Hasil untuk "Crisis management. Emergency management. Inflation"

Bingzheng Chen, Jan Dhaene, Chun Liu et al.

This paper develops a dynamic equilibrium model of the insurance market that jointly characterizes insurers' underwriting, investment, recapitalization, and dividend policies under model uncertainty and financial frictions. Competitive insurers maximize shareholder value under a subjective worst-case probability measure, giving rise to liquidity-driven underwriting cycles and flight-to-quality behavior. While an equilibrium typically fails to exist in such dynamic liquidity management framework with external financial investment, we show that incorporating model uncertainty restores equilibrium existence under plausible parameter conditions. Moreover, the model uncovers a novel relationship between the correlation of insurance and financial market risks and the equilibrium insurance price: negative loadings may emerge when insurance gains and financial returns are positively correlated, contrary to conventional intuition.

Alireza Ghahtarani, Ahmed Saif, Alireza Ghasemi

Asset Liability Management (ALM) represents a fundamental challenge for financial institutions, particularly pension funds, which must navigate the tension between generating competitive investment returns and ensuring the solvency of long-term obligations. To address the limitations of traditional frameworks under uncertainty, this paper implements Distributionally Robust Optimization (DRO), an emergent paradigm that accounts for a broad spectrum of potential probability distributions. We propose and evaluate three distinct DRO formulations: mixture ambiguity sets with discrete scenarios, box ambiguity sets of discrete distribution functions, and Wasserstein metric ambiguity sets. Utilizing empirical data from the Canada Pension Plan (CPP), we conduct a comparative analysis of these models against traditional stochastic programming approaches. Our results demonstrate that DRO formulations, specifically those utilizing Wasserstein and box ambiguity sets, consistently outperform both mixture-based DRO and stochastic programming in terms of funding ratios and overall fund returns. These findings suggest that incorporating distributional robustness significantly enhances the resilience and performance of pension fund management strategies.

Meherjan Islam, Md. Abidul Islam, Farzana Afroj et al.

Bangladesh is highly vulnerable to floods, like natural disasters. Yet, contributions of volunteer-led non-profit organizations (NVOs) in emergency response remain underexplored. This paper investigates how an NVO responded to a flood, from rapid rescue to post-flood recovery, and evaluates the effects of its engagement on public health, organizational learning and growth, and community resilience. We applied a mixed-methods approach, combining organizational document reviews, structured interviews with seven key volunteers, direct field observations, and photographic documentation of relief and medical camp activities (21–28 August 2024). Quantitative data on reported illnesses were analyzed using STATA-18 and R through descriptive statistics, univariate analysis, post-hoc comparisons, and multinomial logistic regression. Qualitative data underwent thematic analysis with a deductive coding framework. The NVO provided critical support through rapid rescue, targeted relief, and medical camps addressing integumentary (46.5%), respiratory (13.2%), skeletal (5%), gastrointestinal (2.6%), and other illnesses (32.7%). Thematic analysis highlighted organizational strengths, including field-level experience, decentralized leadership, adaptability, and strong collaborative capacity with government and other non-government actors. Despite resource constraints, the NVO demonstrated high operational effectiveness and recognition during the crisis. Formal integration of NVOs into national disaster coordination mechanisms is recommended. Institutional, technical, and financial support can strengthen disaster risk reduction, governance, and social development in resource-constrained settings. This study establishes novelty by linking health impact assessment with organizational learning in volunteer-led disaster response, combining quantitative outcomes and qualitative insights to show how grassroots organizations complement formal disaster management and provide actionable recommendations for integration into governance.

