Appendix A: Summary of Hypotheses

No. Hypotheses Frameworks Risk reduction : NS 1 Fatalism increases the likelihood of decision makers who emphasize the PF uncertainty of a crisis and decrease the likelihood of decision makers who emphasize the urgency of responding to it 2 Individualism increases the likelihood of decision makers who disparage PF the threat involved in a crisis 3 Hierarchy increases the likelihood of decision makers who have PF anticipated a crisis 4 Egalitarianism increases the likelihood of decision makers who NS emphasize the threat involved in a crisis 5 Hierarchical culture fears social disorder NS 6 Egalitarian culture fears risk that might harm many people PF 7 Individualistic culture fears risk to freedom PF 8 Fatalistic culture fears risk in general PF Decision Making (-process and -units ): NS 9 Hierarchy increases the likelihood of vertical movement of power up the NS chain of command into the hands of one or a few strong leader(s) 10 Fatalism increases the likelihood of a vertical movement of power up PF the chain of command into the hands of one or a few strong leader(s) 11 Egalitarianism increases the likelihood of a positive relation with GLF occurrence of formal decentralization within a set framework 12 Individualism increases the likelihood of a positive relation with NS occurrence of informal decentralization within a set framework 13 Egalitarianism decreases the likelihood of predominant leader as the NS most infl uential type of decision-making unit in crisis situations 14 Egalitarianism increases the likelihood of coalition of autonomous PF multiple actors as the most important type of decision-making unit in crisis response 15 Hierarchy increases the likelihood of “groupthink” among members of a CLF, GLF decision-making unit

© Springer International Publishing Switzerland 2015 169 Á.E. Bernhardsdóttir, Crisis-Related Decision-Making and the Infl uence of Culture on the Behavior of Decision Makers, DOI 10.1007/978-3-319-20714-8 170 Appendix A: Summary of Hypotheses

No. Hypotheses Frameworks 16 Fatalism increases the likelihood of “New Group Syndrome” among CLF members of a decision-making unit 17 Hierarchy increases the likelihood of “New Group Syndrome” among PF negative members of a decision-making unit CLF positive 18 Hierarchy increases the likelihood of “Rally around the fl ag” among CLF, GLF members of a decision-making unit 19 Hierarchy increases the likelihood of decision makers who do not PF display confl ict within their own decision-making group 20 Egalitarianism increases the likelihood of decision makers who display NS value-confl ict within the decision-making group and toward others 21 Hierarchy increases the likelihood of decision makers who express PF loyalty to the decision-making group 22 Fatalism increases the likelihood of decision makers who display low NS trust in people in general, both within their own group and toward others outside their group 23 Hierarchy increases the likelihood of decision who display a high level GLF of trust toward their own group 24 Egalitarianism increases the likelihood of decision makers who display NS a lower level of trust toward others outside their decision- making group 25 Egalitarianism increases the likelihood of decision makers who are CLF concerned and sensitive toward others and more focused on people and processes 26 Fatalism decreases the likelihood of decision makers within fatalism CLF that are less concerned and sensitive toward others and more focused on the task at hand Information management : NS 27 Hierarchy decreases the likelihood of decision makers who show a lack NS of information 28 Egalitarianism increases the likelihood of decision makers who show a NS lack of information 29 Individualism increases the likelihood of decision makers who offer NS direct and pointed information processing 30 Egalitarianism increases the likelihood of decision makers who will NS offer indirect and unclear information processing 31 Egalitarianism increases the likelihood of decision makers who follow CLF, GLF informal information processing 32 Individualism increases the likelihood of decision makers who follow NS informal information processing 33 Hierarchy increases the likelihood of decision makers who follow NS formal information processing 34 Egalitarianism decreases the likelihood of decision makers who localize CLF information 35 Hierarchy increases the likelihood of decision makers who localize NS information 36 Hierarchy increases the likelihood of decision makers who process NS information in accordance with the “sender” approach Appendix A: Summary of Hypotheses 171

