The newsvendor model revisited: the impacts of high unit holding costs on the accuracy of the classic model

The newsvendor problem has been applied in various business settings. It is often assumed that the decision variable, i.e., order-up-to level, has no impacts on the holding costs for average inventory cycled in a given period, which is the difference between beginning and ending inventory levels on hand in that period. The average holding cost for this portion of inventory is conveniently and approximately calculated as half the product of the unit holding cost and the expectation of the demand in one period if it is assumed that the inventory is approximately evenly consumed. It is a good approximation when the unit holding cost is significantly lower than the unit backorder cost as this optimal solution to inventory level is able to guarantee a low probability of understocking. However, if this condition does not hold, the approximation may deviate from the actual cost and cannot measure the expected holding cost for this portion of inventory. This paper examines the impact of the cycle stock holding cost on the newsvendor model and the conditions under which this portion of cost is not negligible.     

Capital Utilisation and Scale in the English and Welsh Water Industry

The study estimates a variable cost model of the UK water industry. From this variable cost function, estimates of economies of scale and economies of capital utilisation and capacity utilisation are made. The data used cover 20 English and Welsh water companies. The results suggest that only slight, albeit, significant dis-economies of scale and substantial diseconomies of capital utilisation exist in the industry. These estimates indicate that if output increases, with or without holding capital constant, variable costs would increase at a level above the proportional increase in output. If the water industry is not in long-term equilibrium, in terms of capital, neither merger nor acquisition amongst water companies are justified in terms of cost efficiency. A low level of capital utilisation is also indicated for the water industry. It is shown that the level of capital utilisation does increase over the sample period to approximately 30 per cent in 1996, indicating dis-equilibrium, in terms of capital, is present in this sector.     

The Role of Schedule Mismatch in Ending Inventory Decisions in the Presence of Price Cuts

In the high‐tech sector, component suppliers are often able to offer preannounced price cuts (price markdowns) to manufacturers due to technological innovation that allows them to produce the existing components at lower costs. In this context, manufacturers (buyers) are primarily concerned with their existing inventory carried beyond the price cuts in order to lower inventory costs. In this research, we develop a newsvendor‐based decision model for this problem based on our experience in industry and a focal case study environment. Specifically, we consider the issue of delivery and demand uncertainties, and the interplay of the buying firm's operating hours and the transportation carrier's delivery hours, which combine to influence inventory costs and order fulfillment. We illustrate the results with numerical examples and sensitivity analyses, using a real world data set. We found that stockout cost plays a critical role in the ending inventory decisions. Lowering stockout cost will benefit buyers from lower risk of obsolescence costs.     

季节性商品供应链的库存管理战略研究

库存管理是季节性商品销售活动中的重要决策内容,经典报童模型反映了单个决策者的管理模式。遵循季节性商品供应链的运作机制,从供应链管理的角度来进行库存管理,引入库存管理战略优化供应链整体性能,平衡供需矛盾,从而创建一个和谐的供应链环境。     

A COMPARISON OF THE ECONOMIC ORDER QUANTITY AND QUICK RESPONSE INVENTORY REPLENISHMENT METHODS

When determining order quantity, logistics managers can choose between ordering the Economic Order quantity (EOQ) or a Quick Response (QR) quantity. QR is a general term that collectively describes several rapid‐replenishment inventory methods such as Just‐In‐Time or Continuous Replenishment. The QR order quantity is defined as the minimum inventory needed to support operations until the next delivery. The EOQ and the QR methods are substantially different because the EOQ minimizes the joint cost of ordering and holding inventory whereas the QR method minimizes only the cost of holding inventory. The goals of this research are to compare the costs of the two methods and to propose rules that help managers select the more appropriate method to use in specific situations.     

Resilience toward supply disruptions: A stochastic inventory control model with partial backordering under the base stock policy

This paper examines supply-side disruptions using an inventory management framework to gain insights into the economic performance of buyers who use two conventional costing strategies – end-of-cycle and continuous. The proposed model assumes that a single supplier faces full disruptions with a probability, and therefore, fails to procure all the items ordered. Accordingly, the buyer experiences unmet demand, which is assumed to be partially backordered. To make proper replenishment decisions, two base stock (S,T) periodic review optimization models are developed. The objective functions minimize the expected long-run total costs (i.e., ordering, holding, and shortage). After proving their convexity and obtaining the optimal decisions, computational experiments were carried out to investigate the impacts of the change in parameters. The results highlight the importance of selecting a suitable ratio for backorders during supply disruptions, as it leads to lower costs and reduces the inventory obsolescence and overstocking risks. Moreover, the managerial insights derived from this study aid retailers to make better replenishment decisions (in terms of level and frequency) and to be more resilient in times of disruptions. Retailers can benefit from the provided solution algorithm as a computational application.     

