Interagency Communication in Southeast Asian Disaster Governance: A Model Development Using Ism and Micmac Analysis

Interagency Communication in Southeast Asian Disaster Governance: A Model Development Using Ism and Micmac Analysis

Nur Haffiza Rahaman., Liley Afzani Saidi., Rayyan Cheong Tian Ming

Management Department, Universiti Pertahanan Nasional Malaysia, Malaysia

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000262

Received: 11 August 2025; Accepted: 20 August 2025; Published: 05 September 2025

ABSTRACT

Southeast Asia’s high vulnerability to natural hazards demands robust disaster governance mechanisms, with effective interagency communication as a central pillar for coordinated response. Despite regional frameworks such as the ASEAN Agreement on Disaster Management and Emergency Response (AADMER), persistent challenges including fragmented coordination, unclear responsibilities, and limited resource sharing undermine disaster management effectiveness. This study aims to determine and propose a consensus-based model for interagency communication in Southeast Asian disaster governance using Interpretive Structural Modeling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. Expert input from seven professionals in communication, disaster management, and information technology was integrated through the Nominal Group Technique (NGT) to identify seven key approaches: Coordination and Cooperation, Information Sharing, Institutional Relationships, Strategic Communication, Capacity Building, Use of Technology, and Legal and Policy Frameworks. The Structural Self-Interaction Matrix (SSIM) and Reachability Matrix (RM) quantified the driving and dependence powers of these variables. Results show Information Sharing, Strategic Communication, and Capacity Building with the highest driving power (7), indicating their central role as systemic enablers, while Use of Technology had the lowest (3), acting more as a dependent enabler. Level Partitioning positioned all variables at Level 1, revealing a highly integrated network without hierarchical tiering. The MICMAC analysis placed all seven variables in Quadrant III (Linkage Variables), indicating high driving and high dependence powers, where changes in any element could produce cascading effects throughout the system. The study concludes that strengthening interagency communication in Southeast Asian disaster governance requires simultaneous, multi-pronged interventions across all seven approaches, with priority given to enhancing Information Sharing, Strategic Communication, and Capacity Building within strong legal and technological frameworks. The proposed ISM–MICMAC model offers a decision-support tool for policymakers to foster resilient, adaptive, and collaborative disaster governance.

Keywords: Interagency communication, Disaster governance, Southeast Asia, Interpretive Structural Modeling (ISM), MICMAC analysis, Strategic communication,

INTRODUCTION

Southeast Asia is one of the most disaster-prone regions in the world, facing frequent natural hazards such as earthquakes, tsunamis, and typhoons. The region’s vulnerability necessitates robust disaster governance mechanisms to mitigate the impacts of these events. The Association of Southeast Asian Nations (ASEAN) has been at the forefront of regional disaster management efforts, establishing frameworks like the ASEAN Agreement on Disaster Management and Emergency Response (AADMER) and the ASEAN Coordinating Centre for Humanitarian Assistance on Disaster Management (AHA Centre) to facilitate cooperation and coordination among member states (Coe & Spandler, 2022; L. et al., 2021; Simm, 2018). These initiatives aim to enhance regional resilience and ensure a coordinated response to disasters.

Effective interagency communication is crucial for successful disaster governance in Southeast Asia. The complexity of disaster management requires seamless coordination among various governmental and non-governmental organizations, both within and across national borders. Studies have highlighted the importance of developing strong communication systems before disasters occur to ensure effective interagency coordination during emergencies (Kapucu, 2006; Liu et al., 2021). The integration of information technologies and the establishment of communication redundancies are essential to facilitate the rapid dissemination of critical information and improve decision-making processes (Heinkel et al., 2025; Zhu et al., 2025). Moreover, the involvement of local communities and civil society organizations in disaster preparedness and response efforts can significantly enhance resilience and ensure that the needs of vulnerable populations are addressed (Okunola, 2025; Sugiana et al., 2025).

