Routing to Manage Resolution and Waiting Time in Call Centers with Heterogeneous Servers

Published Online:https://doi.org/10.1287/msom.1110.0349

References

  • Aguir S., Karaesmen F., Akşin O. Z., Chauvet F. The impact of retrials on call center performance. OR Spectrum (2004) 26(3):353–376CrossrefGoogle Scholar
  • Aksin Z., Armony M., Mehrotra V. The modern call-center: A multi-disciplinary perspective on operations management research. Production Oper. Management (2007) 16(6):665–688CrossrefGoogle Scholar
  • Armony M. Dynamic routing in large-scale service systems with heterogeneous servers. Queueing Systems (2005) 51(3–4):287–329CrossrefGoogle Scholar
  • Armony M., Bambos N. Queueing dynamics and maximal throughput scheduling in switched processing systems. Queueing Systems (2003) 44(3):209–252CrossrefGoogle Scholar
  • Borst S., Mandelbaum A., Reiman M. I. Dimensioning large call centers. Oper. Res. (2004) 52(1):17–34LinkGoogle Scholar
  • Buist E., L'Ecuyer P. A java library for simulating contact centers. Proc. 2005 Winter Simulation Conf. (2005) (IEEE, Piscataway, NJ) 556–565CrossrefGoogle Scholar
  • Cross K. F. Call resolution: The wrong focus for service quality? Quality Progress (2000) 33(2):64–67Google Scholar
  • Dai J. G., Lin W. Maximum pressure policies in stochastic processing networks. Oper. Res. (2005) 53(2):197–218LinkGoogle Scholar
  • Dai J. G., Tezcan T. Optimal control of parallel server systems with many servers in heavy traffic. Queueing Systems (2008) 59(2):95–134CrossrefGoogle Scholar
  • de Véricourt F., Zhou Y.-P. A routing problem for call centers with customer callbacks after service failure. Oper. Res. (2005) 53(6):968–981LinkGoogle Scholar
  • Falin G., Templeton J. G. C.Retrial Queues (1997) (Chapman and Hall/CRC, London) CrossrefGoogle Scholar
  • Feinberg R. A., Hokama L., Kadan R., Kim I. Operational determinants of caller satisfaction in the banking/financial services call center. Inter. J. Bank Marketing (2002) 20(4/5):174–180CrossrefGoogle Scholar
  • Gans N., Zhou Y.-P. Managing learning and turnover in employee staffing. Operations Res. (2002) 50(6):991–1006LinkGoogle Scholar
  • Gans N., Koole G., Mandelbaum A. Telephone call centers: Tutorial, review, and research prospects. Manufacturing Service Oper. Management (2003) 5(2):79–141LinkGoogle Scholar
  • Gans N., Liu N., Mandelbaum A., Shen H., Ye H. Service times in call centers: Agent heterogeneity and learning with some operational consequences. Borrowing Strength: Theory Powering Applications—A Festschrift for Lawrence D. Brown (2010) 6(Institute of Mathematical Statistics, Beachwood, OH) 99–123IMS CollectionsGoogle Scholar
  • Gurvich I., Whitt W. Scheduling exible servers with convex delay costs in many-server service systems. Manufacturing Service Oper. Management (2009) 11(2):237–253LinkGoogle Scholar
  • Gurvich I., Armony M., Mandelbaum A. Service level differentiation in call centers with fully exible servers. Management Sci. (2008) 54(2):279–294LinkGoogle Scholar
  • Halfin S., Whitt W. Heavy-traffic limits for queues with many exponential servers. Oper. Res. (1981) 29(3):567–588LinkGoogle Scholar
  • Hart M., Fichtner B., Fjalestad E., Langley S. Contact centre performance: In pursuit of first call resolution. Management Dynam. (2006) 15(4):17–28Google Scholar
  • Koole G., Pot A., Talim J. Routing heuristics for multi-skill call centers. Proc. 2003 Winter Simulation Conf. (2003) (IEEE, Piscataway, NJ) 1813–1816CrossrefGoogle Scholar
  • L'Ecuyer P. Modeling and optimization problems in contact centers. Proc. 3rd Internat. Conf. Quant. Eval. Systems (QEST'06) (2006) (IEEE, Piscataway, NJ) 145–154Google Scholar
  • L'Ecuyer P., Buist E. Variance reduction in the simulation of call centers. Proc. 2006 Winter Simulation Conf. (2006) (IEEE, Piscataway, NJ) 604–613Google Scholar
  • Mahajan P. S., Ingalls R. G. Evaluation of methods used to detect warm-up period in steady state simulation. Proc. 2004 Winter Simulation Conf. (2004) 1(IEEE, Piscataway, NJ) 663–671Google Scholar
  • Mandelbaum A., Stolyar A. L. Scheduling exible servers with convex delay costs: Heavy-traffic optimality of the generalized c-rule. Oper. Res. (2004) 52(6):836–855LinkGoogle Scholar
  • Mandelbaum A., Zeltyn S., Spath D., Fähnrich K.-P. Service engineering in action: The Palm/Erlang-a queue, with applications to call centers. Advances in Services Innovations (2007) (Springer, Berlin) 17–46CrossrefGoogle Scholar
  • Pinker E., Shumsky R. The efficiency-quality trade-off of cross-trained workers. Manufacturing Service Oper. Management (2000) 2(1):32–48LinkGoogle Scholar
  • Read B. B. Call center checkup. Call Center Magazine (2003) June 1). http://www.icmi.com/Resources/Articles/2003/June/Call-Center-CheckupGoogle Scholar
  • Ryder G. Routing to develop expertise in customer contact centers. (2009) . Doctoral dissertation, University of California, Santa Cruz, Santa CruzGoogle Scholar
  • Sisselman M. E., Whitt W. Value-based routing and preference-based routing in customer contact centers. Production Oper. Management (2007) 16(3):277–291CrossrefGoogle Scholar
  • Stolyar A. Maxweight scheduling in a generalized switch: State space collapse and workload minimization in heavy traffic. Ann. Appl. Probab. (2004) 14(1):1–53CrossrefGoogle Scholar
  • Whitt W. The impact of increased employee retention on performance in a customer contact center. Manufacturing Service Oper. Management (2006) 8(3):235–252LinkGoogle Scholar
  • Yucesan E. Randomization tests for initialization bias in simulation output. Naval Res. Logist. Quart. (1993) 40(5):643–663CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.