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Attention and Saliency on the Internet: Evidence from an Online Recommendation System

Author

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  • Krishnan, Pramila
  • Helmers, Christian
  • Patnam, Manasa
Abstract
Using high-frequency transaction-level data from an online retail store, we examine whether consumer choices on the internet are consistent with models of limited attention. We test whether consumers are more likely to buy products that receive a saliency shock when they are recommended by new products. To identify the saliency effect, we rely on i) the timing of new product arrivals, ii) the fact that new products are per se highly salient upon arrival, drawing more attention and iii) regional variation in the composition of recommendation sets. We find a sharp and robust 6% increase in the aggregate sales of existing products after they are recommended by a new product. To structurally disentangle the effect of saliency on a consumer?s consideration and choice decision, we use data on individual transactions to estimate a probabilistic choice set model. We find that the saliency effect is driven largely by an expansion of consumers? consideration sets.

Suggested Citation

  • Krishnan, Pramila & Helmers, Christian & Patnam, Manasa, 2015. "Attention and Saliency on the Internet: Evidence from an Online Recommendation System," CEPR Discussion Papers 10939, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10939
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    1. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    2. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, September.
    3. Michael Dinerstein & Liran Einav & Jonathan Levin & Neel Sundaresan, 2018. "Consumer Price Search and Platform Design in Internet Commerce," American Economic Review, American Economic Association, vol. 108(7), pages 1820-1859, July.
    4. Tibor Besedes & Cary Deck & Sudipta Sarangi & Mikhael Shor, 2015. "Reducing Choice Overload without Reducing Choices," The Review of Economics and Statistics, MIT Press, vol. 97(4), pages 793-802, October.
    5. Michael R. Baye & J. Rupert J. Gatti & Paul Kattuman & John Morgan, 2009. "Clicks, Discontinuities, and Firm Demand Online," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(4), pages 935-975, December.
    6. Paola Manzini & Marco Mariotti, 2014. "Stochastic Choice and Consideration Sets," Econometrica, Econometric Society, vol. 82(3), pages 1153-1176, May.
    7. Raj Chetty & Adam Looney & Kory Kroft, 2009. "Salience and Taxation: Theory and Evidence," American Economic Review, American Economic Association, vol. 99(4), pages 1145-1177, September.
    8. repec:tpr:restat:v:97:y:2015:i:5:p:793-802 is not listed on IDEAS
    9. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2003. "Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation," Marketing Science, INFORMS, vol. 22(1), pages 58-84, June.
    10. Sridhar Narayanan & Kirthi Kalyanam, 2015. "Position Effects in Search Advertising and their Moderators: A Regression Discontinuity Approach," Marketing Science, INFORMS, vol. 34(3), pages 388-407, May.
    11. Gal Oestreicher-Singer & Arun Sundararajan, 2012. "The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets," Management Science, INFORMS, vol. 58(11), pages 1963-1981, November.
    12. Kfir Eliaz & Ran Spiegler, 2011. "Consideration Sets and Competitive Marketing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 235-262.
    13. Basar, Gözen & Bhat, Chandra, 2004. "A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area," Transportation Research Part B: Methodological, Elsevier, vol. 38(10), pages 889-904, December.
    14. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    15. Marco A. Haan & José L. Moraga‐González, 2011. "Advertising for Attention in a Consumer Search Model," Economic Journal, Royal Economic Society, vol. 121(552), pages 552-579, May.
    16. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2010. "Online Demand Under Limited Consumer Search," Marketing Science, INFORMS, vol. 29(6), pages 1001-1023, 11-12.
    17. repec:bla:jindec:v:49:y:2001:i:4:p:541-58 is not listed on IDEAS
    18. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-2980, October.
    19. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    20. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
    21. Draganska, Michaela & Klapper, Daniel, 2010. "Choice Set Heterogeneity and the Role of Advertising: An Analysis with Micro and Macro Data," Research Papers 2063, Stanford University, Graduate School of Business.
    22. Michael D. Smith & Erik Brynjolfsson, 2001. "Consumer Decision-making at an Internet Shopbot: Brand Still Matters," NBER Chapters, in: E-commerce, pages 541-558, National Bureau of Economic Research, Inc.
    23. Yusufcan Masatlioglu & Daisuke Nakajima & Erkut Y. Ozbay, 2012. "Revealed Attention," American Economic Review, American Economic Association, vol. 102(5), pages 2183-2205, August.
    24. Bart J. Bronnenberg & Jun B. Kim & Carl F. Mela, 2016. "Zooming In on Choice: How Do Consumers Search for Cameras Online?," Marketing Science, INFORMS, vol. 35(5), pages 693-712, September.
    25. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    26. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    27. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    28. Elisabeth Honka, 2014. "Quantifying search and switching costs in the US auto insurance industry," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 847-884, December.
    29. Hauser, John R & Wernerfelt, Birger, 1990. "An Evaluation Cost Model of Consideration Sets," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(4), pages 393-408, March.
    30. Michelle Sovinsky Goeree, 2008. "Limited Information and Advertising in the U.S. Personal Computer Industry," Econometrica, Econometric Society, vol. 76(5), pages 1017-1074, September.
    31. Alan T. Sorensen, 2007. "Bestseller Lists And Product Variety," Journal of Industrial Economics, Wiley Blackwell, vol. 55(4), pages 715-738, December.
    32. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Incorporating random constraints in discrete models of choice set generation," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 91-102, April.
    33. Catherine Tucker & Juanjuan Zhang, 2011. "How Does Popularity Information Affect Choices? A Field Experiment," Management Science, INFORMS, vol. 57(5), pages 828-842, May.
    34. Hongbin Cai & Yuyu Chen & Hanming Fang, 2009. "Observational Learning: Evidence from a Randomized Natural Field Experiment," American Economic Review, American Economic Association, vol. 99(3), pages 864-882, June.
    35. Elisabeth Honka & Ali Hortaçsu & Maria Ana Vitorino, 2017. "Advertising, consumer awareness, and choice: evidence from the U.S. banking industry," RAND Journal of Economics, RAND Corporation, vol. 48(3), pages 611-646, August.
    36. Octavian Carare, 2012. "The Impact Of Bestseller Rank On Demand: Evidence From The App Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 717-742, August.
    37. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    38. Chiang, Jeongwen & Chib, Siddhartha & Narasimhan, Chakravarthi, 1998. "Markov chain Monte Carlo and models of consideration set and parameter heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 223-248, November.
    39. Elisabeth Honka & Pradeep Chintagunta, 2017. "Simultaneous or Sequential? Search Strategies in the U.S. Auto Insurance Industry," Marketing Science, INFORMS, vol. 36(1), pages 21-42, January.
    40. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
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    Cited by:

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    2. Eliaz, Kfir & Weisburd, Sarit & Oren-Kolbinger, Orli, 2017. "Limited Attention, Salience and Changing Prices: Evidence from a Field Experiment in Online Supermarket Shopping," CEPR Discussion Papers 12014, C.E.P.R. Discussion Papers.
    3. Georg von Graevenitz & Christian Helmers & Valentine Millot & Oliver Turnbull, 2016. "Does Online Search Predict Sales? Evidence from Big Data for Car Markets in Germany and the UK," Working Papers 71, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    4. Florian Heiss & Daniel McFadden & Joachim Winter & Amelie Wuppermann & Bo Zhou, 2016. "Inattention and Switching Costs as Sources of Inertia in Medicare Part D," NBER Working Papers 22765, National Bureau of Economic Research, Inc.
    5. Sim, Jaeung & Park, Jea Gon & Cho, Daegon & Smith, Michael D. & Jung, Jaemin, 2022. "Bestseller lists and product discovery in the subscription-based market: Evidence from music streaming," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 550-567.
    6. Imke Reimers & Joel Waldfogel, 2021. "Digitization and Pre-purchase Information: The Causal and Welfare Impacts of Reviews and Crowd Ratings," American Economic Review, American Economic Association, vol. 111(6), pages 1944-1971, June.
    7. Kummer, Michael E. & Laitenberger, Ulrich & Rich, Cyrus E. & Hughes, Danny R. & Ayer, Turgay, 2021. "Healthy reviews! Online physician ratings reduce healthcare interruptions," ZEW Discussion Papers 21-075, ZEW - Leibniz Centre for European Economic Research.

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    More about this item

    Keywords

    Limited attention; Advertising; Online markets;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • K11 - Law and Economics - - Basic Areas of Law - - - Property Law
    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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