Dynamic inventory decisions for humanitarian aid materials considering budget limitations

In case of disaster, providing relief supplies to the affected people has vital importance. Governmental or non-governmental organizations (NGOs) prepare for disasters by purchasing and stockpiling these aid materials in appropriate quantities. They operate under a limited budget and this budget can either be used before the disaster for stocking decisions under uncertainty or it can be used after the disaster to satisfy the required demand at a higher cost when the uncertainty is resolved. If all the budget is used before the disaster, and if there is no disaster in a long term, there will be a high holding cost. On the other hand, if all the budget is reserved for use after the disaster, meeting the demand will be more costly or the demand may not be met within a certain period of time. Thus, NGOs need to decide how to allocate the budget for pre and post-disaster usage. In this system, the budget of NGOs may also change over time through donations or other incomes. In this point of view, NGOs need to make dynamic stock and budget allocation decisions, under the available budget at hand. In our study, we analyze the dynamic stocking decisions of NGOs using stochastic dynamic programming formulations under budget constraints. We develop infinite horizon stochastic dynamic programming models with and without budget considerations, and compare the results of these models via numerical analysis. Detailed numerical studies and results of the sensitivity analysis show the significance of budget considerations in inventory decisions and the effects of different parameters on the system results.     

Case study in disaster relief: A descriptive analysis of agency partnerships in the aftermath of the January 12th, 2010 Haitian earthquake

This study analyzes the disaster response and recovery efforts following the January 12th, 2010 Haitian earthquake through the eyes of 18 different relief agencies. Focusing on the formation and maintenance of partnerships after the catastrophic earthquake, this paper explores the concepts of cooperation, mutual understanding, and connectivity among agencies responding to the earthquake. The case study is based on results from interviews and interactions with 18 agencies during a month-long trip to Haiti in the summer of 2010. Of the agencies interviewed, it was found that agencies that had no partnerships or presence in Haiti prior to the earthquake were most likely to build new clinics, orphanages, and schools. Additionally, we found that agencies were more likely to develop new partnerships from new contacts rather than dormant contacts. By studying the partnerships between local and international agencies, it was found that their relationships were less stable than partnerships between international agencies. This study hopes to increase understanding and applicability of research in disaster relief networks by providing a new perspective into how agencies work together.     

CEO股票期权激励与并购决策关系研究——代理成本的中介作用和CEO过度自信的调节作用

运用美国上市银行1998—2014年的数据,将股票期权激励、代理成本、CEO过度自信与并购决策纳入统一的框架进行研究,以代理成本为中介变量,CEO过度自信为调节变量,以检验股票期权激励是否会影响并购决策,以及股票期权激励、代理成本、CEO过度自信与并购决策之间的关系。实证结果表明:CEO股票期权激励能够有效刺激其做出并购决策;代理成本对股票期权激励与并购决策的关系存在部分中介效应;CEO过度自信能显著调节股票期权激励与并购决策的关系;CEO过度自信对于股票期权激励与并购决策的关系的调节作用会通过代理成本起作用。     

A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update

Humanitarian aid agencies usually resort to inventory prepositioning to mitigate the impact of disasters by sending emergency supplies to the affected area as quickly as possible. However, a lack of replenishment opportunity after a disaster can greatly hamper the effectiveness of the relief operation due to uncertainty in demand. In this paper, a prepositioning problem is formulated as a two-period newsvendor model where the response phase is divided into two periods. The model acknowledges the demand to be uncertain even after the disaster and utilises the Bayesian approach to revise the demand of the second period. Based on the revised demand, an order is placed at the beginning of the second period to be replenished instantaneously. A two-stage solution methodology is proposed to find the prepositioning quantity and post-disaster replenishment quantity, which minimise the total expected costs of relief operations. A numerical example is presented to demonstrate the solution methodology, and sensitivity analysis is performed to examine the effect of model parameters. The results highlight the indifferent characteristics shown by the replenishment quantity with the variation in model parameters.     

