Chasing Demand: Learning and Earning in a Changing Environment

Published Online:https://doi.org/10.1287/moor.2016.0807

References

  • Araman V, Caldentey R (2009) Dynamic pricing for nonperishable products with demand learning. Oper. Res. 57(5):1169–1188.LinkGoogle Scholar
  • Aviv Y, Pazgal A (2005) A partially observed Markov decision process for dynamic pricing. Management Sci. 51(9):1400–1416.LinkGoogle Scholar
  • Balvers R, Cosimano T (1990) Actively learning about demand and the dynamics of price adjustment. Econom. J. 100(402):882–898.Google Scholar
  • Beck G, Wieland V (2002) Learning and control in a changing economic environment. J. Econom. Dynam. Control 26(9):1359–1377.CrossrefGoogle Scholar
  • Benveniste A, Métivier M, Priouret P (1990) Adaptive Algorithms and Stochastic Approximations (Springer, Berlin).CrossrefGoogle Scholar
  • Besbes O, Zeevi A (2009) Dynamic pricing without knowing the demand function: Risk bounds and near-optimal algorithms. Oper. Res. 57(6):1407–1420.LinkGoogle Scholar
  • Besbes O, Zeevi A (2011) On the minimax complexity of pricing in a changing environment. Oper. Res. 59(1):66–79.LinkGoogle Scholar
  • Besbes O, Zeevi A (2015) On the (surprising) sufficiency of linear models for dynamic pricing with demand learning. Management Sci. 61(4):723–739.LinkGoogle Scholar
  • Besbes O, Gur Y, Zeevi A (2015) Non-stationary stochastic optimization. Oper. Res. 63(5):1227–1244.LinkGoogle Scholar
  • Broder J, Rusmevichientong P (2012) Dynamic pricing under a general parametric choice model. Oper. Res. 60(4):965–980.LinkGoogle Scholar
  • Brown R (1956) Exponential smoothing for predicting demand. Presented at the 10th National Meeting of the Operations Research Society of America, November 16, Operations Research Society of America, Providence, RI.Google Scholar
  • Chen Y, Farias V (2013) Simple policies for dynamic pricing with imperfect forecasts. Oper. Res. 61(3):612–624.LinkGoogle Scholar
  • den Boer A (2015) Tracking the market: Dynamic pricing and learning in a changing environment. Eur. J. Oper. Res. 247(3):914–927.CrossrefGoogle Scholar
  • den Boer A, Zwart B (2014a) Mean square convergence rates for maximum quasi-likelihood estimators. Stochastic Systems 4(2):375–403.LinkGoogle Scholar
  • den Boer A, Zwart B (2014b) Simultaneously learning and optimizing using controlled variance pricing. Management Sci. 60(3):770–783.LinkGoogle Scholar
  • Farias V, van Roy B (2010) Dynamic pricing with a prior on market response. Oper. Res. 58(1):16–29.LinkGoogle Scholar
  • Garivier A, Moulines E (2011) On upper-confidence bound policies for switching bandit problems. Kivinen J, Szepesvari C, Ukkonen E, Zeugmann T, eds. Proc. 22nd Internat. Conf. Algorithmic Learning Theory (ALT) (Springer, Berlin), 174–188.CrossrefGoogle Scholar
  • Harrison J, Sunar N (2015) Investment timing with incomplete information and multiple means of learning. Oper. Res. 63(2):442–457.LinkGoogle Scholar
  • Harrison J, Keskin N, Zeevi A (2012) Bayesian dynamic pricing policies: Learning and earning under a binary prior distribution. Management Sci. 58(3):570–586.LinkGoogle Scholar
  • Holt C (1957) Forecasting seasonals and trends by exponentially weighted moving averages. Memorandum 52, Office of Naval Research, U.S. Department of the Navy, Washington, DC.Google Scholar
  • Keller G, Rady S (1999) Optimal experimentation in a changing environment. Rev. Econom. Stud. 66(3):475–507.CrossrefGoogle Scholar
  • Keskin N, Zeevi A (2014) Dynamic pricing with an unknown demand model: Asymptotically optimal semi-myopic policies. Oper. Res. 62(5):1142–1167.LinkGoogle Scholar
  • Lai T (1995) Sequential changepoint detection in quality control and dynamical systems. J. Roy. Statist. Soc. Ser. B (Methodological) 57(4):613–658.Google Scholar
  • Lai T (2003) Stochastic approximation. Ann. Statist. 31(2):391–406.CrossrefGoogle Scholar
  • Lobo M, Boyd S (2003) Pricing and learning with uncertain demand. Working paper, Stanford University, Stanford, CA.Google Scholar
  • Phillips R (2005) Pricing and Revenue Optimization (Stanford University Press, Stanford, CA).CrossrefGoogle Scholar
  • Rusmevichientong P, Tsitsiklis J (2010) Linearly parameterized bandits. Math. Oper. Res. 35(2):395–411.LinkGoogle Scholar
  • Rustichini A, Wolinsky A (1995) Learning about variable demand in the long run. J. Econom. Dynam. Control 19(5):1283–1292.CrossrefGoogle Scholar
  • Shiryaev A (2010) Quickest detection problems: Fifty years later. Sequential Anal. 29(4):345–385.CrossrefGoogle Scholar
  • Tsybakov A (2009) Introduction to Nonparametric Estimation (Springer, New York).CrossrefGoogle Scholar
  • Wang Z, Deng S, Ye Y (2014) Close the gaps: A learning-while-doing algorithm for a class of single-product revenue management problems. Oper. Res. 62(2):318–331.LinkGoogle Scholar
  • Winters P (1960) Forecasting sales by exponentially weighted moving averages. Management Sci. 6(3):324–342.LinkGoogle 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.