Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
A Call-Routing Problem with Service-Level Constraints
Operations Research
Dimensioning Large Call Centers
Operations Research
Manufacturing & Service Operations Management
Dynamic Routing in Large-Scale Service Systems with Heterogeneous Servers
Queueing Systems: Theory and Applications
Note---A Mathematical Model for Evaluating Cross-Sales Policies in Telephone Service Centers
Manufacturing & Service Operations Management
Revenue Management Through Dynamic Cross Selling in E-Commerce Retailing
Operations Research
Contact Centers with a Call-Back Option and Real-Time Delay Information
Operations Research
Service-Level Differentiation in Call Centers with Fully Flexible Servers
Management Science
Pricing Promotional Products Under Upselling
Manufacturing & Service Operations Management
Cross-Selling in a Call Center with a Heterogeneous Customer Population
Operations Research
Scheduling Flexible Servers with Convex Delay Costs in Many-Server Service Systems
Manufacturing & Service Operations Management
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We study cross-selling operations in call centers. The following questions are addressed: How many customer-service representatives are required (staffing), and when should cross-selling opportunities be exercised (control) in a way that will maximize the expected profit of the center while maintaining a prespecified service level target? We tackle these questions by characterizing control and staffing schemes that are asymptotically optimal in the limit, as the system load grows large. Our main finding is that a threshold priority control, in which cross-selling is exercised only if the number of callers in the system is below a certain threshold, is asymptotically optimal in great generality. The asymptotic optimality of threshold priority reduces the staffing problem to a solution of a simple deterministic problem in one regime and to a simple search procedure in another. We show that our joint staffing and control scheme is nearly optimal for large systems. Furthermore, it performs extremely well, even for relatively small systems.