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Organisational Learning and Dynamics of Institutional Change Following Large-Scale Emergencies: Oman’s Emergency Management System as a Case Study

Al Zaabi, Saqar Obaid Mohammed; (2023) Organisational Learning and Dynamics of Institutional Change Following Large-Scale Emergencies: Oman’s Emergency Management System as a Case Study. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Emergency Management Systems (EMS) exist as an essential disaster risk reduction mechanism by efficiently matching resources to generated needs during crises. However, how they function in actual disaster situations and whether they adapt, evolve and learn from their own experiences have yet to be well-studied, particularly in non-Western contexts. This research is multidisciplinary qualitative research that cuts across the disciplines of disaster management, public administration, social science, political economy and management science. It aims to bring new insights into the phenomenon of organisational learning (of EMS) and the dynamics and forces of institutional change following crises. It reports findings on the nature of organisational learning following an emergency and the factors influencing institutional change. Oman’s EMS was found to be an appropriate case study as the rapidly-urbanising country has recently been struck by the reality of disasters. Secondly, it has adopted a centralised governmental command-and-control model for managing emergencies. Hence, it makes it an interesting case study to understand how this system would respond in large-scale emergencies and whether or not it evolves and learns from the experienced disasters. The primary data collection method was in-depth qualitative interviewing with key response agencies. It was triangulated with these secondary data sources: (1) emergency management ‘EM’ regulations, (2) EM plans and proposals, (3) official reports from responding agencies, (4) media reports about the emergencies, and (5) Twitter user-generated data for the two recent events. First, the response of the ‘formal’ EMS in four consecutive cyclone emergencies was analysed. The objective was to identify systemic failures of the managerial model and the lessons that should be learned and implemented as ‘organisational learning’ outcomes. Concepts from chaos theory were adopted for this purpose. They were found to be capable of explaining the behaviour of the EMS in large-scale emergencies. All the interview participants agreed that the government response to cyclones Phet and Luban in 2010 and 2018 was effective. In those events, responders did not experience unanticipated challenges and could sustain communication lines and deliver aid to affected areas. However, according to all participants, the official response to cyclones Gonu and Mekunu in 2007 and 2018 was perceived as ineffective. The operating environment during those events was characterised by the discontinuity of essential services such as roads, electricity and telecom. The formal EMS could not establish an accurate situational awareness and deliver aid where necessary. In those areas, an informal local-oriented self-organised system emerged to fill the gaps of the formal EMS. Findings show that the government command-and-control EMS is effective under normal conditions, associated with the continuity of essential services and the limitedness of the affected area, which characterised the operating environment in the first two events. However, it was found ineffective under extreme crises due to the excessive centralisation of resources and decision-making powers within the central government, excessive reliance on governmental resources, and a prevalent culture of response-centred management. In such extreme situations, informal local disaster management took place. These key findings call for (1) localising EM, (2) engaging non-state organisations such as volunteer societies and charities, and essential services providers lessons in EM, and (3) updating the assumptions under which the system would operate. Identifying and implementing those lessons show that the EMS learns and evolves from its own experiences while neglecting them shows the existence of learning impediments. The second analysis involved identifying and classifying post-disaster organisational and institutional changes. Findings show that single-loop learning was more prevalent in the case study, which does not entail changing management’s assumptions and norms. The main forms of this learning were changing the organisational structure, adopting new technologies and increasing government emergency resources. In contrast, double-loop learning, which includes implementing the above-required lessons for the system to evolve, has not occurred sufficiently. To identify the dynamics (i.e., the sources or drivers) of change, organisational learning theory and institutional change theory were combined in one analytical framework. Using qualitative thematic analysis as the primary data analysis method, a tension between forces that support changing the status quo and powers that resist and favour the continuation of the centralised, governmental, response-based EMS was found to exist. Exogenous sources – the experienced emergencies, social media prevalence and privatising essential services’ providers – pushed towards decentralising and localising management, engaging new actors and flattening the communication patterns. On the other hand, endogenous processes – historical circumstances of EM in the country, organisational culture and societal norms, and actors’ shared perceptions facilitated the continuation of the status quo. In conclusion, the context of the place is a more influential determinant of organisational double-loop learning to occur or not.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Organisational Learning and Dynamics of Institutional Change Following Large-Scale Emergencies: Oman’s Emergency Management System as a Case Study
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2023. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction
URI: https://discovery.ucl.ac.uk/id/eprint/10167006
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