No. Hypotheses Frameworks 37 Individualism increases the likelihood of decision makers who use the NS “volume” approach in processing information 38 Egalitarianism increases the likelihood of decision makers who use the NS “dialogue” approach in processing information 39 Fatalism increases the likelihood of decision makers who display a PF reactive media strategy 40 Egalitarianism increases the likelihood of decision makers who display PF, CLF a proactive media strategy Learning: NS 41 Fatalism decreases the likelihood of decision makers who learn and CLF modify their practices during or after a crisis 42 Egalitarianism increases the likelihood of decision makers who use NS historical analogy to draw lessons at any point during the crisis 43 Egalitarianism increases the likelihood of decision makers who use NS historical analogy in order to exaggerate the danger 44 Fatalism decreases the likelihood of decision makers who draw NS conclusion or learn based on comparison between present and previous crisis 45 Egalitarianism increases the likelihood of decision makers who PF, CLF emphasize collective learning Note: PF stands for ‘preparedness framework’, CLF for ‘collective learning framework’, and GLF for ‘group loyalty framework’, NS for ‘not supported’ Appendix B: Crisis Management Case Coding Guide

Following is a presentation of chosen variables, (within the TCM dataset) used in this study, including the way in which the variables were coded according to the coding guide.

B . 1 Case Characteristics

1–2 CASENAME – Case Name Description: What is the name of this case as given by the author? 1–7 CASETRIG Description: Which of the following best describes the origin of the crisis or its trig- gering event? (Choose only one) 1 = Technological 2 = Fiscal 3 = Political 4 = Environmental 5 = Military 6 = Legal 7 = Natural Disaster 9 = Unknown 99 = Not Applicable to this case

© Springer International Publishing Switzerland 2015 173 Á.E. Bernhardsdóttir, Crisis-Related Decision-Making and the Infl uence of Culture on the Behavior of Decision Makers, DOI 10.1007/978-3-319-20714-8 174 Appendux B: Crisis Management Case Coding Guide

1–42 CASEDUTP Description: Which one of the following best describes the key decision-making units? Remember you are considering the case as a whole. (choose only one): 1 = Public Organization or Agency 2 = Private (for profi t) Organization/Company 3 = Not-for-Profi t or Non-governmental Organization 4 = Public Actor Using Private Contractors 5 = Public and Private Actors in Joint Collaboration 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) Situational Crisis Characteristics (remember these apply to the case as a whole) 1–44 CASETHRT Description: What is the decision makers’ dominant perception of the severity of the threat overall? 0 = Low (Routine threat with little danger of long-lasting negative consequences.) 1 = Medium (Decision makers’ values/policies may be weakened and/or under- mined, but not beyond repair. In the case of threat to life or human health, the threat is considerable, but not unusual for the type of threat.) 2 = High (Decision makers’ values are seriously threatened, and/or there is a risk of an unacceptable number of deaths and/or injuries.) 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) 1–45 CASETOR Description: Was the original threat perceived by decision makers to have origi- nated from the outside actors (external to the organizations/groups that set out to manage the crisis) or from the inside (problem generated in part or fully by one or more actors involved in managing the crisis)? Note: For natural disasters, code as “99”. 0 = There was no clear perception of where threat originated 1 = Outside 2 = Inside 3 = Both outside and inside 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) Appendux B: Crisis Management Case Coding Guide 175

1–46 CASEURG Description: In general, what is the level of urgency decision makers perceive in the crisis? 0 = Low urgency (Decisions makers can go about their other activities while con- sidering what action to take. The window of opportunity is considered to be open.) 1 = Medium Urgency (Decision makers must act quickly, but have time to con- sider multiple options. The window of opportunity is perceived to be brief but manageable.) 2 = High Urgency (All attention is focused on the decision at hand. A short and narrow window of opportunity is perceived to be open.) 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) 1–47 CASEUCTY Description: In general, how much uncertainty do the decision makers perceive in defi ning the nature of the crisis? 0 = Low Level of Uncertainty (Crisis is easily defi ned with confi dence.) 1 = Medium Level of Uncertainty (Crisis can be defi ned, but without total certainty.) 2 = High Level of Uncertainty (Lack of reference points, fi rst time occurrence, and/or little or no access to relevant information.) 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) 1–48 CASERES Description: Overall, how much uncertainty do the decision makers perceive regarding how to respond to the crisis? 0 = Low Level of Uncertainty (Decision makers have alternatives with which to approach the crisis and feel confi dent that the alternatives will work but are uncertain about which alternative to pick.) 1 = Medium Level of Uncertainty (Decision makers have a system for managing the crisis, but it takes time to fi gure out and they are unsure of the effective- ness of the system.) 2 = High Level of Uncertainty (Decision makers have no way of approaching the crisis; there is a sense of chaos and high stress.) 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) 1–49 CASESPRS Description: How unexpected was the crisis for the decision makers? 176 Appendux B: Crisis Management Case Coding Guide

