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CJ598

Week 2 Assignment

After completing the Reading for this unit, develop a 15-20 slide PowerPoint presentation that addresses the application of theoretical foundations to current knowledge and practice in emergency management. Select three of the theories listed below and consider how each informs our efforts in homeland security and/or emergency management.

· Complexity Theory

· Risk Perception Theory

· Systems Theory

· Vulnerability Theory

Apply the three selected theories to existing policies and procedures in emergency management and/or homeland security and analyze recommendations for improvement. Include the following:

· An overview of each of the selected theories and their relevance to the practice of homeland security and/or emergency management.

· An application of each of the selected theories to real-world examples of efforts related to homeland security and/or emergency management (such as phases of the EM cycle, counterterrorism efforts, etc.) and the established policies and procedures utilized in those efforts.

· An analysis and evaluation of the effectiveness of the selected efforts within the context of the theories applied and established policies and procedures.

· Recommendations for the continued application of theoretical foundations to emergency management knowledge, doctrine, and practice.

Be sure to write in a scholarly and objective tone, avoiding the use of first person, personal pronouns, contractions, and colloquial or conversational language. Use citations from scholarly, peer-reviewed sources throughout to support your content and credit sources of information and ideas.

Note: This assignment requires outside research. Use at least four scholarly, peer-reviewed sources in addition to the Reading material throughout your assignment to support your content and credit sources of information and ideas.

Develop your presentation using bullet points of main ideas on the slides themselves, and use the speaker notes to fully develop the analysis and evaluation component. The speaker notes must be presented in complete sentences. All content — whether on the slides or in the speaker notes — must be properly cited per APA. The use of images or graphics is permitted, but they must be properly cited. Avoid using copyrighted material, such as organizational logos, etc. Select a basic slide design for use throughout the presentation. Maintain a scholarly and objective tone, avoiding the use of first person, personal pronouns, contractions, and colloquial or casual language. Use citations from scholarly, peer-reviewed

sources (a minimum of four in addition to the Reading) throughout to support your content and credit sources of information and ideas.

This is the response given to the problem statement from Week 1 from the professor:

You have a good start here. However, you need to be careful about your use of sources and citations. The Phoenix task force was created in 2013. As such, the source you cite as having commented on the challenges faced by the Phoenix task force cannot have written about it in 2012, when it did not yet exist. In addition, that source makes no mention of this task force specifically. It is important that you are not misattributing content to sources in your citations. Note also that the research must focus on addressing the problem – such as overcoming challenges – rather than simply identifying what those challenges are. As you continue to revise this, be sure you are clearly articulating a focused approach to research that can address the problem.

Please double-check all cited sources to make sure the dates line up with the facts of The Phoenix Task Force. Thank you.

Directions

· Your 15-20 slide requirement is excluding your title, introduction, and reference slides.

· Use one basic slide design and layout.

· Text large enough to be read by your audience (font size 20-34 point).

· Limit slides to between 6 and 8 lines of content.

· You may use pictures, charts and graphs to supplement your material as long as they do not take up the entire slide

· Use bullets for your main points.

· Use speaker notes to fully explain what is being discussed in the bullet points as though you are presenting to an audience, being sure to follow the Standard English (correct grammar, punctuation, etc.).

· Viewpoint and purpose should be clearly established and sustained.

· Presentation should be well ordered, logical and unified, as well as original and insightful.

· Your work should display superior content, organization, style, and mechanics

· Appropriate citation style should be followed

You should also make sure to:

· Use examples to support your discussion

· Cite all sources on a separate reference slide at the end of your PowerPoint and reference and cite within the body of the presentation using APA format and citation style. For more information on APA guidelines, visit Academic Tools.

Directions for Submitting Your Assignment

Compose your assignment and save it in the following format: Course#_LastnameFirstname Unit # Assignment (example: HM598_SmithJohn Unit 1 Assignment). Submit your assignment to the appropriate Dropbox by the end of the unit.

Example of Good Per Reviews you can use:

CJ598

Unit2 DQ & Student Response

Theories of Organizational Behavior and Management

Select two of the four theories discussed in this unit and provide a description and overview of each, supported by scholarly, peer-reviewed sources (NO LAW REVIEW). Discuss the application of each to at least two specific aspects of homeland security and/or emergency management. Describe how both practitioners and academic researchers might use each theory to inform their efforts associated with the two specific aspects you identify. Include supporting citations from scholarly, peer-reviewed sources and provide the complete APA reference for each.

In your response posts, identify additional applications for the theories focused on by your peers.

NOTE: In this week’s discussion, we are focused on the identification and application of theory to emergency management/homeland security efforts. Be sure that you are selecting from the theories discussed in this unit (you should be able to cite the original author/source of the theory) and including supporting citations for the description of each. In discussing the application of these theories, focusing on your own research proposal topic will help you to develop your assignment content for this week. Be sure you are clearly distinguishing between concepts and the established theories. For example, the concept of risk perception itself is not the theory of risk perception.

Respond Kindly to Student #1

(

Hector

Chamo)

Class,

The guided complexity is a theory that can be useful in assessing disaster response management. The three

foundations are system resolution, system scope and system dimension. Coordination with communication will help the

process in planning and the command and control is a self organization with multi organizational collaboration (Bergström,

J., Uhr, C., & Frykmer, T. 2016).

A community’s vulnerability and technology are related to the condition of hazards in their community. All disasters create disruptions and create barriers to resources needed for survival (Norris, Stevens, Pfefferbaum, Wyche, & Pfefferbau,2008). In addition to physical disruption from disaster, mental and health symptoms a factor for people who went through a disaster. Secondary stressors are related to interpersonal relationships, like family conflicts, family strains, and work related problems. When stressors exist prior to a disaster chronic problem increases. It is important to have social resources for every person and groups to become disaster resilient (Zakour, 2010). There is an overview of belief that disasters are triggered by climate change, people moving to unsafe geographic areas. In addition, there is an increase of complex mixtures like technological disasters, example being the 2011 earthquake tsunami nuclear power disaster in Japan. Research is done to seek an understanding on why and how communities become disrupted from disaster events, to take not on creating ways to mitigate pr reduce disruption and vulnerability .

Reference

Bergström, J., Uhr, C., & Frykmer, T. (2016). A Complexity Framework for Studying Disaster

Response Management. Journal of Contingencies & Crisis Management, 24(3), 124–135.

https://doi-org.libauth.purdueglobal.edu/10.1111/1468-5973.12113

Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., & Pfefferbaum, R. L. (2008).

Community resilience as a metaphor, theory, set of capacities, and strategy for disaster

readi- ness. American Journal of Community Psychology, 41(1/2), 127–150.

Zakour, Michael & Gillespie, David. (2012). Community Disaster Vulnerability: Theory,

Research, and Practice. 10.1007/978-1-4614-5737-4.

Hector

Respond Kindly to Student #2

(Luke Leon)

Risk Perception Theory

Risk Perception is how a person views risks and what can happen in decision making. Everyone has their gauge of risk and to the extent of how serious they let that influence their decision (Rohrmann, 2008, p. 2). An example of risk perception in emergency management is when coming up with a mitigation and response plan, decision-makers have to prioritize what risks need more attention over other risks (Rohrmann, 2008, p. 2). Another example of risk perception in homeland security and emergency management is looking beyond individualized risk and assessing group risks that feel like they are at risk of a certain danger (Rohrmann, 2008, p. 5). A specific example in real life is the Black Lives Matter movement as that group feels that black lives are at risk and since the group perceives that risk of their livelihoods being threatened, they have their movement.

Systems Theory

Systems are a combined group of elements that work together to achieve an objective (Simonovic, 2015, p. 3). An emergency management concept that works with this theory is integrated disaster management where the human aspect of life combines with the built or structured environment to create a response (Simonovic, 2015, p. 4). This is a good example because from the human element we are our human systems with emotions, reactions, and feelings whereas we have to interact with other systems like technology, nature, and even animals that may not be aware of the human element that is needed in processes. Another example of systems theory in practice with emergency management is in training and simulations, there is disaster response training, so responders know what to do and the response feels natural, so it is quick and efficient rather than delaying the response and increasing the chance of more damage in the disaster (Simonovic, 2015, p. 4). While the most common thought when first hearing the word systems are computers or programs, systems still apply to the human element as humans have their code and programs to get tasks done and respond to situations.

Practitioners and researchers may use these theories to analyze the response and see how they can be improved (Simonovic, 2015, p. 9). They could also be used to analyze what went wrong or what went right, from a research standpoint they can be used as a study as to why people make the decisions they do with what is given to them in a certain situation or they can be used to question decisions, going back to risk perception theory maybe a mitigation plan focused more on tornadoes rather than floods and this can be used to gauge why decision-makers feared tornadoes over flooding.

References

Rohrmann, B. (2008). Risk perception, risk attitude, risk communication, risk management: A conceptual appraisal, 1–10. Retrieved from https://cdn-nrspp.s3.ap-southeast-2.amazonaws.com/wp-content/uploads/sites/4/2020/08/31175520/TIEMS_2008_Bernd_Rohrmann_Keynote .

Simonovic, S. P. (2015). Systems approach to management of disasters – a missed opportunity. Journal of Integrated Disaster Risk Management, 5(2), 70–83. https://doi.org/10.5595/idrim.2015.0099

Civil Engineering and Environmental Systems, 2015
Vol. 32, Nos. 1–2, 5–17, http://dx.doi.org/10.1080/10286608.2015.1025065

Improving resilience through vulnerability assessmen

and management

Jitendra Agarwal∗

Department of Civil Engineering, University of Bristol, Bristol BS8 1TR, UK

(Received 18 October 2014; accepted 27 February 2015)

The increasing complexity of infrastructure systems and the possibility of severe consequences due to
interdependency and uncertain demands have led to an increased emphasis on resilience. Resilience, in
simple terms, is the ability of a system to withstand adverse conditions and to recover quickly from
these. Its interpretations and linkages to the related concepts of vulnerability and risk are examined. It
is argued that vulnerability is an inherent characteristic of any system, hard or soft, and its identification
and management is essential for improving the system’s resilience. A systems approach to identify the
vulnerable failure scenarios uses the concepts of form, connectivity and hierarchical modelling. Modelling
of interactions with social systems and assessing their consequences requires dealing with uncertainty and
it remains a challenge.

