Managing Clearance Sales in the Presence of Strategic Customers

We study the effect of strategic customer behavior on pricing and rationing decisions of a firm selling a single product over two periods. The seller may limit the availability of the product (that is, ration) in the second (clearance) period. Some customers are strategic and respond to the firm's decisions by timing their purchases. When capacity is nonconstraining and the seller has pricing flexibility, we show that rationing in the clearance period cannot improve revenue. However, when prices are fixed in advance, rationing can improve revenue. In the latter case, we conduct a detailed analysis for linear and exponential demand curves and derive explicit expressions for optimal rationing levels. We find that the policy of doing the better of not restricting availability at the clearance price or not offering the product at the clearance price is typically near optimal. Our analysis also suggests that rationing—although sometimes offering considerable benefit over allowing unrestricted availability in the clearance period—may allow the seller to obtain only a small fraction of the optimal revenue when the prices are chosen optimally without rationing. We extend the analysis to cases where the capacity is constraining and obtain similar results.     

Revenue Management with End‐of‐Period Discounts in the Presence of Customer Learning

Consider a firm that sells identical products over a series of selling periods (e.g., weekly all‐inclusive vacations at the same resort). To stimulate demand and enhance revenue, in some periods, the firm may choose to offer a part of its available inventory at a discount. As customers learn to expect such discounts, a fraction may wait rather than purchase at a regular price. A problem the firm faces is how to incorporate this waiting and learning into its revenue management decisions. To address this problem we summarize two types of learning behaviors and propose a general model that allows for both stochastic consumer demand and stochastic waiting. For the case with two customer classes, we develop a novel solution approach to the resulting dynamic program. We then examine two simplified models, where either the demand or the waiting behavior are deterministic, and present the solution in a closed form. We extend the model to incorporate three customer classes and discuss the effects of overselling the capacity and bumping customers. Through numerical simulations we study the value of offering end‐of‐period deals optimally and analyze how this value changes under different consumer behavior and demand scenarios.     

Strategic Capacity Management When Customers Have Boundedly Rational Expectations

In retailing industries, such as apparel, sporting goods, customer electronics, and appliances, many firms deploy sophisticated modeling and optimization software to conduct dynamic pricing in response to uncertain and fluctuating market conditions. However, the possibility of markdown pricing creates an incentive for customers to strategize over the timing of their purchases. How should a retailing firm optimally account for customer behavior when making its pricing and stocking/capacity decisions? For example, is it optimal for a firm to create rationing risk by deliberately under stocking products? In this study, we develop a stylized modeling framework to answer these questions. In our model, customers strategize over the timing of their purchases. However, customers have boundedly rational expectations in the sense of anecdotal reasoning about the firm's fill rate, i.e., they have to rely on anecdotes, past experiences, or word‐of‐mouth to infer the firm's fill rate. In our modeling framework, we distinguish two settings: (i) capacity commitment, where the firm commits to its capacity level in the long run, or (ii) the firm dynamically changes it in each season. For both settings, within the simplest form of anecdotal reasoning, we prove that strategic capacity rationing is not optimal independent of customer risk preferences. Then, using a general form of anecdotal reasoning, we provide sufficient conditions for capacity rationing to be optimal for both settings, respectively. We show that the result of strategic capacity rationing being suboptimal is fairly robust to different valuation distributions and utility functions, heterogeneous sample size, and price optimization.     

Market segmentation: an integrated framework

Contrary to the narrow, demand-oriented approach to market segmentation taken in much of the marketing and planning literature, this article illustrates a broader, integrated framework which includes both the demand and supply sides of the competitive equation. The author argues that starting with ‘product’ characteristics is both an easier and more actionable way of segmenting markets than the traditional marketing approach that typically begins with the customer or ‘people’ characteristics. This approach can be employed by a business to make decisions about entering a market segment, differentiating a brand from its competition, positioning it in the market and communicating its quality to the customers. Customers, too, generally rely on product characteristics to perceive and evaluate the quality claims made by different competitors. Thus, the article bridges an important gap between strategy formulation and strategy implementation: an area often neglected in the strategy literature. The proposed approach focuses not only on customer benefits or needs, but also on the resources necessary to satisfy them and demonstrates this with examples from Apple, Church & Dwight and many other companies. To show a practical application, the article presents a price-quality-benefit segmentation profile of the US toothpaste market which revealed three strategic groups.     