0 = Not unexpected (Event was anticipated; indeed the possibility of it occurring had been discussed thoroughly.) 1 = Somewhat expected (Policymakers knew something like this was possible but it had not been discussed recently or thoroughly.) 2 = Highly unexpected (Event was a complete surprise.) 9 = Unknown (not enough information to code for this variable) 99 = Not applicable (variable does not apply to this case) 1–50 CASEDMCY Description: What is the country of residence of the key decision maker? (Please use two-letter country code; see list below. If key decision-making unit is trans- national, code as 99.)

B.2 Thematic Analysis

Variables in this section were coded while considering the case as a whole (overall impressions) and taking the perspective of the decision-making unit on which the case writer has focused.

B.2.1 Decision Unit Variables

4–2 DUCAUTH – Decision Unit/Centralization (Contraction of Authority) Description: Was there a vertical movement of power up the chain of command into the hands of one or a few strong leader(s) at any point? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–4 DUDECNT – Decision Unit/Decentralization Description: Did decentralization occur through the use of informal/ad hoc groups or formal dispersal of power at any point? 0 = No decentralization 1 = Ad hoc/informal groups were used (informal decentralization; not institutionalized) 2 = Formal decentralization occurred (within a set framework and procedure) 3 = Both informal and formal decentralization occurred 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case Appendux B: Crisis Management Case Coding Guide 177

B.2.2 Preparedness Variables

4–29 PRSOP – Preparedness variables/Standard Operating Procedures Description: Had any Standard Operating Procedures (formalized, prescribed pro- cesses an organization usually follows in certain situations) been established within the organization for the circumstances they are currently facing ? 0 = No Standard Operating Procedures had been established 1 = Some Standard Operating Procedures had been established, but not specifi - cally for the crisis at hand 2 = Yes, Standard Operating Procedures had been established for crises like this one 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–31 PRSOPEF – Preparedness variables/SOPs effect on crisis Description: If these SOPs were relied upon, what effect did they have on the crisis? 0 = Positive effect (helped) 1 = No effect 2 = Negative effect (exacerbated the crisis) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case

B.2.3 Value Confl ict Variables

4–37 VC1STVAL – Value confl ict variables/Short term values Description: What was the most important short-term value at stake? (e.g., organi- zational agenda, effi ciency, status, career goals, etc., that were at stake for deci- sion makers) 1 = Preservation of life 2 = Economic well-being 3 = Rule of law 4 = Reputation/legitimacy/credibility 5 = Security 6 = Justice 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 178 Appendux B: Crisis Management Case Coding Guide

4–42 VCDGR – Value Confl icts variables/degree of confl ict -stakeholders Description: What was the degree of value confl ict among? 0 = Low (all possess roughly the same values) 1 = Medium (stakeholders possess some of the same, and some differing, values) 2 = High- (stakeholders possess entirely different values; there is no commonal- ity of values) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–44 VCDMG – Value Confl icts variables/within decision unit Description: Were there value confl icts between equivalent individuals within the decision-making group? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case

B.2.4 Leadership Variables

4–47 LDORG – Leadership Variables/Organization of primary decision making unit Description: How was the primary decision-making unit that dealt with this crisis organized? 1 = Centralized (with a chain of command and specifi ed functions) 2 = Overlapping (overlapping areas of responsibility and competition) 3 = Collegial (functioning more as team with accountability shared among those involved) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–49 LDINFTYP – Leadership Variables/most infl uential decision unit type Description: Which types were most infl uential in the decision-making process? 1 = Predominant Leader 2 = Single Group 3 = Coalition 4 = Predominant Leader and Single Group 5 = Predominant Leader and Coalition 6 = Single Group and Coalition Appendux B: Crisis Management Case Coding Guide 179