Keywords: resilience; vulnerability; risk; infrastructure systems; networked systems

1. Introduction

Infrastructure systems such as those for water supply, transport, communication and energy are
socio-technical systems of enormous complexity. Traditionally, these have been designed and
operated as technical systems to achieve a target level of reliability. However, with increasing
social and economic consequences after unpredictable failures, this cannot remain so. For exam-
ple, the economic damage from the failure of North American power grid in 2003 was estimated
to be $6.4 billion (Anderson and Geckil 2003). Similarly, the collapse of I-35W bridge over the
Mississippi River in Minneapolis resulted in estimated economic losses of $71,000–$220,000
per day depending upon adjustment of destinations by the road-users (Xie and Levinson 2011).
There is also increasing evidence of a knock-on effect of the failure of one infrastructure com-
ponent onto another. For example, the 2007 Gloucester floods in the UK (Cabinet Office 2008)
not only disrupted the water supply for nearly 350,000 people but also threatened the opera-
tion of a power plant. The increasing complexity of infrastructure systems has contributed to
the possibility of unintended behaviour. With climate change high on the agenda in scientific
and policy domains, there is increasing realisation that infrastructure systems cannot be designed
for all hidden and uncertain threats. Instead there is a move towards increasing the resilience of
infrastructure systems and societies so that they are better able to cope with unknown demands,
uncertainties of the modelling and the emerging consequences.

*Email: j.agarwal@bristol.ac.uk

mailto:j.agarwal@bristol.ac.uk

6 J. Agarwal

There is a growing body of literature on the resilience of systems in areas such as socio-
ecological systems, complexity theory, disaster research and risk management (see e.g. Francis
and Bekera 2014; Ouyang 2014). Different approaches for resilience are being put forward. The
purpose of this paper is to argue that the identification of vulnerabilities is essential for improving
the resilience of infrastructure systems and systems approaches have an important role to play.
First, the interpretations and linkages between the related terms, resilience, vulnerability and
risk are examined and then a systems approach for vulnerability modelling is introduced and the
relevant systems issues discussed.

Resilience

The term ‘resilience’ is used in different disciplines. In physics, it is the ability of an object to
return to its original shape after being deformed. In medicine, it refers to an individual’s ability
to recover from illness or depression. In the context of ecological systems, resilience implies the
persistence of systems to external influences and their ability to absorb disturbance and adapt
their dynamics (Holling 1973). The latter implies that they may find a new stable state rather
than trying to return to their original state. UNISDR (2009) defines resilience as

the ability of a system, community, or society exposed to hazards to resist, absorb, accommodate to and recover
from the effects of a hazard in a timely manner, including through the preservation and restoration of its essential
basic structures and functions. (24)

This has two important aspects, that is, minimum functionality and time to recover.
In the context of infrastructure systems, Bruneau et al. (2003) (and many others) have related

resilience to the ability of a system (i) to reduce the chances of a shock, (ii) to absorb the shock
and (iii) to recover quickly after a shock. They proposed robustness, rapidity, redundancy and
resourcefulness as the four aspects to measure it. Robustness implies the ability to withstand an
adverse event without disproportionate consequences. Rapidity refers to the speed at which the
recovery occurs. Redundancy points to the presence of duplicate means. Resourcefulness is used
as a measure of the ability of a system to adapt to unexpected events. Redundancy contributes
to robustness, and rapidity depends upon the resources available, thus it could be argued that
robustness and rapidity of recovery are two key aspects of resilience.

According to the UK government (Cabinet Office 2011), a resilient system or organisation
will be able to achieve its core objectives in the face of adversity through a combination of
measures. These have been placed into four categories: resistance (direct physical protection),
reliability (capability to operate under a range of conditions), redundancy (concerned with design
and capacity), and response and recovery (ability to respond and recover). The first three com-
ponents, that is, resistance, reliability and redundancy are closely linked and routinely practised
in the design of engineering systems; however, these are associated with large uncertainties for
human systems.

In both the above approaches, the primary focus is on the restoration of the original state of
the system. Ecological resilience is concerned with finding another stable state. Organisations
tend to be flexible and easy to move into a different state. Technical infrastructure projects take
several years to come to fruition and they are not easy to upgrade or steer into an alternative
state. Haimes (2006) related resilience not only to the ability to recover to a desired state and
to the time taken, but also to the cost to achieve this. He argues that resilience can be improved
through making the system robust and managing the operational factors, for example, prevention,
containment, scenario planning, etc.

A report by the Institute of Public Policy Research (IPPR 2009) refers to three levels of
resilience: (i) the ability of a system to absorb shocks primarily through built-in redundancy,

Civil Engineering and Environmental Systems 7

F
u

n
ct

io
n

Time

100%

Stress

Absorb

Repair
Adapt

Failure

t1 t2

Figure 1. Different approaches to achieve resilience.

(ii) community resilience through preparation and response measures and (iii) anticipating
adverse situations and adapting to circumstances (rather than trying to recover to the original
state). The report also highlights the risks posed by reduced redundancy, just-in-time culture and
interdependent systems. Improved efficiency has magnified vulnerabilities and increased interde-
pendence has created the potential for cascades of failures. Addressing these challenges requires
holistic thinking. In the context of socio-ecological systems, Adger (2006) notes three aspects of
resilience: (i) the magnitude of disturbance before a radical change occurs in system state, (ii) the
capacity to self-organise and (iii) the capacity for adaptation to emerging circumstances. These
can be extended to socio-technical systems, however, the ability to self-organise or adapt must
come from society unless technical systems can be coded with more intelligence.

At a practical level, the ability to absorb a shock or to recover from an adverse state to the orig-
inal state or to a new better state is important. However, understanding uncertainty and coping
with change is at the heart of resilience thinking (Rees 2010). It requires creating an appropri-
ate model of the system and analysing its behaviour for a range of scenarios. Given the diverse
nature of uncertainties and possible changes, a flexible approach is needed. For example, pro-
viding redundancy or increasing the resistance may not always be feasible and to achieve the
desired outcomes the repair and recovery processes must be planned in advance for the poten-
tial vulnerable scenarios. The earlier a system can sense the undesirable events approaching, the
sooner it can begin to respond or to adapt. Figure 1 illustrates a conceptual model of methods
to achieve resilience. Most systems have some absorptive capacity to bear additional stresses.
Adaptation often tends to be a longer term process but failure can be avoided through timely
repair and recovery.

3. Vulnerability

Resilience requires robustness. Robustness is the ability ‘to take a knock’ without disproportion-
ate loss of functionality. In practice, it means that the system will be able to cope with small
variations in demand or minor damage. Advanced optimisation techniques often lead to systems
that are good for the demands considered during the design, but may result in failures should
these demands change. Reliability theory gives the probability of the successful operation of a
system under defined conditions over a stated period of time. However, system outcomes for vari-
ations beyond design basis remain uncertain. Further, modelling issues, nonlinearities and limits
to our knowledge make it difficult to certify a system to be robust. One way to gain insights into
robustness is to examine how a system is vulnerable.

8 J. Agarwal

Vulnerability is commonly referred to in the resilience literature but its usage has tended to be
quite different. Vulnerability captures the idea of susceptibility to damage. Such susceptibility
derives from a characteristic form of the system within a given context. For example, an earth-
quake in California may result in very different consequences from an earthquake of the same
strength in Iran, because of the differences in the technical design and construction of the infras-
tructure. Agarwal, Blockley, and Woodman (2001) defined vulnerability as the susceptibility of
a system to disproportionate consequences in relation to damage or perturbation. Haimes (2006)
related vulnerability to the inherent states of a system that can be exploited to adversely affect
the system. The behaviour of a system is characterised by its state variables. The state variables
are dynamic and so are the vulnerabilities. Infrastructure systems are arranged in a hierarchy and
exhibit vulnerabilities at different levels.

Social scientists tend to view vulnerability in terms of the socio-economic factors that deter-
mine people’s ability to cope with stress or change. Cutter, Boruff, and Shirley (2003) used a
hazards-of-the-places model to identify vulnerability indicators in the US counties. These include
personal wealth, proportion of children and elderly, density of built environment, single sector
economic dependence, housing stock, race and ethnicity, occupation, infrastructure dependence,
etc. Different factors were found to contribute differently to the vulnerability of a place. Morrone
et al. (2011) assessed societal vulnerability based on access to different types of capital: economic
– indicating poverty levels, human – corresponding to education, social – relating to support
networks, and collective assets – such as essential services.

Miller and Nigg (1993) distinguished between ‘event vulnerability’ and ‘consequence vul-
nerability’. McEntire, Crocker, and Peters (2010) related the former to the ‘proneness issues’
and the latter to the ‘capabilities’. The former refers to susceptibility of a system to a par-
ticular event or action and the latter where consequences tend to be higher due to inadequate
strength. Higher consequences derive from inherent weaknesses in the form of a system or due
to severe action. Where this is due to inadequacies in form, this can be referred to as ‘inter-
nal vulnerability’ and that due to severe action (or lack of capacity) can be called ‘external
vulnerability’. In social systems, it is difficult to make a distinction between proneness and capa-
bility and this remains a challenge. Indeed, some authors (e.g. Alwang, Siegal, and Jorgensen
2001) argue that proneness and capability are interwoven and both contribute to the vulner-
ability of the system. The JCSS framework on risk (JCSS 2008) refers to susceptibility of a
component to an action as being vulnerable, and the ensuing disproportionate consequences due
to component failure as a lack of robustness. For example, a steel structure in a harsh marine
environment is vulnerable to corrosion (i.e. external vulnerability) and if a small reduction in
cross-sectional area due to corrosion causes the structure to fail, then it is not robust (i.e. internal
vulnerability).

