Strict Nash networks and partner heterogeneity

Billand, Pascal; Bravard, Christophe; Sarangi, Sudipta

doi:10.1007/s00182-010-0252-8

Cited by 20 publications

(75 citation statements)

References 5 publications

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“…I remark that exclusive partner heterogeneity and exclusive player heterogeneity satisfy this restriction. Consequently my propositions generalize the Proposition 3.1 of Galleotti et al (2006) and Proposition 1 of Billand et al (2011).…”

Section: Introductionsupporting

confidence: 57%

“…SNN has a unique component that is a branching or B i 0 , where i 0 is the lowest cost agent. This property is found in the exclusive partner heterogeneity model of Billand et al (2011).…”

Section: Introductionmentioning

confidence: 62%

“…Following these findings, this paper seeks to establish Proposition 2 in order to further eliminate a major difference between Proposition 1 mentioned above and Proposition 1 in Billand et al (2011). This difference is the fact that Uniform Partner Ranking predicts that non-empty components of SNN are multiple while exclusive partner heterogeneity predicts that the non-empty component of SNN is unique.…”

Section: Introductionmentioning

confidence: 94%

“…For exclusive player heterogeneity, existence of Nash network and full equilibrium characterization of Strict Nash networks (SNNs henceforth) are extensively studied by Galleotti et al (2006), Kamphorst and Laan (2007) and Billand et al (2010). For exclusive partner heterogeneity, full equilibrium characterization and the existence of SNNs are extensively studied by Billand et al (2011) and Billand et al (2012). However, when two heterogeneities are allowed to interact (called two-way heterogeneity henceforth) to my knowledge little is known.…”

Section: Introductionmentioning

confidence: 99%

“…This is achieved through examining how the interactions between these two assumptions influence important properties of Strict Nash networks. Built upon the findings of Billand et al (2011) and Galleotti et al (2006), which assume exclusive partner heterogeneity and exclusive player heterogeneity respectively, I provide a proposition that generalizes the results of these two models by stating that: (i) Strict Nash network consists of multiple non-empty components as in Galleotti et al (2006), and (ii) each non-empty component is a branching or B i network as in Billand et al (2011). This proposition requires that a certain restriction on link formation cost (called Uniform Partner Rankng), which encloses exclusive partner heterogeneity and exclusive player heterogeneity as a specific case, is satisfied.…”

mentioning

confidence: 99%

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On the Interaction between Player Heterogeneity and Partner Heterogeneity in Two-Way Flow Strict Nash Networks

Charoensook

2015

SSRN Journal

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This paper brings together analyses of Two-way Flow Strict Nash networks under exclusive player heterogeneity assumption and exclusive partner heterogeneity assumption. This is achieved through examining how the interactions between these two assumptions influence important properties of Strict Nash networks. Built upon the findings of Billand et al (2011) and Galleotti et al (2006), which assume exclusive partner heterogeneity and exclusive player heterogeneity respectively, I provide a proposition that generalizes the results of these two models by stating that: (i) Strict Nash network consists of multiple non-empty components as in Galleotti et al (2006), and (ii) each non-empty component is a branching or B i network as in Billand et al (2011). This proposition requires that a certain restriction on link formation cost (called Uniform Partner Rankng), which encloses exclusive partner heterogeneity and exclusive player heterogeneity as a specific case, is satisfied. In addition, this paper shows that value heterogeneity plays a relatively less important role in changing the shapes of Strict Nash networks. JEL Classification : C72, D85

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Section: Introductionsupporting

confidence: 57%

“…SNN has a unique component that is a branching or B i 0 , where i 0 is the lowest cost agent. This property is found in the exclusive partner heterogeneity model of Billand et al (2011).…”

Section: Introductionmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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On the Interaction between Player Heterogeneity and Partner Heterogeneity in Two-Way Flow Strict Nash Networks

Charoensook

2015

SSRN Journal

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Modeling resource flow asymmetries using condensation networks

Billand¹,

Bravard²,

Sarangi³

2012

Soc Choice Welf

Self Cite

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This paper analyzes the asymmetries with regard to the resources obtained by groups of players in equilibrium networks. We use the notion of condensation networks which allows us to partition the population into sets of players who obtain the same resources and we order these sets according to the resources obtained. We establish that the nature of heterogeneity plays a crucial role on asymmetries observed in equilibrium networks. Our approach is illustrated by introducing the partner heterogeneity assumption into the one-way flow model of Bala and Goyal [1].

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Stability, efficiency, and contentedness of social storage networks

2019

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Social storage systems are a good alternative to existing data backup systems of local, centralized, and P2P backup. Till date, researchers have mostly focussed on either building such systems by using existing underlying social networks (exogenously built) or on studying Quality of Service (QoS) related issues. In this paper, we look at two untouched aspects of social storage systems. One aspect involves modelling social storage as an endogenous social network, where agents themselves decide with whom they want to build data backup relation, which is more intuitive than exogenous social networks. The second aspect involves studying the stability of social storage systems, which would help reduce maintenance costs and further, help build efficient as well as contented networks.We have a four fold contribution that covers the above two aspects. We, first, model the social storage system as a strategic network formation game. We define the utility of each agent in the network under two different frameworks, one where the cost to add and maintain links is considered in the utility function and the other where budget constraints are considered. In the context of social storage and social cloud computing, these utility functions are the first of its kind, and we use them to define and analyse the social storage network game. Second, we propose the concept of bilateral stability which refines the pairwise stability concept defined by Jackson and Wolinsky (1996), by requiring mutual consent for both addition and deletion of links, as compared to mutual consent just for link addition. Mutual consent for link deletion is especially important in the social storage setting. The notion of bilateral stability subsumes the bilateral equilibrium definition of Goyal and Vega-Redondo (2007). Third, we prove necessary and the sufficient conditions for bilateral stability

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Strict Nash networks and partner heterogeneity

Abstract: Nash networks, Two-way flow models, Point contrabasis, C72, D85,

Cited by 20 publications

References 5 publications

On the Interaction between Player Heterogeneity and Partner Heterogeneity in Two-Way Flow Strict Nash Networks

On the Interaction between Player Heterogeneity and Partner Heterogeneity in Two-Way Flow Strict Nash Networks

Modeling resource flow asymmetries using condensation networks

Stability, efficiency, and contentedness of social storage networks

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