Technical Note—The Multinomial Logit Model with Sequential Offerings: Algorithmic Frameworks for Product Recommendation Displays

References

• Adany R, Feldman M, Haramaty E, Khandekar R, Schieber B, Schwartz R, Shachnai H, Tamir T (2016) All-or-nothing generalized assignment with application to scheduling advertising campaigns. ACM Trans. Algorithms 12(3):1–25.Crossref, Google Scholar
• Aouad A, Segev D (2021) Display optimization for vertically differentiated locations under multinomial logit preferences. Management Sci. 67(6):3519–3550.Google Scholar
• Chekuri C, Khanna S (2005) A polynomial time approximation scheme for the multiple knapsack problem. SIAM J. Comput. 35(3):713–728.Crossref, Google Scholar
• Cohen R, Katzir L, Raz D (2006) An efficient approximation for the generalized assignment problem. Inform. Processing Lett. 100(4):162–166.Crossref, Google Scholar
• Craswell N, Zoeter O, Taylor M, Ramsey B (2008) An experimental comparison of click position-bias models. Najork M, Broder AZ, Chakrabarti S, eds. Proc. 2008 Internat. Conf. Web Search Data Mining (Palo Alto, California), 87–94.Google Scholar
• Davis JM, Topaloglu H, Williamson DP (2015) Assortment optimization over time. Oper. Res. Lett. 43(6):608–611.Crossref, Google Scholar
• Derakhshan M, Golrezaei N, Manshadi V, Mirrokni V (2022) Product ranking on online platforms. Management Sci. Forthcoming.Google Scholar
• Feige U, Vondrák J (2010) The submodular welfare problem with demand queries. Theory Comput. 6(1):247–290.Crossref, Google Scholar
• Feldman J, Zhang D, Liu X, Zhang N (2022) Customer choice models vs. machine learning: Finding optimal product displays on alibaba. Oper. Res. Forthcoming.Google Scholar
• Fleischer L, Goemans MX, Mirrokni VS, Sviridenko M (2011) Tight approximation algorithms for maximum separable assignment problems. Math. Oper. Res. 36(3):416–431.Link, Google 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.Crossref, Google Scholar
• Gallego G, Iyengar G, Phillips R, Dubey A (2004) Managing flexible products on a network. Preprint, submitted April 27, 2020, https://dx.doi.org/10.2139/ssrn.3567371.Google Scholar
• Gallego G, Li A, Truong V, Wang X (2015) Online personalized resource allocation with customer choice. Preprint, submitted November 5, https://arxiv.org/abs/1511.01837.Google Scholar
• Gallego G, Li A, Truong V, Wang X (2020) Approximation algorithms for product framing and pricing. Oper. Res. 68(1):134–160.Link, Google Scholar
• Golrezaei N, Nazerzadeh H, Rusmevichientong P (2014) Real-time optimization of personalized assortments. Management Sci. 60(6):1532–1551.Link, Google Scholar
• Iyengar SS, Lepper MR (2000) When choice is demotivating: Can one desire too much of a good thing? J. Personality Soc. Psych. 79(6):995–1006.Crossref, Google Scholar
• Kaggle (2013) Personalize Expedia hotel searches—ICDM 2013. Accessed August 28, 2013, https://www.kaggle.com/c/expedia-personalized-sort/data.Google Scholar
• Kempe D, Mahdian M (2008) A cascade model for externalities in sponsored search. Papadimitriou CH, Zhang S, eds. Proc. Fourth Internat. Workshop Web Internet Econom., Shanghai, China, 585–596.Google Scholar
• Liu N, Ma Y, Topaloglu H (2020) Assortment optimization under the multinomial logit model with sequential offerings. INFORMS J. Comput. 32(3):835–853.Link, Google Scholar
• MATLAB Optimization Toolbox (2019) Matlab Optimization Toolbox (The MathWorks, Natick, MA).Google Scholar
• Nutov Z, Beniaminy I, Yuster R (2006) A-approximation algorithm for the generalized assignment problem. Oper. Res. Lett. 34(3):283–288.Crossref, Google Scholar
• Richardson M, Dominowska E, Ragno R (2007) Predicting clicks: Estimating the click-through rate for new ads. Williamson CL, Zurko ME, Patel-Schneider PF, Shenoy PJ, eds. Proc. 16th Internat. Conf. World Wide Web, Banff, Alberta, Canada, 521–530.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
• Scheibehenne B, Greifeneder R, Todd PM (2010) Can there ever be too many options? A meta-analytic review of choice overload. J. Consumer Res. 37(3):409–425.Crossref, Google Scholar
• Shmoys DB, Tardos É (1993) An approximation algorithm for the generalized assignment problem. Math. Programming 62:461–474.Crossref, Google Scholar
• Sumida M, Gallego G, Rusmevichientong P, Topaloglu H, Davis J (2021) Revenue-utility tradeoff in assortment optimization under the multinomial logit model with totally unimodular constraints. Management Sci. 67(5):2845–2869.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 K (2009) Discrete Choice Methods with Simulation (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
• Vazirani VV (2003) Approximation Algorithms (Springer Science & Business Media, Atlanta).Crossref, Google Scholar
• Wang R, Sahin O (2017) The impact of consumer search cost on assortment planning and pricing. Management Sci. 64(8):3649–3666.Link, Google Scholar
• Williamson DP, Shmoys DB (2011) The Design of Approximation Algorithms (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar