Corporate performance and military production in South Africa

With the end of the Cold War and apartheid, a process of demilitarisation and dramatic cuts in military spending has marked the transition to democracy in South Africa. Between 1989 and 1997 the South African defence budget was cut by more than 50% in real terms, with most of the cuts coming from the procurement budget, which was cut by nearly 70% in real terms during the same period. These cuts have had a significant impact on the country's defence industrial base. However, there has been surprisingly little research on the changes to defence companies that have taken place since the late 1980s. This paper makes a start at rectifying that deficiency by providing an analysis of the restructuring of the major defence‐dependent companies over the period 1988–97. It uses a number of financial ratios and other measures of corporate performance to compare their experience with non‐defence companies in the rest of the South African economy during the same period.     

Defence research and development: Encouraging private venture R&D with ‘option’ strategies*

Central to the changes in UK Ministry of Defence procurement policies over recent years has been the attempt to shift risk out of the public sector. In the context of research and development this has taken the form of encouraging private venture investment, so‐called PVR&D. Recognising that the scope for PVR&D is necessarily constrained by excessive risk and imperfect information, this paper explores the possible use of Option contracts as a means of expanding the opportunities for private venture funding.     

Military Expenditure,Endogeneity and Economic Growth

Abstract

While not always a concern for the general economic growth literature, the debate over the effects of military spending on growth continues to develop, with no consensus, but a deepening understanding of the limitations of previous work. One important issue that has not been adequately dealt with is the endogeneity of military spending in the growth equation, mainly because of the difficulty of finding any variables that would make adequate instruments. This paper considers this issue, using an endogenous growth model estimated on a large sample of 109 non-high-income countries for the period 1998–2012. The empirical analysis is framed within an instrumental variable setting that exploits the increase in military spending that occurs when unrest in a country escalates to turmoil. The estimation results show that endogeneity arising from reverse causality is a crucial issue, with the instrumental variable estimates providing a larger significant negative effect of military spending on growth than OLS would. This result is found to be robust to different sources of heterogeneity and different time periods.     

Portfolio analysis for defense: taking account of networking

To manage their assets at an enterprise level, defense organizations have turned to portfolio theory for the planning, analysis and management of their military forces and materiel. Despite being well established in the commercial sector, the application of portfolio approaches in defense is problematic. The vexatious question for defense of how to define and measure benefits arising is complicated by the increased utility and effectiveness achieved through networking of military forces and the equipment they use. The authors discuss the challenges for defense in using a portfolio approach and propose a conceptual model for dealing with the effects arising from networking with information and communications technologies.     

Outbound supply chain network design with mode selection and lead time considerations

We present a large‐scale network design model for the outbound supply chain of an automotive company that considers transportation mode selection (road vs. rail) and explicitly models the relationship between lead times and the volume of flow through the nodes of the network. We formulate the problem as a nonlinear zero‐one integer program, reformulate it to obtain a linear integer model, and develop a Lagrangian heuristic for its solution that gives near‐optimal results in reasonable time. We also present scenario analyses that examine the behavior of the supply chain under different parameter settings and the performance of the solution procedures under different experimental conditions. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Response surface analysis of two‐stage stochastic linear programming with recourse

We apply the techniques of response surface methodology (RSM) to approximate the objective function of a two‐stage stochastic linear program with recourse. In particular, the objective function is estimated, in the region of optimality, by a quadratic function of the first‐stage decision variables. The resulting response surface can provide valuable modeling insight, such as directions of minimum and maximum sensitivity to changes in the first‐stage variables. Latin hypercube (LH) sampling is applied to reduce the variance of the recourse function point estimates that are used to construct the response surface. Empirical results show the value of the LH method by comparing it with strategies based on independent random numbers, common random numbers, and the Schruben‐Margolin assignment rule. In addition, variance reduction with LH sampling can be guaranteed for an important class of two‐stage problems which includes the classical capacity expansion model. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 753–776, 1999     

Use of a classifier in a knowledge-based simulation optimization system

This article defines and develops a simulation optimization system based upon response surface classification and the integration of multiple search strategies. Response surfaces are classified according to characteristics that indicate which search technique will be most successful. Typical surface characteristics include statistical measures and topological features, while search techniques encompass response surface methodology, simulated annealing, random search, etc. The classify-then-search process flow and a knowledge-based architecture are developed and then demonstrated with a detailed computer example. The system is useful not only as an approach to optimizing simulations, but also as a means for integrating search techniques and thereby providing the user with the most promising path toward an optimal solution. © 1995 John Wiley & Sons, Inc.     

Inventory rotation policies for slow moving items

In this article we present a stochastic model for determining inventory rotation policies for a retail firm which must stock many hundreds of distinctive items having uncertain heterogeneous sales patterns. The model develops explicit decision rules for determining (1) the length of time that an item should remain in inventory before the decision is made on whether or not to rotate the item out of inventory and (2) the minimum sales level necessary for retaining the item in inventory. Two inventory rotation policies are developed, the first of which maximizes cumulative expected sales over a finite planning horizon and the second of which maximizes cumulative expected profit. We also consider the statistical behavior of items having uncertain, discrete, and heterogeneous sales patterns using a two-period prediction methodology where period 1 is used to accumulate information on individual sales rates and this knowledge is then used, in a Bayesian context, to make sales predictions for period 2. This methodology assumes that over an arbitrary time interval sales for each item are Poisson with unknown but stationary mean sales rates and the mean sales rates are distributed gamma across all items. We also report the application of the model to a retail firm which stocks many hundreds of distinctive unframed poster art titles. The application provides some useful insights into the behavior of the model as well as some interesting aspects pertaining to the implementation of the results in a “real-world” situation.