Thus, a broad distinction exists between those who see vulnerability as the potential damage to
a system and those who see vulnerability as a state that exists within a system before it encounters
a hazardous event. The latter view is that vulnerability exists independently of external hazards.
Social vulnerabilities of this type might include poverty, inequality and housing quality. Material
defects or a lack of corrosion resistance in physical systems also fall in the latter category. It
could be argued that this type of vulnerability is a particular form of hazard – a hazard that is
internal to the system.

The need to reduce vulnerability has been emphasised in disaster research (e.g. Blakie et al.
2003) and it has influenced the current research on climate change. The Intergovernmental
Panel on Climate Change (IPCC 2007) regards vulnerability as a function of ‘climate varia-
tion to which a system is exposed, its sensitivity and its adaptive capacity’. Interestingly, this
encompasses most of the elements of resilience defined by UNISDR (2009). Adger (2006) also
considered vulnerability as having three components that include exposure, sensitivity to pertur-
bations and the capacity to adapt. Exposure here essentially refers to the stresses or perturbations.

Civil Engineering and Environmental Systems 9

It is the sensitivity, that is, the degree to which a system is affected by perturbations, that
relates to vulnerability. Adaptive capacity, that is, the ability of a system to evolve to accom-
modate perturbations, is taken to contribute to resilience rather than vulnerability. Turner et al.
(2003) considered vulnerability in terms of exposure, sensitivity and resilience. They analysed
these at a particular spatial scale and sought to establish links to other scales. Berkes (2007)
argued that a resilience approach helps to understand uncertainty and to reduce vulnerability. A
multi-disciplinary analysis of infrastructure systems requires a shared understanding of different
points-of-views. These differences seem to arise from when the impact is measured. All systems
are dynamic and it is important to consider the time, for example, time t1 or t2 in Figure 1, at
which performance is measured. Vulnerability assessment using consequences at time t2 would
include resilience.

Whatever domain one considers, quantification of vulnerability is not easy. A probabilistic
measure of vulnerability, defined as the ratio of the failure probability of the damaged system to
the failure probability of the undamaged system (Lind 1995), can be applied to almost any sys-
tem. Luers et al. (2003) argued for assessing the vulnerability of important state variables using
generic metrics such as sensitivity to stress, state relative to defined threshold and exposure
to stress. Alwang, Siegal, and Jorgensen (2001) decomposed vulnerability into three compo-
nents: the risk, the risk responses (i.e. managing risk), and the outcome in terms of welfare
loss. They note that ‘the tautological nature of these definitions – risk determines vulnera-
bility, but vulnerability also determines risk – invites confusion’. This seems to derive from
hazards being viewed as risks and as discussed earlier, hazards could be external or within the
system.

In engineering, as compared to human ecology research, there is not enough emphasis on
political and structural causes of vulnerability. Disasters resulting from Hurricane Katrina and
the Fukushima tsunami have exposed such vulnerabilities of modern infrastructure systems.
However, the consequences of such events in a given context can be reduced through planning
using vulnerable failure scenarios. There is a need to identify such scenarios addressing physical,
environmental, social and economic dimensions.

McEntire, Crocker, and Peters (2010) discussed four schools of thought for vulnerability
reduction – physical, engineering, structural and organisational. The focus of the physical
school is on reducing the exposure to hazards, whereas the engineering school aims to increase
the resistance through better design and construction practices. The structural school stresses
the importance of socio-economic factors and demographic characteristics. The organisational
school deals with the effectiveness of response and recovery including the ability to adapt. Both
engineering and structural schools refer to inherent characteristics of their respective systems
(i.e. engineering and social) which can increase or decrease vulnerability. The other two schools
mainly contribute to risk reduction rather than vulnerability reduction. However, certain sys-
tem characteristics that govern vulnerability can contribute to increased exposure to hazards and
hence increased risk. For example, low socio-economic conditions may lead to settlements in
hazardous zones.

Two essential lines of defence against adverse demands are robust internal form and robust
management. A system that is vulnerable in any way cannot be robust. An inappropriate form
if damaged may lead to consequences that are disproportionate to the initial damage. It gains
importance for low chance–high consequence events. Both vulnerability and resilience are not
concerned with the likelihood of external actions. Vulnerability is an inherent property of the
system and resilience is a performance attribute. Elms (1999) noted that many engineers tend to
focus on capacity (strength) rather than vulnerability. Capacity relates to survival and vulnera-
bility to failure. The two views can lead to different results, but the ones based on failure could
be more useful because an identification of weaknesses can provide protection against several
hazards, thus beneficial for improving resilience also.

10 J. Agarwal

4. Risk

Risk and resilience share certain characteristics and it is useful to examine how risk management
can be used to enhance resilience. In engineering, risk is understood as the combination of the
chance of an event occurring and the consequences of an event in a context. In disaster reduction
literature, it is taken as the combination of hazard, exposure and vulnerability. The combination
of exposure and vulnerability determines the consequences, and hazard defined in probabilis-
tic terms gives the chance. So the two definitions are not very different, however each has its
usefulness in connecting risk to resilience.

Risk refers to a potentially dangerous situation that might or might not exist in the future with
consequences we want to avoid. Depending upon the context, consequences may be measured
in terms of fatalities, injuries, cost of repairs, losses due to unavailability of infrastructure and
so on. Risk changes with time and is affected by what we do. It is recognised that risk cannot
be eliminated altogether, but measures must be taken to reduce it. These could include reducing
exposure to hazards or hardening the system to reduce the consequences. The measures taken
to cope with the consequences or recover from these are generally not part of risk management
but they are needed to improve resilience. In the Eliminate, Reduce, Inform, Control (ERIC)
approach to risk management, eliminating or reducing risks, while helpful, does not always imply
that the system has become less vulnerable. This is because risk can be reduced by limiting the
exposure also. The Inform and Control aspects of the ERIC approach are useful for resilience.
By knowing what the remaining risks are, contingency plans can be prepared and where possible
measures can be put in place to control the consequences. These plans or measures need not be
limited to credible risks but can also be developed for the inherent vulnerabilities in the system.

Sarewitz, Pielke, and Keykhah (2003) noted that public policies to mitigate the impact of
extreme events depend upon whether the focus is on reducing risk or on reducing vulnerability.
Reducing vulnerability does not require data about extreme events but risk reduction does. Here
vulnerability relates to inherent characteristics of a system that are independent of any particular
hazard or event, and the risk of an event is distinguished from the risk of an outcome. The risk of
an outcome is based on the risk of an event and the vulnerability of the system. Sarewitz, Pielke,
and Keykhah (2003) also refer to the tension between individual action and collective conse-
quences. Such tensions could be identified through systems thinking. For example, the growth of
megacities due to increased opportunities for economic gains has increased the vulnerability of a
city due to a wide variety of hazards. Extreme events are created by context that is, not simply by
a set of characteristics inherent in physical phenomenon but by interactions with other systems.
For example, the eruption of the Eyjafjallajökull volcano in 2010 became an extreme event due
to atmospheric currents (environmental system), heavy use of the air space (social and economic
system) and the design of aircraft engines (technical system). In this case, road and rail transport
contributed to resilience to some degree, but the robust design of aircraft engines would have
reduced the risk of failure and improved resilience.

5. Preparedness and adaptability

All systems are dynamic and they change in time and space, albeit at different scales. Expect-
ing the unexpected requires preparedness in advance. This not only includes specific measures
but elicitation and integration of local knowledge because global behaviour emerges from local
interactions. Such knowledge may be in form of simple rules or may have been gained from past
events. Models of many nonlinear engineering systems are known to result in multiple states and
the system could reside in one of these states or jump from one to the other depending upon
external input. Such behaviour, typical of low degree of freedom systems, is characterised by the

Civil Engineering and Environmental Systems 11

sensitivity of the system to parameters and initial conditions. In the design of such systems, the
aim usually is to keep them away from sensitive regions to reduce the uncertainty of behaviour
rather than let them move to an alternative state.

For infrastructure systems, it is the adaptability of people who use or interact with the infras-
tructure that can contribute to resilience. For example, having different modes of transport is only
good if people can adapt quickly in case of the failure of any one mode. Adaptability of ecologi-
cal systems contributes significantly to their resilience. Such behaviour results from a collective
response that emerges after a shock. However, this is not the case for technological systems.
Often man-made systems are tailored to their environment and they require human interven-
tion to change their behaviour unless pre-programmed. The latter requires scenario planning and
artificial intelligence to provide some degree of adaptability.

6. Infrastructure criticality

Many physical infrastructure systems are spatially distributed. They are continuously evolving
while interacting with other systems. These infrastructure systems are expected to have a mini-
mum level of resilience. But how does one arrive at these levels? Should these be based on risk
calculations or the continuity of services or something else? The UK government has divided
national infrastructure into nine sectors: communications, emergency services, energy, finance,
food, government, health, transport and water (Cabinet Office 2010). Within each, critical ele-
ments are identified according to the impact of their loss. This has three dimensions: (a) the
impact on delivery of the nation’s essential services, (b) the economic impact and (c) the impact
on life. Severe impact in any dimension could lead to criticality. The severity of impact is dis-
tinguished using three factors: (i) the degree of disruption of service, (ii) the extent of disruption
in terms of population or geographical region and (iii) the duration of disruption. Approximate
ranges are given for the geographical regions and population affected (Table 1) but there are
hardly any indicators of the degree of disruption or the duration of disruption, both of which are
essential to the recovery plans. Also, there is a lack of clarity on the indicators of life quality

Table 1. Description of criticality scales (adapted from Cabinet Office 2010).

