Price-setting newsvendor with strategic consumers

We consider a newsvendor who sells a single product over a single season with the objective of determining both the selling price and stock quantity to maximize the expected profit. The customers are strategic and we consider two demand cases: additive and multiplicative. For each case, we derive the newsvendor׳s optimal decisions and demonstrate that neglecting the price-sensitivity of demand leads the newsvendor to make sub-optimal decisions. Moreover, we show that under certain conditions, strategic consumer behavior may positively affect the newsvendor׳s optimal expected profit in the additive demand case.     

The price-setting newsvendor with service and loss constraints

Current performance measurement systems consider not only financial measures, like costs and profits, but also non-financial indicators with respect to customer service, quality and flexibility. Using the newsvendor model, we analyse the respective influence of these possibly conflicting performance measures on important operations and marketing decisions, for instance the order quantity and the selling price of a product. As in the classical newsvendor model for price-independent as well as price-dependent demand distribution, the objective of the firm is to maximise expected profit. In this paper, we also consider a service constraint—a lower bound for the level of product availability—and a loss constraint—an upper bound for the probability of a loss occurring. For both models, we provide conditions for the existence of solutions. We then analyse the influence of demand variability using a set of conditions specifying the quantiles of the predetermined performance measures: a higher variability of demand implies a smaller admissible region of the decision variables. In the price-independent case, the optimal solution has a control-limit structure: the optimal order quantity is thus given either by the classical newsvendor solution or by the control-limits corresponding to the constraints. In the price-setting model with multiplicative demand, this structure is used to check whether small admissible prices are determined by the service constraint or by the loss constraint. Using these structural results, a procedure is developed to more easily enable the computation of the optimal values of the order quantity, selling price and expected profit.     

Ordering,Pricing, and Lead‐Time Quotation Under Lead‐Time and Demand Uncertainty

In this article, we study the newsvendor problem with endogenous setting of price and quoted lead‐time. This problem can be observed in situations where a firm orders semi‐finished product prior to the selling season and customizes the product in response to customer orders during the selling season. The total demand during the selling season and the lead‐time required for customization are uncertain. The demand for the product depends not only on the selling price but also on the quoted lead‐time. To set the quoted lead‐time, the firm has to carefully balance the benefit of increasing demand as the quoted lead‐time is reduced against the cost of increased tardiness. Our model enables the firm to determine the optimal selling price, quoted lead‐time, and order quantity simultaneously, and provides a new set of insights to managers.     

The newsvendor problem with barter exchange

Barter exchange, as an alternative to move distressed inventory, has become increasingly popular in business. Many companies barter their unsold product for the product they need via barter exchange platforms at full prices. In this paper we consider the newsvendor problem with the barter exchange option. A retailer (the newsvendor) facing stochastic demand not only sells its product, but also buys other product that it needs from the market. It either trades its unsold product for the product it needs on a barter platform or disposes of its unsold product at discounted prices at the end of the selling season like in the classical newsvendor model. We derive the retailer’s optimal order quantity, then analytically and numerically examine the impacts of barter on the retailer’s inventory decisions and profit. We find that barter exchange can help the retailer to manage demand uncertainty and improve profit. The optimal order quantity decreases with barter commission and barter uncertainty, while increases with demand uncertainty and the value of the product that the retailer needs. Barter is more advantageous with lower barter commission, larger demand uncertainty, lower barter uncertainty, and higher value of the product it needs.     

Optimal Dynamic Order Scheduling under Capacity Constraints Given Demand‐Forecast Evolution

We consider a manufacturer without any frozen periods in production schedules so that it can dynamically update the schedules as the demand forecast evolves over time until the realization of actual demand. The manufacturer has a fixed production capacity in each production period, which impacts the time to start production as well as the production schedules. We develop a dynamic optimization model to analyze the optimal production schedules under capacity constraint and demand‐forecast updating. To model the evolution of demand forecasts, we use both additive and multiplicative versions of the martingale model of forecast evolution. We first derive expressions for the optimal base stock levels for a single‐product model. We find that manufacturers located near their market bases can realize most of their potential profits (i.e., profit made when the capacity is unlimited) by building a very limited amount of capacity. For moderate demand uncertainty, we also show that it is almost impossible for manufacturers to compensate for the increase in supply–demand mismatches resulting from long delivery lead times by increasing capacity, making lead‐time reduction a better alternative than capacity expansion. We then extend the model to a multi‐product case and derive expressions for the optimal production quantities for each product given a shared capacity constraint. Using a two‐product model, we show that the manufacturer should utilize its capacity more in earlier periods when the demand for both products is more positively correlated.     

