Infrastructure Risk Research Articles

Historical geomagnetic observations from the Netherlands during the Carrington event (1859)

The Carrington event of September 1859 is the best known example of an extreme geomagnetic storm, often cited when discussing space weather risks for modern infrastructure. Historic observations including auroral sightings, magnetometer records and anecdotes of impacts on telegraph systems have been widely shared before, but none of these have included observations from the Netherlands. Geomagnetic observations taken in Utrecht and Den Helder during the Carrington event were digitised from the Royal Netherlands Meteorological Institute’s (KNMI) yearbook of 1859, and compared to much more detailed magnetograms from London. This combined analysis, beyond its application in communication with Dutch stakeholders, contributes to a better understanding of the interpretation, limitations, and uses of such archived measurements, of which more examples might be available in archives internationally. The observations consist of spot measurements taken three times per day. The Den Helder data only partially record the Carrington storm. Conversion factors from Den Helder have been used to estimate missing conversion factors of the Utrecht data. The correlation between the Dutch declination measurements and those made in London is strong with correlation coefficients larger than 0.7 for the Utrecht data and larger than 0.9 for the Den Helder data. However, there is very little correlation between the Dutch and British inclination measurements. The London horizontal intensity measurements compared to Den Helder data give correlation values larger than 0.8 but the observations from Utrecht match less well. There is a significant deviation between the British data and the Utrecht declination and horizontal intensity measurements during the quiet period between 30 August and 2 September. It is unclear what causes this deviation. Given the proximity of the locations and similarity in latitude, and based on the coherent registration of the measurements, it is reasonable to assume that the magnetic traces captured in London provide a good approximation of the magnetic field variations in the Netherlands during the storm, indicating that these may be used for impact assessment studies for Dutch vital infrastructure.

Mitigating cyberphysical risks in IoT-enabled smart transport infrastructure

Mitigating cyberphysical risks in IoT-enabled smart transport infrastructure

Seismic fragility, loss, and resiliency of old railway masonry arch bridges under near-field ground motion

ABSTRACT Iran’s historic railway arch bridges, many over a century old, face seismic risks due to their original design neglecting lateral loads. As they are often situated in seismically active zones near fault lines, understanding their seismic vulnerability is crucial. The goal of this study is to assess the seismic fragility and loss estimation of such bridges under various seismic events. To this end, the seismic performance of two masonry arch bridges, specifically a bridge with two long spans, named 2LS20, and a bridge featuring five small spans, named 5SS06, along the old Tehran-Qom railway line, is assessed under a set of 28 near-field and 22 far-fault earthquake records. Throughout the nonlinear incremental dynamic analysis, seismic fragility analyses were performed to ascertain the likelihood of damage across distinct limit states for each bridge model under the action of near and far-fault ground motions. Subsequently, throughout the resiliency analysis, the recovery process was simulated to assess the progress of bridge functionality with time. Moreover, seismic loss analyses were conducted to assess the comparative economic viability of the studied models. The results indicate the 5SS06 bridge for lower vulnerability and repair costs with near-fault motions posing higher risks, particularly for extreme damage conditions. Resilience varies significantly based on recovery models, with the 5SS06 bridge showing more effortless recovery under far-fault motions and higher resilience factors under near-fault records. Additionally, predictive equations were proposed for managing seismic risks in similar bridge infrastructures, particularly in Iran’s railway network, aiding resilience and risk mitigation planning.

Developing the Recovery Gap Index: A Comprehensive Tool for Assessing National Disaster Recovery Capacities