Description

Criticality
scale

Degree of
disruption

Extent of
disruption –
geographical

Extent of
disruption –
population

Impact on the
delivery of
essential
services

Infrastructure
importance

CAT 5 Across a number
of sectors

Catastrophic
impact, national
long-term effects

Of unique national
importance

CAT 4 Impact on
essential
services across
the nation

Millions of citizens
affected

Severe Highest impor-
tance to the
sector

CAT 3 Affects a large
geographic
region

Many hundreds of
thousands of people
affected

Substantial
importance to
the sector

CAT 2 Affects whole
counties

Tens of thousands of
people affected

Significant impact

CAT 1 Mostly localised Thousands of people
affected

Moderate

CAT 0 Minor (on national
scale)

12 J. Agarwal

F
u
n
ct
io
n
Time
100%

Shock

Too much loss (R > R*)
& slow recovery (t > t*)

R*,t* acceptable
standardR

Figure 2. A resilience assessment framework (adapted from Chang and Shinozuka 2004).

and economic impact. In structural safety, a life quality index based on life expectancy and gross
domestic product per person has been proposed (e.g. Pandey and Nathwani 2004).

Chang and Shinozuka (2004) proposed a resilience assessment framework based on a com-
parison of loss of system performance to predefined standards as shown in Figure 2. Here, R*
corresponds to robustness standard (but does not measure robustness in itself) such as less than
5% of the population loses water service and t* corresponds to rapidity standard such as 99% of
population has service restored within one week.

Whatever the approach, the minimum levels are largely governed by the societal expectations
and the resources available. It is important that consistent standards are set across all sectors
and any deviations are communicated across the sectors because of the interconnected nature
of infrastructure systems. This leads to the important issue of models of infrastructure systems,
discussed in the next section, so that their performance could be simulated for likely future
events and compared against the minimum agreed standards. This requires all stakeholders to
come together for the benefit of the society and systems professionals have an important role to
play.

7. A systems model for vulnerability and resilience

Infrastructure systems are complex and they consist of not just the physical elements such as
roads and bridges but also include the organisations that run these, the public who use these and
the environment they are part of. They can be considered as a set of interacting objects that are
arranged together in an appropriate form to fulfil a purpose. They can be modelled as holons
that is, they are both wholes and a part of the whole. The nature of objects may differ from one
system to the other. Figure 3 presents a model of the system at different levels of definitions and
an example at a detailed level is shown in Figure 4. Any weakness in one part of the system can
propagate to other parts of the system or different processes may join together to provide the
necessary resistance to stop that happening.

In literature, infrastructure networks such as water supply and electricity grids have been
mainly analysed from two points of view: topological analysis and response analysis (also
referred to as flow models). Topological analysis focuses on connectedness and accessibility.
Properties of links are sometimes taken into account by assigning weights to the links or the
nodes but the analysis is independent of the demands. Response analysis requires a model of
demands that changes with time.

Civil Engineering and Environmental Systems 13

Figure 3. Modelling infrastructure systems at different levels of definition.

Holyhead

Wrexham

Bangor

Aberystwyth

Fishguard

Cardiff
Swansea

Milford
Haven Newport

Pembroke

Bristol

Liverpool

Highway
Rail
Airport
Fer

City/Town

Figure 4. A simplified model of the transport network of Wales (adapted from http://www.traffic-wales.com/media/
33513/welsh-government-strategic-road-network and http://www.nationalrail.co.uk/static/documents/content/Net
work_Rail_national_map(1) ).

Scenario planning for improving resilience requires that vulnerable failure scenarios be iden-
tified. As discussed before, vulnerability is susceptibility to some kind of damage due to certain
characteristics of the form. The system model (Figure 3) is used to systematically look for such
vulnerabilities. First, technical infrastructure systems such as water supply or road networks are

http://www.traffic-wales.com/media/33513/welsh-government-strategic-road-network

http://www.nationalrail.co.uk/static/documents/content/Network_Rail_national_map(1)

14 J. Agarwal

Vulnerability of scenarios

E
vi

d
e

n
ce

f
o

r
ra

p
id

ity
o

f
re

co
ve

Very low

Low

Medium

High

Resilience

Figure 5. Mapping of scenarios for relative resilience.

modelled independently and analysed for damage using the vulnerability theory reported else-
where (Agarwal, Blockley, and Woodman 2003 for structures; Pinto et al. 2010 for water supply).
The key concepts are that of modelling a system as a graph with nodes and links (Figure 4). The
links are the channels of communication between the nodes and associated with each link is a
parameter called well formedness that describes the quality of the form of the link. This param-
eter is used to form clusters (or communities) of neighbouring nodes and links so that they are
able to provide the best functionality to the system. These clusters are grown by including neigh-
bouring nodes and links (or clusters) using a set of criteria until there is one single cluster, the
whole system. This leads to a hierarchical representation of the system that is systematically
searched by introducing damage to identify vulnerable failure scenarios. Each failure scenario
has a vulnerability index based on a measure of damage demand and a measure of consequences
to the form of the system. These can be used to improve the form of the system or to prepare
recovery plans.

Next the impact of failure scenarios of one infrastructure system on the interacting systems
(such as the other utility networks, social/community networks, economy and environment) is
considered (Agarwal, Liu, and Galvan 2014). The interdependency between them can lead to
cascades of failure. For example, the road and rail networks (Figure 4) have their own vulnera-
bilities but are impacted by each other. These vulnerabilities also impact the towns they serve.
While impact on physical infrastructure can be quantified it is not so easy for social or environ-
mental systems. Causal loops (Milke 2013) could help identify positive and negative interactions.
The use of various schemes that recognise incompleteness and enable evidence to be combined,
for example, ‘Italian flags’ (Blockley and Godfrey 2000) can be useful.

An assessment of the rapidity of recovery after damage to a physical or social system also
poses challenges. However, evidence can be gathered from an analysis of the past failures and an
examination of the current system processes to make recovery predictions in the future. A map
of the vulnerability of identified failure scenarios and the corresponding predictions of recovery
(Figure 5) is useful to compare the likely resilience of infrastructure systems. However, such an
assessment of resilience must be treated with caution because of the large uncertainties and the
nonlinear dynamics of the systems.

8. Discussion and conclusion

Systems philosophy requires that social and environmental impact of potential failure scenarios
of technical systems be examined so that appropriate measures can be taken to increase the

Civil Engineering and Environmental Systems 15

resilience of the systems. Infrastructure systems with social dimensions are complex systems
where component interactions are difficult to define or poorly understood and behaviour models
are not fully known. In such a setting, identifying their vulnerabilities and the ability to recover
has to be at the core of resilience building.

There are lessons to be learnt from the complex dynamics of ecological systems where
resilience may derive from structural changes, even though these occur at a much longer time
scale as compared to those for infrastructure systems with a social dimension. Hence resilience-
building measures for the latter are aimed at maintaining the function and the structure, at least
in the short term. Identifying the structural weaknesses, such as through an analysis of form, and
taking remedial actions can provide a powerful method to increase the resilience.

There exists a tension between the improvement in the level of resilience and competing
demands on resources. If the potential consequences are serious enough not to be ignored, action
has to be taken irrespective of resource constraints. Hence, it is necessary to define the accept-
able levels of vulnerability and recovery for all interacting systems. These would invariably
vary depending upon the economic state of the society and its value system but should be at
least aimed at avoiding cascading effects and must be agreed through a dialogue between all the
stakeholders. Development of robust models for spatial and temporal analysis of infrastructure
systems that would allow a range of social behaviours and recovery options to be explored is
very much needed.

Systems thinking for resilience also requires considering all kinds of threats whether techno-
logical, climate, terrorism, cyber or pandemics. Information technology (IT) is now embedded in
all systems. It is difficult to imagine the consequences of sudden loss of IT infrastructure. Even
localised malfunctions are known to cause significant disruptions. Similarly, spread of disease
has become a much greater threat in recent years.

All catastrophic modelling tools determine losses in monetary terms. The impact of the dis-
ruptions to the supply of goods or services is often also measured in economic terms. However,
the social costs (e.g. the lives lost, psychological effects, lost livelihoods, disintegrated com-
munities, etc.) cannot be measured – not just because these are difficult to estimate but due to
ethical issues also. Infrastructure owners assess damage to their infrastructure and restore supply
as quickly as possible. But who should assess the damage done to the communities – infras-
tructure owners, local government or communities themselves? Time and economic constraints
make it difficult to collect all the information needed for assessing the social consequences of
an infrastructure failure. If this remains so, measures to improve resilience may not be fully
effective.

Risk calculations are based on chance of failure and do not deal satisfactorily with human
and organisational issues. Moreover, low probability – high consequence events may be missed
out. Risk is often defined as a triplet: what can go wrong, how likely it is and what are the
consequences. Similarly, resilience can be defined as a triplet: what can go wrong, what are
the consequences and how quickly the system can recover. So risk management contributes to
resilience building but more needs to be done.

Two phases can be identified for resilience building. In the first phase, before the event, vulner-
abilities are identified considering all interactions and managed through redundancy, diversity,
protection, and monitoring. In the second phase, after the event, resourcefulness, including the
preparatory measures, social and economic capital, determines the rate of recovery through repair
and/or gradual adaptation.

Disclosure statement

No potential conflict of interest was reported by the author.

