Pricing Information Bundles in a Dynamic Environment

ACM Electronic Commerce, 2001

Posted: 7 Apr 2007

See all articles by Jeffrey O. Kephart

Jeffrey O. Kephart

IBM Research

Rajarshi Das

IBM Research

Christopher H. Brooks

University of San Francisco

Edmund Durfee

University of Michigan at Ann Arbor - Department of Electrical Engineering and Computer Science

Robert S. Gazzale

University of Toronto - Department of Economics; Williams College - Department of Economics

Jeffrey K. MacKie-Mason

UC Berkeley; University of Michigan

Abstract

We explore a scenario in which a monopolist producer of information goods seeks to maximize its profits in a market where consumer demand shifts frequently and unpredictably. The producer is free to set an arbitrarily complex price schedule-a function that maps the set of purchased items to a price-but without direct knowledge of consumer demand it cannot compute the optimal schedule. Instead, it must employ a form of optimization based on trial and error. By means of a simple model of consumer demand and a modified version of a simple nonlinear optimization routine, we study a variety of parameterizations of the price schedule and quantity some of the relationships among learnability, complexity, and profitability. In particular, we show that fixed pricing or simple two-parameter dynamic pricing schedules are preferred when consumer demand shifts frequently, but that dynamic pricing based on more complex schedules tends to be most profitable when consumer demand shifts very infrequently.

Suggested Citation

Kephart, Jeffrey O. and Das, Rajarshi and Brooks, Christopher H. and Durfee, Edmund and Gazzale, Robert S. and MacKie-Mason, Jeffrey K., Pricing Information Bundles in a Dynamic Environment. ACM Electronic Commerce, 2001, Available at SSRN: https://ssrn.com/abstract=978063

Jeffrey O. Kephart (Contact Author)

IBM Research ( email )

T. J. Watson Research Center
1 New Orchard Road
Armonk, NY 10504-1722
United States

Rajarshi Das

IBM Research ( email )

T. J. Watson Research Center
1 New Orchard Road
Armonk, NY 10504-1722
United States

Christopher H. Brooks

University of San Francisco ( email )

2130 Fulton Street
San Francisco, CA 94117
United States

Edmund Durfee

University of Michigan at Ann Arbor - Department of Electrical Engineering and Computer Science ( email )

1101 Beal Avenue
Ann Arbor, MI 48109
United States

Robert S. Gazzale

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S 3G7
Canada
416.978.2123 (Phone)

HOME PAGE: http://www.economics.utoronto.ca/gazzale/

Williams College - Department of Economics ( email )

24 Hopkins Hall Drive
Williamstown, MA 01267
United States

Jeffrey K. MacKie-Mason

UC Berkeley ( email )

102 South Hall
Berkeley, CA 94720-4600
United States

HOME PAGE: http://jeff-mason.com

University of Michigan ( email )

Ann Arbor, MI 48109-1092
United States

HOME PAGE: http://http:/jeff-mason.com/

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