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CDM WORKING PAPER SERIES

Networks That Matter: Planning and practice in the complex disaster environment

following the September 2009 Padang, Indonesia Earthquake

Leonard J. Huggins and Jian Cui

Working Paper: 1103

http://www.cdm.pitt.edu/AboutCDM/CDMWPS/tabid/1346/Default.aspx

CENTER FOR DISASTER MANAGEMENT

Graduate School of Public and International Affairs

University of Pittsburgh

3913 Wesley W. Posvar Hall

230 S. Bouquet St

Pittsburgh, PA 15260

November 3, 2011

The views expressed herein are those of the authors and do not necessarily reflect the views of

the Center for Disaster Management and the University of Pittsburgh.

© University of Pittsburgh, 2011. By Leonard J. Huggins and Jian Cui. All rights reserved.

Working Paper: Not for citation without consent of the authors

http://www.cdm.pitt.edu/AboutCDM/CDMWPS/tabid/1346/Default.aspx




CDM Working Paper No. 1103

APPAM Paper No.: PAPER2306

November 2011

ABSTRACT

Following the catastrophic tsunami of December 26, 2004, the Government of Indonesia

embarked on a program to reform its disaster management structure with key emphasis on

preparedness. While the new disaster management plan was adopted at the national level before

September 2009, the province of West Sumatra had not yet implemented the new system.

However, the City of Padang, within the province of West Sumatra, was one of the few localities

that actively participated in the reform process and actually implemented the plan prior to

September 30, 2009. On September 30th

, 2009, a 7.8 Magnitude earthquake struck 38 miles off

the shore of Padang and sharply tested the effectiveness of the newly adopted disaster plan. This

paper identifies the networks of communication and coordination that emerged among the actors

engaged in response to the earthquake. While the social network analysis show significant

interaction among national public agencies within the new system of disaster management,

serious gaps remain in promoting coordination among subnational agencies as well as between

private and nonprofit organizations, key sectors essential to maintain a resilient community.

Managers could use this information to reframe the policy issues and guide implementation of

disaster risk reduction strategies for future threats, especially during periods of transition from

one system of disaster management to another.

Leonard J. Huggins

Graduate School for Public and International Affairs

Center for Disaster Management



[email protected]

Jian Cui

Graduate School for Public and International Affairs

Center for Disaster Management



[email protected]

mailto:[email protected]

1

2011 Association for Public Policy Analysis and Management (APPAM)

Fall Research Conference, November 3-5, Washington DC




Introduction

Poor information flow among networked organizations is among the principal sources of failure

in the preparation for, and management of, disasters. On September 30, 2009, a magnitude 7.8

earthquake struck West Sumatra Indonesia collapsing over 3000 buildings and apartments and

leaving over 1115 people dead, despite six months of aggressive disaster preparedness through

the implementation of a new disaster management governance structure in West Sumatra and

other parts of Indonesia (BNPB, 2009). The sobering fact is that such events are no longer

unexpected in this region, but residents prepared for a tsunami that eventually did not occur, and

some sadly lost their life to the Earthquake instead. Disaster managers prepared the community

to anticipate the sequence of interdependent events that may occur in a disaster and to plan

actions to save lives and property. Yet, during the stressful and urgent environment of the actual

disaster, poor information flow, uncertainty and the complexity of the event overwhelmed the

community and disaster managers.

Failures in the interorganizational network further exacerbated delays in communication.

There were gaps in implementation as some organizations still functioned under the older system

of disaster management based on traditional responsibilities while others adopted the new

approach. Such gaps exposed a key policy problem in the timely adaptation and implementation

of public policy. Successful reduction of risk requires not only informed public policy and

systematic education in all phases of disaster management, but also the sustaining of an

organizational network within the disaster response and emergency management environment

(Comfort, 1999).

In 2008, all exercises and training activities were placed under the newly established

BNPB. The exercise held in Padang in February, 2009 served as an organizing framework for

response operations in the October 30, 2009 earthquake. First, public officers with key

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responsibilities for emergency operations immediately contacted one another by radio, and the

Mayor of Padang City activated the emergency plan within five minutes of the earthquake.

Second, when residents felt strong shaking from the earthquake, they followed evacuation signs

posted on the streets (prior to the earthquake), which guided them to higher ground. Third, the

emergency plan activation enabled key officials to mobilize response operations immediately

with continued electrical power.

This paper aims to exam the effectiveness of the new system of disaster response and

preparedness in Indonesia in the aftermath of the October 30, 2009 earthquake. It also identifies

any possible conflict between the co-existing systems. More specifically, we ask the following

questions: 1) how effectively does the de facto system work in terms of interaction and

communication, taking organizational overlapping and conflict into account? 2) to what extent

does the new system supersede the old system while yet being challenged by it? By conducting

network analysis on data from local newspapers for three weeks following the event, the paper

critically examines the role of response networks during times of organizational transformation

from a network perspective. It examines the gaps in the emerging disaster response network

following the earthquake (practice) for consistency with the organizational changes implemented

under the new Indonesian disaster management law (planning).

Background: City of Padang and Indonesia’s Disaster Preparedness Framework

Following the devastation of the December 26, 2004 Indian Ocean Tsunami, public leadership in

Indonesia embarked on an intensive initiative in disaster reduction. The initiative sought to

overhaul existing disaster management legislation and public administration structures to

improve planning and preparedness for disasters. Padang, Indonesia was one of six cities in

Indonesia selected for focused investment in disaster reduction.

Padang was a critical site as almost 75 percent of its 900,000 residents live or work in

low-lying areas prone to inundation from flooding associated with tsunamis (Antara, 2009). This

high degree of vulnerability emphasizes the need to build national and local preparedness as part

of establishing any early warning system. According to the UNESCO Intergovernmental

Oceanographic Commission for the International Early Warning Programme (IEWP), “securing

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the downstream flow of information from the warning centres to populations and communities at

risk” poses the most difficult challenge in early warning systems (UNESCO, 2006).

Organizational transformation

Under the new national disaster management law (Law 24 of 2007), the Government of

Indonesia planned and conducted training and evacuation drills for the communities and public

institutions and leaders. One of the major changes under this new law was the broadening of the

focus to a holistic-approach to disaster management. Such a change required the establishment of

a new national agency, the BNPB (Badan Koordinasi Nasional Penanggulangan Bencana), which

now has greater autonomy than the previous agency. Also, under the new structure, the agency

executive director reports directly to the president, avoiding much of the bottleneck associated

with more hierarchical reporting structures.

