A socio-technical analysis of barriers to effective emergency response systems in facilities: evidence from Ghana Open Access

Sub-Saharan Africa faces increasing natural and human-induced emergencies, such as floods, fires, epidemics and industrial accidents, leading to significant loss of lives and properties (Fu et al., 2024; Adjei et al., 2025a, 2025b). Outdated and inadequate emergency response systems intensify these events. Poor infrastructure hampers timely interventions and worsens disaster outcomes, particularly in densely populated, socioeconomically vulnerable areas. Delayed evacuations, especially involving children and older adults, remain a key factor in preventable fatalities (Ding et al., 2021).

Globally, resilience is a strategic priority. For instance, U.S. national security policy stresses the need for systems to absorb, adapt and recover from shocks (Longstaff et al., 2010). In many African cities, infrastructural fragility and institutional inefficiencies hinder infrastructure resilience. While global research has examined barriers to emergency response systems, including evacuation constraints (Wang et al., 2021), high-rise fire risks (Egodage et al., 2020) and inter-agency coordination challenges (Soltaninejad et al., 2023), these studies are largely situated in technologically advanced or contextually dissimilar environments. Incidents like the Dongdu Commercial Building fire in China, which killed 309 people, underscore the stakes, yet comparable empirical investigations within Sub-Saharan facility contexts remain limited.

While prior studies have advanced knowledge on interdependent infrastructure systems (Ouyang, 2014), emergency technology integration (Damaševičius et al., 2023) and early warning systems (Sutton et al., 2024), they often focus on isolated technical or operational dimensions. Existing regional studies also tend to emphasise broader disaster management systems without sufficiently interrogating facility-level barriers or the interaction between social, institutional and technical factors. Consequently, critical issues such as governance inefficiencies, socio-cultural dynamics, rapid urbanisation and institutional fragmentation remain underexplored within a unified analytical framework. This study is grounded in a socio-technical systems perspective, which conceptualises emergency response systems as the interaction between social components (e.g. institutions, policies, cultural norms and human capacity) and technical components (e.g. infrastructure, technologies and operational systems). This lens emphasises that system performance is shaped not by isolated elements, but by the interdependence between these social and technical subsystems.

This study addresses these gaps by adopting a socio-technical perspective to investigate barriers to emergency response systems in facilities within Sub-Saharan Africa, using Ghana as a case study. It specifically examines how institutional, technical, socio-political and financial constraints interact to influence system effectiveness. Identifying these barriers to emergency response infrastructure is crucial for guiding evidence-based reforms, policy actions and strategic investments. Critical facilities, such as hospitals, schools, commercial centres and public institutions, are vital to national security and public well-being, and their failure during emergencies can cause cascading impacts. With rapid urbanisation and rising climate risks, the urgency for resilient, adaptive and inclusive emergency systems continues to grow (Abudu et al., 2025a, 2025b, 2025c). This study is thus positioned to fill a critical knowledge gap by revealing the multi-dimensional challenges facing emergency response infrastructure in under-resourced contexts. Its findings will inform policy, guide institutional reforms and support the development of a sustainable and locally grounded emergency management system.

Emergencies, whether from natural disasters, health crises, accidents or security threats, pose major risks to public safety, national stability and critical infrastructure (Wang et al., 2021). These unpredictable events demand immediate, coordinated responses to rescue victims and meet urgent needs (Dwarakanath et al., 2021). Vulnerability, as defined by Deen (2015), refers to the capacity to anticipate, endure and recover from hazards. Effective emergency systems rely on the rapid deployment of personnel and resources to vital infrastructure such as hospitals, schools, power grids and transport systems, ideally designed to withstand or adapt to environmental and man-made threats (Gilmore and DuRant, 2021).

Emergency response infrastructure is shaped by the interaction between social elements (people, cultural norms and institutions) and technical elements (infrastructure, equipment and digital systems). The effectiveness of these systems depends on their integration rather than on their individual capabilities. Misalignment can create barriers that hinder preparedness and response efficiency. Rapid urbanisation, particularly in low- and middle-income countries, exacerbates these challenges, as urban growth often outpaces infrastructure development, increasing vulnerability (Wamsler et al., 2020; Abdul and Yu, 2020). High population densities and inadequate shelter amplify disaster risks (Ajibade, 2022). With urban areas projected to hold over 60% of the global population by 2030, including 800 million informal settlers (Rezvani et al., 2023), the urgency for resilient emergency systems is critical. Poor infrastructure planning often leads to overwhelmed facilities and hampers effective evacuation and coordination efforts, while uncertainty about hazards can deter proactive investment (Pelling, 2012).

