The value of VMI beyond information sharing in a single supplier multiple retailers supply chain under a non-stationary (Rn,Sn) policy

This study aims to determine the value of vendor-managed inventory (VMI) over independent decision making with information sharing (IS) under non-stationary stochastic demand with service-level constraints. For this purpose, we utilize mixed-integer linear programming formulations to quantify the benefits that can be accrued by a supplier, multiple retailers and the system as a whole by switching from IS to VMI. More specifically, we investigate the incremental value that VMI provides beyond IS in terms of expected cost savings, inventory reductions, and decrease in shipment sizes from the supplier to the retailers by conducting a large number of computational experiments. Results reveal that the decision transfer component of VMI improves these performance measures significantly when the supplier׳s setup cost is low and order issuing efficiency is high. The benefits offered by VMI are negligible under the problem settings where the supplier׳s order issuing efficiency is low and the production setup serves solely a single replenishment under IS.     

Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights

Integrating retail decisions on such aspects as assortment, pricing, and inventory greatly improves profitability. We examine a multi-period selling horizon where a retailer jointly optimizes assortment planning, pricing, and inventory decisions for a product line of substitutable products, in a market with multiple customer segments. Focusing on fast-moving retail products, the problem is modeled as a mixed-integer nonlinear program where demand is driven by exogenous consumer reservation prices and endogenous assortment and pricing decisions. A mixed-integer linear reformulation is developed, which enables an exact solution to large problem instances (with up to a hundred products) in manageable times. Empirical evidence is provided in support of a classical deterministic maximum-surplus consumer choice model. Computational results and managerial insights are discussed. We find that the optimal assortment and pricing decisions do not exhibit a simple, intuitive structure that could be analytically characterized, which reflects the usefulness of optimization approaches to numerically identify attractive trade-offs for the decision-maker. We also observe that suboptimal inventory policies significantly decrease profitability, which highlights the importance of integrated decision-making. Finally, we find that the seasonality of consumer preferences and supply costs present an opportunity for boosting the profit via higher inventory levels and wider assortments.     

利益相关者、企业社会责任与存货管理策略——基于中国上市公司的经验证据

文章基于2005－2013年中国沪深A股上市公司数据,实证检验了企业履行利益相关者责任及社会总体责任时对存货管理策略的影响。结果表明,企业针对关键利益相关者的社会责任行为对企业存货水平存在显著影响,但具体影响方向因利益相关者的不同而存在差异;由于企业社会责任不同维度的利益相关者权力博弈,使得企业社会责任的整体表现与存货水平间呈现显著U型非线性影响关系。研究结论有助于提高企业存货管理效率,同时为各方利益相关者提供决策有用的实践建议。     

A classification approach based on the outranking model for multiple criteria ABC analysis

The multiple criteria ABC analysis is widely used in inventory management, and it can help organizations to assign inventory items into different classes with respect to several evaluation criteria. Many approaches have been proposed in the literature for addressing such a problem. However, most of these approaches are fully compensatory in multiple criteria aggregation. This means that an item scoring badly on one or more key criteria could be placed in good classes because these bad performances could be compensated by other criteria. Thus, it is necessary to consider the non-compensation in the multiple criteria ABC analysis. To the best of our knowledge, the ABC classification problem with non-compensation among criteria has not been studied sufficiently. We thus propose a new classification approach based on the outranking model to cope with such a problem in this paper. However, the relational nature of the outranking model makes the search for the optimal classification solution a complex combinatorial optimization problem. It is very time-consuming to solve such a problem using mathematical programming techniques when the inventory size is large. Therefore, we combine the clustering analysis and the simulated annealing algorithm to search for the optimal classification. The clustering analysis groups similar inventory items together and builds up the hierarchy of clusters of items. The simulated annealing algorithm searches for the optimal classification on different levels of the hierarchy. The proposed approach is illustrated by a practical example from a Chinese manufacturer. Furthermore, we validate the performance of the approach through experimental investigation on a large set of artificially generated data at the end of the paper.     

