Return policy: Hassle‐free or your money‐back guarantee?

This article compares the profitability of two pervasively adopted return policies—money‐back guarantee and hassle‐free policies. In our model, a seller sells to consumers with heterogeneous valuations and hassle costs. Products are subject to quality risk, and product misfit can only be observed post‐purchase. While the hassle‐free policy is cost advantageous from the seller's viewpoint, a money‐back guarantee allows the seller to fine‐tune the consumer hassle on returning the product. Thus, when the two return policies lead to the same consumer behaviors, the hassle‐free policy dominates. Conversely, a money‐back guarantee can be more profitable even if on average, high‐valuation consumers experience a lower hassle cost than the low‐valuation ones. The optimal hassle cost can be higher when product quality gets improved; thus, it is not necessarily a perfect proxy or signal of the seller's quality. We further allow the seller to adopt a mixture of these policies, and identify the concrete operating regimes within which these return policies are optimal among more flexible policies. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 403–417, 2014     

Inventory control and replenishment with flexible delivery‐time upgrade

We consider a capacitated inventory model with flexible delivery upgrades, in which the seller allocates its on‐hand inventory to price‐ and delivery‐time‐sensitive customers. The seller has two decisions: inventory commitment and replenishment. The former addresses how the on‐hand inventories are allocated between the two classes of customers within an inventory cycle. The latter addresses how the inventory is replenished between inventory cycles. We develop optimal inventory allocation, upgrade, and replenishment policies and demonstrate that the optimal policy can be characterized by a set of switching curves. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 418–426, 2014     

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     

A branch‐and‐price approach for the stochastic generalized assignment problem

In this article, we address a stochastic generalized assignment machine scheduling problem in which the processing times of jobs are assumed to be random variables. We develop a branch‐and‐price (B&P) approach for solving this problem wherein the pricing problem is separable with respect to each machine, and has the structure of a multidimensional knapsack problem. In addition, we explore two other extensions of this method—one that utilizes a dual‐stabilization technique and another that incorporates an advanced‐start procedure to obtain an initial feasible solution. We compare the performance of these methods with that of the branch‐and‐cut (B&C) method within CPLEX. Our results show that all B&P‐based approaches perform better than the B&C method, with the best performance obtained for the B&P procedure that includes both the extensions aforementioned. We also utilize a Monte Carlo method within the B&P scheme, which affords the use of a small subset of scenarios at a time to estimate the “true” optimal objective function value. Our experimental investigation reveals that this approach readily yields solutions lying within 5% of optimality, while providing more than a 10‐fold savings in CPU times in comparison with the best of the other proposed B&P procedures. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 131–143, 2014     

基于维修器材离散随机需求最佳库存量确定研究

结合装备维修器材保障工作,就维修器材离散随机需求最佳库存量确定进行研究,对其建模进行系统分析,结合修理厂维修器材最佳库存量进行实例计算,以指导维修器材最佳库存量的确定.     

MILITARY EXPENDITURE AND ECONOMIC GROWTH

This paper tests the relationship between military expenditure and economic growth by including the impact of the share of military and civilian components of government expenditure in an economic growth model with endogenous technology. In this framework, we empirically consider the hypothesis of a non‐linear effect of military expenditure on economic growth. Differences between the costs and benefits of the defence sector has traditionally explained the non‐linear relationship suggesting that shocks to insecurity may also be a source of non‐linearity as they determine a re‐allocative effect within government expenditure. While parametric partial correlations are in line with empirical findings, the robustness of estimations is tested by using a non‐parametric approach. The negative relationship between military expenditure and growth in countries with high levels of military burden predicted by theory becomes significant only after including a proxy for re‐allocative effects in the growth equation.     

ON THE USE OF TERROR WEAPONS VERSUS MODERN WEAPON SYSTEMS IN AN ARMS RACE BETWEEN DEVELOPED AND LESS DEVELOPED COUNTRIES

Some of the most active arms races are taking place between developed and less developed countries. The inability of less developed countries to compete financially, as well as technologically, with developed countries may be forcing the former to acquire terror weapons (TWP). The Iran–Iraq war in the 1980s and the events of 9/11 proved that the use of TWP is no longer a mere threat; there are several organizations and countries that will not hesitate to use them. This study develops a model of resource allocation in an arms race between a developed country that is characterized by state‐of‐the‐art technology and high GDP, and a less developed country whose technological capability and GDP are much lower. The model is used to predict the optimal mix of weapons of the two countries that are engaged in the arms race. Applying the model to the arms race between Israel and Syria demonstrates its use.     

PROTECTING CULTURAL MONUMENTS AGAINST TERRORISM

Famous cultural monuments are often regarded as unique icons, making them an attractive target for terrorists. Despite huge military and police outlays, terrorist attacks on important monuments can hardly be avoided. We argue that an effective strategy to discourage terrorist attacks on iconic monuments is for a government to show a firm commitment to swift reconstruction. Using a simple game‐theoretic model, we demonstrate how a credible claim to rebuild any destroyed cultural monument discourages terrorist attacks by altering the terrorists' expectations and by increasing the government's reputation costs if they fail to rebuild.     

Alternative models of Greek defence expenditures

This paper models and estimates Greek defence spending over the 1950–1989 period. It employs the Stone‐Geary welfare function and estimates levels of defence expenditures by the Engle‐Granger two‐step procedure. The Dickey‐Fuller test regression for cointegration is specified in terms of the significance of additional augmentations. The Deaton‐Muellbauer functional form is then employed and an estimating equation for the expenditure share of defence is derived. This specification is compared with the levels equation through a number of non‐nested tests involving model transformation.     

Evaluating the trade‐off between military spending and investment in the United States

Using tests of a single equation model and cointegration techniques, this paper finds no evidence of a long run trade‐off, and some evidence of a short‐run trade‐off, between military spending and investment in post‐World War II United States data. The short‐run trade‐off is confined to the 1949–1971 period, and may be the result of the sharp expansion and contraction of military outlays in connection with the Korean and Vietnam Wars. In addition, cointegration techniques are used to identify a possible long‐run trade‐off between military spending and consumption.