The system also transformed the old administrative system of regional ad-hoc agencies

(SATKORLAKs) and municipal councils to local and provincial Disaster Management agencies

(BPBDs) that sought to assess risk, train emergency responders, and educate local people

regarding disaster risk reduction. This process began in 2007, and while the national agency was

well established by the end of 2008, several provinces lagged behind in their commissioning of

the provincial BPBDs.

Figure 1 provides a glimpse of the subset of this new system at the provincial level (West

Sumatra). By 2008, the City of Padang had adopted the action plan and later developed standard

operating procedures for disaster response with responsible public agencies. The City of Padang

commissioned its local BPBD in February 2009, but several localities and provinces such as

West Sumatra did not do so until late 2009 or in 2010. Prior to the earthquake of September 30,

2009, the City of Padang had implemented the new disaster plan through an intensive training

program and field exercise for disaster risk reduction in the City. Notably, while the City of

Padang was prepared to utilize the new plan on September 30, 2009, the Province of West

Sumatra was not fully prepared as it had not fully implemented the new system. Such

unevenness in the transformation and transition to the new structure presents key gaps which

may cause fragmentation in the operating and responding environment, and ultimately

vulnerabilities in information “downflow” as well as decision making.

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Figure 1. Planned Disaster Management Organizational Structure for the Province of West

Sumatra, Indonesia (SOURCE: Disaster Management Plan West Sumatra Province 2008-2012)

The Test

On September, 2009, the 7.8 Magnitude earthquake that struck 38 miles off the shore of

Padang sharply tested the effectiveness of the newly adopted disaster plan. While the City of

Padang was planning and conducting preparedness activities for a tsunami, the earthquake

caused loss of 1,115 lives and severe damage to its infrastructure. How did the City of Padang

and Indonesia perform, in terms of interaction and communication, amidst the transition to a new

disaster management structure? To what extent was the new system taking hold over the old, yet

coexisting, system of disaster management? These are questions that we examine from the

perspective of organizational networks following the disaster event.

Complexity, Organizational Transformation and the Relevance of Networks of Action

The planned transformation of a system of management across many agencies is, even

under the best of circumstances, characterized by inconsistencies and inadequate information that

need to be overcome to mobilize effective action. Working under urgent time constraints in the

complex environment following a major earthquake increases the stress on decision makers who

are responsible for the lives, property, and continuity of operations of their community. Decision

5

makers cope with urgent demands by relying on other actors who share their responsibilities, but

adapt their actions reciprocally through a unity of effort (Flin, 1996). Common training and

coordination may enhance decision making among these actors, but it is the relationships among

them, the exchange of information, and the communication achieved among members of the

team that provides the basis for effective decision making and coordination. This shared

perspective creates a ‘knowledge commons’ among members of an emerging network of actors

that can act collectively under extreme conditions. Establishing integrated patterns of

communication to mobilize action, resources, knowledge and personnel during a disaster event is

therefore critical to reducing risks and saving lives in the uncertain disaster environment.

Holland (1999) grapples with the complexity and interactive exchange of information

among agents and the external environment, where the interacting agents define, follow, and

redefine their working rules through the three fundamental mechanisms of tagging, internal

models, and building blocks. Here, tagging refers to a process that is informed by aggregation,

the first structural property that each agent begins their individual learning and decision making.

Through this process, agents learn through interaction and feedback from other agents and the

environment. During this process, the system aggregates diverse forms of information and

performs nonlinearly. Such process finally forms up the function-based flexible structure of the

system, which lead to the hierarchical but diverse adaptation attribute of the whole system.

Holland’s theory provides a streamlined framework of four structural properties and three

mechanisms to understand the complex adaptive system (figure 2), which facilitates the

application of network analysis. In this theory, complex systems are modeled by structure,

process, and their aggregating hierarchy from micro level to meso and macro levels.

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Figure 2. Theoretical framework of Complex Adaptive System (Holland, 1999)

Disaster preparedness not only requires communication and training, but organizational

coordination mechanism building. In fact, both preparedness and response revolve around action

networks that are inter-organizational, multi-jurisdictional, and interdisciplinary. These

networks depend highly on collaboration among organizations as well as the ability of its

participants to generate valid information, facilitate informed choice and foster timely

commitment to action (Comfort et al, 2011a). Networking during the disaster response provides

a promising representation of the working dynamic system, where effective information and

interaction take place. Preparedness is not only local or national, but also global due to the

increasingly trend in global response to disaster events. As such, disaster preparedness and

disaster management networks undertake a much broader scope than local organizations can

often manage, especially in terms of actor heterogeneity and their roles to adapt to the response

system in general. Further, awareness of changes in local disaster management structure in the

global community can facilitate more coordinated efforts to save lives and properties in the

actual disaster event. However, a prior presumption that every actor would envision the new

working system and thus take advantage of the resources would be farfetched, and would

possibly lead to ineffectiveness, if not to systematic dysfunction and organizational conflict. This

paper examines the local, national and international networks that emerged following the

September 30, 2009 earthquake to further assess how any gaps in collaboration, particularly

associated with the organizational transformation and preparedness, impacted the response.

Disaster preparedness also shows growth in organizational learning. Since the

catastrophic disaster event of December 26, 2004, Indonesia had embarked on substantive

7

training and awareness among both communities and organizations. This approach supports the

finding that the key to early warning systems and disaster preparedness and response is effective

networks of action that relay information to decision makers, vulnerable populations and

responders in a timely manner (Comfort, 2011b). According to Andreou et al, 2010, designing

an information process to support learning relies heavily on the underlying information

infrastructure including the networks that undertake action or facilitate information sharing.

Multiple organizations, multiple information sources and multiple recipients must engage in a

common information system to harness the full reach and effectiveness of the information

exchange to reduce risks and vulnerabilities (Axelrod and Cohen, 1999). The conscious design

of organizational networks of actors is key in the complex disaster environment which relies on

the interconnectedness of both the social and technical networks to provide early and effective

warning to communities (Boulas et al, 2011). Yet, there remain discrepancies between

information generation and dissemination as well as preparedness and practice. This framework

of networks provides an avenue to assess how the City of Padang was able to execute its newly

adopted disaster response plan following the September 2009 earthquake.