The increasing frequency and severity of extreme natural events, along with their escalating impacts, highlight the urgent need for robust tools to assess and strengthen national capacities for disaster preparedness and recovery. In this context, this paper introduces one of these tools, called the Recovery Gap Index (RGI), a comprehensive composite index designed to quantify and evaluate the post-extreme natural event response and recovery capabilities at the country level. The tool addresses the need for a systematic approach to quantify resilience and evaluate the impacts of consecutive events on vulnerable areas. The RGI synthesizes data from three well-established indices: the World Risk Index, INFORM, and Global Infrastructure Risk Model and Index (GIRI), covering critical dimensions related to sociodemographic factors, infrastructure, governance, technology, and economic resilience. By extracting key parameters from these diverse indices and aggregating them, the RGI provides a detailed assessment of each nation’s ability to manage the aftermath of extreme natural events. The index findings reveal significant regional disparities in recovery capacities, with European countries exhibiting stronger resilience, whereas many African and Asian nations face substantial challenges. Furthermore, this study proposes several potential future enhancements, such as the incorporation of early warning systems and insurance coverage metrics, aimed at improving its accuracy and practical application. The RGI aims to be a valuable tool for policymakers, disaster management professionals, and stakeholders, enabling them to make informed decisions and implement targeted interventions to further enhance global disaster resilience.

Mechanism of Crack Development and Strength Deterioration in Controlled Low-Strength Material in Dry Environment

The continuous expansion at the urban scale has produced a lot of construction waste, which has created increasingly serious problems in the environmental, social, and economic realms. Reuse of this waste can address these problems and is critical for sustainable development. In recent years, construction waste has been extensively recycled and transformed into highly sustainable construction materials called controlled low-strength materials (CLSMs) in backfilling projects, pile foundation treatment, roadbed cushion layers, and other applications. However, CLSMs often experience shrinkage and cracking due to water loss influenced by climatic temperature factors, which can pose safety and stability risks in various infrastructures. The purpose of this paper was to study the mechanism of crack formation and strength degradation in a CLSM in a dry environment and to analyze the deterioration process of the CLSM at the macro- and micro-scales by using image analysis techniques and scanning electron microscopy (SEM). The test results show that with the drying time, the CLSM samples had different degrees of cracks and unconfined compressive strength (UCS) decreases, and increasing the content of ordinary Portland cement (OPC) reduced the number of cracks. The addition of bentonite with the same OPC content also slowed down the crack development and reduced the loss of UCS. The development of macroscopic cracks and UCS is caused by the microscopic scale, and the weak areas are formed due to water loss in dry environments and the decomposition of gel products, and the integrity of the microstructure is weakened, which is manifested as strength deterioration. This research provides a novel methodology for the reuse of construction waste, thereby offering a novel trajectory for the sustainable progression of construction projects.

Applications of UAV Digital Photogrammetry in landslide emergency response and recovery activities: the case study of a slope failure in the A-7 highway (S Spain)

Abstract The disruption of vehicle traffic on important transport infrastructure has a major economic impact. Therefore, the instability of highway cut-slopes poses a significant risk for major infrastructures crossing mountainous regions and rocky coasts. The use of Uncrewed Aerial Vehicles (UAVs) is of great help in the prevention of road cut-slope failures and in emergency and rehabilitation of sites impacted by this type of landslides. Here, we show an example of UAV operations in emergency response and recovery in a highway cut-slope failure. We analyzed a failure that occurred on 11 March 2021 in a 52-m-high cut-slope located at 354.3 km of the A-7 Highway (S Spain). We also examine the applications of these analyses to help in risk evaluation and management. We acquired 3050 images and 6 videos with UAVs during 5 field surveys from 11 to 31 March 2021 to follow the evolution of the destabilized cut-slope. The videos taken by UAVs were of great help in the emergency response phase to guide the first steps in the removal of unstable rock blocks. The acquired images served to generate sequential Digital Elevation Models (DEMs) and 3D models (i.e., point clouds and tiled models) using the Digital Photogrammetry technique. These models were used subsequently to identify changes in the topography and calculate volumes of both destabilized and excavated material. The volumetric analyses indicate that 6200 m3 of rock collapsed, producing a deposit of debris of 10,900 m3, and after the partial failure, 15,100 m3 of the slope remained unstable. Therefore, the volume of rock mobilized by the landslide was about 21,300 m3. The recovery activities involved the removal of the collapsed debris and the re-profiling of the slope. This involved the excavation, transportation, and deposition of 83,400 m3 of rock to reduce the slope’s inclination from 64° to 45–33°. We then analyzed the follow-up work generating sequential DEMs during the cut-slope excavation in order to forecast the approximate date of the highway reopening. Thus, an average excavation speed of 1075 m3/day was estimated, and with this value, by March 31, it was possible to initially forecast that the highway could be reopened in the first week of June, not far from June 10, the date on which it was finally reopened. These results were obtained with reduced equipment costs and field time over topography conventional methods, which indicates the usefulness of UAVs and Digital Photogrammetry (UAV-DP) in emergency response and recovery situations provoked by unstable slopes in roads.

