Assortment Optimization and Pricing Under the Multinomial Logit Model with Impatient Customers: Sequential Recommendation and Selection

Published Online:https://doi.org/10.1287/opre.2021.2127

References

  • Aouad A, Segev D (2018) Display optimization for vertically differentiated locations under multinomial logit preferences. Technical report, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
  • Aouad A, Farias V, Levi R (2016) Assortment optimization under consider-then-choose choice models. Technical report, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
  • Aouad A, Feldman J, Segev D, Zhang DJ (2019) Click-based MNL: Algorithmic frameworks for modeling click data in assortment optimization. Technical report, Washington University, St. Louis, MO.Google Scholar
  • Blanchet J, Gallego G, Goyal V (2016) A Markov chain approximation to choice modeling. Oper. Res. 64(4):886–905.LinkGoogle Scholar
  • Boyd S, Vandenberghe L (2004) Convex Optimization (Cambridge University Press, Cambridge, UK).CrossrefGoogle Scholar
  • Bront JJM, Mendez Diaz I, Vulcano G (2009) A column generation algorithm for choice-based network revenue management. Oper. Res. 57(3):769–784.LinkGoogle Scholar
  • Davis JM, Gallego G, Topaloglu H (2014) Assortment optimization under variants of the nested logit model. Oper. Res. 62(2):250–273.LinkGoogle Scholar
  • Derakhshan M, Golrezaei N, Manhshadi V, Mirrokni V (2018) Product ranking on online platforms. Technical report, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
  • Desir A, Goyal V, Zhang J (2016a) Near-optimal algorithms for capacity constrained assortment optimization. Technical report, Columbia University, New York.Google Scholar
  • Desir A, Goyal V, Jagabathula S, Segev D (2016b) Assortment Optimization Under the Mallows Model. Lee DD, Sugiyama M, Luxburg UV, Guyon I, Garnett R, eds. Advances in Neural Information Processing Systems, vol. 29 (Curran Associates, Inc.), 4700–4708.Google Scholar
  • Farias VF, Jagabathula S, Shah D (2013) A non-parametric approach to modeling choice with limited data. Management Sci. 59(2):305–322.AbstractGoogle Scholar
  • Feldman J, Segev D (2019) Improved approximation schemes for MNL-driven sequential assortment optimization. Technical report, Washington University, St. Louis, MO.Google Scholar
  • Feldman J, Paul A, Topaloglu H (2019) Assortment optimization with small consideration sets. Oper. Res. 67(5):1283–1299.LinkGoogle Scholar
  • Flores A, Berbeglia G, van Hentenryck P (2019) Assortment optimization under the sequential multinomial logit model. Eur. J. Oper. Res. 273(3):1052–1064.CrossrefGoogle Scholar
  • Gallego G, Wang R (2014) Multi-product price optimization and competition under the nested attraction model. Oper. Res. 62(2):450–461.LinkGoogle Scholar
  • Gallego G, Iyengar G, Phillips R, Dubey A (2004) Managing flexible products on a network. CORC Technical Report TR-2004-01.Google Scholar
  • Gallego G, Li A, Truong VA, Wang X (2021) Approximation algorithms for product framing and pricing. Oper. Res. Forthcoming.Google Scholar
  • Goulden CH (1939) Methods of Statistical Analysis (John Wiley & Sons, New York).Google Scholar
  • Hopp WJ, Xu X (2005) Product line selection and pricing with modularity in design. Manufacturing Service Oper. Management 7(3):172–187.LinkGoogle Scholar
  • Jagabathula S (2016) Assortment optimization under general choice. Technical report, New York University.Google Scholar
  • James G, Witten D, Hastie T, Tibshirani R (2014) An Introduction to Statistical Learning (Springer, New York).Google Scholar
  • Kaggle (2013) Personalize Expedia hotel searches. Accessed August 5, 2019, https://www.kaggle.com/c/expedia-personalized-sort.Google Scholar
  • Li H, Huh WT (2011) Pricing multiple products with the multinomial logit and nested models: Concavity and implications. Manufacturing Service Oper. Management 13(4):549–563.LinkGoogle Scholar
  • Li H, Webster S (2017) Optimal pricing of correlated product options under the paired combinatorial logit model. Oper. Res. 65(5):1215–1230.LinkGoogle Scholar
  • Liu N, Ma Y, Topaloglu H (2021) Assortment optimization under the multinomial logit model with sequential offerings. INFORMS J. Comput. Forthcoming.Google Scholar
  • Mendez-Diaz I, Bront JJM, Vulcano G, Zabala P (2014) A branch-and-cut algorithm for the latent-class logit assortment problem. Discrete Appl. Math. 164(1):246–263.CrossrefGoogle Scholar
  • Rusmevichientong P, Shen Z-JM, Shmoys DB (2009) A PTAS for capacitated sum-of-ratios optimization. Oper. Res. Lett. 37(4):230–238.CrossrefGoogle Scholar
  • Rusmevichientong P, Shen Z-JM, Shmoys DB (2010) Dynamic assortment optimization with a multinomial logit choice model and capacity constraint. Oper. Res. 58(6):1666–1680.LinkGoogle Scholar
  • Rusmevichientong P, Shmoys D, Tong C, Topaloglu H (2014) Assortment optimization under the multinomial logit model with random choice parameters. Production Oper. Management 23(11):2023–2039.CrossrefGoogle Scholar
  • Song J-S, Xue Z (2007) Demand management and inventory control for substitutable products. Technical report, Duke University, Durham, NC.Google Scholar
  • Sumida M, Gallego G, Rusmevichientong P, Topaloglu H, Davis JM (2019) Revenue-utility tradeoff in assortment optimization under the multinomial logit model with totally unimodular constraints. Technical report, Cornell University, Ithaca, NY.Google Scholar
  • Talluri K, van Ryzin GJ (2004) Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50(1):15–33.LinkGoogle Scholar
  • Talluri KT, van Ryzin GJ (2005) The Theory and Practice of Revenue Management (Kluwer Academic Publishers, Boston).CrossrefGoogle Scholar
  • Vulcano G, van Ryzin GJ, Ratliff R (2012) Estimating primary demand for substitutable products from sales transaction data. Oper. Res. 60(2):313–334.LinkGoogle Scholar
  • Wang R (2012) Capacitated assortment and price optimization under the multinomial logit model. Oper. Res. Lett. 40(6):492–497.CrossrefGoogle Scholar
  • Wang R, Sahin O (2018) The impact of consumer search cost on assortment planning and pricing. Management Sci. 64(8):3649–3666.LinkGoogle Scholar
  • Williamson DP, Shmoys DB (2011) The Design of Approximation Algorithms (Cambridge University Press).CrossrefGoogle Scholar
  • Zhang D, Lu Z (2013) Assessing the value of dynamic pricing in network revenue management. INFORMS J. Comput. 25(1):102–115.LinkGoogle Scholar
  • Zhang H, Rusmevichientong P, Topaloglu H (2018) Technical note: Multiproduct pricing under the generalized extreme value models with homogeneous price sensitivity parameters. Oper. Res. 66(6):1559–1570.LinkGoogle Scholar
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