A Systematic Review of Performance Enhancement of Humanitarian Logistics through Transparency: Current Status and Perspectives

The mechanism of how transparency can help to enhance the performance of humanitarian logistics (HL) following disaster relief operation (RO) needs to be explored. Thus, the main purposes of this paper are to systematically review the barriers to and benefits of transparency in the field of HL in order to improve the performance of HL, and also to highlight the role and unique attributes of transparency in the field of HL. A systematic literature review using the CIMO (context, intervention, mechanism, and outcomes) logic approach was adopted to perform the systematic analysis of the previous investigations relevant to the performance enhancement of HL. Most such previous research investigated transparency in the context of HL, with little examination of the outcomes of transparency in HL. Based upon this process, disaster risk can be reduced and managed through efficient HL. So far, the efficiency and performance of HL has been improved through coordination, collaboration and partnership. In the present study, recent developments corresponding to performance enhancement of HL through transparency are reviewed systematically, with a particular focus on the importance of transparency, what organizations can do to become more transparent and the challenges and potential benefits of transparency. The authors provide an in-depth understanding of the barriers and challenges to transparency faced in this field. Furthermore, the challenges in comparing with recent research are also discussed, along with future directions to improve the performance enhancement of HL through transparency. However, the poor performance of HL is one of the challenging issues associated with disaster risk management. This review article will be fruitful for novice researchers and practitioners in managing disaster risk through efficient HL and further advancement in the field of HL. Furthermore this article raises the awareness of the importance of carefully evaluating decisions related to the fair distribution of relief items

Strengthening Resilience of Supply with Essential Goods through Public-Private Emergency Collaborations: Challenges and Incentives

Private actors ensure the supply of essential goods such as food, drinking water, and medicine to the population. However, crises such as natural disasters, human-caused conflicts, or pandemics can cause disruptions of private supply chains and, subsequently, supply shortages in the market. In this case, public actors need to become active and responsible for supplying the population with essential goods. Nevertheless, the ability of public actors to provide essential goods in a crisis is constrained due to limited resources and a lack of knowledge about the relevant commercial supply chains. Therefore, companies that produce, distribute, or sell essential goods can be valuable partners but must be adequately motivated to participate in crisis management. A promising form of collaboration to strengthen resilience lies in the concept of public-private emergency collaborations (PPECs), elaborated in different studies within the dissertation. The necessity of PPECs and their public acceptance depends on the attitude and preparation of the population, which is why the empirical investigation of these accompanying questions is another central part of the dissertation. Five studies published as companion articles address necessary prerequisites and approaches to the design of collaborations in crises: Study A examines the PPEC concept and puts it into a more specific framework, considering logistical requirements in a game-theoretic model. The model addresses private actors’ incentives to collaborate, such as a positive reputation or learning effects for internal processes. Both can provide a substantial —- not least financial —- advantage for the company in the long run. Study B investigates crises and PPECs from a company perspective by evaluating an empirical study with 398 responses from essential goods and logistics companies. The results show companies’ high interest in participating in PPECs. Nevertheless, the data reveals that certain conditions, such as adequate compensation or consideration of companies’ operational procedures, must be fulfilled for collaboration with public actors. Study C addresses the attitude of the population in a survey of 402 randomly selected participants and finds that the population highly values companies’ involvement in PPECs. The companies’ communication strategy and the population’s risk perception affect the attitude. Study D analyzes the stockpiling behavior of the population in two door-to-door surveys, the first with 330 participants and the second with 402. The timing of the before-and-after survey provides a special value: The study considers possible changes due to the COVID-19 pandemic. The results show low stockpiling levels and that stockpiling has only marginally increased during the COVID-19 pandemic. Study E examines an economic experiment with 262 participants in 13 sessions to clarify the importance of safety-stock levels for companies’ reputation in a failure-prone supply chain. The design made it possible to disentangle indirect losses due to customer churn and direct losses due to disruptions, thus quantifying firm reliability and customer loyalty. Four general recommendations for the stakeholders in crisis management, public actors, private actors, and the population, are derived: First, all stakeholders must adapt their behavior and improve current protection measures and strategies against global crises and supply chain disruptions. Second, humanitarian crisis management is a team effort involving many actors. Therefore, understanding synergies, mutual attitudes, and the incentive constellation of the actors involved is a crucial prerequisite for success. Third, crisis management also includes the right communication strategy. It is not only important to contribute but also to communicate it in a successful and convincing way. Fourth, collaborative approaches, as in PPECs, where each stakeholder brings his or her strengths into the collaboration, are beneficial for all parties involved, and increase society’s overall resilience. Consequently, this dissertation provides valuable insights into the status of humanitarian crisis management from the perspective of different stakeholders. It offers the potential to improve this field of research through collaborative approaches, as in PPECs, addressing the strengths and incentives of stakeholders accordingly