Customer Learning Processes,Strategy Selection,and Performance in Business‐to‐Business Service Firms*

Learning about customers takes place through relevant dialogues with those customers, also known as customer relationship management (CRM). As relationships develop, information about the customer is gathered in the firm's customer information systems (CIS): the content, processes, and assets associated with gathering and moving customer information throughout the firm. This research develops a measure of CIS management capabilities based on learning organization theory and measured by the ability to get, store, move, and use information throughout the business unit. This measure is then used to analyze customer learning processes and associated performance in the context of marketing strategic decision making. This study of 209 business services firms finds that generic marketing strategy positioning (low‐cost and differentiation) and the marketing tactics of personalization and customization are related to CIS development. Customer information systems development in turn is associated with higher levels of customer‐based performance, which in turn is associated with increased business growth. Since the strongest association with customer‐based performance is strategy selection, the long‐term benefits of the knowledge gained from the CIS may be in the ability to assist in measuring customer‐based performance, rather than in the ability to immediately contribute to performance. Finally, for these firms, customization and personalization are not directly associated with performance and thus may not be necessary to support every firm's marketing strategy.     

需求学习下考虑顾客策略行为的供应链决策

顾客策略行为对企业的经营绩效带来了巨大的负面影响, 本文基于供应链背景, 探讨需求学习应对顾客策略行为的作用与价值。构建了由单一制造商、单一零售商和一组顾客群组成的两周期分散式供应链系统的博弈模型, 将顾客划分为短视型和策略型两种类型。采用数理模型和数值分析, 研究了需求学习对于供应链的定价决策、订货决策及整体绩效的影响, 得到如下主要研究结论:第一, 无论面对何种类型的顾客, 零售商均偏好需求学习获取需求更新信息;第二, 面对短视顾客时, 制造商偏好于不获取更新信息, 而当顾客为策略型时, 制造商偏好于获取更新信息;第三, 需求学习有助于提高零售商和供应链系统的利润, 特别当面对策略型顾客时, 需求学习带来的利润增值更大。以上研究结论表明, 需求学习可以有效地缓解顾客策略行为的负面影响, 提高企业的运营绩效。     

Pricing and Capacity Rationing with Customer Disappointment Aversion

Customers are averse to disappointment that arises when economic outcomes fall short of expectations. In this study, we study a two‐period model in which the firm may create rationing in either period. In the anticipation of possible disappointment due to stock‐outs, strategic customers decide when to purchase and the firm determines the prices and rationing levels in each period. We explore the impact of disappointment aversion on customers' strategic purchasing behavior and the firm's pricing and rationing decisions. Without disappointment aversion, it is optimal for the firm to adopt a uniform pricing policy without rationing. However, when strategic customers are averse to disappointment, a firm may be able to increase profits with an appropriate level of rationing. We analyze both the mark‐up and mark‐down policies. We show that, in a mark‐down scenario, the firm always benefits from disappointment aversion behavior by using an appropriate level of rationing in a low‐price period. However, in a mark‐up scenario, whether it is beneficial for the firm to induce disappointment aversion behavior depends on how customers frame payoffs in different periods when forming utilities. Particularly, when customers compartmentalize payoffs in different periods to form utilities, the firm should not induce disappointment aversion behavior.     

电子市场中时间价格敏感需求下的交货期定价决策

电子市场中,如何通过交货期报价来增大需求、提高收益,对于网络营销企业来说是至关重要的.本文假定在一个包含网络营销企业与其客户的运作系统中,需求同时对价格与时间都敏感的条件下,以最优化自身收益为目标、以满足必须达到规定的服务水平为主要约束条件,构建了交货期定价决策模型.通过数值算例,探讨了在电子市场中消费者为价格敏感或交货期敏感时,网络营销企业的最优定价策略.上述结论可以为网络营销企业在电子市场中的定价决策提供有益的指导.     

Two Backorder Compensation Mechanisms in Inventory Systems with Impatient Customers

We study a compensation mechanism design problem with customer‐choice behavior in a continuous review setting where the production and demand processes are stochastic. When a stockout occurs, the firm controls backorders on the basis of certain compensation policies. Customers make decisions to maximize their utility, which is decreasing in the price, the waiting time, and the customer's impatience factor. We assume that the impatience factor is private information held by the customer only. Two compensation mechanisms are designed to control backorders, namely uniform compensation and priority auction with an admission price. Under uniform compensation, the firm offers the same discount to all customers, whereas under auction compensation, priority is granted according to the customers' bid prices. We obtain the optimal stockout price and base stock level under each mechanism, and analyze the properties of the respective optimal policies. Assuming linear waiting costs with uniformly distributed impatience factor, we find that the auction mechanism (1) maintains a lower base stock level and results in greater profit and (2) benefits customers with relatively lower or higher impatience factors, but customers with a medium impatience factor may be rendered worse off. We further show that both compensation mechanisms are suitable for products with a high unit profit, a high lost sales penalty cost, and a high holding cost.     

