SYMBIOTIC SPIES

Spying on the Nuclear Bear: Anglo-American Intelligence and the Soviet Bomb, by Michael S. Goodman. Stanford University Press, 2007. 295 pages, $50.     

WARFARE IN A NEW DOMAIN: THE ETHICS OF MILITARY CYBER-OPERATIONS

While most normative evaluations of military cyber-operations have emerged from the legal community, this article assesses the legitimacy of such operations from a philosophical-ethical perspective. After reviewing the relationship between rights forfeiture and the jus ad bellum and jus in bello criteria of the just war tradition, it applies these criteria to several aspects of cyber-operations, including responses to cyber-activities, the use of cyber-capabilities affecting combatants and civilians, and the use of these capabilities by contractors. Finally, it briefly addresses the legitimacy of limiting rights to privacy and anonymity in service of preventing cyber-harm.     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.     

Military Expenditures,Income Inequality,Welfare and Political Regimes: A Dynamic Panel Data Analysis

The goal of this paper is to investigate the relationship between type of welfare regimes and military expenditures. There is a sizeable empirical literature on the development of the welfare state and on the typology of the welfare regimes. There appear to be, however, no empirical studies that examine welfare regimes with special attention to military spending. This study aims at providing a comprehensive analysis on the topic by considering several different welfare regime typologies. To do so, we use dynamic panel data analysis for 37 countries for the period of 1988–2003 by considering a wide range of control variables such as inequality measures, number of terrorist events, and size of the armed forces. We also replicate the same analyses for the political regimes. Our findings, in line with the literature, show that there is a positive relationship between income inequality and share of military expenditures in the central government budget, and that the number of terrorist events is a significant factor that affects both the level of military expenditure and inequality. Also, the paper reveals a significant negative relationship between social democratic welfare regimes and military expenditures.     

Bioprotection of facilities

The anthrax attacks of 2001 energized research directed toward reducing health consequences from airborne contaminants by augmenting current heating ventilation and air-conditioning (HVAC) systems. Even during peacetime, interest will continue in improving HVAC components to reduce biocontaminants associated with sick building syndrome. Current HVAC design uses numerical simulation methods of ordinary differential equations to predict approximate performance. The authors show that state-space Laplace Transform calculations actually solve the underlying differential equations and yield algebraic expressions that provide new insight. To sharpen the arguments in favor of this methodology, attention is restricted to improving existing HVAC systems to increase protection from an external release of hazardous particulates. By nearly eliminating the need for dynamical simulation, the resulting methods can be applied to far more complex HVAC designs with little additional computational effort. The new methods reduce the time required for computation by three orders of magnitude. These algebraic methods also can be extended to disparate technical problems including internal particulate release, gas masks, and designing new protective buildings.     

Optimal replacement of continuously degrading systems in partially observed environments

Motivated by wind energy applications, we consider the problem of optimally replacing a stochastically degrading component that resides and operates in a partially observable environment. The component's rate of degradation is modulated by the stochastic environment process, and the component fails when it is accumulated degradation first reaches a fixed threshold. Assuming periodic inspection of the component, the objective is to minimize the long‐run average cost per unit time of performing preventive and reactive replacements for two distinct cases. The first case examines instantaneous replacements and fixed costs, while the second considers time‐consuming replacements and revenue losses accrued during periods of unavailability. Formulated and solved are mixed state space, partially observable Markov decision process models, both of which reveal the optimality of environment‐dependent threshold policies with respect to the component's cumulative degradation level. Additionally, it is shown that for each degradation value, a threshold policy with respect to the environment belief state is optimal if the environment alternates between two states. The threshold policies are illustrated by way of numerical examples using both synthetic and real wind turbine data. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 395–415, 2015     

Selling to strategic and loss‐averse consumers: Stocking,procurement, and product design policies

Motivated by the presence of loss‐averse decision making behavior in practice, this article considers a supply chain consisting of a firm and strategic consumers who possess an S‐shaped loss‐averse utility function. In the model, consumers decide the purchase timing and the firm chooses the inventory level. We find that the loss‐averse consumers' strategic purchasing behavior is determined by their perceived gain and loss from strategic purchase delay, and the given rationing risk. Thus, the firm that is cognizant of this property tailors its inventory stocking policy based on the consumers' loss‐averse behavior such as their perceived values of gain and loss, and their sensitivity to them. We also demonstrate that the firm's equilibrium inventory stocking policy reflects both the economic logic of the traditional newsvendor inventory model, and the loss‐averse behavior of consumers. The equilibrium order quantity is significantly different from those derived from models that assume that the consumers are risk neutral and homogeneous in their valuations. We show that the firm that ignores strategic consumer's loss‐aversion behavior tends to keep an unnecessarily high inventory level that leads to excessive leftovers. Our numerical experiments further reveal that in some extreme cases the firm that ignores strategic consumer's loss‐aversion behavior generates almost 92% more leftovers than the firm that possesses consumers’ loss‐aversion information and takes it into account when making managerial decisions. To mitigate the consumer's forward‐looking behavior, we propose the adoption of the practice of agile supply chain management, which possesses the following attributes: (i) procuring inventory after observing real‐time demand information, (ii) enhanced design (which maintains the current production mix but improves the product performance to a higher level), and (iii) customized design (which maintains the current performance level but increases the variety of the current production line to meet consumers’ specific demands). We show that such a practice can induce the consumer to make early purchases by increasing their rationing risk, increasing the product value, or diversifying the product line. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 435–453, 2015     

Revenue management: A real options approach

Revenue management is the process of actively managing inventory or capacity to maximize revenues. The active management typically occurs through managerial levers such as price, promotion, or availability. We present a novel real options approach to revenue management that is specifically suited to the car rental business. We illustrate the concept with actual car rental data. The model produces minimally acceptable prices and inventory release quantities (number of cars available for rent at a given price) as a function of remaining time and available inventory. The pricing and inventory release recommendations of the developed model confirm earlier empirical analysis that suggested current practises discount too deeply early in the booking cycle. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004