Yulei Yang, Qiang Wei, Baofeng Huo

This study aims to optimize pharmaceutical emergency logistics under dynamic demand and disrupted routes during public health crises. By integrating multi-scenario analysis and multimodal transportation, it seeks to minimize response time, unmet demand penalties, and costs while balancing efficiency and equity. The model addresses limitations of traditional single-mode logistics, leveraging COVID-19 case data to enhance adaptability in resource allocation. A robust optimization model is developed, integrating dynamic demand forecasting, scenario probabilities, and capacity constraints across four epidemic stages. The NSGA-III algorithm is employed to solve multi-objective trade-offs, with performance compared against NSGA-II using metrics like spacing and Pareto ratio. Robust standard vectors and scenario probabilities are analyzed to evaluate stability, supported by computational experiments from Chinese cities like Wuhan. NSGA-III outperformed NSGA-II, generating 60% more Pareto solutions in T4 with 3% faster computation. Robust vectors significantly influenced outcomes: γ3 increased penalty costs linearly in high-demand phases, while γ1 escalated procurement expenses over time. Scenario probabilities p3 reduced penalties by 15–20% through coordinated logistics. The framework enables emergency managers to prioritize air transport for urgent deliveries and establish centralized hubs, reducing average response times by 18%. Public-private partnerships and dynamic inventory adjustments improve equity and efficiency, particularly in high-risk regions. This study contributes to the field by unifying dynamic demand modelling, multimodal transport optimization, and robust scenario-based decision-making into a single analytical framework. The application of NSGA-III effectively resolves many-objective optimization challenges, outperforming traditional methods in both diversity and convergence. A scenario-driven parameter analysis is introduced to quantitatively assess the impacts of uncertainty, thereby advancing theory in crisis logistics management.

Greg Drummond, Matthew B. Thompson, D. Gill

Emergency management operations are a complex system involving multiagency hierarchical command structures requiring coordination of significant volumes of information, resourcing and effort across expansive disaster zones within restricted timeframes and with potentially catastrophic consequences. Within these environments establishing a timely and shared understanding among different levels of command and across agencies is crucial yet remains a significant challenge. The problem is subsequently framed as ʻhow can the establishment of a systems‐level common operating picture across hierarchical commands and different agencies be improved in the context of complex emergency management and disaster response?ʼ To address this, we present the Maaloop Framework which builds upon the insights gained from previous research within the context of threat assessment, sensemaking, and critical decision‐making in police, military, ambulance, and firefighting contexts. To the observer trained in its application, it aims to provide an instant, point‐in‐time, global and detailed visual intelligent product of (i) the amount of information identified by decision makers at each location; (ii) how confident those decision makers are in the information and its application to resolve an incident; (iii) how the decision maker in adjacent command levels are using the information being fed to them. In turn, it will assist in improving individual and collective understanding regardless of position within a command hierarchy or agency jurisdiction. We submit that the Maaloop Framework does no more than describe the common constructs and concepts identified in the literature describing decision‐making within these industries and the broader study of decision‐making in the field of psychology. Therefore, this framework is intended to provide a solution to provide systems‐level common operating picture and an initial basis for increased communication and understanding across complex crisis events.

Rohit Kumar Singh

Purpose – This study aims to understand the role of technology adoption (TA) in improving the efficiency and environmental sustainability (ENS) of humanitarian supply chains through collaboration and supply chain agility. This study made an attempt to explore how technological resources can be used strategically to achieve operational efficiency and contribute to sustainable humanitarian logistics. Design/methodology/approach – The data collected from 274 respondents involved in humanitarian logistics is analyzed using the confirmatory factor analysis and the Partial Least Squares Structural Equation Modeling. These respondents include logistics managers, coordinators as well as other relevant personnel from different non-governmental organizations, international aid agencies and relief operations. Findings – The results of this study show that TA plays a critical role in improving both collaboration and supply chain agility in humanitarian operations. It is evidenced that both collaboration and agility significantly moderate the relationship between TA and supply chain outcomes, respectively, improving the effectiveness and ENS of aid delivery. In particular, technology-facilitated collaboration and agility cut down operational costs, reduce the response time and minimize the environmental impact. Originality/value – This study extends the application of dynamic capabilities view in humanitarian operations and supply chain and elaborates on how technological capability improves humanitarian supply chain performance. This study also highlights the mediation role of agility and collaboration to achieve aid delivery efficiency and ENS.

Marco Mattuschka, Noah An der Lan, Max von Danwitz et al.

This paper presents a novel framework for goal-oriented optimal static sensor placement and dynamic sensor steering in PDE-constrained inverse problems, utilizing a Bayesian approach accelerated by low-rank approximations. The framework is applied to airborne contaminant tracking, extending recent dynamic sensor steering methods to complex geometries for computational efficiency. A C-optimal design criterion is employed to strategically place sensors, minimizing uncertainty in predictions. Numerical experiments validate the approach's effectiveness for source identification and monitoring, highlighting its potential for real-time decision-making in crisis management scenarios.

