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Health systems are periodically confronted by crises – think of Severe Acute Respiratory Syndrome, H1N1, and Ebola – during which they are called upon to manage exceptional situations without interrupting essential services to the population. The ability to accomplish this dual mandate is at the heart of resilience strategies, which in healthcare systems involve developing surge capacity to manage a sudden influx of patients. The paper aims to discuss these issues.

This paper relates insights from resilience research to the four “S” of surge capacity (staff, stuff, structures and systems) and proposes a framework based on complexity theory to better understand and assess resilience factors that enable the development of surge capacity in complex health systems.

Detailed and dynamic complexities manifest in different challenges during a crisis. Resilience factors are classified according to these types of complexity and along their temporal dimensions: proactive factors that improve preparedness to confront both usual and exceptional requirements, and passive factors that enable response to unexpected demands as they arise during a crisis. The framework is completed by further categorizing resilience factors according to their stabilizing or destabilizing impact, drawing on feedback processes described in complexity theory. Favorable order resilience factors create consistency and act as stabilizing forces in systems, while favorable disorder factors such as diversity and complementarity act as destabilizing forces.

The framework suggests a balanced and innovative process to integrate these factors in a pragmatic approach built around the fours “S” of surge capacity to increase health system resilience.

The purpose of this paper is to investigate different combinations of collaboration strategies to deal with different types of supply chain disruptions, find the best combination, and provide targeting suggestions for investments.

A system dynamics simulation is applied to study a supply chain with three tiers: a producer, a logistics service provider (LSP), and a retailer. There are three types of disruptions to simulate: a producer capacity disruption, an LSP capacity disruption, and a demand disruption. As each tier has the option to choose whether or not to collaborate with the other two tiers, eight (2×2×2) scenarios are generated to represent different combinations of collaboration strategies.

For a producer capacity disruption, both the producer and the LSP should collaborate by providing their surge capacities, while the retailer does not have to collaborate. For an LSP capacity disruption, the producer should not provide its surge capacity, while the LSP should do so; the retailer does not have to collaborate. For a demand disruption, both the producer and the LSP should not provide their surge capacities, while the retailer should not collaborate but play shortage gaming. Targeting suggestions for investments are provided.

Through system dynamics modeling, this study allows the discussion of surge capacity to help supply chain partners and the discussion of shortage gaming when products are oversupplied, in a disruption recovery system over time.

This study aims to explore the management learning during a long-term crisis like a pandemic. The paper addresses both what health-care managers have learnt during the COVID-19 pandemic and how the management learning is characterized.

The paper is based on a qualitative case study carried out during the COVID-19 pandemic at two different public hospitals in Sweden. The study, conducted with semi-structured interviews, applies a combination of within-case analysis and cross-case comparison. The data were analyzed using thematic deductive analysis with the themes, i.e. sensemaking, decision-making and meaning-making.

The COVID-19 pandemic was characterized by uncertainty and a need for continuous learning among the managers at the case hospitals. The learning process that arose was circular in nature, wherein trust played a crucial role in facilitating the flow of information and enabling the managers to get a good sense of the situation. This, in turn, allowed the managers to make decisions meaningful for the organization, which improved the trust for the managers. This circular process was iterated with higher frequency than usual and was a prerequisite for the managers’ learning. The practical implications are that a combined management with hierarchical and distributed management that uses the normal decision routes seems to be the most successful management method in a prolonged crisis as a pandemic.

The gained knowledge can benefit hospital organizations, be used in crisis education and to develop regional contingency plans for pandemics.

This study has explored learning during the COVID-19 pandemic and found a circular process, “the management learning wheel,” which supports management learning in prolonged crises.

Remote power control basically means control at a distance of major switching operations in a generating and distribution system.

The possibility of a bioterrorism event haunts all healthcare organizations. We believe a bioterrorism event is more likely in an urban area, and that urban multiprovider systems will be the “first line healthcare responders.” Due to the lack of empirical research on this topic and firsthand experience with a bioterrorism event, this paper will provide the theoretical underpinnings to support the rationale for multiprovider systems as “first responders.” This chapter outlines the nature and challenges of bioterrorism for a healthcare organization, the likely “state of the art” preparations for such events on the part of the four categories of healthcare organizations, and finally, the implications for the structuring of multiprovider systems to enhance their ability to plan for, and respond to bioterrorism events. Potential future research issues are also addressed.

The purpose of this paper is to provide a simulation modelling framework to examine the behaviour of a serial make-to-stock (MTS) manufacturing system under the influence of various uncertainties. Further, the study analyses effect of propagation uncertainties from lower to upper stream of supply chain.

System dynamics modelling approach has been adopted for modelling and analysing the behaviour of a serial MTS manufacturing system under the influence of different uncertainties such as demand, supplier acquisition rate, raw material (RM) supply lead time, processing time and delay due to machine failure. The backup supply strategy has been proposed to mitigate the adverse effect of the RM supply uncertainty.

