Organizational culture in Disaster Risk Reduction
Raffaele Giordano and Alessandro Pagano (CNR-IRSA)
In crisis response, an increasing number of individuals, groups, organizations and jurisdictions need to coordinate their actions in order to deliver effective operations.
Organizational culture plays a crucial role in DRR by affecting the way different actors give an interpretation to the critical situation. Organizational culture could affect the way different actors perceive the interaction network – e.g. polycentric, hierarchical, star-shaped, etc. – influencing the process of seeking, trusting and interpreting emergency information. Developing effective emergency management strategies requires a clear understating of the differences among cultural organizations and agents’ understanding of the interaction networks.
Organizational culture is emerging as a crucial aspect to be considered in assessing the performance of an organization. In emergency, organizational culture affects the way different responders interpret the situation, organize tasks and interact with the others.
How do you analyse organizational culture to enhance resilience?
The implementation of information management and communication technologies, even innovative (e.g. internet-of-things, smartphone, smart city cameras and traffic lights, etc.), failed in many situations because of the oversimplification of the social processes at the base of emergency information management. The key steps in the process of transforming risk information and warning into actions – i.e. hearing, understanding, believing, personalizing and deciding – are mediated through social structures. Exposing all individuals to the same information in the same way, without accounting for the different social structures and organizational culture, is likely to negatively affect the ability to generate novel ideas and interpretations of the emergency situation.
This section of the handbook aims at supporting emergency managers in enhancing the interaction processes among actors involved in emergency management and response, through a better understanding of the complexity (ramification) of the interaction network, and ambiguity in problem framing and understanding the situation.
Organizational culture in emergency management
The same Greek origin of the word ‘crisis’ entails the concept of judgment, implying the crucial capacity to make sense and disentangle the clues of a rapidly evolving situation. Evidence demonstrate the danger of lack or delayed decision making during crisis. Decision making and its enactment demands the coordinated involvement of experts and organizations from several fields.
As social systems become increasingly more interdependent with physical and technical systems acting at interconnected spatial and temporal scales, the range of possible interactions among individuals, groups, and organizations, and the context in which these all function increases. Also the number of factors that influence the potential actions and outcomes in constructive or destructive ways also increases. This interconnectedness among the different elements of the system could lead to what we call/are called interdependent crisis. That is, the disruption of one element in the system (e.g. an infrastructure) causes appreciable impact on other elements, which in turn cause further effects on other parts of the system. The extent to which these effects propagate, and how serious these effects become, depends on how tightly coupled the components of the system are, how strong is the original cause, and whether or not adequate counter-measures are in place.
The core activity of taking decisions and implementing actions in this complex and highly dynamic environment often exceeds the ability of a single centralized entity to cope. No single entity can have complete control of these multi-scale, distributed, highly interactive networks, or the ability to evaluate, monitor and manage these emergencies in real time. It’s becoming crucial to overcome the classical emergency management approaches in which institutional organizational structure tends to follow stable boundaries, established authority figures, and protocol driven actions. Nowadays the response to crises becomes an emerging, large-scale system consisting of individuals, groups, organizations and jurisdictions that need to coordinate their actions for delivering effective operations. In crises, a “temporary multi-organisation” as defined by Cherns and Bryant (1984) needs to be deployed, implying several difficulties of coordination and shared management of the situation(s). Cooperative response actions need to be carried out in a network form (Abbasi, 2014), and can benefit or be impaired by the connectivity patterns of the different emergency responders (Vespignani, 2011).
Enhancing the coordination effectiveness in case of emergency among the different responders is the main scope of several studies aimed at overcoming the main organizational factors hindering cooperation. Up to now, most research has been carried out on what happens within a single organisation under stress, while knowledge is still limited on what happens when multiple organisations need to coordinate in unison to make the best of their capacity in a highly stressful environment. That is, lack of cross-sectoral structures, lack of common goals, lack of common concepts, lack of distribution of information, lack of trust, competitive practices and lack of situational awareness ( . Although most of the efforts carried out in order to enhance cooperative emergency management have been focused on technological innovation for information sharing, we need a shift toward enhancing the interactions among the different actors in emergency management.
