Game-based Crisis Simulation and Generation Framework: Design and Implementation Structure

Crisis is an infrequent and unpredictable event. Training and preparation process requires tools for representation of crisis context. Particularly, Crisis Event consists of different situations which can occur at the same time combining into complex situation and becoming a challenge in collaboration of several crisis management departments. Studying of Resource distribution also improving an effectively in solving the ongoing crisis. By integrating modern game technology, development process of assistance and simulation system can become a cost-effective solution to allow observation and test practice procedures. Therefore, we aim to discuss and provide an implementation design choices of general framework tool for representing of coverage terrain, resources, different stakeholders and structure of crisis scenario using Unity3D game engine technology. The paper focuses on the procedural generation of complex 3D environment for crisis scenarios generation and disaster management, and introduces the framework, structure, functions and the visualization, and performance evaluation of the framework

Survey: Development and analysis of a games-based crisis scenario generation system

Crisis is an infrequent and unpredictable event which is challenging to prepare and resolve. Serious-game approach proved to provide potential support in training and simulating event of real-world crisis situation to different stakeholders. Yet in practice, the approach meets with difficulty on how to setup and utilize different core components such as asset management, crisis scenario generation, agent simulation, real-world constraints, and the evaluation process to yield beneficial information upon running the system. To address this issue, the key question is what can be done to propose a general crisis game-based framework providing necessary core components while generating evaluation result yielding potential analytical data for a crisis management process. Therefore, in this paper, we aim to review and consolidate the existing research on scenario generation techniques and related crisis simulation framework, then to propose novel solution to combine both processes and to derive a desirable scenario content which is also being validated in the simulation framework based on the JADE multi-agent architecture. © Springer International Publishing Switzerland 2016

Game Theory of Social Distancing in Response to an Epidemic

Social distancing practices are changes in behavior that prevent disease transmission by reducing contact rates between susceptible individuals and infected individuals who may transmit the disease. Social distancing practices can reduce the severity of an epidemic, but the benefits of social distancing depend on the extent to which it is used by individuals. Individuals are sometimes reluctant to pay the costs inherent in social distancing, and this can limit its effectiveness as a control measure. This paper formulates a differential-game to identify how individuals would best use social distancing and related self-protective behaviors during an epidemic. The epidemic is described by a simple, well-mixed ordinary differential equation model. We use the differential game to study potential value of social distancing as a mitigation measure by calculating the equilibrium behaviors under a variety of cost-functions. Numerical methods are used to calculate the total costs of an epidemic under equilibrium behaviors as a function of the time to mass vaccination, following epidemic identification. The key parameters in the analysis are the basic reproduction number and the baseline efficiency of social distancing. The results show that social distancing is most beneficial to individuals for basic reproduction numbers around 2. In the absence of vaccination or other intervention measures, optimal social distancing never recovers more than 30% of the cost of infection. We also show how the window of opportunity for vaccine development lengthens as the efficiency of social distancing and detection improve

The Channel Strategy of Social Commerce-Based Business Model Innovation

社会化商务应用正成为企业开展商务模式（商业模式）创新活动、应对经济增速放缓、竞争加剧等严峻挑战的重要手段。社会化商务应用企业通常需要考虑如何在微博、人际交往等应用渠道中做出适合的选择、如何在所选的渠道中开展促销活动。为此，本文对社会化商务模式创新的渠道选择策略、渠道促销策略进行了探讨。在分析社会化商务参与者行为、用户与应用企业价值创造、提出社会化商务狭义、广义概念的基础上，结合广义评论行为、产品价值理性评价程度、广义虚拟经济理论中的使用价值、虚拟价值等，本文就社会化商务应用企业、用户所组成的社会经济复杂系统，运用基于主体的计算实验方法构建了营销领域的社会化商务应用模型，开展了社会化商务模式创新...For the decreasing economy growth rate, low growth rate of demand and more intense competition become the serious challenges of companies in many industries. Social commerce which has the advantages of huge users, low cost and high efficiency is one of what the companies should focus on in business model innovation. The adopter of social commerce often needs to decide how to select suitable social...学位：管理学博士院系专业：管理学院_技术经济及管理学号：1772011015357

Dynamic pricing strategy to optimally allocate vaccines

In the United States, the Advisory Committee on Immunization Practices (ACIP) makes recommendations as to which cohorts (identified groups of individuals) ought to have higher priority access to vaccines when their supply is insufficient to immunize all susceptible individuals in the country. Typically, cohorts are determined based on susceptibility to contracting seasonal influenza and on the resulting consequences of infection for different age groups. For seasonal influenza, high-risk cohorts commonly include children, teenagers, pregnant women and people with different chronic diseases. This study proposes the application of revenue management theory to better allocate seasonal influenza vaccines among different risk-based population cohorts. Our model maximizes the number of immunized individuals by dynamically adjusting the price per dose in each cohort as to discourage vaccination in low-risk cohorts and preserve more supply for high-risk cohorts. Experimental results show that up to 12% of infections and deaths due to seasonal influenza could be avoided by implementing this price discrimination policy in hypothetical yet realistic scenarios

flepiMoP: The evolution of a flexible infectious disease modeling pipeline during the COVID-19 pandemic

The COVID-19 pandemic led to an unprecedented demand for projections of disease burden and healthcare utilization under scenarios ranging from unmitigated spread to strict social distancing policies. In response, members of the Johns Hopkins Infectious Disease Dynamics Group developed flepiMoP (formerly called the COVID Scenario Modeling Pipeline), a comprehensive open-source software pipeline designed for creating and simulating compartmental models of infectious disease transmission and inferring parameters through these models. The framework has been used extensively to produce short-term forecasts and longer-term scenario projections of COVID-19 at the state and county level in the US, for COVID-19 in other countries at various geographic scales, and more recently for seasonal influenza. In this paper, we highlight how the flepiMoP has evolved throughout the COVID-19 pandemic to address changing epidemiological dynamics, new interventions, and shifts in policy-relevant model outputs. As the framework has reached a mature state, we provide a detailed overview of flepiMoP's key features and remaining limitations, thereby distributing flepiMoP and its documentation as a flexible and powerful tool for researchers and public health professionals to rapidly build and deploy large-scale complex infectious disease models for any pathogen and demographic setup