Methods and Analysis: Assessing the September 2009 Earthquake Response Networks

We use the techniques and methods of Social Network Analysis (SNA) to identify the networks

of communication and coordination that emerged among the actors engaged in response to the

earthquake. Following a content analysis of local newspapers for three weeks after the event, a

network dataset was developed to provide formal and strict methods to measure interaction and

interdependence among interacting units (Wasserman and Faust, 1994). Within the framework of

SNA, actors and their actions are viewed as interdependent and responsive, rather than

autonomous and isolated. Relational ties here serve as channels to transfer resources and

information, while the de facto structure of the working system that includes both the old and

new management systems serves to buttress the networking flows.

Selection of Articles and Data Coding:

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

8

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 a “Socioteam” at the Center for Disaster Management at the University of

Pittsburgh (i.e. 7 additional doctoral and postdoctoral researchers) to validate systematic social

network coding and to minimize threats to validity.

Analysis:

Once the network data were authenticated, it was imported into UCINET software as well

as ORA where static and dynamic network analyses were performed. Network analysis allows

the researcher to determine the strength of ties among actors in a network of organizations

(Wasserman and Faust, 1994; Borgatti et al, 2002). Both UCINET and ORA were used to

compare consistency of the centrality statistics provided for the network. ORA was also used to

perform the dynamic network analysis over time. The analysis represents network performance

from the global network perspective as well as the local/provincial (Padang/West Sumatra)

network perspective. The findings from the network analysis allow managers to identify gaps in

the response network and use this information to reframe the policy issues and guide investment

for disaster risk reduction of future threats.

Limitations:

Limited by second-hand data, it is nearly impossible to exclude alternative factors leading

to a more effective response to the September 2009 Earthquake. Such factors, such as the local

transportation reform of Padang City before the earthquake as well as specific community

programs to improve the individual capacity at the local level, are not analyzed in this study.

Meanwhile, in their paper “Planning Matters,” Comfort at el. (2009) pointed out three factors

contributing to reducing disaster risk in Padang and West Sumatra from the perspective of

9

network and its effect. They are 1) annual training exercises for tsunami warning and evacuation

organized by national agencies since 2004, 2) high-level public awareness of tsunami risk and

immediate self-evacuation of Padang citizens, 3) back-up generators at key facilities - radio

station, hospitals, fire station, and mayor’s residence to maintain a resilient leadership and

information flow. Though they carry a network epistemology, the understanding of how this

emerging network works in practice still remains less measured and insufficient. The reform of

BNPB system captures these three perspectives. This paper emphasizes the structure of

networks, which creates constraints and opportunities for individual actions. And such structure

is regarded as a lasting pattern of relations among all actors involved in the response period.

Findings: Networks that Matter

Since the catastrophic tsunami event of December 26, 2004, Indonesia has committed resources

to reduce vulnerabilities in communities through disaster preparedness planning, training and

education. The change in disaster management structure to shift to a holistic approach is one of

the key commitments. Network analysis was used to understand the performance of the response

networks following the September 2009 earthquake in the following discussion.

Transforming Policy to Practice: What worked and didn’t work?

Initially and as expected for a disaster with international focus, the Indonesian Office of

the President (IoOOP) was the central actor very early in the response (Figure 3 and 4).

However, after the initial response (3 days) when the focus turned primarily to the disaster

response operations on the ground, the Indonesia BNPB (the new national disaster management

coordinating arm) assumed key centrality for disaster operations (Figure 4). See appendix 3 for

detailed network statistics. Several national ministries and the Government of Indonesia

(GoIndo) also increased their degree of centrality within this phase of the response. Nine of the

top 10 actors with highest level of in-degree centrality were among national ministries

(Appendix 3), where they were pivotal in responding to communications from other

organizations. This showed that at the national level of the new system of managing disasters

was taking hold.

10

Figure 3. Most central organization (IoOOP) in the disaster response network.

Noticeably, however, the old SATKLORLAK (SATKOR) remained among the key

actors with a total degree centrality of 0.100 compared to 0.330 for the most central actor in the

Indonesian Office of the President (Figure 4). This presents an area of conflict. This conflict

arose at two levels: (1) at the national level where several international organizations were not

fully aware of the institutional changes within Indonesia (Figure 4), and (2) at the provincial

level where the province still functioned under the old system of disaster management while the

City of Padang and the national level organizations operated under the new system. International

relief and rescue organizations (except the UN agencies) appeared to coordinate with familiar

faces within the national ministries who at that time did not have central responsibility for

coordination and management of disaster response operations. On the plus side, since the only

coordination with the Satkorlak on the national level involved international agencies, it indicates

that the process of transition to the new system among national organizations was taking hold.

In both cases however, poor information flow caused unevenness in the response operations.

While the province and the City of Padang had the same set of responsibilities working in the

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already complex and changing disaster environment, they were not operating under the same

system of management or rules. Operating under different management structures created an

obstacle to the information flow process, especially at the provincial and local levels.

A common operating picture is fundamental to improve decision making in the disaster

environment (Comfort et al, 2006). Research has shown that information should be extracted

from known domains prior to the disaster and integrated with information generated from the

disasters for response to be highly effective (Comfort, 2011a, von Lutz et al, 2008). However,

actionable knowledge, as such combination is referred to, depends on compatible networks of

action that facilitate the timely exchange and sharing of information, including both information

generation and dissemination. Yet, the uneven transition to the new disaster management

system was not ideally implemented to minimize such inefficiencies. The patterns of

preparedness in West Sumatra were largely dominated by the national organizations. According

to Comfort et al, 2006, a knowledge commons provides an avenue to alleviate such discrepancies

before and during the disaster, as organizations would be operating with the same pool of

information to make better informed decisions in the uncertain disaster environment.

