IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v38y2019i2p253-273.html
   My bibliography  Save this article

Effectiveness of Product Recommendations Under Time and Crowd Pressures

Author

Listed:
  • Kohei Kawaguchi

    (Department of Economics, School of Business and Management, Hong Kong University of Science and Technology, Kowloon, Hong Kong)

  • Kosuke Uetake

    (Marketing Department, Yale School of Management, New Haven, Connecticut 06511)

  • Yasutora Watanabe

    (Graduate School of Economics, University of Tokyo, Tokyo 1130033, Japan)

Abstract

Understanding the effects of contextual factors is crucial in designing context-based marketing. This paper focuses on product recommendations and studies how time and crowd pressures—two prominent contextual effects in the consumer behavior literature—can impact the effectiveness of recommendations. Measuring these effects is not straightforward because the joint distribution of consumer choice, time, and crowd pressures is rarely observed outside the laboratory and recommendations are often endogenously determined. We overcome these issues using data from an experiment conducted with vending machines in railway stations across Tokyo. The machines are equipped with a facial recognition system to make recommendations, and recommendations are changed exogenously in the experiment. This setup provides us with well-measured variables of the time and crowd pressures that affect the effectiveness of recommendations. After showing that recommendations increase the sales of both the recommended and nonrecommended products, we show that time pressures moderate the effectiveness of product recommendations for both recommended products directly and nonrecommended products indirectly. Crowd pressures weaken the direct effect on the recommended products, although its impact on the nonrecommended products is small and not robust in some cases. These results indicate that, when marketers make context-based recommendations, they should be mindful of the consumers under time pressure.

Suggested Citation

  • Kohei Kawaguchi & Kosuke Uetake & Yasutora Watanabe, 2019. "Effectiveness of Product Recommendations Under Time and Crowd Pressures," Marketing Science, INFORMS, vol. 38(2), pages 253-273, March.
  • Handle: RePEc:inm:ormksc:v:38:y:2019:i:2:p:253-273
    DOI: 10.1287/mksc.2018.1132
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/mksc.2018.1132
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.2018.1132?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
    ---><---

    References listed on IDEAS

    as
    1. Jennifer J. Argo & Darren W. Dahl & Rajesh V. Manchanda, 2005. "The Influence of a Mere Social Presence in a Retail Context," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(2), pages 207-212, September.
    2. Elena Reutskaja & Rosemarie Nagel & Colin F. Camerer & Antonio Rangel, 2011. "Search Dynamics in Consumer Choice under Time Pressure: An Eye-Tracking Study," American Economic Review, American Economic Association, vol. 101(2), pages 900-926, April.
    3. Prabuddha De & Yu (Jeffrey) Hu & Mohammad S. Rahman, 2010. "Technology Usage and Online Sales: An Empirical Study," Management Science, INFORMS, vol. 56(11), pages 1930-1945, November.
    4. Guido W. Imbens, 2015. "Matching Methods in Practice: Three Examples," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 373-419.
    5. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    6. 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.
    7. Hui, Michael K & Bateson, John E G, 1991. "Perceived Control and the Effects of Crowding and Consumer Choice on the Service Experience," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(2), pages 174-184, September.
    8. Dhar, Ravi & Nowlis, Stephen M, 1999. "The Effect of Time Pressure on Consumer Choice Deferral," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(4), pages 369-384, March.
    9. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    10. Jidong Zhou, 2014. "Multiproduct Search and the Joint Search Effect," American Economic Review, American Economic Association, vol. 104(9), pages 2918-2939, September.
    11. Dahl, Darren W & Manchanda, Rajesh V & Argo, Jennifer J, 2001. "Embarrassment in Consumer Purchase: The Roles of Social Presence and Purchase Familiarity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 473-481, December.
    12. Suri, Rajneesh & Monroe, Kent B, 2003. "The Effects of Time Constraints on Consumers' Judgments of Prices and Products," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(1), pages 92-104, June.
    13. 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.
    14. Sam K. Hui & Eric T. Bradlow & Peter S. Fader, 2009. "Testing Behavioral Hypotheses Using an Integrated Model of Grocery Store Shopping Path and Purchase Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 36(3), pages 478-493.
    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. Dobromir Stoyanov, 2021. "The role of vending channels in marketing: A systematic review and taxonomy of studies," Journal of Consumer Affairs, Wiley Blackwell, vol. 55(2), pages 654-679, June.
    2. Brian Park & Eunhee Sohn & Soohun Kim, 2020. "Does the pressure to fill journal quotas bias evaluation?: Evidence from publication delays and rejection rates," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-11, August.
    3. Nasim Mousavi & Panagiotis Adamopoulos & Jesse Bockstedt, 2023. "The Decoy Effect and Recommendation Systems," Information Systems Research, INFORMS, vol. 34(4), pages 1533-1553, December.
    4. Ryo Kato & Takahiro Hoshino & Daisuke Moriwaki & Shintaro Okazaki, 2022. "Mobile Targeting: Exploring the Role of Area Familiarity, Store Knowledge, and Promotional Incentives," Discussion Paper Series DP2022-10, Research Institute for Economics & Business Administration, Kobe University.
    5. Ching, Andrew & Kawaguchi, Kohei & Liu, Jia & Yi, Zhang, 2023. "Consumer Responses to Favorite Product Removal: Evidence from Beverage Vending Machines," SocArXiv t34qj, Center for Open Science.
    6. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
    7. Isamar Troncoso & Lan Luo, 2023. "Look the Part? The Role of Profile Pictures in Online Labor Markets," Marketing Science, INFORMS, vol. 42(6), pages 1080-1100, November.
    8. Kohei Kawaguchi & Kosuke Uetake & Yasutora Watanabe, 2021. "Designing Context-Based Marketing: Product Recommendations Under Time Pressure," Management Science, INFORMS, vol. 67(9), pages 5642-5659, September.

