Learning Product Characteristics and Consumer Preferences from Search Data

Published Online:https://doi.org/10.1287/mksc.2023.0118

References

  • Amano T, Rhodes A, Seiler S (2018) Large-scale demand estimation with search data. Harvard Business School Working Paper, No. 19-022. (Revised June 2019. Stanford University Research Paper, No. 18-36, 8-20 2018).Google Scholar
  • Athey S, Blei D, Donnelly R, Ruiz F, Schmidt T (2018) Estimating heterogeneous consumer preferences for restaurants and travel time using mobile location data. AEA Papers Proc. 108:64–67.Google Scholar
  • Bajari P, Nekipelov D, Ryan SP, Yang M (2015) Machine learning methods for demand estimation. Amer. Econom. Rev. 105(5):481–485.CrossrefGoogle Scholar
  • Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63(4):841–890.CrossrefGoogle Scholar
  • Berry S, Levinsohn J, Pakes A (2004) Differentiated products demand systems from a combination of micro and macro data: The new car market. J. Political Econom. 112(1):68–105.CrossrefGoogle Scholar
  • Cardell NS (1997) Variance components structures for the extreme-value and logistic distributions with application to models of heterogeneity. Econometric Theory 13(2):185–213.CrossrefGoogle Scholar
  • Conlon C, Gortmaker J (2020) Best practices for differentiated products demand estimation with PyBLP. RAND J. Econom. 51:1108–1161.Google Scholar
  • Cortes D (2018) Cold-start recommendations in collective matrix factorization. Preprint, submitted September 2, https://arxiv.org/abs/1809.00366.Google Scholar
  • De los Santos B, Wildenbeest M (2017) E-book pricing and vertical restraints. Quant. Marketing Econom. 15:85–122.CrossrefGoogle Scholar
  • Deaton A, Muellbauer J (1980) An almost ideal demand system. Amer. Econom. Rev. 70(3):312–326.Google Scholar
  • Dogru T, Erdogan A, Kizildag M (2018) Marriott Starwood merger: What did we learn from a financial standpoint? J. Hospitality Tourism Insights 1(2):121–136.CrossrefGoogle Scholar
  • Donnelly R, Kanodia A, Morozov I (2020) A unified framework for personalizing product rankings. Preprint, submitted August 3, https://dx.doi.org/10.2139/ssrn.3649342.Google Scholar
  • Einav L (2007) Seasonality in the U.S. motion picture industry. RAND J. Econom. 38(1):127–145.CrossrefGoogle Scholar
  • Elrod T (1988) Choice map: Inferring a product-market map from panel data. Marketing Sci. 7(1):21–40.LinkGoogle Scholar
  • Elrod T, Keane MP (1995) A factor-analytic probit model for representing the market structure in panel data. J. Marketing Res. 32(1):1–16.CrossrefGoogle Scholar
  • Gandhi A, Houde J-F (2016) Measuring substitution patterns in differentiated products industries. NBER Working Paper No. 26375, National Bureau of Economic Research, Cambridge, MA.Google Scholar
  • Honka E (2014) Quantifying search and switching costs in the US auto insurance industry. RAND J. Econom. 45(4):847–884.CrossrefGoogle Scholar
  • Honka E, Seiler S, Ursu R (2024) Consumer search: What can we learn from pre-purchase data? J. Retailing 100(1):114–129.Google Scholar
  • Johnson CC (2014) Logistic matrix factorization for implicit feedback data. Adv. Neural Inform. Processing Systems 27(78):1–9.Google Scholar
  • Keane M (2015) Panel data discrete choice models of consumer demand. Baltagi BH, ed. The Oxford Handbook of Panel Data, online ed. (Oxford Academic, New York).Google Scholar
  • Kim JB, Albuquerque P, Bronnenberg BJ (2011) Mapping online consumer search. J. Marketing Res. 48(1):13–27.CrossrefGoogle Scholar
  • Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. Preprint, submitted December 22, https://arxiv.org/abs/1412.6980.Google Scholar
  • Koren Y, Bell R, Volinsky C (2009) Matrix factorization techniques for recommender systems. Computer 42(8):30–37.CrossrefGoogle Scholar
  • Koulayev S (2014) Search for differentiated products: Identification and estimation. RAND J. Econom. 45(3):553–575.CrossrefGoogle Scholar
  • Lancaster KJ (1966) A new approach to consumer theory. J. Political Econom. 74(2):132–157.CrossrefGoogle Scholar
  • Lewis G, Zervas G (2016) The welfare impact of consumer reviews: A case study of the hotel industry. Unpublished manuscript.Google Scholar
  • Maaten LD, Hinton G (2008) Visualizing data using t-SNE. J. Machine Learn. Res. 9:2579–2605.Google Scholar
  • Magnolfi L, McClure J, Sorensen AT (2022) Embeddings and distance-based demand for differentiated products. Proc. 23rd ACM Conf. Econom. Comput. (Association for Computing Machinery, New York).Google Scholar
  • McFadden D (1973) Conditional logit analysis of qualitative choice behavior. Zarembka P, ed. Frontiers in Econometrics (Academic Press, New York), 105–142.Google Scholar
  • Moraga-González JL, Sándor Z, Wildenbeest MR (2023) Consumer search and prices in the automobile market. Rev. Econom. Stud. 90(3):1394–1440.CrossrefGoogle Scholar
  • Nevo A (2001) Measuring market power in the ready-to-eat cereal industry. Econometrica 69(2):307–342.CrossrefGoogle Scholar
  • Petrin A (2002) Quantifying the benefits of new products: The case of the minivan. J. Political Econom. 110(4):705–729.CrossrefGoogle Scholar
  • Rendle S, Freudenthaler C, Gantner Z, Schmidt-Thieme L (2009) BPR: Bayesian personalized ranking from implicit feedback. Proc. 25th Conf. Uncertainty Artificial Intelligence (UAI ’09) (AUAI Press, Arlington, VA), 452–461.Google Scholar
  • Rudolph M, Ruiz F, Mandt S, Blei D (2016) Exponential family embeddings. Proc. 30th Internat. Conf. Neural Inform. Processing Systems (Curran Associates Inc., Red Hook, NY), 478–486.Google Scholar
  • Ruiz FJ, Athey S, Blei DM (2017) SHOPPER: A probabilistic model of consumer choice with substitutes and complements. Preprint, submitted November 9, https://arxiv.org/abs/1711.03560.Google Scholar
  • Salakhutdinov R, Mnih A (2008) Bayesian probabilistic matrix factorization using Markov chain Monte Carlo. Proc. 25th Internat. Conf. Machine Learn. (Association for Computing Machinery, New York), 880–887.Google Scholar
  • Sams JA (2019) Learning or herding? Understanding social interactions and the distribution of success on a social music sharing platform. Unpublished PhD thesis, Stanford University, CA.Google Scholar
  • Schein AI, Popescul A, Ungar LH, Pennock DM (2002) Methods and metrics for cold-start recommendations. Proc. 25th Annual Internat. ACM SIGIR Conf. Res. Development Inform. Retrieval, 253–260.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.LinkGoogle Scholar
  • Weitzman ML (1979) Optimal search for the best alternative. Econometrica 47(3):641–654.Google 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.