| Price issues in delivering E-content on-demand |
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ACM SIGecom Exchanges
archive
Volume 3 , Issue 2 (Spring, 2002)
table of contents
Pages: 18 - 27
Year of Publication: 2002
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Downloads (6 Weeks): 0, Downloads (12 Months): 11, Citation Count: 1
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ABSTRACT
The explosive increase in Internet bandwidth and usage opens a vista of opportunities to sell multimedia-rich software and services using the Internet. Once e-content is created, the cost of replication is negligible. Customers can download the e-content immediately after online transactions. Alternately, the content provider can stream the content to the customers. A sound business model is necessary for the success of such an enterprise. In this paper, we examine the determinants of revenue for an Internet based on-demand content delivery service. The determinants of revenue are: transaction model, pricing strategy, customer behavior, distribution resources, and competition. We briefly describe each of these factors and discuss how they relate to revenue. Our belief is that by better understanding how these factors affect revenue, content providers can develop services that generate more revenue while also being more compelling to users.
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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ALMEROTH, K., DAN, A., SITARAM, D., AND TETZLAFF, W. 1997. Long term channel allocation strategies for video applications. In IEEE Infocom.
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BRESLAU, L., CAO, P., FAN, L., PHILLIPS, G., AND SHENKER, S. 1999. Web caching and zipf-like distributions: Evidence and implications. In Infocom. 126-134.
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CHAN, S. AND TOBAGI, F. 1999. On achieving profit in providing near video-on-demand services. In Proceedings of the 1999 IEEE International Conference on Communications (ICC'99).
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CHAVEZ, A. AND MAES, P. 1996. Kasbah: an agent marketplace for buying and selling goods. In Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology.
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A. Dan , D. Sitaram , P. Shahabuddin, Scheduling policies for an on-demand video server with batching, Proceedings of the second ACM international conference on Multimedia, p.15-23, October 15-20, 1994, San Francisco, California, United States
[doi> 10.1145/192593.192614]
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JAGANNATHAN, S. AND ALMEROTH, K. C. 2001a. An adaptive pricing scheme for content delivery systems. In Global Internet Symposium. San Antonio, Texas, USA.
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JAGANNATHAN, S., NAYAK, J., ALMEROTH, K., AND HOFMANN, M. 2001. E-content pricing: Analysis and simulation. Tech. rep., University of California Santa Barbara. available at http://www.nmsl.cs.ucsb.edu/papers/ECONTENTPRC.ps.gz.
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JAGANNATHAN, S., NAYAK, J., ALMEROTH, K., AND HOFMANN, M. 2002. On pricing algorithms for batched content delivery systems. Tech. rep., University of California Santa Barbara. available at http://www.nmsl.cs.ucsb.edu/papers/BatchingPrc.ps.gz.
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ODLYZKO, A. 2000. The history of communications and its implications for the Internet. available at http://www.research.att.com/-amo/doc/networks.html.
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TSVETOVATY, M., GINI, M., MOBASHER, B., AND WIECKOWSKI, Z. 1997. Magma: an agent-based virtual market for electronic commerce. Applied Artificial Intelligence.
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CITED BY
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Srinivasan Jagannathan , Jayanth Nayak , Kevin Almeroth , Markus Hofmann, A model for discovering customer value for E-content, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, July 23-26, 2002, Edmonton, Alberta, Canada
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