00 a.m. 16. The types of transactions were coded for Pakistan using the same list of 30 types applied in the content analysis of news reports for the 1999 Marmara, Turkey, response system. For Pakistan, two additional types were identified separately: categories 31: relief/rescue equipment and 32: information technology-­related issues. In later analysis, category 31 will be combined with category 16: repair/reconstruction/recovery; and category 32 will be combined with category 2: communications, for consistency in coding among the earthquake response systems. 17. This section draws on an earlier paper, L. K. Comfort, 2009, “The Dynamics of Disaster Recovery: Resilience and Entropy in Earthquake Response Systems,” paper presented at the International Disaster and Risk Conference, Chengdu, China, July 13–15. 18. The newspaper reports from China Evening Net were obtained from a digital archive of news reports on the 2008 Wenchuan earthquake created by Sichuan Administration College, Chengdu, China, and translated by a team of bilingual graduate students at Nanjing University, under the direction of Dr. Haibo Zhang, professor and director, Center for Management of Social Risk and Public Crisis, Nanjing University, Nanjing, China.

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Chapter 8. Nonadaptive Systems 1. This account draws heavily on an earlier chapter, Comfort 2004. 2. These personal observations were reported in interviews and meetings with local managers and district collectors on two field trips to Gujarat, February 2001 and May 2002. 3. Personal communication, Gandhidham, Gujarat, May 2002. 4. The scientific community has reported magnitudes ranging from 9.0 to 9.7 on the moment magnitude scale for this earthquake. The magnitude of record is usually determined by compiling the magnitudes recorded at different sites, and then recalculating the magnitude based on the full set of information. This process is still underway. This earthquake was, however, the second largest instrumentally recorded earthquake in geologic history. 5. This section draws heavily on an earlier chapter, Comfort 2007. 6. Personal communication, Banda Aceh, Indonesia, March 9, 2005. 7. Personal observation, Banda Aceh, Indonesia, March 10, 2005. 8. The URL is http://www.eeri.org/lfe/clearinghouse/sumatra_tsunami/observ1.php. 9. This section relies heavily on sections from an earlier paper, L. K. Comfort, M. D. Siciliano, and A. Okada, 2010, “Risk Resilience, and Recovery: The Haiti Earthquake, January 12, 2010,” Télescope, Spring–Summer, 37–58 (published in French). 10. These figures were cited at the cluster meetings for education, food, and health as part of the Rapid Interagency Needs Assessment following the January 12, 2010, earthquake. United Nations Logistics Base, Port-­au-­Prince, Haïti, March 8, 9, and 12, 2010. 11. Personal observation, Port-­au-­Prince, Haïti, March 8, 2010.

Chapter 9. Evolving Patterns of System Response 1. See, for example, the series of special issues published by Earthquake Spectra to document the findings of reconnaissance teams on major earthquakes around the world: https://www.eeri .org/projects/learning-from-earthquakes-lfe/lfe-reconnaissance-archive/. 2. Approximately 92% of the area of Turkey is exposed to seismic hazards, with the greatest risk posed by the North Anatolian fault, which crosses virtually the entire nation from east to west (Kandilli Observatory, Bogazici University, Istanbul, 1999; Derin N. Ural, PhD, “Emergency Management in Turkey: Disasters Experienced, Lessons Learned, and Recommendations for the Future.” Center of Excellence in Disaster Management, Istanbul Technical University, Istanbul, Turkey, 2009. 3. As explained in chapter 6, these results for the Wenchuan earthquake analysis must be viewed with caution, as the data source is China News Net (2008), a government-­sponsored newspaper. Yet this analysis represents a systematic effort to collect empirical data from sources publicly currently available.

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INDEX

Bold typeface denotes major earthquakes/disasters in this study. Tables and figures are denoted by “t” or “f ” following the page number. Aceh Province, Indonesia, 51, 74, 180f, 189– 91, 197 action: alignment in space and time and, 36– 37; collectivity and, 20, 24–25, 42, 90–91; educating next generation for, 252; fitting goals to action and 33–34; flexible structure for, 30–33; knowledge and, 8–9, 12, 17–19; networks of, 59–62; operational levels for, 28; shifting fields of, 28–30; strategic action field, 30 adaptation, 24–25, 67–68, 178; capacity, comparative analysis of, 208–34; changing conditions and, 47–48; classes of, 67– 68, 68t; Complex Adaptive Systems of Systems (CASoS) process and, 9–13, 10f; complex systems and, 47; decision making and, 4, 8; dynamic nature of, 167, 211; internal process in operational systems and, 211; measures of, 178, 210; self-­ organization and, 176–77; technical supports for, 12; tests of, 178; updated concept of, 178. See also resilience adaptation, classes of, 67–68, 68t, 236–40; auto-­adaptive systems and, 68–69, 68t, 69t, 76–91; comparison of, 208–34; emergent adaptive systems and, 68t, 71– 72, 72t, 134–75; nonadaptive systems and, 68t, 73–75, 73t, 176–207; operative adaptive systems and, 68t, 69–71, 71t, 92– 133; system coherence in, 236–40. See also specific classes of adaptation adaptive resilience. See resilience Arthur, Brian, 251 assessment of risk. See risk assessment auto-­adaptive systems, 69t, 76–91, 214–16, 237; adaptation to changing conditions and, 77, 78; characteristics of, 68–69, 69t, 76–77; continuing challenge of developing of, 90–91; External/Internal

(E/I) index values for, 214–16, 215t, 216t, 237, 238t; Lushan, China and, 50, 51, 67t, 68, 68t, 69, 69t, 78–90, 214–16; information interchange and management in, 77– 78, 90–91; internal subsystems in, 77–78; jurisdictional authority and funding sources in, 237, 238t; movement toward, 68–69, 69t, 76–80; risk awareness and preparedness activities in, 80–81, 82, 88– 89; seismic monitoring in, 77–78; systems integration functions and, 77–78; volunteer groups in, 77, 78, 90. See also Lushan, China, earthquake (2013) Banda Aceh. See Sumatra, Indonesia, earthquake and tsunami (2004) Beck, Ulrich, 4, 24 betweenness centrality, 55, 57, 97. See also specific earthquake response systems Bhuj, Gujarat, India, earthquake (2001), 50, 51, 67t, 73t, 73,178–89, 228–30, 232t, 240; betweenness centrality and jurisdictions of organizations in, 185, 186f, 187t; building codes and, 181; cascading impacts of, 177; characterization of response and recovery system and, 183–86; corroborating assessment of, 187–88; damage to buildings and infrastructure by, 179–81; date of, 50, 178–79; deaths and losses from, 179, 182; External/Internal (E/I) index for, 228–30, 229t, 232, 232t, 240t; information technology and, 179, 186, 187–89, 206; initial conditions for, 178–83; location of areas affected by, 179, 180f; magnitude of, 50, 51, 179, 182; map of area of, 180f; national disaster law and, 179; network analysis of, 185–86; network diagram of organizations in, 185, 186f; nonadaptive system in, 68t, 73–74,

