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Search Costs, Demand Structure and Long Tail in Electronic Markets: Theory and Evidence

Author

Listed:
  • Anindya Ghose

    (Stern School of Business, New York University)

  • Bin Gu

    (McCombs School of Business, University of Texas at Austin)

Abstract

It is well known that the Internet has significantly reduced consumers’ search costs online. But relatively little is known about how search costs affect consumer demand structure in online markets. In this paper, we identify the impact of search costs on firm competition and market structure by exploring a unique theoretical insight that search costs create a kink in aggregate demand when firms change prices. The significance of the kink reflects the magnitude of online search costs and the kinked demand function provides information on how search costs affect competition in the online market. Using a dataset collected from Amazon and Barnes & Noble, we find that search costs vary significantly across online retailers. Consumers face low search costs for price information from Amazon.com. It leads to a higher price elasticity when the firm reduces prices than when it increases prices, increasing Amazon’s incentive to engage in price competition. On the other hand, consumers face relatively higher search costs for price information from Barnes & Noble. This leads to a lower price elasticity when Barnes & Noble reduces prices than when it increases prices, reducing Barnes & Noble’s incentive to engage in price competition. We also find that search costs decrease with the passage of time as the information about price changes dissipates among consumers, leading to increased price elasticity over time. Finally, we highlight that search costs are lower for popular books compared to rare and unpopular books. These findings have implications for the impact of the Internet on the Long Tail phenomenon.

Suggested Citation

  • Anindya Ghose & Bin Gu, 2006. "Search Costs, Demand Structure and Long Tail in Electronic Markets: Theory and Evidence," Working Papers 06-19, NET Institute, revised Oct 2006.
  • Handle: RePEc:net:wpaper:0619
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    File URL: http://www.netinst.org/Ghose-Gu.pdf
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    References listed on IDEAS

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    Cited by:

    1. Oliver Hinz & Jochen Eckert, 2010. "The Impact of Search and Recommendation Systems on Sales in Electronic Commerce," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(2), pages 67-77, April.
    2. Boivin, Jean & Clark, Robert & Vincent, Nicolas, 2012. "Virtual borders," Journal of International Economics, Elsevier, vol. 86(2), pages 327-335.
    3. Jean Boivin & Robert Clark & Nicolas Vincent, 2010. "Virtual Borders: Online Nominal Rigidities and International Market Segmentation," NBER Working Papers 15642, National Bureau of Economic Research, Inc.
    4. Budzinski, Oliver & Gänßle, Sophia & Lindstädt-Dreusicke, Nadine, 2021. "Data (r)evolution - The economics of algorithmic search and recommender services," Ilmenau Economics Discussion Papers 148, Ilmenau University of Technology, Institute of Economics.
    5. Eyal Carmi & Gal OEstreicher-Singer & Arun Sundararajan, 2010. "Is Oprah Contagious? Identifying Demand Spillovers in Product Networks," Working Papers 10-18, NET Institute.
    6. Georgios Alaveras & Estrella Gomez Herrera & Bertin Martens, 2015. "Geographic Fragmentation in the EU Market for e-Books: The case of Amazon," JRC Working Papers on Digital Economy 2015-13, Joint Research Centre.

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    More about this item

    Keywords

    Electronic Markets; Search Costs; Kinked Demand Curve; Price Elasticity; Price Competition; Long Tail;
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