Chronic shortages of financial and human resources hinder disaster risk reduction (DRR) education in many developing regions, limiting preparedness (Kalogiannidis et al., 2022). Municipalities often lack resources and capacity for comprehensive strategies (Pelling, 2012). Inadequate equipment and personnel can delay responses, especially in underserved areas (Anguelovski et al., 2014). While some cities, like Gimpo, South Korea, invest in smart technologies and partnerships (Myeong et al., 2020), such innovations are scarce in the developing world. Emergency systems investments should reflect national priorities and risk assessments (Bello et al., 2021), but competition for funds often neglects long-term infrastructure, weakening mass casualty responses (Binkley and Kemp, 2022). These challenges show how urban growth, limited institutional capacity and inadequate infrastructure collectively constrain emergency response effectiveness.

Structural vulnerabilities, such as poor housing, informal settlements and ageing infrastructure, intensify disaster impacts. These stem from environmental conditions and socio-economic inequalities that limit communities’ capacity to prepare for and recover from hazards (Bello et al., 2021). Floods disproportionately affect low-income households, damaging property and health while deepening poverty (Deen, 2015). Outdated planning frameworks fail to address evolving urban risks (Pelling, 2012), and urbanisation that neglects vulnerable populations further increases exposure (Anguelovski et al., 2014). Climate change has also heightened the frequency of hazards such as river overflows and extreme rainfall.

Post-disaster, urban populations face food insecurity, disease outbreaks and economic disruption (Al-Wathinani et al., 2023). Cross-sectoral disaster risk management (DRM) strategies, including spatial planning and community preparedness, remain weak in much of Sub-Saharan Africa (Binkley and Kemp, 2022), while infrastructure deficits hinder response efficiency. Resilient systems require regular risk assessment and adaptation (Al-Wathinani et al., 2023). Innovations such as big data platforms, closed-circuit television (CCTV) and internet of things (IoT) can enhance real-time monitoring (Myeong et al., 2020), yet emergencies still cause overcrowding and resource shortages. Vulnerable populations often lack communication infrastructure for early warnings (Perera et al., 2020). Saudi Arabia’s infrastructure modernisation highlights effective strategies for improving resilience (Al-Wathinani et al., 2023).

Strengthening schools, hospitals, and emergency centres is essential for resilience (Al-Wathinani et al., 2023). Adaptive urban systems require climate-informed planning and investment in resilient infrastructure (Travassos et al., 2021), alongside capacity building for responders and facility managers (Al-Wathinani et al., 2023). Diversified systems enhance resilience, while reliance on a single infrastructure increases risk (Pelling, 2012). Effective early warning systems support timely response (Al-Wathinani et al., 2023), but poorly maintained infrastructure delays recovery and increases long-term socio-economic impacts. From a socio-technical lens, these structural vulnerabilities reflect the interaction between weak regulatory systems (organisation), socio-economic inequalities (people) and fragile infrastructure (technology), which together amplify disaster impacts.

Emerging technologies can transform disaster response, but implementation challenges limit their effectiveness. Many emergency telecom systems, including advanced 9–1 - 1, remain outdated and unprepared for modern threats (Gilmore and DuRant, 2021). Digital tools and geospatial data improve coordination and risk mapping, yet technological complacency and poor scenario planning hinder responses to climate-induced events (Travassos et al., 2021). Effective systems must rapidly identify and monitor individuals in distress (Gilmore and DuRant, 2021). The Internet of Emergency Services (IoES) enables real-time data sharing and coordination through IoT (Damaševičius et al., 2023). However, upgrading technologies, improving user capacity and strengthening institutional support are essential, underscoring the interdependence of technology, people and organisations (Damaševičius et al., 2023).

Political structures strongly influence emergency response outcomes. Actors at the national, local and community levels shape DRR through policies and preparedness initiatives (Rezvani et al., 2023). However, short-term relief often outweighs long-term mitigation, with resources favouring politically influential areas, creating disparities (Deen, 2015). Initiatives like South Korea’s “e-Government 2020” show how digital governance enhances transparency (Myeong et al., 2020), while threats such as terrorism require integrated security measures (Binkley and Kemp, 2022). Nonetheless, weak political will and bureaucratic inefficiencies undermine preparedness and response effectiveness (Perera et al., 2020).

