Funds allocation in NPOs: the role of administrative cost ratios

Performance measurement of Non-Profit Organizations (NPOs) is of increasing importance for aid agencies, policy-makers and donors. A widely used benchmark for measuring the efficiency of NPOs is the overhead cost ratio, consisting of the total money spent on administration and fundraising relative to the budget. Donors generally favor a lower overhead cost ratio as it ensures that more money directly reaches beneficiaries. Unlike fundraising expenses, administrative costs do not contribute to advertising the actions of an NPO even though they account for a significant proportion of overhead cost. Reducing administrative expenses is a logical consequence from a financial viewpoint, but might negatively affect NPOs through the resulting administrative capacities. This phenomenon is known as “Nonprofit Starvation Cycle”. This work provides an analytical framework for analyzing NPO decision making concerning administrative costs. The paper provides answers to important research questions on the optimal level of administrative spending, the influencing factors and the effects of available information on NPOs. The research shows that focusing on financial performance measurements can result in reduced utility created for NPOs. Less transparency often leads to increased utility for NPOs, but more transparency can increase NPOs’ utility if the information available exceeds a certain threshold. Fluctuating donations are challenging for NPOs’ planning and may impact administrative capacities negatively.

     

An insurance risk management framework for disaster relief and supply chain disruption inventory planning

Government agencies, not-for-profit organizations, and private corporations often assume leading roles in the delivery of supplies, equipment, and manpower to support initial response operations after a disaster strikes. These organizations are faced with challenging logistics decisions to ensure that the right supplies (including equipment and personnel) are in the right places, at the right times, and in the right quantities. Such logistics planning decisions are further complicated by the uncertainties associated with predicting whether or not a potential threat will materialize into an emergency situation. This paper introduces newsvendor variants that account for demand uncertainty as well as the uncertainty surrounding the occurrence of an extreme event. The optimal inventory level is determined and compared to the classic newsvendor solution and the difference is interpreted as the insurance premium associated with proactive disaster-relief planning. The insurance policy framework represents a practical approach for decision makers to quantify the risks and benefits associated with stocking decisions related to preparing for disaster relief efforts or supply chain disruptions.     

基于后悔理论的灰色应急决策方案动态调整方法

突发事件发展具有可变性、动态性、随机性等特点,这要求决策者能根据实际情况及时调整应急方案,在此过程中决策者往往表现出“有限理性”的心理特征。针对以上情形,提出一种基于后悔理论的决策方法,以解决不确定环境下考虑决策者心理因素的应急方案动态调整问题。该方法首先描述分析了基于灰数信息的应急调整方案的生成过程;然后从后悔规避的视角构造了调整方案集关于处置效果、调整成本、应对损失三方面的灰色感知效用矩阵;进一步,用转移概率矩阵预测突发事件的演化概率,计算各调整方案的灰色综合感知效用值以选出最佳调整方案;最后,通过实例验证了该方法的可行性和有效性。结果表明,该方法贴近决策实际、具有较强的实用性;能够为应急决策的方案调整问题提供方法指导和理论支持。     

Publicity vs. impact in nonprofit disclosures and donor preferences: a sequential game with one nonprofit organization and N donors

Charitable giving is one of the essential tasks of a properly functioning civil society. This task is greatly complicated by the lack of organizational transparency and by the information asymmetries that often exist between organizations and donors in the market for charitable donations. The disclosure of financial, performance, donor-relations, and fundraising-related data is thus an important tool for nonprofit organizations attempting to attract greater donations while boosting accountability and public trust. There are, however, varying payoffs associated with such disclosure depending on the nature of donor preferences and the relative openness and effectiveness of competing organizations. To help understand the interplay between nonprofit organizational disclosures and individual donations, we present a novel game-theoretic model of disclosure–donation interactions that incorporates the predominant forms of both donor preferences and “value-relevant” information.     

