Assessing the value of demand sharing in supply chains

We consider the problem of assessing the value of demand sharing in a multistage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Similar to previous research, we assume each supply chain player constructs its best linear forecast of the leadtime demand and uses it to determine the order quantity via a periodic review myopic order‐up‐to policy. We demonstrate how a typical supply chain player can determine the extent of its available information in the presence of demand sharing by studying the properties of the moving average polynomials of adjacent supply chain players. The retailer's demand is driven by the random shocks appearing in the autoregressive moving average representation for its demand. Under the assumptions we will make in this article, to the retailer, knowing the shock information is equivalent to knowing the demand process (assuming that the model parameters are also known). Thus (in the event of sharing) the retailer's demand sequence and shock sequence would contain the same information to the retailer's supplier. We will show that, once we consider the dynamics of demand propagation further up the chain, it may be that a player's demand and shock sequences will contain different levels of information for an upstream player. Hence, we study how a player can determine its available information under demand sharing, and use this information to forecast leadtime demand. We characterize the value of demand sharing for a typical supply chain player. Furthermore, we show conditions under which (i) it is equivalent to no sharing, (ii) it is equivalent to full information shock sharing, and (iii) it is intermediate in value to the two previously described arrangements. Although it follows from existing literature that demand sharing is equivalent to full information shock sharing between a retailer and supplier, we demonstrate and characterize when this result does not generalize to upstream supply chain players. We then show that demand propagates through a supply chain where any player may share nothing, its demand, or its full information shocks (FIS) with an adjacent upstream player as quasi‐ARMA in—quasi‐ARMA out. We also provide a convenient form for the propagation of demand in a supply chain that will lend itself to future research applications. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 515–531, 2014     

What Happened to Israeli Military Thought?

Abstract

This article addresses the following question: how can one explain the neglect of the intellectual aspects of the profession on the part of the Israel Defense Forces (IDF)? The explanations offered for that neglect are a mixture of cultural and societal factors. The cultural explanation focuses on Israeli strategic culture; the traditional Israeli perception of the combination of rich experience and experience-based intuition as a winning ticket; the tendency to extol improvisation; a cult of material strength; and a strong belief in technology. The social explanation stresses the declining attractiveness of a military career for qualitative young Israelis. The article contends that change can take place only if the IDF undergoes a process of institutional intellectualism – if not willingly then one imposed by the political echelon.     

A mathematical programming approach for improving the robustness of least sum of absolute deviations regression

This paper discusses a novel application of mathematical programming techniques to a regression problem. While least squares regression techniques have been used for a long time, it is known that their robustness properties are not desirable. Specifically, the estimators are known to be too sensitive to data contamination. In this paper we examine regressions based on Least‐sum of Absolute Deviations (LAD) and show that the robustness of the estimator can be improved significantly through a judicious choice of weights. The problem of finding optimum weights is formulated as a nonlinear mixed integer program, which is too difficult to solve exactly in general. We demonstrate that our problem is equivalent to a mathematical program with a single functional constraint resembling the knapsack problem and then solve it for a special case. We then generalize this solution to general regression designs. Furthermore, we provide an efficient algorithm to solve the general nonlinear, mixed integer programming problem when the number of predictors is small. We show the efficacy of the weighted LAD estimator using numerical examples. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

From Blitzkrieg To Attrition: Israel's Attrition Strategy and Staying Power

This article challenges the myth that Israel cannot afford to become involved in a draining war of attrition, arguing instead that Israeli society has repeatedly demonstrated a relatively high staying power. The article opens with a theoretical discussion that focuses on the difference between attrition and blitzkrieg and on the dilemmas Western democracies (WDs) face when coping with attrition. Following sections present Israeli aversion to attrition and the circumstances under which Israel eventually adopted an explicit attrition strategy, and analyse Israeli society's success in demonstrating a high cost tolerance during eight cases of attrition from the 1950s to the present.