Luyun Lin, Yiqing Wang

The increasing development in the consumer credit card market brings substantial regulatory and risk management challenges. The advanced machine learning models applications bring concerns about model transparency and fairness for both financial institutions and regulatory departments. In this study, we evaluate the consistency of one commonly used Explainable AI (XAI) technology, SHAP, for variable explanation in credit card probability of default models via a case study about credit card default prediction. The study shows the consistency is related to the variable importance level and hence provides practical recommendation for credit risk management

D. Surya, M. Durga, Prasad Jogineedi et al.

Introduction: Effective emergency response relies on the timely availability of essential equipment. However, logistical challenges, limited resources, and inefficient distribution often hinder emergency services like fire departments, ambulances, and disaster relief teams. To overcome these issues, emergency equipment sharing, supported by technologies like IoT, AI, blockchain, and mobile platforms, can significantly improve resource allocation and accessibility. This system enables real-time tracking, predictive analytics for demand forecasting, and secure, transparent coordination between agencies. By fostering collaboration across sectors and regions, such a system enhances preparedness, response times, and operational efficiency, ensuring better management of crises. Objectives: The objective of optimizing emergency equipment sharing is to improve resource allocation and availability during crises. This involves enhancing coordination between agencies, using technologies like IoT for real-time tracking, AI for predictive allocation, and blockchain for secure, transparent sharing. The goal is to reduce response time, maximize equipment utilization, and ensure transparency and accountability in resource distribution. Methods: This system integrates IoT, AI, and blockchain for efficient emergency equipment monitoring and allocation. IoT sensors track real-time equipment status, while AI predicts demand for proactive distribution. Blockchain ensures secure transactions through smart contracts, automating equipment sharing and enhancing transparency. Mobile apps facilitate seamless coordination among agencies, improving response times and decision-making. Results: The system successfully streamlines emergency equipment sharing, optimizing resource allocation and transparency. IoT enables real-time tracking, AI supports predictive analytics, and blockchain secures transactions. This improves coordination between agencies, reducing downtime and enhancing crisis management, ultimately saving lives. Conclusions: Optimizing emergency equipment sharing is crucial for improving response times and operational efficiency. Collaboration between agencies like fire departments and hospitals, supported by technologies such as blockchain, IoT, and AI, ensures equipment is readily available and allocated effectively. Data analysis helps resolve disparities and optimize logistics, while a central equipment database and staff training enhance resource use. This approach improves coordination, saves lives, and strengthens community resilience in the face of crises.

Esther Sánchez-Peinado, A. Escribá-Esteve

The purpose of this research is to explore the determinants of socially oriented actions by family firms during the COVID-19 pandemic. Specifically, it aims to understand how family involvement, financial resources and cultural dimensions influence their social responsibility initiatives. By analyzing these factors, the study contributes to the literature on family business behavior and corporate social responsibility (CSR) in crisis contexts, offering insights into the unique interplay of family and cultural influences. This study employs a multi-country dataset to investigate the socially oriented responses of family firms during the COVID-19 pandemic. Robust analytical methods are applied to examine the interplay between family involvement, firm financial conditions, and national cultural dimensions. The analysis incorporates firm-level characteristics and cultural factors across diverse national contexts, leveraging quantitative data to draw insights into the behavior and decision-making of family firms in times of crisis. Our study reveals that family ownership fosters socially oriented responses during crises, while the presence of a family CEO is linked to more cautious, survival-focused behavior. Cultural dimensions significantly shape these dynamics: indulgence, short-term orientation and power distance promote greater social engagement, whereas uncertainty avoidance and long-term orientation temper it. Interestingly, firm size and sales impact did not significantly moderate these relationships, underscoring that identity, stewardship, and cultural norms – not resource availability – drive family firms’ crisis responses. These findings highlight the nuanced interplay between family involvement and cultural context in shaping socially responsible actions. This study relies on self-reported survey data from a single respondent per firm, raising the possibility of social desirability bias. Hofstede’s cultural framework, while widely used, offers a static view of culture that may not fully capture evolving dynamics during crises. Additionally, the study does not disentangle subgroup differences, such as generational stages or family versus non-family CEOs, which may reveal further heterogeneity. Future research should triangulate self-reports with objective indicators, examine alternative cultural models and explore institutional variables (e.g. government responses) to deepen understanding of family firms' socially oriented behavior under extreme conditions. Findings offer guidance for policymakers, business associations and civil society on leveraging family firms’ social potential during crises. Support structures – such as advisory boards or stakeholder councils – can help family CEOs balance survival concerns with broader societal needs. Recognizing cultural influences is crucial: in high power distance or indulgent contexts, targeted initiatives can activate stewardship and community engagement, while in high uncertainty avoidance settings, training and policy messaging can encourage outward-looking actions. Tailoring crisis communication and incentives to cultural logics can improve family firms’ responsiveness, helping societies mobilize these organizations as anchors of resilience in future emergencies. This study underscores the critical role of family firms as community anchors during crises, showing that their actions are shaped by both family dynamics and cultural values. By identifying when and why family firms engage in socially oriented behaviors, the findings help communities, NGOs and public institutions better mobilize these firms to support vulnerable groups. Understanding cultural drivers – such as stewardship in high power distance contexts or empathy in indulgent societies – can inform policies that foster solidarity and shared responsibility, ultimately enhancing social cohesion and collective resilience in the face of future health, economic or environmental emergencies. This study is among the first to examine how family ownership, family management and national culture jointly shape socially oriented responses to a global crisis. Using a large, multi-country dataset, it integrates socioemotional wealth and stewardship perspectives with Hofstede's cultural framework to reveal how identity and cultural context interact in shaping behavior. By distinguishing between family influence in ownership and management, the study uncovers contrasting logics that affect crisis decision-making. These insights advance theory on family firms, enrich cross-cultural research and provide practical guidance for leveraging family firms’ social potential in future emergencies.