Despite the progress made, several challenges remain in achieving effective interagency communication in Southeast Asian disaster governance. Issues such as unclear division of responsibilities, limited resource sharing, and political constraints can hinder coordination efforts (Gong, 2021; Zhu et al., 2025). Additionally, the transnational nature of many disasters requires cooperation among multiple countries, which can be complicated by differing national priorities and capacities (Caballero-Anthony, 2011; Kanteler & Bakouros, 2024). Addressing these challenges requires a comprehensive approach that includes capacity-building initiatives, the development of institutional frameworks for coordination, and the promotion of trust and collaboration among all stakeholders involved in disaster management (Okunola, 2025; Trias & Cook, 2021).

LITERATURE REVIEW

Introduction to Disaster Governance in Southeast Asia Southeast Asia is highly vulnerable to natural disasters, necessitating robust disaster governance mechanisms. The Association of Southeast Asian Nations (ASEAN) has been pivotal in this regard, particularly through the ASEAN Agreement on Disaster Management and Emergency Response (AADMER) and the ASEAN Coordinating Centre for Humanitarian Assistance on Disaster Management (AHA Centre. These frameworks aim to enhance regional cooperation and resilience by facilitating coordination among member states and managing extraregional aid (Coe & Spandler, 2022; L. et al., 2021; Simm, 2018). The AHA Centre empowers ASEAN states to control external humanitarian assistance, thereby transforming international humanitarian authority dynamics in favor of regional actors (Coe & Spandler, 2022).

Challenges in Interagency Communication Effective interagency communication is critical for disaster management, yet it faces several challenges. Factors such as institutional constraints, capacity limitations, and political influences can hinder communication and coordination efforts. For instance, China’s disaster diplomacy in Southeast Asia has shown mixed results due to these constraints, affecting the mobilization and acceptance of aid (Gong, 2021). Additionally, the governance of disaster response in Indonesia highlights the importance of coordination among various actors, information sharing, and resource management to address the complexities of disaster scenarios (Trias & Cook, 2021). These challenges underscore the need for pre-established communication systems to ensure effective interagency coordination during emergencies (Kapucu, 2006).

Role of Information Technologies and Social Media Information technologies and social media play a significant role in enhancing interagency communication and decision-making during disasters. Studies have shown that tailored communication strategies that resonate with local cultures and involve community participation can significantly improve disaster preparedness and response (Sugiana et al., 2025). Social media, in particular, has proven to be a resilient communication tool when traditional networks fail, facilitating real-time information sharing and coordination among agencies and the public (Simon et al., 2015). The use of digital tools and geospatial platforms can further bridge information gaps and foster regional cooperation (van den Homberg, 2017).

Strategies for Improving Interagency Communication To improve interagency communication in disaster governance, several strategies can be adopted. Building strong communication systems before disasters occur is crucial for ensuring effective coordination during emergencies (Kapucu, 2006). Enhancing community engagement through educational programs and innovative communication approaches can also foster a culture of preparedness and resilience (Sugiana et al., 2025). Additionally, leveraging social media and other digital tools for information sharing and collaboration can enhance the overall effectiveness of disaster management efforts (Simon et al., 2015). By addressing these communication barriers and adopting best practices, Southeast Asian countries can strengthen their disaster governance frameworks and improve their response to natural hazards. In conclusion, interagency communication is a vital component of disaster governance in Southeast Asia. While challenges exist, the use of information technologies, community engagement, and pre-established communication systems can significantly enhance coordination and response efforts. By continuing to develop and implement these strategies, ASEAN and its member states can build a more resilient and effective disaster management system.

Research objective

There are two main objectives in writing this article.

1. To determine interagency communication in southeast asian disaster governance model based on expert consensus.
2. To propose the interagency communication in southeast asian disaster governance consensus.

METHODOLOGY

This study employs ISM and MICMAC analyses, incorporating expert input to identify and examine the interrelationships interagency communication in southeast asian disaster governance. Through this process, a hierarchical structure of factors, as recognized by experts, is established. ISM, initially advanced by Warfield (1974) and Sage (1977), is designed to address complex problems or systems with multiple interconnected elements. It is particularly suited for structured group problem-solving methods such as the Nominal Group Technique (NGT), Focus Group Technique (FGT), brainstorming, and focus group discussions (Prasad et al., 2020). The ISM method enables the construction of an organized hierarchical model from a set of variables or components that may exert both direct and indirect influences on one another (Attri, Singh, & Mehra, 2017). As ISM requires group interpretation and decision-making, it is considered interpretative; its ability to simplify the structure of complex issues makes it structural. Modelling is integral to ISM, as each model or digraph represents a distinct configuration of relationships. ISM has been widely applied across various domains, including manufacturing (Singh & Khamba, 2011), education (Muhammad Ridhuan et al., 2014), policy (Kumar et al., 2018), environmental management (Chandramowli et al., 2011), and the aviation industry (Pitchaimuthy et al., 2019). Based on figure 1, the ISM approach follows a structured sequence of steps:

1. Identify the appreciating diversity competency (ADC) through a structured review and discussions with expert panels or by synthesizing relevant literature.
2. Develop the Structural Self-Interaction Matrix (SSIM) by conducting pair-wise comparisons of variables agreed upon and ranked by experts during the Nominal Group Technique (NGT) session. Variables are denoted by symbols V, A, X, and O, which indicate the direction of relationships between variables i and j: (i) to produce an appropriate Digital Ethics Guideline (DEG) model for educational leaders; (ii) V means ADC i is more important than ADC j; (iii) A means DEG j is more important than ADC i; (iv) X means ADC i and j are equally important and related; and (v) O means DEG i and j are unrelated.
3. Construct the final Reachability Matrix (RM) from the SSIM by converting V, A, X, and O into binary values based on these rules: (i) if (i, j) is V, then (i, j) = 1 and (j, i) = 0; (ii) if (i, j) is A, then (i, j) = 0 and (j, i) = 1; (iii) if (i, j) is X, then both (i, j) and (j, i) = 1; (iv) if (i, j) is O, then both (i, j) and (j, i) = 0.
4. Perform level partitioning of the matrix.
5. Develop the hierarchical relationship digraph from the final RM to form the ISM model.
6. Apply Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis to categorize variables into clusters based on their driving and dependence power.

Figure 1: ISM Step

Sample

For this research, we enlisted the help of sex education experts for ISM sessions. Six professional experts were willing to take part in the research. The experts from different education divisions and public sector organizations are profiled in Table 1,  according to their area of knowledge and academic degree

Table 1: Expert Fields Expertise

Data Analysis

Finding from step 1

For the first step, the researcher interviewed experts and reviewed some literature to determine the elements or steps that can be taken to implement Interagency Communication in Disaster Governance (ICDG). The results are as follow.

Table 2: Elements / Guidelines for Interagency Communication in Disaster Governance (ICDG)

Figure 2 : Approach Interagency Communication in Southeast Asian Disaster Governance

Finding from step 2

The Structural Self-Interaction Matrix (SSIM) illustrates the contextual relationships among seven key variables influencing interagency disaster governance. Based on table 3, the matrix uses the symbols V, A, and X to indicate directional influence: “V” shows that the row variable influences the column variable, “A” denotes the opposite (column influences row), and “X” indicates mutual influence. From the table, Coordination and Cooperation (Variable 1) is primarily influenced by Information Sharing (2) and Strategic Communication (4), while it influences Institutional Relationships (3), Capacity Building (5), and Legal and Policy Frameworks (7). Information Sharing emerges as a strong driver, influencing most variables (3, 4, 5, 6) while receiving influence from Institutional Relationships (3). Institutional Relationships shows a balanced interplay, mutually influencing Strategic Communication (4) but driving Capacity Building (5) and Legal and Policy Frameworks (7). Strategic Communication has reciprocal relationships with both Information Sharing and Institutional Relationships and drives Capacity Building. Capacity Building influences Use of Technology (6), which in turn shapes Legal and Policy Frameworks (7). This structure indicates that effective governance hinges on a chain of interconnected drivers, where Information Sharing and Strategic Communication play central bridging roles linking institutional and operational capacities.

Table 3: Structural Self Interaction Matrix (SSIM)

Finding from step 3 (Reachability matrix)

The Reachability Matrix (RM) presents the binary relationships derived from the SSIM, quantifying each variable’s driving power (the number of other variables it influences, including itself) and dependence power (the number of variables influencing it). From table 4 ,the results show that Information Sharing (2), Strategic Communication (4), and Capacity Building (5) have the highest driving power (7), indicating they are strong drivers that significantly shape the system. Legal and Policy Frameworks (7) also has a high driving power (6), reflecting its broad influence. Coordination and Cooperation (1) and Institutional Relationships (3) are moderate drivers (5), suggesting they play supporting but important roles. Use of Technology (6) has the lowest driving power (3), meaning it is more of a dependent variable rather than a driver in the system. On the dependence side, Strategic Communication (4) and Capacity Building (5) show high dependence values (7), suggesting they are both highly influenced by and influential to other factors—making them central connecting variables. This distribution indicates that enhancing Information Sharing and Strategic Communication, while embedding them in robust Capacity Building and Legal and Policy Frameworks, could yield the most substantial improvements in interagency disaster governance.