The Dynamic Newsvendor Model with Correlated Demand

The classic newsvendor model was developed under the assumption that period‐to‐period demand is independent over time. In real‐life applications, the notion of independent demand is often challenged. In this article, we examine the newsvendor model in the presence of correlated demands. Specifically under a stationary AR(1) demand, we study the performance of the traditional newsvendor implementation versus a dynamic forecast‐based implementation. We demonstrate theoretically that implementing a minimum mean square error (MSE) forecast model will always have improved performance relative to the traditional implementation in terms of cost savings. In light of the widespread usage of all‐purpose models like the moving‐average method and exponential smoothing method, we compare the performance of these popular alternative forecasting methods against both the MSE‐optimal implementation and the traditional newsvendor implementation. If only alternative forecasting methods are being considered, we find that under certain conditions it is best to ignore the correlation and opt out of forecasting and to simply implement the traditional newsvendor model.      

考虑战略顾客行为时的供应链性能分析与协调

动态定价策略的广泛应用使得越来越多的顾客具有了战略性,战略顾客会根据产品在销售期内的价格路径确定最优购买时机,零售商则根据顾客的购买行为确定订货数量和销售价格.研究了双方静态博弈时的理性预期均衡解和零售商进行数量承诺时的情形.研究表明:理性预期均衡时的最优销售价格、最优存货数量和最优期望利润分别小于标准报童模型的情形;数量承诺时的最优存货数量小于理性预期均衡时的最优存货数量;最优期望利润则大于理性预期均衡时的最优期望利润,并且在一定条件下可能会大于标准报童模型的最优期望利润,战略顾客行为的存在对零售商可能有利.最后分析了在分散式供应链中如何利用收入分享契约和数量折扣契约实现供应链协调.     

Late season low inventory assortment effects in the newsvendor problem

The assumption of the newsvendor being able to satisfy demand as long as on-hand inventory is positive does not hold for a non-homogenous product. Consumers who do not find a unit of the product which satisfies their secondary features preferences may not purchase the product even though the newsvendor has positive on-hand inventory. This is likely to occur late in the season as inventory level declines. We solve a newsvendor problem in which the probability of purchase by consumers is increasing in on-hand inventory for any inventory level below that which is needed to have a complete assortment. We identify the sufficient optimality condition for the order quantity. We show that, unlike the case of inventory-dependent demand models in the literature, the optimal order quantity may decrease due to the assortment effect. We investigate two types of pre-end of season discounts, immediate all-units and delayed, as ways to mitigate the late season assortment effect and show that in some cases, they can increase the newsvendor׳s profit and free up the shelf space for other products.     

Production and pricing problems in make-to-order supply chain with cap-and-trade regulation

This paper studies the production and pricing problems in MTO (make-to-order) supply chain containing an upstream manufacturer who produces two products based on MTO production and a downstream retailer. The manufacturer is regulated by cap-and-trade regulation and determines the wholesale prices of the two products. To comply with the regulation, the manufacturer can buy or sell emission permits through an outside market. The retailer determines its order quantities to meet the price-sensitive demands. We derive the optimal total emissions and production quantities of the two products, and based on them, we analyze the impact of emission trading price on the optimal production decisions and the two firms’ optimal profits. The emission trading decisions follow a two-threshold policy and the optimal total emissions are increasing in the cap. However, contrary to intuition, the optimal production quantities of the two products may be decreasing in the cap. The manufacturer׳s optimal profit is decreasing (increasing) in the buying (selling) price of emission permits, and that the retailer׳s optimal profit is decreasing in the buying (selling) price of emission permits. The optimal total emissions are decreasing in buying or selling price of emission permits, however, the optimal production quantities of the two products may be increasing (decreasing) in the buying (selling) price of emission permits. Numerical examples are conducted to illustrate our findings and some managerial insights are presented.     

Pre‐Orders for New To‐be‐Released Products Considering Consumer Loss Aversion

Advance selling through pre‐orders is a strategy to transfer inventory risk from a retailer to consumers. A newsvendor retailer can have three strategies to choose from: no advance selling allowed (NAS), moderate advance selling with a moderate discount for pre‐orders (MAS), and deep advance selling with a deep discount for pre‐orders (DAS). This research studies how a retailer could design an advance selling strategy to maximize her own profits. We find some interesting results. For example, there exist two thresholds for the selling season profit margin and two thresholds for consumer's expected valuation. For products with higher profit margin than the high threshold on profit margin, a retailer should always use DAS. For products with medium profit margin within the two thresholds, a retailer should adopt MAS if consumer's expected valuation is lower than the high threshold and use DAS otherwise. For products with lower profit margin than the low threshold, a retailer should use NAS, DAS, or MAS, respectively, if consumer's expected valuation is lower than the low threshold, higher than the high threshold, or between the two thresholds, respectively. Through sensitivity analyses, we also show the effects of multiple consumer characteristics on a retailer's optimal advance selling strategy.     

