Sensitivity of Optimal Capacity to Customer Impatience in an Unobservable M/M/S Queue (Why You Shouldn't Shout at the DMV)

This paper employs sample path arguments to derive the following convexity properties and comparative statics for an M/M/S queue with impatient customers. If the rate at which customers balk and renege is an increasing, concave function of the number of customers in the system (head count), then the head-count process and the expected rate of lost sales are decreasing and convex in the capacity (service rate or number of servers). This result applies when customers cannot observe the head count, so that the balking probability is zero and the reneging rate increases linearly with the head count. Then the optimal capacity increases with the customer arrival rate but is not monotonic in the reneging rate per customer. When capacity is expensive or the reneging rate is high, the optimal capacity decreases with any further increase in the reneging rate. Therefore, managers must understand customers' impatience to avoid building too much capacity, but customers have an incentive to conceal their impatience, to avoid a degradation in service quality. If the system manager can prevent customers from reneging during service (by requiring advance payment or training employees to establish rapport with customers), the system's convexity properties are qualitatively different, but its comparative statics remain the same. Most important, the prevention of reneging during service can substantially reduce the total expected cost of lost sales and capacity. It increases the optimal capacity (service rate or number of servers) when capacity is expensive and reduces the optimal capacity when capacity is cheap.

[1]  Steven Nahmias,et al.  Simple Approximations for a Variety of Dynamic Leadtime Lost-Sales Inventory Models , 1979, Oper. Res..

[2]  Avishai Mandelbaum,et al.  Estimating characteristics of queueing networks using transactional data , 1998, Queueing Syst. Theory Appl..

[3]  Jan A. Van Mieghem,et al.  Price and Service Discrimination in Queueing Systems: Incentive-Compatibility of Gcμ Scheduling , 2000 .

[4]  R. Ravi,et al.  Scheduling and Reliable Lead-Time Quotation for Orders with Availability Intervals and Lead-Time Sensitive Revenues , 2001, Manag. Sci..

[5]  Sunil Kumar,et al.  Diffusion of Innovations Under Supply Constraints , 2003, Oper. Res..

[6]  Phillip J. Lederer,et al.  Pricing, Production, Scheduling, and Delivery-Time Competition , 1997, Oper. Res..

[7]  J. V. Mieghem Dynamic Scheduling with Convex Delay Costs: The Generalized CU Rule , 1995 .

[8]  Wallace J. Hopp,et al.  A Simple, Robust Leadtime-Quoting Policy , 2001, Manuf. Serv. Oper. Manag..

[9]  Philipp Afèche Incentive-Compatible Revenue Management in Queueing Systems : Optimal Strategic Idleness and other Delaying Tactics , 2004 .

[10]  Amy R. Ward,et al.  Approximating the GI/GI/1+GI Queue with a Nonlinear Drift Diffusion: Hazard Rate Scaling in Heavy Traffic , 2008, Math. Oper. Res..

[11]  S. Johansen,et al.  Optimal (r, Q) inventory policies with Poisson demands and lost sales: discounted and undiscounted cases , 1996 .

[12]  Sem C. Borst,et al.  Dimensioning Large Call Centers , 2000, Oper. Res..

[13]  Ward Whitt,et al.  Engineering Solution of a Basic Call-Center Model , 2005, Manag. Sci..

[14]  Christian Terwiesch,et al.  Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint , 2002, Manag. Sci..

[15]  S. Nahmias,et al.  A continuous review model for an inventory system with two supply modes , 1988 .

[16]  Li Chen,et al.  Dynamic Inventory Management with Learning About the Demand Distribution and Substitution Probability , 2008, Manuf. Serv. Oper. Manag..

[17]  Avishai Mandelbaum,et al.  Staffing Many-Server Queues with Impatient Customers: Constraint Satisfaction in Call Centers , 2009, Oper. Res..

[18]  Søren Glud Johansen,et al.  The (r,Q) control of a periodic-review inventory system with continuous demand and lost sales , 2000 .

[19]  Moshe Haviv,et al.  Price and delay competition between two service providers , 2003, Eur. J. Oper. Res..

[20]  Sunil Kumar,et al.  Asymptotically Optimal Admission Control of a Queue with Impatient Customers , 2008, Math. Oper. Res..

