The Click-Based MNL Model: A Framework for Modeling Click Data in Assortment Optimization

References

• Alon N, Spencer JH (2016) The Probabilistic Method, 4th ed. (John Wiley & Sons, Inc., Hoboken, NJ).Google Scholar
• Aouad A, Segev D (2021) Display optimization for vertically differentiated locations under Multinomial Logit preferences. Management Sci. 67(6):3519–3550.Link, Google Scholar
• Aouad A, Farias V, Levi R (2021) Assortment optimization under consider-then-choose choice models. Management Sci. 67(6):3368–3386.Link, Google Scholar
• Blanchet J, Gallego G, Goyal V (2016) A Markov chain approximation to choice modeling. Oper. Res. 64(4):886–905.Link, Google Scholar
• Chapelle O, Zhang Y (2009) A dynamic Bayesian network click model for web search ranking. Proc. 18th Internat. Conf. World Wide Web (ACM, New York), 1–10.Google Scholar
• Chu LY, Nazerzadeh H, Zhang H (2020) Position ranking and auctions for online marketplaces. Management Sci. 66(8):3617–3634.Link, Google Scholar
• Crompton JL, Ankomah PK (1993) Choice set propositions in destination decisions. Ann. Tour. Res. 20(3):461–476.Crossref, 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. 68(6):4024–4041.Link, Google Scholar
• Désir A, Goyal V, Zhang J (2022) Technical note – Capacitated assortment optimization: Hardness and approximation. Oper. Res. 70(2):893–904.Link, Google Scholar
• Feldman J, Topaloglu H (2015) Bounding optimal expected revenues for assortment optimization under mixtures of Multinomial Logits. Production Oper. Management 24(10):1598–1620.Crossref, Google Scholar
• Feldman J, Topaloglu H (2018) Capacitated assortment optimization under the Multinomial Logit model with nested consideration sets. Oper. Res. 66(2):380–391.Link, Google Scholar
• Gallego G, Li A (2017) Attention, consideration then selection choice model. Working paper, University of Hong Kong, Shenzhen, China.Google Scholar
• Gallego G, Li A, Truong VA, Wang X (2020) Approximation algorithms for product framing and pricing. Oper. Res. 68(1):134–160.Link, Google Scholar
• Gao X, Jasin S, Najafi S, Zhang H (2022) Joint learning and optimization for multi-product pricing (and ranking) under a general cascade click model. Management Sci. 68(10):7362–7382.Link, Google Scholar
• Hauser JR (1978) Testing the accuracy, usefulness, and significance of probabilistic choice models: An information-theoretic approach. Oper. Res. 26(3):406–421.Link, Google Scholar
• Honhon D, Jonnalagedda S, Pan XA (2012) Optimal algorithms for assortment selection under ranking-based consumer choice models. Manufacturing Service Oper. Management 14(2):279–289.Link, Google Scholar
• Howard JA, Sheth JN (1969) The Theory of Buyer Behavior (Wiley, New York).Google Scholar
• Jagabathula S, Rusmevichientong P (2016) A nonparametric joint assortment and price choice model. Management Sci. 63(9):3128–3145.Link, Google Scholar
• Jeuland AP (1979) Brand choice inertia as one aspect of the notion of brand loyalty. Management Sci. 25(7):671–682.Link, Google Scholar
• Karp RM (1972) Reducibility Among Combinatorial Problems. Complexity of Computer Computations (Springer, Boston), 85–103.Crossref, Google Scholar
• Laudon KC, Traver CG (2013) E-Commerce (Pearson, London).Google Scholar
• Le Cam L (1960) An approximation theorem for the Poisson binomial distribution. Pacific J. Math. 10(4):1181–1197.Crossref, Google Scholar
• Lim J (2016) Alibaba group FY2016 revenue jumps 33%, EBITDA up 28%. Forbes (May 5), https://www.forbes.com/sites/jlim/2016/05/05/alibaba-fy2016-revenue-jumps-33-ebitda-up-28/#5f15a05f53b2.Google Scholar
• Lo V, Topaloglu H (2019) Assortment optimization under the Multinomial Logit model with product synergies. Oper. Res. Lett. 47(6):546–552.Crossref, Google Scholar
• Luce RD (1959) Individual choice behavior: A theoretical analysis. Frontiers Econometrics 2:105–142.Google Scholar
• Manzini P, Mariotti M (2014) Stochastic choice and consideration sets. Econometrica 82(3):1153–1176.Crossref, Google Scholar
• McFadden D (1974) Conditional logit analysis of qualitative choice behavior. Frontiers Econometrics 2:105–142.Google Scholar
• Montgomery AL, Li S, Srinivasan K, Liechty JC (2004) Modeling online browsing and path analysis using clickstream data. Marketing Sci. 23(4):579–595.Link, Google Scholar
• Richardson M, Dominowska E, Ragno R (2007) Predicting clicks: Estimating the click-through rate for new ads. Proc. 16th Internat. Conf. World Wide Web (ACM, New York), 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
• 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.Crossref, Google Scholar
• Shaked M, Shanthikumar JG (2007) Stochastic Orders (Springer Science & Business Media, New York).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(24):15–33.Link, Google Scholar
• Vazirani VV (2013) Approximation Algorithms (Springer Science & Business Media, Heidelberg, Germany).Google Scholar
• Wang R, Sahin O (2017) The impact of consumer search cost on assortment planning and pricing. Management Sci. 64(8):3469–3970.Google Scholar
• Zhu ZA, Chen W, Minka T, Zhu C, Chen Z (2010) A novel click model and its applications to online advertising. Proc. Third ACM Internat. Conf. Web Search Data Mining (ACM, New York), 321–330.Google Scholar