Donation management for menu planning at soup kitchens

The food industry is confronted with a pressure to reduce waste and to make agreements on donating surplus food to charitable organizations. Charitable organizations such as food banks and soup kitchens can use these donations in preparing food parcels or meals for their clients. For soup kitchens, donation management is strongly influencing menu planning, and conversely, menu planning considerations have a strong impact on donation management decisions. To make the best use of (mostly highly perishable) food donations, we develop an MILP model for integrated donation management and menu planning that proposes a menu plan and suggests which (part of the) donations to accept. The combination of menu planning and donation management is essential for soup kitchens, but has not been studied before.The model is used to assess the impact of contracts on a strategic or tactical level, and captures operational decision making due to the integration of donation management and menu planning. To deal with meal variety considerations and to resemble planning practices, the developed model is solved in a rolling horizon. The results show that (i) the use of donations reduces overall costs for the soup kitchen; (ii) despite the short shelf life of donations, most donations can be used efficiently; and (iii) meal variety can be easily ensured and food donations increase this variety. In addition to the benefits for soup kitchens, the approach has implications for waste reduction in food supply chains, by structural/contractual donations of surplus food by retailers.     

Offshore outsourcing decision making: A policy-maker’s perspective

This research aims at finding the best governing policy for offshore outsourcing of business activities. We use Analytical Network Process, a multicriteria decision making methodology, to create the evaluation framework. From the perspective of decision makers, stakeholders, and influence groups, four policy options are evaluated with respect to approximately 50 economic, political, technological and other factors. The model provides both long-term and short-term views of the outsourcing issue concerned to all parties. The all-inclusive approach helps policy makers to decide on the best policy and has the potential to ease tension between proponents and opponents of offshore outsourcing.     

Bayesian policy support for adaptive strategies using computer models for complex physical systems

In this paper, we discuss combining expert knowledge and computer simulators in order to provide decision support for policy makers managing complex physical systems. We allow future states of the complex system to be viewed after initial policy is made, and for those states to influence revision of policy. The potential for future observations and intervention impacts heavily on optimal policy for today and this is handled within our approach. We show how deriving policy dependent system uncertainty using computer models leads to an intractable backwards induction problem for the resulting decision tree. We introduce an algorithm for emulating an upper bound on our expected loss surface for all possible policies and discuss how this might be used in policy support. To illustrate our methodology, we look at choosing an optimal CO₂ abatement strategy, combining an intermediate complexity climate model and an economic utility model with climate data.     

考虑后悔与失望行为的应急方案选择方法

考虑到在应急管理问题中,当决策者需要进行应急方案选择时,会存在两类心理行为:后悔心理行为和失望心理行为,针对具有混合多指标信息的应急方案选择问题提出了一种新方法。首先,计算应急方案关于伤亡人数、财产损失和社会影响等指标信息的效用值。然后,考虑到决策者的两类心理行为的特征,为确定不同的应急方案的感知效用,分别提出计算方案后悔-欣喜值和失望-愉悦值的方法。进一步地,考虑到不同应急方案的投入成本不同,计算决策者关于不同方案的投入成本的感知效用。在此基础上,根据不同应急方案的总体感知效用值,进行应急方案的排序或优选。最后,通过实例验证所提方法的可行性和有效性。     

A periodic review inventory system with two supply modes

We describe a periodic review inventory system in which there are two modes of resupply, namely a regular mode and an emergency mode. Orders placed through the emergency channel have a shorter supply lead time but are subject to higher ordering costs compared to orders placed through the regular channel. We analyze this problem within the framework of an order-up-to-R inventory control policy. At each epoch, the inventory manager must decide which of the two supply modes to use and then order enough units to raise the inventory position to a level R. We show that given any non-negative order-up-to level, either only the regular supply mode is used, or there exists an indifference inventory level such that if the inventory position at the review epoch is below the indifference inventory level, the emergency supply mode is used. We also develop procedures for solving for the two policy parameters, i.e., the order-up-to level and the indifference inventory level.     

