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A Two-Stage Model of the Promotional Performance of Pure Online Firms

Author

Listed:
  • Jianan Wu

    (A. B. Freeman School of Business, Tulane University, New Orleans, Louisiana 70118)

  • Victor J. Cook

    (A. B. Freeman School of Business, Tulane University, New Orleans, Louisiana 70118)

  • Edward C. Strong

    (A. B. Freeman School of Business, Tulane University, New Orleans, Louisiana 70118)

Abstract

Internet firms frequently employ a two-stage approach to promotional activities. In Stage 1, they attract customers to their websites through advertising. In Stage 2, firms generate sales transactions or sales leads through their website.Comprehensive assessment of the promotional performance of pure online firms requires the study of Stage 1 and of Stage 2 jointly . In this paper we develop a joint two-stage conceptual and econometric model for assessing website promotion on three important dimensions: (1) how advertising response can be measured by linking media schedules to website log files; (2) how advertising and website characteristics jointly affect the desired system outcome of the promotion; and (3) whether the joint investigation of advertising response and desired system outcomes is essential to assess the results of website promotion.Three general findings follow from application of our model to a pure online firm’s campaign to generate sales leads through print advertising. First, advertising and website characteristics affect sales leads in different ways. A characteristic may influence sales leads directly, or indirectly, or both. Second, assessing advertising effectiveness in an online environment may not require costly survey research data. Instead, secondary data available from website log files may be used for such assessment. Third, the interaction between the first and second stages of our two-stage model can lead to misspecifications that produce misleading inferences. This occurs because the unobserved characteristics in generating website visits and sales leads may be correlated.

Suggested Citation

  • Jianan Wu & Victor J. Cook & Edward C. Strong, 2005. "A Two-Stage Model of the Promotional Performance of Pure Online Firms," Information Systems Research, INFORMS, vol. 16(4), pages 334-351, December.
    • Handle: RePEc:inm:orisre:v:16:y:2005:i:4:p:334-351
    DOI: 10.1287/isre.1050.0071
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    References listed on IDEAS

    as
    1. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    2. Pei-Yu (Sharon) Chen & Lorin M. Hitt, 2002. "Measuring Switching Costs and the Determinants of Customer Retention in Internet-Enabled Businesses: A Study of the Online Brokerage Industry," Information Systems Research, INFORMS, vol. 13(3), pages 255-274, September.
    3. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    4. Jonathan W. Palmer, 2002. "Web Site Usability, Design, and Performance Metrics," Information Systems Research, INFORMS, vol. 13(2), pages 151-167, June.
    5. Ritu Agarwal & Viswanath Venkatesh, 2002. "Assessing a Firm's Web Presence: A Heuristic Evaluation Procedure for the Measurement of Usability," Information Systems Research, INFORMS, vol. 13(2), pages 168-186, June.
    6. Edell, Julie E & Staelin, Richard, 1983. "The Information Processing of Pictures in Print Advertisements," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(1), pages 45-61, June.
    7. William Greene, 1998. "Gender Economics Courses in Liberal Arts Colleges: Comment," Working Papers 98-06, New York University, Leonard N. Stern School of Business, Department of Economics.
    8. Punj, Girish N & Staelin, Richard, 1983. "A Model of Consumer Information Search Behavior for New Automobiles," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(4), pages 366-380, March.
    9. Robert C. Blattberg & Abel P. Jeuland, 1981. "A Micromodeling Approach to Investigate the Advertising-Sales Relationship," Management Science, INFORMS, vol. 27(9), pages 988-1005, September.
    10. Maurice W. Sasieni, 1971. "Optimal Advertising Expenditure," Management Science, INFORMS, vol. 18(4-Part-II), pages 64-72, December.
    11. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    12. Vijay Mahajan & Eitan Muller, 1986. "Reply—Reflections on Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 110-111.
    13. Jianan Wu & Arvind Rangaswamy, 2003. "A Fuzzy Set Model of Search and Consideration with an Application to an Online Market," Marketing Science, INFORMS, vol. 22(3), pages 411-434, March.
    14. Wendy W. Moe & Peter S. Fader, 2004. "Dynamic Conversion Behavior at E-Commerce Sites," Management Science, INFORMS, vol. 50(3), pages 326-335, March.
    15. William H. Greene, 1998. "Gender Economics Courses in Liberal Arts Colleges: Further Results," The Journal of Economic Education, Taylor & Francis Journals, vol. 29(4), pages 291-300, January.
    16. van Ophem, Hans, 2000. "Modeling Selectivity in Count-Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 503-511, October.
    17. Boyes, William J. & Hoffman, Dennis L. & Low, Stuart A., 1989. "An econometric analysis of the bank credit scoring problem," Journal of Econometrics, Elsevier, vol. 40(1), pages 3-14, January.
    18. Detmar W. Straub & Donna L. Hoffman & Bruce W. Weber & Charles Steinfield, 2002. "Toward New Metrics for Net-Enhanced Organizations," Information Systems Research, INFORMS, vol. 13(3), pages 227-238, September.
    19. Keller, Kevin Lane, 1991. "Memory and Evaluation Effects in Competitive Advertising Environments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(4), pages 463-476, March.
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