Ordering and controlling the dimensions of strategy

Colin Gray’s dimensions of strategy, built upon the earlier work of Clausewitz and Howard, has theoretical, practical, and pedagogic value for the Strategic Studies community. This paper further develops the theory, arguing that the dimensions can be controlled or managed to improve strategic performance. The dimensions are divided into two categories: “internal” and “external” to the process of strategy. The paper describes the dynamic process by which the internal dimensions, which can be controlled, are used to exert influence over the external dimensions that are beyond the control of the strategist. It is argued that six dimensions hold the key to strategic success: politics and the five dimensions concerned with warfighting. This conclusion validates the Clausewitzian paradigm with its emphasis on policy and battle.     

THE NUCLEAR WEAPON STATES

The nuclear weapon states (NWS) have different perspectives on the desirability and feasibility of a world without nuclear weapons. A review of each of the current nuclear doctrines, postures, and disarmament policies of the five NWS shows that there is a clear divide between them, with some showing relatively determined leadership (the United States and the United Kingdom) and others expressing skepticism, if not complete disinterest (France, Russia, and China). Nevertheless, the prospects for progress on disarmament by the NWS at the 2010 Review Conference of the Treaty on the Non-Proliferation of Nuclear Weapons remain reasonably good. Yet complete success will require much time as well as sustained and applied efforts from the NWS, first and foremost to improve their performance as international security guarantors.     

Finite Markov chain models skip-free in one direction

Finite Markov processes are considered, with bidimensional state space, such that transitions from state (n, i) to state (m, j) are possible only if m ≤ n + 1. The analysis leads to efficient computational algorithms, to determine the stationary probability distribution, and moments of first passage times.     

The value of information sharing in a two‐stage supply chain with production capacity constraints

We consider a simple two‐stage supply chain with a single retailer facing i.i.d. demand and a single manufacturer with finite production capacity. We analyze the value of information sharing between the retailer and the manufacturer over a finite time horizon. In our model, the manufacturer receives demand information from the retailer even during time periods in which the retailer does not order. To analyze the impact of information sharing, we consider the following three strategies: (1) the retailer does not share demand information with the manufacturer; (2) the retailer does share demand information with the manufacturer and the manufacturer uses the optimal policy to schedule production; (3) the retailer shares demand information with the manufacturer and the manufacturer uses a greedy policy to schedule production. These strategies allow us to study the impact of information sharing on the manufacturer as a function of the production capacity, and the frequency and timing in which demand information is shared. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

A fluid queueing model for link travel time moments

We analyze the moments of the random time required for a vehicle to traverse a transportation network link of arbitrary length when its speed is governed by a random environment. The problem is motivated by stochastic transportation network applications in which the estimation of travel time moments is of great importance. We analyze this random time in a transient and asymptotic sense by employing results from the field of fluid queues. The results are demonstrated on two example problems. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

The impact of exponential smoothing forecasts on the bullwhip effect

An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000     

India and Israel: emerging partnership

The absence of formal diplomatic relations between India and Israel from India's hesitant recognition of Israel in 1950 and the establishment of full relations in January 1992, was the result of a complex interplay between two sets of tensions. The first involved the Arab–Israeli dispute, and India's sympathies with a post-colonial Arab world and with the Non-Aligned Movement; the second involved accommodating Muslim opinion within India. Normalization has proceeded more strongly as the growth of Hindu nationalism has weakened Muslim leverage on Indian foreign policy.     

Vehicle fleet refueling strategies to maximize operational range

The focus of this research is on self-contained missions requiring round-trip vehicle travel from a common origin. For a single vehicle the maximal distance that can be reached without refueling is defined as its operational range. Operational range is a function of a vehicle's fuel capacity and fuel consumption characteristics. In order to increase a vehicle's range beyond its operational range replenishment from a secondary fuel source is necessary. In this article, the problem of maximizing the range of any single vehicle from a fleet of n vehicles is investigated. This is done for four types of fleet configurations: (1) identical vehicles, (2) vehicles with identical fuel consumption rates but different fuel capacities, (3) vehicles which have the same fuel capacity but different fuel consumption rates, and (4) vehicles with both different fuel capacities and different consumption rates. For each of the first three configurations the optimal refueling policy that provides the maximal range is determined for a sequential refueling chain strategy. In such a strategy the last vehicle to be refueled is the next vehicle to transfer its fuel. Several mathematical programming formulations are given and their solutions determined in closed form. One of the major conclusions is that for an identical fleet the range of the farthest vehicle can be increased by at most 50% more than the operational range of a single vehicle. Moreover, this limit is reached very quickly with small values of n. The performance of the identical fleet configuration is further investigated for a refueling strategy involving a multiple-transfer refueling chain, stochastic vehicle failures, finite refueling times, and prepositioned fleets. No simple refueling ordering rules were found for the most general case (configuration 4). In addition, the case of vehicles with different fuel capacities is investigated under a budget constraint. The analysis provides several benchmarks or bounds for which more realistic structures may be compared. Some of the more complex structures left for future study are described.