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Do Better Customers Utilize Electronic Distribution Channels? The Case of PC Banking

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Author Info

  • Lorin M. Hitt

    ()
    (University of Pennsylvania, Wharton School, Philadelphia, Pennsylvania 19104)

  • Frances X. Frei

    ()
    (Harvard Business School, Cambridge, Massachusetts)

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    Abstract

    Many service firms are pursuing electronic distribution strategies to augment existing physical infrastructure for product and service delivery. But little systematic study has been made for whether and how characteristics or behaviors might differ between customers who use electronic delivery systems and those who use traditional channels. We explore these differences by comparing customers who utilize personal-computer-based home banking (PC banking) to other bank customers. Case studies and detailed customer data from four institutions suggest that PC banking customers are apparently more profitable, principally due to unobservable characteristics extant before the adoption of PC banking. Demographic characteristics and changes in customer behavior following adoption of PC banking account for only a small fraction of overall differences. It also appears that retention is marginally higher for customers of the online channel.

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    File URL: http://dx.doi.org/10.1287/mnsc.48.6.732.188
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 48 (2002)
    Issue (Month): 6 (June)
    Pages: 732-748

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    Handle: RePEc:inm:ormnsc:v:48:y:2002:i:6:p:732-748

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    Related research

    Keywords: online banking; financial services; electronic commerce; customer profitability;

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    Cited by:
    1. Paredes - Araya, Dusan, 2009. "A Methodology to Compute Regional Housing Index Price using Matching Estimator Methods," MPRA Paper 15016, University Library of Munich, Germany, revised 04 May 2009.
    2. Oz Shy, 2013. "Window shopping," Working Papers 13-4, Federal Reserve Bank of Boston.
    3. Schroeter, Christiane & Anders, Sven M., 2013. "Nutrition Label Usage, Diet Health Behavior, and Information Uncertainty," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151214, Agricultural and Applied Economics Association.
    4. Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
    5. Gensler, Sonja & Leeflang, Peter & Skiera, Bernd, 2013. "Comparing methods to separate treatment from self-selection effects in an online banking setting," Journal of Business Research, Elsevier, vol. 66(9), pages 1272-1278.
    6. Hu, Yu Jeffrey & Tang, Zhulei, 2014. "The impact of sales tax on internet and catalog sales: Evidence from a natural experiment," International Journal of Industrial Organization, Elsevier, vol. 32(C), pages 84-90.
    7. Anja Lambrecht & Katja Seim & Catherine Tucker, 2007. "Stuck in the Adoption Funnel: The Effect of Delays in the Adoption Process on Ultimate Adoption," Working Papers 07-40, NET Institute, revised Oct 2007.
    8. Abdul Wadud, 2013. "Impact of Microcredit on Agricultural Farm Performance and Food Security in Bangladesh," Working Papers 14, Institute of Microfinance (InM).
    9. Anja Lambrecht & Katja Seim, 2006. "Adoption and Usage of Online Services in the Presence of Complementary Offline Services: Retail Banking," Working Papers 06-27, NET Institute, revised Oct 2006.

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