Nonlinear Pricing of Information Goods

Stern School of Business Working Paper No. EC-03-16

43 Pages Posted: 6 Feb 2002

See all articles by Arun Sundararajan

Arun Sundararajan

NYU Stern School of Business; New York University (NYU) - Center for Data Science

Multiple version iconThere are 3 versions of this paper

Date Written: July 2003

Abstract

This paper analyzes optimal pricing for information goods under incomplete information, when both unlimited-usage (fixed-fee) pricing and usage-based pricing are feasible, and administering usage-based pricing may involve transaction costs. It is shown that offering fixed-fee pricing in addition to a non-linear usage-based pricing scheme is always profit-improving in the presence of any non-zero transaction costs, and there may be markets in which a pure fixed-fee is optimal. This implies that the optimal pricing strategy for information goods is almost never fully revealing. Moreover, it is proved that the optimal usage-based pricing schedule is independent of the value of the fixed-fee, a result that simplifies the simultaneous design of pricing schedules considerably, and provides a simple procedure for determining the optimal combination of fixed-fee and non-linear usage-based pricing. The introduction of fixed-fee pricing is shown to increase both consumer surplus and total surplus. The differential effects of setup costs, fixed transaction costs and variable transaction costs on pricing policy are described.

These results suggests a number of managerial guidelines for designing pricing schedules. For instance, in nascent information markets, firms may profit from low fixed-fee penetration pricing, but as these markets mature, the optimal pricing mix should expand to include a wider range of usage-based pricing options. The extent of minimum fees, quantity discounts and adoption levels across the different pricing schemes are characterized, strategic pricing responses to changes in market characteristics are described, and the implications of the paper's results for bundling and vertical differentiation of information goods are discussed.

Keywords: pricing, nonlinear pricing, screening, adverse selection, nonlinear pricing, information goods, digital goods, electronic markets, Internet, software pricing, ASP, second-degree price discrimination

JEL Classification: D42, D82, L1

Suggested Citation

Sundararajan, Arun, Nonlinear Pricing of Information Goods (July 2003). Stern School of Business Working Paper No. EC-03-16 , Available at SSRN: https://ssrn.com/abstract=299337 or http://dx.doi.org/10.2139/ssrn.299337

Arun Sundararajan (Contact Author)

NYU Stern School of Business ( email )

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New York University (NYU) - Center for Data Science ( email )

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