Table 4: Reachability Matrix (RM)

Finding from step 4 & 5

The Level Partitioning (LP) table 5, shows that all seven elements Coordination and Cooperation, Information Sharing, Institutional Relationships, Strategic Communication, Capacity Building, Use of Technology, and Legal and Policy Frameworks share identical Reachability Sets, Antecedent Sets, and Intersection Sets, each containing all variables (1 to 7). Consequently, every element is assigned to Level 1, indicating that in this iteration of ISM analysis, all factors are positioned at the same hierarchical level without a clear tiered dependency structure. This outcome suggests a high degree of interconnectivity and mutual influence among the variables, where each factor is both reachable from and influences all others. While such uniformity reflects strong systemic integration, it may also indicate the need for further refinement of the SSIM or RM to reveal more distinct hierarchical layers for clearer model interpretation in disaster governance contexts.

Table 5 The Level Partitioning (LP)

Figure3: Model Digraph (ISM output)

The ISM digraph model from figure 3,  illustrates a fully interconnected, sequential relationship among the seven key variables influencing interagency disaster governance: Coordination and Cooperation, Information Sharing, Institutional Relationships, Strategic Communication, Capacity Building, Use of Technology, and Legal and Policy Frameworks. Each variable is bidirectionally linked with its immediate neighbors, signifying mutual influence and feedback loops within the system. This structure reflects a tightly coupled governance framework in which improvements or disruptions in one element are likely to cascade across the network. For instance, strengthening Information Sharing not only enhances Institutional Relationships but also indirectly reinforces Strategic Communication and downstream capacities. Conversely, weaknesses in Use of Technology could hinder Capacity Building and compromise the effectiveness of Legal and Policy Frameworks. The model’s linear from figure 4, reciprocal connections highlight the necessity for balanced, simultaneous enhancement across all variables to achieve robust, adaptive disaster governance in the Southeast Asian context.

Figure 4: Model of Interagency Communication in Southeast Asian Disaster Governance

Finding from step 6 (MICMAC analysis)

From  figure 5, the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis follows a similar approach to that implemented by  Singh et al., (2024), serving as a systematic technique to evaluate and categorize variables based on their driving and dependence powers. The primary objective is to identify and map the critical factors influencing interagency communication in Southeast Asian disaster governance, thereby revealing how these variables interact within a complex governance framework. By plotting variables into the MICMAC matrix, the analysis highlights their relative influence and interdependence, enabling the identification of those that act as key drivers, strong dependencies, or highly interactive linkage elements. This classification provides valuable insights for prioritizing strategic interventions, ensuring that efforts to strengthen disaster governance target the most influential and interconnected components of interagency communication.

Figure 5: MIMAC Analyze

The MICMAC analysis scatter plot positions all seven variables Coordination and Cooperation, Information Sharing, Institutional Relationships, Strategic Communication, Capacity Building, Use of Technology, and Legal and Policy Frameworks in the Quadrant III (Linkage Variables) zone, indicating that they possess both high driving power and high dependence power. This placement signifies that these variables are highly interactive and interdependent, where changes in one factor can produce significant cascading effects both influencing and being influenced by others. Linkage variables are typically unstable because any action on them will affect others and, in turn, feedback to themselves, potentially amplifying positive or negative impacts within the system. The absence of variables in the autonomous, dependent, and independent quadrants highlights a governance system characterized by strong systemic coupling, where coordinated and simultaneous development across all dimensions is essential to avoid imbalances that could disrupt overall disaster governance performance.