Stochastic programming and agent-based simulation approaches for epidemics control and logistics planning

This dissertation addresses the resource allocation challenges of fighting against infectious disease outbreaks. The goal of this dissertation is to formulate multi-stage stochastic programming and agent-based models to address the limitations of former literature in optimizing resource allocation for preventing and controlling epidemics and pandemics. In the first study, a multi-stage stochastic programming compartmental model is presented to integrate the uncertain disease progression and the logistics of resource allocation to control a highly contagious infectious disease. The proposed multi-stage stochastic program, which involves various disease growth scenarios, optimizes the distribution of treatment centers and resources while minimizing the total expected number of new infections and funerals due to an epidemic. Two new equity metrics are defined and formulated, namely infection and capacity equity, to explicitly consider equity for allocating treatment funds and facilities for fair resource allocation in epidemics control. The multi-stage value of the stochastic solution (VSS), demonstrating the superiority of the proposed stochastic programming model over its deterministic counterpart, is studied. The first model is applied to the Ebola Virus Disease (EVD) case in West Africa, including Guinea, Sierra Leone, and Liberia. In the following study, the previous model is extended to a mean-risk multi-stage vaccine allocation model to capture the influence of the outbreak scenarios with low probability but high impact. The Conditional Value at Risk (CVaR) measure used in the model enables a trade-off between the weighted expected loss due to the outbreak and expected risks associated with experiencing disastrous epidemic scenarios. A method is developed to estimate the migration rate between each infected region when limited migration data is available. The second study is applied to the case of EVD in the Democratic Republic of the Congo. In the third study, a new risk-averse multi-stage stochastic epidemics-ventilator-logistics compartmental stochastic programming model is developed to address the resource allocation challenges of mitigating COVID-19. This epidemiological logistics model involves the uncertainty of untested asymptomatic infections and incorporates short-term human migration. Disease transmission is also forecasted through deriving a new formulation of transmission rates that evolve over space and time with respect to various non-pharmaceutical interventions, such as wearing masks, social distancing, and lockdown. In the fourth study, a simulation-optimization approach is introduced to address the vaccination facility location and allocation challenges of the COVID-19 vaccines. A detailed agent-based simulation model of the COVID-19 is extended and integrated with a new vaccination center and vaccine-allocation optimization model. The proposed agent-based simulation-optimization framework simulates the disease transmission first and then minimizes the total number of infections over all the considered regions by choosing the optimal vaccine center locations and vaccine allocation to those centers. Specifically, the simulation provides the number of susceptible and infected individuals in each geographical region for the current time period as an input into the optimization model. The optimization model then minimizes the total number of estimated infections and provides the new vaccine center locations and vaccine allocation decisions for the following time period. Decisions are made on where to open vaccination centers and how many people should be vaccinated at each future stage in each region of the considered geographical location. Then these optimal decision values are imported back into the simulation model to simulate the number of susceptible and infected individuals for the subsequent periods. The agent-based simulation-optimization framework is applied to controlling COVID-19 in the states of New Jersey. The results provide insights into the optimal vaccine center location and vaccine allocation problem under varying budgets and vaccine types while foreseeing potential epidemic growth scenarios over time and spatial locations

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Global Governance Initiative Annual Report 2005

This is an annual report of the WEF