Pre-positioning of relief items in humanitarian logistics considering lateral transhipment opportunities

The main objective of this study is to investigate the inclusion of lateral transhipment opportunities into the humanitarian relief chain and to examine the effect of different parameters on minimizing the average distance travelled per item while serving the beneficiaries. Direct shipment model (DT), lateral transhipment model (LTSP) and maritime lateral transhipment model (MLTSP) are developed and compared between each other by using a real life earthquake scenario prepared for the city of Istanbul by JICA (Japanese International Cooperation Agency). Developed mathematical models decide on the locations and number of disaster relief facilities, quantity of relief items to hold at those facilities, and quantity of lateral transhipment between the facilities. Vulnerability of the roads and heterogeneous capacitated facilities are also considered. It can be concluded that both LTSP and MLTSP models gave better results than DT model and lateral transhipment option helps beneficiaries to obtain relief items faster and with higher service level.     

HOW DO RATING AGENCIES’ DECISIONS IMPACT STOCK MARKETS? A META‐ANALYSIS

The purpose of this study is to examine how credit rating agencies’ decisions impact the stock market using a systematic and quantitative review of existing empirical studies. Specifically, we employ a meta‐regression analysis (MRA) to investigate the extent and nature of the effect of rating agencies’ decisions on the stock market. We survey 62 studies published between 1978 and 2015. Our first finding is that the cumulative average abnormal returns calculated from this empirical literature are affected by publication bias. After controlling for publication bias, the main findings of our meta‐analysis indicate that negative rating decisions cause statistically significant negative abnormal returns. This evidence suggests an informational effect. Our results also indicate that positive rating decisions do not have a significant effect. Finally, the MRA results reveal the importance of several factors related to primary study design, as well as to the nature of the data.     

Optimization models in emergency logistics: A literature review

Optimization modeling has become a powerful tool to tackle emergency logistics problems since its first adoption in maritime disaster situations in the 1970s. Using techniques of content analysis, this paper reviews optimization models utilized in emergency logistics. Disaster operations can be performed before or after disaster occurrence. Short-notice evacuation, facility location, and stock pre-positioning are drafted as the main pre-disaster operations, while relief distribution and casualty transportation are categorized as post-disaster operations. According to these operations, works in the literature are broken down into three parts: facility location, relief distribution and casualty transportation, and other operations. For the first two parts, the literature is structured and analyzed based on the model types, decisions, objectives, and constraints. Finally, through the content analysis framework, several research gaps are identified and future research directions are proposed.     

供应同一产品的两个销售商的库存决策研究

模型假设两个销售商销售同一产品，因此当一个销售商缺货时，它的客户可能转向另一个销售商购买同样的产品，即他们之间存在替代性。针对两个销售商的这种关系，给出了三种不同的库存决策。并对模型进行了实际算例分析，比较了两个决策者不同合作模式下的订货策略，为决策者制定有效的订货策略提供了依据。     

Do managers make takeover financing decisions that circumvent more effective outside blockholders?

Consistent with agency theory, we find that bidder managers make takeover financing decisions in ways that circumvent more effective monitors. Bidder managers are more likely to use cash rather than stock when targets have aggressive outside blockholders. We also find that the likelihood of a cash offer decreases when aggressive outside bidder block ownership is relatively low. However, the likelihood of a cash offer increases when aggressive outside bidder blockholding is in the intermediate range, a range of ownership where their continued influence over managerial decisions is threatened by a stock offer. Furthermore, we find that bidder management tends to use cash when its outside bidder blockholders are less aggressive. Overall, our findings indicate that managerial decisions on financing takeovers are motivated to prevent aggressive outside blockholders from gaining more control.     

An optimal inventory model where resupply is possible but uncertain

A model is formulated for computing the optimal stock quantity of an item when resupply is possible but uncertain. The distinguishing feature of the model is that the optimal stock quantity calculation takes into account the cost of resupply and the probability of stock arriving by a specified mode of transport in time for issue to customers. The model is then applied to the problem of determining a preferred mode of transport for an assumed set of parameters.     

