Optimal Uniform Pricing Strategy of a Service Firm When Facing Two Classes of Customers

When facing heterogeneous customers, how should a service firm make its pricing decision to maximize revenue? If discrimination is allowed, then priority schemes and differentiated pricing are often used to achieve that. In many applications, however, the firm cannot or is not allowed to set discriminatory prices, for example, list price in retail stores, online shopping, and gas stations; thus a uniform price must be applied to all customers. This study addresses the optimal uniform pricing problem of a service firm using a queueing system with two classes of customers. Our result shows that the potential pool of customers plays a central role in the firm's optimal decision. Depending on the range of system parameters, which are determined explicitly by the primitive data, the firm's optimal strategy may choose to serve only one class of customers, a subset of a class of customers, or a combination of different classes of customers. In addition, the optimal price is in general not monotonic with respect to the potential market sizes because their changes may lead to a major shift in the firm's decision on which customer class to serve. However, unless such a shift occurs, the optimal price is weakly decreasing in the potential market sizes.     

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.     

Trade-off between quoted lead time and price

In a make-to-order environment, lead time and price can play a crucial role in determining the financial success of a firm. Their importance increases when demand is sensitive to the quoted lead time and price. A model is presented which uses the quoted lead time and price as a mechanism to determine the optimal demand level. The relationships between the model parameters and their impacts on the firm's profit is also analysed. In addition, the effect of the number of job requests, and the mean processing time are examined. Based on the results presented in this paper, there is clear indication that the firm's profit is sensitive to the inventory holding rate, and that the inventory holding cost component is redundant in the presence of a tardiness cost component.     

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.     

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.     

Coordinating Sales and Raw Material Discounts in a Global Supply Chain

In this paper, the supplier of a key component to a global manufacturer offers a one‐time price discount; we study the firm's optimal response to the discount under two different strategies. In the first strategy, the firm does not pass along the discount to its customers (sales subsidiaries); the firm simply coordinates purchasing and production among the different factories to take advantage of this one‐time price discount. In the second strategy, the firm offers price discounts for its most profitable products in different sales subsidiaries to increase their demand. We carried out experiments for the two strategies based on a mathematical programming model, built around Toshiba's global notebook supply chain. Model constraints include, among others, material constraints, bill‐of‐materials, capacity and transportation constraints, minimum lot size constraints, and a constraint on minimum fill rate (service level constraint). Unlike most models of this type in the literature, which define variables in terms of single arc flows, we employ path variables, which allow for direct identification and manipulation of profitable and non‐profitable products.     

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.     

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.     

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。     

Selling Finite Capacity in Bulks*

We consider a firm that owns a limited capacity for the delivery of services or for the production of customized products. Potential buyers specify the amount of capacity they will require for the execution of their intended services, goods or projects. Based on the size of the requirement, the firm makes a bid while being challenged in various ways: (1) it only knows the underlying probability function from which its customers’ reservation prices are drawn, (2) arrival of additional future requests is stochastic, and, (3) the firm knows in advance neither the magnitude of these potential requests nor the buyer's reservation price. The firm aims to maximize its expected profit by choosing its pricing mechanism. The fact that capacity is demanded in varying amounts distinguishes this problem from most available literature in which standard sizes are sold or partial fulfillment and displacement are permitted. Lacking such allowances presents a new challenge to the firm as in conjunction with pricing it should also address the issue of various sizes requests’ compatibility to achieve optimal utilization of its capacity in order to maximize expected profit. In this article, we consider two approaches of handling this problem: myopic and foresighted. We formulate and analyze the problem to obtain the firm's optimal bidding decisions as well as managerial insight about the optimal bid level and its important role in coordinating buyers’ requests. Furthermore, due to this role, pricing patterns in this environment are different than those in standard unit sales.     

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.     

A Comparison of Unconstraining Methods to Improve Revenue Management Systems

Asuccessful revenue management system requires accurate demand forecasts for each customer segment. The forecasts are used to set booking limits for lower value customers to ensure an adequate supply for higher value customers. The very use of booking limits, however, constrains the historical demand data needed for an accurate forecast. Ignoring this interaction leads to substantial penalties in a firm's potential revenues. We review existing unconstraining methods and propose a new method that includes some attractive properties not found in the existing methods. We evaluate several of the common unconstraining methods against our proposed method by testing them on intentionally constrained simulated data. Results indicate our proposed method outperforms other methods in two of three data sets. We also test the revenue impact of our proposed method, expectation maximization (EM), and “no unconstraining” on actual booking data from a hotel/casino. We show that performance varies with the initial starting protection limits and a lack of unconstraining leads to significant revenue losses.     