Urban planning often overlooks DRM, and public investment rarely prioritises risk reduction (Travassos et al., 2021). Political inefficiencies arise from tensions between economic growth and environmental protection (Pelling, 2012). Effective systems require strong leadership, coordination and inclusive governance, yet aligning innovation with governance remains challenging (Myeong et al., 2020). Although land use policies and building regulations are essential, weak implementation in developing countries leads to substandard construction (Abdul and Yu, 2020). While the Building Code (BC) promotes resilience and risk reduction (Al-Wathinani et al., 2023), enforcement is inconsistent, despite the importance of mandatory standards for critical infrastructure (Bello et al., 2021). These gaps reveal misalignments in the socio-technical system that impair both human capacity and technological effectiveness.

Although legal frameworks increasingly acknowledge innovative urban planning, DRM is not consistently embedded in policy or regulation (Wamsler et al., 2020). Bureaucratic inefficiencies and regulatory bottlenecks delay critical interventions. Without legal mandates for agile coordination, agencies face major constraints. Human resource limitations further compromise response capacity. Despite growing partnerships, staff shortages persist, limiting deployment and coverage (Wamsler et al., 2020). A lack of trained personnel and dedicated funding weakens operational readiness. Disaster knowledge and preparedness also remain low at the local level. Public understanding of nature-based or climate-resilient solutions is limited, leading to weak emergency plans (Wamsler et al., 2020).

Cultural and religious norms shape emergency dynamics. These social factors influence how individuals and communities interact with emergency technologies and institutional systems, further reinforcing the importance of integrating people, technology, organisation and environment in understanding emergency response barriers. In some communities, fatalistic beliefs hinder preparedness, whereas others show strong self-reliance. Faith-based institutions often aid awareness and shelter efforts, yet cultural restrictions such as gender-based mobility limits can delay evacuations (Wamsler et al., 2020). Community involvement is vital for effective DRM. Initiatives like early warning systems and participatory planning enhance local awareness (Pelling, 2012; Perera et al., 2020). Still, vague roles and inconsistent outreach limit engagement. Urban efforts, such as climate committees have emerged (Anguelovski et al., 2014), but sustained inclusion is needed. Leveraging local knowledge is critical to tailoring interventions and improving overall system effectiveness (Al-Wathinani et al., 2023).

A summary of the barriers to emergency response infrastructure is presented in Table 1.

This study used a quantitative research strategy to investigate barriers to emergency response systems in facilities in Ghana. The approach enabled the collection of measurable data and analysis of relationships among variables. A survey research design was adopted, using structured questionnaires administered to professionals involved in emergency response and facility management, such as engineers, architects, facility managers, quantity surveyors, building inspectors and National Disaster Management Organisation (NADMO) officers across 43 administrative districts in the Ashanti Region. The target population was 516, with a sample size of 225 determined using Yamane’s formula (1967). A pilot study with 30 participants from district assemblies and academia validated the instrument. Non-probability sampling, specifically purposive and convenience techniques, ensured participation by experienced professionals and practical data collection during piloting. The questionnaire included both closed-ended items, with responses rated on a five-point Likert scale.

Data were cleaned, coded and normalised using Min-Max scaling, then analysed in SPSS (v30). Descriptive statistics summarised respondent profiles and responses. Exploratory Factor Analysis (EFA) using Principal Component Analysis (PCA) to identify latent variables. Factor retention was guided by KMO ≥ 0.6 and Bartlett’s Test (p < 0.05) (Hair et al., 2016), eigenvalues ≥ 1 and factor loadings ≥ 0.5 (Hair et al., 2016; Lesia et al., 2024). Cronbach’s alpha (≥0.7) ensured reliability (Lesia et al., 2024). The Normalisation Value (NV) analysis standardises barriers’ values on a scale from 0 to 1, where the highest mean value is 1, and the lowest is 0. The formula is: (Mean value – Min mean value)/(Max mean value – Min mean value). An NV ≥ 0.60 indicate critical barriers to emergency response in facilities, as supported by Adjei et al. (2025a, 2025b). Content and construct validity were verified through expert review and factor analysis. Ethical standards were upheld, with voluntary, anonymous participation and Institutional Review Board approval (Clearance No. IREC 287 / 24).