Holistic Assessment of Social, Environmental and Economic Impacts of Pipe Breaks: The Case Study of Vancouver

This paper presents a holistic assessment framework for the impacts of water distribution pipe breaks to promote environmentally sustainable and socially resilient cities. This framework considers social, environmental, and economic vulnerabilities as well as probabilities associated with pipe failure. The integration of these features provides a comprehensive approach to understanding infrastructure risks. Taking the city of Vancouver as a case study, the social vulnerability index (SVI) is obtained following the application of a cross-correlation matrix and principal component analysis (PCA) to identify the most influential among 33 selected variables from the 2021 census of the Canadian population. The Environmental Vulnerability Index (EVI) is evaluated by considering the park and floodplain areas. The Economic Vulnerability Index (ECI) is derived from the replacement cost of pipes. These indices offer valuable insights into the spatial distribution of vulnerabilities (consequences) across urban areas. Subsequently, the Consequence of Failure (COF) is computed by aggregating the three vulnerabilities with equal weights. Pipe probability of failure (POF) is evaluated by a Weibull model calibrated on real break data as a function of pipe age. This approach enables a dynamic evaluation of pipe deterioration over time. Risk is finally assessed by combining COF and POF for prioritizing pipe replacement and rehabilitation, with the final objective of mitigating the adverse impacts of infrastructure failure. The findings show the significant impact of ethnicity, socioeconomic indices, and education on the social vulnerability index. Moreover, the areas close to English Bay and Fraser River are more environmentally vulnerable. The pipes with high economic vulnerability are primarily concrete pipes, due to their expensive replacement costs. Finally, the risk framework resulting from the vulnerabilities and pipe break probabilities is used to rank the Vancouver City water distribution network pipes. This ranking system highlights critical areas requiring different levels of attention for infrastructure improvements. All the pipes and corresponding risks are illustrated in Vancouver maps, highlighting that the pipes associated with a very high level of risk are mostly in the south and north of Vancouver.

COMBINED DECISION SUPPORT MODEL FOR DEVELOPMENT PRIORITIES OF THE KYIV CAR TUNNEL NETWORK

An analysis is conducted for the opportunities to reduce climate (ecological), technogenic and safety risks in the Kyiv transport infrastructure in case of construction of the car tunnel system envisioned in the Kyiv city General plan. The involved structural and functional factors included district type in the potential tunnel’s area, downtown factor, population density, daily pendular movement, arterial network density, aver-age traffic speed at peak hours, surface connectivity of the exits (portals) of the tunnel by automobile roads, surface road throughput, criticalness of the transport infrastructure object, and vulnerability in case of military attacks or terrorist acts. The modified morphological analysis method was applied in the research, that con-sidered groups of climate (ecological) and techogenic risks, and also the military (terrorist) threats. This be-came the basis for construction of the decision support model regarding the evaluation of priorities and rank-ings (rational order) of tunnel construction. Additionally, a combination of morphological analysis with analyt-ical hierarchy process was proposed that provided alternative viewpoints with a different ranking compared to the basic model, depending on the given priorities (weights) of risk factors during decision making. This approach may be useful for development of the transport policy with the goal of approaching climate neutrality for big cities, as well as maximum protection of urban transport infrastructure in conditions of wartime threats.Using the developed system tools and combined models, the urban society can become safer and more resilient, managing transport policies on the basis of the system approach, and multi-criteria analysis of im-pact factors.