EXPRESSING INVENTORY CONTROL POLICY IN THE TURNOVER CURVE

Estimation of the inventory level for an entire class of items is a valuable time saver when control of inventories at the aggregate level, rather than the item level, is of interest. Inventory approximation by location in supply chain network configuration and evaluation of inventory control policy shifts, are two examples of application. In this article, various popular inventory policies are related to a general function known as an inventory turnover curve that expresses inventory levels from the combined demand of multiple items. By knowing some basic item characteristics of representative items in a product class, the type of inventory policy being used, and the current aggregate inventory level, an inventory turnover curve can be constructed. This resulting turnover curve can be used to estimate inventory levels within 4.6%, on the average, of theoretically predicted ones.     

How does the retailing industry decide the best replenishment strategy by utilizing technological support through blockchain?

Practitioners face two significant issues: product inaccuracy and transparency in supply chain management. Blockchain is a highly secure and trustworthy means of storing data. Radio frequency identification incorporation is essential if reliability is at a low level. Incorporating radio frequency identification can improve supply chain management in terms of product's visibility for the best replenishment strategy. A production and replenishment coordination via mathematical modeling is visualized through a three-echelon supply chain with a non-reliable production process, and the retailer deals with misplacement issues. The manufacturer handles the inventory flowing reversely and is responsible for proper end-of-life treatment, either repairing or remanufacturing. Repairs are sold in bulk on the secondary market, and remanufactured items are used to prevent retailers' shortages. In this model, radio frequency identification technology on the physical surface is combined with a blockchain on the cyber surface, containing all the information about the product, including its location and attributes. A comparative study is provided for the traditional supply chain with misplacement versus a blockchain-based supply chain with radio frequency identification. An analytical approach is used to arrive at the optimum policy for the practitioners, and numerical analysis illustrates the problem. Numerical experiments indicate that the technology is highly profitable for supply chain management. Radio frequency identification technology can increase profit by up to 61%. After discrepancy, holding cost is the second most sensitive parameter for the profit function. If the holding cost is higher, profit can be increased by 40% using radio frequency identification and blockchain. The negative effect of misplacement is reduced with an increasing demand rate, but the reduction rate is very slow. The choice of not adopting radio frequency identification can only be successful if demand is so high that it can reduce the effect of misplacement.     

RELIABILITY AND REGULATION IN PRICING PUBLIC UTILITY SERVICE

The principal question addressed in this paper concerns the optimal price profile for a regulated public utility where demand is stochastic. Through the introduction of rationing costs and a rate-of-return constraint, marginal revenue will be approximately equated to the cost associated with satisfying the last unit of consumers’demand. This has significant implications for capacity expansion. Namely, capacity is added to keep the risk of failure minimal. As a result, to the extent that the associated costs are higher for the last unit of capacity, a higher marginal revenue and hence price will result. That is, if the marginal unit of capacity has a high operating and delivery cost and low capital cost with high reliability and consequent high total cost (e.g., an internal combustion peaking unit), the indicated result follows. Consequently, there is a direct trade off between the level of risk of failure and marginal revenue. This provides a rationalization for the existence of the price differential between firm and interruptible customers. Finally, if the firm is contrained to earn a fair return on its capital investment, it will set prices to favor the consumers generating the expansion in capacity.     