Zhenkun Wu, Guoqing Zhu, Min Peng et al.

This study addresses the significant fire hazards associated with using thermoplastic materials, particularly PMMA (poly methyl methacrylate), which are prone to flammability and high calorific values. By employing a methodology that combines small-scale experiments and theoretical analysis, this paper investigates the impact of material width on the behavior of discrete flames in open spaces, using specimens ranging from 5 to 10 cm in width. The findings indicate that an increase in specimen width positively affects the burning area and brightness, while the dimensionless flame height and heat release rate per unit width exhibit a negative power law decay with increasing width. This suggests that beyond a critical width, further increases in width have little influence on flame propagation. The results of this study contribute to a better understanding of fire dynamics in thermoplastics and provide valuable insights that could lead to enhanced fire safety standards and material designs. The originality of this research lies in its detailed analysis of how material dimensions influence flame behavior, a topic that has not been extensively explored before, offering significant practical value in applications where fire safety is crucial.

Fernando Acebes, Javier Pajares, Jose M Gonzalez-Varona et al.

Project managers need to manage risks throughout the project lifecycle and, thus, need to know how changes in activity durations influence project duration and risk. We propose a new indicator (the Activity Risk Index, ARI) that measures the contribution of each activity to the total project risk while it is underway. In particular, the indicator informs us about what activities contribute the most to the project's uncertainty so that project managers can pay closer attention to the performance of these activities. The main difference between our indicator and other activity sensitivity metrics in the literature (e.g. cruciality, criticality, significance, or schedule sensitivity indices) is that our indicator is based on the Schedule Risk Baseline concept instead of on cost or schedule baselines. The new metric not only provides information at the beginning of the project, but also while it is underway. Furthermore, the ARI is the only one to offer a normalized result: if we add its value for each activity, the total sum is 100%.

Mahmood Alaghmandan, Olga Streltchenko

In this paper, we discuss aspects of model risk management in financial institutions which could be adopted by academic institutions to improve the process of conducting academic research, identify and mitigate existing limitations, decrease the possibility of erroneous results, and prevent fraudulent activities.

Fernando Acebes, José Manuel González-Varona, Adolfo López-Paredes et al.

The project managers who deal with risk management are often faced with the difficult task of determining the relative importance of the various sources of risk that affect the project. This prioritisation is crucial to direct management efforts to ensure higher project profitability. Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives. However, the existing literature highlights several limitations to use the risk matrix. In response to the weaknesses of its use, this paper proposes a novel approach for prioritising project risks. Monte Carlo Simulation (MCS) is used to perform a quantitative prioritisation of risks with the simulation software MCSimulRisk. Together with the definition of project activities, the simulation includes the identified risks by modelling their probability and impact on cost and duration. With this novel methodology, a quantitative assessment of the impact of each risk is provided, as measured by the effect that it would have on project duration and its total cost. This allows the differentiation of critical risks according to their impact on project duration, which may differ if cost is taken as a priority objective. This proposal is interesting for project managers because they will, on the one hand, know the absolute impact of each risk on their project duration and cost objectives and, on the other hand, be able to discriminate the impacts of each risk independently on the duration objective and the cost objective.