    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. Hämäläinen, Saara, 2022. "Multiproduct search obfuscation," International Journal of Industrial Organization, Elsevier, vol. 85(C).
    2. Luck, Michael & Benkenstein, Martin, 2015. "Consumers between supermarket shelves: The influence of inter-personal distance on consumer behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 26(C), pages 104-114.
    3. Dubois, Pierre & Perrone, Helena, 2015. "Price Dispersion and Informational Frictions: Evidence from Supermarket Purchases," TSE Working Papers 15-606, Toulouse School of Economics (TSE), revised Sep 2017.
    4. Tombs, Alastair G. & McColl-Kennedy, Janet R., 2010. "Social and spatial influence of customers on other customers in the social-servicescape," Australasian marketing journal, Elsevier, vol. 18(3), pages 120-131.
    5. Argo, Jennifer J. & Dahl, Darren W., 2020. "Social Influence in the Retail Context: A Contemporary Review of the Literature," Journal of Retailing, Elsevier, vol. 96(1), pages 25-39.
    6. Krishnan, Balaji C. & Dutta, Sujay & Jha, Subhash, 2013. "Effectiveness of Exaggerated Advertised Reference Prices: The Role of Decision Time Pressure," Journal of Retailing, Elsevier, vol. 89(1), pages 105-113.
    7. Dahm, Martin & Wentzel, Daniel & Herzog, Walter & Wiecek, Annika, 2018. "Breathing Down Your Neck!," Journal of Retailing, Elsevier, vol. 94(2), pages 217-230.
    8. Jia Liu & Olivier Toubia, 2020. "Search query formation by strategic consumers," Quantitative Marketing and Economics (QME), Springer, vol. 18(2), pages 155-194, June.
    9. Kohei Kawaguchi & Kosuke Uetake & Yasutora Watanabe, 2021. "Designing Context-Based Marketing: Product Recommendations Under Time Pressure," Management Science, INFORMS, vol. 67(9), pages 5642-5659, September.
    10. Rhys Murrian & Paul A. Raschky & Klaus Ackermann, 2024. "Friends, Key Players and the Adoption and Use of Experience Goods," Monash Economics Working Papers 2024-17, Monash University, Department of Economics.
    11. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    12. Greenacre, Luke & Martin, James & Patrick, Sarah & Jaeger, Victoria, 2016. "Boundaries of the centrality effect during product choice," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 32-38.
    13. Aydinli, Aylin & Lamey, Lien & Millet, Kobe & ter Braak, Anne & Vuegen, Maya, 2021. "How Do Customers Alter Their Basket Composition When They Perceive the Retail Store to Be Crowded? An Empirical Study," Journal of Retailing, Elsevier, vol. 97(2), pages 207-216.
    14. Hwang, YooHee & Shin, Joongwon & Mattila, Anna S., 2018. "So private, yet so public: The impact of spatial distance, other diners, and power on solo dining experiences," Journal of Business Research, Elsevier, vol. 92(C), pages 36-47.
    15. Raluca M. Ursu & Qingliang Wang & Pradeep K. Chintagunta, 2020. "Search Duration," Marketing Science, INFORMS, vol. 39(5), pages 849-871, September.
    16. Ching, Andrew T. & Erdem, Tülin & Keane, Michael P., 2014. "A simple method to estimate the roles of learning, inventories and category consideration in consumer choice," Journal of choice modelling, Elsevier, vol. 13(C), pages 60-72.
    17. Guido W. Imbens, 2022. "Causality in Econometrics: Choice vs Chance," Econometrica, Econometric Society, vol. 90(6), pages 2541-2566, November.
    18. Rode, Johannes & Müller, Sven, 2016. "Spatio-Temporal Variation in Peer Effects - The Case of Rooftop Photovoltaic Systems in Germany," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84765, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    19. Christa Brelsford & Caterina De Bacco, 2018. "Are `Water Smart Landscapes' Contagious? An epidemic approach on networks to study peer effects," Papers 1801.10516, arXiv.org.
    20. Gabriel S. Sampson & Edward D. Perry, 2019. "Peer effects in the diffusion of water‐saving agricultural technologies," Agricultural Economics, International Association of Agricultural Economists, vol. 50(6), pages 693-706, November.

    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:inm:ormksc:v:38:y:2019:i:2:p:253-273. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.