Unbundling of Ancillary Service: How Does Price Discrimination of Main Service Matter?

We consider a setting where the firm sells a main service (e.g., air travel) and an ancillary service (e.g., baggage delivery) to two types of consumers (e.g., business travelers and leisure travelers). We study how the firm’s ability to charge discriminatory main service prices affects its decision of whether to unbundle the ancillary service from the main service and charge separate prices. Unlike a firm using uniform pricing of main service that unbundles the ancillary service if the consumers that value the main service higher have a high likelihood of purchasing the ancillary service, a firm using discriminatory pricing of main service unbundles the ancillary service if the consumers that value the main service higher have a low likelihood of purchasing the ancillary service. Moreover, discriminatory pricing of main service makes unbundling more (less) likely to be the optimal ancillary service strategy when consumers’ main service valuations and ancillary service valuations are negatively (positively) correlated. Finally, we characterize how firms’ use of main service price discrimination and consumers’ valuation structure (i.e., whether the correlation between consumers’ main service valuations and ancillary service valuations is positive or negative) jointly determine the ancillary service strategies in an industry.http://deepblue.lib.umich.edu/bitstream/2027.42/117358/1/1301_Duenyas.pd

Dynamic Pricing of Substitutable Products in the Presence of Capacity Flexibility

Firms that offer multiple products are often susceptible to periods of inventory mismatches where one product may face shortages while the other has excess inventories. In this paper, we study a joint implementation of price- and capacity-based substitution mechanisms to alleviate the level of such inventory disparities. We consider a firm producing substitutable products via a capacity portfolio consisting of both product-dedicated and flexible resources and characterize the structure of the optimal production and pricing decisions. We then explore how changes in various problem parameters affect the optimal policy structure. We show that the availability of a flexible resource helps maintain stable price differences across products over time even though the price of each product may fluctuate over time. This result has favorable ramifications from a marketing standpoint because it suggests that even when a firm applies a dynamic pricing strategy, it may still establish consistent price positioning among multiple products if it can employ a flexible replenishment resource. We provide numerical examples for the price stabilization effect and discuss extensions of our results to a more general multiple product setting

Pricing of Conditional Upgrades in the Presence of Strategic Consumers

In this paper, we study a conditional upgrade strategy that has recently become common in the travel industry. After a consumer makes a reservation for a product (e.g., a hotel room), she is asked whether she would like to upgrade to a higher-quality (more expensive) one at a discounted price. The upgrade, however, is not fulfilled immediately. The firm fulfills upgrades at check-in if higher-quality products are still available, and the upgrade fee is only charged to the consumer if she gets upgraded. Consumers decide which product type to book and whether to accept an upgrade offer based on the anticipated upgrade probability. We model the consumers' decisions using a Poisson-arrival game framework with incomplete information and prove the existence of Bayesian Nash equilibrium. To further study the firm's optimal upgrade pricing strategy,we also analyze a fluid model which is the asymptotic version of the stochastic model. Our numerical studies validate that our theoretical results derived from the fluid model carry through to the stochastic model. Our analysis identifies multiple benefits of conditional upgrades. First, the firm is able to capture more demand by offering conditional upgrades, Second, conditional upgrades enable the firm to improve its market segmentation by inducing more consumers to purchase higher-quality products. Third, conditional upgrades give the firm more flexibility in better matching fixed capacities to stochastic demands. For a firm that has the ability to optimize product prices, conditional upgrades can generate higher revenues than dynamic pricing.http://deepblue.lib.umich.edu/bitstream/2027.42/117357/1/1300_Duenyas.pd

Should competing firms reveal their capacity?

In this article, we explore when firms have an incentive to hide (or reveal) their capacity information. We consider two firms that aim to maximize profits over time and face limited capacity. One or both of the firms have private information on their own capacity levels, and they update their beliefs about their rival's capacity based on their observation of the other firm's output. We focus on credible revelation mechanisms—a firm may signal its capacity through overproduction, compared to its myopic production levels. We characterize conditions when high‐capacity firms may have the incentive and capability to signal their capacity levels by overproduction. We show that prior beliefs about capacity play a crucial, and surprisingly complex, role on whether the firm would prefer to reveal its capacity or not. A surprising result is that, despite the fact that it may be best for the high‐capacity firm to overproduce to reveal its capacity when capacity information is private, it may end up with more profits than if all capacity information were public knowledge in the first place. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96261/1/21521_ftp.pd

