On the effectiveness of top‐down strategy for forecasting autoregressive demands

We investigate the relative effectiveness of top‐down versus bottom‐up strategies for forecasting the demand of an item that belongs to a product family. The demand for each item in the family is assumed to follow a first‐order univariate autoregressive process. Under the top‐down strategy, the aggregate demand is forecasted by using the historical data of the family demand. The demand forecast for the items is then derived by proportional allocation of the aggregate forecast. Under the bottom‐up strategy, the demand forecast for each item is directly obtained by using the historical demand data of the particular item. In both strategies, the forecasting technique used is exponential smoothing. We analytically evaluate the condition under which one forecasting strategy is preferred over the other when the lag‐1 autocorrelation of the demand time series for all the items is identical. We show that when the lag‐1 autocorrelation is smaller than or equal to 1/3, the maximum difference in the performance of the two forecasting strategies is only 1%. However, if the lag‐1 autocorrelation of the demand for at least one of the items is greater than 1/3, then the bottom‐up strategy consistently outperforms the top‐down strategy, irrespective of the items' proportion in the family and the coefficient of correlation between the item demands. A simulation study reveals that the analytical findings hold even when the lag‐1 autocorrelation of the demand processes is not identical. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007.     

Why they fight? Reconsidering the role of motivation in combat environments

The current combat motivation model based on primary group thesis assumes that the main force behind motivation is peer-bonding or otherwise known as unit cohesion. Cohesion is perceived as an all-encompassing factor that leads to satisfactory (or unsatisfactory in lack thereof) military effectiveness and performance in conflict environments. However, the article identifies three main problems with this perspective: 1. mono-dimensional view of motivation; 2. motivation based on heteronomy, and 3. self-reporting bias. The current model does not consider motivation as a separate entity from cohesion; it does not place motivation as fundamental human value; lastly, it takes motivation as granted by-product of socialization. The article proposes a new combat motivation model based on The Self-Determination Theory. The theory maintains that human motivation requires satisfaction of three psychological needs of competence, relatedness, and autonomy. The degree of satisfaction of those three needs leads to different types of regulated motivations – a continuum from intrinsic to extrinsic – each of which has specifiable consequences for learning, performance, and well-being of an individual.