Existing formal protocols of interaction ignore how cultural diversities, with specific reference to organizational culture, influence the way different actors perceive the topology of their own interactional network, and, consequently, their strategies to cooperate with other entities. Empirical evidences demonstrate how some actors assume a strongly hierarchical structure of the interactions (Sorensen & Stanton, 2013). Other actors consider the multi-central structure as the most effective one to allow the rapid exchange of information and cooperation within each level of the organizational structure and between different levels (Smart & Sycara, 2013). Neglecting these differences could lead to the development of ineffective procedures for emergency management, because the actors will not recognize the network through which they collect the information and cooperate as trustable.
The dynamic and complex nature of crisis situations does not allow for a static framework of the crisis responses. Interaction networks change dramatically during an emergency. Some actors could assume the role of informal leaders, whereas the official responders could be characterized by a low level of trust. The existing institutional protocols for information management in case of emergency seem incapable of adapting themselves to this changing interactional situation.
Finally, the process of interpreting the emergency information (i.e. sensemaking) has to be considered as a social process aiming at selectively focus on certain stimuli and responses (attentional selection), and at generating a shared understanding for coordinated action. This requires a perspective in which the negotiation of meaning of information that is embedded in emergency management become visible. This allows emergency managers to unravel the impacts of differences in institutional and cultural backgrounds and to consider those diversities as a factors enabling/facilitating the collective sense-making. Nevertheless, cognitive diversity is not always a virtue when it comes to collective cognitive processes. On the one hand, evidence suggest that cognitive heterogeneity is useful in mitigating against the cognitive biases that are associated with collective sense-making (e.g. confirmation biases) (Smart & Sycara, 20. On the other hand, different background knowledge and belief can represent a barrier to collective cognitive processes (Smart & Sycara, 2013).
The experiences in EDUCEN demonstrate that in order to shift cultural diversity from a barrier to an enabling factor for cooperative emergency management,requires methods and tools to enhance the understanding of the dynamic processes influencing the interactions among different actors in the different phases of the DRR.
Organizational culture in L’Aquila, Italy
The city of L’Aquila experienced a disastrous earthquake in 2009. Different barriers hampering the cooperation among the different actors were registered during the three main phases of the DRR. The communication limits in the preparatory phases and during the recovery gained a lot of attention.
We mapped the network of interactions among the different emergency responders, both institutional and non-institutional to analyse the flow of information and cooperation activated during the different phases of the 2009 earthquake emergency.
The Case Study looks into the disastrous Magnitude 6.3 earthquake which struck L’Aquila city and its province at 3.32 a.m. on 6 April 2009. The event killed 308 people and injured 1500. Although the physical event was relatively moderate (moment magnitude 6.3), its impacts were particularly great, mainly due to the very high vulnerability of lives, livelihoods, building stock and institutions in the Apennine Mountains.
This event highlighted several limits in the information sharing protocols, and specifically between the institutional actors and the community. These limits had a very negative impact on the level of trust local community had in the emergency managers, with consequences on the acceptability of emergency management and recovery measures. After the earthquake, the local community was forced to abandon the city center. New towns were developed in safer places, disaggregating the original socio-cultural networks. New networks emerged after the disasters, showing different cultural aspects.
In order to cope with emergencies, the official protocol of interactions among the different actors can be represented as in figure 1.
As shown in the figure, the protocol is strongly hierarchical and pemits little information sharing between actors at the same level in the process. The analysis of the interviews carried out in the case study, involving both official responders and members of the community, allowed to map the actual network of interactions, as shown in the following figure.
Table 1: List of stakeholders involved in the L’Aquila CS.
|L.EM||Local Emergency Manager||Individual||Mayor|
|N.EM||National emergency management||Organization||Di.Coma.C.|
|L.TS||Local Technical Support||Organization||Technical Municipal office|
|R.TS||Regional Technical Support||Organization||Regional Civil Protection agency|
|N.TS||National Technical support team||Organization||National Civil Protection agency|
|L.OP1||Local Operational Team #1 (Health assistance)||Organization||Local Red Cross team|
|N.OP1||National Operational Team #1 (Health assistance)||Organization||External Red Cross teams (coordinators and operators)|
|L.OP2||Local Operational Team #2 (Fire Brigade)||Organization||Local Fire Brigade team|
|N.OP2||National Operational Team #2 (Fire Brigade)||Organization||External Fire Brigade teams (coordinators and operators)|
|L.OP3||Local Operational Team #3 (Police Dept.)||Organization||Local Police team|
|N.OP3||National Operational Team #3 (Police Dept.)||Organization||External Police teams (coordinators and operators)|
|C||Community||Individual||Members of the community|
|CL||Community leaders||Individual||Representative of the community|
The comparison between this network and that representing the official protocol of interactions in case of emergency demonstrates the inadequacy of the protocols to fully capture the complexity of the interactions. The actual network is far less hierarchical and accounts for informal interactions taking place even among institutional actors. That is, during the knowledge elicitation phase we learned that, besides the official interactions, in case of emergency the institutional actors activated personal relationships to gather important information.