Variational inequalities for international general financial equilibrium modeling and computation

In this paper, a variational inequality approach for modeling competitive general international financial equilibrium is presented, within which general utility functions and taxes, transaction costs, and price policy interventions are explicitly incorporated. The paper examines taxes that depend both on the origin and on the type of investing sector, and price policy interventions that allow the monetary authorities to set upper and lower prices for all instruments and currencies. The optimal composition of assets and liabilities for each sector of each country, as well as the prices of the instruments and the exchange rates, in terms of a basic currency are obtained. We present both qualitative properties of the equilibrium pattern, and propose an algorithm for the computation of the pattern along with convergence results. Finally, we study the special case where the utility function is quadratic and we apply the proposed algorithm in order to compute the equilibrium pattern for a series of numerical examples.     

A multi-criteria optimization model for humanitarian aid distribution

Natural disasters are phenomenons which strike countries all around the world. Sometimes, either by the intensity of the phenomenon or the vulnerability of the country, help is requested from the rest of the world and relief organizations respond by delivering basic aid to those in need. Humanitarian logistics is a critical factor in managing relief operations and, in general, there is a lack of attention on the development of mathematical models and solution algorithms for strategic and tactical decisions in this area. We acknowledge that in humanitarian logistics traditional cost minimizing measures are not central, and postulate that other performance measures such as time of response, equity of the distribution or reliability and security of the operation routes become more relevant. In this paper several criteria for an aid distribution problem are proposed and a multi-criteria optimization model dealing with all these aspects is developed. This model is the core of a decision support system under development to assist organizations in charge of the distribution of humanitarian aid. Once the proposed criteria and the model are described, an illustrative case study based on the 2010 Haiti catastrophic earthquake is presented, showing the usefulness of the proposal.     

随机需求应急物流多阶段定位-路径鲁棒优化研究

为提高应急物流系统的应急反应能力,论文针对需求随机变化的应急物流定位-路径问题,利用鲁棒优化的思想将灾区物资需求量表示为区间型数据,将应急救援过程划分为多个阶段,以总救援时间和系统总成本最小为目标,构建了多物资多运输车辆应急物流定位-路径优化模型,设计了改进的遗传算法对其进行求解。实例计算结果表明,该模型和算法可以有效地解决应急物流系统中需求随机变化的定位-路径问题,为政府机构应对重大突发事件提供科学的决策参考。     

MOIRA: A decision support system for decision making on aquatic ecosystems contaminated by radioactive fallout

Interventions to restore radionuclide contaminated aquatic ecosystems may reduce individual and collective radiation doses, but may also result in detrimental ecological, social and economic effects. Decision makers must carefully evaluate possible impacts before choosing a countermeasure, hence decision analysis methods constitute an important aid to rank intervention strategies after the contamination of an aquatic ecosystem. We describe MOIRA, a decision support system for the identification of optimal remedial strategies to restore water systems after accidental introduction of radioactive substances. MOIRA includes an evaluation module based on a multi-attribute value model to rank alternatives and a module to perform multiparametric sensitivity analyses, both with respect to weights and values, to allow us to gain insights into the problem. The problem is under certainty since the validation of models used to quantify countermeasure impacts suggests little uncertainty in policy effects.The system is implemented in a PC based decision support system which allows the inclusion of all relevant information.     

Complex behaviour in a production–distribution model

The purpose of this paper is to show how the cascaded structure of a production–distribution chain can produce a wide variety of dynamic behaviours. Despite the apparent simplicity of the chain, the bounded rationality of human decision making interferes with the information feedbacks, nonlinearities and time delays of the system to produce exceedingly complex behaviour. When simulated with realistic parameter values, the model can exhibit stationary periodic, quasiperiodic as well as chaotic and hyperchaotic motions. Lyapunov exponents are used to characterize the different types of behaviour. Repeated simulation reveals how the profile of operating cost is related to the modes of behaviour and to the conditions that generate chaos. Detailed maps of parameter space graphically show the influence of inventory control policies upon dynamics and costs. The analyses illustrate why it is so difficult for decision makers to “navigate” in low-cost policy parameter regions. Suggestions are made for decision heuristics that avoid high-cost, unstable solutions.     

