IDEAS home Printed from https://ideas.repec.org/a/kap/qmktec/v14y2016i3d10.1007_s11129-016-9169-2.html
   My bibliography  Save this article

Costly search and consideration sets in storable goods markets

Author

Listed:
  • Tiago Pires

    (University of North Carolina)

Abstract

Costly search can result in consumers restricting their attention to a subset of products–the consideration set–before making a final purchase decision. The search process is usually not observed, which creates econometric challenges. I show that inventory and the availability of different package sizes create new sources of variation to identify search costs in storable goods markets. To evaluate the importance of costly search in these markets, I estimate a dynamic choice model with search frictions using data on purchases of laundry detergent. My estimates show that consumers incur significant search costs, and ignoring costly search overestimates the own-price elasticity for products more often present in consideration sets and underestimates the elasticity of frequently excluded products. Firms employ marketing devices, such as product displays and advertising, to influence consideration sets. These devices have direct and strategic effects, which I explore using the estimates of the model. I find that using marketing devices to reduce a product’s search cost during a price promotion has modest effects on the overall category revenues, and decreases the revenues of some products.

Suggested Citation

  • Tiago Pires, 2016. "Costly search and consideration sets in storable goods markets," Quantitative Marketing and Economics (QME), Springer, vol. 14(3), pages 157-193, September.
  • Handle: RePEc:kap:qmktec:v:14:y:2016:i:3:d:10.1007_s11129-016-9169-2
    DOI: 10.1007/s11129-016-9169-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11129-016-9169-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11129-016-9169-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Christine Boizot & Jean-Marc Robin & Michael Visser, 2001. "The demand for food products," Post-Print hal-03416605, HAL.
    3. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
    4. 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.
    5. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    6. Igal Hendel & Aviv Nevo, 2006. "Sales and consumer inventory," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 543-561, September.
    7. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
    8. 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.
    9. Sergei Koulayev, 2014. "Search for differentiated products: identification and estimation," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 553-575, September.
    10. 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.
    11. 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.
    12. Kfir Eliaz & Ran Spiegler, 2011. "Consideration Sets and Competitive Marketing," Review of Economic Studies, Oxford University Press, vol. 78(1), pages 235-262.
    13. Christine Boizot & Jean-Marc Robin & Michael Visser, 2001. "The demand for food products," Post-Print hal-03416604, HAL.
    14. 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.
    15. 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.
    16. Boizot, Christine & Robin, Jean-Marc & Visser, Michael, 2001. "The Demand for Food Products: An Analysis of Interpurchase Times and Purchased Quantities," Economic Journal, Royal Economic Society, vol. 111(470), pages 391-419, April.
    17. 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.
    18. Han Hong & Matthew Shum, 2006. "Using price distributions to estimate search costs," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 257-275, June.
    19. Wesley R. Hartmann & Harikesh S. Nair, 2010. "Retail Competition and the Dynamics of Demand for Tied Goods," Marketing Science, INFORMS, vol. 29(2), pages 366-386, 03-04.
    20. Jean‐Pierre Dubé & Günter J. Hitsch & Peter E. Rossi, 2010. "State dependence and alternative explanations for consumer inertia," RAND Journal of Economics, RAND Corporation, vol. 41(3), pages 417-445, September.
    21. 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.
    22. Martin Pesendorfer, 2002. "Retail Sales: A Study of Pricing Behavior in Supermarkets," The Journal of Business, University of Chicago Press, vol. 75(1), pages 33-66, January.
    23. 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.
    24. Igal Hendel & Aviv Nevo, 2006. "Sales and Consumer Inventory," RAND Journal of Economics, The RAND Corporation, vol. 37(3), pages 543-561, Autumn.
    25. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Javier Donna & Andre Trindade & Pedro Pereira & Tiago Pires, 2018. "Measuring the Welfare of Intermediation in Vertical Markets," 2018 Meeting Papers 984, Society for Economic Dynamics.
    2. Andrew T. Ching & Matthew Osborne, 2020. "Identification and Estimation of Forward-Looking Behavior: The Case of Consumer Stockpiling," Marketing Science, INFORMS, vol. 39(4), pages 707-726, July.
    3. Sofronis Clerides & Pascal Courty & Yupei Ma, 2023. "Store expensiveness and consumer saving: Insights from a new decomposition of price dispersion," Quantitative Marketing and Economics (QME), Springer, vol. 21(1), pages 65-94, March.
    4. Michael R. Galbreth & Bikram Ghosh, 2020. "The effect of exogenous product familiarity on endogenous consumer search," Quantitative Marketing and Economics (QME), Springer, vol. 18(2), pages 195-235, June.
    5. Pilli, Luis & Swait, Joffre & Mazzon, José Afonso, 2022. "Jeopardizing brand profitability by misattributing process heterogeneity to preference heterogeneity," Journal of choice modelling, Elsevier, vol. 43(C).
    6. Pires, Tiago, 2018. "Measuring the effects of search costs on equilibrium prices and profits," International Journal of Industrial Organization, Elsevier, vol. 60(C), pages 179-205.
    7. Salvo, Alberto, 2018. "Flexible fuel vehicles, less flexible minded consumers: Price information experiments at the pump," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 194-221.
