The Cost-Effectiveness of Lifesaving Interventions in Sweden

In this article, we discuss under what conditions an estimated cost per statistical life saved can be interpreted as an implied lifevalue. Furthermore, we state optimality conditions with respect to variation in implied lifevalues. The cost-effectiveness, together with references, are presented for 165 lifesaving interventions in Sweden. The cost-effectiveness of interventions has been found in publicly available analyses, or in some cases been calculated by us. Several of these interventions produce net savings for society. The most expensive interventions cost several hundred million SEK, or more, per life saved. To improve the comparability of the interventions, certain criteria have been used to standardize the estimates. Still, dissimilarities in the calculation of implied life values remain and the quality of the original data is in some cases uncertain. Despite this and the fact that the interventions are not a representative sample, it is nevertheless possible to conclude that implied life values vary greatly both within and between different sectors of the Swedish society, much in the same manner as in current U.S. analyses.     

Cost-Effectiveness of Risk-Reduction Measures from a National Viewpoint: A Case Study of the Angra Nuclear Plant in Brazil

In this paper a systemic or national approach to cost-effectiveness analysis of risk-reduction measures is reviewed, and its advantages and limitations are discussed. The method is applied to the problem of the cost-effectiveness of increasing the Angra 3 NPP containment wall thickness from the present 60 cm to 180 cm thick in order to prevent damage to the reactor core in case of a direct commercial aircraft crash on it. It is concluded that this measure is not cost-effective if the referred approach is considered.     

人才环境及基于神经网络的陕西经济发展预测模型研究

利用多层前馈神经网络的反传算法(BP算法),在建立陕西人才环境评价指标体系的基础上,采用MATLAB软件建立了人才环境与经济发展关系的神经网络模型,映射出各年人才环境指标与人均GDP指标之间的函数关系,此BP神经网络可以成功地根据陕西人才环境指标对经济发展进行预测。     

Allocation and Pricing of Substitutable Goods: Theory and Algorithm

Motivated by the thriving market of online display advertising, we study a problem of allocating numerous types of goods among many agents who have concave valuations (capturing risk aversion) and heterogeneous substitution preferences across types of goods. The goal is both to provide a theory for optimal allocation of such goods, and to offer a scalable algorithm to compute the optimal allocation and the associated price vectors. Drawing on the economic concept of Pareto optimality, we develop an equilibrium pricing theory for heterogeneous substitutable goods that parallels the pricing theory for financial assets. We then develop a fast algorithm called SIMS (standardization‐and‐indicator‐matrix‐search). Extensive numerical simulations suggest that the SIMS algorithm is very scalable and is up to three magnitudes faster than well‐known alternative algorithms. Our theory and algorithm have important implications for the pricing and scheduling of online display advertisement and beyond.     

Concentrating on the Worst Performers

There is a substantial variation in the quality of operators of nuclear power plants, and it is therefore widely believed that regulatory attention is best directed at the worst performers. What is not immediately apparent is a strategy for the optimal allocation of regulatory resources. We study a simple model for this problem, and find that, under reasonable assumptions, the optimal allocation does indeed behave as expected. The proper degree of unbalance, however, depends upon the effectiveness of regulation itself and on the variation among performers, ineffective regulation leading to more concentration on the bottom of the list and a net reduction in attention to the top. Not surprisingly, the optimal strategy is to press toward parity in risk, even if it means allowing some plants to become riskier. This strategy leads to a minimized net probability of accident anywhere.     

资源配置最优控制模型研究

针对我国当前所面临的资金短缺和劳动力过剩的实际情况,本文从经济发展的内在规律和长期趋势出发,建立经济发展过程中的资源配置最优控制模型,并通过对模型的实证分析,探索在各种资源约束下经济发展最优化的有效途径,为制定经济发展规划、各种资源的最佳配置等方面提供一定的参考。     

大型建筑工程项目资源配置模型及策略研究——基于系统动力学的建模和仿真

大型建筑工程项目多类型资源的有效配置,是现阶段项目管理理论与工程管理实践面临的关键问题,特别是在考虑工艺顺序和间歇时间的工作可操作性特点,以及多资源之间反馈影响的情况下。通过整合挣值法和系统动力学理论,在分析资源可用性和工作可操作性之间因果关系的基础上,本文构建了大型建筑工程项目多资源配置的系统动力学模型。以上海市重大工程投资统计数据作为模型参数依据,模型的仿真结果表明:建筑工程项目不同类型资源其配置重要性与系统影响性存在显著差异,在制定资源配置策略时应同时考虑项目运作方式的特征与多资源之间的匹配,资源不匹配则容易导致资源配置系统失去稳态或策略失效。这为进一步研究项目管理中多资源配置提供了理论参考和实践支持。     