The key demographic data, including participants’ education, professional roles, facility types and years of experience, factors that establish respondent credibility in relation to emergency response and built environment systems. As shown in Table 2, 67.3% of respondents hold either a bachelor’s degree (34.6%) or a Higher National Diploma (32.7%), with 17.6% possessing a master’s degree. This reflects a well-qualified sample capable of engaging in complex infrastructure and crisis management issues. Professionally, engineers dominate the sample (66.7%), followed by quantity surveyors (17.6%), NADMO officers (7.5%) and building inspectors (5.7%). Facilities managers (1.9%) and architects (0.6%) are minimally represented. The strong technical focus is complemented by NADMO officials, who bring operational disaster management insights.

Participants primarily work on commercial facilities (42.1%), with additional involvement in religious (13.8%), recreational (13.8%) and educational (11.9%) buildings. Healthcare (6.3%) and industrial (3.1%) facilities are less represented, possibly limiting insights into sector-specific emergency needs. Work experience is well-distributed, with 30.2% having 1–5 years, while others span various experience levels.

This section provides a descriptive analysis of barriers to emergency response infrastructure. Variables were ranked within sub-constructs using mean scores, standard deviations and NV in Table 3. Where mean scores matched, lower standard deviations indicated higher priority, reflecting more consistent respondent perceptions.

Mean scores for barriers to emergency response infrastructure ranged from 3.82–4.25, indicating varying levels of agreement. The top three barriers were “Ineffective building by-laws” (4.25), “Inadequate consideration of social, cultural, and religious norms” (4.20), and “Political influence” (4.17), highlighting the need for regulatory updates, inclusive planning, and effective governance. Other notable barriers included “Limited resources and funding” (4.17), “Vulnerability to natural disasters” (4.16), “Lack of knowledge or capacity” (4.16), “Inadequate institutions/organisations” (4.14), “Rapid urbanisation and population growth” (4.12), and “Lack of capacity building” (4.09). Lower-ranked barriers included “Lack of human resources” (4.03), “Inadequate infrastructure” (4.02), “Policy/legal issues” (3.98), “Lack of community engagement” (3.93), “Lack of technology” (3.88), and “Lack of coordination among stakeholders” (3.82). Nine barriers exceeded the NV threshold of 0.60, encompassing building by-laws, socio-cultural norms, political influence, funding limitations, disaster vulnerability, capacity deficits, institutional weaknesses, rapid urbanisation and lack of capacity building. Overall, findings underscore the urgency of policy enforcement, culturally responsive planning, adequate resourcing and targeted capacity building.

Barriers to emergency response were analysed using EFA with PCA extraction. Prior diagnostics included the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test of sphericity to confirm data suitability. Following Schreiber (2021) and Lesia et al. (2024), a KMO ≥ 0.70 validates EFA use. The results showed a high KMO of 0.934 and a significant Bartlett’s test (p < 0.05), confirming sampling adequacy and factorability (Table 4). Communality extraction revealed variance explained between 0.562 and 0.756, surpassing the 0.50 threshold, indicating substantial variance captured per indicator. Factor loadings, representing correlations between variables and components, all exceeded 0.50. One component labelled “socio-technical barriers to emergency response” comprised 15 indicators and accounted for 66.12% of the total variance, demonstrating a robust factor structure.

The scree plot in Figure 1 displayed an inflexion at point two, where the curve flattened, indicating a break. Factors above this point are considered significant contributors to variance, suggesting that a single component should be retained in the model based on this threshold.

The demographic profile of respondents in Table 2 highlights the educated workforce shaping emergency response infrastructure in Ghana. Most have advanced degrees: 34.6% hold bachelor’s degrees, 32.7% hold Higher National Diplomas and 17.6% hold master’s degrees. Engineers make up 66.7% of respondents, reflecting a strong technical focus, while NADMO officers comprise only 7.5%, indicating a potential disconnect between policy and technical implementation. Respondents primarily work in commercial (42.1%), religious (13.8%), recreational (13.8%) and educational (11.9%) facilities, with residential sectors, often the most vulnerable, representing just 8.8%. Experience levels vary, with 30.2% having 1–5 years in the sector, fostering a blend of innovation and expertise. Overall, the demographics reveal strengths and gaps in infrastructure efforts, suggesting that new ideas are needed to enhance Ghana’s emergency response systems.

