Managing Customer Churn via Service Mode Control

Published Online:https://doi.org/10.1287/moor.2021.0179

References

  • [1] Adelman D, Mersereau AJ (2013) Dynamic capacity allocation to customers who remember past service. Management Sci. 59(3):592–612.LinkGoogle Scholar
  • [2] Aflaki S, Popescu I (2014) Managing retention in service relationships. Management Sci. 60(2):415–433.LinkGoogle Scholar
  • [3] Ascarza E, Netzer O, Hardie BGS (2018) Some customers would rather leave without saying goodbye. Marketing Sci. 37(1):54–77.LinkGoogle Scholar
  • [4] Ata B, Harrison JM, Shepp LA (2005) Drift rate control of a Brownian processing system. Ann. Appl. Probab. 15(2):1145–1160.CrossrefGoogle Scholar
  • [5] Atar R, Lev-Ari A (2018) Workload-dependent dynamic priority for the multiclass queue with reneging. Math. Oper. Res. 43(2):494–515.LinkGoogle Scholar
  • [6] Berger PD, Nasr NI (1998) Customer lifetime value: Marketing models and applications. J. Interactive Marketing 12(1):17–30.CrossrefGoogle Scholar
  • [7] Borkar VS (1989) Optimal control of diffusion processes. Pitman Res. Notes Math. 203(36):213–244.Google Scholar
  • [8] Chang SH, Cosman PC, Milstein LB (2011) Chernoff-type bounds for the Gaussian error function. IEEE Trans. Comm. 59(11):2939–2944.CrossrefGoogle Scholar
  • [9] Das Gupta A, Karmarkar US, Roels G (2015) The design of experiential services with acclimation and memory decay: Optimal sequence and duration. Management Sci. 62(5):1278–1296.LinkGoogle Scholar
  • [10] Gaur V, Park Y-H (2007) Asymmetric consumer learning and inventory competition. Management Sci. 53(2):227–240.LinkGoogle Scholar
  • [11] Harrison JM, Sunar N (2015) Investment timing with incomplete information and multiple means of learning. Oper. Res. 63(2):442–457.LinkGoogle Scholar
  • [12] Ho T-H, Park Y-H, Zhou Y-P (2006) Incorporating satisfaction into customer value analysis: Optimal investment in lifetime value. Marketing Sci. 25(3):260–277.LinkGoogle Scholar
  • [13] Johari R, Schmit S (2018) Learning with abandonment. Preprint, submitted February 23, https://arxiv.org/abs/1802.08718.Google Scholar
  • [14] Kahneman D, Wakker PP, Sarin R (1997) Back to Bentham? Explorations of experienced utility. Quart. J. Econom. 112(2):375–406.CrossrefGoogle Scholar
  • [15] Liu Q, van Ryzin G (2011) Strategic capacity rationing when customers learn. Manufacturing Service Oper. Management 13(1):89–107.LinkGoogle Scholar
  • [16] Mirică S (1992) Verification Theorems of Dynamic Programming Type in Optimal Control (Birkhäuser, Basel, Switzerland), 181–191.CrossrefGoogle Scholar
  • [17] Montoya R, Netzer O, Jedidi K (2010) Dynamic allocation of pharmaceutical detailing and sampling for long-term profitability. Marketing Sci. 29(5):909–924.LinkGoogle Scholar
  • [18] Nerlove M, Arrow KJ (1962) Optimal advertising policy under dynamic conditions. Economica 29(114):129–142.CrossrefGoogle Scholar
  • [19] Netzer O, Lattin JM, Srinivasan V (2008) A hidden Markov model of customer relationship dynamics. Marketing Sci. 27(2):185–204.LinkGoogle Scholar
  • [20] Ormeci Matoglu M, Vande Vate J (2011) Drift control with changeover costs. Oper. Res. 59(2):427–439.LinkGoogle Scholar
  • [21] Ormeci Matoglu M, Vande Vate J, Wang H (2015) Solving the drift control problem. Stochastic Systems 5(2):324–371.LinkGoogle Scholar
  • [22] Ovchinnikov A, Milner JM (2012) Revenue management with end-of-period discounts in the presence of customer learning. Production Oper. Management 21(1):69–84.CrossrefGoogle Scholar
  • [23] Pinelis I (2006) On L’Hospital-type rules for monotonicity. J. Inequalities Pure Appl. Math. 7(2):1–19.Google Scholar
  • [24] Radner R, Shepp L (1996) Risk vs. profit potential: A model for corporate strategy. J. Econom. Dynamic Control 20(8):1373–1393.CrossrefGoogle Scholar
  • [25] Reed J, Ward A, Zhan D (2013) On the generalized drift Skorokhod problem in one dimension. J. Appl. Probab. 50(1):16–28.CrossrefGoogle Scholar
  • [26] Ren C, MacKenzie AR (2007) Closed-form approximations to the error and complementary error functions and their applications in atmospheric science. Atmospheric Sci. Lett. 8(3):70–73.CrossrefGoogle Scholar
  • [27] Rust RT, Lemon KN, Zeithaml VA (2004) Return on marketing: Using customer equity to focus marketing strategy. J. Marketing 68(1):109–127.CrossrefGoogle Scholar
  • [28] Salins M, Spiliopoulos K (2017) Markov processes with spatial delay: Path space characterization, occupation time and properties. Stochastic Dynamics 17(6):1750042.CrossrefGoogle Scholar
  • [29] Skorokhod AV (1961) Stochastic equations for diffusion processes in a bounded region. Theory Probab. Appl. 6(3):264–274.CrossrefGoogle Scholar
  • [30] Strulovici B, Szydlowski M (2015) On the smoothness of value functions and the existence of optimal strategies in diffusion models. J. Econom. Theory 159(B):1016–1055.CrossrefGoogle Scholar
  • [31] Sunar N, Birge JR, Vitavasiri S (2019) Optimal dynamic product development and launch for a network of customers. Oper. Res. 67(3):770–790.LinkGoogle Scholar
  • [32] Sunar N, Yu S, Kulkarni VG (2021) Competitive investment with Bayesian learning: Choice of business size and timing. Oper. Res. 69(5):1430–1449.LinkGoogle Scholar
  • [33] Thomas MU (1975) Some mean first-passage time approximations for the Ornstein-Uhlenbeck process. J. Appl. Probab. 12(3):600–604.CrossrefGoogle Scholar
  • [34] Touzi N (2002) Stochastic Control Problems, Viscosity Solutions and Application to Finance (Edizioni della Normale).Google Scholar
  • [35] Wang Z, Zenios S (2021) New venture creation: A drift-variance diffusion control model. Oper. Res. 70(5):2982–2997.LinkGoogle Scholar
  • [36] Ward AR, Glynn PW (2003) Properties of the reflected Ornstein–Uhlenbeck process. Queueing Systems 44(2):109–123.CrossrefGoogle Scholar
  • [37] Zeithaml VA (2000) Service quality, profitability, and the economic worth of customers: What we know and what we need to learn. J. Acad. Marketing Sci. 28(1):67–85.CrossrefGoogle Scholar
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