Figure 4. Total degree centrality for top 8 networked organizations

up to 3 weeks following the earthquake

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Figure 5. Degree centrality among organizations up to 3 weeks

following the earthquake using UCINET

13

The networks that emerged from the September 30, 2009 event were different than those

expected based on the post disaster plan. First, we draw reference to the degree of betweenness

among organizations. Betweenness centrality measures the location of actors in the network

relative to other actors. In essence, an organization with high betweenness has high influence

over what flows in the overall network. By definition of the traditional disasters law, it is

expected that the national BNPBs and the provincial/local BPBD should have high betweenness

centrality and this relationship should be sustained throughout the response phase. However, this

was not the case (Figure 6). The national BNPB accounted for the initial spike in betweenness

centrality on October 1, 2009 while the Padang Office of the Mayor (PadOOM) and West

Sumatra Office of the Governor (WSOOG), not the BPBD, accounted for spikes near the end of

the three week response period under examination. This pattern was not sustained throughout

the period and in fact was much lower than the out and in degree centralities for the same period.

This indicates that while organizations may have been connected, they did not rely primarily on

the BPBD or BNPB for information and activities during most of the response phase. At the

local level, the political administration drove the early operations. Such process further suggests

that information was not appropriately validated by the designated organization, further causing

fragmentation in the information flow.

Figure 6. Comparison of degree centrality among organizations up to

3 weeks following the earthquake

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One notable observation on the national scale, from Figure 6 above, is the sustained

spikes in in-degree and out degree centrality among organizations. In examining this further, we

realized that several organizations have relatively high eigenvector centrality. This is

outstanding for the new system because it suggests that there is no single point of failure should

one of these organizations be removed from the network. Such networks are more resilient and

adaptive than ones that are dominated by a single organization. It is difficult to determine if this

observation would persist once the full transformation to the new disaster structure is complete.

However, all the organizations with high eigenvector centrality are public (black color). Thus

though no single organization represent a point of failure, a single type of organization may in

this case. No nonprofit is among the organizations that orchestrate the flow of information

during the response phase. This is a key point of failure as was demonstrated in the case of the

Haitian earthquake in January 2010, when the entire government structure collapsed leaving

nonprofit and international organizations to assume response leadership in a fragmented

collaborative framework (Comfort et al, 2011b). This gap is not directly addressed with the new

law, though it calls for a collaborative framework for action.

To further examine the effectiveness of the implementation of the law in the City of

Padang, we move from the global disaster and national level to the sub-national (i.e. regional,

provincial, district and local) level of operation. This level presents different challenges as

several provinces had not fully adopted and implemented the law at the time of the September

30, 2009 earthquake. In essence, fragmentation was expected in the system at the sub-national

level. In the global perspective in Figures 7 and 8, the provincial structure for handling disaster

events was very evident with the West Sumatra Governor playing a prominent role in

coordination whereas the West Sumatra BPBD was almost nonexistent, which reflected its

underdeveloped state in this context. It also shows the relevance of key political figures in the

response and recovery process.

15

Figure 7. Eigenvector centrality among organizations by funding type (shape)

and jurisdiction (color) using UCINET

16

Figure 8. Betweenness centrality among organizations by funding type (shape) and jurisdiction (color) using UCINET

17

Also, in figure 9, while the national level showed several dense networks and cliques for

coordination with the national BNBP is central, the coordination among sub-national

organizations remained largely isolated. In fact, the West Sumatra BPBD (WSBPBD) did not

emerge as a central actor in the sub-national network (Figure 10). This is a major gap in

coordination at the sub-national and local level. This is consistent with the view that the

preparedness training was largely orchestrated and dominated by the national BNBP and that the

local focus was somewhat overlooked in this process.

Figure 9. National and subnational networks among Indonesian organizations

by jurisdiction (color)

Key: Jurisdiction

National Provincial District Local City

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Figure 10. Sub-national networks among Indonesian organizations by jurisdiction (color)

Conclusion – Networks that Matter

Consistent with the level of preparedness, it was evident that sub-national coordination

was overshadowed by national coordination efforts. While the national structure was clearly

defined and active in this event, the subnational level of coordination remain fragmented because

agencies were operating under different sets of rules. The province acted under the old Satkorlak

system while the City of Padang operated under the new BPBD system. On one hand,

overlapping rules and actors who follow these rules caused inefficient resource allocation due

either to information asymmetry or path dependence. On the other hand, the limited time for

information exchange made decision making ill-informed. The co-existence of both the old and

new systems created an ambiguous environment among active actors on the ground, which

caused confusion during the response as well as the regular system of public management. To

facilitate more effective collective action in the already dynamic and unstable disaster

environment, the design and implementation of a shared knowledge base at the subnational level

may alleviate the inefficiencies caused by the uneven transition.

Key: Jurisdiction

Provincial District Local City

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Several implications can be drawn from this paper. First, it is essential for designers and

disaster managers to identify the weakness of the changing system and the need for players from

both the old and new systems to interact, in order to smooth the organizational adaptation in the

systemic transition. Reflective adaptation of capabilities to the changing demand and

complexities of new situations and transitions are therefore essential to close the gaps that exist

between policy and practice (Comfort, 1999). Second, there is a need for a knowledge commons

among disaster management agencies in the new BNBD /BPBD system in Indonesia. Despite the

valiant efforts by the City of Padang to implement the new disaster management law, the

organizational networks for communication of risks and actions remained somewhat fragmented

at the broader provincial due to unevenness in transition. However, with a knowledge commons,

the learning triggered by this event should increase the accuracy, relevance and timeliness of

information and the effectiveness of organizational networks for future events. Third, while a

better-designed and highly-integrated new system has been established through jurisdiction, it is

not necessarily working well, especially when external players become involved with the system

and the response efforts. To create and maintain effective information flow, it is important not

only to improve ad hoc collaboration among actors from different jurisdiction and sectors, but

also to disseminate key information to irregular players (such as international relief organizations)

to identify best partners from the new system and thus establish an interactive tie between them

and the regular actors.