Dynamic Customer Acquisition and Retention Management

In consulting, finance, and other service industries, customers represent a revenue stream, and must be acquired and retained over time. In this paper, we study the resource allocation problem of a profit maximizing service firm that dynamically allocates its resources toward acquiring new clients and retaining unsatisfied existing ones. The interaction between acquisition and retention in our model is reflected in the cash constraint on total expected spending on acquisition and retention in each period. We formulate this problem as a dynamic program in which the firm makes decisions in both acquisition and retention after observing the current size of its customer base and receiving information about customers in danger of attrition, and we characterize the structure of the optimal acquisition and retention strategy. We show that when the firm's customer base size is relatively low, the firm should spend heavily on acquisition and try to retain every unhappy customer. However, as its customer base grows, the firm should gradually shift its emphasis from acquisition to retention, and it should also aim to strike a balance between acquisition and retention while spending its available resources. Finally, when the customer base is large enough, it may be optimal for the firm to begin spending less in both acquisition and retention. We also extend our analysis to situations where acquisition or retention success rate, as a function of resources allocation, is uncertain and show that the optimal acquisition and retention policy can be surprisingly complex. However, we develop an effective heuristic for that case. This paper aims to provide service managers some analytical principles and effective guidelines on resource allocation between these two significant activities based on their firm's customer base size.     

DEMAND MANAGEMENT: THE EVALUATION OF PRICE AND DUE DATE NEGOTIATION STRATEGIES USING SIMULATION

The research considers the problem of demand management in a firm where the firm's historical delivery service level reputation influences the number of quotation requests from its potential customers. Customers have a maximum and the firm has a minimum net price to due date tradeoff curve for each job. The demand management function bargains with the customer over price and promised due date. Bargaining finishes either with an agreed price and delivery date or with the customer refusing the firm's bid and placing the order elsewhere. The firm's objective is to maximize its long-term net revenue. The firm's demand management negotiation strategy guides this bidding process. The research demonstrates the use of simulation to test different demand management bidding and negotiation strategies for different market and firm scenarios. The demonstration uses 16 scenarios to test the different demand management negotiation strategies with a model of a classical job shop in a classical market. The investigation examines finite scheduling-based due date estimation methods, as well as the more traditional parameter-based methods. This demonstration shows that it is possible to test different bidding policies, using a simulation model of a firm and its customers, and to obtain usable results.     

通过顾客关系服务化来强化顾客价值过程--顾客关系时代的营销新命题

本文建立在这样一个全新的观念基础之上,即营销资源和活动必须与企业所面临的目标顾客相互一致,同时,顾客价值不是由制造商或服务提供者创造的,而是由顾客在其价值创造过程中创造的.企业的资源、流程和能力并不是企业的生产(如产品)、管理(如网站)、财务(如结算)、法律(如顾客申述的处理)及其它活动过程的结果,而应当被视为顾客价值创造过程的投入要素.因此,供应商的作用是通过向顾客提供恰当的资源要素,如产品、服务、信息、服务补救、个性化关怀等来支持顾客价值创造过程,并与顾客资源形成互动,惟此,顾客才会感知到价值被创造出来.要以此方式运营,企业必须将自己看作是服务企业,而且真正地为顾客服务.为强化顾客价值的生成,企业必须将其客户关系中的所有要素"服务化"(Servicizing),无论是与制造或服务相关的,还是管理、财务或者法律等常规活动.这些常规活动通常属于"隐性服务"(HiddenService),它们在价值创造中的潜力没有得到应有重视.相反,这些要素对顾客价值的生成过程常常起到破坏而不是支撑作用."服务化"意味着要将所有与顾客关系相关的要素,不管它们的类型和特性如何,转化为顾客价值创造过程中的投入要素.最后,本文还探讨了在顾客关系管理时代,如何配置企业营销资源及营销规划等问题.     

Market Impact on IT Security Spending

Traditionally, IT security investment decisions are made in isolation. However, as firms that compete for customers in an industry are closely interlinked, a macro perspective is needed in analyzing these decisions. We utilize the notions of direct‐ and cross‐risk elasticity to describe the customer response to adverse IT security events in the firm and competitor, respectively, thus allowing us to analyze optimal security investment decisions. Examining both symmetric and asymmetric duopoly cases using a continuous‐time Markov chain (CTMC) model, we demonstrate that optimal IT security spending, expected firm profits and willingness of firms to cooperate on security improvements are highly dependent on the nature of customer response to adverse events. We also examine the investment problem when security attacks on different firms are correlated.     