Risks of critical infrastructures during war

Risks of critical infrastructures during war

The Impact of Cyberattacks on Jakarta's Electric Energy Sector: An Evaluation of Risk, Security, and Economic Implications

This research explores the impact of cyberattacks on the electric energy sector in Jakarta. Cyberattacks are increasingly becoming a serious threat to critical infrastructure, including energy systems, affecting the stability and security of electricity supply. The purpose of this study is to evaluate the risk and vulnerability of Jakarta's electrical energy infrastructure to cyberattacks, and to analyze the economic implications of potential disruptions. Using secondary data from scientific journals and agency reports, this study identified Jakarta's high vulnerability to cyber-attacks, particularly in Industrial Control Infrastructure (ICS) and SCADA. The analysis shows that cyber-attacks can cause significant disruptions to electricity supply, having far-reaching impacts on various sectors including transportation, health, and the economy. Key findings highlight the need for stronger security strategies, effective risk mitigation, and increased public awareness. The research provides recommendations for strengthening public policy and investment in the security of electrical energy infrastructure, and underscores the importance of effective communication in managing public expectations and preparation for potential disruptions. This research paves the way for further research in several areas, including the development of innovative cybersecurity technologies and the analysis of the long-term impact of cyberattacks on Jakarta's economic and social stability. Collaborative efforts between the government, private sector and the community are needed to improve resilience to cyberattacks in the electric energy sector.

Country risk mapping in a changing world—comparative survey on academic research and industrial practices

AbstractIn an era marked by rapid geopolitical shifts, persistent pandemics, and escalating climate threats, the imperative to transcend traditional country risk mapping methodologies has never been more critical. This study embarks on a comprehensive examination of the efficiency of current academic and industrial approaches to mapping the multifaceted country risks. By proposing a structured risk mapping framework that incorporates seven pivotal risk categories as Political Risk, Institutional Risk, War and Armed Conflict Risk, Public Security Risk, Socioeconomic Risk, Ecological Threat Risk, and Infrastructure Risk, the research seeks to foster a more nuanced understanding of how different organizations assess and prioritize these risk factors. Employing a dual approach that includes a thorough literature review and an extensive industry survey, and a detailed analysis of each of the seven risk category by juxtaposing relevant academic insights with industry practices, this study examines the discrepancies between academic theories and practical applications in country risk mapping. It reveals underestimate country risk factors, inadequate risk categorization granularity, inconsistencies in risk prioritization, terminological mismatches, and a need for a more integrated and holistic approach to country risk mapping. The paper concludes by proposing future research directions that aim to refine country risk mapping methodologies. It advocates a forward-looking perspective that adequately addresses the complexity and inter-connectivity of global operational risks.

Flood Risk Assessment and Its Implications on Critical Infrastructure Resilience in Nigeria

Flooding is one of the recurrent natural disasters in Nigeria that poses huge threats to not just people but also critical infrastructures. In 2024, the Federal Ministry of Water Resources and Sanitation and the Nigeria Hydrological Services Agency (NIHSA) identified 31 states including the FCT as high-risk areas for significant flood impacts. The impact of floods generally has caused devastating damage to critical infrastructures resulting from high rain intensities for a long duration. It becomes pertinent to evaluate the impact of floods on critical infrastructures like roads, bridges, residential buildings, water supply systems, and electricity facilities. Thus, this research seeks to explore the vulnerabilities and impacts of floods on critical infrastructure which is fundamental to economic growth, development, and coping mechanisms. A structured questionnaire was distributed among a sample of 90 including government department, construction industry, and community members to seek their views on the vulnerability risk of infrastructure and flood sources. Results indicate that most of the damages reported 42% were due to the destruction of roads and bridges, followed by residential houses at 31%. The main cause of flooding identified by 54% of respondents was poor drainage systems, while 31% cited poor waste management as a contributing issue. Hence, restoration of the drainage systems, implementation of prohibitions on encroachment of flood-prone areas and improvement of early warning systems are critical and pressing. The uniqueness of the study lies in its effort to address the gaps and challenges that exist in infrastructure resilience by identifying the most critical elements that are prone to risks and proposing mitigation measures against floods in the urban centers of Nigeria which are experiencing rapid growth.

