Senthil K. Veeraraghavan

Revenue Management with Strategic Customers: Last-Minute Selling and Opaque Selling

Companies in a variety of industries (e.g., airlines, hotels, theaters) often use last-minute sales to dispose of unsold capacity. Although this may generate incremental revenues in the short term, the long-term consequences of such a strategy are not immediately obvious: More discounted last-minute tickets may lead to more consumers anticipating the discount and delaying the purchase rather than buying at the regular (higher) prices, hence potentially reducing revenues for the company. To mitigate such behavior, many service providers have turned to opaque intermediaries, such as Hotwire.com, that hide many descriptive attributes of the service (e.g., departure times for airline tickets) so that the buyer cannot fully predict the ultimate service provider. Using a stylized economic model, this paper attempts to explain and compare the benefits of last-minute sales directly to consumers versus through an opaque intermediary. We utilize the notion of rational expectations to model consumer purchasing decisions: Consumers make early purchase decisions based on expectations regarding future availability, and these expectations are correct in equilibrium. We show that direct last-minute sales are preferred over selling through an opaque intermediary when consumer valuations for travel are high or there is little service differentiation between competing service providers, or both; otherwise, opaque selling dominates. Moreover, contrary to the usual belief that such sales are purely mechanisms for disposal of unused capacity, we show that opaque selling becomes more preferred over direct last-minute selling as the probability of having high demand increases. When firms randomize between opaque selling and last-minute selling strategies, they are increasingly likely to choose the opaque selling strategy as the probability of high demand increases. When firms with unequal capacities use the opaque selling strategy, consumers know more clearly where the opaque ticket is from and the efficacy of opaque selling decreases.

Now or Later: A Simple Policy for Effective Dual Sourcing in Capacitated Systems

We examine a possibly capacitated, periodically reviewed, single-stage inventory system where replenishment can be obtained either through a regular fixed lead time channel, or, for a premium, via a channel with a smaller fixed lead time. We consider the case when the unsatisfied demands are backordered over an infinite horizon, introducing the easily implementable, yet informationally rich dual-index policy. We show very general separability results for the optimal parameter values, providing a simulation-based optimization procedure that exploits these separability properties to calculate the optimal inventory parameters within seconds. We explore the performance of the dual-index policy under stationary demands as well as capacitated production environments, demonstrating when the dual-sourcing option is most valuable. We find that the optimal dual-index policy mimics the behavior of the complex, globally optimal state-dependent policy found via dynamic programming: the dual-index policy is nearly optimal (within 1% or 2%) for the majority of cases, and significantly outperforms single sourcing (up to 50% better). Our results on optimal dual-index parameters are generic, extending to a variety of complex and realistic scenarios such as nonstationary demand, random yields, demand spikes, and supply disruptions.

Quality--Speed Conundrum: Trade-offs in Customer-Intensive Services

In many services, the quality or value provided by the service increases with the time the service provider spends with the customer. However, longer service times also result in longer waits for customers. We term such services, in which the interaction between quality and speed is critical, as customer-intensive services. In a queueing framework, we parameterize the degree of customer intensity of the service. The service speed chosen by the service provider affects the quality of the service through its customer intensity. Customers queue for the service based on service quality, delay costs, and price. We study how a service provider facing such customers makes the optimal “quality--speed trade-off.” Our results demonstrate that the customer intensity of the service is a critical driver of equilibrium price, service speed, demand, congestion in queues, and service provider revenues. Customer intensity leads to outcomes very different from those of traditional models of service rate competition. For instance, as the number of competing servers increases, the price increases, and the servers become slower. This paper was accepted by Sampath Rajagopalan, operations and supply chain management.

Contracting for Infrequent Restoration and Recovery of Mission-Critical Systems

Firms that rely on functioning mission-critical equipment for their businesses cannot afford significant operational downtime due to system disruptions. To minimize the impact of disruptions, a proper incentive mechanism has to be in place so that the suppliers provide prompt restoration and recovery services to the customer. A widely adopted incentive mechanism is performance-based contracting (PBC), in which suppliers receive compensation based on realized system uptime. A key obstacle is that disruptions occur infrequently, making it very expensive for a supplier to commit the necessary resources for recovery because they will be idle most of the time. In this paper, we show that designing a successful PBC creates nontrivial challenges that are unique to this environment. Namely, because of the infrequent and random nature of disruptions, a seemingly innocuous choice of performance measures used in contracts may create unexpected incentives, resulting in counterintuitive optimal behavior. We compare the efficiencies of two widely used contracts, one based on sample-average downtime and the other based on cumulative downtime, and identify the suppliers ability to influence the frequency of disruptions as an important factor in determining which contract performs better. We also show that implementing PBC may create high agency cost when equipment is very reliable. This counterintuitive situation arises because the realized downtimes from which the customer might intuit about the suppliers capacity investment are highly uncertain when there are not many samples of downtimes, i.e., when disruptions occur rarely.