Modernising emergency response infrastructure requires identifying key barriers to effective implementation. This study identified 15 barriers in Ghanaian facilities, with nine critical barriers (NV ≥ 0.60) explaining a substantial proportion of the variance (Table 3). Key barriers include ineffective building by-laws, socio-cultural factors, political influence, limited resources, disaster vulnerability, capacity gaps, weak institutions, rapid urbanisation and lack of capacity building.

The EFA revealed a single dominant component, labelled socio-technical barriers to emergency response, comprising all 15 indicators and explaining 66.12% of the total variance. This indicates that the barriers are interrelated, reflecting interactions between social and technical factors shaping emergency response effectiveness. Ineffective building by-laws are the top barrier (Mean = 4.25, NV = 1.000), highlighting the need for robust and enforceable regulations. Abdul and Yu (2020) emphasise that poor enforcement in developing countries results in unsafe buildings and increased disaster risk. In Ghana, issues such as corruption and weak inspections exacerbate the problem. Although the National Building Code sets important standards for safety and efficiency, local implementation is lacking. Bello et al. (2021) stress that strong building standards are essential for reducing hazards and ensuring societal stability during crises. Weak bylaws increase vulnerability and complicate emergency responses, leading to higher risks of collapse and casualties. A socio-technical perspective reveals that inadequate regulations result in unsafe structures and hinder effective emergency response.

Inadequate consideration of social, cultural, and religious norms ranked second (Mean = 4.20, NV = 0.884). Disaster preparedness is limited in faith-based or conservative communities, which perceive disasters as divine will, thereby reducing proactive engagement (Abudu et al., 2026). Community-Based Organisations can promote culturally sensitive strategies that enhance trust and participation. Integrating social norms into planning strengthens disaster governance and improves responsiveness. This highlights how social behaviours and belief systems interact with technical emergency systems, where ineffective risk communication technologies or warning systems fail when not aligned with the community norms.

Political influence (Mean = 4.17, NV = 0.814) and limited resources and funding (Mean = 4.17, NV = 0.814) ranked third and fourth. Political interference prioritises partisan interests over technical expertise, affecting appointments, resource allocation and policy execution, thus undermining institutional credibility (Deen, 2015; Rezvani et al., 2023). Resource constraints impede preparedness and emergency management, reflecting broader findings in the literature (Pelling, 2012; Anguelovski et al., 2014). Successful international examples, like South Korea’s Smartopia Gimpo project, highlight the impact of targeted investments on emergency responsiveness (Myeong et al., 2020). These findings demonstrate socio-technical interdependencies, where governance failures (social) restrict investment in critical technologies, infrastructure and communication systems (technical), thereby weakening overall system performance.

Vulnerability to natural disasters ranked fifth (Mean = 4.16, NV = 0.791). Environmental and socio-economic risks, such as flood-prone areas, informal settlements, poverty and weak urban planning, complicate disaster management. Bello et al. (2021) note that vulnerability stems from hazard exposure, poor infrastructure, social inequality and weak institutions. In Ghana, floods disproportionately affect low-income populations, causing loss of homes and heightened disease risk (Deen, 2015). Weak legislation and outdated engineering exacerbate this vulnerability, particularly during climate change (Pelling, 2012; Anguelovski et al., 2014; Gilmore and DuRant, 2021). This reflects the interaction between environmental conditions (external context), social vulnerability and inadequate technical infrastructure, reinforcing systemic risk within emergency response systems.

Lack of knowledge or capacity ranked sixth (Mean = 4.16, NV = 0.791). Chronic shortages of trained personnel and technical skills hinder effective management across all emergency phases, from risk assessment to recovery. Bello et al. (2021) highlight that inadequate experience with protocols contributes to stress and poor decision-making. Many agencies lack essential skills for timely coordination despite frequent hazards like floods and disease outbreaks. Abudu et al. (2025a, 2025b, 2025c) note that inconsistent implementation of national strategies and resource shortages impede progress. Abudu et al. (2025a, 2025b, 2025c) emphasise that strong leadership and resource allocation are vital for effective disaster planning. This barrier illustrates the socio-technical gap between human capacity (social) and the operation of emergency technologies and systems (technical), limiting their effective utilisation during crises.