Yannick Becker, Pascal Halffmann, Anita Schöbel

In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To address these challenges, our research explores the power of robust multi-objective optimization. Since portfolio managers frequently measure their solutions against benchmarks, we enhance the multi-objective min-regret robustness concept by incorporating these benchmark comparisons. This approach bridges the gap between theoretical models and real-world investment scenarios, offering portfolio managers more reliable and adaptable strategies for navigating market uncertainties. Our framework provides a more nuanced and practical approach to portfolio optimization under real-world conditions.

Sten Torpan, Sten Hansson, Kati Orru et al.

PurposeThis paper offers an empirical overview of European emergency managers' institutional arrangements and guidelines for using social media in risk and crisis communication.Design/methodology/approachThe authors collected and analysed material including publicly accessible relevant legal acts, policy documents, official guidelines, and press reports in eight European countries – Germany, Italy, Belgium, Sweden, Hungary, Finland, Norway, and Estonia. Additionally, the authors carried out 95 interviews with emergency managers in the eight countries between September 2019 and February 2020.FindingsThe authors found that emergency management institutions' social media usage is rarely centrally controlled and social media crisis communication was regulated with the same guidelines as crisis communication on traditional media. Considering this study's findings against the backdrop of existing research and practice, the authors find support for a “mixed arrangement” model by which centralised policies work in tandem with decentralised practices on an ad hoc basis.Practical implicationsComparative insights about institutional arrangements and procedural guidelines on social media crisis communication in the studied countries could inform the future policies concerning social media use in other emergency management systems.Originality/valueThis study includes novel, cross-national comparative data on the institutional arrangements and guidelines for using social media in emergency management in the context of Europe.

Lauren B. Cain, J. Sutton, Michele K. Olson

In the United States, alerting authorities are authorized by the Federal Emergency Management Agency (FEMA) to notify the public of imminent hazards and threats by sending Wireless Emergency Alerts (WEAs) through the Integrated Public Alert and Warning System (IPAWS). Although recent efforts have been made to examine historical WEA compliance with frameworks such as Mileti and Sorenson's (1990) Warning Response Model, less attention has been paid to information included in WEAs that is not prescribed by message design frameworks from risk communication scholarship. This paper explores the presence of Situational Crisis Communication Theory's (SCCT) instructing and adjusting information in terse mobile alerts. The authors conducted a content analysis of 4777 WEAs sent between 2019 and 2022 to determine how often and in which contexts (i.e., hazard types, 90‐ or 360‐character messages) these strategies are used. We find that the limited definition of adjusting information used in prior research (e.g., direction to mental health resources) is rarely included in WEAs. Additionally, we identify differences in use by message length (90‐ vs. 360‐characters) and hazard type. We conclude that adjusting information in WEAs most frequently takes the form of organisational response information, thereby amending prior definitions of adjusting information to more closely align with the objectives and goals of warning message design.

Wael Alkusaibati, Sofie Pilemalm

ICT-enabled or digitalized co-production of public services has become increasingly relevant to emergency response and crisis management. This study provides a literature review on this phenomenon, exploring both large-scale crises and frequent emergencies. We found that research in the domain is scarce and focuses mainly on the phenomenon in terms of digital volunteerism. In large-scale crises, they mostly refer to spontaneous forms of volunteering, and in smaller emergencies, to more organized volunteers that collaborate with a response organization over time. Similarities to digitalized co-production in the public sector generally include financial, administrative, ICT, and demographic factors. Differences include, e

Li Wei’an, M. Yin

Supply chain disruptions have a significant negative impact on organizational performance, and while companies seek to mitigate the impact of disruption risks, supply chain members propose contingency governance measures from different perspectives to build resilient supply chain systems. However, there is no clear governance consensus on supply chain contingency governance, nor is it clear what research themes exist in this area, so to advance the scientific debate on this topic, this paper presents a systematic review of the literature. Based on the core literature base of Web of Science (WoS), screening 3791 academic publications closely related to supply chain emergency governance as research objects, using visual measurement tools to conduct descriptive statistical analysis and cluster analysis of the literature, summarizing the research on supply chain emergency governance. The results found that the literature in the field of supply chain emergency governance continues to rise, and with the outbreak of the COVID‐19, the number of publications in this field reached a record high in 2021. In the cluster analysis of the literature, supply chain management, blockchain, and emergency response research under the COVID‐19 ranked in the top three research themes. This paper provides a literature review for these three major clusters and summarizes the research on emergency governance under different themes. Finally, future research directions in this area are proposed based on the gaps and limitations of existing research. [ FROM AUTHOR] Copyright of Journal of Contingencies & Crisis Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)