Does the Past Predict the Future? The Case of Delay Announcements in Service Systems

References

• Akąin OZ, Armony M, Mehrotra V (2007) The modern call-center: A multi-disciplinary perspective on operations management research. Production Oper. Management 16(6):665–688.Google Scholar
• Akąin Z, Ata B, Emadi S, Su CL (2017) Impact of delay announcements in call centers: An empirical approach. Oper. Res. 65(1):242–265.Link, Google Scholar
• Allon G, Bassambo A, Gurvich I (2012a) We will be right with you: Managing customer with vague promises. Oper. Res. 59(6):1382–1394.Link, Google Scholar
• Allon G, Bassambo A, Gurvich I (2012b) The impact of delaying the delay announcements. Oper. Res. 59(5):1198–1210.Link, Google Scholar
• Ang E, Kwasnick S, Bayati M, Plambeck EL, Aratow M (2016) Accurate emergency department wait time prediction. Manufacturing Service Oper. Management 18(1):141–156.Link, Google Scholar
• Armony M, Maglaras C (2004) Contact centers with a call-back option and real-time delay information. Oper. Res. 52(4):527–545.Link, Google Scholar
• Armony M, Shimkin N, Whitt W (2009) The impact of delay announcements in many-server queues with abandonments. Oper. Res. 57(1):66–81.Link, Google Scholar
• Armony M, Israelit S, Mandelbaum A, Marmor YN, Tseytlin Y, Yom-Tov GB (2015) On patient flow in hospitals: A data-based queueing-science perspective. Stochastic Systems 5(1):146–194.Link, Google Scholar
• Bertsimas D, Nakazato D (1995) The distributional Little’s law and its applications. Oper. Res. 43(2):298–310.Link, Google Scholar
• Borst S, Mandelbaum A, Reiman MI (2004) Dimensioning large call centers. Oper. Res. 52(1):17–34.Link, Google Scholar
• Brown L, Gans N, Mandelbaum A, Sakov A, Shen H, Zeltyn S, Zhao L (2005) Statistical analysis of a telephone call center: A queueing-science perspective. J. Amer. Statist. Assoc. 100(469):36–50.Crossref, Google Scholar
• Eick S, Massey WA, Whitt W (1993) Mt/G/∞ queues with sinusoidal arrival rates. Management Sci. 39(2):241–252.Link, Google Scholar
• Fleming PA, Stolyar B, Simon B (1994) Heavy traffic limit for a mobile phone system loss model. Proc. 2nd Internat. Conf. Telecomm. Syst. Mod. Anal., Nashville, TN, 158–176.Google Scholar
• Garnett O, Mandelbaum A, Reiman M (2002) Designing a call center with impatient customers. Manufacturing Service Oper. Management 4(3):208–227.Link, Google Scholar
• Guo P, Zipkin P (2007) Analysis and comparison of queues with different levels of delay information. Management Sci. 53(6):962–970.Link, Google Scholar
• Gurvich I, Whitt W (2009) Queue-and-idleness-ratio controls in many-server service systems. Math. Oper. Res. 34(2):363–396.Link, Google Scholar
• Halfin S, Whitt W (1981) Heavy-traffic limits for queues with many exponential servers. Oper. Res. 29:567–588.Link, Google Scholar
• Huang J, Mandelbaum A, Zhang H, Zhang J (2015) Refined models for efficiency-driven queues with applications to delay announcements and staffing. Working paper, The Chinese University of Hong Kong, Hong Kong.Google Scholar
• Ibrahim R, Whitt W (2009) Real-time delay estimation in overloaded multiserver queues with abandonments. Management Sci. 55(10):1729–1742.Link, Google Scholar
• Ibrahim R, Whitt W (2011) Real-time delay estimation based on delay history in many-server queues with time-varying arrivals. Production Oper. Management 20(5):654–667.Crossref, Google Scholar
• Jennings O, Mandelbaum A, Massey W, Whitt W (1996) Server staffing to meet time-varying demand. Management Sci. 42(10):1383–1394.Link, Google Scholar
• Jouini O, Akşin Z, Dallery Y (2011) Call centers with delay information: Models and insights. Manufacturing Service Oper. Management 13(4):534–548.Link, Google Scholar
• Jouini O, Akşin Z, Karaesmen F, Aguir MS, Dallery Y (2015) Call center delay announcement using a newsvendor-like performance criterion. Production Oper. Management 24(4):587–604.Crossref, Google Scholar
• Kang W, Ramanan K (2010) Fluid limits of many-server queues with reneging. Ann. Appl. Probab. 20(6):2204–2260.Crossref, Google Scholar
• Little J, Graves SC (2008) Little’s law. Chhajed D, Lowe TJ, eds. Building Intuition (Springer Science + Business Media, New York), 81–100.Crossref, Google Scholar
• Mandelbaum A, Zeltyn S (2013) Data stories about (im)patient customers in tele-queues. Queueing Systems 75(2–4):115–146.Crossref, Google Scholar
• Pang G, Talreja R, Whitt W (2007) Martingale proofs of many-server heavy-traffic limits for Markovian queues. Probab. Surveys 4:193–267.Crossref, Google Scholar
• Puhalskii AA (1994) On the invariance principle for the first passage time. Math. Oper. Res. (19):946–954.Link, Google Scholar
• Puhalskii AA, Reiman MI (2000) The multiclass GI/PH/N queue in the Halfin–Whitt regime. Adv. Appl. Probab. 32:564–595.Crossref, Google Scholar
• Reed JE, Tezcan T (2012) Hazard rate scaling for the GI/M/n+GI queue. Oper. Res. 60(4):981–995.Link, Google Scholar
• Reed JE, Ward AR (2008) Approximating the GI/GI/1+GI queue with a nonlinear drift diffusion. Math. Oper. Res. 33(3):606–644.Link, Google Scholar
• Reiman MI (1982) The heavy traffic diffusion approximation for Sojourn times in Jackson networks. Disney RL, Ott TJ, eds. Applied Probability—Computer Science: The Interface, Vol. II (Birhauser, Boston), 409–422.Crossref, Google Scholar
• Senderovich A, Weidlich M, Gal A, Mandelbaum A (2015) Queue mining for delay prediction in multi-class service processes. Inform. Systems 53:278–295.Crossref, Google Scholar
• Talreja R, Whitt W (2009) Heavy-traffic limits for waiting times in many-server queues with abandonment. Ann. Appl. Probab. 19(6):2137–2175.Crossref, Google Scholar
• Whitt W (1999a) Predicting queueing delays. Management Sci. 45(6):870–888.Link, Google Scholar
• Whitt W (1999b) Improving service by informing customers about anticipated delays. Management Sci. 45(2):192–207.Link, Google Scholar
• Whitt W (2002) Stochastic-Process Limits (Springer-Verlag, New York).Crossref, Google Scholar
• Whitt W (2004) Efficiency-driven heavy-traffic approximations for many-server queues with abandonments. Management Sci. 50(10):1449–1461.Link, Google Scholar
• Whitt W (2006) Fluid models for multiserver queues with abandonments. Oper. Res. 54(1):37–54.Link, Google Scholar
• Yu Q, Allon G, Bassamboo A (2017) How do delay announcements shape customer behavior? An empirical study. Management Sci. 63(1):1–20.Link, Google Scholar
• Zhang J (2013) Fluid models of many-server queues with abandonment Queueing Systems 73(2):147–193.Crossref, Google Scholar