Service and Price Competition When Customers Are Naive

We consider a system of two service providers each with a separate queue. Customers choose one queue to join upon arrival and can switch between queues in real time before entering service to maximize their spot utility, which is a function of price and queue length. We characterize the steady‐state distribution for queue lengths, and then investigate a two‐stage game in which the two service providers first simultaneously select service rates and then simultaneously charge prices. Our results indicate that neither service provider will have both a faster service and a lower price than its competitor. When price plays a less significant role in customers’ service selection relative to queue length or when the two service providers incur comparable costs for building capacities, they will not engage in price competition. When price plays a significant role and the capacity costs at the service providers sufficiently differ, they will adopt substitutable competition instruments: the lower cost service provider will build a faster service and the higher cost service provider will charge a lower price. Comparing our results to those in the existing literature, we find that the service providers invest in lower service rates, engage in less intense price competition, and earn higher profits, while customers wait in line longer when they are unable to infer service rates and are naive in service selection than when they can infer service rates to make sophisticated choices. The customers’ jockeying behavior further lowers the service providers’ capacity investment and lengthens the customers’ duration of stay.     

End‐of‐Life Inventory Decisions for Consumer Electronics Service Parts

We consider a consumer electronics manufacturer's problem of controlling the inventory of spare parts in the final phase of the service life cycle. The final phase starts when the part production is terminated and continues until the last service contract or warranty period expires. Placing final orders for service parts is considered to be a popular tactic to satisfy demand during this period and to mitigate the effect of part obsolescence at the end of the service life cycle. Previous research focuses on repairing defective products by replacing the defective parts with properly functioning spare ones. However, for consumer electronic products there typically is considerable price erosion while repair costs stay steady over time. As a consequence, there might be a point in time at which the unit price of the product drops below the repair costs. If so, it is more cost effective to adopt an alternative policy to meet service demands toward the end of the final phase, such as offering customers a new product of the similar type or a discount on a next generation product. This study examines the cost trade‐offs of implementing alternative policies for the repair policy and develops an exact expression for the expected total cost function. Using this expression, the optimal final order quantity and switching time from repair to an alternative policy can be determined simultaneously. Numerical analysis of a real world case sheds light on the cost benefits of these policies and also yields insights into the quantitative importance of the various cost parameters.     

Quality‐Speed Competition in Customer‐Intensive Services with Boundedly Rational Customers

We consider a system in which two competing servers provide customer‐intensive services and the service reward is affected by the length of service time. The customers are boundedly rational and choose their service providers according to a logit model. We demonstrate that the service provider revenue function is unimodal in the service rate, its decision variable, and show that the service rate competition has a unique and stable equilibrium. We then study the price decision under three scenarios with the price determined by a revenue‐maximizing firm, a welfare‐maximizing social planner, or two servers in competition. We find that the socially optimal price, subject to the requirement that the customer actual utility must be non‐negative, is always lower than the competition equilibrium price which, in turn, is lower than the revenue‐maximizing monopoly price. However, if the customer actual utility is allowed to be negative in social optimization, the socially optimal price can be higher than the other two prices in a large market.     

A Service Provider's Elicitation of Its Customers’ Demand Distributions by a Price Mechanism

In a service environment a service provider needs to determine the amount and kinds of capacity to meet customers’ needs over many periods. To make good decisions, she needs to know the probability distribution of her customers’ demand in each period. We study a situation in which customers’ demand for a given service is random in each period, but inelastic, or modeled well by this assumption, and cannot be delayed to the next period. This article presents a mechanism that allows a service provider to learn the distribution of a customer's demand by offering him a set of contracts through which he can partially prepay for future service for a reduced cost for units of service based on anticipated needs. We describe the form of a set of contracts that will cause the customer to reveal his demand distribution as he minimizes his expected costs. To justify the effort of organizing and offering contracts, we present an application that demonstrates the cost savings to the service provider with better capacity planning using the truthfully elicited distribution.     

