Joint Assortment Optimization and Discrete Marketing Mix Allocation

References

• Abeliuk A, Berbeglia G, Cebrian M, Van Hentenryck P (2016) Assortment optimization under a multinomial logit model with position bias and social influence. 4OR 14(1):57–75. Crossref, Google Scholar
• Aouad A, Désir A (2025) Representing random utility choice models with neural networks. Management Sci., ePub ahead of print November 17, https://dx.doi.org/10.1287/mnsc.2023.02189.Google Scholar
• Berry ST (1994) Estimating discrete-choice models of product differentiation. RAND J. Econom. 25(2):242–262.Crossref, Google Scholar
• Borden NH (1964) The concept of the marketing mix. J. Advertising Res. 4(2):2–7.Crossref, Google Scholar
• Chen R, Jiang H (2020) Capacitated assortment and price optimization under the nested logit model. J. Global Optim. 77(4):895–918.Crossref, Google Scholar
• Chen X, Li J, Li M, Zhao T, Zhou Y (2022) Assortment optimization under the multivariate mnl model. Preprint, submitted September 30, https://arxiv.org/abs/2209.15220.Google Scholar
• Désir A, Goyal V, Zhang J (2022) Capacitated assortment optimization: Hardness and approximation. Oper. Res. 70(2):893–904.Link, Google Scholar
• Désir A, Goyal V, Segev D, Ye C (2020) Constrained assortment optimization under the Markov chain–based choice model. Management Sci. 66(2):698–721.Link, Google Scholar
• Farrell MH, Liang T, Misra S (2020) Deep learning for individual heterogeneity: An automatic inference framework. Preprint, submitted October 28, https://arxiv.org/abs/2010.14694.Google Scholar
• Feldman J, Zhang DJ, Liu X, Zhang N (2022) Customer choice models vs. machine learning: Finding optimal product displays on alibaba. Oper. Res. 70(1):309–328.Link, Google Scholar
• Frieze AM, Clarke MR (1984) Approximation algorithms for the m-dimensional 0-1 knapsack problem: Worst-case and probabilistic analyses. Eur. J. Oper. Res. 15(1):100–109.Crossref, Google Scholar
• Gallego G, Topaloglu H (2014) Constrained assortment optimization for the nested logit model. Management Sci. 60(10):2583–2601.Link, Google Scholar
• Gallego G, Iyengar G, Phillips R, Dubey A (2004) Managing flexible products on a network. Preprint, submitted April 27, https://doi.org/10.2139/ssrn.3567371.Google Scholar
• Ghuge R, Kwon J, Nagarajan V, Sharma A (2022) Constrained assortment optimization under the paired combinatorial logit model. Oper. Res. 70(2):786–804.Link, Google Scholar
• Goli A, Reiley D, Zhang H (2024) Personalized versioning: Product strategies constructed from experiments on pandora. Marketing Sci. 4(2):327–352.Link, Google Scholar
• Jagabathula S, Rusmevichientong P (2017) A nonparametric joint assortment and price choice model. Management Sci. 63(9):3128–3145.Link, Google Scholar
• Jagpal HS, Brick IE (1982) The marketing mix decision under uncertainty. Marketing Sci. 1(1):79–92.Link, Google Scholar
• Jain L, Li Z, Loghmani E, Mason B, Yoganarasimhan H (2024) Effective adaptive exploration of prices and promotions in choice-based demand models. Marketing Sci. 43(5):1002–1030.Google Scholar
• Li H, Huh WT (2011) Pricing multiple products with the multinomial logit and nested logit models: Concavity and implications. Manufacturing Service Oper. Management 13(4):549–563.Link, Google Scholar
• Li G, Rusmevichientong P, Topaloglu H (2015) The d-level nested logit model: Assortment and price optimization problems. Oper. Res. 63(2):325–342.Link, Google Scholar
• Ma W (2023) When is assortment optimization optimal? Management Sci. 69(4):2088–2105.Link, Google Scholar
• McCarthy EJ, Perreault W (1972) Basic Marketing: A Managerial Approach (Irwin, Homewood, IL).Google Scholar
• Mittal S, Schulz AS (2013) A general framework for designing approximation schemes for combinatorial optimization problems with many objectives combined into one. Oper. Res. 61(2):386–397.Link, Google Scholar
• Rusmevichientong P, Shen ZJM, Shmoys DB (2010) Dynamic assortment optimization with a multinomial logit choice model and capacity constraint. Oper. Res. 58(6):1666–1680.Link, Google Scholar
• Shen M, Tang CS, Wu D, Yuan R, Zhou W (2024) JD.com: Transaction-level data for the 2020 MSOM data driven research challenge. Manufacturing Service Oper. Management 26(1):2–10.Link, Google Scholar
• Talluri K, Van Ryzin G (2004) Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50(1):15–33.Link, Google Scholar
• Train KE (2009) Discrete Choice Methods with Simulation (Cambridge University Press, Cambridge; New York).Crossref, Google Scholar
• Vazirani VV (2001) Approximation Algorithms, vol. 1 (Springer, Berlin, Heidelberg).Google Scholar
• Wang R (2012) Capacitated assortment and price optimization under the multinomial logit model. Oper. Res. Lett. 40(6):492–497.Crossref, Google Scholar
• Wang R (2018) When prospect theory meets consumer choice models: Assortment and pricing management with reference prices. Manufacturing Service Oper. Management 20(3):583–600.Link, Google Scholar
• Wang M, Qi M, Shen ZJM (2023) A learning and optimization framework for personalized product design. Preprint, submitted September 1, https://doi.org/10.2139/ssrn.4554710.Google Scholar
• Williamson DP, Shmoys DB (2011) The Design of Approximation Algorithms (Cambridge University Press, Cambridge; New York).Crossref, Google Scholar
• Zhang H, Rusmevichientong P, Topaloglu H (2020) Assortment optimization under the paired combinatorial logit model. Oper. Res. 68(3):741–761.Link, Google Scholar