patterns of interorganizational collaboration in disaster
TRANSCRIPT
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Patterns of interorganizational collaboration in disaster
risk reduction: Evidence from Swedish municipalities
Linnea Burke Rolfhamre
Master Thesis in Political Science, Spring 2019
Supervisor: Daniel Nohrstedt
Department of Government
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Abstract
Prevention, mitigation and response to large scale disasters is complex. It is widely
argued that collaboration is a necessary component of successful disaster risk reduction
(DRR). However, there are also significant challenges associated with collaboration for DRR.
In this paper I carry out a descriptive, empirical case study of collaboration within disaster
prevention and preparation in Sweden at the municipal level. The aim of the study is to
identify potentially interesting patterns regarding collaboration and obstacles to collaboration
in local disaster risk reduction. The study answers the question: to what extent do Sweden’s
municipalities collaborate with other stakeholders on disaster risk reduction? Interesting
patterns regarding the stability versus volatility of collaboration are identified. This study lays
the foundation for further research on the potential and limitations of collaborative forms of
governance for tackling complex societal phenomena that have a high degree of
interdependency and uncertainty.
Keywords: Disaster risk reduction, collaborative governance, local-level, Sweden, SFS
2006:544
Acknowledgments
I would like to thank the Swedish Civil Contingencies Agency (MSB) for their work
compiling the data used in this study and for answering my questions. I would also like to
thank my advisor, Daniel Nohrstedt, for his guidance with this project. Last but not least, I
would like to thank my wonderful family for their steadfast support.
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Table of Contents
1 Introduction ........................................................................................................................ 5
1.1 Outline ......................................................................................................................... 7
1.2 The Choice of Case ..................................................................................................... 7
1.3 Limits of the Study ...................................................................................................... 8
2 Theory and Previous Research ........................................................................................... 8
2.1 Approaches to Disaster Prevention ............................................................................. 8
2.1.1 The Vulnerability Paradigm ................................................................................. 8
2.1.2 Crisis, Emergency and Disaster Management ..................................................... 9
2.1.3 Disaster Risk Reduction (DRR) ......................................................................... 10
2.1.4 Collaborative Governance ................................................................................. 10
2.2 Collaborative Governance for DRR .......................................................................... 11
2.2.1 The Sendai Framework for Disaster Risk Reduction ........................................ 11
2.2.2 Reasons for Collaboration.................................................................................. 11
2.2.3 Challenges to Collaborative DRR ...................................................................... 14
2.2.4 The Theoretical Tension in Practice .................................................................. 18
3 The Swedish Context ........................................................................................................ 18
3.1 The Legal Framework ............................................................................................... 19
4 Methods ............................................................................................................................ 21
4.1 Choice of Methods .................................................................................................... 21
4.2 The Data .................................................................................................................... 23
4.3 Datasets ..................................................................................................................... 25
4.3.1 Dataset 1: Collaborative Partnerships ................................................................ 25
4.3.2 Dataset 2: Structures for Collaboration.............................................................. 26
4.3.3 Dataset 2: Qualitative Data Section ................................................................... 26
4.3.4 Dataset 3: Collaboration Within and Beyond the Municipality’s Boarders ...... 27
4.3.5 Terminology in the Survey ................................................................................ 28
4.3.6 Categorization of Municipalities........................................................................ 29
4.3.7 Missing Data ...................................................................................................... 29
4.3.8 Language ............................................................................................................ 30
5 Analysis ............................................................................................................................ 30
5.1 Collaborative Partnerships ........................................................................................ 30
5.1.1 Partnerships 2009 to 2012 .................................................................................. 30
5.1.2 Collaborative Partnerships 2009 to 2012 by Groups of Municipalities ............. 32
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5.1.3 Stability of Collaborative Partnerships 2009 to 2012 ........................................ 34
5.1.4 Stability of Collaborative Partnerships 2009 to 2012 by Groups of
Municipalities ................................................................................................................... 36
5.1.5 Collaboration Outside of the Municipalities’ Geographic Area 2015 to 2018 .. 36
5.2 Structures in Place for Collaboration ........................................................................ 37
5.2.1 Structures in Place for Collaboration 2010 to 2014 ........................................... 37
5.2.2 Structures in Place for Collaboration 2010 to 2014 by Groups of Municipalities
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5.2.3 Stability of Structures in Place for Collaboration 2010 to 2014 ........................ 39
5.2.4 Stability of Structures in Place for Collaboration 2010 to 2014 by Groups of
Municipalities ................................................................................................................... 39
5.2.5 Structures in Place for Collaboration 2015 to 2018 ........................................... 40
5.2.6 Stability of Structures in Place for Collaboration 2015 to 2018 ........................ 42
5.3 Text Analysis: Obstacles to Establishing Collaborative Governance Structures, 2010
to 2014 .................................................................................................................................. 43
6 Summary and Conclusions ............................................................................................... 45
6.1 Themes and Patterns that Warrant Further Exploration ............................................ 47
6.1.1 Volatility of Partnerships ................................................................................... 47
6.1.2 Municipalities in the Role of Facilitators........................................................... 47
6.1.3 Mandated Versus Voluntary Collaboration ....................................................... 47
6.1.4 Bilateral Versus Multilateral Collaboration ....................................................... 48
6.2 Closing Remarks ....................................................................................................... 48
7 References ........................................................................................................................ 49
8 Appendix A1 ..................................................................................................................... 54
9 Appendix B ....................................................................................................................... 75
10 Appendix C ................................................................................................................... 78
11 Appendix D ................................................................................................................... 79
12 Appendix E ................................................................................................................... 80
13 Appendix F.................................................................................................................... 86
1 Contact author for a copy of appendix A
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1 Introduction
”Disasters, many of which are exacerbated by climate change and which
are increasing in frequency and intensity, significantly impede progress
towards sustainable development. Evidence indicates that exposure of
persons and assets in all countries has increased faster than vulnerability
has decreased, thus generating new risks and a steady rise in disaster
related losses, with a significant economic, social, health, cultural and
environmental impact in the short, medium and long term, especially at the
local and community levels” (United Nations International Strategy for
Disaster Reduction 2015, 8).
Disasters are expensive and exact a heavy toll on human life. (United Nations
International Strategy for Disaster Reduction 2015). Protection of the most fundamental
human right, the right to life, as well as the practice of democracy, require safe and secure
societies. Global climate change will likely lead to more frequent and intense natural hazards.
Simultaneously, new technology, globalization and increasing trans-boundary
interdependence pose challenges to the way countries prevent, prepare for and respond to
disasters (ibid).
Disaster prevention and mitigation is complex and transcends geographic and
jurisdictional boundaries (McGuire and Silvia 2010). It requires actions that challenge
institutionalized societal power structures (Wisner et al. 2004). Command-and-control risk
management is shifting to more interactive forms of risk governance. As societies take a
broad view of disasters, new approaches to handling risk emerge that incorporate an
understanding of how vulnerabilities and hazards interact (ibid).
Politically, however, there may be little incentive to invest in disaster risk reduction
because there is no guarantee it will pay off. Though large-scale disasters are costly events, at
the local level, there is only a low probability that one will occur (McConnell and Drennan
2006). For local authorities, this means that it is possible to ignore investing in DRR without
facing any consequences if, in fact, no disaster occurs during your tenure. While on the flip
side, investing scarce resources to prevent and prepare for an event that never occurs can be
politically costly. Another political challenge, in addition to financial investment, is tackling
the structural causes of vulnerability. Changing the conditions that create societal
vulnerability can be far more complex and controversial than simply funding disaster
response measures or building hazard mitigating infrastructure (Wisner et al. 2004). In depth
case studies of disaster management focus primarily on collaboration and coordination of
acute responses to ongoing events (Boin et al. 2010; Bruns and Burgess 2014; McGuire and
Silvia 2010).Though research on adaptive and preparatory collaborative governance exists in
the related field of environmental management (Berardo, Heikkila, and Gerlak 2014), more
such research is needed in the context of disaster risk reduction (Nohrstedt and Bodin 2014).
To that end, this empirical study focuses on prevention of, and preparation for, disasters.
Using quantitative data with many units of analysis, the study explores patterns of
collaboration that have not typically been part of previous case studies.
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Disaster risk reduction (DRR) looks at disaster prevention, mitigation and response
through a vulnerability-and-hazard-based understanding of disaster (United Nations
International Strategy for Disaster Reduction 2015). Previous academic literature on disaster
management strongly advocates for broad collaboration in public policy decision-making.
Collaborative governance is a way of conceptualizing such collaborative forms of public
policy decision-making. This paper addresses the reasons collaborative governance is
particularly relevant in disaster risk reduction. It also highlights potential obstacles to
collaboration, including the burden of putting time and effort into the collaborative process,
political fall-out from investing in low-probability events, and problems of free-ride in
collective action.
To further the theoretical discussion on the potential and limitations of collaborative
governance as a means of public policy decision-making, I have carried out a descriptive,
empirical case study of collaboration in disaster prevention and preparation. I want to know if
collaborative governance in DRR is taking place and, if so, whether it is effective. However,
because answering both those questions is beyond the scope of this study, I have taken the
first step toward gauging the extent to which collaboration is used in DRR by mapping its
current use in an empirical case. To further narrow the scope of this paper, I have specifically
focused on mapping several measures of collaboration for which data is available. I have
posed the overarching question, “What can the available data from this case of local DRR tell
us about the extent of collaboration and patterns in collaboration over time?” Based on this
analysis, I provide more detailed recommendations for further research into collaboration in
disaster risk reduction which is one component of understanding the potential of collaborative
governance for public policy decision-making more generally. This study lays the foundation
for further research on the potential and limitations of collaborative forms of governance for
tackling complex societal phenomena that have a high degree of interdependency and
uncertainty.
The study is descriptive and, therefore, does not make any causal claims. Instead of
formally testing a theory, it identifies relevant themes in the theoretical literature and
potentially related trends and patterns in an empirical case. The aim of the analysis is to
empirically describe patterns of interorganizational collaboration over time in the area of
local disaster risk reduction. The study answers the following empirical research question:
To what extent do Sweden’s municipalities collaborate with other stakeholders on
disaster risk reduction?
The empirical sub-questions are:
Which partners2 do the municipalities collaborate with?
To what extent do the municipalities have collaborative governance structures in
place?
2 In this paper, the term partner is used to mean other actor, organization or entity in bilateral or multilateral
collaboration. The term does not refer to partner in the more specific sense of public-private partnerships, even
when partnerships between public and private entities are being discussed.
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What hinders the municipalities from having collaborative governance structures in
place?
Are there any noticeable time trends in municipalities’ use of collaboration?
Are there differences between large, urban municipalities and smaller, rural
municipalities?
This study provides an empirical foundation for further exploration of the extent, nature and
quality of collaborative governance in practice.
1.1 Outline
The study begins with a brief review of the theorical concepts of disaster risk
reduction and collaborative governance. Next, the study reviews available literature on the
importance of collaborative forms of governance for successful DRR. That is then contrasted
with the vast body of literature on collective action problems. The theory section thereby
explores the attributes of DRR that give rise to tension between potential gains from
collaboration and problems associated with collective action.
Next, I carry out a descriptive, empirical case study of disaster prevention and
preparedness in Sweden at the municipal level. For context, I provide a brief overview of the
Swedish institutional context and legal framework surrounding prevention and preparedness
for extraordinary events. Next, I make use of data, compiled by the Swedish Civil
Contingencies Agency (MSB), from surveys of Swedish municipalities from the years 2009
to 2018. I use this data to study patterns of Swedish municipalities’ collaboration with
specific actors, the presence or absence of structures for collaboration and potential
constraints on collaboration.
1.2 The Choice of Case
Swedish municipalities have a high degree of autonomy (Sveriges Kommuner och
Landsting n.d.). They are required to work on disaster prevention, preparation and mitigation;
however, they have some freedom to select whether they want to make use of collaborative
governance approaches (SFS 2006:544). At the international level, discussions of DRR
recommendations focus on socioeconomically less developed countries prone to natural
hazards (United Nations International Strategy for Disaster Reduction 2015). DRR comes up
in the context of foreign aid and investment programs directed towards less
socioeconomically developed areas in countries with weak state institutions and a high degree
of societal vulnerability. The push for locally rooted governance structures has emerged with
that context in mind. However, highly regulated and institutionalized settings, with access to
extensive fiscal resources and scientific information, present a different set of challenges and
possibilities for collective action (Feiock 2009, 360). This study of Swedish municipalities
contributes to our understanding of DRR collaboration in that setting.
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1.3 Limits of the Study
Modernization introduces new risks which differ from age-old natural hazards in that
they cannot be seen or touched, or perhaps even understood by the public. These are risks
such as poor lifestyle choices, carcinogens and radiation (Wisner et al. 2004, 16). The effects
have a slow onset and, in many cases, are individual, though at an aggregate level they may
produce societal crises. Such risks are not discussed in this study. Even though the scope of
this study is not explicitly limited to sudden onset events, it is limited to prevention and
mitigation of disasters and extraordinary events that seriously disrupt society and put people
in harm’s way.
The existing literature on disaster risk reduction focuses on natural hazard prevention,
mitigation, response and recovery. For example, Wisner et al. (2004) focus on the natural
hazards most common in least developed countries and do not discuss risks that are only
associated with highly technologically developed and dependent societies. My study is not
limited to the study of DRR in the context of natural hazards or least developed countries.
Any event or process that has a noticeable and detrimental effect on societal functionality and
human security is within the scope of the study, with a few exceptions. This paper does not
deal directly with military security or technological security. Even so, it is important to
recognize that technological security is becoming increasingly more important to the field of
disaster risk reduction. The relationship between armed conflict and societal vulnerability
should be noted as well. More research integrating theory from the fields of technological
security and physical safety, is needed, as both are highly relevant to human safety and
wellbeing.
2 Theory and Previous Research
2.1 Approaches to Disaster Prevention
2.1.1 The Vulnerability Paradigm
When we hear about disasters in the news, the headlines typically center around
hazards. “Deadly hurricane strikes….”, “flood causes devastation”. Hurricanes and flood are
examples of natural hazards (Wisner et al. 2004, 80). Hazards can also be manmade
phenomena, for example chemical spills or carcinogens in food. The United Nations
International Strategy for Disaster Reduction (UNISDR) writes, “There is no such thing as a
'natural' disaster, only natural hazards” (United Nations International Strategy for Disaster
Reduction n.d.). What they mean is that disasters are caused by human factors, not by nature.
If a tsunami hits a coastal area and there are no humans there, no humans will be harmed. A
hazard is present, but no disaster takes place, if no people or property are there to be exposed
to harm. What turns a hazard into a disaster is the interaction between the hazard and a
vulnerability to the hazard (Wisner et al. 2004, 55–56). MSB defines vulnerability as “the
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attributes or circumstances that expose a society, a system, or property to the negative effects
of an event” (MSBFS 2015:5) (author’s translation)3. Zhang et al. write, “Vulnerability,
which is the degree to which an organization is likely to experience harm due to its exposure
to hazardous events (Turner et al. 2003), is recognized as an outcome of the interaction
between an organization’s exposure to environmental stresses and its ability to prepare for
and react to them effectively” (Zhang, Welch, and Miao 2018, 372). Wisner et al. (2004)
define vulnerability as, “the characteristics of a person or group and their situation that
influence their capacity to anticipate, cope with, resist and recover from the impact of a
natural hazard (an extreme natural event or process)” (Wisner et al. 2004, 11). What all three
definitions have in common is the idea that the outcome of exposure to something potentially
harmful depends on characteristics of the individual or group being exposed. Harm can be
reduced or prevented by decreasing vulnerability. Vulnerability refers, not only to exposure
to harm in the present, but also to the capacity of individuals and groups to recover from
damage and reestablish their livelihoods moving forward (Wisner et al. 2004).
Wisner uses the term disaster to denote “when a significant number of vulnerable
people experience a hazard and suffer severe damage and/or disruption of their livelihood
system in such a way that recovery is unlikely without external aid” (Wisner et al. 2004, 45).
The “pressure and release” model (PAR model), illustrates this understanding of disasters.
According to the PAR model “disaster is a compound function of the natural hazard and the
number of people, characterized by their varying degree of vulnerability to that specific
hazard, who occupy the space and time of exposure to the hazard event” (Wisner et al. 2004,
45). The PAR model is relevant to my study because it distinguishes between hazard and
vulnerability and discusses their relationship, which is fundamental to understanding
contemporary disaster risk reduction.
2.1.2 Crisis, Emergency and Disaster Management
States, societies and individuals have been taking measures to protect themselves
from hazards throughout history. In modern times, this work has been referred to as “risk
management”, “disaster management” and “crisis management”, though these terms lack
clear, universally accepted definitions. Crises are generally characterized as severe and
unexpected threats under circumstances of high uncertainty where there is a need for urgent
decision-making (McConnell and Drennan 2006, 60). Accordingly, “crisis management”
generally refers to organized efforts to make the urgent decisions needed to meet those
threats. Likewise, “disaster management” and “emergency management” refer to responses.
All three terms connote reactive actions to manage a crisis, disaster or emergency.
Prevention, however, is preferable to reaction for the sake of human safety as well as
minimizing financial loss (Gaillard and Mercer 2013). Switching to the term “risk
management” shifts the emphasis away from reaction to events and toward prevention and
preparation. However, it still leaves in place the loaded term “management”, which evokes
the image of top-down structures and a corporate steering model. Using this term makes it all
3Swedish: “De egenskaper eller förhållanden som gör ett samhälle, ett system, eller egendom mottagligt för de skadliga effekterna av en händelse.”
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too easy to do what is politically expedient and focus on natural hazards as the source of
disasters while ignoring the role of underlying vulnerability. (Wisner et al. 2004). Risk
management can then easily become focused on attempting to predict, prevent or protect
against natural hazards through technological, engineered means and fail to tackle the
vulnerability at the root of disasters.
2.1.3 Disaster Risk Reduction (DRR)
A term commonly used in international forums such as the United Nations, is
“disaster risk reduction” (DRR). “Disaster Risk Reduction (DRR) has been proposed as a
systematic mechanism to reduce disaster risks by analysing and managing the causal factors
of disasters including the reduction of vulnerability and improved preparedness for adverse
events” (Djalante 2012). The concept of disaster risk reduction has been widely used for over
a decade to describe a “complex multi-level governance” approach to risk reduction (De
Majo and Olsson 2019). Reducing vulnerability is an explicit and central component of DRR.
The UNISDR writes, “Reducing exposure to hazards, lessening vulnerability of people and
property, wise management of land and the environment, and improving preparedness and
early warning for adverse events are all examples of disaster risk reduction” (United Nations
International Strategy for Disaster Reduction n.d.).
2.1.4 Collaborative Governance
Governance is a concept used to denote decision-making in other forms than the
traditional Weberian state. Governance can be defined in many ways, among them, “a
horizontally organized structure of functional self-regulation encompassing state and non-
state actors bringing about collectively binding decisions without superior authority” (van
Asselt and Renn 2011; Rosenau, Czempiel, and Smith 1992). Governance is a more
pluralistic model of power sharing and decision-making than traditional state government and
bureaucracy. The concept of collaborative governance builds further on that idea in that it
addresses complex, cross-sectoral problems that traditional governance does not (Ansell and
Gash 2008; Bodin and Nohrstedt 2016). Emerson et al. (2011) drawing on the work of Ansell
and Gash, among others, formulate a broad definition of collaborative governance as, “the
processes and structures of public policy decision-making and management that engage
people constructively across the boundaries of public agencies, levels of government, and/or
the public, private and civic spheres in order to carry out a public purpose that could not
otherwise be accomplished” (Emerson, Nabatchi, and Balogh 2012, 2). Other definitions of
collaborative governance require that there be collaboration between the public sector and
non-state stakeholders and specify a certain type of decision-making process (Ansell and
Gash 2008). However, according to Emerson et al.’s definition, collaboration between
different public agencies or levels of government can be considered collaborative governance
and there are no requirements about the process other than that it be constructive.
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I find the Emerson et al. definition of collaborative governance relevant in the context
of risk governance. The importance of horizontal and vertical collaboration within the public
sector to achieve DRR has been discussed. Local DRR takes place in an instructionally
fragmented context (Feiock 2009), where overlapping jurisdictions within the public sector
must collaborate with one another and with public entities. It is not a given that different
public entities have the desire, institutional conditions or resources to cooperate and
collaborate on risk reduction. Emerson et al.’s definition allows focus to be placed on
constructive, cross-boundary decision-making, regardless of which actors are involved. For
that reason, Emerson et al.’s definition guides the understanding of collaborative governance
in this paper. Drawing on the work of Emerson et al. and Gray (1985), the term
“collaboration” in this paper means when two or more partners pool tangible or immaterial
resources to accomplish something they could not have accomplished otherwise.
2.2 Collaborative Governance for DRR
2.2.1 The Sendai Framework for Disaster Risk Reduction
International agreements and institutions recognize and promote the importance of
collaboration and the role of vulnerability in DRR work to a greater extent than national
institutions and policies (Gaillard and Mercer 2013, 94). The Sendai Framework for Disaster
Risk Reduction 2015- 2030 (SFDRR) has been supported by the United Nations Office for
Disaster Risk Reduction (UNISDR) since it was adopted in March 2015 at the Third UN
World Conference. It provides goals, strategies and recommendations for DRR by
addressing “the risk of small-scale and large-scale, frequent and infrequent, sudden and slow-
onset disasters caused by natural or man-made hazards, as well as related environmental,
technological and biological hazards and risks. It aims to guide the multihazard management
of disaster risk in development at all levels as well as within and across all sectors” (United
Nations International Strategy for Disaster Reduction 2015). The Sendai Framework calls
upon governments to actively engage relevant stakeholders in DRR activities. It specifically
names the public, private sector, civil society organizations, academia and the scientific
community as important partners. The priorities and recommendations outlined in the
SFDRR strongly emphasize the ideal of multi-level, all-of-society engagement and are
intended to guide DRR work at the local, national, regional and global level (United Nations
International Strategy for Disaster Reduction 2015). The SFDRR is a powerful document that
sets the norms for priorities and approaches to DRR.
2.2.2 Reasons for Collaboration
In this section I examine what stakeholders stand to gain from collaborating on DRR,
that they could not otherwise have accomplished.
The conditions and circumstances that lead to disasters are complex, uncertain and
involve a broad range of actors. So called “wicked” problems “have to be dealt with in the
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context of great uncertainty with regard to the nature and extent of the risks involved for
individuals and society as a whole” (van Bueren, Klijn, and Koppenjan 2003, 193).
Traditional government bureaucracy is ill-equipped to respond to complex problems that
require dialogue around diverse societal interests and need to engage a wide variety of
stakeholders who make decisions jointly (McGuire and Silvia 2010, 281). Gray (1985) states
that complex problems which affect multiple sectors of society require stakeholders to pool
information and resources (Gray 1985, 931). When collaboration is called for between
stakeholders who are not already part of formally established networks, “traditional
bureaucratic problem-solving methods are maladaptive” (Gray 1985, 932). Gray views crises
and problems that exceed the capacity of a single organization to solve as drivers of
collaboration (Gray 1985, 912) while Emerson et al. view uncertainty as a driver of
collaborative governance, especially when dealing with “’wicked’ societal problems”
(Emerson, Nabatchi, and Balogh 2012, 9). “Uncertainty that cannot be resolved internally can
drive groups to collaborate in order to reduce, diffuse, and share risk” (Emerson, Nabatchi,
and Balogh 2012, 10).
Disasters and their aftermath exceed local communities’ capacity to respond and
recover without access to external tools and resources (Wisner et al. 2004). An effective
emergency response requires cooperation and collaboration with a myriad of different
organizations which have different structures, mandates, purposes and leadership (Drabek
and McEntire 2002). Evacuations, complex rescue operations, avian firefighting or large-
scale debris clearing will likely necessitate collaboration among different public entities,
NGOs, the private sector, and national, regional and international governments and
organizations. This makes cooperation and collaboration necessary for effective DRR
(Gaillard and Mercer 2013, 98), as it improves societies’ capacity to deal with extreme events
(Boin and ’t Hart 2010; Nohrstedt 2015).
Strong DRR requires collaboration to be established both vertically, between local,
regional and state actors, and horizontally, for example between different actors at the local
level (Twigg, 2004). It requires recognizing interdependencies between different entities, at
different levels and across different sectors (McEntire 2007). Local government and public
agencies are instrumental in implementing and enforcing existing laws and regulations,
enacted at the national (and supranational) level, pertaining to DRR. Gaillard and Mercer
(2013) write that poor governance and failure to enforce existing laws and programs is a
significant factor leading to disasters. Gaillard and Mercer (2013), citing the UNISDR, note
that it is often the case that although national action towards DRR has been taken, it has been
undermined because of failure at the local level. When the local level is not properly engaged
and involved, nationally initiated efforts are ineffective. Horizontal participation and
collaboration means engaging all relevant sectors of the local government in DRR as well as
engaging the private sector, NGO’s and the public at large (Gaillard and Mercer 2013, 99).
Collaboration needs to be well established and maintained through “frequent interaction,
including participation in planning and training exercises” (Waugh and Streib 2006, 132).
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DRR calls for institutional conditions that allow collaborative governance to take
place. The relevant stakeholders must be empowered to engage in cross-boundary collective
decision-making. Therefore, ridged governmental structures hamper DRR. “In many
countries DRR policies are handled by the army or civil protection institutions which rely on
military chains of command, treating natural hazards as enemies which should be fought
against” (Gaillard and Mercer 2013, 10). Yet it is the vulnerability that stems from the
unequal distribution of wealth and resources in society that creates the conditions for
disasters (Gaillard and Mercer 2013, 99). Since that vulnerability to hazards is largely
determined by societal power relations, reducing it requires “altering the way power operates
in a society” (Wisner et al. 2004, 7). Initiatives to reduce societal vulnerability are generally
outside of the purview of the military or civil protection agencies. The result is that
collaborative processes for DRR, specifically those focused on reducing vulnerability, are
neglected in favor of prevention and reaction activities that fit into military structures and
institutions better. Military structures are more likely to produce programs to prepare for
hazards and respond to disasters in a top-down and formally organized fashion. Even though
over the past 70 to 80 years, understanding of the need for cooperative and collaborative
processes for DRR has taken place (McGuire and Silvia 2010, 280; Waugh and Streib 2006,
131), command-and-control style, hierarchical frameworks are still the norm in national risk
management policies (Gaillard and Mercer 2013).
Historically, scientific knowledge, gained through formal education, has been favored
over other forms of knowledge relevant to DRR, such as local knowledge gained through
experience (Gaillard and Mercer 2013). National risk reduction work has largely relied on
technological and engineered top-down “solutions” to perceived risks. Some examples of this
are technological early warning systems, dams and levees. Scientific knowledge may be
easier to integrate into hierarchical, top-down structures than local knowledge. National
governments generally rely more heavily on quantitative data than contextual and subjective
information. However, local communities have valuable knowledge about their own needs,
and resources and understand the local context. Gaillard and Mercer (2013) use the example
of traditional folk tales that spread important information about hazards. Folk tales about
tsunamis contributed to community preparedness for the 2004 tsunami. They were a natural,
existing way to disseminate lifesaving information. This type of DRR can be difficult to
measure, report and fit into externally developed structures, institutional frameworks and
laws. On the other hand, scientific knowledge may not produce contextually appropriate
approaches to DRR. In order to make use of local knowledge, it is necessary to engage and
collaborate with “a large array of stakeholders operating across different scales” (Gaillard and
Mercer 2013, 95).
According to the principle of subsidiarity, challenges should be dealt with by the
smallest relevant level of government. Local government is more closely in contact and
dialog with the public than national government (Measham et al. 2011). This makes it an
important part of the puzzle in collaborative DRR. However, it is important to emphasize that
simply relocating responsibility for DRR to the local level is not a solution. Local
communities typically lack the power and resources necessary to reduce their own
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vulnerability. The structures producing vulnerability, such as discrimination and poverty,
exist in a broader context beyond the community itself. Hazards and sources of vulnerability
are not confined within the borders of local jurisdictions (Wisner et al. 2004). Also, local
knowledge and experience will not adequately address emerging risks that the community has
little or no prior experience with.
DRR processes should be “embedded in core organizational processes” (McConnell
and Drennan 2006) and integrated into existing structures, rather than being treated as a
separate, parallel undertaking (Twigg 2004). This means that important DRR work may not
be explicitly labelled as such. The local community may take actions which reduce
vulnerability to hazards while also achieving other goals (Gaillard and Mercer 2013). The
more local you get the more likely it is that DRR work is not explicitly labeled as such, in the
same way that collaboration is less likely to be formalized and more likely to happen
naturally as a result of people knowing one another and interacting informally (MSB 2011).
Clearly there is a strong call for collaborative governance within DRR. Collaboration
is called for because DRR is multi-level, transboundary, uncertain, and complex. It
challenges the existing societal power structures and calls for diverse types of knowledge.
However, collaboration and interdependency bring with them significant governance
challenges and limitations. The next section explores challenges associated with the attributes
of collaborative DRR that have been discussed.
2.2.3 Challenges to Collaborative DRR
Collaboration entails certain risks for the actors involved. Deslatte and Feiock (2018)
define collaboration risks as, “difficulties in coordinating actions, agreeing to a division of
costs, and the potential for parties to defect, renege on agreements or free-ride” (Deslatte and
Feiock 2018, 353). Collaborating can be seen as a way to share risks associated with
uncertain, wicked societal problems (Emerson, Nabatchi, and Balogh 2012). However,
uncertainty is also an obstacle to collaboration. Imperfect and uncertain information about the
costs and benefits of collaborating contribute to collaboration risks (Deslatte and Feiock
2018). As in the classic prisoners-dilemma, imperfect information about what other actors
will do can lead the rational, self-interested individual to make choices that are detrimental to
the group (Ostrom 2015).
Individuals and groups often fail to collaborate even when it would be mutually
beneficial. Proponents of group theory argue that individuals will recognize that they stand to
gain from cooperation and voluntarily cooperate with one another. However, when the
benefits of a collective effort are available to all, individual participants have an incentive to
conserve their own resources and free-ride on the efforts of others (Ostrom 2015, 6). This is
particularly problematic in groups large enough that the absence of an individual’s
contributions goes unnoticed (Francisco 2010; Olson 1965). Overseeing individual’s
contributions and commitments to the collective interest of the group is costly, difficult and
15
ultimately meaningless in the absence of substantive consequences for detrimental behavior
(Ostrom 2015).
Collaborative decision-making can be time and resource intensive (Waugh and Streib
2006, 134). Many public services can be delivered at a lower cost if multiple local
governments collaborate in joint service provision (Blomgren Bingham and O’Leary 2008).
However, there are also costs directly associated with collaboration. The creation of, and
maintenance of self-governing institutions requires the investment of resources (Ostrom
2015). Collaboration requires the allocation of time to be spent on meetings, conferences,
discussions and other forms of coordination and communication. Collaborative processes are
associated with “time and energy costs resulting from the protracted decision-making
process” (Agranoff 2006, 62). Consensus-based and flexible forms of decision-making are
associated with higher decision-making costs than hierarchical and bureaucratic forms of
decision-making (Feiock 2009, 366).
Feiock (2009) studied collective action at the institutional level in the context of
governance in metropolitan areas, investigating the potential of the regional level to provide
necessary structure for effective local collaboration. Drawing on the work of Ostrom (1990)
and others, he developed a framework for understanding institutional collective action.
Collective action problems at the institutional level are related to institutional fragmentation.
“Fragmentation creates diseconomies of scale, positive and negative externalities, and
common property resource problems” (Feiock 2009, 357). At the local level, horizontal
fragmentation refers to having many “general purpose local governments” (Deslatte and
Feiock 2018, 356–57). This requires local governments to collaborate in order to maximize
the efficiency of service provision. Horizontal fragmentation increases the number of
potential collaboration partners to select from but also increases the necessity of
collaborating. Having many potential partners makes the process of seeking out collaboration
and practically collaborating costly. Vertically, collaboration is called for to address the
fragmentation produced by overlap in policy objectives at different levels of government
(Feiock 2009, 358), or what Deslatte and Feiock (2018) later refer to as “the proliferation of
single-purpose districts that overlap municipal governments” (Deslatte and Feiock 2018,
356–57). A third dimension of fragmentation produces functional collective action problems,
arising from the interconnectedness of different services and policy areas (Feiock 2009, 358).
Feiock makes the assumption that individual actors will act according to rational
short-term self-interest unless mitigating institutions are in place to govern collective action
and create the conditions for mutually beneficial collaboration. He argues that incentives and
conditions to establish mitigating institutions are lacking at the local level. He explores the
regional level as a potential venue for mitigating institutions or “tools of regional
governance” to address the institutional fragmentation experienced at the local level (Feiock
2009, 358). The tools Feiock is referring to are governance arrangements, in line with
Ostrom’s recommendations, rather than the hard forms of government regulation, which she
criticized as ineffective. In figure 1, Feiock presents a matrix of regional governance tools
illustrating how they range from “collective multilateral relationships” to “individual bilateral
exchange in networks” on one axis, and from externally enforced to locally embedded on the
16
other axis (Feiock 2009, 359). I find this a useful way of conceptualizing the degree of
formality and local ownership of different collaborative governance arrangements.
Figure 1. Matrix of Regional Governance Tools
(Feiock 2009, 359)
As mentioned above, in many countries, the military or civil defense departments are
responsible for disaster prevention and response. These are generally hierarchical, command-
and-control style organizations. Ridged structures and inflexible bureaucracy can also be a
prominent feature of civil government agencies. As in natural resource management, DRR
work is not effective if compartmentalized into different domains unilaterally managed by
different actors because the domains are interdependent (Ostrom 2015). Waugh and Streib
point out that “noncollegial professions typically do not find open communication and
participation comfortable” (Waugh and Streib 2006, 134). Collaborative decision-making
requires a culture of collaboration to first be established (ibid).
The common characteristics of actors are believed to influence their relationship to
one another. Homophily, as a concept within the social sciences, refers to “the principle that a
contact between similar people occurs at a higher rate than among dissimilar people”
(McPherson, Smith-Lovin, and Cook 2001, 416). The idea of homophily is important to the
study of social network because it explains how and why social clusters of similar individuals
form. “The “homophily hypothesis” predicts that actors are more likely to collaborate with
actors that share some attributes because similarity lowers the threshold for initiating
collaboration” (Nohrstedt and Bodin 2019, 5). Nohrstedt and Bodin (2019) list homophily as
17
one potential endogenous driver of social tie formation in collaborative networks. Likewise, it
implies potential difficulties for heterogeneous actors to form collaborative networks. DRR
calls for collaboration with diverse actors and engagement with diverse types of knowledge
which collaboration between homogenous actors alone cannot achieve.
It is well established that participatory processes are influenced by existing power
relations (Few, Brown, and Tompkins 2007, 53). Participation does not necessarily mean
equal influence, or even any substantive influence (ibid). For example, “community
participation” can be used as a ‘buzzword’ to “clandestinely reinforce existing power
relations at both the local and international levels” (Tozier de la Poterie and Baudoin 2015,
129). Lack of trust between stakeholders can be a significant obstacle to collaborative DRR.
“Governments and scientists still often dismiss the contribution of local communities, while
communities and NGOs are frequently suspicious about governments’ and scientists’
intentions.” (Gaillard and Mercer 2013, 99). The lack of trust can be seen as a manifestation
of imperfect information about the costs and benefits to collaboration. Collaboration take
time to establish. The longevity of a collaborative network depends on “institutionalizing the
social relationships upon which the network is founded” (Imperial et al. 2016, 135).
However, having collaborated once, individuals and organizations have built trust,
relationships and organizational learning that can be redeployed when collaboration is called
for again in the future (Imperial et al. 2016, 142).
Disaster preparedness entails allocating scarce resources towards preparation and
practice for events that have a low probability of occurring (McConnell and Drennan 2006).
This is understandably controversial and preventing a crisis before it happens can be a
thankless task. Few et al. (2007) studied climate change adaptation, which is closely related
to DRR. They conducted a qualitative study with extensive interviews. One of their findings
was that, while people stated that they thought advanced adaptation measures were prudent
on a theoretical level, they still viewed adaptation activities as costly, without any guarantee
that they would prove to be worth the cost later on. Some participants advocated waiting until
hazards became more clearly apparent before attempting to mitigate associated risks. Cost
and uncertainty (as to whether the measures were necessary and effective) made participants
reluctant to support anticipatory adaptation projects (Few, Brown, and Tompkins 2007, 51–
52).
As McConnell and Drennan (2006) point out, the political reward for investing in
successful DRR is generally “limited to the avoidance of flak” (McConnell and Drennan
2006, 63). This can limit the motivation of political actors and private actors alike to set aside
time and resources for DRR work. In the business sector, investing in DRR may not seem
worthwhile from a financial cost-benefit perspective. In the nonprofit sector, there may be
pressure to prioritize activities that interest donors not to mention that reactive programs,
such as emergency assistance, garner more attention than preventative work. The political
reward for investing in robust DRR work can be low. This provides a disincentive for
politically elected representatives to invest in DRR work, because the payoff for them is
small, or even negative when DRR comes at the expense of other public programs (Gaillard
and Mercer 2013).
18
2.2.4 The Theoretical Tension in Practice
This review of themes in existing research shows that there is a strong call for
collaboration in DRR but that there are also relevant obstacles to collaboration. Some central
attributes of DRR, namely complexity, interdependence and institutional fragmentation, are
both reasons collaboration is necessary and obstacles to collaboration. To a large extent, what
makes collaborative DRR meaningful to invest in is also what makes it difficult to achieve.
That tension makes this subject interesting to explore further.
This study takes the first step toward understanding how this tension plays out in the
context of Sweden’s municipalities. Before exploring potential obstacles to collaborative risk
governance in Sweden, we must establish to what extent Sweden’s municipalities are taking a
collaborative governance approach to disaster prevention and preparedness. Based on the
importance of collaboration to successful DRR, I expect that many municipalities engage in
some degree of collaborative governance as part of their disaster prevention and preparation
work. However, due to the challenges discussed, I also expect to see a high number of
municipalities with limited or no reported collaboration. Obstacles to collaboration such as
costs associated with identifying partners and institutional fragmentation should be most
pronounced when first establishing collaboration. Therefore, if municipalities do not
collaborate or report that they have tried unsuccessfully to establish procedures for
collaboration, that would indicate a need for further exploration of this set of obstacles.
Building trust and collaborative norms takes time. Therefore, these themes warrant further
exploration if it appears that collaboration is slowly building over time. If collaborative
partnerships are established, maintained for a period, and then discontinued, that could be
evidence of a different set of challenges. That would be cause for further exploration of
obstacles such as the cost or inconvenience of slower processes of decision-making or
problems with free-riding within ongoing collaborative initiatives.
3 The Swedish Context
Sweden is a parliamentary democracy with a national parliament, 20 regional
(previously county) councils and 290 municipal councils, all of which are publicly elected
(MSB 2018; Sveriges Kommuner och Landsting 2019). The national government oversees
the operation of public agencies and provides the directives that steer them. Examples of
public agencies are the police, the county administrative boards, the Swedish Civil
Contingencies Agency (MSB) and the Swedish Armed Forces.
The regions and municipalities are separate public entities and provide many
important public services. There is not a hierarchical relationship between the local and
regional levels of government. They are self-governing and have jurisdiction over different
public services (Sveriges Kommuner och Landsting n.d.). For example, healthcare is run by
the regional level of government. Emergency preparedness and Rescue Services4, such as the
4 Swedish: Räddningstjänsten
19
fire department, are run at the municipal level (with a few exceptions) (Krisinformation.se
2018) (Lag (2003:778) om skydd mot olyckor). However, municipalities are permitted to
collaborate and establish joint rescue services (3 kap. 12 § LSO). Other examples of services
municipalities are required to provide include primary and secondary education, social
services, infrastructure, water supply, waste management, development planning and
environmental planning (Sveriges Kommuner och Landsting n.d.).
3.1 The Legal Framework
Sweden is in an ongoing process of adapting its civil contingency system to take a
broader, DRR approach to disaster prevention and preparation. Sweden is making efforts to
integrate the ideals and recommendations of the SFDRR into its work with disaster
prevention, mitigation and response. Since 2015, MSB has been the contact point for national
coordination and implementation of the SFDRR (MSB n.d.).
Three foundational principles govern the Swedish civil contingency framework; the
Principle of Responsibility5, the Principle of Proximity6 and the Principle of Normalcy (also
translated as Principle of Equality (MSB 2015))7. According to the principle of responsibility,
whoever is responsible for a function under normal circumstances retains responsibility for
that function during a disruptive event. According to the principle of proximity, disruptive
events should be handled in the geographic area where they occur and by those most closely
affected. According to the principle of normalcy, organizations impacted by a disruptive
event should, to the greatest extent possible, retain their ordinary structure and organization.
Any changes to the ordinary structure of operations should be limited to what is necessary to
manage the situation at hand. (MSB 2018, 25–26).
Any law related to reducing individual and societal vulnerability is relevant to DRR,
therefore the relevant legal framework is very broad. It includes laws regulating development
and construction8, laws regulating education, laws concerning environmental protection, and
much more. One particularly relevant law is Sweden’s Law on Municipal and County
Council Measures Prior to and During Extra-ordinary Events in Peacetime and During
Periods of Heightened Alert (Law 2006:544) (LEH)9. The other is the Law on Protection
from Accidents (Law 2003:778) (LSO)10. From here on they will be referred to by their
Swedish acronyms, LEH and LSO respectively.
LSO will not be the focus of this study. However, it warrants mentioning in more
detail in order to illustrate the importance of the municipal level to Swedish societal risk
management. LSO lists the obligations of private individuals, municipalities and the state
(national level) pertaining to the protection of human lives, health, property and the
environment (1 kap. LSO). For example, according to LSO, individuals who encounter a fire
5 Swedish: ansvarsprincipen 6 Swedish: närhetsprincipen 7 Swedish: likhetsprincipen 8 Plan- och bygglag (2010:900) 9 Lag (2006:544) om kommuners och landstings åtgärder inför och vid extraordinära händelser i fredstid och höjd beredskap (LEH). 10 Lag (2003:778) om skydd mot olyckor (LSO).
20
or accident where somebody’s life is in danger are required, if possible, to warn those in
danger and to call for help (2 kap. 1 § LSO). Responsibility for the majority of preventative
and emergency services is delegated to the municipalities. Municipalities are required to
facilitate individuals fulfilling their responsibilities according to the law (3 kap. 2 § LSO).
Municipalities are also required to work to prevent fires and accidents and to provide rescue
services (3 kap. LSO). Six categories of rescue and emergency services are delegated to the
state rather than the municipality. These are mountain rescue, avian rescue, sea rescue,
environmental sea rescue (i.e. oil spills etc.) search for missing persons and rescue services in
the event of a spill of radioactive material. All other rescue services fall under the jurisdiction
of the municipalities.
LEH requires Swedish municipalities to take measures to reduce their vulnerability
and to ensure they are prepared for events that could otherwise seriously disrupt critical
functions and services. LEH takes an all-hazards approach to contingency planning. The
focus is to some degree on contingency planning and preparation; however, some degree of
prevention and vulnerability reduction is also called for. According to the law, municipalities
must carry out a risk- and vulnerability assessment and establish a plan for the management
of extra-ordinary events (2006:544). MSB has the authority to give further directives on how
the risk analysis and contingency planning is to be carried out. Municipalities are required to
have a local crisis management council that can convene in case of an extra-ordinary event (2
kap. 2 § LEH). The crisis management council can decide to take over other departments’
functions/operations during a crisis if necessary, for the time period necessary (2 kap. 4 §
LEH). Municipalities must strive to assure that actors in the municipality coordinate and
cooperate in planning for and preparing for extra-ordinary events (2 kap. 7 § LEH).
Municipalities should also see to it that crisis management efforts, and information to the
public during crises, is coordinated. The municipality is responsible for seeing to it that
elected and employed municipal staff are trained for their roles in case of an extra-ordinary
event (2 kap. 8 § LEH). The municipalities report what they have done in accordance with
this law to a national agency on a regular basis and provide the national agency with
information during an ongoing event (2 kap. 9 § LEH).
A guiding principle behind the law is that “collaboration is the primary means for
building common capacity for effective action in response to risks and threats” (Nohrstedt
2015). Swedish national agencies encourage collaboration within and between municipalities
as part of planning and preparation for extraordinary events. The municipalities are given
economic incentives to engage in more collaboration (Krisberedskapsmyndigheten and
Svenska Kommunförbundet 2004; Myndigheten för samhällsskydd och beredskap and
Sveriges Kommuner och Landsting 2013). Collaboration outside of the municipalities’
boarders is not mandated by LEH but strongly encouraged by national agencies.
The county administrative boards are responsible for coordinating within their regions
and for coordinating between the municipal and national levels during an extraordinary event.
The county administrative boards are also responsible for managing national and
international funding for DRR (MSB 2018). The government has the overarching
21
responsibility for DRR at the national level, and delegates parts of that responsibility to
public agencies (MSB 2018).The county administrative boards are agencies of the national
government and therefore do not have a political will of their own the way the municipalities
do.
It is clear that LEH and LSO delegate a significant portion of crisis prevention and
preparation responsibility to the municipal level. The municipal level is also responsible for a
wide range of social services, such as education and welfare, closely related to individual and
societal vulnerability from a broader perspective. Therefore, it is highly relevant to study the
municipal level in the Swedish DRR context. The Swedish national legal frameworks
governing risk assessment risk reduction are purposely vague to allow municipalities to adapt
their risk governance work to local conditions (MSB 2011). In fact, municipalities are
explicitly required to adapt their work with risk and vulnerability assessments to their own
needs and local conditions (MSBFS 2015:5). Funding for DRR is available at the national
level, enabling the municipalities to meet the requirements set forth by LEH and LSO (SFS
2003:778; SFS 2006:544).
4 Methods
4.1 Choice of Methods
This descriptive case study makes use of both quantitative and qualitative survey data
which will be described in further detail below. Both interesting quantitative empirical data
on Swedish disaster prevention and preparation, as well as a vast body of literature about
merits and challenges of collaboration in DRR, is available. Through this large N empirical
case study, I bring these two things together to provide an overview of the use of
collaborative governance for disaster risk reduction at the Swedish municipal level.
The municipal level, rather than the national level, is the focus, therefore it should be
understood as a study of many individual units of analysis within one national, legal and
institutional context. I quantitatively explore both macro-level trends and patterns of change
at the individual municipal level in order to describe what collaborative partnerships and
structures look like.
The ten-year time period of the overall study is broken into three shorter time periods
studied individually as described below. These shorter time periods provide limited
information about overall time trends. However, the main purpose of measuring change over
time in this study is methodological. A snapshot of municipalities’ collaboration at a single
point in time could be misleading. It could give the impression that a certain percentage of
municipalities have established collaboration as a consistent part of their organization.
However, if the general trend at the aggregate level is towards more collaboration, but the
individual municipalities’ engagement in collaboration fluctuates, that has different
theoretical implications than if some municipalities always collaborate while others are just
beginning to establish collaborative structures or have no collaborative structures at all. The
aim of this study is to differentiate between municipalities trying out some form of
22
collaboration at some point in time versus incorporating collaborative partnerships as a
consistent part of their work. The four to five-year time periods used are enough to give some
insight into patterns of collaboration in this sense. Studying collaboration at just one point in
time might miss important distinctions that could further inform the theoretical discussion of
drivers and obstacles to collaborative DRR.
Bodin and Nohrstedt (2014) used parts of the same MSB dataset (see Dataset 1
below) in their study titled “Evolutionary Dynamics of Crisis Preparedness Collaboration:
Resources, Turbulence and Network Change in Swedish Municipalities”. They studied
factors influencing change in collaborative network composition and measured network size
as the sum of categories of collaborative partnership using the data in Dataset 1. They used
resource dependency theory (RDT) to study turbulence in network composition and found
that RDT “has limited explanatory value in this case” (Nohrstedt and Bodin 2014, 134).
There is some overlap between their study and this study’s measure of stability in
collaboration in Dataset 1. However, this study focuses on municipalities’ engagement within
individual categories of collaborative partnerships rather than the composition of
municipalities’ collaborative networks, and that measure is only one component of many that
are mapped.
I have measured the stability versus volatility of a municipality’s collaborative
partnership with a given partner by counting the number of times its collaboration status
changed during the time period. For example, if Kalix11 reported collaboration with the police
in 2009, but not in 2010 or 2011, and then reported collaboration with the police again in
2012, they changed collaboration status with that partner twice during the time period (from
yes to no in 2010 and from no to yes in 2012). This shows that Kalix sometimes collaborates
with the police and sometimes does not. The collaborative partnership is labeled unstable.
Stable is operationalized as up to one change. Unstable is operationalized as two or more
changes.
The same method is used to measure the stability of the municipalities’ structures for
collaboration shown in Dataset 2 and the measures of collaboration studied in Dataset 3. If a
municipality states that it has a structure or category of collaboration in place one year and
not the next (or vice-versa) than that counts as one change. The same operationalization of
stable versus unstable is used as for Data Set 1. This measure of stability is not meant to show
whether collaboration is increasing, decreasing or being maintained. It only shows the degree
to which collaboration is stable or volatile within the individual municipalities during the
time periods.
Another presentation of stability over time is provided in appendix A. There, a color-
coded table shows each municipality’s pattern of reported collaboration over time. It shows
whether the municipality had a collaborative partnership or collaborative structure in place
each year. The table differentiates between municipalities that had not yet reported
collaboration during the time period and municipalities that reported collaborative activity
that they later discontinued. The table is large and may be cumbersome to use, however it is
11 Note that this is a fictitious example, not actual data for Kalix
23
included as an appendix for the sake of any visually inclined reader wishing to look at the
results in more detail.
Sweden’s municipalities differ significantly in size, population and demographic
characteristics. They also vary in geological features and climate. There are many potential
ways to group them and explore differences. It would have been very interesting to group the
municipalities by exposure to different types of hazards to see if there were differences in
patterns of collaboration related to exposure. However, that was not possible within the scope
of this study. I wanted, at the very least, to be able to see if there were differences in patterns
of collaboration between rural and urban settings. The size of a municipality’s own
organization can be a factor in collaborative DRR. A larger municipality is more likely to
have specialized employees assigned responsibility for specific tasks, while smaller
municipalities typically have fewer employees with a broader range of responsibilities. In an
urban setting, there are many more potential collaborative partners to choose from. It is
difficult to formulate a clear expectation regarding differences between rural and urban
municipalities in this study, however, both drivers of collaboration and obstacles to
collaboration may vary greatly depending upon the municipalities’ characteristics and setting.
Therefore, this study looks for potential differences between more and less urban
municipalities for exploratory purposes. I focus on identifying possible differences in patterns
for further exploration.
As I worked with the available empirical data, I became better acquainted with its
limitations, which will be discussed in the next section. The survey questions posed to the
municipalities were not formulated with academic research in mind. I have carefully and
systematically selected the most relevant ways to examine the data, taking these limitations
into consideration. There is a significant degree of subjectivity in the data, also discussed
further below. This is one reason I have chosen to examine it descriptively rather than with an
explanatory aim.
The qualitative data section of this study provides some more nuanced information
about potential barriers to collaboration experienced by municipalities, adding depth to the
study. The combined analysis of the quantitative and qualitative survey data provides
important insights into the way the quantitative results should be understood. If this had been
part of a longer research project, I would have selected a sample of municipalities, based on
the quantitative data analysis in this paper, and conducted interviews regarding collaboration
practices to gain further descriptive insight. In the conclusion, I elaborate further on
suggestions for continued research that could build on the foundation of this study.
4.2 The Data
The Swedish Agency for Crisis Preparedness was dissolved in December 2008 and
replaced by the Swedish Civil Contingencies Agency (MSB) in January 2009 (prop.
2007/08:92; SFS 2008:1002). MSB has responsibility for following up on and evaluating the
progress of municipalities’ crisis preparedness efforts. MSB has done this, in part, by
compiling survey data collected annually from Sweden’s 290 municipalities. The surveys
24
include questions about the municipality’s use of national crisis preparedness funding, risk
assessments, contingency planning, training and education, collaboration with other
stakeholders and more. The municipalities have a legal obligation to report to MSB, which
ensures a high response rate. However, which municipal representative completed the survey
in a given municipality and year varies. Typically, the survey is completed by a municipal
civil servant responsible, in some capacity, for safety, security, crisis preparedness or rescue
services within the municipality (Nohrstedt and Bodin 2014).
Sweden has a strong legal framework for public access to information. The Principle
of Public Access12 allows the public to gain information collected by public agencies as long
as the information is not classified for reasons of security or privacy (Regeringskansliet
2015). I was able to request data compiled by MSB regarding the municipalities’ work
pursuant to law SFS 2006:544 and regulations MSBFS 2010:6 and MSBFS 2015:5 for the
time period 2009 to 2018. The advantage of working with existing data compiled by MSB is
that I have access to far more information than I could have collected independently within
the timeframe of this study. The MSB survey provides a large amount of quantitative and
qualitative data collected over a ten-year time period. However, there are also some
disadvantages.
I received access to different parts of the dataset at different times. I received part of
the dataset via a previous research study (Nohrstedt and Bodin 2014) and other parts directly
from the Swedish Civil Contingencies Agency. It took nearly two months to identify and
collect all the relevant raw data. Though the raw dataset contains a vast quantity of truly
interesting information, identifying, sorting and, when necessary, coding, the most relevant
parts took time. Since I am making use of an existing dataset, the survey questions asked
were not tailored to the needs of this study. Unfortunately, there was substantial variation in
the survey questions posed to the municipalities from year to year which required me to
modify my methodological approach to the data. I have put considerable effort into
considering how best to group and analyze the available data for the purposes of this study.
The number of questions in each survey varies from year to year and depends on the
answers the municipalities gave. The survey for 2018, for example, contains over 100
questions. I sorted the survey questions by looking for questions related to collaboration and
then looking among those for questions that were repeated multiple years. I identified three
sets of questions that were both relevant to the purpose of this study and which were posed
during a multi-year time period.
I have broken the data into three datasets covering three time periods during which
comparable questions were asked (see appendix B). Change over time can be studied within
each dataset, with a few limitations which will be discussed below. The reader should be
cautious of drawing direct comparisons between the different datasets, keeping in mind that
they cover different time periods and contain data from different (though largely overlapping)
samples of municipalities, as will be explained below.
12 Swedish: offentlighetsprincipen
25
4.3 Datasets In this section I describe each dataset, its purpose and its unique limitations. The italic
text at the beginning of each section shows the survey question(s) posed to the municipalities.
4.3.1 Dataset 1: Collaborative Partnerships
Which partners does the municipality collaborate with in order to achieve
collaboration and coordination before and during an extraordinary event?
Multiple answers can be selected.
▪ The Police
▪ The County Council
▪ The County
Administrative Board
▪ Other Municipality/ies
▪ The Private Sector
▪ The Swedish Armed
Forces
▪ Religious
Organizations
▪ Other NGOs
▪ Other Organizations
Dataset 1 covers the years 2009-2012, when municipalities were asked which, of a
fixed list of partners, they collaborated with as part of their work on prevention and
preparation for extraordinary events. The exact wording of the questions posed in dataset 1
varies from year to year. In 2009 the municipalities were asked, “Which partners does the
municipality collaborate with, either in crisis management councils, or in other ways?” In
2012 they were instead asked, “Which partners does the municipality collaborate with in
order to achieve collaboration and coordination before and during an extraordinary event?
(for example, a crisis management council, established coordination groups or a similar
structure).” During the years 2009-2012, MSB was following up on the municipalities’ work
according to one set of legally binding guiding documents (SFS 2006:544, MSBFS 2010:6,
(Krisberedskapsmyndigheten and Svenska Kommunförbundet 2004; Myndigheten för
samhällsskydd och beredskap and Sveriges Kommuner och Landsting 2013)13,). The addition
of “to achieve collaboration and coordination…” to the question is not actually changing the
content of the question being posed to the municipalities, it is simply including a more
extensive reference to the legal framework implicitly referred to in 2009. I therefore consider
the questions in Dataset 1 comparable even though the exact wording does change from year
to year. The list of potential collaborative partners the municipalities can select from is the
same for all four years.
13 Swedish: ”Kommunöverenskommelsen” 2004 respektive 2012
26
The list of potential collaborative partners includes a category for “other partners”.
The municipalities have been asked to specify in text which partners they mean. The answers
vary widely and include government agencies, radio and government owned companies such
as the postal service and SOS Alarm. However, many municipalities have used this field to
repeat partners that belong in other categories, such as NGOs and churches. Therefore, I find
this category of limited use as a quantitative measure.
4.3.2 Dataset 2: Structures for Collaboration
Does the municipality have a structure in place for collaboration and
coordination of relevant partners’ preparations for, and actions during an
extraordinary event? (for example, a crisis management council,
established coordination groups or other type of committee).
Dataset 2 covers the years 2010-2014 and consists of data regarding whether the
municipalities had structures in place for collaboration. The formulation of the question is
slightly different in 2010 compared to the subsequent years (see appendix B). It is difficult to
capture the nuance of the change in the Swedish terminology in an English translation14. The
question is followed by a few examples of what MSB has in mind to guide the municipalities
in answering. The examples provided are the same throughout the time period. This is an
indication that the slight change in terminology has not changed the question substantively.
However, the change in terminology should be kept in mind when interpreting the results
from this time period. The year 2010 cannot be considered entirely comparable to the
subsequent years as the change in phrasing could have impacted the municipalities’
interpretation of the question. One example given of having a structure in place is having a
crisis management council. Note that, as mentioned above municipalities are required by law
to have a local crisis management council that can convene in case of an extra-ordinary event
(2 kap. 2 § LEH).
4.3.3 Dataset 2: Qualitative Data Section
Explain why the municipality does not have structures for collaboration
and describe how the municipality is working to fulfill its’ responsibility for
its’ geographic area.
Municipalities that reported that they did not have a structure in place for
collaboration were asked to elaborate as to why. I have compiled the answers, identified eight
themes, and coded the answers accordingly. The categorizations are not exclusive, meaning
one municipality’s answer can contain more than one coded theme. I have examined the
change over time in prominence of the themes and explored possible correlations between
themes and types of municipalities. The themes and analysis of the qualitative data will be
described along with the findings in the results section.
14 Swedish: 2010, “Har kommunen en funktion…”. 2011-, ”Har kommunen former…”
27
4.3.4 Dataset 3: Collaboration Within and Beyond the Municipality’s
Boarders
Answer yes or no:
1. The municipality’s preparations for an extraordinary event have taken
place in collaboration with other municipalities and other partners
outside of the municipality’s own geographic area.
2. The municipality has taken action to enable collaboration among
actors engaged in critical infrastructure provision within the
municipality’s boarders for the purpose of achieving coordination of
preparation for, and measures during, an extraordinary event.
3. The municipality facilitates a collaborative forum that includes
representatives of the municipality and other actors involved in
prevention and management of extraordinary events within the
municipality’s geographic area.
Dataset 3 covers the years 2015-2018. It contains data regarding municipalities’
collaboration with partners within the municipalities’ boundaries and with partners outside of
the municipality. The exact same questions were posed for all the years in the dataset.
However, a big drawback with Dataset 3 is that the questions themselves are vaguer than in
the other two datasets.
The first question can be seen as a measure of municipalities’ choosing to engage in
collaborative activities that are strongly encouraged, but not legally mandated, by national
law and agencies. The yes-or-no answer does not provide information about which specific
partners the municipalities chose to engage with. In the survey, there is a free text box
associated with this question in which the municipalities could provide more details.
However, the type of information they provide there varies. They also make use of
abbreviations and references that would have been impossible to decipher and code within
the scope of this study. The answers to this question should not be interpreted as anything
more or less than they are. They provide a broad picture of the number of municipalities that
engage in cross-boundary collaboration.
As mentioned above, the law LEH states that municipalities must strive to assure that
actors in the municipality coordinate and cooperate in planning for and preparing for extra-
ordinary events (2 kap. 7 § LEH). The second and third questions relate to fulfilling that
obligation. The law does not specifically dictate that the municipalities must carry out the
exact activities specified in the questions, however the legal imperative to engage in the
second two types of collaboration is stronger. They are measures of local, horizontal
collaboration for disaster prevention and preparedness. The third question does not include
any explicit references to what is to be achieved. One could therefore argue that it does not
necessarily measure collaborative governance as such. However, I argue that it can still be
28
included because the implicit purpose of a collaborative forum would be to inform policy and
decision-making or to establish channels of communication for those purposes at a later time.
4.3.5 Terminology in the Survey
The questions posed in the survey are not as clear and concise as is desirable for the
purposes of an academic study, which has some implications for the validity of the study.
Some questions, such as in Dataset 3, refer to multiple aspects of collaboration but with only
one yes-or-no answer. The terminology used in the survey is not clearly defined. The choice
of wording in certain questions changes over time, such as in Dataset 2. The concept “a
structure in place for collaboration and coordination” (in Dataset 2) is never defined, but is
formulated in different ways different years despite the same examples being given.
In the surveys, the municipalities are asked whether they engage in a variety of
categories of collaboration. However, what constitutes collaboration is not defined. I asked
my contact person at MSB if the municipalities had received any instructions or guidelines
for how they should interpret the term “collaborate” when filling out the survey. He
responded that the municipalities had not been given any explicit instructions as to how they
should interpret the term (MSB contact 2019). He mentioned that MSB has published a
document called Common Foundations for Collaboration and Leadership During Disruptions
to Society15. It has been released and updated in different editions, most recently in 2018.
That document contains a description of collaboration in the context of responding to societal
disruptions which states that, “collaboration is the process which, through participants
reaching agreement, accomplishes direction and coordination of available resources” (authors
translation)16 (MSB 2018, 199). However, it specifies that this definition is for the purpose of
that particular publication and therefore is a narrower definition than might otherwise be used
in disaster prevention work. I interpret this to mean that collaboration should be understood
more broadly in the context of disaster risk prevention, preparedness and response and
therefore also in the context of the survey responses this study makes use of.
Collaboration is a contested concept and the way it is defined has far reaching
consequences. One reason MSB might have posed vague questions with room for
interpretation, is that the guiding legislation they are following up on is purposely vague to
allow the municipalities to adapt their work according to their own needs (MSB 2011). In that
spirit, this study makes use of very a broad definition of collaborative governance. However,
the imprecise and subjective nature of the data is one reason this study does not seek to draw
any causal conclusions without further research.
The results of this study say almost nothing about the nature or quality of
collaboration. Further research on that subject is needed. Also, it is important to note that the
survey measured whether municipalities reported that collaboration took place and not
whether collaboration actually took place. The data in this study is valuable in presenting a
15 Swedish: ”Gemensamma grunder för samverkan och ledning vid samhällsstörningar” 16 Swedish: ”Samverkan är den funktion som, genom att aktörer kommer överens, åstadkommer inriktning och
samordning av tillgängliga resurser.”
29
descriptive picture of reported collaboration but the reader should keep in mind that the
individual datapoints contain subjective information rather than objective facts.
4.3.6 Categorization of Municipalities
Since the 1980’s, the Swedish Association of Local Authorities and Regions (SKL)
has published categorizations of Sweden’s municipalities to facilitate the work of
organizations, public agencies and universities (Sveriges Kommuner och Landsting 2017).
The 2011 version used the population size of a municipality as one parameter. It also
included a parameter regarding the percentage of the municipality engaged in industry,
agriculture and forestry respectively. For the 2017 version, SKL did a major revision of the
categories to provide more relevant categories for today’s society. The 2017 version groups
Sweden’s municipalities based on ten parameters. These include population size, population
of the largest urban area, percentage of the population that commutes in to, and out of, the
municipality respectively, as well as revenue in several economic sectors. These parameters
are believed to provide information about commerce, employment opportunities, available
work force and the availability of services in a municipality. Proximity to urban centers, even
when they are outside of the municipalities’ own geographic area, is an important factor in
determining other characteristics of a municipality that have not been a focus of earlier
categorizations (Sveriges Kommuner och Landsting 2017). SKL notes that the choice of
parameters used means that municipalities in the same group may still differ significantly in
terms of demography, level of education, average income and other socioeconomic variables
(Sveriges Kommuner och Landsting 2017). However, the SKL data is useful to this study
because it makes a more nuanced distinction between urban and rural municipalities than
simply using population. Including commuting patterns and economic opportunities provides
some insight into the resources, interdependencies and number of actors present in a
municipality, which is important to this study.
The data used to produce the 2017 SKL categorization of municipalities was collected
2014 (Sveriges Kommuner och Landsting 2017), in the middle of the time period of this
study. The SKL categorization divides Sweden’s municipalities into three main categories
and a total of nine subcategories. SKL notes that some municipalities fell close to the
threshold between categories, which is to be expected. This study only makes use of the three
main categories, not the nine subcategories, as it was determined that using all nine categories
was not meaningful for the purpose of this study. The number of communities close to the
threshold of the three main categories relative to the data sample as a whole is judged to be
insignificant to the results of this study. For the sake of the reader, I will refer to the
categories as group A, urban municipalities, group B, semi-urban municipalities, and group
C, rural municipalities. The definition of each group can be found in appendix D.
4.3.7 Missing Data
Some data is missing from each dataset. In most cases, it is not clear why data is
missing for certain municipalities and time periods. In any case where data was missing for a
given municipality for any year during the dataset time period, that municipality has been
30
excluded from that time period. For that reason, 14 municipalities were excluded from
Dataset 1 (2009-2012), 15 municipalities are excluded from Dataset 2 (2010-2014), and 28
municipalities are excluded from Dataset 3 (2015-2018). See appendix C for a list of the
excluded municipalities. The purpose of eliminating municipalities with missing data is to
make the data within each dataset comparable, enabling the study of change over time within
the datasets. It is possible that the missing municipalities have some common characteristic
and that excluding them impacts the results of the study. However, even in Dataset 3, where
28 municipalities are excluded, the excluded municipalities make up less than 10% of the
total population. A sample consisting of over 90% of the population being studied is still
excellent. The excluded municipalities vary in size and geographic location and do not share
any obvious characteristic that could be expected to impact the results of this descriptive
study.
4.3.8 Language
The survey questions and answers are in Swedish, as are all the agency names, laws
and other Swedish terminology relevant to this study. Whenever text is translated there is a
risk of mistranslation and misinterpretation. I am a native English and Swedish speaker with
experience from Swedish public administration. Therefore, I have chosen to translate the
survey questions, as well as other Swedish terminology used in this paper, myself wherever
official English translations are not provided. I have included an appendix with all translated
text in the original Swedish alongside my English translations for the sake of transparency.
See appendix E for further information on translation.
5 Analysis
In this section I present the results of the data analysis and use them to answer the
research questions posed in the introduction. I have combined the presentation of the data and
discussion of the results in the same section for the convenience of the reader, so that figures
and discussion of their implications appear side by side. This section answers the overarching
research question: To what extent do Sweden’s municipalities collaborate with other
stakeholders on disaster risk reduction?
5.1 Collaborative Partnerships
In this first subsection, I answer the sub-question: Which partners do the
municipalities collaborate with? I also examine whether there are any time trends or
differences between municipalities depending on their degree of urbanization when it comes
to collaborative partnerships.
5.1.1 Partnerships 2009 to 2012
During the time period 2009 to 2012 (Dataset 1), the whole sample of 276
municipalities reported collaborating at least once with at least one partner. At least 97% of
the sample reported collaborating with at least one partner in any given year. In other words,
31
during any given year, the vast majority of Sweden’s municipalities reported that they
engaged in some form of collaborative partnership for disaster prevention and preparation.
Figure 2. Collaboration by Category of Partner and Year
The percentage of municipalities that reported collaboration with a public sector partner,
with a religious organization or other NGO or with a private sector partner during the years
2009 to 2012.
The category referred to as public sector in the figure 2 includes the five public sector
actors listed in the survey; the police, the county council, the county administrative board,
other municipalities and the Swedish Armed Forces. Likewise, religious organizations and
other NGOs are grouped together. Figure 2 shows that in any given year, the vast majority of
the municipalities in the sample collaborated with at least one partner in the public sector.
Collaboration with religious organization or other NGOs was somewhat lower, while
collaboration with private sector partners was much lower.
Figure 3 shows the municipalities’ reported collaboration with the five individual
actors that make up the public sector category. Within the public sector, there are high rates
of reported collaboration with the police, county administrative boards and county councils.
Collaboration with the Swedish Armed Forces was reportedly much lower.
Figure 3. Public Sector Collaboration 2009-2012
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
Police County Council County AdministrativeBoard
Other Municipality/iesSwedish Armed Forces
Public Sector Collaboration 2009-2012
2009 2010 2011 2012
COLLABORATION BY CATEGORY OF PARTNER AND YEAR
Public sector Religious
org./NGO
Private sector
2009 97% 85% 56%
2010 98% 89% 59%
2011 96% 86% 61%
2012 99% 89% 64%
32
It is not unexpected according to the theory of homophily, that municipalities, being
public sector actors themselves, would more easily and more readily collaborate with other
public sector actors. However, it is interesting that reported collaboration with other
municipalities was lower than with the police until 2012, given that the municipalities have
the same nationally mandated obligation to engage in disaster prevention and preparation and
are subject to the same national financial incentives to collaborate. On the other hand,
collaboration between municipalities is steadily increasing. Inter-municipality collaboration,
therefore, could be an interesting category to explore further to learn more about drivers of
increasing collaboration.
It is interesting that collaboration with the Swedish Armed Forces was lower than
with the other categories of partners. The hierarchical, command-and-control nature of the
military was discussed in the theory section as a possible obstacle to participation in
collaborative governance. However, the Swedish Armed Forces may also have a different
degree of relevance as a collaborative partner to different municipalities. To better understand
patterns of collaboration with the Armed Forces, it is interesting to know what percentage of
municipalities ever engage with them as a partner, which will be discussed below.
5.1.2 Collaborative Partnerships 2009 to 2012 by Groups of Municipalities
Next, I organized the municipalities into groups A (urban), B (semi-urban), and C
(rural) in order to look for trends and patterns in reported partnerships.
First, I looked more closely at reported collaboration with the public sector
(aggregated), religious organizations/NGOs (aggregated) and the private sector respectively
to see if there were any differences in the degree of collaboration associated with the
municipalities’ degree of urbanization (i.e. Group A,B or C). There were no meaningful
differences between the three groups of municipalities associated with collaboration with the
public sector (as an aggregated category) or religious organizations/NGOs (as an aggregated
category) (see appendix F). Figure 4 shows differences in the extent to which the different
municipal groups reported collaboration with the private sector category. Although there are
differences, there is no identifiable trend.
33
Figure 4. Private Sector Collaboration 2009-2012
Reported collaboration with the private sector 2009-2012 by group (group A-urban, group
B- semi-urban, group C-rural) as a percentage of the group (i.e. the percentage of group A
that collaborated with the private sector in 2009, etc.) The associated data table can be found
in Appendix F.
I also analyzed the municipal groups’ reported collaboration with each of the five
public sector actors individually. Figure 5 shows no clear trends or patterns emerged
differentiating the municipal groups from one another with one exception. The percentage of
municipalities in group A (urban) that collaborated with the police in any given year was
higher than the percentage of municipalities in groups B and C whose levels of collaboration
were similar to each other.
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
2009 2010 2011 2012
Private Sector Collaboration 2009-2012
Group A Group B Group C
34
Police County Council
Group A Group B Group C Group A Group B Group C
2009 95.2% 92.4% 92.0% 2009 76.2% 86.7% 87.6%
2010 97.6% 89.5% 91.0% 2010 78.6% 83.8% 86.8%
2011 97.6% 86.7% 91.0% 2011 85.7% 83.8% 90.7%
2012 97.6% 93.3% 91.0% 2012 76.2% 89.5% 88.4%
County Administrative Board Swedish Armed Forces
Group A Group B Group C Group A Group B Group C
2009 90.5% 82.9% 81.4% 2009 57.1% 56.2% 51.2%
2010 92.9% 95.2% 92.2% 2010 47.6% 64.8% 53.5%
2011 97.6% 92.4% 96.1% 2011 54.8% 68.6% 62.8%
2012 95.2% 96.2% 97.7% 2012 57.1% 63.8% 64.3%
Other Municipalities
Group A Group B Group C 2009 78.6% 73.3% 77.5% 2010 83.3% 83.8% 89.1% 2011 92.9% 87.6% 89.9% 2012 90.5% 95.2% 94.6%
Figure 5. Public Sector Collaboration by Group
5.1.3 Stability of Collaborative Partnerships 2009 to 2012
Next, I analyzed the stability of the reported collaborative partnerships. Figure 6
shows the stability of collaborative partnerships over the 2009-2012 time period. It provides
some interesting insight to patterns that were not apparent in figures 2 and 3.
