Rachel R. Chen

Estimating the Implied Value of the Customer's Waiting Time

Almost all research in appointment scheduling has focused on the trade-off between customer waiting times and server idle times. In this paper, we present an observation-based method for estimating the relative cost of the customer waiting time, which is a critical parameter for finding the optimal appointment schedule.

Sequencing and scheduling appointments with potential call-in patients

This paper studies appointment scheduling for a combination of routine patients who book well in advance and last-minute patients who call for an appointment later that same day. We determine when these same-day patients should be scheduled throughout the day, and how the prospect of their arrivals affects the appointment times of the routine patients. By formulating the problem as a stochastic linear program, we are able to incorporate random and heterogeneous service times and no-show rates, ancillary physician tasks, and appointment delay costs for same-day patients who prefer to see the doctor as early as possible. We find that the optimal patient sequence is quite sensitive to the no-show probabilities and the expected number of same-day patients. We also develop two simple heuristic solutions to this combinatorial sequencing problem.

Optimal multiple-breakpoint quantity discount schedules for customers with heterogeneous demands: all-unit or incremental?

The suppliers problem of designing a quantity discount schedule is much more complicated when she faces customers who vary in size. This article considers both all-unit and incremental discount schedules with multiple breakpoints that maximize the suppliers net savings. Specifically, we assume that the distribution of customers’ demand belongs to the general family of Benders Pareto curves, which generalizes the well-known “80-20” rule from A-B-C inventory analysis. For any number of breakpoints, we prove that the supplier is at least as well off under the optimal incremental discount schedule as she would be under the optimal all-unit discount schedule. Numerical study shows that most of the savings can be captured by a modest number (five) of breakpoints and that the advantage of incremental schedules over all-unit schedules goes to zero as the number of breakpoints grows large.

Customer Bill of Rights Under No-Fault Service Failure: Confinement and Compensation

Service providers and their customers are sometimes victims of failures caused by exogenous factors such as unexpected bad weather, power outages, or labor strikes. When such no-fault failures occur in confined zones, service providers may confine customers against their will if making arrangements for them to leave is very costly. Such confinements, however, can result in severe pain and suffering, and customer complaints put regulators under pressure to pass a customer bill of rights that allows captive customers to abort failed services. This paper shows that service providers are better off preempting such laws by voluntarily allowing customers to escape the service under failure. Moreover, service providers can profit by targeting compensation to customers based on whether they use or leave the service under failure.

The equivalence of uniform and Shapley value-based cost allocations in a specific game

This paper concerns the possible equivalence of the Shapley value and other allocations in specific games. For a group buying game with a linear quantity discount schedule, the uniform allocation results in the same cost allocation as the Shapley value. In this paper, we explore whether the Shapley axioms can be used to make such connections. We also characterize the functions that result in the equivalence of these two allocations among the class of polynomial total cost functions.

Research Note---Should Captive Sardines Be Compensated? Serving Customers in a Confined Zone

Many services are delivered to a (large) number of customers simultaneously within a confined zone (e.g., restaurants, resorts, trains, and airplanes). Under unexpected high demand, customers experience discomfort from two major sources: (a) the sardine effect that arises when too many customers (i.e., sardines) compete for space and service resources, and (b) the captivity effect that results from an exit cost incurred by customers who self-select to “escape” the unpleasant service. This paper investigates the optimal compensation and pricing policies under these two effects. We find that offering compensation to sardines can improve profit and social welfare. However, consumers do not benefit when compensated for the discomfort from crowding. This paper also provides insights by exploring the impact of changes in the two effects on price and profit.

Reward-Based Crowdfunding Campaigns: Informational Value and Access to Venture Capital

We consider an entrepreneur who designs a reward-based crowdfunding campaign when the campaign provides a signal about the future demand for the product and subsequent venture capital is needed. We find that both the informativeness of the campaign and considerations related to gaining access to venture capital funding affect the entrepreneur’s choice of campaign instruments, as well as her decision of whether to run a campaign. In particular, entrepreneurs should launch the campaign either when it is highly informative or when it is not informative at all. For relatively low levels of informativeness, but not so low that the venture capitalist (VC) completely ignores the campaign outcome in his funding decision, our study suggests that the entrepreneur might forgo the opportunity of acquiring information via crowdfunding because the benefits of crowdfunding are insufficient to offset the risk of campaign failure. We also find that the preference of entrepreneurs in favor of crowdfunding is stronger than ...