Optimal Ordering Policies for Inventory Problems With Dynamic Information Delays

Information delays exist when the most recent inventory information available to the Inventory Manager (IM) is dated. In other words, the IM observes only the inventory level that belongs to an earlier period. Such situations are not uncommon, and they arise when it takes a while to process the demand data and pass the results to the IM. We introduce dynamic information delays as a Markov process into the standard multiperiod stochastic inventory problem with backorders. We develop the concept of a reference inventory position. We show that this position along with the magnitude of the latest observed delay and the age of this observation are sufficient statistics for finding the optimal order quantities. Furthermore, we establish that the optimal ordering policy is of state‐dependent base‐stock type with respect to the reference inventory position (or state‐dependent (s, S) type if there is a fixed ordering cost). The optimal base stock and (s, S) levels depend on the magnitude of the latest observed delay and the age of this observation. Finally, we study the sensitivity of the optimal base stock and the optimal cost with respect to the sufficient statistics.     

供应链融资结构视角下的零售商订购策略研究

本文引入供应链融资结构因素,在传统库存管理模型基础上,研究零售商在面临随机市场需求情形下考虑股权和债权等融资方式的订购策略,建立允许零售商延期支付的最优订购模型,利用最优化理论与方法得到了该模型的最优解,证明了最优解的存在性和唯一性,并分析了债权融资比例、价格成本比例系数、销售价格、订货周期、回购价格、进货价格、缺货成本、库存成本、以及融资利率等因素对最优解的影响。进一步,通过数值示例深入探讨具体市场环境下零售商的最优订购量,并进行了敏感性分析。研究发现,债权融资比例、价格成本比例系数、进货价格、订购周期、库存成本与零售商订购量存在负相关关系;缺货成本、回购价格、销售价格与零售商订购量正相关。相关研究结论可以为零售商订购行为提供科学指导,并为其库存管理提供重要决策依据。     

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.     

Production and Sales Planning in Capacitated New Product Introductions

How should a firm with limited capacity introduce a new product? Should it introduce the product as soon as possible or delay introduction to build up inventory? How do the product and market characteristics affect the firm's decisions? To answer such questions, we analyze new product introductions under capacity restrictions using a two‐period model with diffusion‐type demand. Combining marketing and operations management decisions in a stylized model, we optimize the production and sales plans of the firm for a single product. We identify four different introduction policies and show that when the holding cost is low and the capacity is low to moderate, a (partial) build‐up policy is indeed optimal if consumers are sensitive to delay. Under such a policy, the firm (partially) delays the introduction of its product and incurs short‐term backlog costs to manage its future demand and total costs more effectively. However, as either the holding cost or the capacity increases, or consumer sensitivity to delay decreases, the build‐up policy starts to lose its appeal, and instead, the firm prefers an immediate product introduction. We extend our analysis by studying the optimal capacity decision of the firm and show that capacity shortages may be intentional.     

考虑策略型消费者的在线零售商库存信息披露及联合定价、库存决策模型

在两期销售环境下,研究了面向策略型消费者的在线零售商库存信息披露及联合定价、库存决策问题。考虑在线零售商库存信息共享和隐藏两种库存披露策略,构建了在线零售商两期销售利润模型。通过分析消费者的购买行为,讨论了在具有策略型消费者的市场中,在线零售商应如何选择库存信息披露策略,以及如何制定最优定价和库存决策。在此基础上,分析了相关参数对在线零售商决策及利润的影响。研究结果表明,在线零售商的最优定价及库存决策受消费者估值折扣系数和第二期定价策略的影响。特别地,当在线零售商选择第一期缺货时,更倾向于共享其库存水平信息;当在线零售商选择第二期缺货或者两期均不缺货时,消费者估值折扣系数存在一个阈值,当低于该阈值时,在线零售商会选择隐藏库存水平信息,当高于该阈值时,在线零售商会选择共享库存水平信息。     

The Effects of Sharing Upstream Information on Product Rollover

The process of introducing new and phasing out old products is called product rollover. This paper considers a periodic‐review inventory system consisting of a manufacturer and a retailer, where the manufacturer introduces new and improved products over an infinite planning horizon using the solo‐roll strategy. We consider two scenarios: (1) the manufacturer does not share the upstream information about new‐product introduction with the retailer and (2) the manufacturer shares the information. For each scenario, we first derive the decentralized ordering policy and the system‐optimal ordering policy with given cost parameters. We then devise an optimal supply chain contract that coordinates the inventory system. We demonstrate that when the inventory system is coordinated, information sharing improves the performance of both supply chain entities. However, this may not be true if the inventory system is not coordinated. We also show that under the optimal contract, the manufacturer has no incentive to mislead the retailer about new‐product information in the information‐sharing model. When demand variability increases, information sharing adds more benefits to the coordinated supply chain. Our research provides insights about coordinating product, financial, and information flows in supply chains with product rollover.     