299

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300 I n d e x

Bhuj, Gujarat, India, earthquake (cont.) 73t, 178–89; organizational capacity and, 181–83; organizations participating in response system and, 183–84, 183t, 185–86, 186f, 187t, 228–30; political/ethnic tensions and, 73–74, 243; preliminary classification of response system in, 67t, 68t; prior earthquake experience and, 209; rate of change of organizations participating in response system and, 184, 184f; satellite imagery, use of, 187–89; scale of operations for, 181–82; seismic awareness, deficiencies in, 182, 183, 184, 228; summary of response to, 188–89; transactions performed during response operations and, 184–85, 272t–73t boundaries, 36–37, 42, 46–48; complex, adaptive systems and, 46–48; crossing of, 6, 47; identification and, 54; networks and, 54, 60; space as boundary of risk and, 35–36, 42; systems and, 36–37, 42 building codes, 34, 64t; China and, 84, 88, 165–66, 173; Japan and, 114; Nepal and, 123, 125, 132; Turkey and, 71, 105, 141, 148, 149, 174, 233, 283n2 buildings: Building Occupancy Resumption Program (BORP) and, 32–33; design of, 4, 33–34; performance assessment for, 32–33 California: Hayward fault scenarios, 2, 281nn1, 4; Los Angeles, 3, 36–37; San Francisco Bay Area, 32–33, 35–36 cascading impacts, 2–3, 7, 13, 45, 115–16, 120–22, 177; communication disruption and, 61; escalating error and, 27 case studies. See field studies CASoS (Complex Adaptive Systems of Systems) engineering process, 9–13, 10f; first loop of (problem and model definition) and, 10–11, 10f; second loop of (designing and testing solutions and), 10f, 11; third loop of (field solution and monitoring) and 10f, 11 Castells, Manuel, 61, 75, 178 cell phones, 5, 17, 72, 138, 210; Duzce, Turkey, earthquake response and, 98; Lushan, China, earthquake response and, 78, 79, 80–81, 88, 89, 210; Nepal earthquake response and, 138, 243; Taiwan (Chi Chi) earthquake response and, 150, 174 change, 26–33; adaptation to, in operative adaptive systems and, 92–97, 132–33;

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control/order and, 31; focus of future states, informed by past record and, 247; information as energy and, 26–28, 48; information flow and, 60–61; in operating system parameters vs. environment and, 40–43; organizational adaptation driving and, 34; organizations participating in response systems and (see specific earthquakes); rate of change and, 39, 42, 246– 48; redesign, opportunities for, 30–31 chaos, 29 Chi Chi, Taiwan, earthquake (1999), 50, 67t, 68t,72t, 135–36f, 149–57, 223–24t, 227t, 239t; aftershocks from earthquake, 149; betweenness centrality and jurisdictions of organizations in, 153–55, 153f, 154t; cell phone use and, 150, 174; characterization of response and recovery system and, 150–55; corroborating assessment of, 155–56; date of (September 21, 1999), 50, 149; deaths and damage from, 149–50; emergent adaptive system in, 68t, 71, 72t, 150–55; escalating impacts of, 61; External/Internal (E/I) index for, 223, 224t, 227t, 239t; initial conditions for, 149–50; international assistance in, 155, 223, 227; magnitude of, 50, 149, 173– 74; map of, 136f; National Emergency Plan and, 150; network of organizations in, 153f; openness to new information and, 155–57; organizations participating in response system and, 143t, 151–52, 151t, 153–55, 153f, 223, 227; rate of change of organizations and, 152, 152f; response system in, 67t, 68t; seismic awareness and, 150, 155, 156, 174; summary of response to, 156–57; Taiwan’s relationship with China and, 151–52, 223; technical infrastructure for communications and, 150– 51; time as factor in, 149; transactions performed during response operations of, 152–53, 266t–67t China: building codes in, 84, 88, 165–66, 173; China Earthquake Administration (CEA), 80; Longmenshan fault system and, 80, 81, 165; Lushan, Ya’an, earthquake (April 20, 2013), 50, 76–91; National Earthquake Plan and, 81, 88, 227; “one child” policy in, 166; paired assistance program in, 134; SARS epidemic in (2003), 173; Sichuan Province of, 51, 69, 72, 78, 80, 88, 139, 165, 166, 171, 174, 210, 216; Taiwan, relationship to, 151–52; Tangshan earthquake (1976), 165; Wen-

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chuan earthquake (May 12, 2008), 50, 138, 165–73; Yunnan Province in, 80. See also Lushan, China, earthquake (2013); Wenchuan, China, earthquake (2008) cluster system for humanitarian aid and, 123–24, 131, 158, 161, 163–64, 226 coding of interactions and, 54–55 cognition, distribution and sharing of, 26 cognitive energy, 37 cognitive machines, 11–12 coherence of system as a whole and, 212, 213, 236–37 Collaboration and, 65t collective action and, 20, 24–25, 42; boundaries to, 18; decisions aligned with, 34; jurisdictional scales and, 90–91; resources for, 69, 69t, 71t, 72, 72t, 73t; site-­specific factors in, 32–33; technology and, 244–45 collective problem-­solving and, 12 collective risk, threshold for, 44–45 common meanings, articulation of, 68, 70; auto-­adaptive systems and, 69t, 79, 90; emergent adaptive systems and, 72, 72t; nonadaptive systems and, 73t; operative adaptive systems and, 71t commons: knowledge commons, 30, 178, 247, 252; “Tragedy of the Commons, The” (Hardin), 24 communication, 15–17; adaptation and coordination and, 7; cell phones and social media for, 78, 79, 80–81, 89, 138, 210; channels for, 15–17, 20, 28, 138; components of, 27; disruption, cascading effects and, 61; environment and space for, 178; error and, 27; face-­to-­face and, 26; infrastructure for, 64t, 138, 174, 222; interactivity and, 69; physical means of, 26–27; real-­time, 5, 78, 79; scale and, 18–19, 27; technological changes and, 2–3, 5, 246; technological means of, 26–28, 79, 244– 45. See also decision making; information community: collective action and, 20, 24– 25, 32–33; constraints and dependencies in, 8; shared goals and, 25, 34, 62 community response, 1–2, 48–52; capacity for, 14, 56–57, 167. See also field studies comparative analysis, 49–50, 57–58, 208– 34 complex adaptive systems, 1–21; CASoS process and modeling of, 9–13, 10f; concepts in, 2–3; dual role of technology in, 14–15; information flow-­through and, 8–9, 209; information role in, 15–17; interacting di-

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mensions of, 9–15, 245; in practice and, 13–14; questions used in characterizing and, 19, 57–58; signals and boundaries in, 46–48; uncertainty and, 6 complex adaptive systems of systems, 20; CASoS process and, 9–13, 10f; initial conditions and risk in, 18–19; in practice, 13–14 Complex Adaptive Systems of Systems (CASoS) process, 9–13, 10f complex response systems. See response systems complex systems; aligning scales of operation in, 36–37; risk assessment in, 44–58; risk in, 22–43; theory, four functions in, 68–69, 69t; uncertainty and, 31 complexity: Complex Adaptive Systems of Systems (CASoS) process and, 9–13, 10f; dimensions of, 9–15 computational modeling, 37 computer hacking, 38 control: balance with disorder and, 30, 31; continuum of, 29 coping with risk: community actions for, 32–33; community capacity for, 18–19, 56–57; design for future action and, 33–34 costs: economic costs, 2, 281n1; indirect costs, 2; loss of life and, 2, 281n1; most costly earthquakes and, 2, 281n1. See also specific earthquakes/disasters culture, 9, 20, 65t, 245; Risk and Culture (Wildavsky and Douglas), 23; shared meanings and, 68, 245 data, 44–58; analysis of, 53–57; collection of, 11, 14; interpretation of, 14–15; management of, 247; sources for, 52–53 data sources, 52–57, 247; documentary reports and, 52; field observations and interviews and, 52–53, 56–57; newspaper reports and, 52, 54, 57 deaths from natural disasters, 2, 281n1. See also specific earthquakes decision making, 28–30; changing environments for, 28–30; chronology of, 56; cognitive machines and, 11–12; under conditions of uncertainty, 3, 208–9; continuous evolution of, 11–12; dimensions for, 28; modeling as support for, 39; multiple dimensions in, 66; organizational and policy processes and, 12–13; real-­time information and, 12; recognition priming and, 18; shared risk and, 3;