Parameterized fragility-based uncertainty influence quantification and sensitivity analysis methodology: Concept, formulation, and application

Uncertainty modeling is a crucial issue in the seismic risk and resilience assessment of structures and infrastructures. Understanding and quantifying the impact of structural model parameter uncertainty (i.e., the epistemic uncertainty) on seismic fragility of structures are still open issues in the field of earthquake engineering. To this end, this study proposes a parameterized fragility-based methodology to quantify and rank the influence of multiple model parameter uncertainties on the seismic fragility result when their uncertainty is simultaneously involved. The concept and detailed procedure of this methodology is first introduced in this study. After that, the proposed methodology is applied to a case study bridge, i.e., unbonded laminated rubber bearing (ULRB) supported highway bridge retrofitted with transverse steel damper (TSD), to investigate how the uncertainty of the concerned model parameters affects the seismic fragility of the selected benchmark bridge when separately using the residual and peak displacements as engineering demand parameters (EDPs). The parameter sensitivity of fragility corresponding to these two EDPs is then quantified by a new proposed index and ranked using Tornado diagrams. In addition, the seismic fragility result when considering different sources of uncertainty is compared and discussed in this study through the parameterized fragility model. The result shows whether considering the uncertainty of model parameters has a more considerable influence on the fragility result when using the residual displacement as EDP as compared with using peak displacement as EDP. The sensitivity ranking of the parameters is affected by the damage level or the nonlinearity of the structural system. Regarding the residual and peak bearing displacements of ULRB-supported highway bridges, the friction coefficient is the most sensitive parameter.

Mitigating aging infrastructure risks: An optimized epoxy resin system for water supply pipeline rehabilitation

Urban water supply networks are crucial for ensuring the delivery of safe drinking water to urban populations; however, the aging infrastructure in these systems has led to a rising incidence of leaks and frequent pipeline failures, posing serious risks. Traditional repair approaches encounter limitations in terms of efficiency, durability, and environmental safety, particularly when employed in potable water pipelines. To address these challenges, we developed a novel multi-component amine-cured epoxy resin system specifically optimized for in-situ curing under ambient conditions. This study comprehensively examines the mechanical properties, water absorption behavior, and curing kinetics of this resin system, formulated to reduce volatile organic compound emissions while enhancing durability under prolonged water exposure. Experimental findings demonstrate that the E2 formulation exhibited superior tensile strength, flexural properties, and fracture toughness relative to other formulations, with a two-stage water absorption model accurately predicting resin behavior in moisture-laden environments. Moreover, finite element modeling and laboratory testing confirmed the influence of bubble defects on mechanical performance, and a negative pressure defoaming technique effectively reduced defect volume, resulting in a 17.6 % improvement in tensile strength. Collectively, this research advances the practical application of rapid-curing resins, offering a resilient, safe, and sustainable solution for the rehabilitation of aging water pipeline networks.

Landslide-bridge interaction: Insights from an extensive database of Italian case studies

Despite the wealth of documented case studies, systematic approaches to correlate landslide characteristics with the damage they cause to bridges are rare. The correlation is challenging due to the complexity of landslides, which can vary in movement types, volume, velocities, materials, and orientations. Additionally, the lack of universally applicable models to forecast bridge responses in case of landslide interaction adds complexity. Recognizing the urgency of addressing this challenge, various countries, including Italy, have introduced guidelines and strategies to manage infrastructure risks and enhance safety. Efforts are underway to develop practical tools for authorities and infrastructure managers, encompassing factors influencing bridge response, especially under the action of natural hazards. This article presents a database of landslide-bridge interactions in Italy, developed under the FABRE Consortium. The database was compiled by analysing 382 bridges across 12 Italian regions. The article explores correlations between landslide characteristics and risk classification for bridges, defined as “Landslide Class of Attention” (L-CoA). The analysis shows that landslide volume is directly correlated with L-CoA severity, with larger volumes leading to higher classifications. Very slow-moving landslides are prevalent in high-risk L-CoA categories, suggesting they are associated with significant volumes and severe consequences. Complete interference between landslides and infrastructure poses the highest risk, while partial interference also contributes significantly. Combined landslides tend to result in more severe L-CoA classifications. The findings underscore the importance of better understanding the interactions between landslides and bridges, to develop predictive models and mitigate the risks posed by landslides to infrastructure in Italy and beyond.