消费者预算约束对推荐奖励策略的影响研究

在社会化商务研究中,大多数研究考虑消费者的购买意愿对企业决策的影响,很少有文献探讨消费者的资金不足时对企业开展在线营销活动效果的影响.本文讨论了当消费者消费预算有约束情况下,在线企业采用推荐奖励策略对营销效果的影响.首先建立了销售企业、已有顾客、已有顾客的朋友(潜在顾客)三者之间的博弈模型,其中假设朋友的预算是私有信息,企业和已有顾客不知道该信息.通过对博弈模型的求解,发现当朋友存在预算约束时,企业采用高价格、高奖励的推荐奖励策略并不总是有效;当潜在顾客(朋友)对产品的购买意愿处于中间状态时,只有其预算偏高时,企业采取推荐奖励策略才能获得更高的利润.此外,在基本推荐奖励策略的基础上,拓展企业提供融资策略以及考虑朋友对推荐奖励反感程度的情况.研究发现,融资成本较高时,融资和奖励之间存在相互替代效果,但融资成本较低时,与融资效果与消费者的购买意愿程度相关;当潜在消费者对推荐策略存在反感时,企业仍存在一定的赢利空间.研究结果对在线企业开展推荐奖励策略的实践具有参考价值.     

竞争环境下客户服务投入对企业利润影响的均衡分析

客户服务投入是企业吸引新顾客和维持现有顾客的重要手段之一。然而,服务投入究竟是否能给企业带来价值？对于这一问题,业界和学界都没有明确的答案。本文通过建模的方法研究在竞争的市场环境下,固有的市场因素对客户服务投入价值的影响。研究发现,服务竞争的市场均衡结构是两家厂商都投入客户服务。服务投入给企业带来的价值随着产品差异度的提高而提高,随着厂商自身市场份额的增加而增加。即,在产品差异度高的市场,服务投入更容易给企业带来价值。而在集中度高的市场,服务投入更容易给市场份额大的企业带来价值。     

The Production of Several Items in a Single Facility with Linearly Changing Demand Rates

In this paper we extend the ELSP model to allow for linearly changing demand rates over a fixed planning horizon. This extension of the ELSP research provides a model that can be used in coordinating the production and marketing planning activities in a firm. The model allows the user to evaluate the impact of changes in product demand on production costs and customer service. We solve the model using a standard nonlinear programming package (MINOS) and show through examples based on actual production data how the model can be used to support coordinated production and marketing planning.     

需求与提前期不确定下的生产—销售协调

考虑一个按订单生产企业,其需求同时取决于价格和提前期。在企业内部,销售部门进行定价决策,生产部门则进行订货和提前期的决策。文中将生产及销售部门之间的相互作用表示成一个Nash博弈模型,并证明了纯策略均衡的存在性和唯一性。此外,提出了一个能够协调生产和销售部门决策的机制。最后,通过数值分析讨论了各参数对部门均衡决策的影响以及企业不需要运用协调机制的条件。     

On service degrade at a discount: Capacity, demand pooling, and optimal discounting

In this paper we study the capacity investment decisions and operational strategies of a firm providing two-class services facing uncertain demands. The capacity decisions of the resources are made before demands are observed. Each service can be implemented by its corresponding resource. Should a mismatch between the capacity and the actual demand for the services arise, the low-class resource can be used as a substitute for the high-class service. We introduce an operational strategy called degrade-at-a-discount, where a price discount is offered to motivate customers to accept a lower class service when their original choice is out of capacity. By formulating the problem as a one-period, two-stage stochastic problem, we analyze how to set up the optimal capacity and the optimal discount. We also conduct a comprehensive numerical study to show the benefits of the degrade-at-a-discount strategy.     

基于消费者隐性需求的营销模式研究策略

消费者隐性需求的相关理论和实践研究逐渐受到国内外学者的重视,这对于营销理论的再造和营销学的演进具有一定的理论价值。本文从营销范式的演进规律归纳得出,营销范式的转换归根结底源于隐性需求的开发。在此基础上,对传统营销模式及营销组合对隐性需求研究的普适性进行了检验,并探讨了基于隐性需求的4Vs营销模式及其现实意义。     

Demand and Production Management with Uniform Guaranteed Lead Time

Recently, innovation‐oriented firms have been competing along dimensions other than price, lead time being one such dimension. Increasingly, customers are favoring lead time guarantees as a means to hedge supply chain risks. For a make‐to‐order environment, we explicitly model the impact of a lead time guarantee on customer demands and production planning. We study how a firm can integrate demand and production decisions to optimize expected profits by quoting a uniform guaranteed maximum lead time to all customers. Our analysis highlights the increasing importance of lead time for customers, as well as the tradeoffs in achieving a proper balance between revenue and cost drivers associated with lead‐time guarantees. We show that the optimal lead time has a closed‐form solution with a newsvendor‐like structure. We prove comparative statics results for the change in optimal lead time with changes in capacity and cost parameters and illustrate the insights using numerical experimentation.