Pricing with Limited Knowledge of Demand
Name
w21679.pdf
Size
377.93 KB
Format
Adobe PDF
Checksum (MD5)
a37ebf7203687a5298a5e0a16fc11b55
Author(s)
Cohen, Maxime C.
Perakis, Georgia
Pindyck, Robert S
Date Issued
July 2016
Journal
Proceedings of the 2016 ACM Conference on Economics and Computation - EC '16
Publisher
Association for Computing Machinery (ACM)
Citation
Cohen, Maxime C., Georgia Perakis, and Robert S. Pindyck. “Pricing with Limited Knowledge of Demand.” Proceedings of the 2016 ACM Conference on Economics and Computation - EC ’16, 24-28 July, 2016, Maastricht, The Netherlands, ACM, 2016.
Version
Original manuscript
Abstract
How should a firm price a new product for which little is known about demand? We propose a pricing rule that can be used if the firm can estimate (even roughly) the maximum price it can charge and still expect to sell some units, and the firm need not know in advance the quantity it will sell. The rule is simple: Set price as though the demand curve were linear. We show that if the true demand curve is one of many commonly used demand functions, or even a more complex function, and if marginal cost is known and constant, the firm can expect its profit to be close to what it would earn if it knew the true demand curve. We derive analytical performance bounds for a variety of demand functions, calculate expected profit performance for randomly generated demand curves, and evaluate the welfare implications of our pricing rule.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2940716.2940734