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decision making (cont.) technical infrastructure and, 12, 37–39, 246; time available for, 18 decisions: adaptation and, 8; decision-­ support systems and, 37–38; informational basis of, 14–15, 37–38; quality of, 3, 8, 13–15 design, 33–37; fitting goals to action and, 33–34; redesign and, 4, 31–32, 133, 156; uncertainty and, 34–37 distributed cognition, 26 documentary reports, 52–54 Douglas, Mary, 23 Duzce, Turkey, earthquake (1999), 50, 67t, 68t,70–71t, 92–3f, 96–105, 139, 217–18t, 221, 239t; betweenness centrality and jurisdictions of organizations in, 102f, 103, 103t; cell phones and amateur radio in, 98; characterization of response and recovery system and, 98–104; corroborating assessment of, 104; date of, 50, 97; deaths and losses from, 97; External/­ Internal (E/I) index for, 217, 219t, 221t, 239t; initial conditions for, 97–98; location, and availability of response services and, 97–98, 217; magnitude of, 50, 93, 97, 283n1; map of area of, 93f; multiorganizational response in, 98; National Disaster Law and, 98, 105; network diagram of organizations in, 102f; operative adaptive system in, 68t, 70, 71t, 97–105; organizations participating in response system and, 99, 100t, 102–4, 102f, 103t, 217; preliminary classification of response system in, 67, 67t, 68t; prior earthquake experience (Marmara) and, 67, 96, 97, 104, 132–33, 139, 217; rate of change of organizations in response system and, 99, 101t; seismic awareness and, 98–99, 104–5, 217, 233; space as factor in, 97–98, 105; summary of response to, 104–5, 132–33; time as factor in, 104; transactions performed during response operations and, 99–103, 256t–57t; Turkish Red Crescent in, 98, 103 Earthquake Engineering Research Center (EERI), 197, 209 earthquakes: costs of (1985–2017), 2, 281n1; general characteristics and timing of, 50– 52; learning from, 209–10; list of earthquakes covered in this study, 50; paired examples of, 209–10; Ring of Fire and, 50; study period (1999–2015), 19, 49–50,

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66; time span between, 249; timing of field studies of, 51–52; transfer of knowledge to other hazards and, 2, 249–50. See also field studies; specific earthquakes by place name electrical power systems, 5–6; CASoS analysis of, 10–11; monitoring of, 9 emergent adaptive systems, 68t, 71–72, 72t, 134–75, 233, 238–39; capacity for adaptation in, 227; changes over period of study of, 138–40; characteristics of, 134–35, 233; Chi Chi, Taiwan, earthquake (1999) and, 50, 67t, 138, 149–57; communication in, 135, 138–39, 174, 233; distinguished from operative adaptive systems, 135; External/Internal (E/I) index values for, 222–28, 224t–25t, 227t, 239–40, 239t; external/internal relationships in, 139; field study cases of, 138–40; flexibility in organizational processes, 71; general concept of, 135; information, role in, 135–38; jurisdictional authority and funding sources, analysis of, 239–40, 239t; knowledge base in, 135–38; Marmara, Turkey, earthquake (1999) as, 50, 67t, 138, 140– 49; methods of analysis and, 139; openness to new information and, 71, 72t; organizational infrastructure in, 138, 174; Pakistan earthquake (2005) as, 50, 67t, 138, 157–65; rate of organizational change and, 138–39; reassessment of systems in practice and, 173–75; redefinition of, 134–40; risk awareness and communication in, 135–38, 233; risk reduction planning and implementation in, 233; shared goal in, 135; technical infrastructure in, 138; Wenchuan, China, earthquake (2008) as, 50, 67t, 138, 165–73. See also specific earthquakes empathy, 30 energy, 9, 19, 60; cognition and, 37; information as, 26–28, 41, 48, 60, 75, 138, 174, 222; money as, 60, 74; social energy and, 17, 89 entropy, 16, 40, 282n5 error correction, 19, 30, 65t, 241; autocorrection and, 247; feedback and, 30–31 External/Internal (E/I) index, 211–32; auto-­ adaptive systems and, 214–16, 215t, 216t, 237, 238t; coherence of system as a whole and, 212, 213, 236–40; calculation of, 212–13; data for, 212, 213; definition of, 55–56; equation for, 55–56, 212; emergent adaptive systems and, 222–28, 224t–

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25t, 227t; jurisdictional authority and funding sources, analysis of, 237–40, 238t–40t; measure of system’s performance and, 212, 213, 236–40, 247; meso scale of organization depicted in, 250; nonadaptive systems and, 228–32, 229t– 30t, 232t; square matrixes for, 212–13; statistical significance (P) of values for, 215, 216t, 221, 221t, 227–28, 227t; thresholds in organizational performance indicated by, 211, 236–37, 247 external resources: dependence on, 55–56, 237–40, 238t–40t; rebuilding and recovery and, 242; requests for, 56, 211 Facebook, 129–30, 129t, 178 feedback, 7, 9, 15 ,30, 65t field studies, 48–52; comparative analysis of, 49–50, 57–58, 208–34; current study and, 48–52; data, methods, and measurement for, 44–58; earthquakes and, 50; research questions and, 19, 50, 57–58; semistructured interviews and, 52–53, 56–57, 284n7; severity of earthquakes and, 50, 51; specific response systems and 3, 42, 48–52; study periods and (1999–2015), 19, 48, 66; timing of field observations after the event and, 51–52; underlying premises and, 20. See also response systems fires, firefighting crew responses, 25–26 flexibility, 30–33, 211, 64t–65t, 71, 211 freedom, individual, vs. collective, 42 Fukushima Daiichi nuclear power plant: damage to reactors and, 45, 115, 121, 221; radiation release from, 115, 119, 122; widespread effects of radiation release from, 44, 122. See also Tohoku, Japan, earthquake, tsunami, and nuclear breach (2011) funding sources. See jurisdictional authority and funding sources geotechnical analysis, 64t global aspects of seismic risk, 1–6, 61, 251– 52 Global Earthquake Model (GEM), 59, 282n1 Gorkha, Nepal, earthquakes (2015). See Nepal earthquakes (2015) Governing the Commons: The Evolution of Institutions for Collective Action (Ostrom), 24–25 Gujarat, India. See Bhuj, Gujarat, India, earthquake (2001)

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Haïti earthquake (2010), 50, 67t, 68t, 73t, 176, 178, 181f, 199–206, 228, 230–232t, 236, 240t; betweenness centrality and jurisdictions of organizations in, 203–4, 203f, 204t; building codes and, 200, 205, 206; building structure assessment program and, 59, 282n1; characterization of response and recovery system and, 200– 204; corroborating assessment of, 205; damage and destruction from, 199; date of, 50; deaths and losses from, 199; External/Internal (E/I) index for, 230t, 231– 32, 232t, 240t; initial conditions for, 199– 200, 206; international response and, 73, 202, 204t, 205, 206; lack of monitoring and preparedness in, 74; magnitude of 50, 199; map of area, 181f; national disaster plan, lack of, 200; network diagram of organizations in, 202–3, 203t; nonadaptive system in, 68t, 73, 73t; organizations participating in response system and, 201–3, 201t, 203f, 204t, 206, 231–32; political strife and dysfunction in, 74; preliminary classification of response system in, 67t, 68t; rate of change of organizations participating in response system and, 201–2, 202f; reconstruction and development challenges after, 205, 206; responses to, 205–6; seismic awareness and, 200, 205, 206, 228; transactions performed during response operations and, 202, 276t–77t; United Nations peacekeeping force in, 74, 200 Hanshin earthquake (Kobe, Japan, 1995), 7, 68, 96, 114, 209, 217 Hardin, Garrett, 24 Hayward fault, scenarios for, 2, 10, 13, 281nn1, 4 hierarchies, 40, 47, 60 Holland, John, 47 humans: cognitive machines and, 11–12; human-­made disasters and, 2; human-­ technical interfaces and, 15–17; interdependence with machines and, 11–12, 39; limits of cognition in, 37, 38 ICT (information and communication technologies), 5–6, 11, 61, 209 impacts, cascading and escalating effects of, 2–3, 7, 13, 45, 61, 115–16, 120–22, 177 India: Bhuj, Gujarat, earthquake ( January 26, 2001), 50, 51, 178–89; building codes in, 181; Latur earthquake in, 182; Mumbai, seismic risk in, 3; national disaster

