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Herding Among Retail Shoppers: the Case of Television Shopping Network

Author

Listed:
  • Ye Hu

    (University of Houston)

  • Kitty Wang

    (University of Houston)

  • Ming Chen

    (University of North Carolina at Charlotte)

  • Sam Hui

    (University of Houston)

Abstract

Herding behavior refers to the behavior of individuals behaving similarly as a group without directions to coordinate. Herding can demonstrate rational characteristics. When consumers believe that others may have private information about a product, they infer unobserved information through other people’s behaviors, thereby engaging in similar actions themselves. While rational herding behavior has been found mostly in high involvement environments such as the financial markets, this paper provides evidence that such behavior may also occur in a comparatively lower involvement environment such as retailing. To demonstrate herding behavior and test shoppers’ rationality in such, the authors employ a unique dataset from a major TV shopping channel. In this setting, information about other buyers’ purchase decisions is only sometimes observed by shoppers. Evidence suggests that herding happens among shoppers and the herding behavior appears to exhibit rationality. The authors find that herding effects (1) are stronger when relative price discount is smaller, (2) are more prominent for a product category with less digitalizable attributes, and (3) appear to happen mainly in the earlier part of a sales pitch when shoppers have less information about a product and are more uncertain about their product valuation.

Suggested Citation

  • Ye Hu & Kitty Wang & Ming Chen & Sam Hui, 2021. "Herding Among Retail Shoppers: the Case of Television Shopping Network," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(1), pages 27-40, June.
  • Handle: RePEc:spr:custns:v:8:y:2021:i:1:d:10.1007_s40547-020-00111-8
    DOI: 10.1007/s40547-020-00111-8
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    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. Hawkins, Scott A & Hoch, Stephen J, 1992. "Low-Involvement Learning: Memory without Evaluation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 19(2), pages 212-225, September.
    3. Marco Cipriani & Antonio Guarino, 2005. "Herd Behavior in a Laboratory Financial Market," American Economic Review, American Economic Association, vol. 95(5), pages 1427-1443, December.
    4. Uri Simonsohn & Dan Ariely, 2008. "When Rational Sellers Face Nonrational Buyers: Evidence from Herding on eBay," Management Science, INFORMS, vol. 54(9), pages 1624-1637, September.
    5. Hu, Ye & Li, Xinxin, 2011. "Context-Dependent Product Evaluations: An Empirical Analysis of Internet Book Reviews," Journal of Interactive Marketing, Elsevier, vol. 25(3), pages 123-133.
    6. Armin Falk & Andrea Ichino, 2006. "Clean Evidence on Peer Effects," Journal of Labor Economics, University of Chicago Press, vol. 24(1), pages 39-58, January.
    7. Richard W. Sias, 2004. "Institutional Herding," The Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 165-206.
    8. Brunnermeier, Markus K., 2001. "Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding," OUP Catalogue, Oxford University Press, number 9780198296980.
    9. Babenko, Ilona & Tserlukevich, Yuri & Vedrashko, Alexander, 2012. "The Credibility of Open Market Share Repurchase Signaling," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(5), pages 1059-1088, October.
    10. Lamont, Owen A., 2002. "Macroeconomic forecasts and microeconomic forecasters," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 265-280, July.
    11. Alba, Joseph W & Hutchinson, J Wesley, 1987. "Dimensions of Consumer Expertise," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(4), pages 411-454, March.
    12. Devenow, Andrea & Welch, Ivo, 1996. "Rational herding in financial economics," European Economic Review, Elsevier, vol. 40(3-5), pages 603-615, April.
    13. Herzenstein, Michal & Dholakia, Utpal M. & Andrews, Rick L., 2011. "Strategic Herding Behavior in Peer-to-Peer Loan Auctions," Journal of Interactive Marketing, Elsevier, vol. 25(1), pages 27-36.
    14. Trueman, Brett, 1994. "Analyst Forecasts and Herding Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 97-124.
    15. Welch, Ivo, 2000. "Herding among security analysts," Journal of Financial Economics, Elsevier, vol. 58(3), pages 369-396, December.
    16. 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.
    17. Zaichkowsky, Judith Lynne, 1985. "Measuring the Involvement Construct," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(3), pages 341-352, December.
    18. Shasha Lu & Li Xiao & Min Ding, 2016. "A Video-Based Automated Recommender (VAR) System for Garments," Marketing Science, INFORMS, vol. 35(3), pages 484-510, May.
    19. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    20. Xin Wang & Ye Hu, 2009. "The effect of experience on Internet auction bidding dynamics," Marketing Letters, Springer, vol. 20(3), pages 245-261, September.
    21. Juanjuan Zhang & Peng Liu, 2012. "Rational Herding in Microloan Markets," Management Science, INFORMS, vol. 58(5), pages 892-912, May.
    22. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    23. Avery, Christopher & Zemsky, Peter, 1998. "Multidimensional Uncertainty and Herd Behavior in Financial Markets," American Economic Review, American Economic Association, vol. 88(4), pages 724-748, September.
    24. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    25. Amy Wenxuan Ding & Shibo Li, 2019. "Herding in the consumption and purchase of digital goods and moderators of the herding bias," Journal of the Academy of Marketing Science, Springer, vol. 47(3), pages 460-478, May.
    26. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    27. Shiller, Robert J, 1995. "Conversation, Information, and Herd Behavior," American Economic Review, American Economic Association, vol. 85(2), pages 181-185, May.
    28. Brown, Jacqueline Johnson & Reingen, Peter H, 1987. "Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(3), pages 350-362, December.
    29. Seshadri Tirunillai & Gerard J. Tellis, 2012. "Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," Marketing Science, INFORMS, vol. 31(2), pages 198-215, March.
    30. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    31. Rajiv Lal & Miklos Sarvary, 1999. "When and How Is the Internet Likely to Decrease Price Competition?," Marketing Science, INFORMS, vol. 18(4), pages 485-503.
    32. Bruce Sacerdote, 2001. "Peer Effects with Random Assignment: Results for Dartmouth Roommates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 681-704.
    33. Avery, Christopher N. & Chevalier, Judith A., 1999. "Herding over the career," Economics Letters, Elsevier, vol. 63(3), pages 327-333, June.
    34. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    35. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    36. Catherine Tucker & Juanjuan Zhang, 2011. "How Does Popularity Information Affect Choices? A Field Experiment," Management Science, INFORMS, vol. 57(5), pages 828-842, May.
    37. Min Ding & Jehoshua Eliashberg & Joel Huber & Ritesh Saini, 2005. "Emotional Bidders---An Analytical and Experimental Examination of Consumers' Behavior in a Priceline-Like Reverse Auction," Management Science, INFORMS, vol. 51(3), pages 352-364, March.
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