Search Duration

Published Online:https://doi.org/10.1287/mksc.2020.1225

References

  • Ackerberg D (2003) Advertising, learning and consumer choice in experience good markets: A structural empirical examination. Internat. Econom. Rev. 44(3):1007–1040.CrossrefGoogle Scholar
  • Blake T, Nosko C, Tadelis S (2016) Return to consumer search: Evidence from eBay. Working paper, eBay Research Labs, San Jose, CA.Google Scholar
  • Branco F, Sun M, Villas-Boas JM (2012) Optimal search for product information. Management Sci. 58(11):2037–2056.LinkGoogle Scholar
  • Branco F, Sun M, Villas-Boas JM (2016) Too much information? Information provision and search costs. Marketing Sci. 35(4):605–618.LinkGoogle Scholar
  • Brezzi M, Lai T (2002) Optimal learning and experimentation in bandit problems. J. Econom. Dynam. Control 27(1):87–108.CrossrefGoogle Scholar
  • Chen Y, Yao S (2016) Sequential search with refinement: Model and application with click-stream data. Management Sci. 34(4):606–623.Google Scholar
  • Chernoff H (1965) Sequential test for the mean of a normal distribution III (small t). Ann. Math. Stat. 36(1):28–54.Google Scholar
  • Chernoff H, Ray SN (1965) A Bayes sequential sampling inspection plan. Ann. Math. Statist. 36(5):1387–1407.CrossrefGoogle Scholar
  • Chick SE, Gans N (2009) An economic analysis of simulation selection problems. Management Sci. 55(3):421–437.LinkGoogle Scholar
  • Chick SE, Gans N, Yapar O (2018) Bayesian sequential learning for clinical trials of multiple correlated medical interventions. Working paper, INSEAD, Paris.Google Scholar
  • Chick S, Frazier PI (2012) Sequential sampling with economics of selection procedures. Management Sci. 58(3):1–16.LinkGoogle Scholar
  • De los Santos B (2017) Consumer search on the internet. Working paper, Clemson University, SC.Google Scholar
  • De los Santos B, Hortaçsu A, Wildenbeest MR (2012) Testing models of consumer search using data on web browsing and purchasing behavior. Amer. Econom. Rev. 102(6):2955–2980.Google Scholar
  • De los Santos B, Hortaçsu A, Wildenbeest MR (2017) Search with learning for differentiated products: Evidence from e-commerce. J. Bus. Econom. Statist. 35(4):626–641.CrossrefGoogle Scholar
  • De los Santos B, Koulayev S (2017) Optimizing click-through in online rankings for partially anonymous consumers. Marketing Sci. 36(4):542–564.LinkGoogle Scholar
  • Dong X, Morozov I, Seiler S, Hou L (2018) Estimation of preference heterogeneity in markets with costly search. Working paper, Santa Clara University, Santa Clara, CA.Google Scholar
  • Dukes A, Liu L (2015) Online shopping intermediaries: the strategic design of search environments. Management Sci. 62(4):1064–1077.LinkGoogle Scholar
  • Erdem T, Keane MP (1996) Decision-making under uncertainty: Capturing choice dynamics in turbulent consumer goods markets. Marketing Sci. 15(1):1–21.LinkGoogle Scholar
  • Erdem T, Keane MP, Sun B (2008) A dynamic model of brand choice when price and advertising signal product quality. Marketing Sci. 27(6):1111–1125.LinkGoogle Scholar
  • Fradkin A (2017) Search, matching, and the role of digital marketplace design in enabling trade: Evidence from Airbnb. Working paper, Boston University, Boston.Google Scholar
  • Gardete P, Antill M (2019) Guiding consumers through lemons and peaches: a dynamic model of search over multiple characteristics. Working paper, Nova School of Business and Economics, Lisbon, Portugal.Google Scholar
  • Ghose A, Ipeirotis P, Li B (2012) Designing ranking systems for hotels on travel search engines by mining user-generated and crowd-sourced content. Marketing Sci. 31(3):492–520.LinkGoogle Scholar
  • Ghose A, Ipeirotis P, Li B (2014) Examining the impact of ranking on consumer behavior and search engine revenue. Management Sci. 60(7):1632–1654.LinkGoogle Scholar
  • Ghose A, Ipeirotis P, Li B (2019) Modeling consumer footprints on search engines: An interplay with social media. Management Sci. 65(3):1363–1385.LinkGoogle Scholar