库存持有成本的降低途径简析

库存持有成本是与库存数量直接相关的那一部分成本。要准确地衡量物流系统的绩效,必须对持有成本进行精确分析。本文分析了物流系统中库存持有成本的构成及影响因素,并对库存持有成本的降低途径提出几点浅见。     

基于供应链管理的制造型企业库存优化研究与实践——以AIP公司库存管理优化为例

库存不仅占用流动资金,增加储运成本,而且还会带来诸如安全、变质、贬值等一系列风险.因此,如何科学地削减库存总量,保持合理的库存水平,实现企业低成本运营,一直是企业界所关注的热点问题.鉴于此,本研究在全面库存管理思想的指导下,分析了AIP公司的库存管理现状,通过加强物流管理、改善内部供应链、扩大信息共享范围等手段,解决了库存量偏高和库存结构不合理问题,实现了优化库存总量、降低经营成本和提高市场竞争力等企业目标,并据此提出库存管理内容和模式的一些创新观点,从技术层面找到了普遍适用的库存管理与控制的有效措施,以期对制造型企业的库存管理有借鉴意义.     

供应链管理视角下的企业预付款融资采纳研究

文章结合供应链管理理论及营运资金管理理论,从供应链管理运作管理的视角出发,深入分析影响企业采纳预付款融资的因素。基于来自全国717个企业的供应链金融调查数据,文章利用对二分类因变量进行回归建模的Logistic回归模型,对企业采纳预付款融资的发生概率进行拟合。研究结果表明,从融资企业资金需求的角度,供应商提供原材料的平均交付周期越长、企业所采购物料的价格波动越大,越倾向于采纳预付款融资来解决资金问题,维持企业正常运营。结合金融机构信用风险控制的考虑,相对于原材料价格波动小的企业,所在供应链信息化程度高对帮助原材料价格波动大的企业获得金融机构授信的作用更显著。同时,文章认为出于确保还款资金来源的考虑,金融机构更倾向于向原材料库存平均周转天数短的企业授信;由于融资企业引入外部金融机构资金带来了额外的融资成本,会激励企业更努力做好其原材料库存管理,缩短原材料库存平均周转天数,尽早预付款融资,降低融资成本。     

LOGISTICS AND ASSORTMENT DEPTH IN THE RETAIL SUPPLY CHAIN: EVIDENCE FROM GROCERY CATEGORIES

Managing the logistical issues resulting from changes in assortment depth in the retail supply chain is challenging, involving various complex tradeoffs. While increasing assortment depth can increase sales, it also increases inventory‐holding costs and reduces the amount of space for other items. As space is taken from existing items to increase assortment depth, it reduces the inventory‐holding capacity of existing items on the shelf, increasing expected annual cost of lost sales. The paper presents a conceptual model of the relationships between assortment depth, category gross margins, and the logistical concerns resulting from inventory costs and out‐of‐stocks. Evidence for the significance of depth and resulting costs are provided in an examination of 100 product categories from a case study of a retail grocery chain.     

Low-carbon decision-making model of online shopping supply chain considering the O2O model

A demand function of online shopping supply chain based on online-to-offline (O2O) fusion degree is proposed by considering the low-carbon awareness of online shoppers in view of the low-carbon decision making of supply chain in combination with the O2O operation background. On this basis, a low-carbon decision-making model based on online stores and their suppliers is established, and the application of the model is analyzed. Results show that the promotion of low-carbon operation is efficient when the consistency of online and offline operations of online stores and their suppliers is high. In addition, the decision making considering the cost of carbon information release is highly conducive to improving the low-carbon awareness of online shoppers if the low-carbon level of online shopping goods is lower than the low-carbon standard. Accordingly, the low-carbon operation of online shopping supply chain will be promoted.     

Price competition between green and non green products under corporate social responsible firm

This article deals with a newsvendor inventory model in light of green product marketing of corporate social responsible firms. In this model, comparison between green and non green marketing is analyzed including subsidy and tax implementation by Government where the Government offers higher subsidy and lower tax to the green producer unlike the lower subsidy and higher tax to the non green producer. There is also price contest between green and non green producer as the demands of the products are dependent on sales price, carbon emission and corporate social responsibility index. Assuming the cost and profit parameters, an expected profit function of the systems is formulated and maximized analytically. Finally, numerical examples are illustrated to justify the proposed model.     

A Model of Household Grocery Shopping Behavior

The shopping trip to the grocery store is one of the most basic elements of consumer behavior. The authors seek to provide an understanding of the factors that account for variations in shopping behavior across households. They present a model of shopping behavior that assumes that households seek to minimize the travel cost associated with shopping and the cost of holding goods in inventory. As in the classic EOQ model, observed shopping behavior reflects the manner in which households balance these costs while meeting their consumption needs. A number of propositions derived from the model are tested using data on shopping trips made by households over a one-year period. The results support the model and indicate that the relationship between household characteristics and shopping behavior can be fairly complex: for some households shopping may have a recreational aspect while for others it may compete directly with wage-earning activity.     

