On the Efficiency of Cost-based Decision Rules for Capacity Planning
通过仿真实验，探讨在硬约束下使用成本信息进行产能决策的经济损失，并比较瓶颈规划法与产品成本法的效果，发现瓶颈规划法更优且接近最优解。
Recent literature on activity based costing suggests that using costs to make long-run and capacity decisions is economically sound. This conclusion relies on the assumption that capacity resources impose soft constraints (i.e., capacity can be increased in the short-run on an as-needed basis). However, many capacity resources impose hard constraints (i.e., capacity once installed cannot be changed in the short run). In this paper, we explore the economic loss from using information for capacity when capacity constraints are hard. We also examine two other capacity rules that adopt an input resource-based perspective to capacity. Using simulation experiments, we show that the solution from a bottleneck planning approach dominates the product cost based solution and, provides an excellent approximation to the optimal solution to the capacity problem.