Evaluating Pricing Strategy Using e-Commerce Data: Evidence and Estimation Challenges
As Internet-based commerce becomes increasingly widespread, large data sets about the demand for and pricing of a wide variety of products become available. These present exciting new opportunities for empirical economic and business research, but also raise new statistical issues and challenges. In this article, we summarize research that aims to assess the optimality of price discrimination in the software industry using a large e-commerce panel data set gathered from Amazon.com. We describe the key parameters that relate to demand and cost that must be reliably estimated to accomplish this research successfully, and we outline our approach to estimating these parameters. This includes a method for ``reverse engineering'' actual demand levels from the sales ranks reported by Amazon, and approaches to estimating demand elasticity, variable costs and the optimality of pricing choices directly from publicly available e-commerce data. Our analysis raises many new challenges to the reliable statistical analysis of e-commerce data and we conclude with a brief summary of some salient ones.
|Date of creation:||Sep 2006|
|Date of revision:|
|Publication status:||Published in Statistical Science 2006, Vol. 21, No. 2, 131-142|
|Contact details of provider:|| Web page: http://arxiv.org/|
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- Yannis Bakos & Erik Brynjolfsson, 1999.
"Bundling Information Goods: Pricing, Profits, and Efficiency,"
INFORMS, vol. 45(12), pages 1613-1630, December.
- Yannis Bakos & Erik Brynjolfsson, 1997. "Bundling Information Goods: Pricing, Profits and Efficiency," Working Paper Series 199, MIT Center for Coordination Science.
- 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.
- Arun Sundararajan, 2003. "Nonlinear pricing of information goods," Industrial Organization 0307003, EconWPA.
- 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,"
INFORMS, vol. 49(11), pages 1580-1596, November.
- Brynjolfsson, Erik & Smith, Michael D. & Yu, (Jeffrey) Hu, 2003. "Consumer Surplus in the Digital Economy: Estimating the Value of Increased Product Variety at Online Booksellers," Working papers 4305-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Jerry A. Hausman, 1996.
"Valuation of New Goods under Perfect and Imperfect Competition,"
in: The Economics of New Goods, pages 207-248
National Bureau of Economic Research, Inc.
- Jerry A. Hausman, 1994. "Valuation of New Goods under Perfect and Imperfect Competition," NBER Working Papers 4970, National Bureau of Economic Research, Inc.
- Hausman, J.A., 1994. "Valuation of New Goods Under Perfect and Imperfect Competition," Working papers 94-21, Massachusetts Institute of Technology (MIT), Department of Economics.
- Arun Sundararajan, 2003. "Managing Digital Piracy: Pricing, Protection and Welfare," Law and Economics 0307001, EconWPA.
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