The effect of variations of various factors on the performance of a MTS manufacturing supply chain in measured through various performance measures like work-in-progress (WIP) inventory, backlog and RM shortage at both manufacturer’s and supplier’s end. The benefit of adopting backup supply strategy under RM supply uncertainty is demonstrated.

This work is limited to analysis of a serial MTS manufacturing system dealing with a single product having two machines only. The study can be easily extended to a more complex system with multiple machines, lines and products.

A simple simulation framework has been proposed to analyse the effect of various uncertainties on the performance of a MTS manufacturing system. The managers can simulate complex systems using simulation approaches to generate if-then scenarios to gain insight into practical problems and formulate strategies to mitigate adverse effect of uncertainties at various level of supply chain.

The study analyses behaviour of MTS manufacturing system under the effect of various uncertainties operating simultaneously in the system. A backup supplier strategy is proposed to improve the service level at the customer’s end through improving service level at the supplier’s end. Similarly, effective strategies can be tested with the proposed simple model to reduce the effect of uncertainty at different levels of the supply chain.

The purpose of this paper is to study the managing of emergencies pertinent to public health which is critical to the well‐being of a society; as such, the management mechanisms employed should be of great interest and significance for research.

This paper first relies on extensive literature to describe the mechanism used in the USA from three aspects – organizational structure, management system, and logistics network. For the purpose of comparison, the Chinese version of the mechanism is presented from the same three aspects. The two management systems are then compared both qualitatively and quantitatively.

Deficient areas in Chinese public‐health management mechanism as well as challenging issues associated with supply chain design and coordination for emergency supplies in the context of large‐scale public health emergencies with low frequency but catastrophic impacts are found. Specifically, the following three important research problems are revealed from the comparative study: how to establish an efficient organizational structure that incorporates all the relevant entities in public‐health emergency management? How to establish an information system for emergency management that integrates disease surveillance, control, and prevention? How to design an efficient and cost‐effective logistics network to ensure prompt and sufficient delivery of emergency supplies?

To date, this research has been the first of its kind that compares two countries' emergency management systems in the context of public health management.

The purpose of this paper is to present a dynamic model to measure the degree of system’s leanness under dynamic demand conditions using a novel integrated metric.

The multi-stage production system model is based on a system dynamics approach. The leanness level is measured using a new developed integrated metric that combines efficiency, WIP performance as well as service level. The analysis includes design of experiment technique at the initial analysis to examine the most significant parameters impacting the leanness score and then followed by examining different dynamic demand scenarios. Two scenarios were examined: one focussed low demand variation with various means (testing the impact of demand volumes) while the second focussed on high demand variation with constant means (testing the impact of demand variability).

Results using the data from a real case study indicated that given the model parameters, demand rate has the highest impact on leanness score dynamics. The next phase of the analysis thus focussed on investigating the effect of demand dynamics on the leanness score. The analysis highlighted the different effects of demand variability and volumes on the leanness score and its different components leading to various demand and production management recommendations in this dynamic environment.

The presented lean management policies and recommendations are verified within the scope of similar systems to the considered company in terms of manufacturing settings and demand environment. Further research will be carried to extend the dynamic model to other dynamic manufacturing and service settings.

The developed metric can be used not only to assess the leanness level of the systems which is very critical to lean practitioners but also can be used to track lean implementation progress. In addition, the presented analysis outlined various demand management as well as lean implementation policies that can improve the system leanness level and overall performance.

The presented research develops a novel integrated metric and adds to the few literature on dynamic analysis of lean systems. Furthermore, the conducted analysis revealed some new aspects in understanding the relation between demand (variability and volume) and the leanness level of the systems. This will aid lean practitioners to set better demand and production management policies in today’s dynamic environment as well as take better decisions concerning lean technology investments.

The purpose of this paper is to offer a critical examination of the aftermath of the L’Aquila earthquake of 6 April 2009. It considers the elements of the recovery process that are unique or exceptional and endeavours to explain them.

The analysis is based on a survey and synthesis of the abundant literature on the disaster, coupled with observations from the author’s many visits to L’Aquila and personal involvement in the debates on the questions raised during the aftermath.

Several aspects of the disaster are unique. These include the use of large, well-appointed buildings as temporary accommodation and the efforts to use legal processes to obtain justice for alleged mismanagement of both the early emergency situation and faults in the recovery process.

Politics, history, economics and geography have conspired to make the L’Aquila disaster and its aftermath a multi-layered event that poses considerable challenges of interpretation.

The L’Aquila case teaches first that moderate seismic events can entail a long and difficult process of recovery if the initial vulnerability is high. Second, for processes of recovery to be rational, they need to be safeguarded against the effects of political expediency and bureaucratic delay.

Many survivors of the L’Aquila disaster have been hostages to fortune, victims as much of broader political and socio-economic forces than of the earthquake itself.

Although there are now many published analyses of the L’Aquila disaster, as the better part of a decade has elapsed since the event, there is value in taking stock and making a critical assessment of developments. The context of this disaster is dynamic and extraordinarily sophisticated, and it provides the key to interpretation of developments that otherwise would probably seem illogical.