Figure 6. Stability of Collaborative Partnerships
Each year during the time period, at least 80% of the municipalities reported
collaboration with a county council. However, only 67% of the municipalities consistently
1% 3% 0% 2%
17%13%
5%
15%
78%
67%
76%
66%
34%29%
54%
40%
9%
15% 17%22%
29%
32%
22%
29%
11% 12%6% 8%
18% 20%16% 14%
1% 3% 0% 1% 3%6%
3% 3%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Police County Council County AdminBoard
OtherMunicipalities
Swedish ArmedForces
Private Sector Religious Org. NGOs
Stability of Collaborative Partnerships
Never Always 1 Change 2 Changes 3 Changes
35
collaborated with a county council every year during the time period. 15% of municipalities
had an unstable collaboration with a county council, meaning they stopped or started
collaborating with a county council at least twice during the time period. Only 3% of
municipalities never engaged with a county council. This illustrates the importance of the
stability measurement. Based on the annual percentage of reported collaboration, I might
have made the incorrect assumption that roughly 80% of municipalities consistently engaged
with county councils while roughly 20% did not. Instead, almost all the municipalities (97%)
tried out some collaboration with a county council, yet only 67% were consistent with their
collaboration.
As I have already shown, 56 to 64% of municipalities reported collaboration with the
private sector in any given year. Figure 6 shows that only 29% of the municipalities
collaborated with the private sector every year throughout the 2009 to 2012 time period. In
other words, a relatively low percentage of municipalities consistently collaborated with the
private sector over the four-year period. 13% of the municipalities never reported
collaborating with the private sector and 26% of the municipalities engaged in unstable
collaboration with the private sector. I find that noteworthy as well. As with the county
councils, these findings point to a very different pattern of collaboration than if it had been
the same core group of municipalities that collaborated with the private sector every year.
Instead, these findings show that 87% of municipalities tried out some collaboration with the
private sector during the time period. The individual municipalities’ collaboration with the
private sector is volatile over time. Collaboration with the private sector was the most volatile
of the categories in the survey.
The volatility of collaboration with the Swedish Armed Forces is also relatively high.
It comes in second place, with 21% of municipalities engaging in a volatile pattern of
collaboration. 19% of municipalities have volatile collaboration with religious organizations.
17% have volatile collaboration with other NGOs.
As shown by figure 6, 17% of municipalities in the sample never reported any
collaboration with the Swedish Armed Forces, the highest percentage of nonengagement for
any of the partners. NGOs were a close second at 15%, followed by the private sector at 13%.
I think it is noteworthy that only 5% of the municipalities never engaged in collaboration
with a religious organization during the time period. The overwhelming majority of
municipalities engaged in collaboration at some point with a county council, county
administrative board, other municipalities, the police and religious organizations.
It is noteworthy that collaboration with private sector actors is comparatively low and
unstable. The public sector plays a central role in many critical societal functions such as
telecommunications, food distribution, and energy provision. The public sector arguably has
some role in critical societal service provision in all municipalities. However, public sector
actors may also be those most dissimilar in organization and structure to the municipalities.
36
5.1.4 Stability of Collaborative Partnerships 2009 to 2012 by Groups of
Municipalities
I used the same measure of stability shown in figure 6 to analyze the municipalities by
group (A, B and C) separately and compared the results (see appendix F). I did not identify
any notable differences in patterns and trends between the three groups (urban, semi-urban
and rural).
5.1.5 Collaboration Outside of the Municipalities’ Geographic Area 2015
to 2018
During the time period 2015 to 2018, the municipalities were asked if their
preparations for an extraordinary event included collaboration with other municipalities and
other partners outside of the municipality’s own geographic area. Figure 7 shows the results.
Figure 7. Collaboration Beyond Municipality
Municipalities answering yes to this question could be referring to collaboration with
other municipalities, county councils, county administrative boards or others, taking place
bilaterally or in, for example, multilateral regional collaboration groups. At least 96% of the
sample reported that they had engaged in collaboration with other municipalities or some
other partner outside of the municipality’s own geographic area in any given year during the
2015-2018 time period. As figure 8 shows, all of the municipalities in the sample answered
“yes” to the question at least once during the time period. Over 90% (242 municipalities)
answered “yes” every year.
252
260 259256
248
250
252
254
256
258
260
262
70.0%
75.0%
80.0%
85.0%
90.0%
95.0%
100.0%
2015 2016 2017 2018
Collaboration Beyond Municipality
37
Number of municipalities that
answered “yes”… (2015-2018)
Never 0
Always 242
1 Change 14
2 Changes 6
3 Changes 0
Figure 8. Municipalities Collaborating with Partners Outside of Their Geographic Area
Nine municipalities (note, number not percent) answered “no” the first year this
survey question was posed but “yes” all subsequent years (see appendix A). That leaves only
eleven municipalities that changed their answer from “yes” to “no” during the time period. In
other words, nearly all the municipalities in the sample (96%) consistently answered “yes” to
this question after 2015. The eleven municipalities who changed their answer from “yes” to
“no” at some point included municipalities from all three of the groups of municipalities
(urban, semi-urban and rural) (see appendix A).
The analysis of this data shows that a high number of municipalities consistently
report that their preparations for an extraordinary event included collaboration with other
municipalities and other partners outside of the municipality’s own geographic area during
the 2015 to 2018 time period.
5.2 Structures in Place for Collaboration
In this subsection, I answer the sub-question:
To what extent do the municipalities have collaborative governance structures in
place?
I also examine whether there are any time trends or differences between
municipalities depending on their degree of urbanization when it comes to collaborative
governance structures.
5.2.1 Structures in Place for Collaboration 2010 to 2014
During the years 2010 to 2014, the municipalities answered some variation of the
question, “Does the municipality have a structure in place for collaboration and coordination
of relevant partners’ preparations for, and actions during an extraordinary event? (for
example, a crisis management council, established coordination groups or other type of
committee).” Figure 9 shows that the percentage of municipalities who answered that they
have a structure in place increased during the time period. It should be kept in mind that it is
possible that the large jump that took place between 2010 and 2011 is related to the
reformulating of the question in 2011. By 2014, only 6% of municipalities answered that they
did not have a structure in place for collaboration.
38
Figure 9. Municipalities with a Structure in Place
5.2.2 Structures in Place for Collaboration 2010 to 2014 by Groups of
Municipalities
Figure 10 shows the percentage of municipalities in each of the municipality groups
(urban, semi-urban and rural) who reportedly did not have a structure in place. To properly
interpret this figure, it is important to remember that the groups are not equal in size. There
are 43 urban municipalities, 99 semi-urban municipalities and 132 rural municipalities. The
figure shows the percentage of municipalities in the group answering “no”, to facilitate
comparison between the groups. The numbers above each bar show the actual number of
municipalities from that group that answered “no”.
Figure 10. No Structure in Place, Percentage of Group
Figure 10 shows a similar overall trend in all three groups. By 2014, only 17 of the
municipalities in the sample (274 of Sweden’s 290 municipalities) answered that they did not
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2011 2012 2013 2014
Municipalities With a Structure in Place
8
56
2
0
18
9
13 14
6
43
2022
811
0
5
10
15
20
25
30
35
40
45
50
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
2010 2011 2012 2013 2014
No Structure in Place, Percentage of Group
Group A Group B Group C
39
have a structure for collaboration in place. Five municipalities answered no to the question all
five years. The five municipalities are in different regions but geographically near one
another. One of them is in Group B, semi-urban, and four are in Group C, rural.
5.2.3 Stability of Structures in Place for Collaboration 2010 to 2014
Looking at all the municipalities in the sample together, shown in figure 11, 58
municipalities, or 21% answered the question differently once during the time period. In
other words, they went from saying they had a structure in place to saying they did not or
vice versa. Of those 58 municipalities that changed their answer once, 52 of them changed
their answer from no to yes, showing a strong trend towards establishing the type of
structures referred to in the question. Fewer municipalities, 33 or 12% of the sample, gave a
different answer more than once during the time period.
Figure 11. Stability
Of the six municipalities who changed their answer from “yes” to “no”, thereby
moving against the overall trend, four of them changed in 2014. Since we do not know what
happened subsequent years, it is difficult to say much about what pattern they represent. The
remaining two municipalities reported that they had structures for collaboration in place in
2010 but not any of the subsequent years.
5.2.4 Stability of Structures in Place for Collaboration 2010 to 2014 by
Groups of Municipalities
Next, I once again organized the municipalities by group (urban, semi-urban and
rural) and looked at the stability of reported structures for collaboration. There was no
noteworthy difference between the stability of structures for collaboration between the
different groups (see appendix F).
5 178 58 24 8 1
1.8%
65.0%
21.2%
8.8%
2.9% 0.4%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
0
20
40
60
80
100
120
140
160
180
200
never always 1 change 2 changes 3 changes 4 changes
Stability
40
5.2.5 Structures in Place for Collaboration 2015 to 2018
During the years 2015 to 2018, the municipalities were asked to answer “yes” or “no”
to the following two statements.
“The municipality has taken action to enable collaboration among actors
engaged in critical infrastructure provision within the municipality’s
boarders for the purpose of achieving coordination of preparation for, and
measures during, an extraordinary event.”
“The municipality facilitates a collaborative forum that includes
representatives of the municipality and other actors involved in prevention
and management of extraordinary events within the municipality’s
geographic area.”
In this section, I will abbreviate the first statement as, “enabled collaboration on
critical infrastructure provision” and the second as, “facilitated a collaborative forum”.
Figure 12 shows that approximately 80% of municipalities reported enabling
collaboration on critical infrastructure provision each year.
Figure 12. Enabled Collaboration on Critical Infrastructure Provision
Figure 13 shows the percentage of municipalities within each group (urban, semi-
urban and rural) that enabled collaboration on critical infrastructure provision each year. The
urban group, Group A, reported enabling collaboration at a slightly higher rate than the other
two groups. There is relatively little change over time in the data, except for an upward trend
in Group C.
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
2015 2016 2017 2018
Enabled Collaboration on Critical Infrastructure Provision
41
Figure 13. Enabled Collaboration on Critical Infrastructure Provision: By Group as
Percentage of Group
As shown in figure 14, approximately 70% of municipalities reported each year that
they facilitated a collaborative forum within their municipality.
Figure 14. Facilitated a Collaborative Forum
Figure 15 shows that Group A reported facilitating a collaborative forum at a slightly
higher rate than the other two groups. There is little change over time in the percentage of
municipalities within each group who answered the question positively.
3031 31
29
82 81 82 8191
100 104 104
0
50
100
150
200
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
2015 2015 2015 2015
Enabled Collaboration on Critical Infrastructure Provision: By Group as Percentage of Group
Group A Group B Group C
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
2015 2016 2017 2018
Facilitated a Collaborative Forum
42
Figure 15. Facilitated a Collaborative Forum by Group as Percentage of Group
5.2.6 Stability of Structures in Place for Collaboration 2015 to 2018
As figure 16 shows, only 6% of the municipalities in the sample never reported
enabling collaboration on critical infrastructure provision during the time period, meaning
that 94 % did at some point during the time period. Only approximately 7% reported enabling
collaboration on critical infrastructure provision in a volatile pattern over the time period.
Figure 16. Stability: Infrastructure
Compared to the question above, fewer municipalities ever reported facilitating a
collaborative forum. As figure 17 shows, approximately 11% of the municipalities in the
sample never reported facilitating a collaborative forum within their municipality. Of the
89% that did at some point report facilitating a collaborative forum, 8% did so in a volatile
pattern.
Stability: Facilitated a collaborative forum
Never 10.7% Always 49.6%
1 Change 31.3% 2 Changes 7.3% 3 Changes 1.1%
Figure 17. Stability: Collaborative Forum
25 25
28 27
7265
73 7284 8593 93
0
20
40
60
80
100
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
2015 2015 2015 2015
Facilitated a Collaborative Forum by Group as Percentage of Group
Group A Group B Group C
Stability: enabled collaboration on critical infrastructure provision
Never 6.1% Always 64.1%
1 Change 23.3% 2 Changes 6.5% 3 Changes 0.0%
43
This analysis shows that a higher percentage of municipalities consistently reported
enabling collaboration on critical infrastructure provision than facilitating a collaborative
forum. The percentage of municipalities that reported that they engaged in these activities
each year did not increase or decrease in any noteworthy way during the time period.
5.3 Text Analysis: Obstacles to Establishing Collaborative
Governance Structures, 2010 to 2014
In this subsection, I make use of qualitative data to answer the sub-question:
What hinders the municipalities from having collaborative governance structures in
place?
Figure 18 shows the overall percentage of municipalities reporting that they did not
have a structure in place for collaboration (discussed above).
Figure 18. Municipalities with No Structure in Place
To provide an overview of the free text answers given by the municipalities, I first read
through all the data and made a list of common themes. I identified eight categories of
responses and coded each municipality’s answer accordingly.
Dataset 2: Coding of themes in text answers
1. Informal structures are used (we know each other, informal network etc.)
2. Other existing structures are used (an existing regional group, an existing
collaborative group established for another purpose etc.)
3. Lack of resources (money, time etc.)
4. Working on putting a structure in place/coming soon
5. Partner-related reason (lack of interest from partners, could not identify
partners etc.)
0%
5%
10%
15%
20%
25%
30%
2010 2011 2012 2013 2014
Municipalities with No Structure in Place, 2010-2014
44
6. A practical/administrative obstacle (change of staff, absence of a formal
decision, internal reorganization etc.)
7. Other
8. The answer does not provide any information (simply restating the question,
no reason given, blank etc.)
Multiple themes can be included in one text answer. Therefore, each municipality’s
response is coded according to all the identified themes in the text. This means a single
municipality’s response can count towards more than one category. It was not possible to
create a short but meaningful list of themes that encompassed every single text answer in the
dataset. Therefore, there is an “other” category. However, only 15 responses are coded
“other” (8 in 2010, 6 in 2011, none in 2012 or 2013). For a table showing the presence of
each theme by year, see appendix F.
Three themes emerged as dominant. They are (1) informal structures are used, (2)
other existing structures are used and (4) working on putting a structure in place. Figure 19
shows that of the municipalities who reported that they did not have a structure in place, at
least 40% each year reported in their text answer that they had informal structures in place or
made use of some other existing group for collaboration.
Informal or other existing structures in place
2010 2011 2012 2013 2014
Number 25 22 34 19 10
Percent 40% 65% 83% 83% 59%
Number of municipalities who reported having informal or other existing structures in place
for collaboration followed by what percentage of the total group of “no structure in place”
they make up.
Figure 19. Informal or Other Existing Structures in Place
This means that the majority of municipalities (except in 2010) who report not having a
structure in place for collaboration in fact report having access to informal structures or
existing groups for collaboration.
The other dominant theme in the text responses was that structures were not in place
yet but would be soon. Figure 20 shows the number and percentage of municipalities whose
answers contained references to putting structures in place in the future.