时变供需下基于商业信用的零售商最优订货策略

论文在时变供需环境下,即市场需求为斜坡式时间函数及补货率依赖于市场需求情境下,探讨了基于商业信用的供应链中零售商最优订货策略。首先,根据商业信用期和零售商补货周期的关系,分两种情形构建了零售商库存模型;其次,根据零售商的库存模型,证明了其最优解的存在,并给出相关的命题和算法来求解零售商的最优库存策略;最后,通过数值算例和灵敏度分析来论证文中的有关结论。研究发现:当供应商给予零售商的商业信用期较短时,此时市场需求仍处于增长期,随着市场需求稳定时间点的增大,零售商的最优订货周期逐渐减小,最优订货量和年费用也逐渐减小;当供应商给予零售商的商业信用期较长时,此时市场需求已趋于稳定期,随着市场需求稳定时间点的增大,零售商的最优订货周期逐渐增大,最优订货量和年费用也逐渐增大;当供应商生产与市场需求依赖性逐渐增大时,零售商的最优订货周期逐渐增大,最优订货量及年费用也逐渐增大。     

Inventory leanness and the financial performance of firms

This paper examines the financial consequences that inventory leanness has on firm performance. We conduct an econometric analysis using 4324 publicly traded US manufacturing companies for the period 1980–2008. Using an instrumental variable fixed effects estimator we find a nonlinear relationship between inventory leanness and financial performance. However, we note that the maximum point of this inverted U-shaped relationship often lies at the extreme end of the investigated sample – suggesting a decreasing return from leanness rather than an optimal level. We show that the strength of this relationship is highly dependent on both the industry and inventory component (raw materials, work in process and finished goods) studied. The main novelty and direct implication of our findings is that most firms still have much potential to increase profitability by becoming leaner and they are unlikely to cross a threshold where profitability decreases with increased leanness. We display how much the average firm could gain by becoming leaner and show how this sensitivity changes by inventory component and industry. Finally, we highlight several new econometric aspects that we believe must be addressed when empirically investigating the inventory-performance link.     

The Value of Information for Managing Retail Inventory Remotely

An important difference between both manufacturing and wholesaling vs. retail is the information available concerning inventory. Typically, far less information characterizes retail. Here, an extreme environment of information shortfall is examined. The environment is technically termed “unattended points of sale,” but colloquially called vending machines. Once inventory is loaded into a machine, information on demand and inventory level is not observed until the scheduled reloading date. Technological advances and business process changes have drawn attention to the value of information (VOI) in retail inventory in many venues. Moreover, technology is now available that allows unattended points of sale to report inventory information. Capturing the value of this information requires changes in current business practice. We demonstrate the value of capturing information analytically in an environment with restrictive demand assumptions. Experiments in an environment with realistic demand assumptions and parameter values show that the VOI depends greatly on operating characteristics and can range from negligible effects to increasing profitability 30% or more in actual practice.     

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.     

分段的延期支付条件下临时订货策略分析

商业活动中供应商时常会给采购商短期的价格折扣,目的是使采购商进行临时的大量采购;供应商为了鼓励采购商订货,会针对采购规模给予其不同的延期支付期限;而当价格恢复到定常时,延期支付的期限则为供求双方事先规定的常值,采购商按照允许延期支付的EOQ模型订货。将延期支付基本EOQ模型中存在的门槛式延期支付规则(只有当采购量大于特定值才可以延期支付货款)应用并推广到这种临时采购中:延期支付期限是临时采购量的分段函数。由于采购商可以采取按低价追加订货或者放弃这个机会,基于这2种策略年度成本差异最大化,分析了采购商最优的追加订货批量如何确定的问题,拓宽了允许延期支付的EOQ模型应用范围。     

Forecasting Product Returns for Remanufacturing Operations

Driven by legislative pressures, an increasing number of manufacturing companies have been implementing comprehensive recycling and remanufacturing programs. The accurate forecasting of product returns is important for procurement decisions, production planning, and inventory and disposal management in such remanufacturing operations. In this study, we consider a manufacturer that also acts as a remanufacturer, and develop a generalized forecasting approach to determine the distribution of the returns of used products, as well as integrate it with an inventory model to enable production planning and control. We compare our forecasting approach to previous models and show that our approach is more consistent with continuous time, provides accurate estimates when the return lags are exponential in nature, and results in fewer units being held in inventory on average. The analysis revealed that these gains in accuracy resulted in the most cost savings when demand volumes for remanufactured products were high compared to the volume of returned products. Such situations require the frequent acquisition of cores to meet demand. The results show that significant cost savings can be achieved by using the proposed approach for sourcing product returns.     

