Keeping an eye on South Asian skies: America’s pivotal deterrence in nuclearized India–Pakistan crises

Since declaring their nuclear weapons capabilities in 1998, India and Pakistan have engaged in three major crises that each threatened to escalate into war. In each crisis, the USA engaged in active diplomacy to dissuade the South Asian rivals from taking escalatory actions. Previous literature on the crises has described the American role, but has not theorized third-party involvement in a nuclearized regional rivalry. We apply Timothy Crawford’s pivotal deterrence theory to the nuclearized India–Pakistan conflict, and extend the original theory to cover the novel condition of a non-superpower nuclear dyad, in the context of a single-superpower international system. We find that America’s pivotal deterrence generally enhanced stability in the India–Pakistan crises, and unlike in pre-nuclear South Asia, other great powers supported American diplomacy. However, we suggest that future regional crises between nuclear rivals, in South Asia or elsewhere, may present greater challenges for pivotal deterrence.     

The ambivalent coalition: doing the least one can do against the Islamic state

The effort to degrade and defeat the Islamic State is like many other multilateral military efforts – characterized by widely varying contributions to the effort. This article seeks to understand the patterns of contributions. Three sets of explanations are applied: the lessons of Afghanistan and Libya, variations in how potential contributors feel the threat posed by the Islamic State, and domestic political dynamics. While there may be some political processes that overlap with the big lessons and with the threat of the Islamic State, the patterns of contributions thus far suggest that the key drivers of reactions to the Islamic State are the desire not to repeat Afghanistan combined with some impetus provided by Islamic State attacks in the various homelands. The conclusion suggests some policy implications as well as some ideas for future research.     

Growth recovery after civil conflict: a fractional integration approach

Using recent econometric techniques based on fractional integration, we find that developing countries recover their economic growth faster than developed countries in response to a shock. Following this methodology, we find that longer civil conflicts are associated with a faster recovery process. We further investigate this issue by exploring correlations with components of GDP, military spending, institutions and aid and find heterogeneous effects of these channels by duration of conflict. Higher government spending is correlated with faster recoveries post longer conflicts, and higher consumption spending is linked to faster recoveries following shorter conflicts. Military spending appears to be driving the government expenditure that makes countries recover from longer conflicts. More democratic institutions are associated with faster recoveries post short wars but slower recoveries following long wars.     

The lobbies’ network at the EU policy level: the case of security and defense

Lobbyists may not share the same interests, but they usually agree to form a link in a network which could eventually be used to spread information, to search for potential partners, to speak with one voice to decision makers. In other words, social links represent value for lobbyists because they may ultimately facilitate access. In this article, we explore the network of the Security and Defense lobbies in the EU and we describe its structure.     

Properties of a mean residual life function arising from renewal theory

The present article discusses the properties of the mean residual life function in a renewal process. We examine the relationship this function has with the failure rate function and the conventional mean, variance and coefficient of variation of residual life. We also discuss some monotonicity properties of the mean residual life function. A partial order based on the renewal mean residual function is introduced along with its interrelationship with some existing stochastic orders. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

The effects of model parameter deviations on the variance of a linearly filtered time series

We consider a general linear filtering operation on an autoregressive moving average (ARMA) time series. The variance of the filter output, which is an important quantity in many applications, is not known with certainty because it depends on the true ARMA parameters. We derive an expression for the sensitivity (i.e., the partial derivative) of the output variance with respect to deviations in the model parameters. The results provide insight into the robustness of many common statistical methods that are based on linear filtering and also yield approximate confidence intervals for the output variance. We discuss applications to time series forecasting, statistical process control, and automatic feedback control of industrial processes. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Threshold incentives over multiple periods and the sales hockey stick phenomenon

In this article, we study threshold‐based sales‐force incentives and their impact on a dealer's optimal effort. A phenomenon, observed in practice, is that the dealer exerts a large effort toward the end of the incentive period to boost sales and reach the threshold to make additional profits. In the literature, the resulting last‐period sales spike is sometimes called the hockey stick phenomenon (HSP). In this article, we show that the manufacturer's choice of the incentive parameters and the underlying demand uncertainty affect the dealer's optimal effort choice. This results in the sales HSP over multiple time periods even when there is a cost associated with waiting. We then show that, by linking the threshold to a correlated market signal, the HSP can be regulated. We also characterize the variance of the total sales across all the periods and demonstrate conditions under the sales variance can be reduced. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

An integer decomposition algorithm for solving a two‐stage facility location problem with second‐stage activation costs

We study a stochastic scenario‐based facility location problem arising in situations when facilities must first be located, then activated in a particular scenario before they can be used to satisfy scenario demands. Unlike typical facility location problems, fixed charges arise in the initial location of the facilities, and then in the activation of located facilities. The first‐stage variables in our problem are the traditional binary facility‐location variables, whereas the second‐stage variables involve a mix of binary facility‐activation variables and continuous flow variables. Benders decomposition is not applicable for these problems due to the presence of the second‐stage integer activation variables. Instead, we derive cutting planes tailored to the problem under investigation from recourse solution data. These cutting planes are derived by solving a series of specialized shortest path problems based on a modified residual graph from the recourse solution, and are tighter than the general cuts established by Laporte and Louveaux for two‐stage binary programming problems. We demonstrate the computational efficacy of our approach on a variety of randomly generated test problems. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Neighborhood search heuristics for selecting hierarchically well‐formulated subsets in polynomial regression

The importance of subset selection in multiple regression has been recognized for more than 40 years and, not surprisingly, a variety of exact and heuristic procedures have been proposed for choosing subsets of variables. In the case of polynomial regression, the subset selection problem is complicated by two issues: (1) the substantial growth in the number of candidate predictors, and (2) the desire to obtain hierarchically well‐formulated subsets that facilitate proper interpretation of the regression parameter estimates. The first of these issues creates the need for heuristic methods that can provide solutions in reasonable computation time; whereas the second requires innovative neighborhood search approaches that accommodate the hierarchical constraints. We developed tabu search and variable neighborhood search heuristics for subset selection in polynomial regression. These heuristics are applied to a classic data set from the literature and, subsequently, evaluated in a simulation study using synthetic data sets. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

A facility reliability problem: Formulation,properties, and algorithm

Having a robustly designed supply chain network is one of the most effective ways to hedge against network disruptions because contingency plans in the event of a disruption are often significantly limited. In this article, we study the facility reliability problem: how to design a reliable supply chain network in the presence of random facility disruptions with the option of hardening selected facilities. We consider a facility location problem incorporating two types of facilities, one that is unreliable and another that is reliable (which is not subject to disruption, but is more expensive). We formulate this as a mixed integer programming model and develop a Lagrangian Relaxation‐based solution algorithm. We derive structural properties of the problem and show that for some values of the disruption probability, the problem reduces to the classical uncapacitated fixed charge location problem. In addition, we show that the proposed solution algorithm is not only capable of solving large‐scale problems, but is also computationally effective. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010