考虑顾客惰性时的供应链定价与存货决策研究

本文研究了存在顾客惰性时的零售商的最优定价与存货决策问题。假定产品的销售分为正常销售阶段和清仓处理阶段,顾客在确定最优购买时机时会战略性地比较提前购买和延迟购买时获得的期望效用,同时顾客也可能存在延迟购买的消费惰性。利用理性预期均衡分析,分析了存在顾客惰性时零售商的最优定价与存货数量,并且比较了战略顾客行为下和顾客惰性下的零售商的最优定价和存货数量的关系。研究表明,顾客惰性的存在减少了零售商的期望利润,降低了零售商的最优销售价格,同时也降低了零售商的最优存货数量。     

Disaster relief routing: Integrating research and practice

Disaster relief presents many unique logistics challenges, with problems including damaged transportation infrastructure, limited communication, and coordination of multiple agents. Central to disaster relief logistics is the distribution of life-saving commodities to beneficiaries. Operations research models have potential to help relief agencies save lives and money, maintain standards of humanitarianism and fairness and maximize the use of limited resources amid post-disaster chaos. Through interviews with aid organizations, reviews of their publications, and a literature review of operations research models in transportation of relief goods, this paper provides an analysis of the use of such models from the perspective of both practitioners and academics. With the complexity of disaster relief distribution and the relatively small number of journal articles written on it, this is an area with potential for helping relief organizations and for tremendous growth in operations research.     

Evolutionary dynamics of supervision-compliance game on optimal pre-positioning strategies in relief supply chain management

Emergency supply reserves are indispensable material bases in relief supply chain management. However, limited in-kind relief resources stockpiled in government-managed depositories may fail to meet the surging demand following the disaster. This paper develops an optimal pre-positioning strategy for emergency supplies with pre-purchasing contracts between local governments (LGs) and emergency supply manufacturers (ESMs) to properly address demand uncertainty in different disaster scenarios. Physical materials and production capacity are integrated into a holistic and hybrid reserve model to mitigate overstock or stock-out risks. Applying an evolutionary game-theoretic framework, contract enforcement has been extensively analyzed to avoid LGs dereliction of duty and ESMs’ breach of contract. A novel dynamic penalty mechanism is proposed to control the fluctuations in strategy choices and effectively improve ESMs’ compliance without LGs’ excessive inputs on supervision. The numerical simulation results, along with sensitivity analyses on major cost-accounting, demand characteristics, and environmental parameters, show that safety stock is the primary guarantee in most cases, while reactive stock acts as an important supplement for disasters with long-term consequences. The joint reserve policy (except for no action strategy) outperforms the price-only contract on the total reserved quantity of emergency supplies at a lower long-term average cost. The initial state and cost-benefit structures dominate the complex interplay and periodical fluctuations in the supervision-compliance game. The doomed cycle of order, disorder, and reorder in contract performance management can be well managed under the proposed dynamic penalty mechanism, which appears much more efficient and incentive-compatible in promoting both parties to fulfill their obligations.     

The acquisition and utilization of technical information by administrative agencies.

Through a review and integration of the heretofore rather distinct literatures dealing with (1) policy making in administrative agencies, (2) the use of scientific and technical information in public policy, and (3) the utilization of policy research, this paper develops preliminary conceptual frameworks of the variables affecting the acquisition and the utilization of technical information by administrative agencies. Although previous research, based largely upon case studies of a few decisions within a single agency, has resulted in numerous bivariate hypotheses, the number of variables involved and recognized problems of generalizing the results suggest that future research be oriented toward a number of strategies capable of simultaneously examining the effect of numerous variables over large numbers of cases.     

Corporate governance and firm performance relationship: Implications for risk‐adjusted return behavior

We examine the impact of corporate governance on firm performance and stock return behavior using panel data for Indian listed firms for 2006 to 2015. Our results suggest that corporate governance improves firm performance. However, corporate governance information fails to provide excess risk‐adjusted returns to investors, as governance information is well assimilated in prevailing stock prices. In addition to extending the scant literature focused on emerging markets, our findings will prove useful to investors, fund managers, and rating agencies in making investment decisions and regulators in assessing the impact of governance norms.     

