Efficient Pricing of Geomarketing Internet Services
Efficient Pricing of Geomarketing Internet Services: European vs. American Approach
Alenka Krek Institute for Geoinformation, Technical University Vienna Gusshausstrasse 27-29/127, A-1040 Vienna krek@geoinfo.tuwien.ac.at
Abstract Geomarketing information is information which enables the user to take better and faster decisions about marketing and sales activities. The main source of information are geographic, demographic, and statistic data. These data are usually collected and maintained by several institutions and come in a variety of forms and formats. The final integrators acquire datasets, sort, filter and organize them, and offer in advance defined analyses. In this paper we focus on geomarketing services offered on the Internet where usually no physical good is exchanged. The subject of trade is geomarketing information the user is able to extract from the datasets. The main issue is how to set a Pareto efficient price for geomarketing information. The situation is Pareto efficient when the sum of user’s and service provider’s surplus is maximized. We investigate nonlinear pricing strategies and their efficiency to serve mass markets and attract users with different willingness to pay. Nonlinear pricing is used in a broader sense to include the practice of selling the same information product on various vertical markets at prices that are not in proportion to the differences in marginal cost. The market research for the GISMO project (Krek et al. 2000) showed that the US market differs substantially from the European. It has characteristics of a commodity market, where providers offer very similar or equal products at similar prices. This is feasible only if the prices for raw datasets, which represent the main barrier to enter the market, are low or zero. Competition among service providers drives prices down and enables them to successfully serve a mass market. The European approach is mostly determined by the high prices of datasets and restrictions
Alenka Krek Institute for Geoinformation, Technical University Vienna Gusshausstrasse 27-29/127, A-1040 Vienna krek@geoinfo.tuwien.ac.at
Abstract Geomarketing information is information which enables the user to take better and faster decisions about marketing and sales activities. The main source of information are geographic, demographic, and statistic data. These data are usually collected and maintained by several institutions and come in a variety of forms and formats. The final integrators acquire datasets, sort, filter and organize them, and offer in advance defined analyses. In this paper we focus on geomarketing services offered on the Internet where usually no physical good is exchanged. The subject of trade is geomarketing information the user is able to extract from the datasets. The main issue is how to set a Pareto efficient price for geomarketing information. The situation is Pareto efficient when the sum of user’s and service provider’s surplus is maximized. We investigate nonlinear pricing strategies and their efficiency to serve mass markets and attract users with different willingness to pay. Nonlinear pricing is used in a broader sense to include the practice of selling the same information product on various vertical markets at prices that are not in proportion to the differences in marginal cost. The market research for the GISMO project (Krek et al. 2000) showed that the US market differs substantially from the European. It has characteristics of a commodity market, where providers offer very similar or equal products at similar prices. This is feasible only if the prices for raw datasets, which represent the main barrier to enter the market, are low or zero. Competition among service providers drives prices down and enables them to successfully serve a mass market. The European approach is mostly determined by the high prices of datasets and restrictions
References: Gong, J. and P. Srinagesh, The Economics of Layered Networks.,Internet Economics, L. W. McKnight and J. P. Bailey, The MIT Press, Cambridge, Massachusetts, 1998. Krek, A., H. Hochmair, P. Wenzl, Comparison study of the geomarketing services available on the Internet, GISMO project - Second progress report, Institute for Geoinformation, TU Vienna, pp 61, 2000. Pigou, A. C., The Economics of Welfare, Macmillan, London, 1920. Samuelson, P. A., Economics, An Introductory Analysis, McGraw-Hill Book Company, Inc., 1967 Tapscott, D., The digital economy: promise and peril in the age of networked intelligence, McGraw-Hill, Inc., USA, 1996. Varian, H. R., “Price Discrimination and Social Welfare.” American Economic Review 75: 870875, 1985. Varian, H. R., “Differential pricing and efficiency.” First Monday, peer-reviewed journal on the internet, 1999. Wilson, R., Nonlinear pricing, Oxford University Press, Inc., New York, 1993. 9