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India (cont.) law in, 179; prior earthquakes in, 51; seismic awareness in, 3, 181, 182. See also Bhuj, Gujarat earthquake (2001) Indonesia: Aceh Province, 51, 74, 180f, 189– 91, 197, 199; conflict and politics in, 74; disaster preparedness improvement in, 217–20; national disaster plan and, 106, 109, 112; Padang earthquake (September 30, 2009), 50, 105–13; seismic preparedness in, 105–6; Sumatra earthquake and tsunami in, 50, 51, 189–99; tsunami awareness/preparedness in, 106, 107. See also specific earthquakes information, 15–17, 26–28, 41, 241–42; access to, 5, 174; decision making and, 28– 30, 37–38; definition/theories of, 15–17; directed information flow and, 15; as energy, 26–28, 41, 48, 60, 75, 78, 138, 174, 222; exchange of, 14–15, 241–42; human-­ technical interface and, 15–17; infrastructure for, 65t, 138, 174, 222; integration of diverse types of, 26; limits to collection and transmission of, 38; noise and, 15, 27; time and, 12, 78; resilience and, 241–42; role of, 5, 8–9, 15–17, 241–42; transmission of, 26–28, 38, 60–61, 78, 90, 243– 44; transmission to lay public of, 12, 72, 243. See also information flow information and communication technologies (ICT), 5, 61, 209; managing risks and, 6; shifts in, 5–6, 11 information flow, 5, 11, 15–16, 65t, 209, 210; channels for, 15–17, 20, 28, 138; computational modeling of, 37; direction and, 15; effect on time, space, and scale and, 60– 61; feedback from, 15, 30–31; importance of, 133; integration across scales of, 42; interactivity and, 36; across jurisdictional levels and, 37, 62; limits on channels for, 15–16; mismatch in, 28; research questions on, 19; simultaneous transmission and exchange of, 60–61; technology and, 5–6, 11–12, 15–17, 20, 26–28, 78, 222, 243–44; technology constraints on, 20, 28; tracing of, 48, 210 information technology, 14–15, 72, 79, 209; changing role of, 42–43; in management of collective actions across jurisdictions, 90–91; research questions on, 19; satellite imagery, 72, 124, 166, 174, 187–89 infrastructure: communications infrastructure, 64t, 138, 174, 222; critical infrastructure, 64t; information infrastructure, 65t,

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138, 174, 222; interdependent systems of, 4, 7; underground, bundling of and risks to initial conditions, 7, 18–19, 53; case studies of, 49; data sources for, 52; energy and, 19, 60; importance for response operations of, 60–62, 74–75; scale, space, time and, 18–19, 60 Institutional Analysis and Development Framework (Ostrom), 25 institutions: Governing the Commons (Ostrom), 24–25; impact of risk on, 25–26 interactions, 9–15, 245; coding of, 54–55; nonlinearity and, 6–7, 9; organizations and, 55, 211–12, 213; resilience and, 245; social interaction and, 25–26; technology and, 243–45 interconnections, 11–12, 39, 62 interdependent systems: cascading impacts in, 2–3, 7, 13, 45, 61–62; CASoS modeling and analysis of, 9–13, 10f; collaboration across boundaries in, 6; decision impact in, 8; degree of interdependence of, 12–13; global operational networks and, 3–4; infrastructure and, 4, 7; multiple actors in, 9; nonlinear interactions in, 6–7; risk assessment in, 45–46; sociotechnical systems and, 7, 45–46; system of systems and, 5–6 International Research Institute in Disaster Science, 122 International Risk Governance Council, 39 interviews, 52–53, 56–57 Istanbul, Turkey, seismic risk in, 3 Jakarta, seismic risk in, 3 Japan: building codes in, 114, 115; disaster preparedness in, 67, 96, 113–15, 121–22; Hanshin earthquake (Kobe, 1995), 7, 68, 96, 114, 209, 217; national disaster plans in, 114; real-­time dissemination of seismic data and, 12, 243; seismic information network in, 114; seismic preparedness in, 113–15, 121; Tohoku triple disaster (March 11, 2011), 2–3, 50, 113–23; Tokyo, seismic risk in, 3; tsunami awareness and preparedness in, 114, 115, 121 jurisdictional authority and funding sources, 236, 237–40, 238t–40t Kathmandu, Nepal. See Nepal earthquakes (2015) Kaufmann, Stuart, 29 knowledge: access to, 31; action and, 8–9,

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12, 17–19; bridging different fields of, 30; local knowledge bases and, 31–32; national knowledge bases and, 65t; propositions about risk and, 40–43, 57; shared knowledge bases and, 13, 178, 241 knowledge commons, 30, 178, 247, 252 learning, 31, 209–10; collective scale and, 69, 75, 248; importance in complex systems of, 31; information as catalyst for, 26–27, 245; Learning from Earthquakes (LFE) Program, 209; prior earthquake/disaster experiences and, 139–40, 209–10, 217 limits: channels for information flow and, 15–16; collection and transmission of information and, 38; human cognition and, 37, 38 local knowledge bases, 31–32 Los Angeles, California, 3, 36–37 Lushan, Ya’an, China, earthquake (2013), 50, 67t, 68t, 69, 76–91, 214–15t, 216t, 237–38t; adaptive performance in, 79; as auto-­adaptive system, 68, 68t, 69, 69t, 76–91; betweenness centrality and jurisdictions of organizations in, 85–87, 86f, 87t; building codes and, 84, 88; cell phone and social media use and, 78, 79, 80–81, 88, 89, 210; characterization of earthquake response system and, 81–87; China Earthquake Administration (CEA) and, 80; communication and, 78, 79; corroborating assessment of, 88–89; date of, 50, 80, 81; deaths and losses from, 81; donations of money, goods and services in, 84, 88–89; External/Internal (E/I) index for, 214–16, 215t, 216t, 237, 238t; initial conditions for, 80–81; jurisdictional authority and funding sources, analysis of, 237, 238t; knowledge base created in, 80, 89; Longmenshan fault system and, 80, 81; Lushan County and, 78–81; magnitude of, 50, 81, 87; map of area, 79f; medical care and health services in, 84; network analysis, sources of electronic data for, 279t–80t; network diagram of organizations in, 85, 86f; operative adaptive system in, 68t; organizations involved in response operations and,81, 82–84, 83t, 88; Pengguan fault and, 81; preliminary classification of response system in, 67t, 68t; prior earthquake experience and, 68, 80, 88, 139, 216, 234; questions regarding response factors, 90–91; rapidity of response in, 81–82, 84, 88, 90; rate of