Selling to Conspicuous Consumers: Pricing, Production, and Sourcing Decisions

Consumers often purchase goods that are “hard to find” to conspicuously display their exclusivity and social status. Firms that produce such conspicuously consumed goods such as designer apparel, fashion goods, jewelry, etc., often face challenges in making optimal pricing and production decisions. Such firms are confronted with precipitous trade-off between high sales volume and high margins, because of the highly uncertain market demand, strategic consumer behavior, and the display of conspicuous consumption. In this paper, we propose a model that addresses pricing and production decisions for a firm, using the rational expectations framework. We show that, in equilibrium, firms may offer high availability of goods despite the presence of conspicuous consumption. We show that scarcity strategies are harder to adopt as demand variability increases, and we provide conditions under which scarcity strategies could be successfully adopted to improve profits. Finally, to credibly commit to scarcity strategy, we show that firms can adopt sourcing strategies, such as sourcing from an expensive production location/supplier or using expensive raw materials. This paper was accepted by Preyas Desai and Pradeep Chintagunta, marketing.

Herding in Queues with Waiting Costs: Rationality and Regret

We study how consumers with waiting cost disutility choose between two congested services of unknown service value. Consumers observe an imperfect private signal indicating which service facility may provide better service value as well as the queue lengths at the service facilities before making their choice. If more consumers choose the same service facility because of their private information, longer queues will form at that facility and indicate higher quality. On the other hand, a long queue also implies more waiting time. We characterize the equilibrium queue-joining behavior of arriving consumers and the extent of their learning from the queue information in the presence of such positive and negative externalities. We find that when the arrival rates are low, utility-maximizing rational consumers herd and join the longer queue, ignoring any contrary private information. We show that even when consumers treat queues as independently evolving, herd behavior persists with consumers joining longer queues above a threshold queue difference. However, if the consumers seek to minimize ex post regret when making their decisions, herd behavior may be dampened.

Equilibrium in Queues Under Unknown Service Times and Service Value

In the operations research literature, the queue joining probability is monotonic decreasing in the queue length; the longer the queue, the fewer consumers join. Recent academic and empirical evidence indicates that queue-joining probabilities may not always be decreasing in the queue length. We provide a simple explanation for these nonmonotonic queue-joining strategies by relaxing the informational assumptions in Naors model. Instead of imposing that the expected service time and service value are common knowledge, we assume that they are unknown to consumers, but positively correlated. Under such informational assumptions, the posterior expected waiting cost and service value increase in the observed queue length. As a consequence, we show that queue-joining equilibria may emerge for which the joining probability increases locally in the queue length. We refer to these as “sputtering equilibria.” We discuss when and why such sputtering equilibria exist for discrete as well as continuously distributed priors on the expected service time with positively correlated service value.

Selling to Strategic Customers: Opaque Selling Strategies

Over the past few years, firms in the travel and entertainment industries have begun using novel sales strategies for revenue management. In this chapter, we study a selling strategy called opaque selling, in which firms guarantee one of several fully specified products, but hide the identity of the product that the consumer will actually obtain until after the purchase is completed. Several firms such as Hotwire, Priceline, and Mystery Flights engage in opaque selling of travel products. The academic literature in this area is recent and evolving. We first survey the nascent literature on opaque selling strategies. After presenting the current state of theory and practice, we analyze in-depth a model of competing firms selling horizontally differentiated products through an opaque channel. Consumers strategically time their purchases by developing rational expectations about future availability in the opaque market, keeping in mind that demand is uncertain and product supply could be limited. This model helps illustrate the conditions under which opaque selling can increase firm profits. We conclude the chapter by discussing ongoing research and charting out future research directions.

Models of Herding Behavior in Operations Management

When new innovative products and services are introduced into the market, the consumers often do not have complete information about the quality of such products or services. Even though they collect information from several sources, their private information about the product is generally noisy and inaccurate. Under such cases, the consumers complement their private information with some available public information based on what /other/ consumers chose. For example, customers might look at the queue length information in choosing a restaurant/sports bar, or examine available sales information while choosing a recently released book, or observe stock-out information in buying a new electronic product. In these cases, the consumers might ignore their own private information and could decide to wait in the longer queue, or to purchase a more popular book, or to wait for a stocked-out electronic product. Modeling consumer behavior with such positive externalities causes the overall demand to be significantly different from traditionally modeled consumer demand. Not surprisingly, such consumer decision processes also significantly impact firms’ capacity decisions: Long queues or stock-outs might signal better quality and thus generate more demand. Operations management literature in this area is nascent and emerging. In this chapter, we present current results in the operations management literature from papers that model consumer herding behavior and explore important future research directions.

Simple Policies for Managing Flexible Capacity

In many scenarios, a fixed capacity is shared flexibly between multiple products. To manage such multiproduct systems, firms need to make two sets of decisions. The first one requires setting an inventory target for each product, and the second requires dynamically allocating the scarce capacity among the products. It is not known how to make these decisions optimally. In this paper, we propose easily implementable policies that have both theoretical and practical appeal. We first suggest simple and intuitive allocation rules that determine how such scarce capacity is shared. Given such rules, we calculate the optimal inventory target for each product. We demonstrate analytically that our policies are optimal under two asymptotic regimes represented by high service levels (i.e., high shortage costs) and heavy traffic (i.e., tight capacity). We also demonstrate that our policies outperform current known policies over a wide range of problem parameters. In particular, the cost savings from our policies beco...