An Analysis of Dual‐Kanban Just‐In‐Time Systems in a Non‐Repetitive Environment

Recent advances in approaches and production technologies for the production of goods and services have made just‐in‐time (JIT) a strong alternative for use in intermittent and small batch production systems, especially when time‐based competition is the norm and a low inventory is a must. However, the conventional JIT system is designed for mass production with a stable master production schedule. This paper suggests supplementing the information provided by production kanbans with information about customer waiting lines to be used by operators to schedule production in each work‐station of intermittent and small batch production systems. This paper uses simulation to analyze the effect of four scheduling policy variables—number of kanbans, length of the withdrawal cycle, information about customer waiting lines, and priority rules on two performance measures—customer wait‐time and inventory. The results show that using information about customer waiting lines reduces customer wait‐time by about 30% while also reducing inventory by about 2%. In addition, the effect of information about customer waiting lines overshadows the effect of priority rules on customer wait‐time and inventory.     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

Acting with the best of intentions… or not: A typology and model of impression management in leadership

Impression management (IM) is important for effective leadership. Followers accept influence from individuals who meet their perceptions of what it means to be a leader, and IM is an important way of impacting those perceptions. Yet, the extant literature on leader IM is fragmented. We unify the literature in this area by creating a multi-dimensional typology and multi-level model of IM in leadership. We examine the multi-dimensional nature of IM as a construct composed of information processing, communicative, and goal-directed components, thereby creating eight IM archetypes. Then, we examine how IM can be used to impact follower perceptions of the leader through the lenses of transformational/charismatic, authentic, and leader categorization theories. This research unites a currently fragmented area of research and sparks new questions about how leader behaviors can be used to influence followers toward multi-level leadership outcomes.     

A review of RFID technology and its managerial applications in different industries

Radio frequency identification (RFID) is an emerging technology that is increasingly being used in supply chain management. RFID technology plays an important role in supporting logistics and supply chain processes because of their ability to identify, trace and track information throughout the supply chain. The technology can provide suppliers, manufacturers, distributors and retailers precise real time information about the products. This accurate knowledge of the inventory would result in lower labor cost, simplified business processes and improved supply chain efficiency. If properly used, it has the potential to cut ordering lead time and cost on inventory control, increase the accuracy of inventory information, help avoid stockouts and boost the number of inventory turns. In this paper, we provide an overview of the current state of RFID applications in different industries and its impact on business operations. We provide extensive literature survey and develop a framework for future research areas in this field.     

An exploration of ‘sticky’ inventory management in the manufacturing industry

Traditional models examining relationships between firm resources and revenues assume that the many expenses and asset holdings change in proportion to changes in demand. However, research has found that for many costs and assets assumed to be variable, the magnitude of a change in a cost or asset in proportion to a change in revenue is smaller during periods when revenue decreases compared to the change in the cost or asset when revenue increases. Costs and assets which behave in this manner have been denoted as ‘sticky’ costs or assets. This study examines if inventory in the manufacturing industry is managed in a ‘sticky’ manner and what implications inventory stickiness has on firm performance. Utilising firm panel data over a 25-year time window we find that inventory stickiness does exist amongst manufacturers and that it has negative implications for firm performance.     

Knowing What Your Customer Wants: Improving Inventory Allocation Decisions in Online Movie Rental Systems

In Online Movie Rental Systems, customer desire to rent can often be observed before the actual consumption occurs. Desire represents uncensored (or true) demand information. Hence, the impact of inventory decisions (numbers of physical copies of different movies) can be accurately traced to the creation of desire (via Word‐of‐mouth), and then to rental. Word‐of‐Mouth (WOM) has been recognized as one of the most influential sources of information transmission, especially for experience goods. Poor inventory decisions may result in lost rentals in two ways: One is the loss of rentals because of low inventory (direct effect), and the other is the loss of the possible demand (rentals) that could have been created through WOM (indirect effect). We use data from an online DVD‐by‐mail firm to estimate the direct and indirect effects of inventory decisions, considering the circular relationship: Rental generates WOM, WOM creates Desire, and Desire turns into Rental. We find that the magnitude of indirect effects is significant, comparable to and sometimes even exceeding direct effects. The value of the empirical findings to facilitate better inventory allocation decisions is examined.     

Optimal inventory model for items with imperfect quality and shortage backordering

In this study, we develop an optimal inventory model for items with imperfect quality and shortage backordering. Such implicit assumption is reasonable in view of the fact that poor-quality items do exist during production. They are usually picked up during the screening process and are withdrawn from stock instantaneously. It is assumed that all customers are willing to wait for new supply when there is a shortage. The analysis shows that our model is a generalization of the models in current literatures. An algorithm and numerical analysis developed show that our model always results in better performance.     

Lowering Inventory Systems Costs by Using Regression-Derived Estimators of Demand Variability*

Scientific techniques for inventory management typically are applied to systems containing many items. Such techniques require an estimation of the demand variance (and mean) of each item from historical data. This research demonstrates a significant potential for improvement in system cost performance from using least-squares regression fits of a variance-to-mean functional relation instead of the standard statistical variance estimate. Even when there is a moderate degree of heterogeneity among items and when the form of the variance-to-mean relation is misspecified, substantial cost savings may be realized. The cost of statistical uncertainty may be reduced by half. The research also provides evidence that system cost is fairly insensitive to the number of items used to fit the regression. This paper provides the underlying reason why a regression-derived variance estimator yields lower cost: it is less variable than the usual individual item variance estimator.