[21]  Avishai Mandelbaum,et al.  A model for rational abandonments from invisible queues , 2000, Queueing Syst. Theory Appl..

[22]  Ward Whitt,et al.  Staffing a Call Center with Uncertain Arrival Rate and Absenteeism , 2006 .

[23]  Avishai Mandelbaum,et al.  Designing a Call Center with Impatient Customers , 2002, Manuf. Serv. Oper. Manag..

[24]  Erica L. Plambeck,et al.  Note: A Separation Principle for a Class of Assemble-to-Order Systems with Expediting , 2007, Oper. Res..

[25]  Evan L. Porteus Foundations of Stochastic Inventory Theory , 2002 .

[26]  W. Hopp,et al.  Quoting Customer Lead Times , 1995 .

[27]  Katta G. Murty,et al.  Nonlinear Programming Theory and Algorithms , 2007, Technometrics.

[28]  Sunil Kumar,et al.  Multiserver Loss Systems with Subscribers , 2009, Math. Oper. Res..

[29]  Constantinos Maglaras,et al.  Pricing and Capacity Sizing for Systems with Shared Resources: Approximate Solutions and Scaling Relations , 2003, Manag. Sci..

[30]  J. Shanthikumar,et al.  Stochastic convexity and its applications , 1988, Advances in Applied Probability.

[31]  Søren Glud Johansen,et al.  Optimal and approximate (Q, r) inventory policies with lost sales and gamma-distributed lead time , 1993 .

[32]  Avishai Mandelbaum,et al.  Statistical Analysis of a Telephone Call Center , 2005 .

[33]  Peter W. Glynn,et al.  A Diffusion Approximation for a GI/GI/1 Queue with Balking or Reneging , 2005, Queueing Syst. Theory Appl..

[34]  Avishai Mandelbaum,et al.  Call Centers with Impatient Customers: Many-Server Asymptotics of the M/M/n + G Queue , 2005, Queueing Syst. Theory Appl..

[35]  Ward Whitt,et al.  Staffing of Time-Varying Queues to Achieve Time-Stable Performance , 2008, Manag. Sci..

[36]  Yew Sing Lee,et al.  Pricing and Delivery-Time Performance in a Competitive Environment , 1994 .

[37]  Andreas Brandt,et al.  Asymptotic Results and a Markovian Approximation for the M(n)/M(n)/s+GI System , 2002, Queueing Syst. Theory Appl..

[38]  Jan A. Van Mieghem,et al.  Price and Service Discrimination in Queueing Systems: Incentive-Compatibility of Gcμ Scheduling , 2000 .

[39]  Roman Kapuscinski,et al.  Reliable Due-Date Setting in a Capacitated MTO System with Two Customer Classes , 2007, Oper. Res..

[40]  Erica L. Plambeck,et al.  The Impact of Duplicate Orders on Demand Estimation and Capacity Investment , 2003, Manag. Sci..

[41]  Erica L. Plambeck,et al.  Optimal Control of a High-Volume Assemble-to-Order System , 2006, Math. Oper. Res..

[42]  D. Yao,et al.  Second-order stochastic properties in queueing systems , 1989, Proc. IEEE.

[43]  Ger Koole,et al.  TECHNICAL NOTE - A Note on Profit Maximization and Monotonicity for Inbound Call Centers , 2011, Oper. Res..

[44]  Erica L. Plambeck,et al.  Optimal Leadtime Differentiation via Diffusion Approximations , 2004, Oper. Res..

[45]  MandelbaumAvishai,et al.  Call Centers with Impatient Customers , 2005 .

[46]  J. Michael Harrison,et al.  A Method for Staffing Large Call Centers Based on Stochastic Fluid Models , 2005, Manuf. Serv. Oper. Manag..

[47]  Hector A. Rosales-Macedo Nonlinear Programming: Theory and Algorithms (2nd Edition) , 1993 .

[48]  Ward Whitt,et al.  Fluid Models for Multiserver Queues with Abandonments , 2006, Oper. Res..

[49]  Steven Nahmias Queues with Impatient Customers , 2011 .

[50]  Haim Mendelson,et al.  Optimal Incentive-Compatible Priority Pricing for the M/M/1 Queue , 1990, Oper. Res..

[51]  Paul R. Kleindorfer,et al.  Service Constrained s, S Inventory Systems with Priority Demand Classes and Lost Sales , 1988 .