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Appendix 1: Network Map Key for Node Colors and Shapes (modified for UCINET analysis)

Organizational Source of Funding Organizational Jurisdiction

Source Color Jurisdiction Shape

Public Local Circle in Square

Private Provincial Box

Non-Profit National Circle

International Down Triangle

Appendix 2: Abbreviations for Organizations used in Network Analysis (both ORA &

UCINET Analysis)

Organization Name Acronym

Source of

Funding Jurisdiction

Abrizal Bakri Province ABP public provincial

ADF Health Survey Team ADFHT public international

ADF Engineer Reconnaissance Team ADFRT public international

Aceh-Nias Rehabilitation and Reconstruction

Board (BRR) AHBRR public national

Aceh Legislative Assembly ALA public provincial

ANTARA ANTARA public national

Office of Aceh Vice Governor (Muhammad

Nazar) AOVG public national

Aceh Provincial Government APG public provincial

Association of Aceh Islamic Boarding Schools ASAIBS nonprofit provincial

Association of Indonesian Tours and Travels ASITA nonprofit national

Andalas University AU public national

Australian Defense Force AusADF public international

Royal Australian Air Force AusAF public international

Australian Agency for International Development AusAID public international

Australian Defense Force AusDF public international

Australian Department of Foreign Affairs and

Trade, AusDFAT public international

Australian Embassy in Indonesia (Paul Robilliard) AusEMB public international

Australian Federal Police AusFP public international

Australian Military AusM public international

Australian, Office of Foreign Minister (Stephen

Smith) AusOFM public international

Australia, Office of Prime Minister (Kevin Rudd) AusOPM public international

Australian SAR Team AusSAR public international

AXIS Communications AXIS private national

23


Source of


National Development Planning Board (Bappenas) Bappenas public national

National Search and Rescue Agency BASARNAS public national

Batavia Air BATAIR private national

Puncak Niaga Holdings Bhd BHD private international

Meteorology, Climatology and Geophysics

Agency BMKG public national

Blood Transfusion Unit (Bengkulu) BnUTDC nonprofit local

PT BTD (utility) BTD public local

Blood Transfusion Unit (Bukit Tinggi) BTUTDC nonprofit local

Embassy of Canada in Jakarta CANEMB public international

Canadian Ministry of Foreign Affairs CanMIFA public international

China Red Cross ChRC public international

Bank Bumiputra Commerce Islamic (CIMB) CIMB private national

Canada SAR CSAR public international

Command Post of the Coordination Unit for

Disaster Control CUDC public local

Church World Services CWS nonprofit international

European Commission EC public international

Emergency Capacity Building Consortium of

Indonesia ECB nonprofit national

European Commission for Humanitarian Aid and

Development ECHA public international

Office of the President of the European

Commission (Jose Barroso) ECOP public international

East Kutai Regent EKR public local

The Earth (Kusmayanto Kadiman) Observatory of

Singapore (Kerry Sieh) EOS public international

European Union SAR EUSAR public international

France's Civil Security Detachment FCSD public international

Tithe forum FOZ FOZ nonprofit national

France Rescue Team FSAR public international

Garuda Indonesia GARIndo public national

Government of Australia GoAUS public international

Government of China GoCHN public international

Government of Denmark GoDEN public international

Government of France GoFRA public international

Government of Germany GoGER public international

Government of Indonesia GoINDO public national

Government of Italy GoIta public international

24


Source of


Government of Japan GoJAP public international

Government of Malaysia GoMAL public international

Government of Norway GoNOR public international

Government of Qatar GoQAT public international

Government of Russia GoRUS public international

Government of Saudi Arabia GoSAU public international

Government of Singapore GoSIN public international

Government of South Korea GoSK public international

Government of Switzerland GoSWI public international

Government of Taiwan GoTAI public international

Government of Thailand GoTHA public international

Government of the United Arab Emirates GoUAE public international

Government of the United Kingdom GoUK public international

Government of USA GoUSA public international

Germany SAR GSAR public national

Gama Study Center GSC private local

Hungarian Directorate General for Disaster

Handling HDG public international

HK Logistics HKL private international

Hope HOPE nonprofit international

Halim Perdanakusumah Air Force Airport HPAFPT public national

Cipto Mangunkusmo Hospital HpCM public national

Crown Medical Center Hospital, Malaysia HpCMC public national

M. Jamil Hospital HpMJ public provincial

M. Jamil Hospital(Victim Identification Center) HpMJVIC public national

Hungarian Search and Rescue HSAR public international

Ambacang Hotel HtlAMB private national

Hotel Baskoni Plaza HTLBP private national

Hang Tuah Hotel HTLTH private national

Indonesian Air Carriers Association IANACA nonprofit national

Imam Bonjol University IBUniv public national

International Red Cross IFRC nonprofit international

Bank International Indonesia, Padang Branch IIBANK private national

Indonesian Association of Congresses and

Conventions INCDCA nonprofit national

Indonesian Air Force IndoAF public national

Indosat IndoSAT public national

United National Insarag (Switzerland SAR) INSARAG public international

25


Source of


Adityawarman Museum IoAM nonprofit national

Office of the Indonesian Ambassador to Malaysia

(Da'I Bactiar) IoAmb public national

National Disaster Mitigation Agency IoBNPB public national

Indonesian Cabinet IoCab public national

Office of the Coordinating Minister for Political,

Legal, and Security Affairs (Widodo AS) IoCMPLSA public national

Office of the Coordinating Minister for People's

Welfare (Aburizal Bakri) IoCMPW public national

European Commission for Humanitarian

Operations, Jakarta IoECHO public international

Indonesia Foreign Affairs Ministry IoFAM public national

Indonesian Fire Fighters IoFF public national

Indonesian Tithe Center IoITC nonprofit national

International Organization for Migration IOM nonprofit international

Indonesian Ministry of Communication and

Information IoMCI public national

Indonesia Ministry of Culture and Tourism IoMCT public national

Indonesian Ministry of Finance IoMF public national

Indonesian Ministry of Health IoMH public national

Indonesian Ministry of Home Affairs IoMHA public national

Indonesian Ministry of Health's Crisis Control

Center IoMHCCC public national

Ministry of Higher Education IoMHE public national

Indonesian Ministry of Health's Regional Crisis

Control Center IoMHRCCC public national

