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dc.contributor.authorKephart, Jeffrey O.
dc.contributor.authorDas, Rajarshi
dc.contributor.authorBrooks, Christopher H.
dc.contributor.authorDurfee, Edmund H.
dc.contributor.authorGazzale, Robert S.
dc.contributor.authorMacKie-Mason, Jeffrey K.
dc.date.accessioned2007-04-10T20:13:28Z
dc.date.available2007-04-10T20:13:28Z
dc.date.issued2001
dc.identifier.citationACM Electronic Commerce 2001, Tampa. <http://hdl.handle.net/2027.42/50440>en
dc.identifier.urihttps://hdl.handle.net/2027.42/50440
dc.description.abstractWe 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.en
dc.format.extent1368288 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen
dc.titlePricing Information Bundles in a Dynamic Environmenten
dc.typeArticleen_US
dc.subject.hlbsecondlevelInformation and Library Science
dc.subject.hlbtoplevelSocial Sciences
dc.contributor.affiliationumInformation, School ofen
dc.contributor.affiliationumcampusAnn Arboren
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/50440/1/DynamicBundling.pdfen_US
dc.owningcollnameInformation, School of (SI)


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