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change of organizations participating in response system and, 84, 85f; response profile for, 80–90; scale of operations in, 82–84, 89; seismic awareness and preparedness activities in, 80–81, 82, 88–89, 233–34; self-­organization in, 69, 78, 88, 89; spatial location, response mobilization and, 81, 82, 88, 89; summary of, 89– 90; time as factor in, 81–82, 88, 89; transactions performed during response operations to, 84, 254t–55t; volunteers in, 81, 90 machine-­learning techniques, 11–12 Mann Gulch fire, 25 Marmara, Turkey, earthquake (1999), 50, 67t, 68t,71–72t, 96,134–36f, 140–49, 222–4t, 227t, 239; betweenness centrality and jurisdictions of organizations in, 145– 46, 146f, 147t; building codes and, 141, 148, 149, 174, 233; characterization of response and recovery system and, 141–45; communications disruption after, 148; communications infrastructure and, 149; corroborating assessment of, 147–48; date of, 50, 140; deaths and losses from, 140; emergent adaptive system in, 68t, 71, 72t, 141–45; External/Internal (E/I) index for, 222–23, 224t, 227t, 239t; initial conditions for, 140–41; interviews for, 141, 143, 284n7; magnitude of, 50, 140; map of area of, 136f; National Disaster Law and, 141, 145, 146; network analysis of, 145–46, 146f, 147t; network diagram of organizations in, 145, 146f; organizations participating in response system and, 141–43, 142t, 222–23, 227; performance gap between laws and actions in, 137, 141, 148, 174, 233; preliminary classification of response system in, 66, 67t, 68t; rate of change of organizations participating in response system, 143, 144f; seismic awareness and, 141, 147; space as factor in, 140, 148; summary of response to, 148– 49; ten communities damaged by, 140, 148; time as factor in, 140; transactions performed during response operations and, 143–45, 264t–65t; Turkish Red Crescent (Kizilay) in, 145–46, 147t; weaknesses in response measures to, 66–67 measurement, 44–58; instruments for, 62; risk and, 44–46; signals and boundaries for, 46–48 media, amplification of threats by, 23

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megacities, 3–4 memory, collective, information technology and, 14–15 Method of Splitting Tsunami (MOST), 15–16 methods, 44–58, 246–48; analysis and, 53– 57; Bayes and, 57; coding of interactions to, 54–55; comparative analysis of, 49– 50, 57–58; data sources for, 52–53; documentary analysis of formal plans and, 53– 54; External/Internal (E/I) index and, 55–56, 139; mixed methods and, 48, 53, 139; network analysis and, 54–57; process tracing and, 54; risk measurement and, 44–46; signals and boundaries and, 46– 48; simultaneous monitoring of multiple conditions and, 246; triangulation and, 53 metrics, 41 Mexico City, seismic risk in, 3 modeling: CASoS (Complex Adaptive Systems of Systems) engineering process and, 9–13, 10f; computational modeling and, 37; future states and, 246, 251; as means of anticipating risk, 39; resilient systems and, 4–5, 242–46; tsunamis and, 15–16, 115, 122, 133 monitoring: auto-­adaptive systems and, 77– 78; CASoS process and, 10f, 11; electrical power systems and, 9; need for long-­term commitment in, 78; procedures for, 65t; simultaneous monitoring of multiple conditions and, 246; trained personnel for, 78 MOST (Method of Splitting Tsunami), 15–16 Multidisciplinary Center for Earthquake Engineering Research (MCEER), 4 Mumbai, India, seismic risk in, 3 NAFTA (North American Free Trade Agreement), 38 NASA, 29 national disaster plans/laws, 64t, 66; China and, 81, 88, 227; India and, 179; Indonesia and, 106, 109, 112, 192; Japan and, 114; Nepal and, 70, 123, 125; Turkey and, 66, 71, 98, 141, 145, 146, 222 national knowledge bases, 65t Nepal earthquakes (2015), 50, 67t, 68t, 71t, 92, 94f, 96, 123–32, 219t, 221t, 239t, 246; betweenness centrality and jurisdictions of organizations in, 128–29, 128f, 129t; building codes and, 123, 124, 132; cell phones and, 138, 243; characterization of

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response and recovery system and, 124– 30; cluster system for humanitarian aid in, 123–24, 131; communication and information flow after, 125, 129–30, 132, 243, 244, 246; corroborating assessment of, 130–31; dates and time of, 50, 123, 125; deaths from, 125; Dharahara Tower collapse in, 1–2; earthquake awareness and preparedness actions and, 70–71, 123–25; ethnic/political tensions affect recovery efforts in, 48, 68, 70, 221; External/Internal (E/I) index for, 220t, 221, 221t, 239t; Facebook and, 129–30, 129t; GIS knowledge base for, 124; global framework, importance of, 132; Gorkha and, 94f, 125; high risk awareness and, 70; initial conditions of, 123–24; international aid, request for, 125–26, 131, 211; Kathmandu, buildings and response in, 1–2, 18, 125; landslide risk and preparedness measures in, 124; Madhesi group, political tensions and, 48, 131; magnitude of earthquakes in, 50, 94, 125; map of area, 94f; mobilization of response operations and, 125–26; national building code and, 123; National Disaster Response Framework (NDRF) and, 123, 125; National Information Technology Center (NITC) and, 125; National Society for Earthquake Technology (NSET) and, 124; Nepali Congress Party and, 129t, 130; network diagram of organizations in, 128, 128f, 130; operative adaptive system in, 68t, 70, 71t, 123–32; organizations participating in response system in, 126, 126t, 128–30, 128f, 221; preliminary classification of response system in, 67, 67t, 68t; rate of change of organizations participating in response system in, 126, 127f; Reconstruction and Rehabilitation Policy and, 130; recovery efforts and, 48, 68, 70, 131, 133; response capacity dimensions in, 67; risk awareness and reduction in, 70–71; satellite imagery and geographic analysis in, 124, 125; scales of operation in, 132; space as factor in, 132; summary of response to, 131–32, 133; time as factor in, 125, 132; transactions performed during response operations in, 126–28, 262t–63t; USAID and, 129t, 130; Village Development Committees and, 129t, 130 network analysis, 3, 51, 54–57; betweenness centrality and, 55, 57, 97; diagrams of, 57,

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85, 86f; dynamic nature of, 247; External/Internal (E/I) index and, 55–56, 247; frequency distributions and, 55; interactions among organizations and, 55; operative adaptive systems and, 96, 97; types of network measures and, 55 network diagrams. See specific earthquakes networks, 41, 59–66; action and, 59–62; actors and interactions in, 54–55; boundaries of, 54, 60; cell phone networks and, 5, 17, 72, 81–82; common goal in, 60, 62; design of, 59–62; emergence under conditions of uncertainty and, 62; interconnections and vulnerabilities in, 62; interdependence of, 3–4; nodes in, 55; in practice, 63–66, 64t–65t; resilience and, 248 news reports, 52, 54, 57 nodes, 55 nonadaptive systems, 68t, 73–75, 73t, 176– 207, 233; Bhuj, Gujarat, India, earthquake and, 50, 178–89; cascading impacts in, 177; characteristics of, 73t, 176–77; communications and, 177, 178; External/ Internal (E/I) index values for, 228–32, 229t–30t, 232t, 239–40, 240t; Haïti earthquake (2010) and, 50, 199–206; initial conditions in, 74; integration of communication infrastructure with organizational planning in, 233; jurisdictional authority and funding sources, analysis of, 239–40, 240t; lack of monitoring and preparedness in, 74, 182, 184, 190, 200, 206, 228, 232, 233; network performance and duration in, 177–78; operational systems in, 177; reassessment and comparison of, 206–7; redefinition of, 176–78; seismic risk, lack of awareness of, 182, 184, 190, 200, 206, 228, 232, 236; Sumatra, Indonesia, earthquake and tsunami (2004) as, 50, 189–99; system coherence and resiliency and, 236; technical/communications structure and, 176–77, 207; transition from response to recovery in, 207. See also specific earthquakes nonlinear interactions and systems, 6–9 North American Free Trade Agreement (NAFTA), 38 Northridge earthquake (Los Angeles, 1994), 36–37 nuclear power plants. See Fukushima Daiichi nuclear power plant; Tohoku, Japan, earthquake, tsunami, and nuclear breach (2011)

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operational levels, 28 operational networks, global interdependence of, 3–4 operational systems: comparative analysis of, 208–34; continuity in, 210–14; information flow and, 209, 210; initial conditions and, 210; prior disaster experience and, 209–10; thresholds in, 236–37, 247 operative adaptive systems, 68t, 69–71, 71t, 91–133, 233–34; capacity to evolve and, 96, 132–33; changing contexts, adaptation in response to, 92–97, 132–33; characteristics of, 92–97, 233–34; comparison of, 216–22; differentiation among, 95; Duzce, Turkey, earthquake (1999) as, 50, 67, 97–105; energy in, 95, 222; evolution of, 208–34; External/Internal (E/I) index values for, 216–22, 219t–20t, 221t, 238, 239t; external resources and, 96; internal/external dynamic in, 97; jurisdictional authority and funding sources, analysis of, 238, 239t; maps of locations, 93f–94f; multiple scales of operation in, 133, 222; Nepal earthquakes (2015) as, 50, 67, 123–32; network analysis of, 96, 97; Padang, Indonesia, earthquake (2009) as, 50, 67, 105–13; performance under stress and, 92, 95, 96; planning for risk reduction in, 233–34; preliminary characteristics of, 71t; prior earthquake experience and, 96, 209–10; time, space, scale, and energy in, 95, 97, 133; Tohoku, Japan, triple disaster (2011) as, 50, 67, 113–23; transition from response to recovery in, 95, 97, 132–33, 211. See also specific earthquake/disaster examples organizational design, 12 organizational dysfunction, firefighting and, 25–26 organizational flexibility, 64t–65t, 71, 211 organizational infrastructure, 138 organizational response systems. See response systems organizations, 244–45; design and, 34; frequency distributions of, 55; high reliability in, theories of, 29; horizontal classification of, 212; information exchange and, 17, 19, 20, 25–26; interactions among, 19, 55, 211–12, 213; as major actor in response operations, 11–13, 17, 20, 244; network analysis of, 54–57; vertical classification of, 212. See also jurisdictional authority and funding sources Ostrom, Elinor, 24–25, 30, 247

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Padang, Indonesia, earthquake (2009), 50, 67t, 68t, 71t, 92, 93f, 96, 105–13, 217–18t, 220–21, 239; betweenness centrality and jurisdictions of organizations in, 109–11, 110f, 111t; characterization of response and recovery system in, 106–11; corroborating assessment of, 112; date of, 50; deaths from, 107, 283n4; evacuation of city after, 133, 233; External/Internal (E/I) index for, 217–20, 219t, 221t, 239t; information exchange as factor in, 113; initial conditions for, 105–6; magnitude of, 50, 93, 106, 220; map of area, 93f; National Disaster Plan and, 106, 109, 112; network diagram of organizations in, 109, 110f; operative adaptive system in, 68t, 70, 71t, 105–13; organizations participating in response system and, 107, 108t, 109–11, 109f, 110f, 111t; preliminary classification of response system in, 67t, 68t; preparedness activities and, 96, 105–6, 112, 220, 233; prior earthquake experience and, 96, 112, 133, 217, 220; rate of change of organizations participating in response system and, 107, 109f; scales of operation in, 113; summary of response to, 112–13, 133; time as factor in, 106, 112; transactions performed during response operations and, 107–9, 258t–59t, 284n16; tsunami destructiveness in, 106–7, 220; tsunami preparedness and, 106, 107, 133, 220 Pakistan earthquake (2005), 50, 67t, 68t, 71, 72t, 135, 137f, 138, 157–65, 222, 225– 27, 239t; area of, 137f; betweenness centrality and jurisdictions of organizations in, 161f, 162–63, 162t; characterization of response and recovery system and, 157– 63; cluster plan for humanitarian aid in, 158, 161, 163–64226; communications loss from, 138, 163; communications systems and, 158–59, 163, 164, 174; corroborating assessment of, 163–64; date of, 50, 157; deaths and damage from, 157; Earthquake Reconstruction and Recovery Authority (ERRA) and, 164; emergent adaptive system in, 68t, 71, 72t, 158–63; External/Internal (E/I) index for, 225t, 226, 227t, 239t; initial conditions for, 157–58; location and terrain and, 138, 158, 160, 163, 226; locations affected by, 137f, 157; magnitude of, 50, 157, 174; network diagram of organizations in, 161–62, 161f; organizations participating in response

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system and, 159, 159t, 160f, 161–63, 161f, 226, 227; preliminary classification of response system in, 67t, 68t; rate of change of organizations participating in response system in, 159, 160f; satellite imagery use and, 158, 160; seismic awareness and, 157, 164, 174; seismic monitoring, lack of, 158; response to, 164–65; transactions performed during response operations and, 159–61, 268t–69t Pakistan floods (2010), 209–10 performance: adaptivity and, 79; anomalies as signals of changing conditions and47– 48; assessment indicators/criteria for, 63–66, 64t–65t; coherence in system performance and, 212, 213, 236–40; External/Internal (E/I) index as measure of, 212, 213, 236–40; future states/models of, 246, 251; gaps in integration of, 216–22; measures of, 246–48; organizational, learning and, 209–10; organizational flexibility dimension and, 64t–65t, 211; performance assessment for buildings and, 32–33; performance patterns in four classes of adaptation and, 67–75, 67t, 69t, 71t, 72t, 73t; technical dimension of, 64t policies: complex policy environments, role of information in, 15–17; documentary analysis of, 53–54; initial profile of, 53; national disaster response plans and, 64t; seismic risk as global policy problem, 1–6, 61 Port-­au-­Prince, Haïti. See Haïti earthquake (2010) problem-­solving, 12, 28–30. See also decision making problem-­solving spaces, 42 process tracing, 3, 54 public risk, shared risk as, 6–9, 39–40 public space, 178 questions: characterizing complex adaptive systems and, 19, 57–58; research in this study and, 19, 50, 57–58, 213, 234 random events, 7 real-­time information, 12 recognition primed decision making, 18 redesign: learning/assessment processes and, 175, 235; public space/forum for, 178; systems and, 4, 6, 31–32, 133, 156 reliability, high, 29 research, questions and, 19, 50, 57–58, 213, 234

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resilience, 235–52; anticipation of threats and, 4; assessment for, 235–36; building of, 133, 208–10, 240–46; challenges of seismic policy and, 248–49; classes of adaptation and, 236–40; coherence of whole system and, 236–40; culture and, 245; data management and, 247; design of resilient systems and, 235–36; as evolving, dynamic process, 250, 251; External/Internal (E/I) indexes and, 236–40, 238t–40t; funding and jurisdictional authority as indicators of, 236, 237–40, 238t–40t; information and, 242–43; innovation and, 248; interaction and, 245; international support, role of, 240; learning and, 240–41, 248, 250; Lushan, China, as example of, 76– 91; methods of analysis and performance measurement for, 246–48; model of, 4–5, 242–46; networks of action for, 248; 100 Resilient Cities Program and, 35–36, 282n4; organization and, 244–45; requirements for building resilient systems and, 240–42; as social process, 241, 251; societies and, 250–51; sociotechnical framework for, 242–46; system integration and, 236, 237–40; technology and, 243–44 resonance of response systems and environment, 69; auto-­adaptive systems and, 69, 69t, 79; emergent adaptive systems and, 72t; nonadaptive systems and, 73t; operative adaptive systems and, 71t resources: allocation of, 60; collective action and, 69, 69t, 71t, 72, 72t, 73t, 79; external resources, dependence on, 55–56; request for, 56. See also External/Internal (E/I) index response capacity: building, 91, 167, 210; dimensions and assessment of, 64t–65t; initial conditions and, 18–19; interdependencies of dimensions of, 67; official plans and, 56–57 response system dimensions, 64t–65t; cultural values and, 65t; organizational flexibility and, 64t–65t, 211; technical structure and, 64t, 66–67, 67t response systems, 3, 48–52, 66–75; adaptation classes of, 67–68, 68t; assessment indicators for, 2, 64t–65t; auto-­adaptive system, movement toward, 68–69, 68t, 69t, 76–91; comparative analysis of, 49– 50, 57–58, 208–34; dimensions of, 64t– 65t; earthquakes in this study and, 50–52;

