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Pricing of partially compatible products
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Electronic Commerce archive
Proceedings of the 8th ACM conference on Electronic commerce table of contents
San Diego, California, USA
SESSION: The price is optimal table of contents
Pages: 218 - 226  
Year of Publication: 2007
ISBN:978-1-59593-653-0
Authors
David Kempe  University of Southern California, Los Angeles, CA
Adam Meyerson  UCLA, Los Angeles, CA
Nainesh Solanki  Media Defender: Inc., Los Angeles, CA
Ramnath Chellappa  Emory University, Atlanta, GA
Sponsors
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we examine a duopolistic market where the two firms compete to sell a system of components. Components are digital (firms haveunlimited supply at no marginal cost), and customers are homogeneous in their component preferences. Each customer will assemble a utility maximizing system by purchasing each necessary component from one of the two firms. While components from the same firm are always compatible, pairwise compatibility of components from rival firms may vary; in addition to utility due to the quality of the system purchased, customers have negative utility for purchasing incompatible parts. We investigate algorithms and hardness results for profit-maximizing decisions of the firms with regards to their price-setting, component value-enhancing and compatibility-enabling strategies. The users' behavior can be modeled as a minimum cut computation, and the company's strategies require addressing novel and interesting questions about graph cuts and flows. We develop a polynomial-time algorithm for finding profit-maximizing prices if the qualities and compatibilities are fixed. On the other hand, we show that finding profit-maximizing quality improvements is equivalent to the Maximum Size Bounded Capacity Cut problem, and thus NP-complete. Finally, for the problem of improving compatibilities to maximize the price, we give polynomial approximation hardness results even in very restricted cases, but show that if all components have uniform prices, and quality differences are small, then an approximation can be found in polynomial time.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
David Kempe: colleagues
Adam Meyerson: colleagues
Nainesh Solanki: colleagues
Ramnath Chellappa: colleagues