7 = Predominant Leader, Single Group, and Coalition 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–55 GRDRRF – Group Dynamic variables/“Rally around the fl ag” Description : Was “Rally around the fl ag” evident at any point in this case? (Did decision-making group members come together around a common value or sym- bol in a way that discouraged debate or discussion?) 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–56 GRDGTHK – Group Dynamic variables/“Groupthink” Description : Was “Groupthink” evident at any point in this case? (Did decision- making group focus on maintaining cohesion and loyalty by striving for unanim- ity and closing itself off from information that differed from or challenged predominant opinion?) 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–57 GRDNEW – Group Dynamic variables/“New Group Syndrome” Description : Was “New group syndrome” evident at any point in this case? (With few procedural norms, did decision-making group members tend to conform to what leaders asked?) 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–59 GRDGOM – Group Dynamic variables/“Game of Maiden” Description : Was a “Game of Maiden” evident at any point in this case? (Did mem- bers of a decision-making group try to avoid being associated with negative events by shifting responsibility for actions to another person/group/ organization?) 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 180 Appendux B: Crisis Management Case Coding Guide

4–62 GRDLYLT – Group Dynamic variables/decision unit in-group loyalty Description: What was the level of group loyalty exhibited by decision-making group members? 0 = Low (little loyalty) 1 = Moderate (some loyalty) 2 = High (much loyalty) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–69 GRDITRST – Group Dynamic variables/Trust toward in-group Description: What was the level of trust the decision maker(s) displayed through behavior/deeds or words toward their own group ? 0 = Low (little trust) 1 = Moderate (some trust) 2 = High (much trust) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–70 GRDOTRST – Group Dynamic variables/Trust toward others Description: What was the level of trust the decision maker(s) displayed through behavior/deeds or words toward others outside their decision-making group? 0 = Low (little trust) 1 = Moderate (some trust) 2 = High (much trust) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case

B.2.5 Crisis Communication Variables

4–80 CCCRED – Crisis Communication variables/Credibility with media Description: What was the key decision maker(s)’ degree of credibility with the media at the outset of the crisis? 0 = Low 1 = Medium 2 = High 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case Appendux B: Crisis Management Case Coding Guide 181

4–81 CCRLTN – Crisis Communication variables/Media relationship throughout crisis Description: How did the decision maker(s)’ relationship with the media change/ develop throughout the crisis? 0 = Deteriorated 1 = Stayed about the same 2 = Improved 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–82 CCSTRTG – Crisis Communication variables/Primary media strategy Description: What was the decision maker(s)’ primary strategy with regard to the media? (not a scale) 1 = Proactive 2 = Reactive 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–87 CCDCRDA – Crisis Communication variables/Level of coordination of crisis communication- all Description: What was the degree of coordination across all decision-making groups regarding communicating with the media and external stakeholders? 0 = Little or no coordination (decision makers communicated separately and pro- vided confl icting information) 1 = Moderate coordination (information was presented at scheduled times but with each decision-making unit presenting their own information) 2 = High level of coordination (decision-making units had one point person present- ing information and an integrated strategy for dealing with media and public) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–88 CCCMPLX – Crisis Communication variables/Complexity of communication between units Description: In general, what was the level of complexity in the decision-making units’ approach/form of communicating with each other? (not a scale) 1 = Sender (“one-way” from sender to receiver) 2 = Volume (socially and contextually based communication taking into account nature of audience) 182 Appendux B: Crisis Management Case Coding Guide

3 = Dialogue (interaction between sender, channel used to send information, and receiver; “two-way”) 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–91 CCXTREME – Crisis Communication variables/Extreme portrayal Description: In general, did decision makers go to extremes in estimating the effects of the crisis, either painting the situation as overly bleak or too rosy? 0 = No 1 = Decision makers were overly positive 2 = Decision makers were overly negative 3 = Decision makers changed over time from one extreme to another 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case

B.2.6 Learning/Adaptation Variables

4–128 LGNMOD – Learning/Adaptation variables/Learn but not modify Description: Did any decision makers learn at any time during this crisis but not modify their approach and assumptions until this crisis was over? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–129 LGMOD – Learning/Adaptation variables/Learning and modifying Description: Did any decision maker learn from positive or negative feedback received during the crisis and modify their practices as a result during the crisis? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–130 LGHIST – Learning/Adaptation variables/Historical analogies Description: Did any decision maker use historical analogies to draw lessons at any point during the crisis? 0 = No 1 = Yes Appendux B: Crisis Management Case Coding Guide 183

