RFID‐Enabled Visibility and Retail Inventory Record Inaccuracy: Experiments in the Field

Accurate inventory records are key to effective store execution, affecting forecasting, ordering, and replenishment. Prior empirical research, however, shows that retailer inventory records are inherently inaccurate. Radio Frequency Identification (RFID) enables visibility into the movement of inventories in the supply chain. Using two different field experiments, the current research investigates the effectiveness of this visibility in reducing retail store inventory record inaccuracy (IRI). Study 1 used an interrupted time‐series design and involved daily physical counts of all products in one category in 13 stores (8 treatments and 5 controls) of a major global retailer over 23 weeks. Results indicate a significant decrease in IRI of approximately 26% due to RFID‐enabled visibility. Using an untreated control group design with pre‐test and post‐test, Study 2 expands the number of categories to five and the number of stores to 62 (31 treatment and 31 control stores). Results show that the effectiveness of RFID in reducing IRI varies by category (ranging from no statistically significant improvement to 81%). Results also suggest that RFID ameliorates the effects of known determinants of IRI and provide the key insight that the technology is most effective for product categories characterized by these determinants.     

Optimal Planning Quantities for Product Transition

The replacement of an existing product with a new one presents many challenges. In particular, uncertainties in a new product introduction often lead to extreme cases of demand and supply mismatches. This paper addresses inventory planning decisions for product upgrades when there is no replenishment opportunity during the transition period. We allow product substitution: when a company runs out of the old product, a customer may be offered the new product as a substitute. We show that the optimal substitution decision is a time‐varying threshold policy and establish the optimal planning policy. Further, we determine the optimal delay in a new product introduction, given the initial inventory of the old product.     

ABC Classification: Service Levels and Inventory Costs

ABC inventory classifications are widely used in practice, with demand value and demand volume as the most common ranking criteria. The standard approach in ABC applications is to set the same service level for all stock keeping units (SKUs) in a class. In this paper, we show (for three large real life datasets) that the application of both demand value and demand volume as ABC ranking criteria, with fixed service levels per class, leads to solutions that are far from cost optimal. An alternative criterion proposed by Zhang et al. performs much better, but is still considerably outperformed by a new criterion proposed in this paper. The new criterion is also more general in that it can take criticality of SKUs into account. Managerial insights are obtained into what class should have the highest/lowest service level, a topic that has been disputed in the literature.     

An Advanced Heuristic for Multiple‐Option Spare Parts Procurement after End‐of‐Production

After‐sales service is a major source of profit for many original equipment manufacturers in industries with durable products. Successful engagement in after‐sales service improves customer loyalty and allows for competitive differentiation through superior service like an extended service period during which customers are guaranteed to be provided with service parts. Inventory management during this period is challenging due to the substantial uncertainty concerning demand over a long time horizon. The traditional mechanism of spare parts acquisition is to place a large final order at the end of regular production of the parent product, causing major holding costs and a high level of obsolescence risk. With an increasing length of the service period, more flexibility is needed and can be provided by adding options like extra production and remanufacturing. However, coordinating all three options yields a complicated stochastic dynamic decision problem. For that problem type, we show that a quite simple decision rule with order‐up‐to levels for extra production and remanufacturing is very effective. We propose a heuristic procedure for parameter determination which accounts for the main stochastic and dynamic interactions in decision making, but still consists of relatively simple calculations that can be applied to practical problem sizes. A numerical study reveals that the heuristic performs extremely well under a wide range of conditions, and therefore can be strongly recommended as a decision support tool for the multi‐option spare parts procurement problem. A comparison with decision rules adapted from practice demonstrates that our approach offers an opportunity for major cost reductions.     

Design of Stockless Production Systems

In make‐to‐stock production systems finished goods are produced in anticipation of demand. By contrast, in stockless production systems finished goods are not produced until demand is observed. In this study we investigate the problem of designing a multi‐item manufacturing system, where there is both demand‐ and production‐related uncertainty, so that stockless operation will be optimal for all items. For the problem of interest, we focus on gaining an understanding of the effect of two design variables: (i) manufacturing speed—measured by the average manufacturing rate or, equivalently, the average unit manufacturing time, and (ii) manufacturing consistency—measured by the variation in unit manufacturing times. We establish conditions on these two variables that decision makers can use to design stockless production systems. Managerial implications of the conditions are also discussed.     