The adoption of environmental and risk management practices: Relationships to environmental performance

The Strategic Goals Program sponsored by the United States Environmental Protection Agency which focuses on the Metal Finishing Industry is used to investigate some pertinent issues related to small manufacturing enterprises' environmental performance. Results from the initial years of this program are used to evaluate a number of hypotheses related to the relationship between environmental performance and adoption of environmental and risk management practices, especially among smaller organizations. The methodology uses unique structuring of data to determine temporal environmental performance using data envelopment analysis. Results show that early and increased investment in these practices and programs may not provide for better performance benefits. The findings have implications for environmental managers in smaller organizations and policy makers overseeing these types of organizations.     

Modelling the Flow of Projects Through an Architects' Office

There are many types of organization which have to deal with very variable workloads of project-like activities. They include research laboratories, design organizations and advertising agencies as well as O.R. departments. Their characteristic problem is that of avoiding over-run on due dates and on costs.This is a case study of architects' offices but the other comparable complex queueing systems present similar problems. A simulation model has been developed called OFFice SIMulation. Experiments with the model applied to building design offices have provided new insights into the running of such offices. Also they have raised a number of general questions indicating the dangers of deterministic attitudes in the management of this type of system. These questions are concerned with (i) the trade-off between elapsed time and resources, (ii) loss of formal unified control at the top in favour of informal independent responses at the bottom, (iii) long transient times to introduce change, (iv) loss of the usual benefits of large-scale operations.     

Reserving relief supplies for earthquake: a multi-attribute decision making of China Red Cross

Earthquake usually causes grievous damages especially in the earthquake prone areas. Building a fast and effective relief system is very important. China Red Cross is the largest humanitarian organizations in China. To improve its disaster response system, reserving relief supplies gets more and more attentions. In this article, a decision making programming based on the data envelopment analysis method is proposed in the construction of reserve network for China Red Cross with three factors, including cost, risk and utility. Four warehouses are selected and the optimal allocation strategies are obtained under the principles of equity and effectiveness which should be obeyed in humanitarian assistance.     

Non zero-sum stochastic games in admission,service and routing control in queueing systems

The purpose of this paper is to investigate situations of non-cooperative dynamic control of queueing systems by two agents, having different objectives. The main part of the paper is devoted to analyzing a problem of an admission and a service (vacation) control. The admission controller has to decide whether to allow arrivals to occur. Once the queue empties, the server goes on vacation, and controls the vacations duration (according to the state and past history of the queue). The immediate costs for each controller are increasing in the number of customers, but no convexity assumptions are made. The controllers are shown to have a stationary equilibrium policy pair, for which each controller uses a stationary threshold type policy with randomization in at most one state. We then investigate a problem of a non-zero sum stochastic game between a router into several queues, and a second controller that allocates some extra service capacity to one of the queues. We establish the equilibrium of a policy pair for which the router uses the intuitive Join the shortest queue policy.     

A Markov decision process model for equitable distribution of supplies under uncertainty

Many individuals suffering from food insecurity obtain assistance from governmental programs and nonprofit agencies such as food banks. Much of the food distributed by food banks come from donations which are received from various sources in uncertain quantities at random points in time. This paper presents a model that can assist food banks in distributing these uncertain supplies equitably and measure the performance of their distribution efforts. We formulate this decision problem as a discrete-time, discrete state Markov decision process that considers stochastic supply, deterministic demand and an equity-based objective. We investigate three different allocation rules and describe the optimal policy as a function of available inventory. We also provide county level estimates of unmet need and determine the probability distribution associated with the number of underserved counties. A numerical study is performed to show how the allocation policy and unmet need are impacted by uncertain supply and deterministic, time-varying demand. We also compare different allocation rules in terms of equity and effectiveness.     

不确定条件下应急供应链可靠性评价模型

以应急供应链可靠性为评价对象,在对其影响因素进行分析的基础上,从保障机制、信息系统、网络结构、运作流程、资金保障五个方面构建了评价指标体系,考虑应急供应链可靠性评价信息受主客观因素影响难以精确测定,依据指标特点运用语言评价值,区间值,数值多种形式测定指标值,然后将语言评价值和数值转化为区间值,运用层次分析法、熵值法分别计算一、二级指标权重,再运用联系数对指标值和权重进行集结排序。最后设计算例验证了模型的有效性和适用性。