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Search and Product Differentiation at an Internet Shopbot

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  • Brynjolfsson, Erik
  • Dick, Astrid Andrea
  • Smith, Michael D.

Abstract

Price dispersion among commodity goods is typically attributed to consumer search costs. We explore the magnitude of consumer search costs using a data set obtained from a major Internet shopbot. For the median consumer, the benefits to searching lower screens are $2.24 while the cost of an exhaustive search of the offers is a maximum of $2.03. Interestingly, in our setting, consumers who search more intensively are less price sensitive than other consumers, reflecting their increased weight on retailer differentiation in delivery time and reliability. Our results demonstrate that even in this nearly-perfect market, substantial price dispersion can exist in equilibrium from consumers preferences over both price and non-price attributes

Suggested Citation

  • Brynjolfsson, Erik & Dick, Astrid Andrea & Smith, Michael D., 2004. "Search and Product Differentiation at an Internet Shopbot," Working papers 4441-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
  • Handle: RePEc:mit:sloanp:5046
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    References listed on IDEAS

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    Cited by:

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    2. Michael R. Baye & John Morgan & Patrick Scholten, 2006. "Information, Search, and Price Dispersion," Working Papers 2006-11, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    3. Stühmeier Torben, 2015. "Price Disclosure Rules and Consumer Price Comparison," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(2), pages 815-835, April.
    4. Anindya Ghose & Michael D. Smith & Rahul Telang, 2006. "Internet Exchanges for Used Books: An Empirical Analysis of Product Cannibalization and Welfare Impact," Information Systems Research, INFORMS, vol. 17(1), pages 3-19, March.
    5. Wojciech Hardy, 2020. "Consumer switching costs in a market with legal and pirate providers," IBS Working Papers 08/2020, Instytut Badan Strukturalnych.
    6. Anindya Ghose & Sha Yang, 2009. "An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets," Management Science, INFORMS, vol. 55(10), pages 1605-1622, October.
    7. Anindya Ghose, 2005. "Used Good Trade Patterns: A Cross-Country Comparison of Electronic Secondary Markets," Working Papers 05-19, NET Institute, revised Oct 2005.
    8. Gérard P. Cachon & Christian Terwiesch & Yi Xu, 2008. "On the Effects of Consumer Search and Firm Entry in a Multiproduct Competitive Market," Marketing Science, INFORMS, vol. 27(3), pages 461-473, 05-06.
    9. Baomin Dong & Guixia Guo & Frank Yong Wang, 2021. "A signalling model of loss leader pricing strategy," Australian Economic Papers, Wiley Blackwell, vol. 60(2), pages 289-307, June.
    10. Animesh Animesh & Siva Viswanathan & Ritu Agarwal, 2011. "Competing “Creatively” in Sponsored Search Markets: The Effect of Rank, Differentiation Strategy, and Competition on Performance," Information Systems Research, INFORMS, vol. 22(1), pages 153-169, March.
    11. Sha Yang & Anindya Ghose, 2010. "Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence?," Marketing Science, INFORMS, vol. 29(4), pages 602-623, 07-08.
    12. Chen Liang & Yili Hong & Bin Gu, 2016. "Effects of IT-enabled Monitoring on Labor Contracting in Online Platforms: Evidence from a Natural Experiment," Working Papers 16-01, NET Institute.
    13. Jeffrey D. Shulman & Xianjun Geng, 2019. "Does It Pay to Shroud In-App Purchase Prices?," Information Systems Research, INFORMS, vol. 30(3), pages 856-871, September.
    14. Arnold, Michael & Zhang, Lan, 2020. "Competition with an information clearinghouse and asymmetric firms: Why more than two firms compete (or not) for shoppers," Games and Economic Behavior, Elsevier, vol. 122(C), pages 55-82.

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