Reference : Blockchain Governance: An Overview and Prediction of Optimal Strategies Using Nash Eq...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences; Finance
http://hdl.handle.net/10993/42468
Blockchain Governance: An Overview and Prediction of Optimal Strategies Using Nash Equilibrium
English
Khan, Nida mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ahmad, Tabrez mailto [ArcelorMittal, Europe]
Patel, Anass mailto [570easi, France]
State, Radu mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
In press
3rd AUE International Research Conference
Springer
Yes
International
AUEIRC 2020
25-03-2020 to 26-03-2020
[en] Blockchain governance ; IT governance ; Nash Equilibrium ; Game Theory ; Mathematical optimization
[en] Blockchain governance is a subject of ongoing research and an interdisciplinary view of blockchain governance is vital to aid in further research for establishing a formal governance framework for this nascent technology. In this paper, the position of blockchain governance within the hierarchy of Institutional governance is discussed. Blockchain governance is analyzed from the perspective of IT governance using Nash equilibrium to predict the outcome of different governance decisions. A payoff matrix for blockchain governance is created and simulation of different strategy profiles is accomplished for computation of all Nash equilibria. We also create payoff matrices for different kinds of blockchain governance, which were used to propose novel mathematical formulae usable to predict the best governance strategy that minimizes the occurrence of a hard fork as well as predicts the behavior of the majority during protocol updates.
http://hdl.handle.net/10993/42468
FnR ; FNR11617092 > Nida Khan > > Data Analytics and Smart Contracts for traceability in finance > 01/03/2017 > 31/01/2021 > 2017

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