  • Gittins J, Jones D (1974) A dynamic allocation index for the sequential design of experiments. Gani J, Sarkadi K, Vince I, eds. Progress in Statistics (North-Holland, Amsterdam), 241–266.Google Scholar
  • Gittins J (1979) Bandit processes and dynamic allocation indices. J. Royal Statist. Soc. 41(2):148–177.Google Scholar
  • Gittins J (1989) Multiarmed Bandit Allocation Indices (John Wiley & Sons, New York).Google Scholar
  • Hong H, Shum M (2006) Using price distributions to estimate search cost. RAND J. Econom. 37(2):257–275.CrossrefGoogle Scholar
  • Honka E (2014) Quantifying search and switching costs in the U.S. auto insurance industry. RAND J. Econom. 45(4):847–884.CrossrefGoogle Scholar
  • Honka E, Chintagunta P (2017) Simultaneous or sequential? Search strategies in the U.S. auto insurance industry. Marketing Sci. 36(1):21–42.LinkGoogle Scholar
  • Hu M, Dang C, Chintagunta P (2019) Search and learning at a daily deals website. Marketing Sci. 38(4):609–642.Google Scholar
  • Jindal P, Aribarg A (2018) The value of price beliefs in consumer search. Working paper, UNC Kenan-Flagler Business School, Chapel Hill, NC.Google Scholar
  • Ke TT, Villas-Boas JM (2019) Optimal learning before choice. J. Econom. Theory 180(March):383–437.Google Scholar
  • Ke TT, Shen ZM, Villas-Boas JM (2016) Search for information on multiple products. Management Sci. 62(12):3576–3603.LinkGoogle Scholar
  • Kim JB, Albuquerque P, Bronnenberg BJ (2010) Online demand under limited consumer search. Marketing Sci. 29(6):1001–1023.LinkGoogle Scholar
  • Kim JB, Albuquerque P, Bronnenberg BJ (2017) The probit choice model under sequential search with an application to online retailing. Management Sci. 63(11):3911–3929.LinkGoogle Scholar
  • Koulayev S (2013) Search with dirichlet priors: Estimation and implications for consumer demand. J. Bus. Econom. Statist. 31(2):226–239.CrossrefGoogle Scholar
  • Koulayev S (2014) Search for differentiated products: identification and estimation. RAND J. Econom. 45(3):553–575.CrossrefGoogle Scholar
  • Lai T (1987) Adaptive treatment allocation and the multiarmed bandit problem. Ann. Statist. 15(3):1091–1114.CrossrefGoogle Scholar
  • Lin S, Zhang J, Hauser JR (2014) Learning from experience, simply. Marketing Sci. 34(1):1–19.LinkGoogle Scholar
  • Ma L (2016) Only the interested learn: A model of proactive learning of product reviews. Working paper, Guanghua School of Management, Beijing.Google Scholar
  • McFadden D (1989) A method of simulating moments for estimation of discrete response models without numerical integration. Econometrica 57(5):995–1026.CrossrefGoogle Scholar
  • Moraga-Gonzalez J, Wildenbeest M (2008) Maximum likelihood estimation of search cost. Eur. Econom. Rev. 52(5):820–848.CrossrefGoogle Scholar
  • Moraga-Gonzalez JL, Sandor Z, Wildenbeest M (2015) Consumer search and prices in the automobile market. Working paper, VU University, Amsterdam.Google Scholar
  • Narayanan S, Manchanda P, Chintagunta P (2005) Temporal differences in the role of marketing communication in new product categories. J. Marketing Res. 42(3):278–290.CrossrefGoogle Scholar
  • Rothschild M (1974) Searching for the lowest price when the distribution of prices is unknown. J. Political Econom. 82(4):689–711.CrossrefGoogle Scholar
  • Seiler S (2013) The impact of search costs on consumer behavior: a dynamic approach. Quant. Marketing Econom. 11(2):155–203.CrossrefGoogle Scholar
  • Seiler S, Pinna F (2017) Estimating search benefits from path-tracking data: measurement and determinants. Marketing Sci. 36(4):565–589.LinkGoogle Scholar
  • Stigler GJ (1961) The economics of information. J. Political Econom. 65(3):213–225.CrossrefGoogle Scholar
  • Ursu R (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 M (1979) Optimal search for the best alternative. Econometrica 47(3):641–654.CrossrefGoogle Scholar
  • Wu C, Che H, Chan T, Lu X (2015) The economic value of online reviews. Marketing Sci. 34(5):739–754.LinkGoogle 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.