16 J. Agarwal

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2. Resilience

3. Vulnerability
4. Risk
5. Preparedness and adaptability
6. Infrastructure criticality
7. A systems model for vulnerability and resilience
8. Discussion and conclusion
Disclosure statement

A Complexity Framework for
Studying Disaster Response
Management

Johan Bergstr€om, Christian Uhr and
Tove Frykmer
Division of Risk Management and Societal Safety, Lund University, PO Box 118, SE-22100
Lund, Sweden. E-mails: Johan.Bergstrom@risk.lth.se, Christian.Uhr@risk.lth.se, Tove.Frykmer@risk.lth.se

Guided by complexity theory, in this article, we argue that a complex understanding of
disaster response management can be achieved by making multiple, transparent and
modest interpretations. We suggest an analytical framework in which multiple system
interpretations are constructed, all based on explicit analytical choices according to
three aspects: (1) system dimension, (2) system scope and (3) system resolution. We
apply the framework to a major Swedish forest fire and conclude that direction and
coordination as system properties, emerging at a macro level, are the result of inter-
play between various patterns of influences. These patterns, we argue, can be con-
structed and analysed through a complexity framework allowing for the construction,
and contrasting, of multiple system interpretations.

1. The need for a complex understand-
ing of disaster response management

In this study, we are interested in how to generate acomplex understanding of disaster response manage-
ment. We will introduce an analytical language for
studies of how disaster response systems achieve
direction and coordination. This language is rooted in
complexity theory, allowing for multiple interpreta-
tions, based on transparent and clear analytical choices
to generate a complex and modest understanding of
disaster response.
The study begins with outlining what we mean by

direction and coordination in a disaster response con-
text. Then, we contrast a complex understanding from
a reductionist one to build an analytical framework
for studies of disaster response management, which is
rooted in complexity theory. The societal response to
a large wildfire in Sweden is used to demonstrate how
the analytical framework can be applied. Finally, we
will end with reflections on some central challenges

related to studying disaster response management
from a complexity perspective.

1.1. Achieving direction and coordination in a
disaster response system

The meaning of key terms such as coordination, Com-
mand & Control and leadership is disparate and some-
times also emotive. Scholars who spring from the
sociological tradition, focusing on managerial aspects
of civil emergencies and disasters, seem to distance
themselves from military vocabulary and problem
framing. For some scholars, Command & Control can
be an expression representing obsolete strictly hierar-
chical management paradigms (see, e.g. Quarantelli,
1988; Seddon, 2005). For others, Command & Con-
trol science can describe a progressive research field
dealing with complexity including self-organization and
multi-organizational collaboration (see, e.g. the Com-
mand & Control Research Program, CCRP). Terms
such as coordination are used in parallel for describing

Journal of Contingencies and Crisis Management Volume 24 Number 3 September 2016

an approach, an activity, a structure or an effect (see
Drabek, 2007; Ekman & Uhr, 2015; Quarantelli, 1988;
Uhr, 2009). When it comes to other related terms,
such as leadership, Stogdill (1974) wrote that ‘there
are almost as many different definitions of leadership
as there are persons who have attempted to define
the concept’ (p. 7). Management as a term is in itself a
bottomless barrel of meanings.

This heterogeneous semantic blend does not lead
to us arguing for a general standardization of meaning
of key terms, because such a condition most likely is
impossible due to the uncountable actors using the
words. Several attempts have been made in related
research fields, for example within risk management
(see Kaplan, 1997), though with limited success.
Rather, we accede to an approach suggesting that a
central aspect of disaster response management is to
achieve direction and coordination among available
resources in order to meet a range of needs during
the acute phase of a disaster. This approach is not
intended to provocatively challenge existing paradigms,
but rather to bring attention to what needs to be
achieved instead of immersing in the details on how
to do it. We are interested in providing an analytical
framework for studying, in actual cases, multiple inter-
pretations of how direction and coordination is
achieved and challenges related to achieving direction
and coordination.

Ekman and Uhr (2015) advocate the need for direc-
tion and coordination to make use of existing capabil-
ity. Without direction, the capabilities of the resources
will be useless, because they will by definition remain
passive. Without coordination, the resources are likely
to be in each other’s way and not supporting each
other when possible and necessary. We see direction
as an internal effect among the resources meaning that
the resources engaged in a response are oriented
towards formulated goals (Ekman & Uhr, 2015). As
emergencies and disasters are phenomena considered
to be taking place in dynamic and partially unpre-
dictable settings, a goal and the path to it cannot be
predetermined in detail. The environment in which the
resources act is characterized by uncertainty (Breh-
mer, 1992). Directions cannot be predetermined in
detail, and there is no single actor grasping what vari-
ous needs that might emerge, or what synergies that
might occur. Coordination is here seen as an internal
effect among the resources meaning that activities and
subgoals are adjusted to make most possible use of
available resources (Ekman & Uhr, 2015). Disaster
scholars such as Comfort suggest that coordination
implies ‘aligning one’s actions with those of other rele-
vant actors and organisations to achieve a common
goal’ (Comfort, 2007, p. 194). Malone and Crowston
(1990) define coordination as the act of managing
interdependencies between activities performed to

achieve a goal. These definitions harmonize with those
suggested by Ekman and Uhr (2015), however, focusing
on activities and not effects.
Researchers within the field of disaster research

such as Quarantelli (1988), Dynes (1990), Dynes and
Aguirre (2008), and Drabek (2007) all advocate a
focus on coordination in prescriptive discussions of
disaster response management. However, it can be
challenging to understand the various aspects and
nuances of the term and how to relate it to other
terms concerning ‘management’. Coordination (or
coordination models) is sometimes described as an
alternative to ‘bureaucratic models’, such as the ‘com-
mand & control model’ (Drabek & McEntire, 2003).
Recently, various models, and studies, of ‘Incident
Command Systems’ have addressed the need to make
the systems themselves allow for dynamic organiza-
tional structures (e.g. Jensen & Waugh, 2014; Rimstad,
Nj�a, Rake, & Braut, 2014; Scholtens, Jorritsma, & Hel-
sloot, 2014, which all appeared in the same special
issue of this journal). We argue that bureaucratic
models are tools, in addition to others, for achieving
direction and coordination. Some models are func-
tional tools and some might be dysfunctional, all
depending on the context.
In this study, we will pay attention to the systems

of resources that normally are engaged when a society
responds to a disaster; a disaster response system that
needs direction and coordination at various levels
to meet individual, societal and environmental needs.
We argue that constructing a complex understanding
of such systems is crucial when trying to explore
the space of possibilities that any disaster response
system has in its attempts to achieve direction and
coordination.

1.2. A complex understanding

The ultimate aim of this study was to achieve what
we call a complex understanding of any disaster man-
agement operation. A fundamental principle of com-
plexity theory is that it is impossible for any actor to
grasp the complete working of the system as a whole.
Further, all complexity frameworks have as their start-
ing point the holistic principle that the behaviour of
the system as a whole cannot be reduced to the func-
tioning of the constituent components, but only
sought in their nonlinear interactions and relations.
Indeed, complexity theory does not offer one coher-
ent theory. Using the words of Heylighen, Cilliers and
Gershenson: ‘Complexity science is little more than
an amalgam of methods, models and metaphors from
a variety of disciplines rather than an integrated
science’ (Heylighen, Cilliers, & Gershenson, 2007, p.
117). Such disciplines include quantum mechanics
(Capra, 1982), biology (Von Bertalanffy, 1950),

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A framework for a complex understanding 125

ecosystem theory (Gunderson & Holling, 2002) and
even postmodern philosophy (Cilliers, 1998).
To describe complexity theory in terms of scientific

facts about how to understand a disaster response
system would be self-contradictory. Instead, complex
systems are often described in terms of a number of
principles that explain why complex problems are so
inherently difficult. Such principles typically include
nonlinear interactions, openness, emergent behaviour,
system dynamics and resilient behaviour emerging
from diversity and requisite variety. However, while
we also wish to account for such principles in our
interpretations of disaster management operations,
the complexity framework developed for this study
has not been intended to show, or measure, the com-
plexity of disaster management operations (below we
will refer to this as an ontological approach to com-
plexity). Instead, we adopt a social constructivist per-
spective, adopted from Cilliers’ approach to
complexity (Cilliers, 2005) from which complexity
theory implies the need to highlight and analyse multi-
ple interpretations of any disaster management opera-
tion, make transparent analytical choices and be
modest about any claims made regarding the manage-
ment of disasters (below referred to as an epistemo-
logical approach to complexity).

1.3. Complexity as epistemology or ontology

Studies of disaster response from a complexity per-
spective typically approach the notion of complexity
as ontology, that is as a characteristic or state of the
system. In such studies, the aim is typical to describe
how complexity manifests itself in the disaster
response system. Comfort (e.g. Comfort, 1994, 1995)
utilizes complexity theory in arguing that self-organiza-
tion as a phenomenon of disaster response makes the
disaster response system complex. Self-organization is
in these writings viewed as an emergent property,
showing that the system is indeed complex and there-
fore poses certain challenges in terms of management
strategies. In more recent writings, Comfort argues
that system complexity (inherent in the scale and mul-
tiple dependencies within a multi-organizational disas-
ter response system) give rise to challenges of
coordination and suggests solutions in terms of deci-
sion support systems that can facilitate coordination
among multiple stakeholders as well as incorporating
dynamic changes (self-organization) of the disaster
response system itself (Comfort, Sungu, Johnson, &
Dunn, 2001). With the same focus on how to orga-
nize disaster response operations Comfort criticizes
the idea of hierarchical organizations, arguing that they
are typically unable to adapt to the dynamics of disas-
ters (Comfort, 1999; Comfort & Kapucu, 2006). Also
Kiel (1995) as well as Atkinson and Moffat (2005)

offer normative approaches, ontologically arguing that
since disaster response systems are complex, certain
management strategies should be applied.