Decision making in the newsvendor problem: A cross-national laboratory study

In this paper, we conduct a laboratory experiment using the classic newsvendor problem to examine cross-national differences in inventory ordering patterns between Chinese and American decision makers based on a theoretical examination of the role of the Doctrine of the Mean in Chinese decision making. Drawing on the theory of context-dependent preferences (specifically extremeness aversion), we also revisit the flat-maximum hypothesis of Bolton and Katok [12], i.e., “thinning the set of order options leads to newsvendor decisions that achieve a higher proportion of maximum expected profit.” The results show that the “pull-to-center” effect is more prominent for Chinese than Americans, i.e., average order quantities of Chinese subjects are closer to the anchor of mean demand than those of American subjects. Furthermore, we find that thinning the set of order options such that the optimal order quantity is a middle option, not an extreme option in the choice set, leads to better performance in newsvendor decisions, which complements the flat-maximum hypothesis.     

Joint Initial Stocking and Transshipment—Asymptotics and Bounds

A common problem faced by many firms in their supply chains can be abstracted as follows. Periodically, or at the beginning of some selling season, the firm needs to distribute finished goods to a set of stocking locations, which, in turn, supply customer demands. Over the selling season, if and when there is a supply‐demand mismatch somewhere, a re‐distribution or transshipment will be needed. Hence, there are two decisions involved: the one‐time stocking decision at the beginning of the season and the supply/transshipment decision throughout the season. Applying a stochastic dynamic programming formulation to a two‐location model with compound Poisson demand processes, we identify the optimal supply/transshipment policy and show that the optimal initial stocking quantities can be obtained via maximizing a concave function whereas the contribution of transshipment is of order square‐root‐of T. Hence, in the context of high‐volume, fast‐moving products, the initial stocking quantity decision is a much more important contributor to the overall profit. The bounds also lead to a heuristic policy, which exhibits excellent performance in our numerical study; and we further prove both the bounds and the heuristic policy are asymptotically optimal when T approaches infinity. Extension to multiple locations is also discussed.     

不同货架空间分配顺序下农产品供应链优化问题研究

货架是超市和生鲜便利店的重要资源，不仅具有储存和展示农产品的功能，同时货架空间大小对农产品的销量具有重要影响。针对产品需求受货架空间与零售价格共同影响的两级农产品供应链，在考虑供应商主导和零售商主导的情况下，分别对零售商在销售季节来临前和来临后分配货架空间四种分散式农产品供应链的最优决策与利润进行了分析，并与一体化供应链的最优决策进行了比较。研究发现，不论是在供应商主导还是在零售商主导的农产品供应链中，零售商在销售季节来临前分配货架空间，相比在销售季节来临后分配货架空间，农产品的批发价格与零售价格更高，分配的货架空间更小，供应商和零售商均获得更少的利润，相应的农产品供应链整体利润更少。因此，零售商在销售季节来临后分配货架空间对农产品供应链更有利。相比一体化供应链，分散式供应链的零售价格更高，分配的货架空间更小，供应链整体利润小于一体化供应链的最优利润，本文给出了基于利润共享与成本共担的合同对分散式供应链进行协调。最后，通过数值算例研究了参数变化对最优决策和供应链利润的影响。     

Flexible Capacity Investments and Product Mix: Optimal Decisions and Value of Postponement Options

In this article, we study a firm's interdependent decisions in investing in flexible capacity, capacity allocation to individual products, and eventual production quantities and pricing in meeting uncertain demand. We propose a three‐stage sequential decision model to analyze the firm's decisions, with the firm being a value maximizer owned by risk‐averse investors. At the beginning of the time horizon, the firm sets the flexible capacity level using an aggregate demand forecast on the envelope of products its flexible resources can accommodate. The aggregate demand forecast evolves as a Geometric Brownian Motion process. The potential market share of each product is determined by the Multinomial Logit model. At a later time and before the end of the time horizon, the firm makes a capacity commitment decision on the allocation of the flexible capacity to each product. Finally, at the end of the time horizon, the firm observes the demand and makes the production quantity and pricing decisions for end products. We obtain the optimal solutions at each decision stage and investigate their optimal properties. Our numerical study investigates the value of the postponed capacity commitment option in supplying uncertain operation environments.     