Dynamic Pricing in e‐Services under Demand Uncertainty

High volatility of the e‐services market, due to increasing competition, low life cycle of products, and easy availability of information about competing service offerings to customers, makes the demand for service offerings quite uncertain. Revenue management in such markets calls for real‐time techniques to learn the demand and its dependence on both the price and the service level associated with the service offering. We assume firms reply on exploratory approaches for demand estimation, in which firms experiment with different service offerings in order to simultaneously learn the demand while doing business. Such exploration and learning process can be costly without supervision. As reported by Rothschild (Journal of Economic Theory, 9 185‐202, 1974), traditional Bayesian dynamic control approaches may conclude with suboptimal offerings. We propose a novel demand learning approach that is guaranteed to converge to the optimal offering. The approach combines simulated annealing algorithm with Bayesian learning. We further present intelligent techniques that adaptively reduce the effort of exploration on suboptimal service offerings so as to improve the long‐run average profit.     

The Impact of Contracts and Competition on Upstream Innovation in a Supply Chain

We consider a supply chain with an upstream supplier who invests in innovation and a downstream manufacturer who sells to consumers. We study the impact of supply chain contracts with endogenous upstream innovation, focusing on three different contract scenarios: (i) a wholesale price contract, (ii) a quality‐dependent wholesale price contract, and (iii) a revenue‐sharing contract. We confirm that the revenue‐sharing contract can coordinate supply chain decisions including the innovation investment, whereas the other two contracts may result in underinvestment in innovation. However, the downstream manufacturer does not always prefer the revenue‐sharing contract; the manufacturer's profit can be higher with a quality‐dependent wholesale price contract than with a revenue‐sharing contract, specifically when the upstream supplier's innovation cost is low. We then extend our model to incorporate upstream competition between suppliers. By inviting upstream competition, with the wholesale price contract, the manufacturer can increase his profit substantially. Furthermore, under upstream competition, the revenue‐sharing contract coordinates the supply chain, and results in an optimal contract form for the manufacturer when suppliers are symmetric. We also analyze the case of complementary components suppliers, and show that most of our results are robust.     

ASSESSING SOCIAL COSTS OF INEFFICIENT PROCUREMENT DESIGN

This paper considers the social costs implied by inefficient allocation of contracts in a first‐price, sealed‐bid procurement auction with asymmetric bidders. We adopt a constrained (piecewise linear) strategy equilibrium concept and estimate the structural parameters of the bidders' distribution of costs. We estimate social costs defined as the predicted cost difference between the winning firm and the most efficient bidding firm. We also compare the expected procurement costs under two different auction formats. The data is collected from procurement auctions of road painting in Sweden during 1993–1999. The results indicate that the social costs of inefficient contract allocation is about 2% of total potential production cost and that an efficient second‐price auction would lower the expected procurement cost by 2.5%. (JEL: D44, H57, C15)     

The Role of Contract Negotiation and Industry Structure in Production Outsourcing

Despite the spread of cost‐driven outsourcing practices, academic research cautions that suppliers' cost advantage may weaken manufacturers' bargaining positions in negotiating outsourcing agreements, thereby hurting their profitability. In this study, we attempt to further understand the strategic impact of low‐cost outsourcing on manufacturers' profitability by investigating the contractual form of outsourcing agreements and the industry structure of the upstream supply market. We consider a two‐tier supply chain system, consisting of two competing manufacturers, who have the option to produce in‐house or to outsource to an upstream supplier with lower cost. To reach an outsourcing agreement, each manufacturer engages in bilateral negotiation with her supplier, who may be an exclusive supplier or a common supplier serving both manufacturers. Our analysis shows that wholesale‐price contracts always mitigate the competition between manufacturers regardless of whether they compete with price or quantity. In contrast, two‐part tariffs intensify the competition when the manufacturers compete with quantity, but soften it when they compete with price. As a result, when outsourcing with two‐part tariffs, the manufacturers may earn lower profits than they would from in‐house production, although the suppliers are more cost efficient. This suggests that managers have to be wary about the downside of using coordinating contracts such as two‐part tariffs when pursuing low‐cost outsourcing strategies. Our analysis also sheds some light on the profitability of using an exclusive supplier for outsourcing. When outsourcing with wholesale‐price contracts, the competing manufacturers are better off outsourcing to an exclusive supplier. However, when outsourcing with two‐part tariffs, the manufacturers may earn higher profits by outsourcing to a common supplier than to an exclusive one when the manufacturers' bargaining power is sufficiently strong (weak) under quantity (price) competition.     

