Display Optimization for Vertically Differentiated Locations Under Multinomial Logit Preferences

References

• Abadi M , Barham P , Chen J , Chen Z , Davis A , Dean J , Devin M , et al. . (2016) Tensorflow: A system for large-scale machine learning. 12th Sympos. Operating Systems Design Implementation, Savannah, GA, 265–283.Google Scholar
• 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.Google Scholar
• Agarwal A , Hosanagar K , Smith MD (2011) Location, location, location: An analysis of profitability of position in online advertising markets. J. Marketing Res. 48(6):1057–1073.Crossref, Google Scholar
• Aouad A , Farias V , Levi R (2020) Assortment optimization under consider-then-rank choice models. Management Sci. Forthcoming.Google Scholar
• Ben-Akiva ME , Lerman SR (1985) Discrete Choice Analysis: Theory and Application to Travel Demand (MIT Press, Cambridge, MA).Google Scholar
• Bettman JR , Luce MF , Payne JW (1998) Constructive consumer choice processes. J. Consumer Res. 25(3):187–217.Crossref, Google Scholar
• Blanchet JH , Gallego G , Goyal V (2016) A Markov chain approximation to choice modeling. Oper. Res. 64(4):886–905.Link, Google Scholar
• Breugelmans E , Campo K , Gijsbrechts E (2007) Shelf sequence and proximity effects on online grocery choices. Marketing Lett. 18(1–2):117–133.Crossref, Google Scholar
• Bront JJM , Méndez-Diaz I , Vulcano G (2009) A column generation algorithm for choice-based network revenue management. Oper. Res. 57(3):769–784.Link, Google Scholar
• Chandon P , Hutchinson JW , Bradlow ET , Young SH (2009) Does in-store marketing work? Effects of the number and position of shelf facings on brand attention and evaluation at the point of purchase. J. Marketing 73(6):1–17.Crossref, Google Scholar
• Chandukala SR , Kim J , Allenby GM , Otter T (2008) Choice Models in Marketing: Economic Assumptions, Challenges and Trends (Now Publishers Inc., Delft, Netherlands).Google Scholar
• Davis JM , Gallego G , Topaloglu H (2013) Assortment planning under the multinomial logit model with totally unimodular constraint structures. Working paper, Cornell University, Ithaca, NY.Google Scholar
• Davis JM , Gallego G , Topaloglu H (2014) Assortment optimization under variants of the nested logit model. Oper. Res. 62(2):250–273.Link, Google Scholar
• Davis JM , Topaloglu H , Williamson DP (2015) Assortment optimization over time. Oper. Res. Lett. 43:608–611.Crossref, Google Scholar
• Désir A , Goyal V , Zhang J (2014) Near-optimal algorithms for capacity constrained assortment optimization. Working paper, Columbia University, New York.Google Scholar
• Dreze X , Hoch SJ , Purk ME (1995) Shelf management and space elasticity. J. Retailing 70(4):301–326.Crossref, Google Scholar
• Farias V , Jagabathula S , Shah D (2013) A non-parametric approach to modeling choice with limited data. Management Sci. 59(2):305–322.Link, Google Scholar
• Feldman J , Topaloglu H (2017) Capacitated assortment optimization under the multinomial logit model with nested consideration sets. Oper. Res. 66(2):380–391.Link, Google Scholar
• Feldman J , Zhang D , Liu X , Zhang N (2018) Taking assortment optimization from theory to practice: Evidence from large field experiments on Alibaba. Working paper, Washington University, St. Louis.Google Scholar
• Feldman JB , 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
• Ford LR (1957) Solution of a ranking problem from binary comparisons. Amer. Math. Monthly 64(8):28–33.Crossref, Google Scholar
• Frank RE , Massy WF (1970) Shelf position and space effects on sales. J. Marketing Res. 7(1):59–66.Crossref, 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
• Ghose A , Yang S (2009) An empirical analysis of search engine advertising: Sponsored search in electronic markets. Management Sci. 55(10):1605–1622.Link, Google Scholar
• Ghose A , Ipeirotis PG , Li B (2014) Examining the impact of ranking on consumer behavior and search engine revenue. Management Sci. 60(7):1632–1654.Link, Google Scholar
• Grover R , Vriens M (2006) The Handbook of Marketing Research: Uses, Misuses, and Future Advances (Sage Publications, Thousand Oaks, CA).Crossref, Google Scholar
• Guadagni PM , Little JD (1983) A logit model of brand choice calibrated on scanner data. Marketing Sci. 2(3):203–238.Link, Google Scholar
• Hauser JR (2014) Consideration-set heuristics. J. Bus. Res. 67(8):1688–1699.Crossref, Google Scholar
