TY - GEN
T1 - Externalities and peer effects of collective adoption in networks
AU - Vesaghi, Arash
AU - Mansouri, Mo
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/12
Y1 - 2016/8/12
N2 - Analyzing complex system with independent sub system is a difficult problem. Socio-Technical phenomena are among these type of problems. In the past two decades, agent based modeling and simulation played a significant role in our understanding of complex emergent socio-Technical phenomena. Several problems such as adoption of new technology, diffusion of contagious disease and social networks have been explored by using ABMs. One of the major question is with regards to collective outcomes. We believe that collective actions and phenomenon such as mob mentality are harmonized results of peer pressure effect and network externalities effect. In many studies the emphasize is on gauging the equilibrium state. The relaxation time as factor ruling the time gap between each transition is missing in almost all analysis. We try to explore the possibility of combo effect and measure the time to reach consensus in the system. We show that the consensus time depends on network structure and strength of each effect.
AB - Analyzing complex system with independent sub system is a difficult problem. Socio-Technical phenomena are among these type of problems. In the past two decades, agent based modeling and simulation played a significant role in our understanding of complex emergent socio-Technical phenomena. Several problems such as adoption of new technology, diffusion of contagious disease and social networks have been explored by using ABMs. One of the major question is with regards to collective outcomes. We believe that collective actions and phenomenon such as mob mentality are harmonized results of peer pressure effect and network externalities effect. In many studies the emphasize is on gauging the equilibrium state. The relaxation time as factor ruling the time gap between each transition is missing in almost all analysis. We try to explore the possibility of combo effect and measure the time to reach consensus in the system. We show that the consensus time depends on network structure and strength of each effect.
KW - Peer effect
KW - agent based modeling
KW - decision making
KW - network
KW - network externality
UR - http://www.scopus.com/inward/record.url?scp=84986005310&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84986005310&partnerID=8YFLogxK
U2 - 10.1109/SYSOSE.2016.7542920
DO - 10.1109/SYSOSE.2016.7542920
M3 - Conference contribution
AN - SCOPUS:84986005310
T3 - 2016 11th Systems of Systems Engineering Conference, SoSE 2016
BT - 2016 11th Systems of Systems Engineering Conference, SoSE 2016
T2 - 11th Systems of Systems Engineering Conference, SoSE 2016
Y2 - 12 June 2016 through 16 June 2016
ER -