政府竞争、资本配置与上市公司“壳资源”转让

地方政府间的晋升锦标赛迫使政府官员寻求一切可能的方式完成政绩、争夺和保护地区的优势资源,人为地干预资本资源配置.以2000年至2006年地方上市国有企业被民营企业并购、控制权发生转移的公司作为样本,以是否为辖区内并购作为因变量,以行业调整的绩效指标和企业规模作为自变量,建立Logit回归模型,探讨稀缺的"壳资源"在辖区内外转让是否因其质量的不同而具有差异性.在控制公司特征、治理因素和年份固定效应等因素后,发现在卖方主导的国有上市公司"壳资源"转让过程中,地方政府倾向于将绩效好、影响力大的国有企业转让给本地民营企业,而将绩效差、影响力小的国有企业转让给外地民营企业.根据地区竞争力水平对样本进行分组,发现竞争力排名靠后的地区比排名靠前的地区"壳资源"的质量在辖区内外转让的差异更为明显,表明在经济基础较为薄弱的辖区,地方政府更倾向于采取地方保护主义的方式维持地方经济.     

机动车限牌的社会福利影响和最优配额研究

为了应对日益严重的交通拥堵和空气污染问题,中国越来越多的大城市采取限牌政策来控制机动车保有量的增长.通过估计北京、上海、天津和南京4座城市机动车使用外部成本,和消费者对机动车牌照的支付意愿(willingness to pay,WTP),对拍卖、摇号和混合3种机动车限牌政策的社会福利影响进行了定量分析.实证研究结果表明,摇号模式带来的社会福利损失最大,拍卖模式带来的社会福利损失最小,混合模式带来的社会福利损失居中.与最优牌照配额相比,2012年北京和上海的真实配额存在138亿元和28.6亿元的社会福利净损失.如果4座城市采用最优配额和牌照拍卖制度,在控制机动车数量增长的同时,将获得10亿到200亿不等的可用于城市交通基础设施建设或公共交通补贴的可观的财政收入.     

锦标赛制度与基金风险调整:理论拓展与经验证据

从理论与实证角度分析了CEO开放性特征对战略惯性及组织绩效的作用机制,得到以下研究结论:第一,CEO开放性程度越高,组织越倾向于采取适应环境的动态资源配置战略,从而组织的战略惯性程度越低;第二,CEO的股权拥有程度和自主权高低程度对其开放性程度与组织惯性之间关系起到显著调节作用,即CEO持股水平越高则开放性CEO维持组织战略现状的动机越强,而CEO所拥有的管理自主权越高则越倾向于去打破组织的战略现状;第三,组织制度环境对CEO开放性程度与战略惯性之间关系同样起到显著的调节作用,在国企任职的CEO相对于家族企业任职的CEO而言,其开放性程度对组织惯性的负向影响程度更小;第四,相比于线性关系,倒U型假设更有助于解释战略惯性与组织绩效之间的关系。     

CEO开放性特征、战略惯性和组织绩效①--基于中国上市公司的实证分析

从理论与实证角度分析了CEO开放性特征对战略惯性及组织绩效的作用机制,得到以下研究结论：第一,CEO开放性程度越高,组织越倾向于采取适应环境的动态资源配置战略,从而组织的战略惯性程度越低;第二,CEO的股权拥有程度和自主权高低程度对其开放性程度与组织惯性之间关系起到显著调节作用,即CEO持股水平越高则开放性CEO维持组织战略现状的动机越强,而 CEO所拥有的管理自主权越高则越倾向于去打破组织的战略现状;第三,组织制度环境对CEO开放性程度与战略惯性之间关系同样起到显著的调节作用,在国企任职的CEO相对于家族企业任职的CEO而言,其开放性程度对组织惯性的负向影响程度更小;第四,相比于线性关系,倒U型假设更有助于解释战略惯性与组织绩效之间的关系。     

Managing Risk at the Tucson Sector of the U.S. Border Patrol

This article describes a risk analysis used to inform resource allocation at the Tucson Sector of the U.S. Border Patrol, the busiest sector for alien and drug trafficking along the Southwest land border with Mexico. The model and methodology that underlie this analysis are generally applicable to many resource allocation decisions regarding the management of frequently occurring hazards, decisions regularly made by officials at all levels of the homeland security enterprise. The analysis was executed by agents without previous risk expertise working under a short time frame, and the findings from the analysis were used to inform several resource allocation decisions.     

Optimal Allocation of Effort to Software Maintenance: A Queuing Theory Approach

We develop variations of the M|G|1 queue to model the process of software maintenance within organizations and use these models to compute the optimal allocation of resources to software maintenance. User requests are assumed to arrive following a Poisson process and a binomial distribution is used to model duplication of requests. We obtain expressions for expected queue lengths with an exponential server using an N‐policy for an integer N≥1. We also obtain the optimal batching size and mean service rate by minimizing the total cost consisting of the cost of the server, the cost of waiting, and the fixed cost of maintenance, if applicable.     