9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–131 LGEXP – Learning/Adaptation variables/Learning from experience Description: In the aftermath of this crisis, did decision makers draw any con- clusions or learn any lessons based on comparisons (perceived similarities/ differences) between this crisis and other/previous crisis experiences of the group? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case

B.2.7 Crisis Culture Variables

4–134 CUPART – Crisis Culture variables/Preparedness Description: Which was most dominant in participating in preparedness and plan- ning for crises like the present one? 1 = Public 2 = Government and/or governmental agency 3 = Individual households and businesses 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–137 CUDCSV – Crisis Culture variables/Decision maker decisiveness Description: How decisive were the actions of decision makers? 1 = Not very decisive – hesitant 2 = Moderately decisive 3 = Highly decisive 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–138 CUFOCUS – Crisis Culture variables/Decision maker focus Description: In general, were the decision makers more focused on: 1 = Task 2 = Process/People 3 = Both 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 184 Appendux B: Crisis Management Case Coding Guide

4–141 CULOCAL – Crisis Culture variables/Information sharing Description: In general, was information localized (few people had access to information)? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–142 CUCHNL – Crisis Culture variables/Information Channels Description: In general, which information channel was most dominant? 1 = Formal 2 = Informal 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–143 CUIPROC – Crisis Culture variables/Information processing Description: In general, was decision makers’ information processing: 0 = Lacking 1 = Indirect and unclear 2 = Direct and to the point 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–146 CUCONC – Crisis Culture variables/Concern for other Description: Did concern and sensitivity for others (outside the decision-making group) become salient in communications within the decision-making group? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–147 CUCLNG – Crisis Culture variables/Collective Learning Description: Was collective learning emphasized by decision makers? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–152 CUREGS – Crisis Culture variables/Organizational Regulations Description: In the aftermath of the crisis, were new organizational rules/regula- tions established (as a result of the learning process)? Appendux B: Crisis Management Case Coding Guide 185

0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–153 CULEG – Crisis Culture variables/New legislation Description: In the aftermath of the crisis, was any legislation introduced as a result of the learning process? 0 = No 1 = Yes 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–154 CUBLAME – Crisis Culture variables/Blame Description: Whom did the public blame most if things went wrong? 0 = No blame assigned 1 = Decision makers 2 = System (political institutions) 3 = Technology 4 = Fate/bad luck 5 = Stakeholders 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case 4–155 CUDUBLM – Crisis Culture variables/Blame Description: Is the dominant focus of the decision makers to blame: 0 = No blame 1 = Individual(s) within their own group who did not know established proce- dures and/or lacked expertise 2 = Personal incompetence of a subordinate 3 = System 4 = Technology 9 = Unknown – not enough information available to code 99 = Not Applicable – does not apply to this case Appendix C: TCM Crisis Cases Dataset

Titles of crisis cases Authors Asian Financial Crisis: IMF in Indonesia LaJune Barnes Train Accident at Khanna, India 1998 Venu Prasad Arabandi Love Canal Hazardous Disposal Site Jack Schuler 2003 California Wildland Fires Andrea Powers Hurricane Katrina Jaime L. Bell Crisis in Congo Jessica Arnett Myanmar Crisis 2007: Saffron Revolution Austin Cusak Tiananmen Crisis of 1989 Thuy Dang Siege of Colombian Palace of Justice Felipe Estefan Plot to Assassinate Hitler, 1944 Matthew Duncan Violence in Israeli-Palestinian Confl ict 2006 John Paul Mejia India Pakistan Brinkmanship Crisis Arun Pathak 2002 Gujarat Riots Suprita Kudesia 2008 Waste Emergency in Naples Pierpaolo Capalbo Falcone Assassination by Cosa Nostra Emily Mallozzi Kidnapping of Aldo Moro by the Red Brigade, 1978 Alexia Christensen NEIS (National Education Information System) in Korea Byoung-Gi Kim Korean Financial Crisis Richard Ahn Rail Strike in South Korea 2003 NamKyo Seo 1997 Korean Financial Crisis Jong Hoon Park Daewoo Group Financial Crisis Yong Hwan Kim Korean Cargo Truckers Boycott Sang-Yuk Kim Strike of S. Korean Gov. Employees’ Union 2004 Hyunsoo Kim Guangzhou Crisis of 1839 Jason Burns The Hanbo Scandal Bang Ryul Yum

