State‐Dependent Forward Guidance and the Problem of Inconsistent Announcements

Forward guidance can be provided as an unconditional promise, i.e. commitment to a specific low policy rate. Alternatively, the promise may include an escape clause, i.e. a condition defining the state of the economy under which the central bank would not keep such a low rate and, instead, it would revert to setting policy under discretion. The escape clause can be expressed as a threshold in terms of a specific variable. The present paper shows that, when such a threshold is expressed in terms of an endogenous variable (e.g. output, inflation), there are cases where it becomes impossible for the central bank to act in a way that is consistent with its promise. Consistency imposes limits on the policy rate that can be set since reverting immediately to the optimal discretionary rate can be incompatible with exceeding the threshold.     

Using the Pack‐and‐a‐Half Rule to Eliminate Backroom Inventories in Retail Operations

In the retail industry, backroom inventories are typically associated with higher labor costs and greater operational complexity. Thus, retailers look for ways to eliminate backroom inventories. A heuristic used for this purpose is the pack‐and‐a‐half rule which suggests that the shelf space allocated for a product should be at least 50% larger than the case pack quantity in which the product is delivered. Despite its popularity among retailers, the pack‐and‐a‐half rule has been ignored in the academic literature. We introduce the pack‐and‐a‐half rule, assess its impact on a retailer's profits, identify cost, demand, and product characteristics driving this impact, and propose a modification. Based on an analysis of data obtained from a retailer on 1,986 SKUs in 20 categories, we find that the pack‐and‐a‐half rule decreases a retailer's profits, on average, by 10% when applied uniformly across all SKUs. Further, this decrease is significantly affected by product depth, product width, demand elasticity, case pack quantity, and inventory carrying cost. Finally, we develop a set of modifications based on these variables where the pack‐and‐a‐half rule is applied selectively and in a stepwise fashion. These modifications limit the decrease in a retailer's profits to a range between 6% and 7%.     

Testing Rival Theories of Budgetary Decision–making in the US States

This article tests three common budgetary decision–making theories in the US states. Pooled time series cross–section analysis is used from 1960 to 1996 to test the garbage can theory and incrementalism, and from 1989 to 1996 to test various theories of rational budgeting. The results demonstrate that there was some support for all three theories in terms of their impact on reducing state budget outputs. Rational budgeting reduces expenditures in aggregate, incrementalism has relatively low explanatory power below the aggregates, and garbage can budgeting is more prevalent in functional areas than for government as a whole. These findings imply that the future research agenda on budgetary decision–making theories should focus more on a system–wide approach, which takes into account many of the characteristics of all three rival models of decision–making, rather than exclusively focusing on each one singly.     

浅析我国服务业的库存问题及应对策略

服务业在整个经济中的地位是衡量一国经济结构合理程度、国际竞争力强弱、经济社会发展协调水平等的重要评判指标之一。与中国经济快速持续发展相比,服务业发展落后的短腿现象却日益突出,而服务业的库存管理问题更是落后。     

供应链管理模式下零库存理论及其在企业中的应用

主要分析了影响企业库存管理的因素，介绍了实现企业零库存的主要方法，针对目前国内企业的库存现状，提出了实现零库存的库存控制理论、实施方法和途径及在实现过程中应注意的问题。     

军队物资库存的一个最优控制问题

讨论了非均衡军队物资库存问题，以最优控制理论为工具，得出了消耗量与库存量之间的变量关系，从而达到在保障供应的前提下，提高军事经济效益的目的     

机动平台识别器方位零值的几种标校方法

方位零值标校是识别器设邸统标校的一项重要内容。针对机动平台识别器设备进场安装，提出了几种标校方法，旨在解决机动平台识别器的方位零值标校问题。     

基于六西格玛流程改进的库存管理优化

库存管理是企业用来控制实际库存问题的方法，主要帮助企业经营者确定何时补充订货、补充订货多少以及安全库存等问题。现有的库存控制研究往往只关注数学建模阶段的精确性，而对库存波动根源认识不足，导致数学模型越来越复杂、完善，但库存仍然居高不下、难以控制。本文针对该问题，提出了在库存管理中糅合六西格玛管理理念的思想，通过六西格玛方法揭示库存积压的根源，从源头着手，进行流程改进，从而达到库存优化、提高客户满意度的目的。文章通过实际案例证实了基于六西格玛理念的库存优化管理的有效性。     

三层次供应链中最优库存决策

本文研究由多供应商、多制造商和多零售商构成的三层次供应链最优库存模型,在供应链中引入协调机制使整个供应链库存总费用最小.