A Territorial Conflict: Trade-offs and Strategies

We study a war scenario in which the winner occupies the loser’s territory. Attacking a territory increases the chance of winning, but also causes harm, which in turn decreases the territory’s value (i.e. the reward of winning). This paper highlights the effects of this trade-off on the equilibrium strategies of the warring states in a contest game with endogenous rewards. Providing both static and dynamic models, our analysis captures insights regarding strategic behavior in asymmetric contests with such conflict.     

Asbestos in the collection of the Royal Armouries and the conservation of a First World War German gasmask

In March 2015, in order to comply with Health and Safety Regulations, the Royal Armouries contracted an external company to carry out an asbestos audit. This article looks at what that audit entailed and also how a gasmask suspected of containing asbestos, was made safe in order to conserve and display it.     

基于复杂网络的作战描述模型研究*

针对传统作战模型重点关注兵力的毁伤,不能充分地反映信息时代作战的特点,提出了一个基于复杂网络的作战描述模型,把作战单元抽象成节点,把各单元之间的相互作用抽象成有向边,将战场描述为一个由传感器、决策器、影响器、目标四类节点组成的有向网络图。定义了网络模型的若干特征参数,把作战环看成是反映作战能力的指标,并区别分析了标准作战环和广义作战环,能更好地反映信息时代作战的特点。最后实例研究了传统作战条件下决策器连通程度的变化给作战能力带来的影响。     

装备战损量的兰彻斯特方程预计方法*

针对装备战损量预计这一未来作战装备保障必须解决的核心问题,运用兰彻斯特方程探讨解决途径。从分析影响装备战损的因素出发,综合讨论目前预计装备战损量的方法,提出基于指数多元兰彻斯特方程的装备战损量预计模型和模型中毁伤能力系数的确定方法,得到了装备战损量的兰彻斯特方程预计方法,并举例验证。该方法将经验计算与模拟计算相结合,用较简单的确定性解析方程描述所考虑因素对装备战损量的客观约束关系,较好地满足了未来信息化条件下作战装备战损量预计的需要。     

Measuring Intermediate Outcomes of Liberia’s Disarmament,Demobilization, Rehabilitation and Reintegration Program

This paper re-analyzes data from a survey of ex-combatants in Liberia conducted in, to estimate the effect of Liberia’s Demobilization, Disarmament, Rehabilitation and Reintegration program on participants’ income and employment status. As program completion was not random, these estimates are biased. I use propensity score matching to obtain a more precise estimate. The results indicate a higher employment rate for those who complete the program, although there is consistently no effect on income. These results have implications for both evaluating the outcomes in Liberia and the integrated approach to ex-combatant reintegration that the program embodied.     

微信:网络舆论战的新利器

微信以惊人的速度发展,成为时下最热门的社交信息平台和绝大多数手机用户的一种生活方式。微信是舆论生成和扩散的重要平台,其多元化的信息、多渠道的传播以及创新的特点,为网络舆论战带来了全新的机遇。把握微信的信息传播特点,有效针对特定对象人群,采取积极主动的方式开展网络舆论宣传与自我防御,使微信成为舆论战发展的有力工具,是新时期开展网络舆论战的必然选择。     

The German wars of liberation 1807–1815: The restrained insurgency

In the Age of Napoleon, ‘small wars’ and ‘revolutionary war’ were closely connected. There were, however, different strands of this phenomenon: speaking professionally, conservative officers condemned small wars as an irregular regression to previous less disciplined forms of warfare. The Prussian state continually tried to discipline and regulate spontaneous risings. Yet the irregular character of small wars offered the opportunities for a less complex way of fighting, thus enabling the arming of the ‘people’ to fight. Individual undertakings, such as Ferdinand von Schill's doomed campaign in 1809, were designed to spark off a general popular uprising. But they were cheered by many and supported by few. Meanwhile, Neidhardt von Gneisenau conceived guerrilla-style Landsturm home-defence forces, which were designed for an irregular people's war. These concepts were put into practice in the ‘war of freedom’ – or ‘war of liberation’ – in 1813. Eventually both the mobilisation and the tactics remained regular, however, despite the emphatic appeal to a national ‘people's war’.     

Approximations and empirics for stochastic war equations

The article develops a theorem which shows that the Lanchester linear war equations are not in general equal to the Kolmogorov linear war equations. The latter are time‐consuming to solve, and speed is important when a large number of simulations must be run to examine a large parameter space. Run times are provided, where time is a scarce factor in warfare. Four time efficient approximations are presented in the form of ordinary differential equations for the expected sizes and variances of each group, and the covariance, accounting for reinforcement and withdrawal of forces. The approximations are compared with “exact” Monte Carlo simulations and empirics from the WWII Ardennes campaign. The band spanned out by plus versus minus the incremented standard deviations captures some of the scatter in the empirics, but not all. With stochastically varying combat effectiveness coefficients, a substantial part of the scatter in the empirics is contained. The model is used to forecast possible futures. The implications of increasing the combat effectiveness coefficient governing the size of the Allied force, and injecting reinforcement to the German force during the Campaign, are evaluated, with variance assessments. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

Size Still Matters: Explaining Sri Lanka’s Counterinsurgency Victory over the Tamil Tigers

The military effectiveness literature has largely dismissed the role of material preponderance in favor of strategic interaction theories. The study of counterinsurgency, in which incumbent victory is increasingly rare despite material superiority, has also turned to other strategic dynamics explanations like force employment, leadership, and insurgent/adversary attributes. Challenging these two trends, this paper contends that even in cases of counterinsurgency, material preponderance remains an essential—and at times the most important—factor in explaining battlefield outcomes and effectiveness. To test this, the paper turns to the case of the Sri Lankan state’s fight against the Tamil Tiger insurgency, a conflict which offers rich variation over time across six periods and over 25 years. Drawing on evidence from historical and journalistic accounts, interviews, memoirs, and field research, the paper demonstrates that material preponderance accounts for variation in military effectiveness and campaign outcomes (including military victory in the final campaign) better than strategic explanations. Additionally, a new quantitative data-set assembled on annual loss-exchange ratios demonstrates the superiority of materialist explanations above those of skill, human capital, and regime type.