Key Finding

The analysis identified seven interrelated approaches essential to strengthening interagency communication in Southeast Asian disaster governance: (1) Coordination and Cooperation, (2) Information Sharing, (3) Institutional Relationships, (4) Strategic Communication, (5) Capacity Building, (6) Use of Technology, and (7) Legal and Policy Frameworks. The Structural Self-Interaction Matrix (SSIM) revealed strong mutual relationships between consecutive variables, reflecting a tightly connected system where each element influences and is influenced by others. Information Sharing and Strategic Communication emerged as pivotal bridging elements, linking institutional frameworks with operational practices. The Reachability Matrix (RM) further quantified these relationships, showing that Information Sharing, Strategic Communication, and Capacity Building have the highest driving power (7), indicating their critical role as system drivers. Legal and Policy Frameworks also scored high (6), emphasizing its foundational influence. In contrast, Use of Technology recorded the lowest driving power (3), suggesting it functions more as an enabler rather than a core driver. Dependence power values revealed that Strategic Communication and Capacity Building are both highly influenced by and exert significant influence on other factors, placing them at the center of systemic interactions.

Level Partitioning results placed all variables at Level 1, indicating no hierarchical tiering but rather a highly integrated structure. This was visually reflected in the ISM digraph, where all variables are linearly connected with bidirectional influence, underscoring the need for simultaneous, coordinated development across all dimensions. The MICMAC analysis classified all seven variables within Quadrant III (Linkage Variables), signifying that they possess both high driving and high dependence powers. This placement highlights the dynamic and potentially unstable nature of the system where interventions in any single variable will have ripple effects across all others and may feedback to affect the initiating factor. Such interdependence demands holistic strategies rather than isolated interventions. Overall, the findings emphasize that effective interagency communication in Southeast Asian disaster governance relies on a network of mutually reinforcing elements. Strengthening Information Sharing, Strategic Communication, and Capacity Building while embedding them within robust Legal and Policy Frameworks and supported by appropriate Technology is essential for enhancing governance resilience. The high interconnectivity observed suggests that strategic improvements must be coordinated across all seven approaches to avoid systemic imbalance and ensure sustainable disaster management outcomes.

CONCLUSION

This study set out to develop an interagency communication model for Southeast Asian disaster governance using Interpretive Structural Modeling (ISM) and MICMAC analysis. The results highlight that seven critical approaches Coordination and Cooperation, Information Sharing, Institutional Relationships, Strategic Communication, Capacity Building, Use of Technology, and Legal and Policy Frameworks form a highly interconnected system in which each element both influences and is influenced by the others. The ISM analysis revealed that these variables operate without hierarchical tiering, underscoring the fact that effective disaster governance in the region requires a simultaneous and coordinated approach across all dimensions rather than a sequential or siloed implementation strategy.

The Reachability Matrix (RM) and MICMAC analysis further emphasized the systemic interdependence of these approaches. Information Sharing, Strategic Communication, and Capacity Building emerged as high-driving-power variables, indicating their central role in enabling and sustaining effective governance. At the same time, all variables were classified as linkage factors within Quadrant III of the MICMAC framework, confirming their dual nature as both influencers and dependents. This mutual reinforcement is a strength for integrated governance but also a potential vulnerability, as changes positive or negative in one variable can cascade throughout the entire system.

From a practical standpoint, the findings underscore the need for policymakers, disaster managers, and interagency coordinators to prioritize capacity-building programs, invest in robust communication systems, and strengthen institutional frameworks. Enhancing the technological backbone for disaster communication while ensuring alignment with legal and policy directives can further consolidate the region’s preparedness and response capabilities. Importantly, the emphasis on linkage variables suggests that any interventions must be multi-pronged, addressing several elements concurrently to avoid destabilizing the system and to maximize the positive ripple effects across interconnected components.

Ultimately, this research contributes a structured, evidence-based model that can serve as a decision-support tool for ASEAN member states and other stakeholders in disaster governance. By applying ISM–MICMAC analysis, the study offers a replicable framework for understanding complex interagency dynamics and prioritizing strategic interventions. Future research could refine the model by incorporating a broader range of stakeholders, conducting longitudinal studies to capture evolving relationships, and testing the framework in real disaster scenarios. Strengthening interagency communication through this integrated model has the potential to enhance regional resilience, minimize disaster impacts, and foster a more adaptive and collaborative governance system for Southeast Asia.

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