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When Shopbots Meet Emails: Implications for Price Competition on the Internet

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  • Yuxin Chen
  • K. Sudhir

Abstract

The Internet has dramatically reduced search costs for customers by using such technologies as shopbots. Email based targeting is relatively inexpensive; the targeting itself can be more precise because firms can better track individual purchase behavior on the Internet. In this paper we address the question: How does the convergence of low search cost for consumers and better targeting ability for firms affect price competition on the Internet? Current theoretical research suggests that both (1) lower search costs and (2) better targeting ability generally lead to more intense price competition. Taken individually, these results would lead us to expect that there will be greater price competition on the Internet due to lower search costs and better targeting. In this paper, we argue that targeting ability increases as search costs fall. Falling search costs can lead to improvements in targeting ability in the form of greater "targeting reach" (the ability to individually address consumers) and "precision" (the ability to distinguish consumers on the basis of their loyalty). We show that the interaction between consumer search and targeting ability can reduce the intensity of competition and raise prices as consumer search and targeting become easier on the Internet.

Suggested Citation

  • Yuxin Chen & K. Sudhir, 2004. "When Shopbots Meet Emails: Implications for Price Competition on the Internet," Quantitative Marketing and Economics (QME), Springer, vol. 2(3), pages 233-255, September.
  • Handle: RePEc:kap:qmktec:v:2:y:2004:i:3:p:233-255
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    References listed on IDEAS

    as
    1. J. Yannis Bakos, 1997. "Reducing Buyer Search Costs: Implications for Electronic Marketplaces," Management Science, INFORMS, vol. 43(12), pages 1676-1692, December.
    2. Yuxin Chen & Chakravarthi Narasimhan & Z. John Zhang, 2001. "Individual Marketing with Imperfect Targetability," Marketing Science, INFORMS, vol. 20(1), pages 23-41, November.
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    Citations

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    Cited by:

    1. Fernando Branco & Monic Sun & J. Miguel Villas-Boas, 2012. "Optimal Search for Product Information," Management Science, INFORMS, vol. 58(11), pages 2037-2056, November.
    2. Zheyin (Jane) Gu & Yunchuan Liu, 2013. "Consumer Fit Search, Retailer Shelf Layout, and Channel Interaction," Marketing Science, INFORMS, vol. 32(4), pages 652-668, July.
    3. Dutta, Champa Bati & Das, Debasish Kumar, 2017. "What drives consumers' online information search behavior? Evidence from England," Journal of Retailing and Consumer Services, Elsevier, vol. 35(C), pages 36-45.
    4. Bilal AFSAR & Jawaria Andleeb QURESHI & Asim REHMAN & Rehmat Ullah BANGASH, 2011. "Consumer Panacea Over Internet Usage In Pakistan," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(1), pages 43-52, May.
    5. Erik Brynjolfsson & Astrid Dick & Michael Smith, 2010. "A nearly perfect market?," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 1-33, March.
    6. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
    7. Maarten C. W. Janssen & Marielle C. Non, 2009. "Going Where the Ad Leads You: On High Advertised Prices and Searching Where to Buy," Marketing Science, INFORMS, vol. 28(1), pages 87-98, 01-02.
    8. V. Kumar & Ashutosh Dixit & Rajshekar (Raj) G. Javalgi & Mayukh Dass, 2016. "Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing," Journal of the Academy of Marketing Science, Springer, vol. 44(1), pages 24-45, January.
    9. Raj, S.P. & Rhee, Byong-Duk & Sivakumar, K., 2020. "Manufacturer adoption of a unilateral pricing policy in a multi-channel setting to combat customer showrooming," Journal of Business Research, Elsevier, vol. 110(C), pages 104-118.
    10. Jie Jennifer Zhang & Bing Jing, 2007. "The Impacts of Shopbots on Online Consumer Search," Working Papers 07-34, NET Institute, revised Sep 2007.

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    More about this item

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • L0 - Industrial Organization - - General
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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