    8. Javier D. Donna & Pedro Pereira & Tiago Pires & André Trindade, 2022. "Measuring the Welfare of Intermediaries," Management Science, INFORMS, vol. 68(11), pages 8083-8115, November.
    9. Maarten Janssen & Edona Reshidi, 2023. "Discriminatory Trade Promotions in Consumer Search Markets," Marketing Science, INFORMS, vol. 42(2), pages 401-422, March.
    10. Avery Haviv, 2022. "Consumer Search, Price Promotions, and Counter-Cyclic Pricing," Marketing Science, INFORMS, vol. 41(2), pages 294-314, March.
    11. Fernando Luco & Guillermo Marshall, 2021. "Diagnosing Anticompetitive Effects of Vertical Integration by Multiproduct Firms," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 59(2), pages 381-392, September.
    12. David Ronayne, 2020. "The Only Dance in Town: Unique Equilibrium in a Generalized Model of Price Competition," Economics Series Working Papers 874, University of Oxford, Department of Economics.
    13. Johannes Johnen & David Ronayne, 2021. "The only Dance in Town: Unique Equilibrium in a Generalized Model of Price Competition," Journal of Industrial Economics, Wiley Blackwell, vol. 69(3), pages 595-614, September.
    14. Kazuko Kano, 2018. "Consumer Inventory and Demand for Storable Goods: New Evidence from a Consumer Survey," The Japanese Economic Review, Springer, vol. 69(3), pages 284-305, September.
    15. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.
    16. José L Moraga-González & Zsolt Sándor & Matthijs R Wildenbeest, 2021. "Simultaneous Search for Differentiated Products: The Impact of Search Costs and Firm Prominence," The Economic Journal, Royal Economic Society, vol. 131(635), pages 1308-1330.
    17. Donna, Javier D. & Pereira, Pedro & Pires, Tiago & Trindade, Andre, 2018. "Measuring the Welfare of Intermediaries in Vertical Markets," MPRA Paper 90465, University Library of Munich, Germany.
    18. Anna Lu, 2017. "Consumer Stockpiling and Sales Promotions," Discussion Papers of DIW Berlin 1680, DIW Berlin, German Institute for Economic Research.
    19. Yi-Lin Tsai & Elisabeth Honka, 2021. "Informational and Noninformational Advertising Content," Marketing Science, INFORMS, vol. 40(6), pages 1030-1058, November.
    20. Takeshi Fukasawa, 2022. "The Biases in Applying Static Demand Models under Dynamic Demand," Discussion Paper Series DP2022-18, Research Institute for Economics & Business Administration, Kobe University, revised Jul 2022.
    21. Soetevent, Adriaan R., 2021. "I’d Like to Move It! Consumption Rivalry in the EV Public Charging Market: Demand Estimation with Deterministic Choice Set Variation," EconStor Preprints 228520, ZBW - Leibniz Information Centre for Economics.
    22. Fabio Antoniou & Raffaele Fiocco, 2023. "Storable Good Market With Intertemporal Cost Variations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(1), pages 361-385, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mantian (Mandy) Hu & Chu (Ivy) Dang & Pradeep K. Chintagunta, 2019. "Search and Learning at a Daily Deals Website," Marketing Science, INFORMS, vol. 38(4), pages 609-642, July.
    2. Navid Mojir & K. Sudhir, 2014. "Price Search Across Time and Across Stores," Cowles Foundation Discussion Papers 1942R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2019.
    3. Navid Mojir & K. Sudhir, 2014. "A Model of Multi-pass Search: Price Search across Stores and Time," Cowles Foundation Discussion Papers 1942R2, Cowles Foundation for Research in Economics, Yale University, revised Feb 2020.
    4. Helmers, Christian & Krishnan, Pramila & Patnam, Manasa, 2019. "Attention and saliency on the internet: Evidence from an online recommendation system," Journal of Economic Behavior & Organization, Elsevier, vol. 161(C), pages 216-242.
    5. Avery Haviv, 2022. "Consumer Search, Price Promotions, and Counter-Cyclic Pricing," Marketing Science, INFORMS, vol. 41(2), pages 294-314, March.
    6. Février, Philippe & Wilner, Lionel, 2016. "Do consumers correctly expect price reductions? Testing dynamic behavior," International Journal of Industrial Organization, Elsevier, vol. 44(C), pages 25-40.
    7. Anna Lu, 2017. "Inference of Consumer Consideration Sets," Discussion Papers of DIW Berlin 1681, DIW Berlin, German Institute for Economic Research.
    8. Pires, Tiago, 2018. "Measuring the effects of search costs on equilibrium prices and profits," International Journal of Industrial Organization, Elsevier, vol. 60(C), pages 179-205.
    9. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    10. 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.
    11. Thomas Blake & Chris Nosko & Steven Tadelis, 2016. "Returns to Consumer Search: Evidence from eBay," NBER Working Papers 22302, National Bureau of Economic Research, Inc.
    12. 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.
    13. Hana Choi & Carl F. Mela, 2019. "Monetizing Online Marketplaces," Marketing Science, INFORMS, vol. 38(6), pages 948-972, November.
    14. Javier D. Donna, 2021. "Measuring long‐run gasoline price elasticities in urban travel demand," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 945-994, December.
    15. Lu, Zhentong, 2022. "Estimating multinomial choice models with unobserved choice sets," Journal of Econometrics, Elsevier, vol. 226(2), pages 368-398.
    16. Navid Mojir & K. Sudhir, 2014. "Price Search Across Stores and Across Time," Cowles Foundation Discussion Papers 1942, Cowles Foundation for Research in Economics, Yale University, revised Mar 2016.
    17. 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.
    18. Raluca M. Ursu & Qingliang Wang & Pradeep K. Chintagunta, 2020. "Search Duration," Marketing Science, INFORMS, vol. 39(5), pages 849-871, September.
    19. 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.
    20. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.

    More about this item

    Keywords

    Search costs; Consideration set; Information; Storable goods; Dynamic discrete-choice models;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:qmktec:v:14:y:2016:i:3:d:10.1007_s11129-016-9169-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.