AN INVESTIGATION INTO THE EFFECT OF FULL‐SCALE SUPPLY CHAIN MANAGEMENT SOFTWARE ADOPTIONS ON INVENTORY BALANCES AND TURNS

Supply chain management (SCM) software vendors, analysts, and others claim that firms implementing SCM software stand to benefit by being able to reduce inventory holdings and increase inventory turns. We theorize that full‐scale implementations lead to system‐wide inventory optimization, which in turn leads to cost improvement associated with inventory balances and turns. To examine the question, we develop an analytical model of inventory optimization, then analyze the effects of the model with a numerical experiment, and finally confirm the results with an empirical examination. We find that firm‐wide implementation is significant in explaining improvement in inventory metrics, relative to pre‐implementation metrics for our sample. Our empirical tests indicate that implementing SCM software across only a portion of the firm does not impact inventory metrics, but that the scale of implementation does. More precisely, we find that firms implementing SCM software across the entire company significantly improve both inventory turns and inventory as a percent of revenue relative to partially‐implementing firms and non‐implementers.     

Stock replenishment policies for a vendor-managed inventory in a retailing system

Using Vendor Managed Inventory (VMI), the vendor determines the replenishment decisions at the location of buyers (retailers). This strategy is used primarily for handling demand fluctuations stemming from the Bullwhip effect, leading the system to prevent from holding excessive inventory that result in a reduction in the overall cost of the supply chain. The main advantages of VMI for vendors are higher levels of accessibility to inventory information and more direct contact with the customers. Similarly, VMI has some pros for the buyers, such as shared risk with upper levels of supply chain and reduction in their holding costs of inventory. In this paper, a vendor-managed inventory system is developed containing one vendor and two buyers in which the main assumption is that back-ordering and lost sales are permitted. In this system, (r, Q) and (R, T) replenishment policies are compared according to their performances to see which one performs more cost-efficiently when partial back-ordering is allowed. In accordance, mathematical models utilizing (r, Q) and (R, T) replenishment policies are developed, and algorithms for deriving the optimal replenishment decision variables are proposed. Moreover, significant differences between the two replenishment policies are discussed. The main finding obtained by this research is that when shortage is permitted, both (r, Q) and (R, T) replenishment policies under VMI have pros and cons in different contexts.     

Sales expectations and inventory changes in retail trade

In this paper a single equation inventory investment model is estimated for the United States retail sector. Monthly data for the 1970s are utilized. In estimating the model it is alternatively assumed that expectations were formed according to a seasonal model, to perfect foresight, and to a narrowly rational expectations model. We find that a model in which expected sales and the expected rate of inflation are narrowly rational can explain most of the variation in retail inventory investment during the time period studied. The results of the estimation imply that retailers have a relatively short forecast horizon, that they can react quickly to either unexpected sales or to a deviation of actual from desired inventory stocks, and that an increase in the real of interest has a statistically negative impact on retail inventory investment.     

Analyzing leases with the after-tax cost of debt

A generalized expression of the net advantage of leasing (NAL) is used to assess the implications of discounting incremental cash flows at the firm's before-tax cost of debt and the firm's after-tax cost of debt, respectively. If no personal tax biases are assumed, then the before-tax cost of debt should be used to compute NAL. If the before-tax cost of debt is the correct discount rate, then any change in the firm's borrowing level brought about by the decision to lease rather than purchase will alter the computed NAL by the amount of the present value of the tax savings on interest payments. Thus using the before-tax cost of debt is consistent with basic MM valuation theory. Using the after-tax cost of debt, in contrast, implies that any associated change in the firm's borrowing level is irrelevant for purposes of computing NAL. Sufficient conditions are specified for the after-tax cost of the debt to be the correct discount rate for lease versus purchase analysis. Finally, lease analysis in a MM world is compared to lease analysis in a Miller tax world. For the special case of a 100% leverage ratio, the specification of NAL is the same in both worlds. Use of the after-tax cost of debt is correct in a Miller world and is a good approximation in an MM world provided the cash flows are predominantly debt financed.