45
A structure will be in place soon
2010 2011 2012 2013 2014
Number 25 16 12 9 6
Percent 36% 47% 29% 38% 35%
Number of municipalities reporting that they expected to have a structure in place for
collaboration soon, followed by what percentage of the total group of “no structure in place”
they make up.
Figure 20. Structure Coming Soon
I was interested to know if municipalities that wrote that they would have structures in
place for collaboration soon went on to report structures in place in subsequent years. I found
that they mostly did. Of the 25 municipalities that reported that they did not have a structure
in place in 2010 but would soon, only four reported that they did not have a structure in place
again the next year. Of the 16 municipalities that reported that they did not have a structure in
place in 2011 but would soon, one reported that it still did not have a structure in place the
following year. Of the 12 municipalities in 2012, two still did not report a structure in place
the following year. Finally, of the 9 municipalities in 2013, only one reported that it did not
have a structure in place in 2014.
Figure 21 shows that the vast majority of municipalities who reported that they did
not have a structure for collaboration in place wrote that they had informal structures in place,
made use of other existing groups or that they would have a structure in place soon.
Informal/other structure in place, or structure coming
soon
2010 2011 2012 2013 2014
Number 42 30 37 23 12
Percent 61% 88% 90% 96% 71%
Figure 21. Other Structure or Coming Soon
Without this information, one might have assumed that municipalities that reported
that they did not have a structure for collaboration in place lacked an interest in collaborating
or were faced with some other obstacle preventing collaboration. However, the qualitative
data paints a different picture. It indicates that many municipalities without formal structures
in place rely on informal structures or make use of other existing groups. Others are working
toward putting structures in place, and they mostly report having succeeded in subsequent
years.
6 Summary and Conclusions
Collaboration is important to successful DRR. That message comes across loud and
clear in the theoretical literature, in international norm-setting documents like the Sendai
Framework, and in the legal framework surrounding disaster prevention and preparedness in
Sweden. As has been described, Sweden’s principles of responsibility, proximity and
46
normalcy are in line with international recommendations that DRR be undertaken within
existing institutional structures. Significant responsibility for disaster prevention and response
is delegated to the municipal level. Therefore, the basic institutional conditions are in place
for engagement at the local level in DRR.
Given the strong imperative to collaborate, I sought to explore the extent of
collaboration taking place at the Swedish municipal level. I expected to find a high number of
municipalities engaged in some form of collaboration, but also many municipalities not
collaborating due to a broad range of potential obstacles. I did not find the group of non-
collaborating municipalities that I expected to find. The results show that all of Sweden’s
municipalities reported engaging in some form of collaboration related to disaster prevention
and preparedness during the time period studied.
Clear patterns emerged showing which categories of actors the municipalities
collaborated with and how stable their collaboration was. During the 2009 to 2012 time
period, collaboration between municipalities steadily increased. Reported collaboration with
the police was high, as was collaboration with regional public sector actors (county councils
and county administrative boards). Though it is interesting to see who the municipalities
reported collaborating with, that information is limited because the exact nature of that
collaboration is unknown. In many ways it is more interesting to make note of who the
municipalities explicitly do not collaborate with, because reporting no collaboration is a less
ambiguous statement. Collaboration with the private sector was notably lower than with the
public sector. Among the municipalities that did engage with the private sector, many did not
engage consistently from year to year. The pattern of collaboration was volatile. A similar
pattern was identified regarding collaboration with the Swedish Armed Forces. Lower
collaboration with the Swedish Armed Forces than with other public actors could be related
to the cultural and structural obstacles discussed in the theory section. However, the police
are generally also associated with hierarchical, command-and-control structures, and they
were one of the most popular collaborative partners.
Based on the theoretical literature, I expected scarce resources and costs of
collaborating to come up more often as an obstacle to collaboration in the qualitative data.
While limited resources was one theme in the answers, is was not the most prominent. The
data indicates that the majority of municipalities that did not report a structure in place for
collaboration had relied on more informal networks of collaboration or already existing
groups or were in the process of putting structures in place. Those that reported that they
would have a structure in place soon did, in fact, report having a structure in place in later
years. Only a handful named obstacles to collaboration that they did not foresee overcoming
soon.
I expected more noticeable differences between the urban and rural categories of
municipalities based on the theoretical literature on fragmentation (costs associated with
identifying partners), trust and collaborative culture. There were only small differences
between urban, semi-urban and rural municipalities in certain measures of collaboration, but
not any noteworthy overall differences between them in patterns of collaboration.
47
6.1 Themes and Patterns that Warrant Further Exploration
6.1.1 Volatility of Partnerships
The identified volatility of certain collaborative partnerships warrants further
exploration. Engaging in volatile collaboration versus always or never engaging in
collaboration has different implications for the obstacles to collaboration discussed in the
theory section. Establishing collaborative governance structures requires an initial investment
of resources (Ostrom 2015). It would be meaningful to explore why municipalities do not
maintain a collaborative partnership once they have invested in establishing collaboration,
presumably in response to some driving force. It could be, as Imperial et al. (2016) argue, that
the relationship, once established, can be dormant when not needed and then redeployed
when it becomes relevant again. On the other hand, volatility could be a sign of obstacles to
maintaining collaboration over time, such as high costs associated with collective decision
making. Further exploration of the reasons behind the municipalities’ volatile collaborative
partnerships is needed.
6.1.2 Municipalities in the Role of Facilitators
The survey questions asked about the municipalities in two roles. On the one hand,
the municipalities were asked questions about collaborative partnerships they engaged in as
part of their disaster prevention and preparedness work. On the other hand, the municipalities
were asked about the work they have done to bring other actors together to collaborate with
one another on disaster prevention and preparedness. Many municipalities reported taking
steps to enable collaboration among actors engaged in critical infrastructure provision within
the municipality’s boarders for the purpose of achieving coordination of preparation for, and
measures during, an extraordinary event. Somewhat fewer reported having facilitated a
collaborative forum that includes representatives of the municipality and other actors
involved in prevention and management of extraordinary events within the municipality’s
geographic area.
It would be interesting to delve more deeply into the municipality’s role as a
facilitator of collaboration between other local actors. The municipalities generally reported
more collaboration vertically, with public actors at the regional level and national agencies,
than horizontally, with the public sector, NGOs and churches. It would be interesting to study
the municipalities taking on the role Feiock describes for regional actors, setting the
framework and acting as a third-party mechanism enforcing or encouraging other actors’
collaboration within the municipality.
6.1.3 Mandated Versus Voluntary Collaboration
Municipalities have a legal obligation under LEH to strive to assure that actors in the
municipality coordinate and cooperate in planning for and preparing for extraordinary events
(2 kap. 7 § LEH). Collaboration outside of the municipalities’ boarders, on the other hand, is
not mandated by LEH, though it is strongly encouraged in other ways. Nonetheless, the data
indicated that collaboration with other municipalities is on the rise. A high percentage of
municipalities reported collaboration with other municipalities and other partners outside of
the municipality’s own geographic area. Not all municipalities reported having a structure in
48
place for collaboration and coordination despite the municipalities’ legal obligations in that
area. It would be interesting to further explore potential differences in patterns of engagement
between mandated forms of collaboration and more voluntary types of collaboration.
6.1.4 Bilateral Versus Multilateral Collaboration
The results of the qualitative section illustrate that collaborative constellations range
from informal and interpersonal networks to more formally organized structures. Many
municipalities made references to collaborating through existing structures rather than putting
their own collaborative structures in place. It would be interesting to further explore the
extent of bilateral versus multilateral collaboration that the municipalities engage in, and the
implications. Making use of existing structures for collaboration on disaster prevention and
preparation makes sense for the sake of avoiding a proliferation of parallel structures.
Integrating disaster prevention and preparation work into existing multilateral collaboration
structures could reduce many of the collaboration costs noted in the theory section. It would
be worthwhile to know if the municipalities (who increasingly report collaboration with one
another) collaborate bilaterally or within the structure of a group organized by a third party at
the regional level.
6.2 Closing Remarks
This study should be viewed as one step in a larger study of collaborative governance
in disaster risk reduction, which should of course include a study of the degree to which
collaboration entails substantive and meaningful influence for all participants. Exploring the
quality of collaboration was beyond the scope of this study. However, it would be worthwhile
to conduct a more in-depth study of the outcomes or accomplishments derived from the
Swedish municipalities’ reported collaboration on disaster prevention and preparedness.
49
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8 Appendix A Complete color-coded table showing all the municipalities’ answers to each question in each
of the three datasets, for overview. Municipalities are assigned anonymous codes and
organized by SKL category.
Appendix A is excluded from the DiVA upload of this paper. Contact the author for a copy
of appendix A.
75
9 Appendix B
Questions used from Dataset 1, Dataset 2 and Dataset 3
Dataset 1: Collaborative partnerships
2009
Which partners does the municipality collaborate with, either in crisis management councils, or in other ways? Multiple answers can be selected.
o The Police o The County Council o The County Administrative Board o Other Municipality/Municipalities o The Private Sector o The Swedish Armed Forces o Religious Organizations o Other NGOs o Other Organizations
2010 Which partners does the municipality collaborate with, either in crisis management councils or in other ways? Multiple answers can be selected.
o The Police o The County Council o The County Administrative Board o Other Municipality/Municipalities o The Private Sector o The Swedish Armed Forces o Religious Organizations o Other NGOs o Other Organizations
2011 Which partners does the municipality collaborate with in order to achieve collaboration and coordination before and during an extraordinary event? Multiple answers can be selected.
o The Police o The County Council o The County Administrative Board o Other Municipality/Municipalities o The Private Sector o The Swedish Armed Forces o Religious Organizations o Other NGOs o Other Organizations
2012 Which partners does the municipality have an ongoing collaborate with in order to fulfill its task of having collaboration and coordination before and during an extraordinary event? Multiple answers can be selected.
o The Police
76
o The County Council o The County Administrative Board o Other Municipality/Municipalities o The Private Sector o The Swedish Armed Forces o Religious Organizations o Other NGOs o Other Organizations
Dataset 2: Structure in place for collaboration
2010 Does the municipality have, within its organizational structure, a person or group responsible for collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event? (for example, a crisis management council, established coordination groups or other type of committee). Explain why the municipality does not have a structure for collaboration.
2011 Does the municipality have a structure in place for collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event? (for example, a crisis management council, established coordination groups or other type of committee). Explain why the municipality does not have structures for collaboration and describe how the municipality is working to fulfill its’ responsibility for its’ geographic area.
2012 Does the municipality have a structure in place for collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event? (for example, a crisis management council, established coordination groups or other type of committee). Explain why the municipality does not have structures for collaboration and describe how the municipality is working to fulfill its’ responsibility for its’ geographic area.
2013 Does the municipality have a structure in place for collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event? (for example, a crisis management council, established coordination groups or other type of committee).
Briefly explain how the municipality works to achieve collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event.
2014 Does the municipality have a structure in place for collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event? (for example, a crisis management council, established coordination groups or other type of committee).
77
Briefly explain how the municipality works to achieve collaboration and coordination of relevant partners’ preparations for, and actions during an extraordinary event (including coordination of information to the public under such circumstances).
Dataset 2: Coding of themes in text answers
9. Informal structures are used
10. Other existing structures are used (an existing regional group, an existing collaborative group established for another purpose)
11. Lack of resources (money, time etc.)
12. Working on putting a structure in place/coming soon
13. Partner-related reason (lack of interest from partners, could not identify partners etc.)
14. A practical/administrative obstacle (change of staff, absence of a formal decision, internal reorganization etc.)
15. Other
16. The answer does not provide any information (simply restating the question, no reason given, blank)
Dataset 3: Collaboration within and beyond the municipalities geographic area
2015-2018
1. The municipality’s preparations for an extraordinary event have taken place in collaboration with other municipalities and other partners outside of the municipality’s own geographic area. 2. The municipality has taken action to enable collaboration among actors engaged in critical infrastructure provision within the municipality’s boarders for the purpose of achieving coordination of preparation for, and measures during, an extraordinary event. 3. The municipality facilitates a collaborative forum that includes representatives of the municipality and other actors involved in prevention and management of extraordinary events within the municipality’s geographic area.
78
10 Appendix C
List of municipalities excluded from each dataset due to missing data
point(s)
Missing from Dataset 1 (14)
Missing from Dataset 2 (16) Missing from Dataset 3 (28)
Arjeplog Botkyrka Åmål
Gagnef Degerfors Åsele
Jokkmokk Eslöv Askersund
Kalix Höganäs Botkyrka
Malå Höör Burlöv
Orust Sjöbo Eslöv
Övertorneå Skurup Falun
Sollefteå Simrishamn Göteborg
Stockholm Södertälje Huddinge
Sundbyberg Surahammar Karlsborg
Täby Svalöv Lysekil
Trosa Umeå Malmö
Vänersborg Vadstena Markaryd
Värmdö Värmdö Munkedal
Vindeln Nacka
Vimmerby Rättvik
Sigtuna
Solna
Storuman
Sundbyberg
Sunne
Svedala
Upplands Väsby
Upplands-Bro
Vaggeryd
Vansbro
Vara
Värmdö
79
11 Appendix D
The Swedish Association of Local Authorities and Regions’ (SKL) Categorization of
Municipalities 2017 (author’s translation)
Category Subcategory Short definition Number
Group A:
Municipalities
containing major cities
or near major cities
A1. Major cities At least 200,000
residents in the
municipality’s largest
urban center
3
A2. Commuting
municipalities near
large cities
At least 40% of
working residents
commute to a major
city or municipality
near a major city
43
Group B:
Municipalities
containing large cities
or near large cities
B3. Large cities At least 40,000 and
few than 200,000
residents in the
municipality’s largest
urban center
21
B4. Commuting
municipalities near
large cities
At least 40% of
working residents
commute to a large
city.
52
B5. Long-distance
commuting cities near
large cities
Fewer than 40% of
working residents
commute to a large
city.
35
Group C: Municipality
containing smaller
cities/smaller urban
areas and rural
municipalities
C6. Smaller city/urban
area
At least 15,000 and
fewer than 40,000
residents in the
municipality’s largest
urban center.
29
C7. Commuting
municipality near
smaller city/urban area
At least 30 % of
employed commute in
or out to smaller
cities/urban areas.
52
C8. Rural municipality Fewer than 15,000
residents in the
municipality’s largest
urban center, low rate
of commuting.
40
C9. Rural municipality
with tourism
Rural municipality
meeting at least two
criteria related to
tourism […]
15
(Kommungruppsindelning 2017 n.d.)
80
12 Appendix E
Original Swedish alongside English translations
This appendix is included for the sake of clarity and transparency. In some cases, I have made
use of English translations provided by Swedish organizations themselves. Where English
titles and translations were not provided, I have translated from Swedish to English myself.