冲击型负荷下的生产存储模型研究

建立了考虑冲击需求、变化生产率的最优生产存储库存策略. 其特点是:把一个生产周 期分为多个生产阶段,各个生产阶段时间可以不同;在每个生产阶段中,允许生产率小于需求 率,允许提前生产;而且,最大生产率要小于最大需求率. 研究发现,为满足冲击需求,提前存储 较多而启动机器数量较少,或提前存储较少而启动机器数量较多,不一定能够取得最佳效益, 要根据存储费用和启动费用共同确定. 在有限生产率的条件下,得出一种寻求最优生产- 库存 策略,为此类库存系统的管理决策提供了理论依据.     

Optimal Ordering Policies for Stochastic Inventory Problems with Observed Information Delays

Information delays exist in an inventory system when it takes time to collect, process, validate, and transmit inventory/demand data. A general framework is developed in this paper to describe information flows in an inventory system with information delays. We characterize the sufficient statistics for making optimal decisions. When the ordering cost is linear, the optimality of a state‐dependent base‐stock policy is established even when information flows are allowed to cross over time. Additional insights into the problem are obtained via a comparison between our models and the models with stochastic order lead times. We also show that inventory can substitute for information and vice versa.     

Inventory Management for Customers with Alternative Lead Times

It is common for suppliers operating in batch‐production mode to deal with patient and impatient customers. This paper considers inventory models in which a supplier provides alternative lead times to its customers: a short or a long lead time. Orders from patient customers can be taken by the supplier and included in the next production cycle, while orders from impatient customers have to be satisfied from the on‐hand inventory. We denote the action to commit one unit of on‐hand inventory to patient or impatient customers as the inventory‐commitment decision, and the initial inventory stocking as the inventory‐replenishment decision. We first characterize the optimal inventory‐commitment policy as a threshold type, and then prove that the optimal inventory‐replenishment policy is a base‐stock type. Then, we extend our analysis to models to consider cases of a multi‐cycle setting, a supply‐capacity constraint, and the on‐line charged inventory‐holding cost. We also evaluate and compare the performances of the optimal inventory‐commitment policy and the inventory‐rationing policy. Finally, to further investigate the benefits and pitfalls of introducing an alternative lead‐time choice, we use the customer‐choice model to study the demand gains and losses, known as demand‐induction and demand‐cannibalization effects, respectively.     

客户集中度、市场环境与存货管理效率

客户处在供应链的下游,对企业存货的采购、生产和销售都会产生重要影响,而多变的市场环境也在无形当中影响着客户与企业之间的关系。从企业所处行业、地区产品市场和客户三个角度所带来的市场环境变化入手,采用2011—2017年我国沪深两市A股制造业上市公司的数据,实证分析客户集中度与企业存货管理效率之间的关系。研究发现:(1)客户集中度越高,企业存货管理效率越高；(2)产品市场竞争力度越强,客户集中度对企业存货管理效率的影响越大；(3)产品市场发育越好,客户集中度对企业存货管理效率的影响越大。进一步研究发现,当企业因客户生产经营原因导致需求发生较大变化时,客户集中度对企业存货管理效率的正向影响更加显著。研究结论表明,政府应当注重市场竞争力的提升和良好经营环境的建设,使得企业在维护客户关系的同时充分发挥客户集中度对企业存货管理效率的积极作用。     

The household inventory as urban ‘theatre’ in late medieval Burgundy

In 1413 at the death of his wife Guillemot, Jean Aubert, a group of witnesses and a clerk of the local mayoralty met to value the possessions of their residence, resulting in an inventory full of notes and values on rooms and their objects. Within the existing historiography of the Burgundian Netherlands and its northern European neighbours, inventories and their objects tend to be analysed from two perspectives: the Burgundian court and the ‘consumer revolution’. Applying insights from Erving Goffman and Bruno Latour, this article suggests a third perspective should have priority: the urban ‘theatre’ within which objects were documented and placed. Therefore it sets up an alternate methodology which begins with the inventory to build a picture of the theatre (the urban context and residence), the actors (the Aubert family) and the audience (the witnesses of the inventory) to establish new insights into the operation of Burgundian power and the dynamics of the ‘consumer revolution’.