Indonesian Ministry of Industry IoMI public national

Indonesian Ministry of Law and Human Rights IoMLHR public national

Ministry of Manpower and transmigration IoMMT public national

Indonesian Ministry of Public Transportation IoMPT public national

Indonesian Ministry of Public Works IoMPW public national

Indonesian Ministry of Religious Affairs IoMRA public national

Indonesian Ministry of Research and Technology IoMRT public national

Indonesia Ministry of Trade IoMTD public national

Indonesian Navy IoN public national

National Archive and Library IoNAL public national

National Defense Forces IoNDF public national

National Mandate Party IoNMP public national

(Indonesian) National Police IoNP public national

26


Source of


National Security Division IoNSD public national

Office of the Coordinating Minister for Economy

(Sri Mulyani Indrawati) IoOCME public national

Office of the Cabinet Secretary (Sudi Silalahi) IoOCS public national

Office of the First Lady (Ani Yudhoyono) IoOFL public national

Office of Military Chief (General Djoko Santosa) IoOMC public national

Office of the President of Indonesia (Susilo

Bambang Yudhoyono) IoOOP public national

Office of Police Chief (General Bambang

Hendarso Danuri) IoOPC public national

Office of the State Secretary (Hatta Rajasa) IoOSS public national

Office of Vice President of Indonesia (Jusuf Kalla) IoOVP public national

Office of Vice President (Boediono) IoOVP_B public national

Indonesian Red Cross IoRC public national

Indonesian SAR Team IoSAR public national

Indonesian Tourism Association Board IoTAB nonprofit national

International SAR team (Rescue Workers) ISAR public international

Islamic Studies Students ISS private international

Italian Red Cross ItaRC nonprofit international

Indonesian Tourism and Travel Fair ITTF public national

Jakarta Health Office JakHO public national

Jakarta Provincial Government JakPG public provincial

Jakarta Convention Center JCC public national

Japanese Foreign Affairs Ministry (Katsuya

Okada) JFAM public international

Jambi Governor JG public local

Japan International Cooperation Agency JICA public international

Blood Transfusion Unit (Jakarta) JkUTDC nonprofit local

Japanese Disaster Relief Team (Japan SAR Team) JSAR public international

Kerinci District Coordination Board for Disaster

Mitigation KDCBDM public district

Kerinci District Public Relations and Protocol KDPRP public district

Kepahiyan Geophysics Station KGS private provincial

Regional government of Klanten district, Central

Java province KlaRG public district

Kuala Lumpur International Airport KLIPT public national

Melaka Islamic University College (KUIM) KUIM public national

Malaysia's Air Asia MAA private international

Malaysian Armed Forces MalAF public international

27


Source of


Malaysian doctors MalDOC public international

Malaysia Building Experts MalExp public international

Office of the Prime Minister of Malaysia (Najib

Razak) MalOPM public international

Maybank MBANK private international

Mercy Corps International MCI nonprofit international

Office of the Chief Minister, Melaka Province

(Mohd Ali Rustam) MelOCM public international

Melaka Provincial Government, Malaysia MelPG public international

Medical Emergency Rescue Committee MERC public national

Office of the Foreign Ministry, Malaysia MFM public international

Maninjau Hydro-electric power plant MHEPP private provincial

Mercy International MI nonprofit international

Mercy Malaysia MM nonprofit international

Media Prima Bhd MPB private international

Maninjau power plant MPP private provincial

Minangkabau Airport MPT public national

Malaysian Search and Rescue Team (Smart) MSAR public international

Muhammadiyah MUHAM nonprofit national

National Alms Collecting Agency NACA nonprofit national

Provinical Government of Nanggroe Aceh

Daraussalam NAD public provincial

National Coordinating Agency for Surveys and

Mapping (Bakosurtanal) NCASM public national

Norway's Ministry of Environment and

International Development (Erik Solheim) NMEID public international

NSTP-Media Prima Disaster Fund NSTP nonprofit national

The New Straits Times Press Berhad NSTPB private international

Nahdlatul Ulama NU nonprofit local

Padang's Culture and Touism Office (head:Edi

Hasmi) PaCTO public local

Padang Government PadGov public local

Office of Mayor, Padang (Fauzi Bahar) PadOOM public local

Office of the Deputy Mayor, Padang City (Marlis

Rahman) PadOPM public local

Padang Seaport PadSPRT public local

Palembang City Government PalCG public local

Rapid-UK PAPID-UK public international

Blood Transfusion Unit (Pekan Baru) PBUTDC nonprofit local

28


Source of


PDAM Water Company PDAM public national

Blood Transfusion Unit (Padang) PdUTDC nonprofit local

Pertamina Fuels PERTA public national

Primary Health Care Team (International

Physicians) PHCT public international

Indonesian Hotels and Restaurants Association PHRI nonprofit national

Makassar Municipal Legislative Council of the

Prosperous Justice Party PKS nonprofit local

PKS Post Disaster Management Center PKS_PDMC nonprofit national

Blood Transfusion Unit (Palembang) PleUTDC nonprofit local

Pauh Limo power plant PLPP private provincial

Blood Transfusion Unit (Palarawan Riau) PlUTDC nonprofit local

Padangpanjang Meteorology, Climatology and

Geophysics Agency PPBMG public provincial

Office of Padang Pariman District Head (Muslim

Kasim) PPODH public local

PIP power plant PPP public national

Padang Pariaman Regional Government PPRG public district

Padangpariaman Public Works Department PPWD public local

Padang State University PSU public national

PT PLN Electricity Company PTPLN public national

Riau Governor RGP public local

Ria Public Works RPWD public local

Russian Ministry of Emergency Situations RusMES public international

Office of the President of Russia (Dmitry

Medvedev) RusOOP public international

Yayasan Salam Malaysia Salam nonprofit international

Saudi Arabia SAR SASAR public national

Sultan Azlan Shah Foundation SASF nonprofit international

Sulit Air Sepakat Organization SASO private national

Coordination Unit for Disaster Mitigation

(Satkorlak) of the Disaster Management Agency SATKOR public national

Saudi Arabian Embassy in Indonesia SauEmb public international

Scout Movement SCOUT nonprofit national

Simpang Empat power plant SEPP private provincial

Singkarak Hydro-electric power plant SHEPP private provincial

Soekarno Hatta International Airport SHPRT public national

Blood Transfusion Unit (Sijunjung) SjUTDC nonprofit local

South Korea SAR SKSAR public international

29


Source of


Syiah Kuala Univeristy SKU public national

Blood Transfusion Unit (Solo) SlUTDC nonprofit local

Singapore Office of Prime Minister (Lee Hsien

Loogn) SOPM public international

Singapore Search and Rescue Team SSAR public international