Ansvarsprincipen
Närhetsprincipen
Likhetsprincipen
The Principle of Responsibility
The Principle of Proximity
The Principle of Normalcy
Lag (2006:544) om kommuners och
landstings åtgärder inför och vid
extraordinära händelser i fredstid och höjd
beredskap
Law (2006:544) on municipal and county
council measures prior to and during extra-
ordinary events in peacetime and during
periods of heightened alert
Lag (2003:778) om skydd mot olyckor The Law on Protection from Accidents
(Law 2003:778)
Kommun Municipality
Krisberedskapsmyndigheten The Swedish Agency for Crisis
Preparedness
Mindre städer/tätorter och
landsbygdskommuner
Small towns/urban areas and rural
municipalities
Myndigheten för samhällsskydd och
beredskap (MSB)
The Swedish Civil Contingencies Agency
Offentlighetsprincipen Principle of public access
Räddningstjänsten Rescue Services
Samhällsviktig verksamhet Critical infrastructure
Samverka Collaborate
Storstäder och storstadsnära kommuner Large cities and municipalities near large
cities
Större städer och kommuner nära större stad Cities/large towns and municipality near
cities
Sveriges Kommuner och Landsting Swedish Association of Local Authorities
and Regions
Survey data
Dataset 1
2009
Vilka aktörer samverkar kommunen
med, antingen i krishanteringsråd eller i
annan form? Flera alternativ kan väljas.
o Polisen
o Landstinget
o Länsstyrelsen
o Annan kommun/andra
kommuner
o Näringslivet
Which partners does the municipality
collaborate with, either in crisis
management councils, or in other ways?
Multiple answers can be selected.
o The Police
o The County Council
o The County Administrative
Board
81
o Försvarsmakten
o Trossamfund
o Andra frivilligorganisationer
o Andra aktörer
o Other
Municipality/Municipalities
o The Private Sector
o The Swedish Armed Forces
o Religious Organizations
o Other NGOs
o Other Organizations
2010 Vilka aktörer samverkar kommunen
med, antingen i krishanteringsråd eller i
annan form? Flera alternativ kan väljas.
o Polisen
o Landstinget
o Länsstyrelsen
o Annan kommun/andra
kommuner
o Näringslivet
o Försvarsmakten
o Trossamfund
o Andra frivilligorganisationer
o Andra aktörer
Which partners does the municipality
collaborate with, either in crisis
management councils or in other ways?
Multiple answers can be selected.
o The Police
o The County Council
o The County Administrative
Board
o Other
Municipality/Municipalities
o The Private Sector
o The Swedish Armed Forces
o Religious Organizations
o Other NGOs
o Other Organizations
2011 Vilka aktörer samverkar kommunen
med för att åstadkomma samverkan och
samordning inför och under en
extraordinär händelse? Flera alternativ
kan väljas
o Polisen
o Landstinget
o Länsstyrelsen
o Annan kommun/andra
kommuner
o Näringslivet
o Försvarsmakten
o Trossamfund
o Andra frivilligorganisationer
o Andra aktörer
Which partners does the municipality
collaborate with in order to achieve
collaboration and coordination before
and during an extraordinary event?
Multiple answers can be selected.
o The Police
o The County Council
o The County Administrative
Board
o Other
Municipality/Municipalities
o The Private Sector
o The Swedish Armed Forces
o Religious Organizations
o Other NGOs
o Other Organizations
2012 Med vilka aktörer har kommunen en
löpande samverkan för att fullgöra sin
uppgift att åstadkomma samverkan och
samordning inför och under en
extraordinär händelse? Flera alternativ
kan väljas
o Polisen
o Landstinget
o Länsstyrelsen
o Annan kommun/andra
kommuner
o Näringslivet
Which partners does the municipality
have an ongoing collaborate with in
order to fulfill its task of having
collaboration and coordination before
and during an extraordinary event?
Multiple answers can be selected.
o The Police
o The County Council
o The County Administrative
Board
o Other
Municipality/Municipalities
82
o Försvarsmakten
o Trossamfund
o Andra frivilligorganisationer
o Andra aktörer
o The Private Sector
o The Swedish Armed Forces
o Religious Organizations
o Other NGOs
o Other Organizations
Dataset 2
Dataset 2: Structure for collaboration
2010 Har kommunen en funktion för att
åstadkomma samverkan och samordning
av berörda aktörers åtgärder inför och
under en extraordinär händelse? (t.ex. ett
krishanteringråd, förberedda
samordningsgrupper eller motsvarande
funktion)
Motivera varför kommunen inte har en
funktion för samverkan:
Does the municipality have, within its
organizational structure, a person or
group responsible for collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event? (for example, a
crisis management council, established
coordination groups or other type of
committee).
Explain why the municipality does not
have a structure for collaboration.
2011 Har kommunen former för att
åstadkomma samverkan och samordning
av berörda aktörers åtgärder inför och
under en extraordinär händelse? (t.ex. ett
krishanteringsråd, förberedda
händelsegrupper/samverkansgrupper eller
motsvarande)
Motivera varför kommunen inte har
former för samverkan och beskriv hur
kommunen arbetar för att fullgöra sitt
geografiska områdesansvar.
Does the municipality have a structure
in place for collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event? (for example, a
crisis management council, established
coordination groups or other type of
committee).
Explain why the municipality does not
have structures for collaboration and
describe how the municipality is
working to fulfill its’ responsibility for
its’ geographic area.
2012 Har kommunen former för att
åstadkomma samverkan och samordning
av berörda aktörers åtgärder inför och
under en extraordinär händelse? (t.ex. ett
krishanteringsråd, förberedda
händelsegrupper/samverkansgrupper eller
motsvarande).
Motivera varför kommunen inte har
former för samverkan och beskriv hur
kommunen arbetar för att fullgöra sitt
geografiska områdesansvar.
Does the municipality have a structure
in place for collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event? (for example, a
crisis management council, established
coordination groups or other type of
committee).
Explain why the municipality does not
have structures for collaboration and
describe how the municipality is
83
working to fulfill its’ responsibility for
its’ geographic area.
2013 Har kommunen former för att
åstadkomma samverkan och samordning
av berörda aktörers åtgärder inför och
under en extraordinär händelse? (t.ex. ett
krishanteringsråd, förberedda
händelsegrupper/samverkansgrupper eller
motsvarande)
Beskriv kortfattat hur kommunen verkar
för att åstadkomma samverkan och
samordning av berörda aktörers åtgärder
inför och vid en extraordinär händelse
(inklusive samordning av information till
allmänheten under sådana förhållanden).
Does the municipality have a structure
in place for collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event? (for example, a
crisis management council, established
coordination groups or other type of
committee).
Briefly explain how the municipality
works to achieve collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event.
2014 Har kommunen former för att
åstadkomma samverkan och samordning
av berörda aktörers åtgärder inför och
under en extraordinär händelse? (t.ex. ett
krishanteringsråd, förberedda
händelsegrupper/samverkansgrupper eller
motsvarande)
Beskriv kortfattat hur kommunen verkar
för att åstadkomma samverkan och
samordning av berörda aktörers åtgärder
inför och vid en extraordinär händelse
(inklusive samordning av information till
allmänheten under sådana förhållanden).
Does the municipality have a structure
in place for collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event? (for example, a
crisis management council, established
coordination groups or other type of
committee).
Briefly explain how the municipality
works to achieve collaboration and
coordination of relevant partners’
preparations for, and actions during an
extraordinary event (including
coordination of information to the
public under such circumstances).
Dataset 3
2015-
2018
1. Kommunens förberedelser inför en
extraordinär händelse har skett i
samverkan med kommuner och andra
aktörer utanför det egna geografiska
området.
2. Kommunen har tagit initiativ som
möjliggör för aktörer som bedriver
samhällsviktig verksamhet inom
kommunens geografiska område att
samverka i syfte att uppnå samordning
av förberedelser inför och åtgärder
under en extraordinär händelse.
1. The municipalities’ preparations for
an extraordinary event have taken place
in collaboration with other
municipalities and other partners
outside of the municipality’s own
geographic area.
2. The municipality has taken action to
enable collaboration among actors
engaged in critical infrastructure
provision within the municipality’s
geographic area for the purpose of
achieving coordination of preparation
84
3. Kommunen är sammankallande för
ett samverkansorgan i vilket
representanter för kommunen och
aktörer involverade i arbetet med att
förebygga och hantera extraordinära
händelser inom kommunens geografiska
område ingår.
for, and measures during, an
extraordinary event.
3. The municipality facilitates a
collaborative forum that includes
representatives of the municipality and
other actors involved in prevention and
management of extraordinary events
within the municipalities geographic
area.
SKL Kommungruppsindelning 2017
(Kommungruppsindelning 2017 n.d.)
Huvudgrupp Kommungrupp Kort definition
A. Storstäder och
storstadsnära kommuner
A1. Storstäder Minst 200 000 invånare i
kommunens största tätort
A2. Pendlingskommun
nära storstad
Minst 40% utpendling till storstad
eller storstadsnära kommun
B. Större städer och
kommuner nära större
stad
B3. Större stad Minst 40 000 och mindre än 200
000 invånare i kommunens
största tätort
B4. Pendlingskommun
nära större stad
Minst 40% utpendling till större
stad
B5.
Lågpendlingskommun
nära större stad
Mindre än 40% utpendling till
större stad
C. Mindre städer/tätorter
och
landsbygdskommuner
C6. Mindre stad/tätort Minst 15 000 och mindre än 40
000 invånare i kommunens
största tätort
C7. Pendlingskommun
nära mindre stad/tätort
Minst 30% ut- eller inpendling till
mindre stad/tätort
C8.
Landsbygdskommun
Mindre än 15 000 invånare i
kommunens största tätort, lågt
pendlingsmönster
C9.
Landsbygdskommun
med besöksnäring
Landsbygdskommun med minst
två kriterier för besöksnäring,
dvs. antal gästnätter, omsättning
inom
detaljhandel/hotell/restaurang i
förhållande till invånarantal
85
Translation of SKL Categorization of Municipalities 2017
Category Subcategory Short definition
Group A: Municipalities
containing major cities or
near major cities
A1. Major cities At least 200,000 residents in
the municipality’s largest
urban center
A2. Commuting
municipalities near large
cities
At least 40% of working
residents commute to a major
city or municipality near a
major city
Group B: Municipalities
containing large cities or near
large cities
B3. Large cities At least 40,000 and few than
200,000 residents in the
municipality’s largest urban
center
B4. Commuting
municipalities near large
cities
At least 40% of working
residents commute to a large
city.
B5. Long-distance
commuting cities near large
cities
Fewer than 40% of working
residents commute to a large
city.
Group C: Municipality
containing smaller
cities/smaller urban areas and
rural municipalities
C6. Smaller city/urban area At least 15,000 and fewer
than 40,000 residents in the
municipality’s largest urban
center.
C7. Commuting municipality
near smaller city/urban area
At least 30 % employed of
commute in or out to smaller
cities/urban areas.
C8. Rural municipality Fewer than 15,000 residents
in the municipality’s largest
urban center, low rate of
commuting.
C9. Rural municipality with
tourism
Rural municipality meeting
at least two criteria related to
tourism […]
86
13 Appendix F Further data associated with analysis section.
Further information associated with figure 2
The category “other organizations” was eliminated and the remaining eight categories of
collaborative partners were grouped into three categories.
Public sector The Police
The County Council
The County Administrative
Board
Other Municipality/ies
The Swedish Armed Forces
Religious org./NGOs Religious Organizations
Other NGOs
Private sector The Private Sector
Other Organizations
Figure 2 shows the number and percentage of municipalities in the Dataset 2 sample (276)
that reportedly collaborated with at least one partner by year in each category. The first
column shows any collaboration with any partner (in number of municipalities and then
percent of sample) followed by collaboration with public sector actors, religious
organizations and NGOs and private sector actors.
Collaboration by category of partner and year (number and % of municipalities
in sample) Public sector Religious
org./NGO
Private sector
2009 274 99% 268 97% 235 85% 155 56%
2010 273 99% 271 98% 245 89% 163 59%
2011 267 97% 266 96% 238 86% 167 61%
2012 274 99% 274 99% 247 89% 177 64%
87
Data associated with figure 4.
Group
A
Nr Mun.
any
Nr public
any
Nr
volonteer
Nr
buisness
Never 0
2009 41 98% 40 95% 36 86% 28 67%
2010 41 98% 41 98% 36 86% 19 45%
2011 42 100% 42 100% 37 88% 24 57%
2012 41 98% 41 98% 39 93% 25 60%
Group
B
Nr Mun.
any
Nr public
any
Nr
volonteer
Nr
buisness
Never 0
2009 105 100% 104 99% 89 85% 62 59%
2010 105 100% 104 99% 98 93% 70 67%
2011 98 93% 98 93% 89 85% 56 53%
2012 104 99% 104 99% 97 92% 67 64%
Group
C
Nr Mun.
any
Nr public
any
Nr
volonteer
Nr
buisness
Never 0
2009 128 99% 124 96% 110 85% 65 50%
2010 127 98% 126 98% 111 86% 74 57%
2011 127 98% 126 98% 112 87% 87 67%
2012 129 100% 129 100% 111 86% 85 66%
88
Figure associated with “Stability of Collaborative Partnerships 2009 to 2012 by Groups
of Municipalities”
0.0% 1.0% 3.0%
69.8%65.7% 62.9%
16.3% 18.2%25.0%
11.6% 12.1%5.3%2.3% 2.0% 3.8%
0.0% 1.0% 0.0%0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
Group A Group B Group C
Stability by group 2010-2014 - % of group
never always 1 change 2 changes 3 changes 4 changes
89
Text analysis: obstacles to establishing collaborative governance structures, 2010 to
2014
Category 1:
Informal
Category 2:
Existing
2010 2011 2012 2013 2014 2010 2011 2012 2013 2014
22 16 26 16 8 8 9 15 4 5
32% 47% 63% 67% 47% 12% 26% 37% 17% 29%
Category 3: Lack of
resources Category 4: Coming soon
2010 2011 2012 2013 2014 2010 2011 2012 2013 2014
11 1 3 0 0 25 16 12 9 6
16% 3% 7% 0% 0% 36% 47% 29% 38% 35%
Category 5: Partner-related reason Category 6: Practical/administrative obstacle
2010 2011 2012 2013 2014 2010 2011 2012 2013 2014
6 1 3 0 1 5 1 5 0 0
9% 3% 7% 0% 6% 7% 3% 12% 0% 0%
Category 7: Other Category 8: Non-response
2010 2011 2012 2013 2014 2010 2011 2012 2013 2014
8 6 0 0 0 11 0 0 1 4
12% 18% 0% 0% 0% 16% 0% 0% 4% 24%