“Because we’re dying in here”: A study of environmental vulnerability and climate risks in incarceration infrastructure

This article draws on the stories of formerly incarcerated people to examine the ways in which the physical and social infrastructures of carceral facilities increase incarcerated people's vulnerability to environmental hazards exacerbated by climate change. We present qualitative data from interviews and focus groups with people who have been incarcerated in prisons and/or jails in Colorado regarding their experiences with incarceration infrastructure, amplifying the voices of formerly incarcerated people to identify vulnerabilities which have been deliberately hidden by carceral social and institutional processes, and adding them to the academic dialogue around incarceration and climate change. By providing testimony on the ways in which incarceration infrastructure—how they are designed, built, and maintained—amplify environmental harm, we identify how incarceration infrastructures create environmental vulnerability along axes of temperature, air quality, and water supply even before incarcerated people are exposed to climate hazards. Then, we illustrate ways incarcerated people encounter limits to their agency to mitigate this vulnerability, suggesting the need for structural change. Finally, we provide evidence that climate-related extreme temperatures, wildfires, and flood events experienced by our participants exploited the axes of vulnerability laid out above, affecting the majority (65%) of our 35 study participants. Overall, we argue current carceral infrastructure creates material realities that regularly cross the threshold of cruel and unusual punishment, and our argument supports decarceration as a necessary public policy intervention for robust, just, and humane climate resilience.

Disaster Risk Assessment and Analysis of Physical Infrastructure: A Comprehensive Review of Scientific Methods and Techniques

Physical infrastructure plays a crucial role in fostering economic development and societal well-being. However, they are susceptible to potential impacts when exposed to various hazards, which makes risk assessment and analysis essential for ensuring resilience. This paper presents a comprehensive review of the extant literature to provide an in-depth understanding of the research landscape developed to assess and analyze disaster risk to physical infrastructure. The objectives of this study are 1) to comprehend the disaster risk assessment methods and techniques from the global literature, 2) to analyze the trend and growth pattern of research on disaster risk assessment and 3) to identify the nuances in the methods for assessing disaster risk. This study employs bibliometric analysis along with a comprehensive literature review of selected papers extracted from the Scopus database. The study realized that research focusing on disaster risk assessment is scarce in developing countries at risk, especially India, Bangladesh, China, and Pakistan. Existing studies have attempted to develop conceptual as well as theoretical frameworks for risk assessment, and also employed assessment methods such as digital twins, risk indices, risk curves, and the like. Furthermore, the study realized that a higher emphasis on assessing the risk of transportation infrastructure disregards the other major physical infrastructure. The bibliometric analysis further indicates the need for a comprehensive and robust risk analysis tool for physical infrastructure with a standardized quantitative analysis model that can analyze the impacts of hazards. Deep learning coupled with GIS and remote sensing techniques can be considered a promising approach for risk assessment in future research. In conclusion, this comprehensive bibliometric analysis provides a detailed overview of the research landscape of physical infrastructure risk assessment and analysis. The insights derived from this analysis can help to identify the research gap in the disaster risk assessment globally highlighting the potential methods and techniques for the same.