South Sumatra Healthcare Team SSHT public provincial

South Sumatra SAR SSSAR public provincial

Save the Children (International) STC nonprofit international

Save the Children (Indonesia) STCIo nonprofit national

Water Association of Selangor, Kuala Lumpur and

Putrajaya (SWAn) SWAn private national

The Cultural Park TCP public national

PT Telkom Group Telkom public national

Tabung Gempa Nusantara (Malay Archipelago

Earthquake Fund) TGN nonprofit international

Indonesian Army (TNI) TNI public national

Turkey SAR TSAR public national

Turkey Humanitarian Aid TurHA public international

the Economic and Trade Office of the Taipei

Economic and Trade Office TwETO public international

Taiwan Redcross TwRC nonprofit international

UK Department for International Development UKDFID public international

UK Embassy in Jakarta UKEMB public international

UK Office of the Prime Minister (Gordon Brown) UKOPM public international

Office of UK Secretary of State (Douglass

Alexander) UKOSS public international

UK Red Cross UKRC nonprofit international

UK Search and Rescue Team UKSAR public international

United Nations UN public international

United Nations Disaster Assessment and

Coordination UNDAC public international

UNESCO UNESCO public international

United Nations Children's Fund UNICEF public international

United Nations Office for the Coordination of

Humanitarian Affairs UNOCHA public international

UN Office of the Secretary General (Ban Ki-

moon) UNOSG public international

United Nations Population Fund UNPF public international

United States Agency for International

Development USAID public international

30


Source of


US Consulate General, Medan USCGM public international

US Disaster Assistance Response Team (DART) USDART public international

U.S. Defense Ministry USDOD public international

US State Department's Office of Foreign Disaster

Assistance USDOFA public international

US Emergency Hospital in Indonesia USEH public international

US Embassy in Jakarta (Osius) USEMB public international

United States Geological Survey USGS public international

Harvard University, Boston USHU nonprofit international

United States Military USM public international

Office of the President of the United States

(Barack Obama) USOOP public international

United States SAR USSAR public international

The University of North Sumatra USU public national

UTDD Riau (Blood Transfusion?) UTDD nonprofit local

World Bank WB nonprofit international

World Food Programme (WFP) WFP public international

World Health Organization (WHO) WHO public international

West Java Provincial Government WJPG public provincial

West Sumatra's local Meteorology, Climatology

and Geophysics WSBMKG public provincial

West Sumatra BPBD WSBPBD public provincial

West Sumutra Culture and Tourism Office WSCTO public provincial

Office of West Sumatra Deputy Governor (Marlis

Rahman) WSDG public provincial

Office of West Sumatra Governor (Gamawan Fauzi) WSOOG public provincial

Office of the Vice Governor of West Sumatra WSOVG public provincial

West Sumatra Province WSP public provincial

West Sumatra Provincial Government WSPG public provincial

West Sumatra Public Works Department WSPWD public provincial

West Sumatra Satkorlak WSSAT public provincial

West Sumatra's Tourism Service WSTS public provincial

West Sumatra Wira Brja Military Resort WSWBMR public national

World Vision (International) WV nonprofit international

World Vision (Indonesia) WVIo nonprofit national

XL (Telecommunications) XL private national

Zipur Public Works ZPWD public local

31

Appendix 3: Standard Network Analysis Report (ORA Analysis)

Network Level Measures

Input network(s) for all measures: Organization x Organization

Measure Value

Row count 286.000

Column count 286.000

Link count 284.000

Density 0.003

Isolate count 99.000

Component count 117.000

Reciprocity 0.022

Characteristic path length 3.598

Clustering coefficient 0.036

Network levels (diameter) 8.000

Network fragmentation 0.773

Krackhardt connectedness 0.227

Krackhardt efficiency 0.988

Krackhardt hierarchy 0.906

Krackhardt upperboundedness 0.537

Degree centralization 0.072

Betweenness centralization 0.026

Closeness centralization 0.002

Reciprocal? No (2% of the links are reciprocal)

32

Node Level Measures

Measure Min Max Avg Stddev

Total degree centrality 0.000 0.075 0.004 0.008

Total degree centrality [Unscaled] 0.000 43.000 2.126 4.358

In-degree centrality 0.000 0.080 0.004 0.009

In-degree centrality [Unscaled] 0.000 23.000 1.063 2.687

Out-degree centrality 0.000 0.070 0.004 0.008

Out-degree centrality [Unscaled] 0.000 20.000 1.063 2.339

Eigenvector centrality 0.000 1.000 0.186 0.333

Closeness centrality 0.003 0.004 0.003 0.000

Closeness centrality [Unscaled] 0.000 0.000 0.000 0.000

Betweenness centrality 0.000 0.026 0.000 0.002

Betweenness centrality [Unscaled] 0.000 2098.222 32.937 192.378

Hub centrality 0.000 1.000 0.081 0.237

Authority centrality 0.000 1.000 0.103 0.281

Information centrality 0.000 0.020 0.003 0.005

Information centrality [Unscaled] 0.000 2.712 0.484 0.681

Clique membership count 0.000 15.000 0.280 1.208

Simmelian ties 0.000 0.000 0.000 0.000

Simmelian ties [Unscaled] 0.000 0.000 0.000 0.000

Clustering coefficient 0.000 1.000 0.036 0.119

33

Key Nodes

This chart shows the Organization that is repeatedly top-ranked in the measures listed below.

The value shown is the percentage of measures for which the Organization was ranked in the top

three.

Total degree centrality

The Total Degree Centrality of a node is the normalized sum of its row and column degrees.

Individuals or organizations who are "in the know" are those who are linked to many others and

so, by virtue of their position have access to the ideas, thoughts, beliefs of many others.

Individuals who are "in the know" are identified by degree centrality in the relevant social

network. Those who are ranked high on this metrics have more connections to others in the same

network. The scientific name of this measure is total degree centrality and it is calculated on the

agent by agent matrices.

34

Input network: Organization x Organization (size: 286, density: 0.00347205)

Rank Organization Value Unscaled Context*

1 IoOOP 0.075 43.000 20.653

2 GoINDO 0.047 27.000 12.597

3 WSOOG 0.035 20.000 9.072

4 IoOCS 0.030 17.000 7.561

5 IoOSS 0.030 17.000 7.561

6 IoRC 0.028 16.000 7.058

7 UN 0.028 16.000 7.058

8 IoMPT 0.026 15.000 6.554

9 PadOOM 0.025 14.000 6.051

10 IoMPW 0.025 14.000 6.051

* Number of standard deviations from the mean of a random network of the same size and density

Mean: 0.004 Mean in random network: 0.003

Std.dev: 0.008 Std.dev in random network: 0.003

In-degree centrality

The In Degree Centrality of a node is its normalized in-degree. For any node, e.g. an individual

or a resource, the in-links are the connections that the node of interest receives from other nodes.

