Operations & Supply Chain Management

Customer switching costs are an important factor in account-based services such as telecommunications, financial, insurance and brokerage services. In these businesses, existing customers incur significant costs if they switch to another provider. Such costs include physical configuration and installation costs, contractual costs (e.g. termination fees) and cognitive costs of learning. These switching costs enable a firm to extract more revenue from incumbent customers by charging them higher prices.

The principal performance measures in an inventory system involve key characteristics of the system's inventory position, i.e., the total inventory the firm is economically committed to, as well as the average order size or order frequency. As to the former, the focus among operation managers is on the maximum inventory (position), the average inventory and the minimum inventory, the latter being related to the so-called safety stock concept. Financial analysts and macroeconomists pay particular attention to the sales/inventory ratio, also referred to as the inventory turnover.

Scarcity has long been known to impact consumers' choices. Yet, the impact of shelf-based scarcity in retail environments, created by stocking level depletion, has received almost no attention in the literature. Indeed, little research to date has even examined if consumers will attend to shelf-based scarcity in retail environments, much less how this cue can impact choice. A priori, given the inherently noisy and cue-filled nature of retail environments, it is quite reasonable to expect that shelf-based scarcity would play little to no role in consumers' choices.

Capacity decisions in service operations often involve a trade-off between operating cost and the level of service offered to customers. Although the cost of attaining a pre-specified level of service has been well-studied, there isn't much research studying how customer service levels affect revenue and profit. This paper conducts an empirical study to analyze how waiting in a queue in the context of a retail store affects customer purchasing behavior. Our methodology uses a novel technology based on digital imaging to record periodic information about the queuing system.

We address the following problems that arise in the management of call center operating under certain Service Level Agreements (SLAs): (1) setting the capacity levels of the agent pools; (2) constructing a routing scheme for arriving customers; and (3) devising a dynamic priority rule for customers waiting at each pool. We develop a mathematical programming approach to simultaneously solve this integrated planning problem and show how it can be used in strategic call center design studies.

We consider a sequential adaptive allocation problem which is formulated as a traditional two armed bandit problem but with one important modification: at each time step t, before selecting which arm to pull, the decision maker has access to a random variable Xt which provides information on the reward in each arm. Performance is measured as the fraction of time an inferior arm (generating lower mean reward) is pulled.

Maximizing throughput for heterogeneous parallel server queues has received quite a bit of attention from the research community and the stability region for such systems is well understood.  However, many real-world systems have periods where they are temporarily overloaded.  Under such scenarios, the unstable queues often starve limited resources.  This work examines what happens during periods of temporary overload.  Specifically, we look at how to fairly distribute stress.  We explore the dynamics of the queue workloads under the MaxWeight scheduling policy duri

In modern equity markets, traders have a choice of many exchanges, each operating as an electronic limit order book that can be modeled as a pair of multi-class queues operating under the "time/price" priority rule. The dynamics of the exchanges are coupled via price protection mechanisms. We present mathematical models to study the order routing problem, characterize market equilibria, and derive insights about the queue, delay and adverse selection measures for different exchanges. We present some empirical data that supports our findings.

We propose and study a market microstructure model of a stochastic and dynamic matching problem. Sellers arrive over time supplying capacity to this market that is characterized by a feature set that includes its price. Sellers are also characterized by their delay tolerance and financial considerations. In turn, buyers arrive over time seeking capacity and are endowed with a choice model that allows them to compare and tradeoff options that differ in their features and price.