需求信息滞后下的零售商决策与牛鞭效应分析

牛鞭效应是一种在企业经营中广泛存在的普遍现象,对企业的生产经营产生了极大的负面影响。本文考虑一个供应商和一个零售商组成的简单两级供应链系统。在这个系统中,首先建立在需求信息滞后情况下的零售商库存决策和混合决策(库存决策和定价决策)模型;然后进行决策对牛鞭效应的影响分析。结果显示:在需求信息存在滞后的情况下,零售商最优决策的定价和订货点的期望值是确定的,与需求信息滞后期的长度无关;零售商的库存决策能产生牛鞭效应,且牛鞭效应会随需求滞后期增加而逐渐减少;零售商的混合决策能否产生牛鞭效应,取决于需求自相关系数的变化,而与需求滞后期无关,但随着需求滞后期会改变期变化程度。此外,库存决策还是混合决策,在需求不具有滞后时较具有滞后时牛鞭效应表现得较为为减弱;零售商的混合决策与库存决策相比,只有在需求的自相关系数取较小值时,才表现得更为强烈,否则会减弱。因而对于零售商而言,适当的需求信息滞后以及供应商对零售商的定价柔性能减少牛鞭效应。     

出版企业应收账款与存货管理研究

采用案例研究方法,以凤凰传媒、中南传媒、长江传媒和出版传媒4家A股上市公司为例,分析出版行业的应收账款和存货管理情况,并提炼出相应的经验和启示。分析认为:在财务上,出版企业在做好内部控制与预警机制的同时,还可以尝试金融创新;在渠道上,出版企业应进行资源整合,打通出版环节与发行环节,可以增强应收账款周转率,还可以促进以销定产,从源头上减少存货;在业务上,出版企业要多做好产品,尽力挖掘好产品的延伸价值,推进数字出版、按需印刷,从根本上减轻存货压力。     

VMI供应链下考虑补货策略的的契约设计

结合(r,Q)和(s,S)两种库存补货策略,提出了货权属供应商的VMI供应链的契约设计问题。采用风险分担的思想,给出了两种可行的风险分担的契约形式。在离散需求下,通过参数试验的形式,分别研究了两种契约形式对供应链效率的影响。研究结果表明,两种契约能够使得供应链的效率达到满意,同时对于影响效率的参数有一定的鲁棒性,并且在一定情况下能协调供应链。相比收益分享契约,引入风险分享的契约形式能够使得供应链协作的效率更高。研究结论对VMI契约设计有参考意义。     

Inventory Systems with Unreliable Suppliers

The aim of this article is to establish the optimal control of a periodic-review inventory system with two suppliers. One of them delivers orders immediately, the other one is unreliable delivering the orders immediately only with probability p ∈ (0, 1). Two cases are considered. In the first case, it is possible to order any inventory amount from each of suppliers. In the second case, the system budget is restricted.     

Pool‐Point Distribution of Zero‐Inventory Products

We study zero‐inventory production‐distribution systems under pool‐point delivery. The zero‐inventory production and distribution paradigm is supported in a variety of industries in which a product cannot be inventoried because of its short shelf life. The advantages of pool‐point (or hub‐and‐spoke) distribution, explored extensively in the literature, include the efficient use of transportation resources and effective day‐to‐day management of operations. The setting of our analysis is as follows: A production facility (plant) with a finite production rate distributes its single product, which cannot be inventoried, to several pool points. Each pool point may require multiple truckloads to satisfy its customers' demand. A third‐party logistics provider then transports the product to individual customers surrounding each pool point. The production rate can be increased up to a certain limit by incurring additional cost. The delivery of the product is done by identical trucks, each having limited capacity and non‐negligible traveling time between the plant and the pool points. Our objective is to coordinate the production and transportation operations so that the total cost of production and distribution is minimized, while respecting the product lifetime and the delivery capacity constraints. This study attempts to develop intuition into zero‐inventory production‐distribution systems under pool‐point delivery by considering several variants of the above setting. These include multiple trucks, a modifiable production rate, and alternative objectives. Using a combination of theoretical analysis and computational experiments, we gain insights into optimizing the total cost of a production‐delivery plan by understanding the trade‐off between production and transportation.     

委托代理理论下应急物资库存成本控制

运用委托代理理论方法研究了政府委托应急物资生产企业管理应急物资库存后,存在道德风险时,政府如何激励企业努力降低应急物资库存成本的问题。首先分析不同情形下政府与企业的库存成本构成,继而假设政府利用招标机制将应急物资的采购和库存管理一体化操作,建立满足企业参与约束及激励相容约束条件的政府期望效用最大化模型。最后用遗传算法进行仿真计算,结合算例分析政府和企业在不同情形下的收益与成本,结果表明实施激励可明显增加政府的期望效用。