For example, imagine an agent by knowledge matrix then the number of in-links a piece of

knowledge has is the number of agents that are connected to. The scientific name of this measure

is in-degree and it is calculated on the agent by agent matrices.

Rank Organization Value Unscaled

1 IoOOP 0.080 23.000

2 GoINDO 0.077 22.000

3 IoOCS 0.056 16.000

4 IoRC 0.049 14.000

5 IoOSS 0.042 12.000

6 IoMPW 0.035 10.000

7 WSP 0.031 9.000

8 IoMI 0.031 9.000

9 IoMPT 0.028 8.000

10 IoBNPB 0.024 7.000

35

Out-degree centrality

For any node, e.g. an individual or a resource, the out-links are the connections that the node of

interest sends to other nodes. For example, imagine an agent by knowledge matrix then the

number of out-links an agent would have is the number of pieces of knowledge it is connected to.

The scientific name of this measure is out-degree and it is calculated on the agent by agent

matrices. Individuals or organizations who are high in most knowledge have more expertise or

are associated with more types of knowledge than are others. If no sub-network connecting

agents-to-knowledge exists, then this measure will not be calculated. The scientific name of this

measure is out degree centrality and it is calculated on agent by knowledge matrices. Individuals

or organizations who are high in "most resources" have more resources or are associated with

more types of resources than are others. If no sub-network connecting agents-to-resources exists,

then this measure will not be calculated. The scientific name of this measure is out degree

centrality and it is calculated on agent by resource matrices.

Input network(s): Organization x Organization


1 IoOOP 0.070 20.000

2 WSOOG 0.052 15.000

3 UN 0.049 14.000

4 PadOOM 0.042 12.000

5 IoOMC 0.031 9.000

6 AusOFM 0.031 9.000

7 IoOPC 0.028 8.000

8 GoAUS 0.024 7.000

9 IoCMPW 0.024 7.000

10 AusADF 0.024 7.000

Betweenness centrality

The Betweenness Centrality of node v in a network is defined as: across all node pairs that have

a shortest path containing v, the percentage that pass through v. Individuals or organizations that

are potentially influential are positioned to broker connections between groups and to bring to

bear the influence of one group on another or serve as a gatekeeper between groups. This agent

occurs on many of the shortest paths between other agents. The scientific name of this measure is

betweenness centrality and it is calculated on agent by agent matrices.

36

Input network: Organization x Organization (size: 286, density: 0.00347205)

Rank Organization Value Unscaled Context*

1 GoINDO 0.026 2098.222 0.086

2 IoOOP 0.026 2075.705 0.083

3 UN 0.011 861.667 -0.042

4 IoBNPB 0.009 696.778 -0.058

5 AusOFM 0.007 526.833 -0.076

6 WSPG 0.006 512.833 -0.077

7 IoCMPW 0.005 371.648 -0.092

8 IoOVP 0.003 222.667 -0.107

9 IoOCS 0.003 203.865 -0.109

10 UNOCHA 0.002 201.583 -0.109

* Number of standard deviations from the mean of a random network of the same size and density

Mean: 0.000 Mean in random network: 0.016

Std.dev: 0.002 Std.dev in random network: 0.120

Information centrality

Calculate the Stephenson and Zelen information centrality measure for each node.


1 WSOOG 0.020 2.712

2 IoOOP 0.020 2.704

3 UN 0.019 2.669

4 PadOOM 0.019 2.589

5 IoOMC 0.017 2.420

6 AusOFM 0.017 2.408

7 IoOPC 0.017 2.344

8 GoAUS 0.016 2.252

9 IoMPT 0.016 2.248

10 AusADF 0.016 2.245

37

Clique membership count

The number of distinct cliques to which each node belongs. Individuals or organizations who are

high in number of cliques are those that belong to a large number of distinct cliques. A clique is

defined as a group of three or more actors that have many connections to each other and

relatively fewer connections to those in other groups. The scientific name of this measure is

clique count and it is calculated on the agent by agent matrices.

Rank Organization Value

1 IoOOP 15.000

2 GoINDO 9.000

3 IoBNPB 6.000

4 WSOOG 4.000

5 AusOFM 4.000

6 PadOOM 3.000

7 IoCMPW 2.000

8 IoOCME 2.000

9 IoOCS 2.000

10 IoOSS 2.000

Clustering coefficient

Measures the degree of clustering in a network by averaging the clustering coefficient of each

node, which is defined as the density of the node's ego network.

Rank Organization Value

1 MBANK 1.000

2 MM 0.500

3 IoMHA 0.479

4 IoOMC 0.479

5 IoOPC 0.479

6 IoMI 0.479

7 IoCMPLSA 0.472

8 IoMCI 0.472

9 IoMLHR 0.472

10 IoMPT 0.417

38

Key Nodes Table

This shows the top scoring nodes side-by-side for selected measures.

Rank Betweenness

centrality

Closeness

centrality

Eigenvector

centrality

In-degree

centrality

Out-degree

centrality

Total degree

centrality

1 GoINDO GoUSA IoOOP IoOOP IoOOP IoOOP

2 IoOOP UKEMB IoMHCCC GoINDO WSOOG GoINDO

3 UN AusAID JakHO IoOCS UN WSOOG

4 IoBNPB AusADF HpCM IoRC PadOOM IoOCS

5 AusOFM UKDFID AOVG IoOSS IoOMC IoOSS

6 WSPG PadGov SATKOR IoMPW AusOFM IoRC

7 IoCMPW USAID IoMCT WSP IoOPC UN

8 IoOVP GoUK Bappenas IoMI GoAUS IoMPT

9 IoOCS MCI IoMF IoMPT IoCMPW PadOOM

10 UNOCHA RusOOP STC IoBNPB AusADF IoMPW

Produced by ORA developed at CASOS - Carnegie Mellon University

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