Centralized resource planning and Yardstick competition

Multidivisional and decentralized firms often operate inefficiently. In most cases, central management's instruments to influence its branches' behavior are limited. Although relative performance evaluation has been argued to be of great use in defining incentive mechanisms, such approaches cannot be transferred easily to internal performance management. We approach this issue by changing the perspective of performance evaluation. Based on the recently introduced CRA-DEA model, we develop a new super-efficiency measure that enables to establish purposive intra-organizational incentive mechanisms. By means of a numerical example, analyzing the performance of a German retail bank, the applicability of our measure is shown and compared to standard DEA models. Centralized super-efficiency seems able to suit the specific needs of intra-organizational performance management.     

Preventing and Diagnosing Colorectal Cancer with a Limited Colonoscopy Resource

This paper explores how the capacity of colonoscopy services should be allocated for screening and diagnosis of colorectal cancer to improve health outcomes. Both of these services are important since screening prevents cancer by removing polyps, while diagnosis is required to start treatment for cancer. This paper first presents a basic compartmental model to illustrate the trade‐off between these two analytically. Further, a more realistic population dynamics model with resource constraints is introduced for colorectal cancer screening and analyzed numerically. The best resource allocation decisions are investigated with the objectives of minimizing mortality or incidence rates. We provide a sensitivity analysis with respect to policy and disease‐related parameters. We conclude that to minimize mortality, the capacity should be rationed to ensure that the wait for diagnosis is at reasonable levels. When the relevant performance measure is the incidence rate, screening is allocated more capacity compared to the case with mortality rate measure. We also show that benefits from increasing compliance to screening programs can only be realized if there is sufficient service capacity.     

效率与公平视角下企业及政府的资源配置决策

考虑企业及政府资源配置中效率与公平目标的不同内涵,采用"客户嫉妒"和"个体变权"刻画不同主体的决策行为,分别引入公平参数建立多目标决策模型,并提出基于客户和决策者偏好的公平参数选择方法,实现效率与公平的权衡。将模型转化为变分不等式,设计修正投影算法求解。通过算例进一步分析了不同主体的决策行为差异、公平参数的选择及影响。研究表明:企业与政府的效率最优决策相近,但公平最优决策差异明显;客户公平偏好越高,企业资源配置的分化特征反而越显著;政府决策者公平偏好越高,所有个体间资源配置趋于均等。     

Guiding Resource Allocations Based on Terrorism Risk

Establishing tolerable levels of risk is one of the most contentious and important risk management decisions. With every regulatory or funding decision for a risk management program, society decides whether or not risk is tolerable. The Urban Area Security Initiative (UASI) is a Department of Homeland Security (DHS) grant program designed to enhance security and overall preparedness to prevent, respond to, and recover from acts of terrorism by providing financial assistance for planning, equipment, training, and exercise needs of large urban areas. After briefly reviewing definitions of terrorism risk and rationales for risk-based resource allocation, this article compares estimates of terrorism risk in urban areas that received UASI funding in 2004 to other federal risk management decisions. This comparison suggests that UASI allocations are generally consistent with other federal risk management decisions. However, terrorism risk in several cities that received funding is below levels that are often tolerated in other risk management contexts. There are several reasons why the conclusions about terrorism risk being de minimis in specific cities should be challenged. Some of these surround the means used to estimate terrorism risk for this study. Others involve the comparison that is made to other risk management decisions. However, many of the observations reported are valid even if reported terrorism risk estimates are several orders of magnitude too low. Discussion of resource allocation should be extended to address risk tolerance and include explicit comparisons, like those presented here, to other risk management decisions.     

联合经济批量模型中的损失补贴与利益分配问题研究

针对单供应商和单采购商构成的供应链系统,分采购商占主导地位和供应商占主导地位两种情形,讨论了采购商的最优订货决策与供应商的最优生产决策,以及它们合作情形下的系统最优决策,给出了采购商和供应商各自独立决策与联合决策下,它们各自的成本函数以及供应链系统的总成本函数.最后,通过比较独立决策与联合决策下采购商和供应商的成本函数,分析了联合经济批量模型中的损失补贴与利益分配问题.     

Optimal Resource Allocation for Defense of Targets Based on Differing Measures of Attractiveness

This article describes the results of applying a rigorous computational model to the problem of the optimal defensive resource allocation among potential terrorist targets. In particular, our study explores how the optimal budget allocation depends on the cost effectiveness of security investments, the defender's valuations of the various targets, and the extent of the defender's uncertainty about the attacker's target valuations. We use expected property damage, expected fatalities, and two metrics of critical infrastructure (airports and bridges) as our measures of target attractiveness. Our results show that the cost effectiveness of security investment has a large impact on the optimal budget allocation. Also, different measures of target attractiveness yield different optimal budget allocations, emphasizing the importance of developing more realistic terrorist objective functions for use in budget allocation decisions for homeland security.