Inadequate institutions or organisations ranked seventh (Mean = 4.14, NV = 0.744). Weak governance, limited funding, fragmented coordination, poor leadership and communication gaps delay disaster management and reduce service delivery. Limited local authority and top-down policies undermine enforcement and community-based approaches. Strengthening institutions requires clarifying roles, decentralising authority, improving logistics and enhancing cross-sector coordination (Abudu et al., 2025a, 2025b, 2025c). Institutional weaknesses (social structures) further constrain the integration and coordination of emergency technologies (technical), leading to delays and inefficiencies in response systems.

Rapid urbanisation and population growth ranked eighth (Mean = 4.12, NV = 0.698). Unplanned expansion strains infrastructure, reduces emergency service reach and increases vulnerability, particularly in informal settlements. Literature affirms that urban growth often outpaces infrastructure and land-use planning, heightening hazard exposure (Abdul and Yu, 2020; Wamsler et al., 2020). Integrated planning and resilient infrastructure investment are critical to enhancing preparedness and reducing disaster impacts (Ajibade, 2022; Rezvani et al., 2023). This demonstrates how rapid environmental and spatial changes (context) interact with limited infrastructure systems (technical) and governance capacity (social), intensifying emergency response challenges.

Lack of capacity building ranked ninth (Mean = 4.09, NV = 0.628). Insufficient training programs, professional development and disaster preparedness initiatives hinder the ability of emergency personnel and facility managers to effectively respond to crises. These gaps reduce technical proficiency, delay coordination and limit the implementation of updated DRR practices (Al-Wathinani et al., 2023; Wamsler et al., 2020). Investing in continuous capacity-building enhances emergency management, strengthens institutional knowledge and supports coordinated response systems. This reinforces the socio-technical link, as inadequate human development limits the adoption of emergency technologies.

This study identifies key stakeholders, including policymakers, regulatory bodies, emergency agencies such as NADMO, facility managers and built environment professionals. The findings inform policy by highlighting the need for stronger regulation, enforcement and resource allocation. For practitioners, it emphasises capacity building, infrastructure improvement and the integration of socio-cultural factors into emergency planning. This study contributes to theory by developing a socio-technical perspective that links institutional, technical and social barriers. Practically, it supports targeted interventions such as training, policy reform and strategic investments. At the societal level, the findings foster improved safety, reduced disaster risks and greater resilience, aligning with the study’s focus on coordination, regulation and capacity building.

The study reveals that the barriers to modernising emergency response systems in Ghanaian facilities are multifaceted and deeply embedded within technical, institutional, financial, socio-cultural and political domains. These barriers not only hinder the development of effective emergency response infrastructure but also compromise institutions’ and communities’ ability to respond swiftly and efficiently during crises. Overcoming these challenges requires a comprehensive, systems-based approach that prioritises regulatory reform, sustained capacity development, adequate and consistent funding, inclusive stakeholder engagement and the strengthening of governance frameworks at both local and national levels.

The analysis identified nine critical barriers that significantly constrain the implementation of modern emergency response systems. These include ineffective and outdated building by-laws; a lack of attention to cultural, religious and social norms in the design and operation of emergency systems; chronic underfunding and resource limitations; political interference and instability; heightened vulnerability to natural hazards; widespread gaps in technical knowledge and operational capacity; fragmented and inadequate institutional structures; rapid pace of urbanisation outstripping the capacity of emergency services; and lack of capacity building. These barriers reflect systemic weaknesses that require both structural and behavioural transformations. Addressing them will necessitate not only policy and legal reforms but also the mobilisation of cross-sectoral collaboration, community participation, technological innovation and emergency preparedness strategies.

The findings highlight that these barriers are not isolated but are interconnected within a socio-technical system, where breakdowns in governance, culture and human capacity (social components) directly interact with and limit the effectiveness of infrastructure, technologies and emergency systems (technical components). By confronting these barriers head-on, Ghana and similarly positioned countries can begin to build emergency response systems that are not only robust and adaptive but also equitable, inclusive and responsive to the evolving nature of risk in today’s complex socio-environmental landscape. The study presents a comprehensive framework that identifies nine critical barriers: technical, institutional, financial, socio-cultural and political, thereby enhancing the understanding of emergency response challenges in developing countries.

This socio-technical framing provides a more integrated perspective by demonstrating how interactions between people, organisations, technology and the environment collectively shape emergency response outcomes. The study recommends further research on regional comparisons, the application of smart technologies in emergency systems and longitudinal studies to assess the long-term impacts of reform efforts.