List of cases, used in this study, drawn from the Transboundary Crisis Management (TCM) dataset located at the Moynihan Institute of Global Affairs, Syracuse University

© Springer International Publishing Switzerland 2015 187 Á.E. Bernhardsdóttir, Crisis-Related Decision-Making and the Infl uence of Culture on the Behavior of Decision Makers, DOI 10.1007/978-3-319-20714-8 188 Appendix C: TCM Crisis Cases Dataset

Titles of crisis cases Authors Gulf War Crisis Julio Arana Watergate Break-In Ronald Marcsisn Air Traffi c Controllers Strike (PATCO) Jonathan Rost Attica Prison Riot Timothy Mahar Crisis Management in Love Canal Yung Ki Lee The Federal Raid on Ruby Ridge Anita Puterbauch Columbia Shuttle Disaster Allan C. Breese 1981 Air Traffi c Controllers Strike Andrew Hyatt The Collapse of Arthur Andersen Patrick Kelly Long Term Capital and the Federal Reserve David R Lacasse Ranger School Deaths 1995 Richard J Hoerner DC Anthrax Situation Chris Dixon Bay of Pigs Stephen Choquette Jones The Attack on Pearl Harbor Michael Curtis 2000 US Elections, Florida Jaime W. Saunders Truman and U.S. Foreign Policy Tim Meador Suez Canal Abdulrazzak Alsadoon Attica Prison Riot Laura Blake The Collapse of WorldCom Shonale Burke US Military and the Mayaguez Incident Robert Borders Apollo 13 Cynthia Robertson Kosovo Crisis of 1998–1999 Michael Scherger Bhopal (Chaudhary) Sanjay Chowdbury Nuclear Waste Site Crisis Hee-Sook Yoo Biker Wars in Scandinavia 1994–1997 Lina Svedin 1974 Turkish Military Intervention in Cyprus Sotirios V. Gountas BSE and British Government’s Action William Mark Thornhill II President Bush’s Rejection of the Kyoto Protocol Miki Ouchi 1975 New York City Financial Crisis Barry Weiss YMCA Lisa Hoeschele The Enron Collapse Karen Kerling San Francisco’s Loma Prieta Earthquake of 1989 Kathy Allison Disaster at Waco William Koester Exxon Valdez Patricia A. Watson Yellowstone Forest Fire Ruthanna Hawkins DMZ-One Tree Crisis at Panmunjom, Korea 1976 Michael T. Perrin 2000 US Presidential Election Ekin Senlet DC Sniper Richard A. DeLude II Space Shuttle Columbia Disaster S. Fullen Exxon Valdez Oil Spill 1989 Jessica Tevebaugh Red River Floods 1997 Lina Svedin Collapse of the De La Concorde Overpass Marie-Claude Francoeur Denmark Cartoon Crisis Mykhaylo Komarnytskyy Earthquake in Gujarat, India Bhatiacharyya Amitava Appendix C: TCM Crisis Cases Dataset 189