A nonparametric self-adjusting control for joint learning and optimization of multi-product pricing with finite resource capacity

We study a multi-period network revenue management problem where a seller sells multiple products, made from multiple resources with infinite capacity, in an environment where the underlying demand function is a priori unknown (in the nonparametric sense). The objective of the seller is to simultaneously learn the unknown demand function and dynamically price his products to minimize the expected revenue loss. For the problem where the number of selling periods and initial capacity are scaled by k > 0, it is known that the expected revenue loss of any non-anticipating pricing policy is (pk). However, there is a considerable gap between this theoretical lower bound and the performance bound of the best known heuristic control in the literature. In this paper, we propose a Nonparametric Self-adjusting Control and show that its expected revenue loss is O(k1=2+ log k) for any arbitrarily small >0, provided that the underlying demand function is sufficiently smooth. This is the tightest bound of its kind for the problem setting that we consider in this paper and it significantly improves the performance bound of existing heuristic controls in the literature; in addition, our intermediate results on the large deviation bounds for spline estimation and nonparametric stability analysis of constrained optimization are of independent interest and are potentially useful for other applications

Optimal Learning Algorithms for Stochastic Inventory Systems with Random Capacities

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156225/2/poms13178_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156225/1/poms13178.pd

Priority Rules for Multi‐Task Due‐Date Scheduling under Varying Processing Costs

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135700/1/poms12606.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135700/2/poms12606_am.pd

Dynamic Pricing and Replenishment with Customer Upgrades

We study a joint implementation of price‐ and availability‐based product substitution to better match demand and constrained supply across vertically differentiated products. Our study is motivated by firms that utilize dynamic pricing as well as customer upgrades, as ex ante and ex post mechanisms, respectively, to mitigate inventory mismatches. To gain insight into how offering product upgrades impacts optimal price selection, we formulate a multiple period, nested two‐stage model where the firm first sets prices and replenishment levels for each product while the demand is still uncertain, and after observing the demand, decides how many (if any) of the customers to upgrade to a higher quality product. We characterize the structure of the optimal upgrade, pricing and replenishment policies and find that firms having greater flexibility to offer product upgrades can restrain their reliance on dynamic pricing, enabling them to better protect the price differentiation between the products. We also show how the quality differential between the products or changes in the replenishment cost structures influence the optimal policy. Using insights gained from the optimal policy structure, we construct a heuristic policy and find that it performs well across various parameter values. Finally, we consider an extension in which the firm dynamically sets upgrade fees in each period. Our results overall help further our understanding of the intricate relationship among a firm's decisions on pricing, replenishment, and product upgrades in an effort to better match demand and constrained supply

Optimal control of an assembly system with demand for the end-product and intermediate components

This article considers the production and admission control decisions for a two-stage manufacturing system where intermediate components are produced to stock in the first stage and an end-product is assembled from these components through a second-stage assembly operation. The firm faces two types of demand. The demand for the end-product is satisfied immediately if there are available products in inventory while the firm has the option to accept the order for later delivery or to reject it when no inventory is available. Demand for intermediate components may be accepted or rejected to keep components available for assembly purposes. The structure of demand admission, component production and product assembly decisions are characterized. The proposed model is extended to take into account multiple customer classes and a more general revenue collecting scheme where only an upfront partial payment is collected if a customer demand is accepted for future delivery with the remaining revenue received upon delivery. Since the optimal policy structure is rather complex and defined by switching surfaces in a multidimensional space, a simple heuristic policy is proposed for which the computational load grows linearly with the number of products and its performance is tested under a variety of example problems

Experience of Underrepresented Students in Master’s-Level Counselor Education Programs

The purpose of this phenomenological investigation was to understand the racial and ethnic experiences of underrepresented Master’s-level counseling graduate students in CACREP-accredited counselor education programs. The second author conducted semi-structured interviews with six masters-level counseling graduate students. Data analysis revealed four composite themes that comprised students’ experience. The themes were: Perceived Cultural Competence, Individual Characteristics, Connection and Advocacy, and Bringing “It” Up. Implications on how counselor education programming and curriculum can provide support for underrepresented students are provided