Previous work has also been conducted focusing on
different techniques aiming at mapping complex disas-
ter response systems (Abrahamsson, Hassel, & Tehler,
2010; Uhr & Johansson, 2007; Uhr, Johansson, & Fred-
holm, 2008) and the connections between different
levels of the system (O’Sullivan, Kuziemsky, Toal-Sulli-
van, & Corneil, 2013). These studies, using social net-
work analysis or system dynamics modelling, have an
epistemological take on complexity because they sug-
gest a framework for analysing and evaluating emer-
gency response. Yet, they are epistemological
approaches with ontological commitments because
they focus on mapping the complex actor-network
and its interactions; that is it focus on ‘showing the
complexities’ of the system.

In this study, we distinguish between complexity as
epistemology and complexity as ontology to empha-
size that our interest is not in assessing whether or
not a disaster response system is complex or not, or
to what extent, which features of complexity that it
shows, or how to best manage the complexities. Our
framework rather aims at exploring the space of pos-
sibility in working to achieve direction and coordina-
tion in any disaster response operation, using
complexity theory as the epistemology guiding our
analytical choices. A complexity epistemology defies
the ability to make final and noncontroversial claims
regarding any disaster response operation. It rather
embraces multiple perspectives, transparency and
modesty about any claims made. As Cilliers puts it:

We cannot have complete knowledge of complex
systems; we can only have knowledge in terms of a
certain framework. There is no stepping outside of
complexity (we are finite beings), thus there is no
framework for frameworks. We choose our frame-
works (Cilliers, 2005, p. 258).

As Cilliers argues from a complexity perspective
there are only normative ways in which to choose
frameworks of analysis. Analytical choices are based
on normative assumptions of what aspects of disaster
management operations that are interesting to inter-
pret and analyse. In developing an epistemological
framework intended to facilitate the generation of a
complex understanding of disaster response manage-
ment, we therefore need to incorporate a trans-
parency of the analytical choices made, so that our
normative positions become open to further discus-
sion and critique.

Further, Cilliers’ approach to complexity embraces
the principle of multiple perspectives that ‘different
descriptions will decompose the system in different

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126 Johan Bergstr€om, Christian Uhr and Tove Frykmer

ways. Different descriptions may also have different
degrees of complexity’ (ibid, p. 257). Consequently,
our analytical framework has been developed to
account for multiple interpretations of one disaster
response operation. This in order to generate knowl-
edge characterized by epistemological pluralism (Healy,
2003) and to avoid the reductionist reasoning of com-
ing up with one correct version of the system and its
behaviour.

The final point that we want to stress and include
in our efforts to develop a framework able to facilitate
the generation of a complex understanding of disaster
management operation is the modesty that Cilliers
argues for:

A modest position should not be a weak position,
but a responsible one. Such a position will be devel-
oped by examining three arguments: the argument
that modest positions lead to relativism, the argu-
ment that modest positions are subject to the per-
formative contradiction and the argument that
modest positions are vague (Cilliers, 2005, p. 256).

This appeal to the modesty of the analyst is rooted
in the complexity theory view of knowledge as funda-
mentally provisional, depending on time, space and
framework of analysis. The way in which we wish to
account for this modesty in our analytical framework
is again in making our analytical choices transparent
and in making clear that additional interpretations will
always be possible and should always be appreciated
in further debate.

To summarize our view on complexity, the above
review suggest that a framework developed with the
intention to generate a complex understanding of dis-
aster response needs to:

• Allow for a discussion on direction and coordina-
tion as emergent phenomena from the various inter-
actions and relations in the disaster response.

• Allow for multiple interpretations of such interac-
tions and relations within the same analysis.

• Highlight the potential conflicts, overlaps or even
interactions between such perspectives.

• Make explicit the analytical choices made for con-
structing the multiple interpretations.

• Be modest in recognizing that additional interpreta-
tions will always be possible and should always be
appreciated.

2. Building a complex understanding:
multiple interpretations based on
three system aspects

To address the above-mentioned criteria for building a
complex understanding, our analytical framework is

based on constructing multiple system interpretations,
and for each system, interpretation makes explicit the
analytical choices according to three aspects: (1) sys-
tem dimension, (2) system scope and (3) system reso-
lution. Each of these three aspects is outlined below.

2.1. Aspect one: dimension

The first analytical choice to make explicit in a disas-
ter response analysis rooted in a complexity episte-
mology is what we call the system dimension. A
system dimension is the theoretical perspective con-
structing the analysis of relations and interactions
between system actors and elements. To do so, the
dimension will include both the actor(s) and the rela-
tionships studied. One example of a system dimension
is an informal network, where the actors are individu-
als and the relations connecting them to each other
are built on trust. Another dimension could be
bureaucracies describing formal roles and formal
power relations. Approaching the system as held
together by interacting functions, (a functionalist
approach), is yet another example of a system dimen-
sion. In conjunction with an analysis, one may include
principally different elements, for example individuals
using computers that are interacting through commu-
nication relations.
When studying direction and coordination during

disaster response, relations connecting the actors are
of particular interest if they enable influence, such as
communication relations, formal power relations, trust
relations etcetera. In fact, influence could be seen as a
relation between actors in itself (see Fredholm & Uhr,
2007).

2.2. Aspect two: scope

The aspect of scope refers to the analytical drawing of
the boundary around what actors and relationships
that are to be included in the interpretation. If con-
structing an interpretation based on the dimension
bureaucracies, describing roles and formal power rela-
tions, it is necessary to create an outer boundary for
what roles to include in the interpretation (not what
kind of roles or the relationships between them as in
the case of the aspect dimension above). The system
scope can be based on relevance, for example by
including the bureaucratic structures perceived to be
relevant for the response operation (and consequently
argue why others are not). It can also be based on
spatial demarcations, for example by including only
bureaucracies describing roles and formal power
relations on an accident scene, at the county adminis-
trative board or similar. Typically, system scope will be
defined in terms of both relevance and spatial
demarcations.

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A framework for a complex understanding 127

2.3. Aspect three: resolution

The system resolution has to do with a level of detail.
As we choose larger scopes of analysis, it becomes
necessary to simplify the elements by clustering them.
Sometimes, it is relevant to interpret single roles and
their relations within one organization, but sometimes
it is necessary to choose a lower system resolution by
clustering roles. Informal networks based on trust can
be analysed from a group perspective, and technical
system dimensions can be described as interlinked
clusters of communication devices and so on.
There is a logical link between system resolution

and system scope. A wide system scope often sacri-
fices a detailed system resolution, similar to a wide
angle lens. A narrow system scope allows detailed sys-
tem descriptions, similar to a macro lens, but sacri-
fices a comprehensive analysis. Within a complexity
epistemology, it therefore makes sense to vary the
system resolution in different interpretations in order
to compare and contrast them with each other.

2.4. Grasping the interpretations

The aim of us introducing this framework is to facilitate
the generating of a complex understanding of the space
of possibility for achieving direction and coordination in
disaster response. To us, a complex understanding
implies the interpretation of a diversity of perspective:
a variety of dimensions, scopes and resolutions. Such a
diversity of interpretations not only generates a multi-
tude of interpretations, but also accounts of how the
interpretations themselves interact, complement each
other or contradict each other. Conflicting interpreta-
tions add to the complex understanding and the analyti-
cal modesty that we try to stimulate.
Using the multiple interpretations generated through

the framework of transparently choosing aspects of
study ultimately make us able to construct a convincing
description of how direction and coordination are
achieved in disaster response operations. Also, we aim
at constructing different challenges related to achieving
direction and coordination and ultimately learning out-
put in terms of advice concerning how to meet the
challenges.

3. Application of the analytical frame-
work on the recent Swedish wildfire

In this section, we use the analytical framework intro-
duced above to understand how direction and coordi-
nation were achieved during a major wildfire in
Sweden 2014. Two of the authors behind this article
were present as observers and researchers in the joint
command centre for 4 days. Our analysis is to be
seen as a demonstration of how to use the theoretical

framework and not as a thorough analysis of the disas-
ter response system during the event. The data under-
lying the demonstration of the framework comprise
field notes, observations, public reports and 24 inter-
views, of which five were on site and 19 after the
operation ended. The data were collected for an anal-
ysis of direction and coordination during the handling
of the wildfire and will now serve the purpose of
showing multiple interpretations in our analytical
framework. Examples from interviews have been
translated from Swedish by the authors.

The extensive wildfire broke out on the 31 July
2014 in the county of V€astmanland in Sweden. The
emergency response operation was officially ended on
the 11 September. During the response, a wide range
of societal resources were engaged, such as fire and
rescue service organizations from different parts of
Sweden, the police, the County Administrative Board,
central agencies, the Swedish Armed Forces, volunteer
organizations, unorganized volunteers, private organi-
zations and Italian and French water bombing aircrafts
with crew.

Below, we will introduce six different interpreta-
tions of how direction and coordination were
achieved during different stages of the event. Following
the interpretations, we discuss shortly how such inter-
pretations together contribute to a complex under-
standing of the disaster response system. We should
already here acknowledge that our aim with the
example is not to generate such a complex under-
standing, but only to show the principle path towards
it with the selected interpretations.

3.1. Interpretation one – a system of two sepa-
rate formal organizations

The Swedish system for civil safety is, as most of the
Swedish political system, based on a decentralized
principle of local responsibility. As is regulated in the
Swedish Civil Protection Act, municipalities are
responsible for providing fire and rescue services
within their geographical borders. In the case of the
wildfire of V€astmanland in 2014, the fire actually
started close to, and soon crossed, the borders of
two different municipalities, meaning that two different
fire and rescue service organizations were involved in
the response.

