Demand Estimation Under the Multinomial Logit Model from Sales Transaction Data

Published Online:https://doi.org/10.1287/msom.2020.0878

References

  • Andersen E (1970) Asymptotic properties of conditional maximum-likelihood estimators. J. Royal Statist. Soc. B 32(2):283–301.Google Scholar
  • Barndorff-Nielsen O (1983) On a formula for the distribution of the maximum likelihood estimator. Biometrika 70(2):343–365.CrossrefGoogle Scholar
  • Ben-Akiva M , Lerman S (1994) Discrete Choice Analysis: Theory and Applications to Travel Demand , 6th ed. (MIT Press, Cambridge, MA).Google Scholar
  • Cohen M , Leung Z , Perakis G , Panchamgam K , Smith A (2017) The impact of linear optimization on promotion planning. Oper. Res. 65(2):446–468.LinkGoogle Scholar
  • Cox D , Reid N (1987) Parameter orthogonality and approximate conditional inference. J. Royal Statist. Soc. B 49(1):1–18.Google Scholar
  • Dai J , Ding W , Kleywegt A , Wang X , Zhang Y (2014) Choice-based revenue management for parallel flights. Working paper, Georgia Institute of Technology, Atlanta.Google Scholar
  • Davis J , 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
  • Ding W (2017) Estimation and optimziation problems in revenue management with customer choice behavior. Unpublished doctoral dissertation, Georgia Institute of Technology, Atlanta.Google Scholar
  • Farias V , Jagabathula S , Shah D (2013) A nonparametric approach to modeling choice with limited data. Management Sci. 59(2):305–322.LinkGoogle Scholar
  • Fisher M , Olivares M , Staats BR (2020) Why empirical research is good for operations management, and what is good empirical operations management? Manufacturing Service Oper. Management 22(1):170–178.Google Scholar
  • Ford LR (1957) Solution of a ranking problem from binary comparisons. Amer. Math. Monthly 64(8):28–33.CrossrefGoogle Scholar
  • Greene W (2012) Econometric Analysis , 7th ed. (Pearson, Boston).Google Scholar
  • Guadagni P , Little J (1983) A logit model of brand choice calibrated on scanner data. Marketing Sci. 2(3):203–238.LinkGoogle Scholar
  • Hunter D (2004) MM algorithms for generalized Bradley-Terry models. Ann. Statist. 32(1):384–406.CrossrefGoogle Scholar
  • Hunter DR , Lange K (2000) Rejoinder. J. Comput. Graphical Statist. 9(1):52–59.Google Scholar
  • Kok G , Fisher M , Vaidyanathan R (2008) Assortment planning: Review of literature and industry practice. Agrawal N , Smith S , eds. Retail Supply Chain Management (Springer, New York), 99–153.CrossrefGoogle Scholar
  • Liu Q , van Ryzin G (2008) On the choice-based linear programming model for network revenue management. Manufacturing Service Oper. Management 10(2):288–310.LinkGoogle Scholar
  • Moore T , Sadler B , Kozick R (2008) Maximum-likelihood estimation, the Cramér–Rao bound, and the method of scoring with parameter constraints. IEEE Trans. Signal Processing 56(3):895–908.CrossrefGoogle Scholar
  • Murphy S , Van der Vaart A (2000) On profile likelihood. J. Amer. Statist. Assoc. 95(450):449–465.CrossrefGoogle Scholar
  • Newman J , Ferguson M , Garrow L , Jacobs T (2014) Estimation of choice-based models using sales data from a single firm. Manufacturing Service Oper. Management 16(2):184–197.LinkGoogle Scholar
  • Neyman J , Scott E (1948) Consistent estimates based on partially consistent observations. Econometrica 16(1):1–32.CrossrefGoogle Scholar
  • Nicholson W (1992) Microeconomic Theory: Basic Principles and Extensions , 5th ed. (Dryden Press, Fort Worth, TX).Google Scholar
  • Queenan CC , Ferguson M , Higbie J , Kapoor R (2007) A comparison of unconstraining methods to improve revenue management systems. Production Oper. Management 16(6):729–746.CrossrefGoogle Scholar
  • Ratliff R , Rao B , Narayan C , Yellepeddi K (2008) A multi-flight recapture heuristic for estimating unconstrained demand from airline bookings. J. Revenue Pricing Management 7(2):153–171.CrossrefGoogle Scholar
  • Rusmevichientong P , Shen ZJM , Shmoys D (2010) Dynamic assortment optimization with a multinomial logit choice model and capacity constraint. Oper. Res. 58(6):1666–1680.LinkGoogle Scholar
  • Subramanian S , Harsha P 2017. Demand modeling in the presence of unobservable lost sales. Working paper, IBM Thomas J. Watson Research Center, Yorktown Heights, NY.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.LinkGoogle Scholar
  • Train K (2003) Discrete Choice Methods with Simulation (Cambridge University Press, New York).CrossrefGoogle Scholar
  • Vulcano G , van Ryzin G , Chaar W (2010) Om practice-choice-based revenue management: An empirical study of estimation and optimization. Manufacturing Service Oper. Management 12(3):371–392.LinkGoogle Scholar
  • Vulcano G , van Ryzin G , Ratliff R (2012) Estimating primary demand for substitutable products from sales transaction data. Oper. Res. 60(2):313–334.LinkGoogle Scholar
  • Wang R (2019) Consumer choice and market expansion: Modeling, optimization and estimation. Working paper, Carey Business School, Johns Hopkins University, Baltimore.Google Scholar
  • Wu CF (1983) On the convergence properties of the EM algorithm. Ann. Statist. 11(1):95–103.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.