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emergent adaptive systems and, 68t, 71– 72, 72t, 134–75; evolution of, 40, 48–49, 208–34; External/Internal (E/I) indexes for, 55–56, 211–32; field studies and, 3, 42, 48–52; four functions in, 68–69, 69t; frequency distributions, organizations, and, 55, 211; importance of initial conditions for, 60–62, 74–75; network analysis of, 54–57; nonadaptive systems and, 68t, 73–75, 73t, 176–207; operative adaptive systems and, 68t, 69–71, 71t, 92–133; organizational interactions in, 211–12, 213; performance assessments and, 2, 63–66, 64t–65t; in practice, 63–66; preliminary classification of, 66–67, 67t, 68t; resonance with environment and, 69, 69t, 71t, 73t; systems integration and, 77–78, 237; technical structure in, 64t, 66–67, 177; technical vulnerabilities of, 5–6; time, space, scale, and energy in, 60, 75, 76; transition from response to recovery and, 95, 97, 132–33, 211, 242. See also specific earthquakes and disasters by place name Ring of Fire, 50 risk: changing concepts of, 23–26; in complex systems, 22–43; cultural context of, 9; definition and redefinition of, 3, 23; dimensions and framing of, 17–19; dynamic, interacting conditions and, 3, 245; dynamics of change and, 26–33; as global policy problem, 1–6, 61; interconnected, complex systems and, 2–3; multiple perspectives on, 13–14, 43; in practice, 59– 75; scale and, 3–4; as threat to social order, 23–24; uncertainty and, 3, 22–23. See also seismic risk; shared risk risk, propositions on: what we do know and, 40–41, 47; what we don’t know that we don’t know and, 42–43; what we know that we don’t know and, 41–42, 57 Risk and Culture (Wildavsky and Douglas), 23 risk assessment, 4–5, 42, 44–58, 64t; complex systems and, 44–58; geographic location in, 4–5, 35; measurement of risk and, 44–46; modeling for, 39; theoretical approaches to, 4–5; uncertainty in, 22–23 risk awareness: nonadaptive systems and, 74; operative adaptive systems and, 69– 71, 71t; policies and laws representing, 53–54; preparedness activities and training for, 80–81, 82, 88–89; public education and, 90. See also specific earthquakes by place name

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risk management, 4–5, 248–49, 251–52; collective action and, 24–25; initial conditions for, 18–19; next steps in, 251–52; shared cognition of 26, 39–43. See also resilience risk mitigation: design in, 4, 33–37; fitting goals to action and, 33–34 risk perception, 20, 42, 75; extreme events and, 62; from multiple perspectives, 13– 14, 43; in nonadaptive systems, 74; signals of change in, 58 Risk Society (Beck), 24 safety, as process of selecting risks, 4 San Andreas fault, 32 San Francisco: Building Occupancy Resumption Program (BORP) in, 32–33; seismic risk and risk mitigation in, 32–33 San Francisco Bay Area: 100 Resilient Cities Program in, 35–36, 282n4; seismic risk in, 35–36. See also Hayward fault satellite imagery, 72, 124, 166, 174, 187–89 satellite phones, 174, 245, 246 scale, 9, 18–19, 42, 60: allocation of resources and, 60; broader concept of, 61; communication and, 18–19, 27, 90; megacities and, 3–4; operations at multiple scales and, 62, 75, 78, 90–91, 95, 133, 222; scales of operation, aligning, 36–37, 42; seismic hazards and, 3–4 seismic risk: dilemma of, 6, 249; as a global policy problem, 1–6, 61; numbers of nations exposed to, 3; scale and, 3–4. See also risk awareness self-­organization, 8, 27, 67; adaptation as, 176–77; in Lushan, China (2013), 69, 78, 88, 89; preparedness activities and, 71, 88–89 sensors, 14; accelerometers as, 62; data collection by, 11 September 11, 2001, terrorist attacks, 23, 24 shared risk, 3, 6–9, 39–43; decisions on, 3; definition/redefinition of, 39–40; non­ linear response to, 7–8; as public risk, 6–9, 39–40; public space vs. individual risk, 39–40 Shared Risk: Complex Systems in Seismic Response (Comfort), 2, 7–8, 39–40, 58 shared social space, 18, 39–40, 42, 78 shared values, 65t, 241 signals, 46–48; cross-­boundaries and, 56; identification and, 58; performance anomalies as, 47–48; request for external resources as, 56

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Simon, Herbert, 30–31 social energy, 17, 89 social interaction, risk dynamics in, 25–26 social media, 129–30, 129t, 178; in Lushan, China, earthquake response and, 78, 89 social order, risk as threat to, 23–24 social space and, 18, 42, 78 social systems, information as energy in, 26–28 sociotechnical adaptation. See adaptation, classes of sociotechnical systems, 5; data/information collection and use of, 9, 14; dual role of, 14–15, 17; emergence of, 20; flexible structure for, 30–31, 211; high reliability in, 29; information technology role in, 42–43; interdependence of, 7, 45–46; uncertainty and, 34–37 space, 9, 18, 35–36, 42, 60–61; as boundary of risk, 35–36; broader concept of, 61; collective problem-­solving spaces and, 12; density and, 41; as geographic location, 60, 74; of information exchange, 61, 75; public space and, 178; social space and, 18, 42, 78; space of flows and, 61, 75; spatial extent of seismic risk and, 78; state space and, 46 state of the system, 46–47 strategic action field, 30 Sumatra, Indonesia, earthquake and tsunami (2004), 50, 51, 67t, 68t, 73t, 176, 180f, 189–99, 232, 228t, 240; Aceh Province, 51, 74, 180f, 189–91, 197, 199; Banda Aceh, 190–91, 192, 196; betweenness centrality and jurisdictions of organizations in, 195–96, 195f, 196t, 197; characterization of response and recovery system and, 191–94; civil and political conflict and, 74, 190–91, 192, 198, 206; communication infrastructure and, 191, 197–98; corroborating assessment of, 197–98; cultural aspects in, 190–91; deaths and losses from, 190, 191, 192, 197; External/Internal (E/I) index for, 229t, 230–31, 232, 232t, 240t; Free Aceh movement and, 74, 190, 198, 206; Indonesian Army (TNI) in response to, 192, 196; information flow, asymmetry in, 197–98; initial conditions for, 189–91; international response in, 73, 191, 192, 195f, 197, 198, 206; magnitude of, 50, 189, 231, 285n4; map, area of, 80f; national disaster policy and, 192; nation’s tsunami effects and, 190, 191–92, 194, 230–31; network analysis of, 194–96,