Redesign strategies of a comprehensive robust relief network for disaster management

We address the problem of designing as well as redesigning a relief network over multiple periods as a strategic decision which plays a critical role in the post-disaster management. Design of the relief network has a significant impact on the effective performance of disaster response operations. For considering both the uncertainty and dynamism of the decision-making environment, a comprehensive scenario-based robust approach embedded in the rolling horizon framework is proposed. The proposed mixed-integer linear programming model is inspired by a real case study of a disaster management in Iran, which aims to minimize the total cost of network management. Furthermore, restorative strategies are considered to increase the efficiency and robustness of the proposed relief network under disaster. To tackle the proposed optimization model, a heuristic solution algorithm is adopted. The results indicate that the proposed robust relief network provides an affordable access to its demand points in a sustainable manner under disaster. In addition, extensive computational results illustrate the efficiency of the proposed model in dealing with the considered disaster management issues.     

Using announcement options in the bid construction phase for disaster relief procurement

This paper presents an analysis of the bid construction phase of procurement auctions in disaster relief and humanitarian logistics. Substitution and partial fulfillment options are presented in formulations to allow bidders with fewer inventories to offer substitute item types and partial bids in auctions. During the auction announcement phase, a coordinating platform for disaster locations (i.e., auctioneer) allows substitution and partial fulfillment options to the relief suppliers (i.e., bidders) when acceptable. Thus, suppliers with fewer inventories can offer substitute item types and participate in more auctions by partially bidding. A genetic algorithm, a simulated annealing algorithm and an integer program are used for the analysis of the bid construction phase with different announcement options. Heuristic solution techniques and an IP formulation help understand the dynamics of the bid construction problem. It is shown that the addition of substitution and partial fulfillment options is essential to diversify and increase the usable capacity of the supplier base. Additionally, the partial fulfillment option enables better usage of supplier inventories in an environment with scarce supplies.     

Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution

This paper presents a new facility location problem variant with application in disaster relief. The problem is unique in that both verified data and unverified user-generated data are available for consideration during decision making. The problem is motivated by the recent need of integrating unverified social data (e.g., Twitter posts) with data from more traditional sources, such as on-the-ground assessments and aerial flyovers, to make optimal decisions during disaster relief. Integrating social data can enable identifying larger numbers of needs in shorter amounts of time, but because the information is unverified, some of it may be inaccurate. This paper seeks to provide a “proof of concept” illustrating how the unverified social data may be exploited. To do so, a framework for incorporating uncertain user-generated data when locating Points of Distribution (PODs) for disaster relief is presented. Then, three decision strategies that differ in how the uncertain data is considered are defined. Finally, the framework and decision strategies are demonstrated via a small computational study to illustrate the benefits user-generated data may afford across a variety of disaster scenarios.     

Debris removal during disaster response: A case for Turkey

Debris occurs from the ruin and wreckage of structures during a disaster. Proper removal of debris is of great importance because it blocks roads and prohibits emergency aid teams from accessing disaster-affected regions. Poor disaster management, lack of efficiency and delays in debris removal cause disruptions in providing shelter, nutrition, healthcare and communication services to disaster victims, and more importantly, result in loss of lives. Due to the importance of systematic and efficient debris removal from the perspectives of improving disaster victims quality of life and allowing the transportation of emergency relief materials, the focus of this study is on providing emergency relief supplies to disaster-affected regions as soon as possible by unblocking roads through removing the accumulated debris. We develop a mathematical model for the problem that requires long CPU times for large instances. Since it is crucial to act quickly in an emergency case, we also propose a heuristic methodology that solves instances with an average gap of 1% and optimum ratio of 80.83%.     

Sustainable humanitarian supply chain management – exploring new theory

Disaster response operations aim at helping as many victims as possible in the shortest time, with limited consideration of the socio-economic context. During the disaster rehabilitation phase, the perspective needs to broaden and comprehensively take into account the local environment. We propose a framework of sustainable humanitarian supply chain management (SCM) that facilitates such comprehensive performance. We conceptualise the framework by combining literature from the fields of sustainable and humanitarian SCM. We test the framework through an analytic induction process by means of multiple case studies of four relief organisations. Our framework suggests that supply chain design needs to be aligned not only to relief organisations’ enablers, but also to the population's long-term requirements as well as any socio-economic and governmental contingency factors. A good fit between these dimensions leads to sustainable performance. The framework provides an instrument for relief organisations to achieve sustainable performance in the disaster rehabilitation phase.