Optimal Control of Replenishment and Substitution in an Inventory System with Nonstationary Batch Demand

We study an inventory system in which a supplier supplies demand using two mutually substitutable products over a selling season of T periods, with a single replenishment opportunity at the beginning of the season. As the season starts, customer orders arrive in each period, for either type of products, following a nonstationary Poisson process with random batch sizes. The substitution model we consider combines the usual supplier‐driven and customer‐driven schemes, in that the supplier may choose to offer substitution, at a discount price, or may choose not to; whereas the customer may or may not accept the substitution when it is offered. The supplier's decisions are the supply and substitution rules in each period throughout the season, and the replenishment quantities for both products at the beginning of the season. With a stochastic dynamic programming formulation, we first prove the concavity of the value function, which facilitates the solution to the optimal replenishment quantities. We then show that the optimal substitution follows a threshold rule, and establish the monotonicity of the thresholds over time and with respect to key cost parameters. We also propose a heuristic exhaustive policy, and illustrate its performance through numerical examples.     

Optimal ordering and pricing decisions for a target oriented newsvendor

This paper is the first to study pricing and target oriented decision making together in the newsvendor model. Specifically, this paper studies a newsvendor who decides on order quantity and selling price to maximize the probability of achieving both profit and revenue targets simultaneously. First, it is shown that the probability of a newsvendor achieving both targets depends critically on the relative magnitudes of the profit margin and the ratio between the profit target and the revenue target. Second, the closed-form expressions of the optimal order quantity, the optimal selling price, and the maximal profit and revenue probability are obtained. It is shown that if the product has greater price elasticity, the best strategy is always to price lower and order more.     

Transfer of risk in the newsvendor model with discrete demand

In this paper we consider the transfer of risk in a newsvendor model with discrete demand. We view the newsvendor model as a leader/follower problem where the manufacturer (leader) decides the wholesale price and the retailer (follower) decides the quantity ordered. Taking a Pareto-optimal contract as a starting point, the manufacturer wishes to design a real option contract to enhance profits. A new real option contract is said to be feasible if both parties' expected profit is at least as great as in the original contract. When demand is discrete, there are usually infinite feasible contracts that yield maximum expected profits to the manufacturer. In the paper we show that either all, some or none of these real option contracts offer an improved position for the retailer.     

Accurate Response with Refurbished Consumer Returns

Centering around anticipative and reactive capabilities of firms, accurate response is an important supply‐side strategy to deal with demand uncertainty. Clearly, the structure of the possible reaction will crucially influence the optimal anticipative decision making. In this article, we extend the existing literature in this area by including a new reactive capability, namely the utilization of refurbished consumer returns from early sales to react to demand later in the selling season. Because consumer returns depend on previous sales, there is also a direct link to the anticipative supply decision. We capture this effect in a newsvendor‐type model and provide both analytical and numerical insights into the optimal anticipative and reactive decisions as well as the value of refurbishing in terms of the retailer's expected profitability.     

CAPACITATED REMANUFACTURING WITH SERVICE LEVEL CONSTRAINTS*

This research examines production planning and control for a remanufacturer that can sell returned items on a graded as‐is basis or remanufacture the returned items. Using a GI/G/1 queuing network, we model the firms decision to remanufacture an optimal product mix over the long run that maximizes profits while maintaining a desired service level. We further use simulation to explore dispatching heuristics that can be used at the shop‐floor level to achieve the desired optimal product mix, while meeting the service level constraint. Our research is grounded in actual practice and the results provide key insights into the decision‐making process required to maximize profits and minimize average flow times for remanufactured products.     

运输成本对批量敏感时的供应链批量协调策略比较研究

以一个多周期、随机客户需求和单位产品运输成本对批量敏感的供应链为研究对象,建立了由生产商负责产品运输时,供应链分散决策情形下的最佳批量模型,并提出了基于批量折扣和改由批发商负责产品运输的供应链批量协调策略.研究结果表明:当由生产商负责产品运输时,单位产品运输成本对批量越不敏感,生产商的最佳生产批量越小,与批发商要求的短周期、小批量订货越接近;如果改由批发商负责产品运输,批发商的最佳订货批量更接近于生产商的最佳生产批量.最后,通过数例分析发现,对生产商来讲,当单位产品运输成本对批量不太敏感时,批量折扣政策优于改由批发商负责产品运输的策略,但当单位产品运输成本对批量较敏感时,后者优于前者.