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197–98; network diagram of organizations in, 195, 195f; nonadaptive system in, 68t, 73, 73t; organizations participating in response system and, 192–94, 193t, 194f, 195–96, 196t, 198, 230–31; preliminary classification of response system in, 67t, 68t; rate of change of organizations participating in response system and, 194, 194f; response sectors working individually in, 197; seismic awareness and, 74, 190, 198, 228, 231; summary of response to, 198–99; transactions performed during response operations and, 194–95, 274t–75t; tsunami awareness and, 190; tsunami damages and losses and, 190, 191, 192, 197; tsunami speed and wave heights and, 190; tsunami timing in, 190; tsunami warnings, lack of, 190; two separate response networks in, 197–98 system, boundaries and state of, 42, 46–48 systems integration, 77–78, 237–40 systems of systems, 5–6, 13–14, 20, 41; Complex Adaptive Systems of Systems (CASoS) process and, 9–13, 10f; continual evolution of, 20; information flow in, 210; initial conditions and risk in, 18–19; multiple perspectives in, 13–14; risk assessment in, 45 Taiwan. See Chi Chi, Taiwan, earthquake (1999) technical structure, 64t, 66–67, 177; auto-­ adaptive systems and, 76–77; emergent adaptive systems and, 138, 174; nonadaptive systems and, 176–77; operative adaptive systems and, 92, 95; preliminary classification of response systems and, 67t technological change, 2–3, 5, 11, 246 technology, 14–15, 37–39; in communication/information flow, 26–28, 79, 243– 44; in decision making, 12, 37–39; dual role in complex adaptive systems and, 14– 15, 17; human-­technical interface and, 15– 17, 244–45; impact of, 4, 5–6, 23; information and communication technologies (ICT) and, 5, 11, 61, 78; integration into decision making and, 37–38; interactions and scales in, 40, 243–45; organizational systems and, 5–6; rapid change in, 2, 5, 11, 246; real-­time dissemination of seismic data, 12, 243; research questions on, 19; resilience and, 243–44; risk and, 37– 39; risks of, 4, 5–6, 24; as threat to social order, 24

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threats, 23–24 thresholds, 41; action and, 44–45, 58; External/Internal (E/I) indexes and, 211, 236– 37, 247; points of change and, 208, 210, 211, 236 time, 9, 18, 35, 60; as chronological and linear metric, 60, 74; decision making and, 8, 18; information flow and, 61; risk and action as functions of, 35; shift in perception of, 61, 75; “timeless time,” and 61 Tohoku, Japan, earthquake, tsunami, and nuclear breach (2011), 2–3, 50, 51, 67t. 68t, 71t, 92, 94f, 96, 113–23, 209, 219, 221, 239, 248; auto-­adaptation, Japan previously classified as moving toward, 121, 243–44; betweenness centrality and jurisdictions of organizations in, 119, 119f, 120t; cascade of events in, 115–16, 120–21; cascading effects of, 62, 70, 120–22; characterization of response and recovery system and, 115–19; corroborating assessment of, 120–21; dates of, 3, 115; deaths and costs of, 116; earthquake preparedness and, 113–15, 121; External/Internal (E/I) index for, 220–21, 220t, 221t, 239t; Fukushima Daiichi nuclear reactor damage and radiation release and, 45, 115, 119, 121, 122, 221; Fukushima uninhabitability and, 44, 122; information exchanges and, 16, 122–23; initial conditions for, 113–15; International Research Institute in Disaster Science and, 122; magnitude of, 50, 94, 115, 122, 220–21; map of area, 94f; MOST model of tsunami detection and, 15–16; national disaster plans and, 114; network diagram of organizations in, 119f, 120–21; nuclear plant safety measures and, 114–15; operative adaptive system in, 68t, 70, 71t, 113–23; organizations participating in response system and, 116, 117t, 118–19; preliminary classification of response system in, 67, 67t, 68t; preparedness activities and, 96, 221, 233; prior earthquake experience (Hanshin) and, 68, 96, 122, 209, 217, 220; public confidence, loss of, 122; questions raised by, 123; rate of change of organizations participating in response system and, 116, 118f; response capacity dimensions and, 67; space as factor in, 122–23; summary of responses to, 121–23, 133; system overwhelmed by extreme events and, 115–16, 119, 121–22, 220, 248; technical structure preparedness and, 67, 70; time as factor

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Tohoku, Japan, earthquake, tsunami, and nuclear breach (cont.) in, 122; transactions performed during ­response operations and, 116–18, 260t– 61t; tsunami alerts issued and, 115; tsunami heights vs. estimations of, 115, 133, 221; tsunami modeling and, 115, 122, 133; tsunami preparedness measures and, 114, 115; tsunami risk, underestimation of, 70, 115, 119, 121, 133, 221; trade-­offs for case studies and, 42, 49 “Tragedy of the Commons, The” (Hardin), 24 transactions: coding of, 55; frequency distributions of, 55; tables of, by classes of adaptation, 254t–84t transition from response to recovery and, 95, 97, 132–33, 211, 242 transport systems, interconnections of, 6 trust between leaders and citizens, 69–70; auto-­adaptive systems and, 69t, 79; emergent adaptive systems and, 72, 72t; nonadaptive systems and, 73t; operative adaptive systems and, 71t tsunamis: Method of Splitting Tsunami (MOST) and, 15–16; MOST model of tsunami detection and, 15–16; Padang, Indonesia, earthquake and, 106–7, 220; Sumatra, Indonesia and 50, 51, 189–99; Tohoku, Japan (2011), 2–3, 15–16, 113– 23; tsunami height estimations, 115, 121; tsunami modeling, 115, 122, 133. See also specific tsunami occurrences by place name Turkey: building codes in, 71, 105, 141, 148, 149, 174, 233, 283n2; Duzce earthquake and, 50, 97–105; Marmara earthquake and, 50, 140–49; national disaster law in, 66, 71, 98, 105, 141, 145, 146, 222; National Earthquake Research Center in, 141, 222; prior earthquakes in, 51, 71; seismic awareness in, 98–99, 104–5, 141, 174, 217, 222; seismic hazards in, 285n2; technical dimension and, 66–67, 71; weaknesses in response dimensions in, 66–67 Twitter, 178 uncertainty, 22–23, 34–37; Bayesian modeling and, 57; in complex, adaptive systems, 6, 31; decision making and, 3, 208–

9; in decisions to reduce risk, 3, 208–9; elements and scales in, 34–37; emergence of networks and, 62; risk and, 22–23 United Nations: cluster system for humanitarian aid and, 123–24, 131, 158, 161, 163– 64, 226; Office for the Coordination of Humanitarian Assistance (OCHA) and, 123, 158, 161, 162, 164, 191, 192, 199; peacekeeping force in Haïti and, 74 values, cultural, shared and12, 18, 65t, 241 vulnerabilities, poliicies and, 4 Wenchuan, China, earthquake (2008), 50, 68t, 71t, 72t, 134–35, 137f, 138–39, 165– 74, 222, 225–27, 239; Beichuan fault, 81; betweenness centrality and jurisdictions of organizations in, 170–71, 171f, 172t; building code and, 165–66, 173; characterization of response and recovery system and, 166–71; children, loss of, 166, 173; corroborating assessment of, 173; data on, 166–67, 173, 285n3; date of, 50, 165; deaths and losses from, 165; displaced families, relocation of, 167; emergent adaptive system in, 68t, 71, 72t, 166– 71; External/Internal (E/I) index for, 225t, 226–27, 227t, 239t; initial conditions for, 165–66; Longmenshan fault and, 165; magnitude of earthquake, 50, 165, 174; map of area, 137f; network diagram of organizations in, 170, 171f; organizations participating in response system and, 167–69, 168t, 170–71, 171f, 172t, 226– 27; preliminary classification of response system in, 67t, 68t; public response to, 166; rapid mobilization of response in, 166; rate of change of response system and, 169, 169f; resource mobilization for, 72; satellite imagery and, 166; seismic awareness and, 165, 173, 174; summary of response to, 173; transactions performed during response operations, 169–70, 270t–71t; transition from response to recovery in, 166, 167 Wildavsky, Aaron, 4, 23 wildfires, firefighting responses to, 25–26 Yahoo.com hacking attacks (2013, 2014), 38 Yarnell Hill, Arizona, wildfire in, 25–26

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A NOTE ON THE T YPE

This book has been composed in Adobe Text and Gotham. Adobe Text, designed by Robert Slimbach for Adobe, bridges the gap between fifteenth-­­­ and sixteenth-­­­century calligraphic and eighteenth-­­­century Modern styles. Gotham, inspired by New York street signs, was designed by Tobias Frere-­­­Jones for Hoefler & Co.

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