In an interpretation of the formal system of the
response operation during the first days of the wild-
fire, we take the formal roles as actors and the formal
power relations between them as our dimension of
study. As our scope, we combine relevance and spatial
demarcation by focusing on the senior commanding
staff within the relevant fire and rescue service organi-
zations present at the command posts rather than all
individual fire fighters involved. This enables us to

128 Johan Bergstr€om, Christian Uhr and Tove Frykmer

interpret the more strategic challenges of achieving
direction and coordination in the response operation.
The resolution chosen for this interpretation is at the
individual level. A conceptual illustration of this inter-
pretation is shown in Figure 1.

When an incident affects several municipalities, as
in our case, the Swedish fire and rescue service orga-
nizations should cooperate and coordinate their
resources in the response operation. Despite this, the
formal fire and rescue service organizations involved
in the wildfire did not achieve this but rather
remained as two separate organizations with separate
incident commands (Ministry of Justice, 2015), which
is illustrated in the figure above with the dashed line
in between the formal organizations. This can also be
exemplified with examples from our interviews:

We had one incident command in XX [location]
and one in XX [location], I think. And it was
unclear: who is the incident commander here and
who is the boss here?

And then I realized that the work was still per-
formed on two different sides.

It was really strange with two separate incident
response operations, I thought that was very
strange. I didn’t understand it.

During Monday the 4 August, the fire spread rapidly
and the response operation expanded in terms of
actors and resources, such as the Swedish Armed
Forces, volunteer organizations and forest property
owners (Ministry of Justice, 2015). The actors of this

formal system realized that the response system
lacked the ability to achieve acceptable direction and
coordination among the resources to meet the needs
and therefore asked the County Administrative Board
to assume responsibility of the handling of the wildfire
(County Administrative Board of V€astmanland, 2014).
This was executed on Tuesday the 5th and at the
same time the County Administrative Board appointed
a highly experienced commander to be the new inci-
dent commander of the operation (Ministry of Justice,
2015).

3.2. Interpretation two – a formal, centralized
system

From the moment that the County Administrative
Board of V€astmanland assumed responsibility for the
disaster response operation, we need a new interpre-
tation of the formal system. The aspect resolution (in-
dividual level) remains the same but we need to
change the dimension and scope of the interpretation.
The dimension now consists of formal roles and for-
mal relations between them and the scope takes the
form of the joint command centre that was estab-
lished at a conference facility in the village of Ramn€as.
For a conceptual illustration of interpretation two,
see Figure 2.
The previously active fire and rescue service organi-

zations were still active, but the command structure
now changed. In addition to the fire and rescue ser-
vice, other organizations and authorities such as the
police and the Swedish Armed Forces were included
in the system, as well as County Administrative Board
representatives. These actors are represented with

Figure 1. Conceptual illustration of interpretation one.

Figure 2. Conceptual illustration of interpretation two.

A framework for a complex understanding 129

formal roles horizontally attached to the incident
commander and with their respective organizational
structure beneath. The appointed incident commander
expressed in one of our interviews that the greatest
challenge during the start-up of the new formal cen-
tralized organization was to ‘form one response oper-
ation with all aspects included’.
As the formal, centralized organization was formed

an earlier sense of chaos was changed into a sense of
calm focus, as expressed in one of our interviews:

On the Wednesday a structure had been created,
there were staff on site as well as in the incident
command, we have a staff room, we have positions,
we have titles, we have assignments. [. . .] Since that
day, it looks like home.

During observations on site, we could note that
also actors not formally involved in the chain of com-
mand ranging from this newly appointed commander
expressed that he was also their commander. The
interpretation of the formal command structure is not
able to capture such accounts, and since most obser-
vation reports and early evaluations of the operation
remain at the level of formal roles and responsibilities,
we need additional interpretations of how direction
and coordination were achieved in the disaster
response operation, leading to interpretation three.

3.3. Interpretation three – a system of trust

The commander had great freedom in selecting the
fire and rescue service staff acting in the new joint
command centre organization. Several appointments
reflect relations of trust between the actors rather
than formal relations and can be seen in our interview
with the commander:

Then I began to pick from the group of people I
know and trust in order to man these functions.

Further down in the now extended fire and rescue
service organization similar patterns of trust can be
distinguished:

Then, in the relationship with XX [the commander]
and XX [the chief of staff] there was a more per-
sonal trust which made it very simple.

When we reported at nine there were a lot of
rotations and stuff going on in there, and one per-
son heard that I was from Gothenburg and then he
pointed at me and said that you will be responsible
for the north-eastern sector, then he asked me
who I was.

A senior commanding officer in the fire and rescue
service came up with the expression ‘the Ramn€as
spirit’, which reflected the high level of trust in the
response organization:

Number one in this success story [achieving direc-
tion and coordination in Ramn€as] is the County
Board governor who gave confidence to XX [the
commander] and in a way to me. Number two was
XX [the commander], he gave confidence, he
allowed for a great arena to act on. I think I came
up with the expression ‘the Ramn€as spirit’ and I
think that is a product of all that, where it started
with the County Board governor.

Additional examples of trust can be seen in how
actors not formally subordinate to the commander or
the fire and rescue service, such as the police, were
nevertheless perceived as so:

Yes, I experience that it is that way, that he [the
commander] is the one people turn to, he gets that
role at least.

We [the fire and rescue service] own the response
operation. [. . .] When the police or the Armed
Forces want to do something they ask me.

Also members of the police acting at this joint com-
mand centre expressed to us, in informal conversa-
tions, that they perceived themselves as subordinate
to the commander in charge of the fire and rescue
service operation. Several observations on site also
justify seeing the organization of the joint command
centre as based on relations of trust, rather than of
only formal delegations. One observation involves a
fire and rescue service employee, being interested in
what was going on in Ramn€as managed to hitchhike
with a military helicopter to the joint command cen-
tre. There, he happened to know the person respon-
sible of operational control, who soon had his friend
appointed head of fire and rescue operations for a
particular geographical sector.

Thus, our interpretation three entails a new dimen-
sion of humans as actors and relations of trust
between them. We keep the scope as the joint com-
mand centre in Ramn€as, and the resolution the individ-
uals acting there. For a conceptual illustration of
interpretation three, see Figure 3.

This also becomes an interpretation of how the for-
mal joint command organization is dynamically orga-
nized and re-organized partially based on relationships
of trust. However, this does not make the organiza-
tion informal. Using the interpretations together, we
start to build a more complex understanding of the

130 Johan Bergstr€om, Christian Uhr and Tove Frykmer

disaster response operations and how direction and
coordination were achieved.

3.4. Interpretation four – a functional system

The response operation was managed from one room
at the Ramn€as conference centre, which can be called
the incident command room. In the room relevant
actors such as the fire and rescue service’s operational
senior staff, air space coordinators and the Swedish
Transport Administration were gathered. Interviews
with staff from the incident command room revealed
that relations in this room were mainly based on func-
tions rather than formal relations and that one would
turn to the relevant function in order to achieve
direction and coordination:

I didn’t ask any commanding fire and rescue officer
when we wanted water bombing, instead I went
straight to the helicopter responsible.

We sat so close to each other in Ramn€as so it was
better to go out to the military with what we
needed, the police was in the same room.

In this room there were many actors, for example
the Swedish Transport Administration is an actor
that I usually never use that way. [. . .] It probably
built on that we were in the same room, it became
natural that one ‘here’s a task that I can solve’, that
is the Swedish Transport Administration voluntarily
took over a task so that we [the fire and rescue
service] didn’t need to handle that.

This functional system is our interpretation four. As
dimension, we have functions and functional relations
between them. The room sets a spatial demarcation
for the scope of the system, and as resolution, we take
the individual level. For a conceptual illustration of
interpretation four, see Figure 4.

3.5. Interpretation five – a socio-technical net-
work of forest property owners and their tools

Disasters involve actors who are not engaged in any
formal command organization (Drabek et al., 2003),
but still achieve direction and coordination of
resources to meet certain needs. During observations
on site, we could note that local forest property own-
ers came together to try to protect their property.
As they perceived a need (a threat to their property)
and had the tools to act, they were able to achieve
direction and coordination among their own resources
to meet the need of protecting their properties from
fire by, for example creating firebreaks in the forest.
The composition of interpretation five can be under-
stood as a result of self-organization. However, one
must bear in mind that we emphasize interpretations
and thus leave ontological considerations aside. Exam-
ples from our interviews also justify this interpreta-
tion:

There were property owners, forest property own-
ers, they had interests but they didn’t express it
that way, but they wanted to help.

There were a lot of civilians who wanted to help,
mostly people living there who had resources they
believed we needed, like tractors and so on.

Our interpretation five is a socio-technical network
of forest property owners and their tools forming the
dimension. The forest property owners were held
together by agreements, probably based on previous
relationships and a common incentive to protect their
property. Thus, the relations in this interpretation con-
sist of these agreements as well as ownership linking
the owners to their tools. The scope of this interpreta-
tion is made up of the spatial demarcation of forest
property owners and their resources in the specific
areas threatened by the fire. The resolution is at the

Figure 3. Conceptual illustration of interpretation three.

Figure 4. Conceptual illustration of interpretation four.

A framework for a complex understanding 131

level of individuals and their tools. In Figure 5, we
show a conceptual illustration of interpretation five.