Coordinating Service‐Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case‐Based Decision Theory*

The subject of this article is the simultaneous choice of product price and manufacturing capacity if demand is stochastic and service‐level sensitive. In this setting, capacity as well as price have an impact on demand because several aspects of service level depend on capacity. For example, delivery time will be reduced if capacity is increased given a constant demand rate. We illustrate the relationship between service level, capacity, and demand reaction by a stylized application problem from the after‐sales services industry. The reaction of customers to variations in service level and price is represented by a kinked price‐demand‐rate function. We first derive the optimal price‐capacity combination for the resulting decision problem under full information. Subsequently, we focus on a decision maker (DM) who lacks complete knowledge of the demand function. Hence the DM is unable to anticipate the service level and consequently cannot identify the optimal solution. However, the DM will acquire additional information during the sales process and use it in subsequent revisions of the price‐capacity decision. Thus, this decision making is adaptive and based on experience. In contrast to the literature, which assumes certain repetitive procedures somewhat ad hoc, we develop an adaptive decision process based on case‐based decision theory (CBDT) for the price‐capacity problem. Finally, we show that a CBDT DM in our setting eventually finds the optimal solution, if the DM sets the price based on absorption costs and adequately adjusts the capacity with respect to the observed demand.     

Are Self‐Service Customers Satisfied or Stuck?

This paper investigates the impact of self‐service technology (SST) usage on customer satisfaction and retention. Specifically, we disentangle the distinct effects of satisfaction and switching costs as drivers of retention among self‐service customers. Our empirical analysis examines 26,924 multi‐channel customers of a nationwide retail bank. We track each customer's channel usage, overall satisfaction, and retention over a 1‐year period. We find that, relative to face‐to‐face service, customers who use self‐service channels for a greater proportion of their transactions are either no more satisfied, or less satisfied with the service they receive, depending on the channel. However, we also find that these same customers are predictably less likely to defect to a competitor if they are heavily reliant on self‐service channels characterized by high switching costs. Through a mediation model, we demonstrate that, when self‐service usage promotes retention, it does so in a way that is consistent with switching costs. As a robustness check, we examine the behavior of channel enthusiasts, who concentrate transactions among specific channels. Relative to more diversified customers, we find that self‐service enthusiasts in low switching cost channels defect with greater frequency, while self‐service enthusiasts in high switching cost channels are retained with greater frequency.     

Pareto‐Improving Contracts for Express Package Delivery Services

We address the problem of an express package delivery company in structuring a long‐term customer contract whose terms may include prices that differ by day‐of‐week and by speed‐of‐service. The company traditionally offered speed‐of‐service pricing to its customers, but without day‐of‐week differentiation, resulting in customer demands with considerable day‐of‐week seasonality. The package delivery company hoped that using day‐of‐week and speed‐of‐service price differentiation for contract customers would induce these customers to adjust their demands to become counter‐cyclical to the non‐contract demand. Although this usually cannot be achieved by pricing alone, we devise an approach that utilizes day‐of‐week and speed‐of‐service pricing as an element of a Pareto‐improving contract. The contract provides the lowest‐cost arrangement for the package delivery company while ensuring that the customer is at least as well off as he would have been under the existing pricing structure. The contract pricing smoothes the package delivery company's demand and reduces peak requirements for transport capacity. The latter helps to decrease capital costs, which may allow a further price reduction for the customer. We formulate the pricing problem as a biconvex optimization model, and present a methodology for designing the contract and numerical examples that illustrate the achievable savings.     