Smart hotspot detection using geospatial artificial intelligence: A machine learning approach to reduce flood risk

This study employs Geospatial Artificial Intelligence (GeoAI) and the Random Forest Machine Learning (ML) algorithm to enhance flood hazard assessments in Portugal. It utilizes NASA's LP DAAC (2023) Digital Elevation Model (DEM) and slope data from EPIC WEBGIS PORTUGAL DATA, offering detailed topographical insights for environmental planning. Additionally, it incorporates data on proximity to water bodies from the Portuguese Environment Agency and the European Environment Agency, and soil characteristics from EPIC WEBGIS PORTUGAL DATA, facilitating a thorough examination of flood risks. This approach prioritizes long-term land features over short-term weather patterns, providing a comprehensive understanding of flood vulnerability. The study processes data at a 1 km x 1 km resolution, adapting TIFF maps for compatibility with the Random Forest model. The produced flood hazard maps identify potential flood hotspots at both national and city levels, crucial for urban planning. These maps aid in assessing the vulnerability of key infrastructure and assets, such as transport networks and buildings. The research highlights the importance of integrating additional data on assets and socioeconomic factors to enhance urban resilience. It sets the stage for future research aimed at improving predictive accuracy and underscores the necessity of extensive geospatial analytics in managing infrastructure risks.

APPROACHES TO THE CLASSIFICATION OF SUSTAINABLE DEVELOPMENT RISKS OF A ENTERPRISES

The role of risk consideration in enterprise management continues to grow over time. Rapid development of new technologies, obsolescence of existing ones, commoditization, globalization, digitalization, and the rise of the new electronic and information economy, characterized by internal imbalance, rapid transformations, and high external turbulence, not only broaden the range of risks but also qualitatively transform them, necessitating dedicated studies. The aim of the article is to improve the classification of risks of risks related to sustainable enterprise development. Research methods: generalization, systematization. The article refines the classification of sustainable development risks for enterprises, expanding the classification features and adding new types: “Emerging Risks” and “Unexpected Risks”, in addition to “Entrepreneurial Risks”. The risks associated with sustainable enterprise development are detailed by type. Specifically, “Emerging Risks” include relocation risks, risks of military actions, infrastructure risks, Industry 4.0 risks, customization, commoditization, and others. “Unexpected Risks” include force majeure, terrorism, "black swan" events, and others. Entrepreneurial risks encompass reputational, interface, partnership risks, and others. This classification approach, unlike others, emphasizes modern external challenges and globalization threats. The author’s proposals can be applied in the practical activities of enterprises and form the basis of a methodological approach to risk management within a risk-oriented framework. This approach includes identifying and assessing risks and implementing corresponding measures to minimize (or eliminate) them depending on the risk level.

THE STATE AND PROSPECTS OF THE DEVELOPMENT OF THE TOURISM INDUSTRY IN UKRAINE IN THE CONDITIONS OF GLOBAL CHALLENGES

The article examines the state and prospects of international tourism development in Ukraine amid global crises, particularly the COVID-19 pandemic and the Russian-Ukrainian war. A comprehensive analysis of key factors affecting the tourism industry is conducted, including international travel restrictions, geopolitical instability, economic difficulties, and changes in consumer behavior. It demonstrates how global crises, such as COVID-19 and the Russian-Ukrainian war, have led to a significant reduction in international tourist flows, decreased foreign exchange earnings from tourism activities, and created additional risks for tourism infrastructure. In such conditions, the recovery of the industry and its integration into the country's economic development require a comprehensive approach that includes not only investments but also the digitalization of tourism services. The research highlights key changes in tourist flows, the level of economic activity in the sector, and the impact of internal and external challenges on tourism infrastructure. It was found that after a significant decline in 2022 due to the war, a gradual recovery began in 2023 thanks to the development of domestic tourism and the opening of new safe routes. Digitalization has become a key factor in the development of the modern tourism industry, affecting all stages of the tourist experience. The implementation of digital technologies, such as online booking, mobile applications, virtual and augmented reality, allows companies to enhance their service and improve competitiveness. The article emphasizes the importance of strengthening tourism infrastructure and supporting entrepreneurship in times of instability. Directions for further research are proposed, including the development of domestic tourism, the assessment of the resilience of tourism entities to crises, and the analysis of the long-term effects of the war on international tourist flows. The study underscores the significance of the tourism industry for Ukraine's economic recovery and its potential for integration into the global tourism market.