Entry Deterrence of Capacitated Competition Using Price and Non‐Price Strategies

We analyze the role of pricing and branding in an incumbent firm's decision when facing competition from an entrant firm with limited capacity. We do so by studying two price competition models (Stackelberg and Nash), where we consider the incumbent's entry‐deterrence pricing strategy based on a potential entrant's capacity size. In an extension, we also study a branding model, where the incumbent firm, in addition to pricing, can also invest in influencing market preference for its product. With these models, we study conditions under which the incumbent firm may block the entrant (i.e., prevent entry without any market actions), deter the entrant (i.e., stop entry with suitable market actions) or accommodate the entrant (i.e., allow entry and compete), and how the entrant will allocate its limited capacity across its own and the new market, if entry occurs. We also study the timing difference between the two different dynamics of the price competition models and find that the incumbent's first‐mover advantage benefits both the incumbent and the entrant. Interestingly, the entrant firm's profits are not monotonically increasing in its capacity even when it is costless to build capacity. In the branding model, we show that in some cases, the incumbent may even increase its price and successfully deter entry by investing in consumer's preference for its product. Finally, we incorporate demand uncertainty into our model and show that the incumbent benefits from demand uncertainty while the entrant may be worse off depending on the magnitude of demand uncertainty and its capacity.     

Examining the Firm's Value Creation Process: A Managerial Perspective of the Firm's Value Offering Strategy and Performance

The primary pursuit of any business is to understand what customers value and to create that value for them. While customers are the final arbiter of value, it is the firm's role to explore, interpret and deliver value based on what they believe customers are seeking. Based on this premise we adopt the firm's perspective on value creation to extend both Bowman and Ambrosini's theoretical framework and the work of DeSarbo, Jedidi and Sinha and focus on two issues. The first is the strategic emphasis firms place on the design and delivery of their value offering. The second is the extent the firm's value offering explains performance differentials at the customer‐centric performance level. We present a conceptual model of how firms gain positional advantage via their value offering and the realized outcomes they achieve. We present two approaches to modelling the firm's value offering (type II and type IV models) and articulate the theoretical underpinnings and results for these models. Our results validate the conceptualization of the firm's value offering and suggest that creating superior value offerings enables firms to achieve superiority in customer‐centric performance.     

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.     

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.     

Multichannels Strategy Implementation: The Role of Channel Alignment Capabilities*

A firm's distribution channels represent a key portfolio of resources that can be leveraged for competitive advantage. One approach to this portfolio that has become increasingly important in recent years is multichannel distribution (MCD). While this strategy has important benefits in terms of market coverage and firm performance, the use of multiple channels seriously affects downstream channel roles such as service delivery, as the financial rewards to channel members and the services they offer are separated. A channel member who offers poor or no service can free‐ride on the services offered to the same customer from a different channel. We draw on agency theory to explain these negative consequences. Additionally, the resource‐based view of the firm along with capabilities theory provides two key means of alleviating these consequences: channel tracking capabilities and reward alignment capabilities. The study, conducted in an industry facing serious MCD issues (the outdoor sporting goods industry), used key informant data matched to secondary data. Our results show that managers can reap the performance rewards of MCD strategies while minimizing its negative consequences. In particular, monitoring practices such as frequent site visits and phone contact with customers develop the firm's channel tracking capabilities, allowing managers to better monitor downstream activities. This becomes particularly important as the complexity from having multiple channels increases. Likewise, reward alignment capabilities such as retail price maintenance agreements and cooperative advertising enable the manager to minimize conflict among channel participants by ensuring sufficient profitability for all channel members.     

Supply Diversification with Responsive Pricing

We study sourcing and pricing decisions of a firm with correlated suppliers and a price‐dependent demand. With two suppliers, the insight—cost is the order qualifier while reliability is the order winner—derived in the literature for the case of exogenously determined price and independent suppliers, continues to hold when the suppliers' capacities are correlated. Moreover, a firm orders only from one supplier if the effective purchase cost from him, which includes the imputed cost of his unreliability, is lower than the wholesale price charged by his rival. Otherwise, the firm orders from both. Furthermore, the firm's diversification decision does not depend on the correlation between the two suppliers' random capacities. However, its order quantities do depend on the capacity correlation, and, if the firm's objective function is unimodal, the total order quantity decreases as the capacity correlation increases in the sense of the supermodular order. With more than two suppliers, the insight no longer holds. That is, when ordering from two or more suppliers, one is the lowest‐cost supplier and the others are not selected on the basis of their costs. We conclude the paper by developing a solution algorithm for the firm's optimal diversification problem.     

Product Launches and Buying Frenzies: A Dynamic Perspective

Buying frenzies caused by a firm's intentional undersupplying of a new product are frequently evident in several industries including electronics (cell phones, video games), luxury automobiles, and fashion goods. We develop a dynamic model of buying frenzies that incorporates the firm's manufacturing and sale of a product over time and characterizes the conditions under which inducing such frenzies is an optimal strategy. We find that buying frenzies occur when customers are sufficiently uncertain about their valuations of the product and when they discount the future sufficiently but not excessively. We propose measures of “customer desperation” and of the extent of scarcity to measure the depth and breadth of buying frenzies, respectively. We also demonstrate that such frenzies can have a significantly positive effect on firm profits and partially recover the loss due to non‐commitment to future prices. This study provides managerial insights on how firms can influence market response to a new product through production, pricing, and inventory decisions to induce profitable frenzies.