Titles of crisis cases Authors Election Bombing in Andhra Pradesh, India Suresh Chonba Hijacking of Indian Airlines Flight 814 Lok Ranjan Ethnic Violence in Assam, India Davinder Kumar The 26/11 Mumbai Attacks Roko Shanti Devkota Chhetri Great Hanshin Earthquake Junko Eiko Capital Relocation Project in Korea Sang Seob Kim 2002 Cheonggyecheon Restoration Project Mihyang Park Y2K in Korea Yong-sik Shin Buan Nuclear Waste Disposal Facility Deuk Won Reuw Buan Crisis in South Korea Koon Joo Lee Presidential Impeachment in South Korea, 2004 Suik Kim Sampoong Department Store Collapse Daeja Kim Murder of Theo Van Gogh Sarah Goldfarb Thailand 2008 Political Crisis Giang Nguyen Hood Crisis between Turkey and US, 2003 Ozlem Savas Guns of Dorchester: American Siege and British Response in Michael Apicelli Revolutionary Boston London Transit Bombings 2005 Ashley Volkmar 1998 US Embassy Bombings in East Africa Diana Keller Watergate and the Fall of Richard Nixon John Barone Pan Am 103 and Syracuse University Lil O’Rourke Assassination attempt on President Reagan Raphael J. Hamilton Los Angeles Riots of April 1992 Obrien Simasiku Iran Hostage Crisis Ed Cox US Policy on Haiti during Clinton Administration Gifford Miles FEMA Response to Hurricane Isabel, 2003 Erin Connolly Cuban Missile Crisis James Petrone The US BSE Crisis John Flaherty Hurricane Isabel Teresa Irving New York City Transit Strike 2005 David Bailey Ramstein Air Show Disaster Rebecca Terry U-2 Incident Thomas Squires Accident at Three Mile Island (March) Steve March FAA and September 11 John Joseph Woodin Apollo 13 Jay H. Cha Rapid City Flood 1972 Richard Horsley Oklahoma City Bombing Nathan Thiel Georgia Water Crisis 2006–2007 Matthew Clayton Aub Ghraib Crisis Nikki Allem Kenya’s Post-2007 Election Crisis Monica Clark Haitian School Collapse of 2008 Petrona Salmon Baia Mare Cyanide Spill Anna Bartosiewicz Bhopal Gas Tragedy Anand Rao 190 Appendix C: TCM Crisis Cases Dataset

Titles of crisis cases Authors Riots in Malegaon Kishore Gajbhiye Flash Floods in Sirsa, India Sundeep Singh Dhillon Tsunami in Andaman and Nicobar Islands 2004 Anuradha Sharma Chatgi Korean Currency Crisis, 1997 YongKeun Pai 1994 North Korea Nuclear Crisis Hyun Su Han Jeonnam, Korea, College Merger Seung-cheol Lim Rangoon Bombing of 1983 Heesoon Kim Lebanon and Hezbollah’s Internal Clash, 2008 Lamis Sleiman Pan Am 103, Lockerbie Perspective Melissa Dios US Government Policy, Plan Colombia Brian Ramirez Iran Hostage Crisis and the Carter Administration Richard Reagan Love Canal Dana Horrell Columbine School Shooting (Lamanna) Gloria C. Lamanna Hurricane Andrew John Styer Hurricane Iniki, 1992 Robert Donner Virginia Tech Massacre Paul Dimoh Florida’s 2004 Hurricanes Gilbert Huron 1987 US Stock Market Crash Marco Markov U.S. Intervention in Somalia (Averil) Bryan Avenill Cryptosporidium Outbreak Cecile Batchelor Somalia (Seitz) Marcus Seitz Labor Day Storm John G. Eberle 9/11: Response of St. Vincent’s Hospital Christopher Morley Black River Contamination, New York State Philip Church Collapse of the Silver Bridge Robert Sinnett Duke University Lacrosse Scandal Wayne Westervelt Abbreviations and Acronyms

A S As sertiveness CLF C ollective L earning F ramework CRISMART Cris is Ma nagement R esearch and T raining Center in Stockholm ECB E uropean C entral B ank E U E uropean U nion F O F uture O rientation G E G ender E galitarianism GGCT G rid- G roup C ultural T heory GLF G roup L oyalty F ramework GLOBE G lobal L eadership and O rganizational B ehavior E ffectiveness Research Program H O H uman O rientation HRO H igh R eliability O rganizations InC In -Group C ollectivism InstC Inst itutional C ollectivism NASA N ational A eronautics and S pace A dministration (USA) N A T O N orth A tlantic T reaty O rganization NGS New Group Syndrome P D P ower D istance P F P reparedness F ramework P O P erformance O rientation SOP S tandard O perating P rocedures SPSS S tatistical P ackage for the S ocial S ciences TCM T ransboundary C risis M anagement project at Moynihan Institute of Global Affairs at Syracuse University U A U ncertainty A voidance

© Springer International Publishing Switzerland 2015 191 Á.E. Bernhardsdóttir, Crisis-Related Decision-Making and the Infl uence of Culture on the Behavior of Decision Makers, DOI 10.1007/978-3-319-20714-8 Bibliography

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