Bidding for surplus in network allocation problems

Slikker, Marco

doi:10.1016/j.jet.2007.01.010

Cited by 32 publications

(41 citation statements)

References 17 publications

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“…They defined the egalitarian allocation rule and the component-wise egalitarian allocation rule. Slikker (2007) characterized axiomatically the Myerson value, the position value and the component-wise egalitarian solution and also proposed three non-cooperative bargaining procedures that result in the same payoffs as the three rules. For other works concerning non-cooperative foundations of allocation rules, we should mention, e.g., Pérez-Castrillo and Wettstein (2001) who presented an implementation of the Shapley value, and Pérez-Castrillo and Wettstein (2005) who described a mechanism that ends in the Myerson value of the monotonic cover of the value function.…”

Section: Related Literaturementioning

confidence: 99%

An allocation rule for dynamic random network formation processes

2015

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Most allocation rules for network games presented in the literature assume that the network structure is fixed. We put explicit emphasis on the construction of networks and examine the dynamic formation of networks whose evolution across time periods is stochastic. Time series of networks are studied that describe processes of network formation where links may appear or disappear at any period. Moreover, convergence to an efficient network is not necessarily prescribed. Transitions from one network to another are random and ruled by a stochastic process, typically a Markov chain. We propose the link-based scenario allocation rule for such dynamic random network formation processes and provide its axiomatic characterization. By considering a monotone game and a particular (natural) network formation process, we recover the link-based flexible network allocation rule of Jackson (Games Econ Behav 51:128-154, 2005a).

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Section: Related Literaturementioning

confidence: 99%

An allocation rule for dynamic random network formation processes

2015

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“…In a subsequent paper Jackson (2005) extended a solution concept for Communication situations to Network games: the Myerson value and called it "the equal bargaining rule". Borm, Owen, and Tijs (1992), Slikker and van den Nouweland (2001), Slikker (2005Slikker ( , 2007, Haeringer (2006), Kamijo (2009), Kamijo and Kongo (2009), Ghintran (2013), van den Nouweland and Slikker (2012) etc., extended and characterized another solution concept for Communication situations and Network games: the Position value. Recently the kappa value is defined by Belau (2013) as a more generalized version of the position value for Communication situations that accounts for various potential alternatives to the actual network in place.…”

Section: Introductionmentioning

confidence: 99%

A solution concept for network games: The role of multilateral interactions

Borkotokey

Kumar

Sarangi

2015

European Journal of Operational Research

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“…This research is related to the work of Slikker (2007) who provide comparable axiomatizations of the Myerson value and of the egalitarian solutions for cooperative games on networks. Our characterization of the component-wise egalitarian solution can be considered as closer to the characterization of the Myerson value since the equal gain/loss property, which is the corner stone of the axiom of fairness, is reused in the axiom of fairness for neighbors, even if it is applied to different pairs of players.…”

Section: Introductionmentioning

confidence: 99%

Fairness and fairness for neighbors: The difference between the Myerson value and component-wise egalitarian solutions

2012

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We replace the axiom of fairness used in the characterization of the Myerson value (Myerson, 1977) by fairness for neighbors in order to characterize the component-wise egalitarian solution. When a link is broken, fairness states the two players incident to the link should be affected similarly while fairness for neighbors states that a player incident to the link and any of his other neighbors should be affected similarly. Fairness for neighbors is also used to characterize the component-wise egalitarian surplus solution and a two-step egalitarian solution. These results highlight that egalitarian and marginalistic allocation rules can be obtained by applying the same equal gain/loss property to different types of players.

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Bidding for surplus in network allocation problems

Cited by 32 publications

References 17 publications

An allocation rule for dynamic random network formation processes

An allocation rule for dynamic random network formation processes

A solution concept for network games: The role of multilateral interactions

Fairness and fairness for neighbors: The difference between the Myerson value and component-wise egalitarian solutions

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