Technical Note—Data-Based Dynamic Pricing and Inventory Control with Censored Demand and Limited Price Changes

References

• Araman VF, Caldentey R (2009) Dynamic pricing for nonperishable products with demand learning. Oper. Res. 57(5):1169–1188.Link, Google Scholar
• Aviv Y, Pazgal A (2005) A partially observed Markov decision process for dynamic pricing. Management Sci. 51(9):1400–1416.Link, Google Scholar
• Basu AP, Ghosh JK (1980) Asymptotic properties of a solution to the likelihood equation with life-testing applications. J. Amer. Statist. Assoc. 75(370):410–414.Google 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.Link, Google 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.Link, Google Scholar
• Bhattacharyya GK (1985) The asymptotics of maximum likelihood and related estimators based on type II censored data. J. Amer. Statist. Assoc. 80(390):398–404.Crossref, Google Scholar
• Borovkov A (1998) Mathematics Statistics (Gordon and Breach Science Publishers, Amsterdam).Google Scholar
• Broder J (2011) Online algorithms for revenue management. Unpublished doctoral thesis. Cornell University, Ithaca.Google Scholar
• Broder J, Rusmevichientong P (2012) Dynamic pricing under a general parametric choice model. Oper. Res. 60(4):965–980.Link, Google Scholar
• Burnetas AN, Smith CE (2000) Adaptive ordering and pricing for perishable products. Oper. Res. 48(3):436–443.Link, Google Scholar
• Chen B, Chao X (2019) Parametric demand learning with limited price explorations in a backlog stochastic inventory system. IISE Trans. 51(6):605–613.Google Scholar
• Chen B, Chao X, Ahn HS (2019) Coordinating pricing and inventory replenishment with nonparametric demand learning. Oper. Res. 67(4):1035–1052.Google Scholar
• Chen L, Plambeck E (2008) Dynamic inventory management with learning about the demand distribution and substitution probability. Manufacturing Service Oper. Management 10(2):236–256.Link, Google Scholar
• Chen Q, Jasin S, Duenyas I (2019) Nonparametric self-adjusting control for joint learning and optimization of multi-product pricing with finite resource capacity. Math. Oper. Res. 44(2): 601–631.Google Scholar
• Cheung WH, Simchi-Levi D, Wang H (2017) Dynamic pricing and demand learning with limited price experimentation. Oper. Res. 65(6):1722–1731.Link, Google Scholar
• den Boer A, Zwart B (2013) Simultaneously learning and optimizing using controlled variance pricing. Management Sci. 60(3):770–783.Link, Google Scholar
• Ding X, Puterman ML, Bisi A (2002) The censored newsvendor and the optimal acquisition of information. Oper. Res. 50(3):517–527.Link, Google Scholar
• Farias VF, van Roy B (2010) Dynamic pricing with a prior on market response. Oper. Res. 58(1):16–29.Link, Google Scholar
• Greene W (2004) The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects. Econom. J. 7(1):98–119.Crossref, Google Scholar
• Harrison JM, Keskin NB, Zeevi A (2012) Bayesian dynamic pricing policies: Learning and earning under a binary prior distribution. Management Sci. 58(3):570–586.Link, Google Scholar
• Huh WT, Rusmevichientong P (2009) A non-parametric asymptotic analysis of inventory planning with censored demand. Math. Oper. Res. 34(1):103–123.Link, Google Scholar
• Huh WT, Levi R, Rusmevichientong P, Orlin JB (2011) Adaptive data-driven inventory control with censored demand based on Kaplan-Meier estimator. Oper. Res. 59(4):929–941.Link, Google Scholar
• Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J. Amer. Statist. Assoc. 53(282):457–481.Crossref, Google Scholar
• Keskin NB, Zeevi A (2014) Dynamic pricing with an unknown demand model: Asymptotically optimal semi-myopic policies. Oper. Res. 62(5):1142–1167.Link, Google Scholar
• Lariviere MA, Porteus EL (1999) Stalking information: Bayesian inventory management with unobserved lost sales. Management Sci. 45(3):346–363.Link, Google Scholar
• Levi R, Roundy RO, Shmoys DB (2007) Provably near-optimal sampling-based policies for stochastic inventory control models. Math. Oper. Res. 32(4):821–839.Link, Google Scholar
• Lovejoy WS (1990) Myopic policies for some inventory models with uncertain demand distributions. Management Sci. 36(6):724–738.Link, Google Scholar
• Murray GR, Silver EA (1966) A Bayesian analysis of the style goods inventory problem. Management Sci. 12(11):785–797.Link, Google Scholar
• Petruzzi NC, Dada M (2002) Dynamic pricing and inventory control with learning. Naval Res. Logistics 49:303–325.Crossref, Google Scholar
• Scarf HE (1959) Bayes solution to the statistical inventory problem. Ann. Math. Statist. 30(2):490–508.Crossref, Google Scholar
• Scarf HE (1960) Some remarks on Bayes solutions to the inventory problem. Naval Res. Logistics Quart. 7:591–596.Crossref, Google Scholar
• Sen PK (1976) Weak convergence of progressively censored likelihood ratio statistics and its role in asymptotic theory of life testing. Ann. Statist. 4(6):1247–1257.Crossref, Google Scholar
• Sobel M (1981) Myopic solutions of Markov decision processes and stochastic games. Oper. Res. 29:995–1009.Link, Google Scholar
• Subrahmanyan S, Shoemaker S (1996) Developing optimal pricing and inventory policies for retailers who face uncertain demand. J. Retailing 72(1):7–30.Crossref, Google Scholar
• Zeng D, Lin DY (2007) Maximum likelihood estimation in semiparametric regression models with censored data. J. Royal Statist. Soc.: Ser. B Statist. Methodology 69(4):507–564.Crossref, Google Scholar
• Zeng D, Lin DY, Yin G (2005) Maximum likelihood estimation for the proportional odds model with random effects. J. Amer. Statist. Assoc. 100(470):470–483.Crossref, Google Scholar