Lead Time and Price Quotation Mode Selection: Uniform or Differentiated?

Firms in service and make‐to‐order manufacturing industries often quote lead times and prices to customers. We define uniform quotation mode (UQM) as the strategy where a firm offers a single lead time and price quotation, and differentiated quotation mode (DQM) is where a firm offers a menu of lead times and prices for customers to choose from. Both modes are followed in practice. Firms should determine which is more profitable. We classify customers into two groups: lead time sensitive (LS) and price sensitive (PS). LS customers value lead time reduction more than PS customers. We develop mathematical models of both quotation modes and analyze them to determine the most profitable mode under specified situations as well as the best lead time and price quotations within each mode. We find that DQM is dominated by UQM whenever PS customers have positive utilities from UQM or LS customers have positive utilities from DQM. Otherwise, which quotation mode is better depends on multiple factors, such as customer characteristics (including lead time reduction valuation and product valuation of a customer, and the proportion of LS customers) and production characteristics (including the desired service level and service or production cost).     

Dynamic Pricing,Production, and Channel Coordination with Stochastic Learning

We consider a decentralized two‐period supply chain in which a manufacturer produces a product with benefits of cost learning, and sells it through a retailer facing a price‐dependent demand. The manufacturer's second‐period production cost declines linearly in the first‐period production, but with a random learning rate. The manufacturer may or may not have the inventory carryover option. We formulate the resulting problems as two‐period Stackelberg games and obtain their feedback equilibrium solutions explicitly. We then examine the impact of mean learning rate and learning rate variability on the pricing strategies of the channel members, on the manufacturer's production decisions, and on the retailer's procurement decisions. We show that as the mean learning rate or the learning rate variability increases, the traditional double marginalization problem becomes more severe, leading to greater efficiency loss in the channel. We obtain revenue sharing contracts that can coordinate the dynamic supply chain. In particular, when the manufacturer may hold inventory, we identify two major drivers for inventory carryover: market growth and learning rate variability. Finally, we demonstrate the robustness of our results by examining a model in which cost learning takes place continuously.     

Profitability of Service‐Level‐Based Price Differentiation with Inventory Rationing

In this paper, we study the profitability of service‐level‐based price differentiation (SLBPD) in an inventory‐rationing context. SLBPD implies that a company offers several combinations of prices and guaranteed service levels, from which customers self‐select; different customers choose different offerings because they incur different shortage costs if an order is not fulfilled immediately. We develop an analytical model for SLBPD and explore if and when such a service differentiation strategy yields higher profits than a single undifferentiated offering. The results of our analyses suggest that SLBPD is profitable only if a company faces pricing restrictions, e.g., because of competitive pressure or regulatory restrictions. We develop necessary and sufficient conditions under which a specific and relevant form of SLBPD (called “service‐level‐based upselling”) is profitable, and provide an algorithm to compute the optimal parameters of such a policy. Based on this algorithm we carry out numerical analyses that allow us to characterize the profit increment of service‐level‐based upselling. We derive managerial insights into the attractiveness of SLBPD and explain how our basic analytical framework can be extended to account for more complex practical features.     

Combined Pricing and Portfolio Option Procurement

In this paper, we study a single‐product periodic‐review inventory system that faces random and price‐dependent demand. The firm can purchase the product either from option contracts or from the spot market. Different option contracts are offered by a set of suppliers with a two‐part fee structure: a unit reservation cost and a unit exercising cost. The spot market price is random and its realization may affect the subsequent option contract prices. The firm decides the reservation quantity from each supplier and the product selling price at the beginning of each period and the number of options to exercise (inventory replenishment) at the end of the period to maximize the total expected profit over its planning horizon. We show that the optimal inventory replenishment policy is order‐up‐to type with a sequence of decreasing thresholds. We also investigate the optimal option‐reservation policy and the optimal pricing strategy. The optimal reservation quantities and selling price are shown to be both decreasing in the starting inventory level when demand function is additive. Building upon the analytical results, we conduct a numerical study to unveil additional managerial insights. Among other things, we quantify the values of the option contracts and dynamic pricing to the firm and show that they are more significant when the market demand becomes more volatile.     