• Hauser JR , Wernerfelt B (1990) An evaluation cost model of consideration sets. J. Consumer Res. 16(4):393–408.Crossref, Google Scholar
• Hausman J , McFadden D (1984) Specification tests for the multinomial logit model. Econometrica 52(5):1219–1240.Crossref, Google Scholar
• Jerath K , Ma L , Park YH , Srinivasan K (2011) A “position paradox” in sponsored search auctions. Marketing Sci. 30(4):612–627.Link, Google Scholar
• Jeziorski P , Segal I (2015) What makes them click: Empirical analysis of consumer demand for search advertising. Amer. Econom. J. Microeconom. 7(3):24–53.Crossref, Google Scholar
• Kempe D , Mahdian M (2008) A cascade model for externalities in sponsored search. Papadimitriou C, Zhang S, eds. Internet and Network Economics (WINE 2008), Lecture Notes in Computer Science, vol. 5385 (Springer, Berlin, Heidelberg), 585–596.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
• Luce RD (1959) Individual Choice Behavior: A Theoretical Analysis (John Wiley & Sons, Hoboken, NJ).Google Scholar
• McFadden D (1973) Conditional logit analysis of qualitative choice behavior. Zarembka P, ed. Frontiers Econometrics (Wiley, New York), 105–142.Google Scholar
• McFadden D (1980) Econometric models for probabilistic choice among products. J. Bus. 53(3):S13–S29.Crossref, Google Scholar
• McFadden D , Tye WB , Train K (1977) An application of diagnostic tests for the independence from irrelevant alternatives property of the multinomial logit model. Technical report, Institute of Transportation Studies, University of California, Berkeley.Google Scholar
• Mehta N , Rajiv S , Srinivasan K (2003) Price uncertainty and consumer search: A structural model of consideration set formation. Marketing Sci. 22(1):58–84.Link, Google Scholar
• Méndez-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.Crossref, Google Scholar
• Narayanan S , Kalyanam K (2015) Position effects in search advertising and their moderators: A regression discontinuity approach. Marketing Sci. 34(3):388–407.Link, Google Scholar
• Negahban S , Oh S , Shah D (2012) Iterative ranking from pair-wise comparisons. Pereira F, Burges CJC, Bottou L, Weinberger KQ, eds. Advances in Neural Information Processing Systems, vol. 25 (Curran Associates, Red Hook, NY), 2474–2482.Google Scholar
• Payne JW (1976) Task complexity and contingent processing in decision making: An information search and protocol analysis. Organ. Behav. Human Performance 16(2):366–387.Crossref, Google Scholar
• Plackett RL (1975) The analysis of permutations. J. Royal Statist. Soc. Ser. C: Appl. Statist. 24(2):193–202.Google Scholar
• Rusmevichientong P , Topaloglu H (2012) Robust assortment optimization in revenue management under the multinomial logit choice model. Oper. Res. 60(4):865–882.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
• 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
• Shocker AD , Ben-Akiva M , Boccara B , Nedungadi P (1991) Consideration set influences on consumer decision-making and choice: Issues, models, and suggestions. Marketing Lett. 2(3):181–197.Crossref, Google Scholar
• Silk AJ , Urban GL (1978) Pre-test-market evaluation of new packaged goods: A model and measurement methodology. J. Marketing Res. 15(2):171–191.Crossref, 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, MA). Crossref, Google Scholar
• Tversky A , Kahneman D (1981) The framing of decisions and the psychology of choice. Science 211(4481):453–458.Crossref, Google Scholar
• Tversky A , Kahneman D (1986) Rational choice and the framing of decisions. J. Bus. 59(4.2):S251–S278.Google Scholar
• Ursu RM (2018) The power of rankings: Quantifying the effect of rankings on online consumer search and purchase decisions. Marketing Sci. 37(4):530–552.Link, Google Scholar
• Wu J , Rangaswamy A (2003) A fuzzy set model of search and consideration with an application to an online market. Marketing Sci. 22(3):411–434.Link, Google Scholar
• Xiong C , Wang T , Ding W , Shen Y , Liu TY (2012) Relational click prediction for sponsored search. Proc. 5th ACM Internat. Conf. Web Search Data Mining (ACM, New York), 493–502.Google Scholar
• Xu W , Manavoglu E , Cantu-Paz E (2010) Temporal click model for sponsored search. Proc. 33rd Internat. ACM SIGIR Conf. Res. Development Inform. Retrieval (ACM, New York), 106–113.Google Scholar
• Yang S , Ghose A (2010) Analyzing the relationship between organic and sponsored search advertising: Positive, negative, or zero interdependence? Marketing Sci. 29(4):602–623.Link, Google Scholar