The combination of the different networks allowed to map the complex interactions among the main elements activated during the flood emergency, i.e. agents, knowledge and tasks (see Figure below).
The Figure shows the actual complexity of the interaction mechanisms supporting the emergency management. Failure in this network – lack of an information, missing cooperation for task implementation, etc. – could provoke uncontrollable cascading effects leading to the failure of the whole emergency management process. Therefore, it becomes crucial for the emergency managers to enhance their comprehension of this complexity, in order to implement actions aiming to increase the effectiveness of the emergency management network and to reduce its vulnerability.
The experiences carried out in the L’Aquila CS demonstrated how the organizational culture influences the way the different organizations perceive the interaction network in which they have to operate in case of emergency. Some institutional actors, such as local emergency managers, considered the multi-central structure as the most effective structure to enable a rapid exchange of information within each level of the organizational structure and between different levels. These levels seem capable to adapt their information collection strategy to different conditions, showing resilience to failures in official protocols of information sharing. Institutional actors with a dense network of interactions – regional emergency management – seemed capable to shift from the formal to the informal network in order to gather the information needed. But the official responders, such as the national civil protection and the fire brigades, assumed a strongly hierarchical structure for information exchange. These actors exclusively trusted information flowing from the top through intermediary, and easily recognizable, levels. This is because they needed to reduce “noise” in information collection. Neglecting these differences can lead to ineffective strategies for information sharing for emergency management. Integrating Murcia’s emergency management into a hierarchically structured network could negatively affect its role as response coordinator. To the contrary, increasing the number of information centres in the responders’ networks could paralyze their activities. The experiences gained in L’Aquila suggested that developing effective emergency management strategies requires a clear understating of the differences among agents’ understanding of the interaction network.
Finally, the adopted methodology allowed us to emphasize the role of the community in the emergency management phases, and to make the institutional actors aware of the need to account for the community’s understanding of the emergency situation. Specifically, the analysis of the community network allowed us to better comprehend the reasons why the level of trust in institutional information is so low. The community network is strongly polycentric, allowing community members to select the more suitable information sources and activate informal networks of information sharing, as the information provided through institutional channels is not easy for them to comprehend. The analysis of the network allowed to define the central role played by the community leaders in facilitating the flow of information. They represent the actual information centres for the community. This result was considered as crucial for the definition of potential improvements of the emergency management procedure.
Organizational culture in Lorca, Spain
The Lorca municipality has historically suffered serious disaster episodes. The St. Wenceslas Flood (2012) caused several fatalities and damages to buildings and infrastructures. This experience showed some bottlenecks in the “formal” channels of information and data sharing. In particular, the capability of the institutions to provide community with accessible and understandable information on flood risk was strongly questioned and leaded to some conflicts involving community and institutions.
The methodology described was implemented to analyse the interaction network supporting the flood emergency management in Lorca and Puerto Lumbreras municipalities, located in the autonomous region of Murcia in Southeastern Spain. The area is highly disaster prone, mainly floods, but also droughts and earthquakes. Lorca is the third city within Murcia and the main one in the shire of Alto Guadalentín, a large valley that has become a key agricultural area in Spain. Paradoxically, the area is characterised by a semi-arid climate.
The area has historically suffered serious disaster episodes. Specifically, Lorca’s Puerto Lumbreras area is more prone to hazard: major events include the Puerto Lumbreras flood in 1973 and St. Wenceslas Flood in 2012. These events caused several fatalities and damages to buildings and infrastructures (e.g. Puentes dam was destroyed twice by flooding).
The flood episodes typically occurring in the area may be extremely dangerous due to their quick onset: the flow rate can increase up to 2000 m3/s within minutes, conveying in two hours approximately the same volume of water that is normally expected in a whole year. Specifically, in the flash flood event of the 2012, the Nogalte wadi, a tributary to Guadalentín river, changed from a dry riverbed to a wide and fast-flowing river in less than 20 minutes (Figure 4).
In order to cope with flash flood emergencies, a protocol of interactions was developed aiming at facilitating the coordination and the flow of information among the different institutions and official responders. Figure 5 schematizes the official protocol of interactions in case of emergency in the Murcia autonomous region.
As shown in the figure, the protocol assumes a hierarchical structure concerning the flow of information. The Spanish Meteorological Institute (AEMET) is responsible for disseminating the early warning based on the weather forecasts. According to the level of warning - red, orange and yellow - actions should be taken by Murcia’s emergency management unit (Murcia 112). During flood events, two independent monitoring networks collect data:
- the rainfall monitoring system provides real time data to Murcia 112.
- the SAIH, the Segura River Basin monitoring system, provides accurate and updated data on rainfall, the level of the water in the riverbeds and the level in the reservoirs.
These two monitoring systems do not exchange information. According to the protocol of interaction, Murcia 112 plays the central role in the emergency management. It coordinates the rescue activities of the first responders through Murcia’s flood response committee, INUNMUR. On the other side of the interaction network, the Segura river basin authority, in case of warning, activates its internal monitoring and decision-making committee whose main scope is to adopt the needed actions for managing the water in the reservoir according to the flow of water in the riverbeds.
The Municipality represents the interface between the emergency management authority and the local community. According to the existing protocol of interventions, its main role is to facilitate the flow of information to the community and to implement the decisions taken by Murcia 112 at local level, e.g. the evacuation of the local population.
Previous experiences had shown bottlenecks in the “formal” channels of information and data sharing. In particular, the capability of the institutions to provide community with accessible and understandable information on flood risk was strongly questioned and leaded to some conflicts involving community and institutions. Moreover, ineffective communication among institutional agents was registered, both between the Segura river basin authority and Murcia 112, and between Murcia 112 and the Municipality. Based on these experiences, negotiations were started to revise the operative protocol. Our analysis aims to support this revision and adaptation process through the analysis of the formal and informal networks of interaction, and the detection of the vulnerable elements in the network.
The following pages describe the results obtained through the implementation of this methodology.
The official protocol of interactions to be activated among the institutions in case of emergency was used in this work as a starting point for the definition of the set of actors to be involved in the knowledge elicitation phase. Table 2 shows the list of the institutional actors involved in the cognitive mapping interviews. A main role was assigned to the institutional actors as well, which can also be useful to generalize the methodology. The acronyms were selected in order to facilitate the development of the network maps, as shown in the following.
|Spanish meteorological Agency (AIMET)||National technical support||N.WF|
|Segura river basin authority||Regional technical support||L.TS|
|Murcia emergency management||Local emergency management||L.EM1|
|Fire brigades||Local operational team||L.OP1|
|Military emergency unit (UME)||National operational team||N.OP|
|National civil protection||National EM||N.EM|
|National Government||National coordination||N.GOV|
|Municipality||Local emergency management||L.EM2|
|Other Municipalities||Local emergency managers||L.EM3|
|Local Police||Road functionality||L.OP2|
|Network managers||Road functionality||R.OP2|
|State police||National emergency unit||N.OP3|
Table 2: List of institutional stakeholders involved in the flood emergency management
The aggregation of the collected narratives allowed to develop the complex maps of interaction, as shown in the following figure.
Figure 6 shows the actual complexity of the interaction mechanisms supporting emergency management. Failure in this network – lack of an information, missing cooperation for task implementation, etc. – can provoke uncontrollable cascading effects leading to the failure of the whole emergency management process. Therefore, it becomes crucial for the emergency managers to enhance their comprehension of this complexity, in order to implement actions aiming to increase the effectiveness of the emergency management network and to reduce its vulnerability.
To this aim, graph theory measures described previously were implemented in order to identify the key elements and the main vulnerabilities of the network. Table 3 shows the results of the analysis aiming at identifying the key agents in the network.
|Total centrality degree||National civil protectionMunicipality||These actors are characterized by a high number of connection (both in- and out-) with most of the other agents in the network.|
|Betweennes Centrality||MunicipalitySegura RBAMurcia 112Community leaders||These actors occur on many of the shortest paths between other agents. This means that these actors can easily move information from one part of the other of the network.|
|Hub centrality||Segura RBAMurcia 112Community leaders||Individuals or organizations that act as hubs are sending information to a wide range of others each of whom has many others reporting to them. Therefore, they act as hub of information within the network.|
|Most knowledge||Segura RBAMurcia 112National civil protectionMedia||These actors have access to important pieces of information.|
|Most task||Murcia 112MunicipalityNational civil protectionSegura RBA||These actors are called to perform the most important tasks.|
Table 3. Key agents in the Lorca flood emergency network
The analysis allowed us to identify the most crucial agents in the network accounting for the complexity of their relationships with the other agents, which affects their capability in moving information from one side of the network to the other. Moreover, the adopted approach assumed that an agent is crucial in the network performance if she/he brings important knowledge and if she/he cooperates in performing important tasks.
