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150324s2006 xx |||||o 00| ||eng c |
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|a (DE-627)JST050600680
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|a (JST)4102301
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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1 |
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|a Ou, J.
|e verfasserin
|4 aut
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|a A Differentiated Service Scheme to Optimize Website Revenues
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|c 2006
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|a Text
|b txt
|2 rdacontent
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|a Computermedien
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|2 rdamedia
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|a Online-Ressource
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|a We consider a website host server with web quality of service (QoS) capabilities to offer differentiated services. A quantitative modelling framework is set up to analyse the economic benefits of differentiated services and to build optimization models for managing the website host's connection bandwidth to the Internet (which is assumed to be the bottleneck factor determining the QoS). Three models are formulated corresponding to three operational scenarios to provide differentiated services. The first is for the marketing manager to classify visit requests as premium or basic when the information technology (IT) manager has already reserved bandwidths for the two classes, and the second is for the IT manager to allocate the total available bandwidth to each class when the marketing manager has already designated which visit requests are premium and which are basic. The third is for the joint optimization of request classification and bandwidth allocation when centralized coordination is possible. Analytic results are obtained for a special case that corresponds to very impatient customers requesting large amounts of data. Qualitative insights gained and numerical results obtained strongly support the implementation of differentiated services. More interestingly, the decentralized models that use simple and rough-cut rules yield solutions almost as good as the joint optimization model.
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|a Copyright 2006 Operational Research Society Ltd
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4 |
|a OR modelling
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| 650 |
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4 |
|a Queueing theory
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| 650 |
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4 |
|a Non-convex optimization
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| 650 |
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|a Bandwidth allocation
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| 650 |
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|a Quality of service
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| 650 |
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|a Economics
|x Microeconomics
|x Income
|x Revenue
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| 650 |
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4 |
|a Applied sciences
|x Technology
|x Communications technology
|x Communication systems
|x Digital communication systems
|x Internet
|x World Wide Web
|x Websites
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| 650 |
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4 |
|a Applied sciences
|x Engineering
|x Telecommunications
|x Data transmission
|x Data bandwidth
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| 650 |
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Decision theory
|x Operations research
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| 650 |
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4 |
|a Mathematics
|x Mathematical values
|x Mathematical variables
|x Mathematical independent variables
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| 650 |
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4 |
|a Business
|x Business administration
|x Business management
|x Performance management
|x Performance metrics
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| 650 |
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4 |
|a Applied sciences
|x Computer science
|x Computer programming
|x Mathematical programming
|x Nonlinear programming
|x Objective functions
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| 650 |
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4 |
|a Applied sciences
|x Engineering
|x Telecommunications
|x Data transmission
|x File transfers
|x Downloading
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| 650 |
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4 |
|a Applied sciences
|x Technology
|x Communications technology
|x Communication systems
|x Digital communication systems
|x Internet
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| 650 |
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4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical models
|x Parametric models
|x Theoretical Papers
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| 655 |
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4 |
|a research-article
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| 700 |
1 |
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|a Sharafali, M.
|e verfasserin
|4 aut
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| 773 |
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8 |
|i Enthalten in
|t The Journal of the Operational Research Society
|d Taylor & Francis, Ltd.
|g 57(2006), 11, Seite 1323-1340
|w (DE-627)320465098
|w (DE-600)2007775-0
|x 14769360
|7 nnns
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| 773 |
1 |
8 |
|g volume:57
|g year:2006
|g number:11
|g pages:1323-1340
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0 |
|u https://www.jstor.org/stable/4102301
|3 Volltext
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|a AR
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|d 57
|j 2006
|e 11
|h 1323-1340
|