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Versioning and Quality Distortion in Software? Evidence from E-Commerce Panel Data

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Author Info

  • Anindya Ghose

    ()
    (NYU, Stern School of Business)

  • Arun Sundararajan

    ()
    (NYU, Stern School of Business)

Abstract

We present a framework for measuring software quality using pricing and demand data, and empirical estimates that quantify the extent of quality degradation associated with software ver- sioning. Using a 7-month, 108-product panel of software sales from Amazon.com, we document the extent to which quality varies across di¤erent software versions, estimating quality degradation that ranges from as little as 8% to as much as 56% below that of the corresponding ?agship ver- sion. Consistent with prescriptions from the theory of vertical di¤erentiation, we also ?nd that an increase in the total number of versions is associated with an increase in the di¤erence in quality between the highest and lowest quality versions, and a decrease in the quality di¤erence between "neighboring" versions. We compare our estimates with those derived from two sets of subjective measures of quality, based on CNET editorial ratings and Amazon.com user reviews, and discuss competing interpretations of the signi?cant di¤erences that emerge from this comparison. As the ?rst empirical study of software versioning that is based on both subjective and econometrically estimated measures of quality, this paper provides a framework for testing a wide variety of results in IS that are based on related models of vertical di¤erentiation, and its ?ndings have important implications for studies that treat web-based user ratings as cardinal data.

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Bibliographic Info

Paper provided by NET Institute in its series Working Papers with number 05-14.

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Length: 31 pages
Date of creation: Oct 2005
Date of revision: Oct 2005
Handle: RePEc:net:wpaper:0514

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Web page: http://www.NETinst.org/

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  1. Severin Borenstein & Nancy L. Rose, 1991. "Competition and Price Dispersion in the U.S. Airline Industry," NBER Working Papers 3785, National Bureau of Economic Research, Inc.
  2. Anindya Ghose & Vidyanand Choudhary & Tridas Mukhopadhyay & Uday Rajan, 2002. "Personalized Pricing and Quality Differentiation on the Internet," Review of Marketing Science Working Papers 2-1-1005, Berkeley Electronic Press.
  3. Raymond J. Deneckere & R. Preston McAfee, 1996. "Damaged Goods," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 5(2), pages 149-174, 06.
  4. Boom, Anette, 2004. ""Download for Free" - When Do Providers of Digital Goods Offer Free Samples?," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 70, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
  5. Kwoka, John E, Jr, 1992. "Market Segmentation by Price-Quality Schedules: Some Evidence from Automobiles," The Journal of Business, University of Chicago Press, vol. 65(4), pages 615-28, October.
  6. Mussa, Michael & Rosen, Sherwin, 1978. "Monopoly and product quality," Journal of Economic Theory, Elsevier, vol. 18(2), pages 301-317, August.
  7. Judith Chevalier & Austan Goolsbee, 2003. "Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com," Quantitative Marketing and Economics, Springer, vol. 1(2), pages 203-222, June.
  8. Arun Sundararajan, 2003. "Managing Digital Piracy: Pricing, Protection and Welfare," Law and Economics 0307001, EconWPA.
  9. Erik Brynjolfsson & Yu (Jeffrey) Hu & Michael D. Smith, 2003. "Consumer Surplus in the Digital Economy: Estimating the Value of Increased Product Variety at Online Booksellers," Management Science, INFORMS, vol. 49(11), pages 1580-1596, November.
  10. Eugenio J. Miravete, 2002. "Estimating Demand for Local Telephone Service with Asymmetric Information and Optional Calling Plans," Review of Economic Studies, Oxford University Press, vol. 69(4), pages 943-971.
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