Motivating Retail Marketing Effort: Optimal Contract Design

We study a distribution channel where a manufacturer relies on a sales agent for selling the product, and for investing in the most appropriate marketing effort. The agent's effort is hard to monitor. In addition, the cost of effort is the agent's private information. These impose challenges to the manufacturer in its endeavor to influence the agent's marketing effort provisions and to allocate profit between the two parties. We propose two contract forms. The franchise fee contract is a two‐part price schedule specifying a variable wholesale price and a fixed franchise fee. The retail price maintenance contract links the allowed retail price that the agent charges customers with total payment to the manufacturer and sales level. Under information asymmetry, for implementing either contract form, the manufacturer needs to offer a menu of contracts, hoping to invoke the “revelation principle” when the agent picks a certain contract from that menu. We show that the two contract forms perform differently, and each party's preference toward a particular contract form is linked with the total reservation profit level and/or the sales agent's cost type. We provide managerial guidelines for the manufacturer in selecting a better contract form under different conditions.     

The Impact of Revenue‐Maximizing Priority Pricing on Customer Delay Costs

Speed is an increasingly important determinant of which suppliers will be given customers' business and is defined as the time between when an order is placed by the customer and when the product is delivered, or as the amount of time customers must wait before they receive their desired service. In either case, the speed a customer experiences can be enhanced by giving priority to that particular customer. Such a prioritization scheme will necessarily reduce the speed experienced by lower‐priority customers, but this can lead to a better outcome when different customers place different values on speed. We model a single resource (e.g., a manufacturer) that processes jobs from customers who have heterogeneous waiting costs. We analyze the price that maximizes priority revenue for the resource owner (i.e., supplier, manufacturer) under different assumptions regarding customer behavior. We discover that a revenue‐maximizing supplier facing self‐interested customers (i.e., those that independently minimize their own expected costs) charges a price that also minimizes the expected total delay costs across all customers and that this outcome does not result when customers coordinate to submit priority orders at a level that seeks to minimize their aggregate costs of priority fees and delays. Thus, the customers are better off collectively (as is the supplier) when the supplier and customers act independently in their own best interests. Finally, as the number of priority classes increases, both the priority revenues and the overall customer delay costs improve, but at a decreasing rate.     

RELIABILITY-CONSTRAINED PRICING,CAPACITY, AND QUALITY: AN ILLUSTRATION OF ECONOMIC CONCEPTS TO POSTAL SERVICES

A model is developed from which welfare-optimal prices, capacities, and reliabilities for a service provider are simultaneously determined. Solutions are determined under conditions of stochastic demand subject to a reliability constraint on service quality. Both quality of service provided, as well as price, impact on demand for services rendered. Results indicate that (i) optimal prices are equated to the reliability-constrained marginal costs, (ii) optimal reliabilities require that the marginal benefits of increasing reliability are equated to the marginal costs of doing so, and (iii) optimal capacity allocation involves minimizing the system's expected costs subject to meeting the prespecified reliability constraint for service quality. The model is applied to postal delivery services in light of the growing competition that has emerged in this industry.     

Fleet Replacement,Technology Choice,and the Option to Breach a Leasing Contract

We analyze the option to breach a leasing contract when replacing a fleet of ICVs (internal combustion engine vehicles) and EVs (electric vehicles) subject to cost uncertainty. We derive the optimal policy for technology choice and breaching ICV contracts. The decision to breach is shown to offer both cost savings resulting from reduced ICV operating costs and preemptive acquisition, but incurs additional costs arising from the need to compensate for breached vehicles and in the form of opportunity costs. We also demonstrate that the effects of breaching a leasing contract have a ripple effect across the decision horizon, thus amplifying the impact of a single breach. A numerical study based on data from La Poste, the French postal service, shows that breaching a leasing contract in this context offers measurable cost benefits.     

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.