3.6. Interpretation six – a system of
communication

Due to the large area covered by the wildfire, the
operation was separated in geographical sectors to
divide the workload into smaller segments, something
that is commonly done in fire and rescue service
operations. From our functional system, orders were
sent to one or several of these geographical sectors,
where fire and rescue service staff and other
resources such as the Swedish Armed Forces and
organized/self-organized volunteers assisted in per-
forming the tasks. Due to perceived unclear formal
responsibilities, it was not at all times clear for the fire
and rescue service personnel whether they formally
‘owned’ the resources in the sector and whether they
consequently could give formal orders to them. Nev-
ertheless, the actors in the geographical sector prag-
matically worked together to achieve direction and
coordination to solve the needs, which can be noted
in our interviews:

I had around six units and military there. On Wed-
nesday there were volunteers [forest property own-
ers] there, on Thursday we became friends and on
Friday we hugged when I was going home. I had an
awesome cooperation with the volunteers.

Out there were a lot of military helping out, they
managed themselves and just reported how much
people they had and then we [fire and rescue ser-
vice] split them up.

The organised volunteers and the military were fan-
tastic, they just delivered.

One fire and rescue service commander responsible
for a geographical sector mentioned how the cooper-
ation around firebreaks took place:

There were forest machines, and after the machines
came bulldozers and after was a military tank with
a water tank and after that came two men putting
out small fires that could appear after the machines.

Our interpretation six is made by looking at the
relationships between the fire and rescue service as a
group and other group of actors in the sector, which
then also includes our socio-technical network of
property owners and their tools, that is interpretation
five. The dimension of this interpretation consists of
humans as actors connected by relations of communi-
cation rather than, for example formal relations. The
scope includes spatial demarcation of the geographical
sector and the resolution is based on interacting groups
of actors, representing the fire and rescue services,
forest property owners, the Swedish armed forces
and organized volunteers. This interpretation is shown
as a conceptual illustration in Figure 6 with the fire
and rescue service as the hub of communication.

Not everything was unproblematic in our system of
communication. For instance, the initiatives of the
property owners described in interpretation five were
often performed without the knowledge of the fire
and rescue service staff and the fire and rescue ser-
vice did not have any influence on the direction of the
resources. When the forest property owners did not
get response from their official contact attempts with
the fire and rescue service (Ministry of Justice, 2015),
they probably decided to act on own initiative. Not
knowing when or where the local property owners
were acting was looked upon with concern for the
safety of the property owners. When one of the
authors joined for a control drive in the area, fire-
breaks not ordered by members of the fire and rescue
service were discovered. Prior to the occasion, there

Figure 5. Conceptual illustration of interpretation five.

132 Johan Bergstr€om, Christian Uhr and Tove Frykmer

was also an incident when the joint command centre
needed to interact with local and self-directing actors
by actually rescuing them from dangerous situations.
In addition, the forest property owners were at times
perceived as difficult to control by the fire and rescue
services:

So when I get out there, around ten farmers [forest
property owners] with these fertilizers stand there,
and when you call for more people and so on, then
there is a lot going on. And these farmers were
really difficult to control.

3.7. Grasping the interpretations

In Table 1, a summary of the six interpretations is
given.

How was direction and coordination achieved in
this Swedish fire disaster? What are the needs that
should be met by achieving direction and coordination
among the resources? What defines a resource? Are
local incentives a problem or a necessary resource?

Table 1 suggests that the answers are to be found
in a complex understanding allowing multiple perspec-
tives. Based on our observations, we conclude that
different interpretations are possible, but that single
actors are trapped in their respective rationalities and
thus have difficulties in grasping multiple perspectives
allowing a complex understanding. This may not only
affect the quality of evaluation and learning processes
after an emergency/crisis/disaster, it also becomes an
operational problem during a response, for example
to the wildfire case described in this study. When
working to achieve direction and coordination among
a conglomerate of different resources (fire are rescue
service, visiting volunteers, military, local property
owners, etc.), not only the existence of various goals
must be acknowledged. One must also realize that
direction and coordination as system properties,
emerging at a macro level, are the result of interplay
between various patterns of influences visible only
through multiple interpretations.
In this short introduction to how our analytical

framework can be used, we have included different
perspectives generating not only different answers to

Figure 6. Conceptual illustration of interpretation six.

Table 1. Summary of the Six Interpretations

Interpretation Dimension Scope Resolution

1. A system of two separate
formal organizations

Formal roles and power relations Fire and rescue service
command in two
municipalities

Individuals

2. A formal, centralized system Formal roles and power relations The joint command centre Individuals
3. A system of trust Humans and trust relations The joint command centre Individuals
4. A functional system Functions and functional relations The incident command room Individuals
5. A socio-technical network of
forest property owners
and their tools

Forest property owners with tools and
agreement/ownership relations

Forest property owners and their
tools in specific areas

Individuals
and tools

6. A system of communication Humans and communication relations The geographical sector Groups

A framework for a complex understanding 133

the questions asked above, but also additional ques-
tions, such as Are self-organized local actors with
resources a coordination problem to consider or a
necessary resource to appreciate? Do direction and
coordination emerge through means of formal struc-
tures or structures of trust? What happens when
these interpretations coexist and interact? What hap-
pens when actors change their views of each other or
even themselves? The complex understanding is
shown when we are modest enough to construct this
pluralism of possible interpretations.

4. Discussion of implications for disaster
studies and response management

The first critical question to be raised concerning our
suggested framework, and our demonstration of how
it can be used, is whether it allows for an understand-
ing of complex systems or a complex understanding
of systems. The complex understanding implies the
construction of multiple interpretations, and a mod-
esty about the ‘correctness’ of any such interpretation
by acknowledging that interpretations are provisional
in time as well as space; acknowledging that there will
always be room for additional interpretations (the
more ontological assumption that no actor, or
researcher can fully grasp the complexity of the whole
system). Not only will there always be room for addi-
tional interpretations, interpretations will also only
seem valid in constrained temporal and spatial scales.
This is not only because the dynamics of the disasters
changes the response operation in a tactical sense, but
also because actors’ views of other actors will change
and actors’ self-images might change too as a disaster
unfolds. Further, this modesty is also achieved by
being clear about the analytical choices made to con-
struct different interpretations. This is in our frame-
work operationalized as the different aspects of every
interpretation.
We should also note that one aspect, in which our

view of complexity theory differs from the way that it
is typically operationalized in the field of disaster
research, is our view of the principle of emergence. In
the disaster literature, emergence is typically made
synonymous with self-organization and ‘ad hoc solu-
tions’ (e.g. Boersma, Comfort, Groenendaal, & Wol-
bers, 2014; Comfort, 1994). To us, seeing emergence
as the core system argument that the (emergent)
behaviour of the whole cannot be reduced to the
behaviour of the constituent components but only
understood in terms of interactions and relations
(Dekker, Bergstr€om, Amer-W�ahlin, & Cilliers, 2013),
self-organization does not emerge as much as it has
emerging consequences in terms of additional chal-
lenges to the system’s abilities to achieve direction
and coordination. Again, this is a matter of perspective

(involving dimension, scope and resolution of the sys-
tem), but our focus is rather on direction and coordi-
nation as emergent phenomena, emerging from the
interactions between self-organization, communication,
use of various resources, formal command structures,
regulations, weather and other aspects perceived rele-
vant to the one studying a disaster response system.

We have distinguished between complexity as epis-
temology and complexity as ontology in order to
emphasize that we do not intend to argue for ‘how’
complex a particular disaster response operation was
or for how to best direct and coordinate complex dis-
aster management operations. Instead, we highlight
how some critical, and in the disaster management lit-
erature typically ignored, points from complexity the-
ory can inform our development of a complex
understanding. However, of course, there is a connec-
tion here between complexity as ontology and com-
plexity as epistemology. Hence; generating a complex
understanding is not simply an academic exercise but
can feed back to practitioners and system designers in
several ways. First and foremost, just showing the
potential coexistence of multiple interpretations of
one single disaster response operation could be a ped-
agogical tool for teaching some central challenges to
efforts for achieving direction and coordination and
serve as a start of discussion for how to address some
of them. Second, how different interpretations coexist
and influence effort to achieve direction and coordina-
tion could be built in to scenarios used in disaster
response training and simulation. Third, our concep-
tual tool for understanding various interpretations of
recourses engaged in response operations can support
efficient response in naturalistic settings, that is in real
emergency situations. One example is when arranging
meetings for composing situational pictures. Instead of
trying to achieve a one dimensional (homogeneous)
understanding of resources engaged in a response
operation, participants can be encouraged to try to
achieve a heterogeneous holistic understanding, consti-
tuted by different coexisting interpretations.

It might be possible that some readers interpret
our idea on complex understanding as an alternative
to existing response doctrines, such as ICS/NIMS.
That is not our intension. The aim has been to pro-
mote an approach that enables further understanding
and reveals the need for being humble when con-
structing representations of reality.

Our six interpretations of the wildfire disaster
response operation are only brief introductions to
what could be subject for further analysis. For example,
to deepen the interpretation of a functional system
models such as the functional resonance analysis
method (FRAM) aimed at analysing functional relations
in terms of how different functions ‘resonate’ with each
other (Hollnagel, 2012) could be useful. When going

134 Johan Bergstr€om, Christian Uhr and Tove Frykmer

ahead with deeper analysis of the disaster response
operation manifested as interlinked social networks,
other analysis methods, including snowballing (Uhr,
2009), can be employed. The intention of our (deliber-
ately broad) framework is to make it work for events
of multiple scales and to allow it to include multiple
methods of analysis for the multiple interpretations
made. Bigger scale events than the Swedish forest fire
that we have analysed would much likely require a great
number of system interpretations in order to generate
what could be claimed to be a complex understanding.

Perhaps, the most important implication of the
framework that we suggest is that of being modest in
the claims we make, we hope that also people
involved in disaster response (or evaluations of disas-
ter response) will approach each other with humble-
ness. That is what a complex understanding allows by
defying simple statements and solutions often revert-
ing to heroes and villains.

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