The results of analysis demonstrate the importance of the three most influential institutional actors at local level, i.e. the Segura river basin authority, Murcia’s emergency management and the municipality. These actors had a dense network of interactions with the other agents (centrality measures), and had access to a wide set of crucial information allowing them to carry out crucial tasks. Beside these results, the analysis of the network emphasizes the actual role in the emergency management of the community leaders and the media. These actors were not mentioned in the official protocol of intervention. Specifically, the community leaders could easily act as an interface between the institutional system and the local communities. Their high value of the betweenness centrality and hub centrality demonstrate that these actors could facilitate the sharing of the emergency information.
Similarly, the network analysis showed that role the media could play during an emergency. Most institutional actors were in direct contact with media. Therefore, they had access to important information.
The developed network was also analysed in order to identify key vulnerabilities, i.e. those elements that could lead to failures of the emergency management operations and/or to decreasing effectiveness of the responding actions. The graph measures mentioned in Table 3 were implemented. The key vulnerabilities are described in Table 4 below.
|Type of elements||Key vulnerability||Meaning|
|Agent||Community leaders||This actor has a high degree of centrality but a low degree of “most knowledge”: s/he has access to limited knowledge impeding their role as information providers. They represent a barrier rather than a bridge to information sharing.|
|Municipality||This actor has a high degree of “most task” and a low degree of “most knowledge”. This is mainly due to the limited capacity of the municipality to understand the technical information provided by the other actors. As result, the effectiveness of its actions is limited.|
|Media||This actor has a high degree of “most knowledge”, because it receives information directly from the institutional actors. Nevertheless, its low centrality degree reduces its capability to effectively share the information with the community.|
|Knowledge||Flood emergency management plan||This information should play a crucial role since it has a high level of ‘most task” (it supports a large number of tasks). Nevertheless, it is poorly shared among the different agents (low degree of most knowledge).|
|River flow monitoring and forecasting||This information represents a key vulnerability because it has a high betweenness centrality in the knowledge x knowledge network (i.e. it could activate other information), but it is not easily accessible to most actors.|
|Task||Preparedness activity with community||This task is characterized by a high degree of centrality in the Task x Task network: it could facilitate the implementation of numerous other tasks. However, only the municipality is responsible for the correct implementation of this task.|
Table 4. Key vulnerability in the network of Lorca flood emergency management
The results of the analysis were used as basis for the discussion with the local decision-makers and stakeholders. At the beginning of the process, they were aware that improvements in the protocol of interactions were needed. Nevertheless, they were focusing exclusively on the interaction among the institutional actors. The analysis carried out in this work increased their awareness about the role played by the informal interactions, taking place within the institutional system and between institutional actors and the members of the community. Using the results of the key vulnerabilities analysis, participants started discussing about suitable strategies to improve the flood emergency management plan, accounting for the complexity of interactions. Specifically, the discussion initially focused on the role of the media. Most institutional actors agreed that enabling a more effective bi-directional communication with the community members through the social media would be beneficial for sharing emergency information. The institutional actors were interested in enhancing the capability of the current media channels to collect, store and analyse the feedbacks from the community. The capability of local communities to contribute to the monitoring of the emergency evolution was deemed important by the participants.
In order to enhance the preparedness for flood emergency management, the need to improve the cooperation between institutional actors and the local community was considered crucial. According to the results of the discussion, this activity could improve the capability of local population to react in case of emergency in cooperation with the official responders. To this aim, suggestions were made to train the community leaders to be referred to as “agent of change”. Participants referred to the results of the “key agents” analysis in order to identify this potential improvement.
Therefore, the first and most important positive result of the methodology concerns the increased awareness of the institutional actors about the need to shift the focus from investing economic and human resources in developing innovative emergency information collection tools, to enhance the capability of the different actors to co-operate in case of emergency.