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Part of book or chapter of book
Data sources: UnpayWall
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I.R. "OLYMPIAS"
Article . 2005
Data sources: I.R. "OLYMPIAS"
https://doi.org/10.1007/115279...
Part of book or chapter of book . 2005 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2019
Data sources: DBLP
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The Efficiency of Optimal Taxes

Authors: George Karakostas; Stavros G. Kolliopoulos;

The Efficiency of Optimal Taxes

Abstract

It is well known that the selfish behavior of users in a network can be regulated through the imposition of the so-called optimal taxes on the network edges. Any traffic equilibrium reached by the selfish users who are conscious of both the travel latencies and the taxes will minimize the social cost, i.e., will minimize the total latency. Optimal taxes incur desirable behavior from the society point of view but they cause disutility to the network users since the users' total cost is in general increased [4]. Excessive disutility due to taxation may be undesirable from the societal perspective as well. In this work we examine the efficiency of taxation as a mechanism for achieving the desired goal of minimizing the social cost. We show that for large classes of latency functions the total disutility due to taxation that is caused to the users and/or the system is bounded with respect to the social optimum. In addition, we show that if the social cost takes into account both the total latency and the total taxation in the network, the coordination ratio for certain latency functions is better than the coordination ratio when taxation is not used.

Country
Greece
Keywords

transportation network

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Average
Green