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Björn Rupp

dblp:85/4710 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Network optimization and economics · 100%
Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network optimization and economics › pricing
internet pricing
0.011999
Internet demand under different pricing schemes · EC 1999
Network optimization and economics
resource allocation
0.011999
Internet demand under different pricing schemes · EC 1999
Algorithmic game theory and mechanism design
mechanism design
0.011999
Internet demand under different pricing schemes · EC 1999
Algorithmic game theory and mechanism design
pricing
0.011999
Internet demand under different pricing schemes · EC 1999

Methods — techniques the papers use, named apart from their topics

empirical analysis · 0.0demand modeling · 0.0
YearPublicationVenuePosition
1999 Internet demand under different pricing schemes
abstract
The proliferation of electronic commerce has emphasized \nthe need for multiple qualities of service (QoS) that meet \nuser requirements for, e.g., best-eort services, transactional \nguarantees, prioritized services, and bandwidth reservations. \nWhen Internet users will be able to choose from a large selection \nof network services, an important question is whether \nthis \nexibility will be appreciated by the user and how much \nvalue is placed on network resources. This paper focuses on \nuser acceptance of dierent usage-based pricing models for \nnetwork services as well as on which users benet from dynamic \npricing. The analytic results presented here are based \non pricing experiments conducted within the INternet Demand \nEXperiment (INDEX). The pricing experiments comprise \nper-minute and byte-volume pricing. After describing \nthe experimental design and characterizing our subject pool \nusing demographic data, we analyze user demand for Internet \naccess by comparing the three experiments in terms of \ntraÆc generation, QoS selection, and expenditure. Finally, \nwe show which user groups will benet from such services.
Jörn Altmann, Björn Rupp, Pravin Varaiya
EC2